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1. Health and Demographic Surveillance Systems Within the Child Health and Mortality Prevention Surveillance Network

Author: Nida I. Shaikh, Nega Assefa, Karen L. Kotloff, Shams El Arifeen, Sunday A. Adedini, Amanda L. Wilkinson, Thomas Misore, Mary Claire Worrell, Pratima L Raghunathan, Abu Mohd Naser, Ariel Nhacolo, Samba O. Sow, Uma U Onuwchekwa, Ashka Mehta, Milagritos D. Tapia, Shabir A. Madhi, Robert F. Breiman, Charfudin Sacoor, Melkamu Merid Mengesha, Atique Iqbal Chowdhury, Reinhard Kaiser, Solveig A. Cunningham, and David Obor
Subjects: Microbiology (medical), Laboratory methods, Surveillance data, business.industry, 030231 tropical medicine, Population health, Champs study, Demographic data, Child health, Sierra leone, Child mortality, 03 medical and health sciences, 0302 clinical medicine, Infectious Diseases, Environmental health, Medicine, 030212 general & internal medicine, business, human activities
Abstract: Health and demographic surveillance systems (HDSSs) provide a foundation for characterizing and defining priorities and strategies for improving population health. The Child Health and Mortality Prevention Surveillance (CHAMPS) project aims to inform policy to prevent child deaths through generating causes of death from surveillance data combined with innovative diagnostic and laboratory methods. Six of the 7 sites that constitute the CHAMPS network have active HDSSs: Mozambique, Mali, Ethiopia, Kenya, Bangladesh, and South Africa; the seventh, in Sierra Leone, is in the early planning stages. This article describes the network of CHAMPS HDSSs and their role in the CHAMPS project. To generate actionable health and demographic data to prevent child deaths, the network depends on reliable demographic surveillance, and the HDSSs play this crucial role.
Published: 2019
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2. Examination of Sleep and Obesity in Children and Adolescents in the United States

Author: Solveig A. Cunningham, Livvy Shafer, and Puneet Kaur Chehal
Subjects: Pediatric Obesity, Health (social science), Adolescent, business.industry, Public Health, Environmental and Occupational Health, Overweight, medicine.disease, Bedtime, Obesity, Sleep in non-human animals, United States, Body Mass Index, 03 medical and health sciences, 0302 clinical medicine, Consistency (negotiation), 030225 pediatrics, Medicine, Humans, 030212 general & internal medicine, business, Association (psychology), Child, Sleep, Sleep duration, Clinical psychology
Abstract: Purpose: This study contributes to the growing literature on the association between sleep and obesity by examining the associations between hours of sleep, consistency of bedtime, and obesity among children in the US. Design: Analysis of a nationally representative sample of non-institutionalized children from the 2016-17 National Survey of Children’s Health. Setting: US, national. Subjects: Children ages 10-17 years (n = 34,640) Measures: Parent reported weeknight average hours of sleep and consistency of bedtime. Body mass index classified as underweight, normal, overweight or obesity using parent-reported child height and weight information, classified using CDC BMI-for-Age Growth Charts. Analysis: Multivariate logistic regression models were used to estimate associations between measures of sleep and body mass index weight category adjusting for individual, household and neighborhood characteristics. Results: An additional hour of sleep was associated with 10.8% lower odds of obesity, net of consistency in bedtime. After controlling for sleep duration, children who usually went to bed at the same time on weeknights had lower odds of obesity (24.8%) relative to children who always went to bed at the same time. Conclusion: Sleep duration is predictive of lower odds of obesity in US children and adolescents. Some variability in weeknight bedtime is associated with lower odds of obesity, though there were no additional benefits to extensive variability in bedtime.
Published: 2021

3. Development of a temporally harmonized asset index: evidence from across 50 years of follow up of a birth cohort in Guatemala

Author: Jithin Sam Varghese, John A. Maluccio, Aryeh D. Stein, Manuel Ramirez-Zea, and Solveig A. Cunningham
Subjects: Rural Population, Medicine (General), Longitudinal study, Percentile, Index (economics), Epidemiology, 050204 development studies, Life course epidemiology, Health Informatics, 03 medical and health sciences, R5-920, 0302 clinical medicine, Multiple correspondence analysis, Social mobility, 0502 economics and business, Humans, Longitudinal Studies, 030212 general & internal medicine, Asset (economics), Proxy (statistics), 05 social sciences, Guatemala, Cross-Sectional Studies, Geography, Socioeconomic Factors, Cohort, Birth cohort, Research Article, Follow-Up Studies, Demography
Abstract: Background Asset-based indices are widely-used proxy measures of wealth in low and middle-income countries (LMIC). The stability of these indices within households over time is not known. Methods We develop a harmonized household asset index using Principal Component Analysis for the participants (n = 2392) of INCAP Longitudinal Study, Guatemala using data from six waves of follow-up over the period of 1965–2018. We estimate its cross-sectional association with parental schooling (in 1967–75) and attained schooling (in 2015–18) of cohort members. We study how patterns of cross-sectional loadings change over time and between urban-rural settings. We assess its robustness to omission of assets or study waves and alternate specifications of factor extraction procedure (exploratory factor analysis, multiple correspondence analysis). Results The harmonized index constructed using 8 assets and 11 housing characteristics explained 32.4% of the variance. Most households increased in absolute wealth over time with median wealth (25th percentile, 75th percentile; households) increasing from − 3.74 (− 4.42, − 3.07; 547) in 1967 to 2.08 (1.41, 2.67; 1145) in 2017–18. Ownership of television, electricity, quality of flooring and sanitary installation explained the largest proportion of variance. The index is positively associated with measures of schooling (maternal: r = 0.16; paternal: r = 0.10; attained: r = 0.35, all p Conclusion A temporally harmonized asset index constructed from consistently administered surveys in a cohort setting over time may allow study of associations of life-course social mobility with human capital outcomes in LMIC contexts. The approach permits exploration of trends in household wealth of the sample over a follow-up period against repeated cross-sectional surveys which permit the estimation of only the mean trajectory.
Published: 2021
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4. Spouse’s Diabetes Status and Incidence of Depression and Anxiety: An 18-Year Prospective Study

Author: Solveig A. Cunningham, Mohammed K. Ali, Shivani A. Patel, and Jannie Nielsen
Subjects: Research design, Activities of daily living, Endocrinology, Diabetes and Metabolism, 030209 endocrinology & metabolism, Anxiety, 03 medical and health sciences, 0302 clinical medicine, Diabetes mellitus, Internal Medicine, Diabetes Mellitus, Medicine, Humans, 030212 general & internal medicine, Prospective Studies, Prospective cohort study, Spouses, Depression (differential diagnoses), Advanced and Specialized Nursing, business.industry, Depression, Incidence (epidemiology), Incidence, Clinical Care/Education/Nutrition/Psychosocial Research, medicine.disease, Spouse, medicine.symptom, business, Demography
Abstract: OBJECTIVE We investigated the risk of depression and anxiety in people whose spouse did or did not have diabetes. We also examined associations between depression and anxiety and severity of spouse’s diabetes. RESEARCH DESIGN AND METHODS We analyzed prospective self-reported data about diagnosed depression/anxiety and diabetes in cohabiting couples in the national Panel Study of Income Dynamics (PSID) during 1999–2017 (n = 13,500, 128,833 person-years of follow-up, median follow-up 8.1 years). We used Poisson models to estimate incidence and incidence rate ratios (IRRs) of depression/anxiety, according to spouse’s diabetes status overall and by severity of diabetes. RESULTS Age-, sex-, and race-adjusted incidence of depression/anxiety was 8.0/1,000 person-years (95% CI 6.5, 9.6) among those whose spouse had diabetes and 6.5/1,000 person-years (95% CI 6.0, 6.9) among those whose spouse did not have diabetes. Those whose spouse had diabetes had higher risk of depression/anxiety (IRR 1.24 [95% CI 1.01, 1.53]). Those whose spouse had diabetes-related limitations in daily activities (IRR 1.89 [95% CI 1.35, 2.67]) and diabetes combined with other chronic conditions (IRR 2.34 [95% CI 1.78, 3.09]) were more likely to develop depression/anxiety, while those whose spouse had diabetes with no limitations or additional chronic conditions had incidence of depression/anxiety similar to that of subjects whose spouses did not have diabetes. CONCLUSIONS People living with a spouse with diabetes are at higher risk of developing depression/anxiety than people whose spouse does not have diabetes; this risk is driven by the severity of the spouse’s diabetes. Strategies to address the impacts of diabetes on families need to be devised and tested.
Published: 2021

5. Unhealthy weight among children in Spain and the role of the home environment

Author: Elizabeth Vaquera, Rebecca Jones, Marga Marí-Klose, Solveig A. Cunningham, Pau Marí-Klose, and Universitat de Barcelona
Subjects: Male, Pediatric Obesity, Immigration, lcsh:Medicine, Overweight, Logistic regression, Body Mass Index, 0302 clinical medicine, Prevalence, Global health, 030212 general & internal medicine, Underweight, Educació familiar, Child, lcsh:QH301-705.5, media_common, Hàbits alimentaris, General Medicine, Research Note, Child, Preschool, Female, medicine.symptom, media_common.quotation_subject, Food habits, 030209 endocrinology & metabolism, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Thinness, Environmental health, medicine, Humans, Family, Obesity, lcsh:Science (General), Nutrició, Nutrition, Obesitat en els infants, Home environment, business.industry, Body Weight, lcsh:R, medicine.disease, Cross-Sectional Studies, Obesity in children, Normal weight, lcsh:Biology (General), Spain, Domestic education, business, lcsh:Q1-390
Abstract: Objective Unhealthy weight is a major global health concern. This study examines unhealthy weight among children in Spain and the role of the home environment therein. Data are from a 2010 national survey of families with children. We examined unhealthy weight among children ages 5–10 years using the WHO Child Growth Standards and used multivariate logistic regression to assess associations with family characteristics. Results There was a high prevalence of unhealthy weight, with only 46% of children at normal weight. Both underweight and obesity were higher among boys (14%; 22%) than girls (13%; 12%). Underweight and obesity were higher among children of mothers with obesity and those with unemployed parents. Obesity was higher among children of mothers who were less educated (35%) and among children of immigrants (19%). We find high levels of unhealthy weight in children, with both underweight and obesity being predicted by the same family environment characteristics. Electronic supplementary material The online version of this article (10.1186/s13104-018-3665-2) contains supplementary material, which is available to authorized users.
Published: 2018
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6. Adolescent Sugar-Sweetened Beverage Intake is Associated With Parent Intake, Not Knowledge of Health Risks

Author: Stephen Onufrak, Elizabeth A. Lundeen, Sohyun Park, Solveig A. Cunningham, and Heidi M. Blanck
Subjects: Adult, Male, Parents, 0301 basic medicine, Health Knowledge, Attitudes, Practice, Health (social science), Adolescent, Dental Caries, Weight Gain, Article, Beverages, 03 medical and health sciences, Sex Factors, stomatognathic system, Dietary Sucrose, Environmental health, Diabetes Mellitus, Humans, Medicine, Child, Sugar, 030109 nutrition & dietetics, business.industry, Body Weight, Age Factors, Public Health, Environmental and Occupational Health, Middle Aged, stomatognathic diseases, Cross-Sectional Studies, Socioeconomic Factors, Female, Self Report, Energy Intake, business
Abstract: Purpose: To examine associations of adolescent sugar-sweetened beverage (SSB) intake with parent SSB intake and parent and adolescent knowledge of SSB-related health risks. Design: Quantitative, cross-sectional. Setting: 2014 SummerStyles survey. Subjects: Nine hundred and ninety parent and adolescent (12-17 years) pairs. Measures: The outcome was self-reported adolescent intake (0, >0 to 0 to Analysis: Separate multinomial logistic regression models were used to estimate adjusted odds ratios (aORs) for adolescent SSB intake ≥1 time/day (ref: 0 times/day), according to (1) parent SSB intake and (2) parent and (3) adolescent knowledge. Results: About 31% of adolescents consumed SSBs ≥1 time/day, and 43.2% of parents consumed SSBs ≥2 times/day. Adolescent and parent knowledge that SSB intake is related to health conditions ranged from 60.7% to 80.4%: weight gain (75.0% and 80.4%, respectively), diabetes (60.7% and 71.4%, respectively), and dental caries (77.5% and 72.9%, respectively). In adjusted models, adolescent SSB intake ≥1 time/day was associated with parent intake ≥2 times/day (aOR = 3.30; 95% confidence interval = 1.62-6.74) but not with parent or adolescent knowledge of health risks. Conclusion: Parental SSB intake may be an important factor in understanding adolescent behavior; knowledge of SSB-related health conditions alone may not influence adolescent SSB behavior.
Published: 2018
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7. Incidence of diabetes after a partner's diagnosis

Author: Julie A. Schmittdiel, Mohammed K. Ali, Solveig A. Cunningham, and Sara R. Adams
Subjects: Male, Gerontology, Epidemiology, Population, 030209 endocrinology & metabolism, Logistic regression, Article, California, Odds, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Diabetes mellitus, Diabetes Mellitus, Humans, Medicine, 030212 general & internal medicine, Spouses, education, education.field_of_study, business.industry, Incidence, Incidence (epidemiology), Public Health, Environmental and Occupational Health, Middle Aged, medicine.disease, Propensity score matching, Female, business, Cohort study
Abstract: People socially connected with each other often share health risks, possibly due to shared environments and behaviors. In a retrospective cohort study, we examined whether incidence of diabetes was different for individuals with recently diagnosed partners compared to individuals similar on other characteristics but whose partners were never diagnosed with diabetes. We analyzed 2007–11 data from Kaiser Permanente Northern California (KNPC), an integrated health system with >3.5 million members. We estimated annual diabetes incidence controlling for demographic, socio-economic, behavioral, and health characteristics. Using propensity score matching and multivariate logistic regression, we compared odds of incident diabetes among co-residing partners ages 18–89 years of people who had been diagnosed with diabetes during the previous year (in robustness checks up to the previous three years) and people who had never been diagnosed but were similar on observed characteristics. Partners of newly-diagnosed people had annual diabetes incidence of 16.4/1,000, equivalent to10.8 times higher (95%CI: 9.2–12.6) than people whose spouses had never been diagnosed (1.5/1,000). Odds remained higher three years after a spouses’ diagnosis (45.4 vs. 11.7/1,000). Adjusting for other characteristics, odds of diabetes for those with a partner diagnosed in the previous year were 8.7 times higher CI: 7.4–10.2) than among those whose partner had never been diagnosed. Partners of persons with recently-diagnosed diabetes developed diabetes at much higher rates than partners of persons with similar characteristics who were never diagnosed with diabetes. Individuals with a recently diagnosed partner could be considered a high-risk population for screening and prevention.
Published: 2017
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8. The Maternal Gut Microbiome During Pregnancy

Author: Anne L. Dunlop, Solveig A. Cunningham, Elizabeth J. Corwin, and Sara Edwards
Subjects: 0301 basic medicine, medicine.drug_class, Mothers, Physiology, Pharmacology (nursing), Bacterial composition, Article, 03 medical and health sciences, Immune system, Pregnancy, Maternity and Midwifery, medicine, Humans, 030109 nutrition & dietetics, business.industry, Gastrointestinal Microbiome, Maternal metabolism, medicine.disease, Gut microbiome, Gastrointestinal Tract, Metabolism, 030104 developmental biology, Estrogen, Female, business, Risk Reduction Behavior, Hormone
Abstract: The gut microbiome is a critical component of an individual’s metabolism and overall health. The prenatal period is marked by unique inflammatory and immune changes that alter maternal gut function and bacterial composition as the pregnancy advances. The composition of the maternal gut microbiome contributes to obstetric outcomes with long-term health sequelae for mother and child. Estrogen and progesterone also impact gut function, especially during the prenatal period. These physiologic changes in pregnancy allow for adjustments in maternal metabolism and weight necessary to support the pregnancy. This article will review the normal hormonal, metabolic and immunologic changes to the maternal gut microbiome throughout the prenatal period, in addition to relevant implications for nurses providing care for pregnant women.
Published: 2017
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9. Healthfulness, Modernity, and Availability of Food and Beverages: Adolescents’ Perceptions in Southern India

Author: Nida I. Shaikh, Shailaja S Patil, Solveig A. Cunningham, and Amanda Maxfield
Subjects: Male, 0301 basic medicine, Adolescent, media_common.quotation_subject, India, Medicine (miscellaneous), 030209 endocrinology & metabolism, Food Supply, Beverages, 03 medical and health sciences, 0302 clinical medicine, Residence Characteristics, Environmental health, Perception, Humans, media_common, 030109 nutrition & dietetics, Ecology, Modernity, Urbanization, Commerce, Advertising, General Medicine, Diet, Geography, Attitude, Socioeconomic Factors, Food, Female, Nutritive Value, Food Science
Abstract: This study uses freelists to document perceptions of healthfulness, modernity, and availability of foods and beverages among adolescents ages 13-18 years (n = 26) in urbanizing India. Among the 10 foods and beverages adolescents perceived as "new," half were also seen as modern and unhealthy, 4 as traditional and unhealthy, and 3 as modern and healthy. Of those 10 "new" foods, 4 were reported as available only in supermarkets, 4 only in kiraana (local) stores, and 6 in both. Adolescents ascribed healthfulness and modernity to food and beverage items and were aware of their availability across stores.
Published: 2017
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10. Grandmothers’ perspectives on the changing context of health in India

Author: Susannah D. Gloor, Solveig A. Cunningham, and Shailaja S Patil
Subjects: Rural Population, Gerontology, medicine.medical_specialty, India, lcsh:Medicine, 030209 endocrinology & metabolism, Context (language use), Grandmothers, Gender roles, General Biochemistry, Genetics and Molecular Biology, Chronic disease, 03 medical and health sciences, Globalization, 0302 clinical medicine, Environmental health, Epidemiology, Humans, Medicine, Family, 030212 general & internal medicine, lcsh:Science (General), lcsh:QH301-705.5, Aged, business.industry, Social change, digestive, oral, and skin physiology, lcsh:R, Grandparent, Feeding Behavior, General Medicine, Middle Aged, medicine.disease, Obesity, Diet, 3. Good health, Grandparents, lcsh:Biology (General), Data collection, Female, Food preparation, business, Research Article, lcsh:Q1-390
Abstract: Background The prevalence of obesity and other chronic diseases is increasing in India and around the world. As globalization and social changes are believed to be at the root of these epidemiological changes, these factors must be better understood. This study engaged older adults to gain an important perspective on globalization and health. Methods A free-list instrument and a structured survey were developed and used to gather data on changes in diet, activity, and women’s roles from ten grandmothers in rural India. Results Grandmothers indicated that household chores and food preparation are less labor-intensive and time-consuming due to mechanization and the availability of prepared foods than a generation earlier. Families are more often eating food out, bringing prepared food home, and using ready-made food mixes; adolescents are continuing to eat meals at home, but now snack with friends outside the home more frequently. Conclusions Using both a free-list instrument and a structured survey, grandmothers were able to provide insights about the changing context of dietary patterns and family roles arising with globalization that may be contributing to the rise in chronic disease. Electronic supplementary material The online version of this article (doi:10.1186/s13104-017-2583-z) contains supplementary material, which is available to authorized users.
Published: 2017
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11. The stability of children's weight status over time, and the role of television, physical activity, and diet

Author: Solveig A. Cunningham and Sandra L. Jackson
Subjects: Male, Longitudinal study, Epidemiology, 030209 endocrinology & metabolism, Overweight, Article, 03 medical and health sciences, Screen time, 0302 clinical medicine, Humans, Medicine, Longitudinal Studies, Obesity, 030212 general & internal medicine, Early childhood, Child, Prospective cohort study, Exercise, business.industry, Body Weight, Public Health, Environmental and Occupational Health, Anthropometry, medicine.disease, Health Surveys, United States, Diet, Child, Preschool, Cohort, Female, Television, medicine.symptom, business, Demography
Abstract: Weight-related behaviors such as sedentary activity, physical activity, and diet have been the focus of efforts to prevent and reduce the occurrence of obesity and overweight in children, but few longitudinal studies have examined the effects of weight-related behaviors on changes in weight status over time in children. This study examines the effects of weight-related behaviors on subsequent changes in weight during childhood. We used the Early Childhood Longitudinal Study Kindergarten Cohort (ECLS-K), a nationally representative prospective cohort of children in the United States. Data, including anthropometric measures, were collected six times across 1998–2007 (analytic sample = 4938). We employed an autoregressive cross-lagged model in a structural equation model framework to assess the effects of behavioral factors -intake of fruit, vegetables, fast food and sugar-sweetened beverages, television viewing, and physical activity - on weight stability over time. BMI z-scores were highly stable throughout childhood: the standardized parameter estimates of BMI z-scores on subsequent-period BMI z-scores ranged from 0.79 to 0.86. BMI z-scores were least stable between Kindergarten and 1st grade but became highly stable between 3rd and 5th grades. After accounting for prior weight, behavioral factors had little effect on subsequent weight. The most important behavioral factor was TV viewing in the 1st and 3rd grades: an additional hour of daily TV viewing was associated with 0.04 higher BMI z-score. It is important to prevent excessive weight gain early in childhood, as weight patterns are long-lasting; the most important behavioral factor may be limiting children's screen time.
Published: 2017
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12. Forecasting the prevalence of overweight and obesity in India to 2040

Author: Solveig A. Cunningham, Ian M. Timæus, Shivani A. Patel, Rebecca Jones, Lynda Clarke, Sanjay Kinra, Rein M G J Houben, Shammi Luhar, Luhar, Shammi [0000-0003-2165-3142], Jones, Rebecca [0000-0001-5237-5785], Cunningham, Solveig [0000-0002-2354-1526], and Apollo - University of Cambridge Repository
Subjects: Male, Physiology, Overweight, Body Mass Index, Geographical Locations, 0302 clinical medicine, Endocrinology, Epidemiology, Medicine and Health Sciences, Prevalence, 030212 general & internal medicine, Geographic Areas, 2. Zero hunger, education.field_of_study, Multidisciplinary, Geography, Incidence (epidemiology), Mortality rate, 1. No poverty, Middle Aged, 3. Good health, Physiological Parameters, Medicine, Female, medicine.symptom, Research Article, Urban Areas, Adult, medicine.medical_specialty, Asia, Death Rates, Endocrine Disorders, Science, Population, India, 030209 endocrinology & metabolism, History, 21st Century, 03 medical and health sciences, Young Adult, Population Metrics, medicine, Diabetes Mellitus, Humans, Obesity, education, Aged, Population Biology, business.industry, Body Weight, Biology and Life Sciences, medicine.disease, Rural Areas, Age Groups, Metabolic Disorders, People and Places, Earth Sciences, Population Groupings, Rural area, business, Body mass index, Demography, Forecasting
Abstract: Background In India, the prevalence of overweight and obesity has increased rapidly in recent decades. Given the association between overweight and obesity with many non-communicable diseases, forecasts of the future prevalence of overweight and obesity can help inform policy in a country where around one sixth of the world's population resides. Methods We used a system of multi-state life tables to forecast overweight and obesity prevalence among Indians aged 20-69 years by age, sex and urban/rural residence to 2040. We estimated the incidence and initial prevalence of overweight using nationally representative data from the National Family Health Surveys 3 and 4, and the Study on global AGEing and adult health, waves 0 and 1. We forecasted future mortality, using the Lee-Carter model fitted life tables reported by the Sample Registration System, and adjusted the mortality rates for Body Mass Index using relative risks from the literature. Results The prevalence of overweight will more than double among Indian adults aged 20-69 years between 2010 and 2040, while the prevalence of obesity will triple. Specifically, the prevalence of overweight and obesity will reach 30.5% (27.4%-34.4%) and 9.5% (5.4%-13.3%) among men, and 27.4% (24.5%-30.6%) and 13.9% (10.1%-16.9%) among women, respectively, by 2040. The largest increases in the prevalence of overweight and obesity between 2010 and 2040 is expected to be in older ages, and we found a larger relative increase in overweight and obesity in rural areas compared to urban areas. The largest relative increase in overweight and obesity prevalence was forecast to occur at older age groups. Conclusion The overall prevalence of overweight and obesity is expected to increase considerably in India by 2040, with substantial increases particularly among rural residents and older Indians. Detailed predictions of excess weight are crucial in estimating future non-communicable disease burdens and their economic impact.
Published: 2020

13. Extrapolating sparse gold standard cause of death designations to characterize broader catchment areas

Author: Allan W. Taylor, Charfudin Sacoor, Dickens Onyango, Quique Bassat, Inacio Mandomando, Solveig A. Cunningham, Robert H. Lyles, Emily Zielinski-Gutierrez, Suprateek Kundu, and Victor Akelo
Subjects: Selection bias, Epidemiology, Applied Mathematics, Maximum likelihood, media_common.quotation_subject, Gold standard (test), Missing data, 01 natural sciences, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Statistics, Credible interval, 030212 general & internal medicine, 0101 mathematics, Psychology, media_common, Cause of death
Abstract: Objectives The Child Health and Mortality Prevention Surveillance (CHAMPS) Network is designed to elucidate and track causes of under-5 child mortality and stillbirth in multiple sites in sub-Saharan Africa and South Asia using advanced surveillance, laboratory and pathology methods. Expert panels provide an arguable gold standard determination of underlying cause of death (CoD) on a subset of child deaths, in part through examining tissue obtained via minimally invasive tissue sampling (MITS) procedures. We consider estimating a population-level distribution of CoDs based on this sparse but precise data, in conjunction with data on subgrouping characteristics that are measured on the broader population of cases and are potentially associated with selection for MITS and with cause-specific mortality. Methods We illustrate how estimation of each underlying CoD proportion using all available data can be addressed equivalently in terms of a Horvitz-Thompson adjustment or a direct standardization, uncovering insights relevant to the designation of appropriate subgroups to adjust for non-representative sampling. Taking advantage of the functional form of the result when expressed as a multinomial distribution-based maximum likelihood estimator, we propose small-sample adjustments to Bayesian credible intervals based on Jeffreys or related weakly informative Dirichlet prior distributions. Results Our analyses of early data from CHAMPS sites in Kenya and Mozambique and accompanying simulation studies demonstrate the validity of the adjustment approach under attendant assumptions, together with marked performance improvements associated with the proposed adjusted Bayesian credible intervals. Conclusions Adjustment for non-representative sampling of those validated via gold standard diagnostic methods is a critical endeavor for epidemiologic studies like CHAMPS that seek extrapolation of CoD proportion estimates.
Published: 2020
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14. In, out, and fluctuating: obesity from adolescence to adulthood

Author: Carmen D. Ng and Solveig A. Cunningham
Subjects: Adult, Male, Rural Population, Longitudinal study, Adolescent, Urban Population, Epidemiology, Ethnic group, Black People, Overweight, 01 natural sciences, White People, Article, Body Mass Index, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Sex Factors, Asian People, medicine, Prevalence, Humans, 030212 general & internal medicine, Longitudinal Studies, Obesity, 0101 mathematics, business.industry, Incidence (epidemiology), Incidence, 010102 general mathematics, nutritional and metabolic diseases, Hispanic or Latino, medicine.disease, United States, Black or African American, Socioeconomic Factors, Residence, Female, Ordered logit, medicine.symptom, business, Body mass index, Demography
Abstract: Purpose While high levels of obesity prevalence and incidence have been well documented, there is less research on obesity dynamics over time. In this article, we sought to understand the body mass index (BMI) trajectories in and out of obesity from adolescence to adulthood. Methods We used the National Longitudinal Study of Adolescent to Adult Health to explore American obesity dynamics from mean ages 15–28 years. We analyzed six BMI trajectories from 1994 to 2008 and examined their contextual sociodemographic correlates using ordinal logistic regression models. Results More than 50% of adolescents with normal BMI moved to overweight/obesity by adulthood; only 8% of overweight and 2% of obese adolescents achieved normal BMI in adulthood. While some sociodemographic characteristics such as sex, race/ethnicity, place of residence, and parents’ education were associated with being in certain BMI trajectories among adolescents with normal BMI, they were not so associated among adolescents starting at obesity. Conclusions Transitioning to higher BMI categories was common, whereas the opposite direction was rare. Pathways to obesity prevention might be easier to identify than those to reversal, as contextual factors had more explanatory power for youths with normal BMI than for those with obese BMI.
Published: 2019

15. Impact of Weight Status on the Cardiopulmonary Fitness Outcome of a School-Based Physical Activity Program

Author: Julie A. Gazmararian, Solveig A. Cunningham, and Rena C Moon
Subjects: Multi-stage fitness test, Gerontology, Male, Pediatric Obesity, Physical fitness, education, Overweight, Childhood obesity, Article, Education, Body Mass Index, 03 medical and health sciences, 0302 clinical medicine, 030225 pediatrics, medicine, Humans, 030212 general & internal medicine, Child, Cardiovascular fitness, Exercise, Academic year, Physical Education and Training, Schools, business.industry, Public Health, Environmental and Occupational Health, medicine.disease, Philosophy, Cardiorespiratory Fitness, Female, Parental consent, medicine.symptom, business, Body mass index
Abstract: Background The effectiveness of school-based physical activity interventions for improving cardiopulmonary fitness (CPF) of overweight and obese children is not well established. In this study, we evaluated whether overweight and obese children had similar changes in body mass index (BMI) and CPF as normal weight children after participating in a program for one academic year. Methods Using purposive sampling at the school level, we selected 16 program and 7 control schools in a large metropolitan area in the Southeast during the 2015-2016 academic year. In these schools, 3396 fourth-graders participated with parental consent. Of these, 2332 (68.7%) participated in BMI measures and 1780 (52.4%) in Progressive Aerobic Cardiovascular Endurance Run (PACER) measures for CPF at two time points. Results Students of all weight statuses pre-program did not show changes in BMI after program implementation. All students showed statistically significant improvements in the PACER test at follow-up, regardless of their participation in the program. However, overweight and obese children showed less improvement in CPF level than their normal weight classmates, regardless of their participation in the program. Conclusion Special attention for improving engagements of overweight and obese children may be needed to achieve improvements in their CPF level similar to that of normal weight students.
Published: 2019

16. Longitudinal patterns of physical activity, sedentary behavior and sleep in urban South African adolescents, Birth-To-Twenty Plus cohort

Author: Richard J. Munthali, Sara K. Hanson, Solveig A. Cunningham, Aryeh D. Stein, Lisa K. Micklesfield, Shane A. Norris, Felipe Lobelo, and Terryl J. Hartman
Subjects: Male, Longitudinal study, Adolescent, Health Behavior, Population, Physical activity, Walking, World health, South Africa, 03 medical and health sciences, Leisure Activities, 0302 clinical medicine, 030225 pediatrics, medicine, Humans, 030212 general & internal medicine, Child, education, Exercise, education.field_of_study, business.industry, 4. Education, lcsh:RJ1-570, lcsh:Pediatrics, Sedentary behavior, Models, Theoretical, medicine.disease, Sleep in non-human animals, Obesity, Adolescence, 3. Good health, Adolescent Behavior, Pediatrics, Perinatology and Child Health, Cohort, Regression Analysis, Female, Sleep, business, Goals, Low or middle income country, Research Article, Follow-Up Studies, Sports, Demography
Abstract: Background Adolescence is a critical phase of human development that lays the foundation for health in later life. Of the 1.8 billion adolescents in the world, roughly 90% live in low and middle-income countries. Yet most longitudinal studies of adolescent physical activity, sedentary behavior, and sleep come from high-income countries. There is a need for a better understanding of these behaviors to inform obesity and chronic disease prevention strategies. Aims The aim of this study is to identify longitudinal patterns and associations between physical activity, sedentary behavior and sleep in urban South African adolescents. Methods We analyzed data from the Birth-to-Twenty Plus Cohort (Bt20+), a longitudinal study of children in Soweto, Johannesburg, South Africa. Behaviors were self-reported annually between ages 12 and 17 y. We used Latent Class Growth Analysis to group participants into classes based on common longitudinal trajectories of time spent in informal physical activity, organized sports, walking to and from school, sedentary behavior, and school-night and weekend sleep, respectively. We performed group-based multi-trajectory modeling to identify latent clusters of individuals who followed similar trajectories of informal physical activity, organized sports and walking to and from school, and who followed similar trajectories of these three domains together with sedentary behavior and sleep. Results The large majority of males (82%) and all females failed to meet the World Health Organization (WHO) physical activity recommendation for adolescents of 60 min of moderate-vigorous intensity physical activity per day. The physical activity domains clustered together in three multi-trajectory groups that define individuals’ overall physical activity pattern. While two patterns indicated decreases in physical activity throughout adolescence, one pattern, including 29% of the sample in males and 17% of the sample in females, indicated higher levels of activity throughout adolescence. Sedentary behavior and sleep trajectories did not cluster together with the physical activity domains. Conclusion Most adolescents in this South African population did not meet WHO recommendations for physical activity. In this population, trajectories of sedentary behavior and sleep were independent of physical activity. Electronic supplementary material The online version of this article (10.1186/s12887-019-1619-z) contains supplementary material, which is available to authorized users.
Published: 2019
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17. Food subsidies, nutrition transition, and dietary patterns in a remote Indian district

Author: Nida I. Shaikh, Solveig A. Cunningham, Ashlesha Datar, Amanda E. Chernishkin, and Shailaja S Patil
Subjects: Consumption (economics), 0303 health sciences, Ecology, Poverty, 030309 nutrition & dietetics, Dietary intake, 05 social sciences, Context (language use), Subsidy, 03 medical and health sciences, Environmental health, Rural people, 0502 economics and business, Nutrition transition, 050202 agricultural economics & policy, Business, Safety, Risk, Reliability and Quality, Safety Research, Bespoke, Food Science
Abstract: We examined food subsidies and dietary intake in a remote district of India in the context of globalizing food environments. We used bespoke quantitative instruments to collect data on frequency of intake of 69 foods and a dietary variety score among 937 adults. We compared frequency of intake between urban and rural people receiving and not receiving subsidies. Subsidy recipients, who live in poverty, had slightly less varied diets and less frequent consumption of expensive foods, especially fruits and dairy, than non-recipients. However, there were no differences between poor and non-poor in frequency of intake of rice and pulses, both of which are provided through the subsidies to the poor.
Published: 2021
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18. Relationship between prenatal growth, postnatal growth and childhood obesity: a review

Author: EK Matthews, Jingkai Wei, Solveig A. Cunningham, Sociology, and Interface Demography
Subjects: Adult, Male, Pediatric Obesity, Pediatrics, medicine.medical_specialty, Calorie, Adolescent, Adolescent Nutritional Physiological Phenomena, Medicine (miscellaneous), 030209 endocrinology & metabolism, Childhood obesity, Fetal Development, 03 medical and health sciences, Child Development, 0302 clinical medicine, Pregnancy, Risk Factors, medicine, Humans, 030212 general & internal medicine, Postnatal growth, Child, Infant Nutritional Physiological Phenomena, Evidence-Based Medicine, Nutrition and Dietetics, business.industry, Infant, Maternal Nutritional Physiological Phenomena, Adolescent Development, Overweight, medicine.disease, Obesity, Increased risk, Child, Preschool, Female, Diet, Healthy, Child Nutritional Physiological Phenomena, business, Body mass index
Abstract: Evidence is accumulating that obesity risks become established early in life. The goal of this systematic review is to assess whether there is evidence that rapid postnatal growth holds different implications for childhood obesity risks for children who experienced different patterns of prenatal growth. We conducted systematic database searches in PubMed and Embase in October 2014 for studies assessing the implications of prenatal and postnatal growth for childhood obesity. The 18 studies meeting inclusion criteria indicated that risks of obesity increased with birthweight; risks of obesity also increased with rapid postnatal growth for children across the birthweight distribution. Fifteen studies indicated that rapid postnatal growth is linearly associated with obesity for children and adolescents of all sizes at birth, with no interaction effect. Three studies reported interaction effects with postnatal growth, conferring additional increased risk of obesity among children and adolescents who were small at birth. Both prenatal and postnatal growth are important risk factors for obesity, and their combined effects should be analyzed further to understand how obesity risks develop early in life.
Published: 2017
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19. Alcohol Consumption and Incident Stroke Among Older Adults

Author: Edmond K. Kabagambe, Solveig A. Cunningham, Lisa M Matz, Claudia S. Moy, Aleena Mosher, Virginia J. Howard, Suzanne E. Judd, Sociology, and Interface Demography
Subjects: Male, medicine.medical_specialty, Race, Alcohol Drinking, Sociology and Political Science, Social Psychology, Epidemiology, The Journal of Gerontology: Joint Section: Smoking, Alcohol, and Drug Use Among Older Adults, White People, Health(social science), National cohort, 03 medical and health sciences, Sex Factors, 0302 clinical medicine, Risk Factors, gender, medicine, Humans, cardiovascular diseases, 030212 general & internal medicine, Life-span and Life-course Studies, Stroke, Socioeconomic status, Aged, Proportional Hazards Models, business.industry, Proportional hazards model, Incidence, Incidence (epidemiology), Middle Aged, alcohol use, medicine.disease, United States, Black or African American, Clinical Psychology, Socioeconomic Factors, Cohort studies, Female, Geriatrics and Gerontology, business, Gerontology, Alcohol consumption, 030217 neurology & neurosurgery, Demography, Cohort study
Abstract: Objectives This study examines the relationship between alcohol consumption and incident stroke among older adults and tests whether alcohol consumption contributes to observed race and sex differences in stroke. Method Data are from a U.S. national cohort of black and white adults aged 45 and older, the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. Current and past drinking levels were reported at baseline (2003-2007). Participants who had never had a stroke were followed for adjudicated stroke events through September 2015 (n = 27,265). We calculated Cox proportional hazard models for stroke, adjusting for demographic, socioeconomic, behavioral, and health characteristics. Results Participants, mean age 64.7 years, consumed on average 2.2 drinks/week and experienced 1,140 first-time stroke events over median 9.1 years follow-up. Nondrinkers had a 12% higher risk of stroke than current drinkers; the risk of stroke among nondrinkers largely reflected high risks among past drinkers; these differences were explained by socioeconomic characteristics. Among current drinkers, light drinkers had significantly lower stroke risks than moderate drinkers after accounting for demographic, socioeconomic, behavioral, and health characteristics. Implications of alcohol did not differ between blacks and whites but did differ by sex: Especially among women, nondrinkers, and specifically past drinkers, had higher risks; these differences were largely explained by health characteristics and behaviors. Alcohol did not explain race and sex differences in stroke incidence. Discussion Among older adults, those who used to, but no longer, drink had higher risks of stroke, especially among women; current light drinkers had the lowest risk of stroke.
Published: 2017
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20. Development and evaluation of a Nutrition Transition-FFQ for adolescents in South India

Author: Jennifer K. Frediani, K.M.V. Narayan, Shailaja S Patil, Kathryn M. Yount, Nida I. Shaikh, Reynaldo Martorell, Solveig A. Cunningham, and Usha Ramakrishnan
Subjects: Male, 0301 basic medicine, Food intake, Adolescent, Concordance, Health Behavior, India, Medicine (miscellaneous), Food group, 03 medical and health sciences, Environmental health, Nutrition transition, Humans, Medicine, Eating behaviour, Demography, Face validity, Schools, 030109 nutrition & dietetics, Nutrition and Dietetics, business.industry, Portion Size, Public Health, Environmental and Occupational Health, Reproducibility of Results, Nutrition Surveys, Research Papers, Diet Records, Diet, Mental Recall, Red meat, Female, business, Kappa
Abstract: ObjectiveTo develop and evaluate a Nutrition Transition-FFQ (NT-FFQ) to measure nutrition transition among adolescents in South India.DesignWe developed an interviewer-administered NT-FFQ comprising a 125-item semi-quantitative FFQ and a twenty-seven-item eating behaviour survey. The reproducibility and validity of the NT-FFQ were assessed using Spearman correlations, intra-class correlation coefficients (ICC), and levels of agreement using Bland–Altman and cross-classification over 2 months (NT-FFQ1 and NT-FFQ2). Validity of foods was evaluated against three 24-h dietary recalls (24-HR). Face validity of eating behaviours was evaluated through semi-structured cognitive interviews. The reproducibility of eating behaviours was assessed using weighted kappa (κw) and cross-classification analyses.SettingVijayapura, India.SubjectsA representative sample of 198 adolescents aged 14–18 years.ResultsReproducibility of NT-FFQ: Spearman correlations ranged from 0·33 (pulses) to 0·80 (red meat) and ICC from 0·05 (fruits) to 1·00 (tea). On average, concordance (agreement) was 60 % and discordance was 7 % for food groups. For eating behaviours,κwranged from 0·24 (eating snacks while watching television) to 0·67 (eating lunch at home) with a mean of 0·40. Validity of NT-FFQ: Spearman correlations ranged from 0·11 (fried traditional foods) to 0·70 (tea) and ICC ranged from 0·02 (healthy global foods) to 1·00 (grains). The concordance and discordance were 48 % and 8 %, respectively. Bland–Altman plots showed acceptable agreement between NT-FFQ2 and 24-HR. The eating behaviours had acceptable face validity.ConclusionsThe NT-FFQ has good reproducibility and acceptable validity for food intake and eating behaviours. The NT-FFQ can quantify the nutrition transition among Indian adolescents.
Published: 2017
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21. Parental Perception of Neighborhood Safety and Children’s Physical Activity

Author: Karla I. Galaviz, Deena Zytnick, Michelle C. Kegler, and Solveig A. Cunningham
Subjects: Male, Parents, medicine.medical_specialty, Longitudinal study, Poison control, 030209 endocrinology & metabolism, Article, Occupational safety and health, 03 medical and health sciences, 0302 clinical medicine, Residence Characteristics, Environmental health, Injury prevention, Odds Ratio, Humans, Medicine, Orthopedics and Sports Medicine, Longitudinal Studies, 030212 general & internal medicine, Early childhood, Child, Exercise, Recreation, business.industry, Human factors and ergonomics, Child, Preschool, Physical therapy, Regression Analysis, Environment Design, Female, Perception, Residence, Safety, business
Abstract: Background:We examined the relationship between parents’ perception of neighborhood safety and children’s physical activity and use of recreation facilities in a US nationally representative sample of fifth grade children.Methods:We used data from the Early Childhood Longitudinal Study Kindergarten cohort, fifth grade sample (N = 9827). Multivariate logistic and linear regression models were used to examine associations between parents’ perception of neighborhood safety for outside play and number of days children engage in physical activity, as well as children’s use of recreational facilities for physical activity.Results:Children who used recreational facilities engaged in physical activity on more days of the week compared with children who did not use a facility (3.3 days vs. 3.8 days, P < .0001). Children from neighborhoods perceived as unsafe by parents engaged in almost 1 less day per week in physical activity (β = –.89, P < .0001). Children from neighborhoods perceived as unsafe were less likely to use recreational facilities compared with children from neighborhoods perceived as safe (odds ratio = 0.72, P < .0001). Children from less affluent families across rural and urban areas had half the odds of using recreational facilities compared with children from the wealthiest families living in urban areas.Conclusions:Parents’ perception of neighborhood safety for outside play can deter or promote children’s physical activity and use of recreational facilities. Children from less affluent families are less likely to use facilities than children from wealthy families, regardless of place of residence.
Published: 2016
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22. A 'snapshot' of physical activity and food habits among private school children in India

Author: Sara Thorpe, Shailaja S Patil, Solveig A. Cunningham, and Erin M. Staab
Subjects: 0301 basic medicine, Gerontology, 030109 nutrition & dietetics, Private school, media_common.quotation_subject, Psychological intervention, Physical activity, Food habits, medicine.disease, Obesity, Article, 03 medical and health sciences, 0302 clinical medicine, Geography, Perception, Developmental and Educational Psychology, Nutrition transition, medicine, Photovoice, sense organs, 030212 general & internal medicine, Socioeconomics, media_common
Abstract: Concerns about increasing obesity in poorer parts of the world, including India, have often been premised in terms of global shifts in activity levels and caloric consumption. Lifestyle changes have been documented in large cities, but we do not know whether these changes are reaching young people in less urban locations. This study used photo journals to explore children’s perceptions of their food and activity habits in a remote Indian city. Children expressed interest in active pastimes, learning, and health, and indicated traditional, modern, local, and global influences in their lives. Findings offer context for research and interventions.
Published: 2016
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23. Going global: Indian adolescents’ eating patterns

Author: Usha Ramakrishnan, Solveig A. Cunningham, Nida I. Shaikh, Shiva S. Halli, and Shailaja S Patil
Subjects: Male, 0301 basic medicine, Food intake, Adolescent, media_common.quotation_subject, Food consumption, India, Medicine (miscellaneous), 03 medical and health sciences, Environmental health, Nutrition transition, Humans, media_common, Consumption (economics), 030109 nutrition & dietetics, Nutrition and Dietetics, Street foods, Public Health, Environmental and Occupational Health, Feeding Behavior, Research Papers, Diet, Cross-Sectional Studies, Geography, Female, Leafy vegetables, Ordered logit, Energy Intake, Diversity (politics)
Abstract: ObjectiveTo describe adolescents’ eating patterns of traditional, global/non-local and mixed foods, and the factors that may influence food consumption, access and preferences, in a globalizing city.DesignA representative sample of school-going adolescents completed a cross-sectional survey including an FFQ designed to identify traditional and global foods. Student’sttest and ordinal logistic regression were used to examine weekly food intake, including differences between boys and girls and between adolescents attending private and public schools.SettingVijayapura city, Karnataka State, India.SubjectsAdolescents (n399) aged 13–16 years.ResultsCompared with dietary guidelines, adolescents consumed fruit, green leafy vegetables, non-green leafy vegetables and dairy less frequently than recommended and consumed energy-dense foods more frequently than recommended. Traditional but expensive foods (fruits, dairy, homemade sweets and added fat) were more frequently consumed by private-school students, generally from wealthier, more connected families, than by public-school students; the latter more frequently consumed both traditional (tea, coffee, eggs) and mixed foods (snack and street foods;P≤0·05). Girls reported more frequent consumption of global/non-local packaged and ready-to-eat foods, non-green leafy vegetables and added fat than boys (P≤0·05). Boys reported more frequent consumption of eggs and street foods than girls (P≤0·05).ConclusionsAdolescents’ eating patterns in a globalizing city reflect a combination of global/non-local and traditional foods, access and preferences. As global foods continue to appear in low- and middle-income countries, understanding dietary patterns and preferences can inform efforts to promote diversity and healthfulness of foods.
Published: 2016
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24. Beyond recent BMI: BMI exposure metrics and their relationship to health

Author: Fernando Riosmena, Michael R. Elliott, Solveig A. Cunningham, and Carmen D. Ng
Subjects: Chronic condition, Health (social science), Population health, Overweight, Article, 03 medical and health sciences, 0302 clinical medicine, Medicine, Obesity, 030212 general & internal medicine, National Longitudinal Surveys, lcsh:Social sciences (General), Young adult, Body mass index, 2. Zero hunger, 030505 public health, business.industry, lcsh:Public aspects of medicine, Longitudinal studies, Health Policy, Public Health, Environmental and Occupational Health, nutritional and metabolic diseases, lcsh:RA1-1270, medicine.disease, Health indicator, 3. Good health, Chronic health, lcsh:H1-99, medicine.symptom, 0305 other medical science, business, Demography
Abstract: Body mass index (BMI) is generally used to classify adiposity. Despite the fact that the consequences of adiposity for chronic health accumulate and manifest over time, most population health research exploring the implications of high BMI measures only its recent intensity. Some studies have used retrospective measures involving maximum weight, and even fewer have used BMI at multiple time points to estimate cumulative exposure to adiposity. The goal of this study was to compare BMI exposure metrics that captured different dimensions of body mass – intensity, history, and duration – in models of health indicators linked with adiposity. We used self-reported BMI of young adults (ages 18 – 33 years, n = 8,608) across 11 waves of data from the National Longitudinal Survey of Youth 1997 to evaluate eight BMI exposure metrics: most recent, maximum, mean, and median BMI, proportion of time with overweight/obesity, and excess BMI-years with overweight/obesity. We used these metrics in models of self-reported general health, chronic condition, and diabetes, and ascertained how most recent BMI performed when compared with other metrics that better capture the dynamics of BMI. The Akaike information criteria and Vuong tests were used for model comparison, and the strengths of associations were also compared. Most recent BMI was the best metric for explaining general health. Median BMI was best for explaining diabetes, with most recent BMI under-estimating the association by 13% relative to median BMI. For chronic condition, there was no clear best metric. We concluded that most recent BMI is useful for explaining health outcomes, though other metrics should also be given consideration, particularly for conditions that develop over time. Metrics that accounted for both intensity and history performed quite well, but the duration measures might be less useful., Highlights • BMI is dynamic, so researchers need to consider beyond BMI at the time of survey. • We calculated 8 BMI-based metrics accounting for intensity, history, and duration. • Most recent BMI was the best metric, based on AIC, for explaining general health. • Most recent BMI understated the association for diabetes, relative to median BMI.
Published: 2020
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25. Protecting children's health in a calorie-surplus context: Household structure and child growth in the United States

Author: Kathryn M. Yount, Eeshwar K. Chandrasekar, Kate Cartwright, and Solveig A. Cunningham
Subjects: Longitudinal study, Physiology, Social Sciences, Growth, Pediatrics, Body Mass Index, Families, Fathers, 0302 clinical medicine, Child Development, Sociology, Medicine and Health Sciences, Public and Occupational Health, 030212 general & internal medicine, Early childhood, Longitudinal Studies, Child, Children, Family Characteristics, Multidisciplinary, Schools, Child Health, Grandparent, 3. Good health, Spring, Physiological Parameters, Child, Preschool, Medicine, Seasons, Psychology, Research Article, Childhood Obesity, Adolescent, Science, Mothers, 030209 endocrinology & metabolism, Childhood obesity, Education, 03 medical and health sciences, medicine, Humans, Obesity, Body Weight, Biology and Life Sciences, Anthropometry, medicine.disease, Child development, Age Groups, People and Places, Earth Sciences, Population Groupings, Energy Intake, Body mass index, Demography
Abstract: Studies from the social and health sciences have tended to view the household as the locus of access to and distribution of care, resources, monitoring and modeling for children's wellbeing. Obesity may present a special case for the study of investments in children, being a component of health for which more of certain inputs may not lead to better outcomes. We expanded on common measures of household structure in the child health literature by considering co-residence and relatedness of parents, grandparents, other relatives, and other children. Data were from a longitudinal sample of 6,700 children participating in the Early Childhood Longitudinal Study Kindergarten Class of 1998-99 (ECLS-K), the largest U.S. national dataset with measures of child anthropometrics and household structure at seven time-points over nine years. We used lagged survey-adjusted regressions to estimate associations between household structure and subsequent changes in children's weight between ages 5 and 14 years in terms of BMI gain and incident obesity. Adjusting for household structure more thoroughly, children living in households with two parents rather than one parent did not experience advantages in terms of less excess weight gain or lower incidence of obesity during elementary and middle school. Children living with a grandmother gained more weight than children not living with a grandmother. Living with siblings and with non-related adults was associated with less weight gain. These findings corroborate a scenario in which, for health problems associated with caloric surplus, classic household factors have more complex associations with child wellbeing.
Published: 2019

26. UNHEALTHY WEIGHT IN INDIAN FAMILIES: THE ROLE OF THE FAMILY ENVIRONMENT IN THE CONTEXT OF THE NUTRITION TRANSITION

Author: Ilana G Raskind, Shailaja S Patil, Solveig A. Cunningham, and Regine Haardörfer
Subjects: 0301 basic medicine, 030109 nutrition & dietetics, business.industry, Social ecology, Distribution (economics), Context (language use), Management, Monitoring, Policy and Law, Overweight, Article, 03 medical and health sciences, 0302 clinical medicine, medicine, Nutrition transition, Survey data collection, 030212 general & internal medicine, Sibling, medicine.symptom, Underweight, Psychology, business, Demography
Abstract: India faces a dual burden of increasing obesity and persistent underweight as it experiences the nutrition transition—the dietary and lifestyle changes that accompany globalization, economic development, and technological change. Yet, the nutrition transition is not solely a top-down process; rather, global forces converge with local practices at multiple levels of the social ecology. The family environment, a key site for the transmission of local customs and norms, remains largely unexplored in India. We examined the extent to which opposite-gender siblings and mother–child pairs were concordant or discordant in body weight, and whether domains of the family environment, specifically, food practices, food-related gender norms, and household resources, were associated with patterns of unhealthy weight within and between families. Multilevel dyadic analysis and logistic regression were conducted using survey data from a representative sample of 400 families in a Southern Indian city. We identified substantial clustering of weight among opposite-gender sibling pairs (ICC = 0.43) and mother–child pairs, as well as important patterns of discordance, including 11% of families experiencing a dual burden of underweight and overweight. Household resources, including mother’s education and income, were salient in explaining the distribution of body weight within and between families. Importantly, less examined domains of the family environment were also relevant, including food practices (e.g., grocery shopping frequency), and food-related gender norms (e.g., mother’s control of food served at home). Continued exploration of how global and local practices converge in households will be necessary to develop programming that effectively addresses India’s dual burden of unhealthy weight.
Published: 2018

27. Influence of a New Diabetes Diagnosis on the Health Behaviors of the Patient’s Partner

Author: Julie A. Schmittdiel, Solveig A. Cunningham, Sara R. Adams, Mohammed K. Ali, and Jannie Nielsen
Subjects: Adult, Male, medicine.medical_specialty, Teachable moment, Adolescent, medicine.medical_treatment, Health Status, Health Behavior, 030209 endocrinology & metabolism, California, Cohort Studies, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Weight loss, Internal medicine, Diabetes mellitus, medicine, Diabetes Mellitus, Humans, 030212 general & internal medicine, Spouses, Original Research, Aged, Aged, 80 and over, business.industry, Middle Aged, medicine.disease, Logistic Models, Relative risk, Smoking cessation, Population study, Health education, Female, medicine.symptom, Family Practice, business, Cohort study
Abstract: PURPOSE When a person is given a diagnosis of diabetes, the changes in his or her health behaviors may influence the behaviors of his or her partner. The diabetes diagnosis may affect household members’ perceptions of their own health risks, which could trigger behavioral change. The purpose of this study was to assess whether partners of persons with newly diagnosed diabetes changed their health behaviors compared with partners of persons without diabetes. METHODS The study population consisted of Kaiser Permanente Northern California health plan members from 2007 to 2011. This cohort study assessed differences in change of 8 health behaviors. The study compared coresiding partners of persons with newly diagnosed diabetes before and after a diabetes diagnosis with a 5 to 1 matched sample of coresiding partners of persons without diabetes. RESULTS A total of 180,910 couples were included in the analysis. After adjusting for baseline characteristics, partners of persons with newly diagnosed diabetes had significantly higher rates of participation in weight management–related health education classes (risk ratio [RR] = 1.50; 95% CI, 1.39-1.63); smoking cessation medication use (RR = 1.25; 95% CI, 1.05-1.50); glucose screening (RR = 1.07; 95% CI, 1.05-1.08); clinically meaningful weight loss (RR = 1.06; 95% CI, 1.02-1.11); lipid screening (RR = 1.05; 95% CI, 1.04-1.07); influenza vaccination (RR = 1.03; 95% CI, 1.02-1.04); and blood pressure screening (RR = 1.02; 95% CI, 1.02-1.03) compared with partners of persons without diabetes. CONCLUSIONS There were small but significant differences in health-related behavioral changes among partners of persons with newly diagnosed diabetes compared with partners of persons without diabetes, even when no intervention occurred. This finding suggests a diabetes diagnosis within a family may be a teachable moment to improve health behaviors at the household level.
Published: 2018

28. Before-school and after-school childcare and children's risk of obesity

Author: Solveig A. Cunningham, Nikkil Sudharsanan, and Parini M. Shah
Subjects: Gerontology, Longitudinal study, Nutrition and Dietetics, business.industry, Health Policy, education, Public Health, Environmental and Occupational Health, 030209 endocrinology & metabolism, Odds ratio, Logistic regression, medicine.disease, Childhood obesity, Odds, 03 medical and health sciences, 0302 clinical medicine, Pediatrics, Perinatology and Child Health, Cohort, medicine, 030212 general & internal medicine, Early childhood, Risk factor, business
Abstract: Summary Background In the USA, half of children are regularly cared for before or after school by someone other than a parent. Objective Describe the relationship between childcare arrangements and obesity among school-aged children. Methods Data are from the fifth-grade wave of the Early Childhood Longitudinal Study – Kindergarten Cohort 1998–1999, a nationally representative study of US children who were in kindergarten in 1998–1999 or first grade in 1999, collected in spring 2004 (analytic sample = 9617). We estimated survey-adjusted logistic regression models to examine the association between childcare arrangements before and after school and obesity. Results The prevalence of obesity was highest among fifth graders who received care from multiple sources and lowest among children who received care from adults not related to them in either the child's or the caregiver's home [29.9%, 95% confidence interval {CI}: 18.7%, 44.3%; and 17.3%, 95% CI: 12.1%, 24.0%]. Childcare arrangement was not an independent risk factor for obesity for most children. However, Hispanic children who were cared for by a person who was not a relative had significantly higher odds of obesity compared with non-Hispanics in similar care arrangements (odds ratio: 5.11, 95% CI: 2.00, 13.06). Conclusion Type of childcare before or after school was not an independent risk factor for obesity in most fifth graders, but implications of childcare for Hispanic children should be explored further.
Published: 2016
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29. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013

Author: Yong Zhao, Hadi Danawi, Bach Xuan Tran, Gene Bukhman, Vasiliki Stathopoulou, Taavi Tillmann, Nelson Alvis-Guzman, Yongmei Li, Jerry Puthenpurakal Abraham, Sudan Prasad Neupane, Jack Caravanos, Ben Schöttker, Rafael Lozano, Damian G Hoy, Yoshihiro Kokubo, Nicholas J K Breitborde, Sergey Soshnikov, Yukito Shinohara, Randall V. Martin, Michael Brainin, Fernando Perez-Ruiz, Yingfeng Zheng, Santosh Mishra, Julio Cesar Montañez Hernandez, Michael Phillips, Belinda J. Gabbe, Hebe N. Gouda, Ziad A. Memish, Rupert R A Bourne, Guoqing Hu, Emmanuel A. Ameh, Abigail McLain, Michelle L. Bell, Christopher Margono, Marissa Iannarone, Wilkister N. Moturi, Donald H. Silberberg, Carl Abelardo T. Antonio, Nataliya Foigt, Anand Dayama, Yanping Wang, Amanda J. Mason-Jones, Bolajoko O. Olusanya, Monica S. Vavilala, Katherine B Gibney, David Tanne, Sidibe S Kany Roseline, Marcella Montico, Abhishek Singh, Sarah Derrett, Alireza Esteghamati, Seok Jun Yoon, Corine Karema, Rakhi Dandona, David M. Pereira, Kazem Rahimi, Gitanjali M. Singh, Vivekanand Jha, John Hornberger, Anne M. Riederer, Kathryn H. Jacobsen, Andrea Pedroza, Lily Alexander, Fiona M. Blyth, Tommi Vasankari, Kyle J Foreman, Rana J. Asghar, Tilahun Nigatu Haregu, Yousef Khader, Rafael Alfonso-Cristancho, Suzanne Barker-Collo, Lydia S. Atkins, Simerjot K. Jassal, Mohammad Ali Sahraian, Peter Scarborough, Hans W. Hoek, E. Ray Dorsey, Muluken Dessalegn, David C. Schwebel, Gavin Shaddick, Thomas D. Fleming, Mohammad Tavakkoli, Dorairaj Prabhakaran, Mohammad H. Forouzanfar, Christopher C. Mapoma, Jost B. Jonas, Erin C Mullany, Gene F. Kwan, Johanna M. Geleijnse, Antonio Luiz Pinho Ribeiro, Roberto Tchio Talongwa, Tolesa Bekele, Jed D. Blore, Gunn Marit Aasvang, Philimon Gona, Miguel Angel Alegretti, Babak Eshrati, Mitsuru Mukaigawara, Richard F. Gillum, Odgerel Chimed-Ochir, Ubai Alsharif, Richard C. Franklin, Felix Masiye, Richard T. Burnett, Sanjay Krishnaswami, Martin McKee, John J Huang, Lucía Cuevas-Nasu, Wagner Marcenes, Walid Ammar, Knud Juel, Joseph R. Zunt, Martha M Téllez Rojo, Mamta Swaroop, Noela M Prasad, Azmeraw T. Amare, Tim Driscoll, Michael Kravchenko, Heresh Amini, Amir Sapkota, Theo Vos, Charlotte Watts, Dennis Odai Laryea, D. Alex Quistberg, Justin Beardsley, Cheng Huang, Adnan M. Durrani, Sarah V Thackway, Rita Van Dingenen, Manami Inoue, Martha Híjar, Honglei Chen, Amany H. Refaat, Yichong Li, Vineet K. Chadha, Wenzhi Wang, Louisa Degenhardt, Kingsley N. Ukwaja, Nayu Ikeda, James D. Wilkinson, Linh N Bui, Maria Hagströmer, Gonghuan Yang, Ann Kristin Knudsen, David J. Margolis, Soewarta Kosen, Hans Kromhout, Atsushi Goto, Man Mohan Mehndiratta, Thomas N. Williams, Michael Soljak, Yun Jin Kim, Hideaki Toyoshima, Jeyaraj D Pandian, Borja del Pozo-Cruz, Soufiane Boufous, Ivy Shiue, Anders Larsson, Guilherme V. Polanczyk, John Powles, Yara A. Halasa, Robin Room, Ratilal Lalloo, Carolina Batis Ruvalcaba, Panniyammakal Jeemon, Elisabete Weiderpass, Jürgen Rehm, Ejaz Ahmad Khan, Alicia Aleman, Zacharie Tsala Dimbuene, Elena Alvarez, Rachelle Buchbinder, Randah R. Hamadeh, Bryan Hubbell, Sadaf G. Sepanlou, Farhad Islami, Costas A. Christophi, Heidi Stöckl, Ismael R. Campos-Nonato, Nigel Bruce, Edward J Mills, Samuel A L Perry, Taavi Lai, Baffour Awuah, Mete Saylan, Karen J. Courville, Arindam Basu, Vanessa De la Cruz-Góngora, Teresita González de Cosío, Naohiro Yonemoto, Frida Namnyak Ngalesoni, Muluken Azage Yenesew, Atte Meretoja, Michael Brauer, Cyrus Cooper, Giorgia Giussani, Valentina S. Arsic Arsenijevic, Vasiliy Victorovich Vlassov, André Karch, Leilei Duan, Matthew M Coates, Omid Ameli, Gelin Xu, Matthias Endres, Ganesan Karthikeyan, Ione Jayce Ceola Schneider, Mohamed Hsairi, Palwasha Anwari, Mazin J. Al Khabouri, Dariush Mozaffarian, Juan R. Sanabria, Pablo M. Lavados, Sumeet S. Chugh, Johan Ärnlöv, Ivo Rakovac, Maurice Giroud, Haidong Kan, Ibrahim Abdelmageem Mohamed Ginawi, José Luis Texcalac-Sangrador, Luigi Naldi, Erica Leigh Slepak, Deena Alasfoor, James E. Saunders, Richard Matzopoulos, Talal Bakfalouni, Stein Emil Vollset, Andrea Werdecker, Lennert J. Veerman, Lorenzo Monasta, Henrica A. F. M. Jansen, Reyna A Gutiérrez, Brittany Wurtz, Luz Maria Sanchez, Lijing L. Yan, M. Patrice Lindsay, Michele Meltzer, Sanjay Basu, Steven van de Vijver, Alaa Badawi, Thomas Claßen, Young-Ho Khang, Brett M. Kissela, Jun Zhu, In-Hwan Oh, Fiona J Charlson, Maria Cecilia Bahit, Dinorah González-Castell, Rosario Cárdenas, Dan Poenaru, Sayed Saidul Alam, Mitchell T. Wallin, Harish Chander Gugnani, James Leigh, Ferrán Catalá-López, Lidia Morawska, Jim van Os, Stephanie J. London, Kaire Innos, Isabelle Romieu, Fiorella Cavalleri, Adrian Davis, Hwee Pin Phua, Chakib Nejjari, Héctor Gómez Dantés, Boris I. Pavlin, Karen Sliwa, Lynne Gaffikin, Constance D. Pond, Michael F. MacIntyre, Blake Thomson, Norberto Perico, Ronny Westerman, Samantha M. Colquhoun, Michael H. Criqui, Ana Maria Nogales Vasconcelos, Wubegzier Mekonnen, Bulat Idrisov, Ana Basto-Abreu, Andrew G. M. Bulloch, Jasvinder A. Singh, Vinod K. Paul, Emin Murat Tuzcu, Svetlana Popova, Hmwe H Kyu, Richard L. Guerrant, Mohammed I. Albittar, Srikanth Mangalam, Steven E. Lipshultz, Lela Sturua, Semaw Ferede Abera, Eduardo Bernabé, George D. Thurston, Bruno F. Sunguya, Tiffany Ku, Alejandra G. Contreras, Abdullah Sulieman Terkawi, Charles Atkinson, Ashkan Afshin, Heidi J. Larson, Abdullatif Husseini, Jose C. Adsuar, Reza Assadi, Ademola Lukman Adelekan, Joshua A. Salomon, Yousef M. Elshrek, Gokalp Kadri Yentur, Devina Nand, Narayanaswamy Venketasubramanian, Graça Maria Ferreira De Lima, Maheswar Satpathy, Fotis Topouzis, Traolach S. Brugha, Hywel C Williams, Coen H. Van Gool, Andrew H. Kemp, Awoke Misganaw, Amado D Quezada, Norito Kawakami, Bert Brunekreef, Peter Burney, Tati S. Warouw, Jongmin Lee, Inga Dora Sigfusdottir, Marcel Tanner, Solveig A. Cunningham, Benjamin O. Anderson, Tariku Jibat Beyene, Lars Barregard, Xia Wan, Giuseppe Remuzzi, Bernadette Thomas, Lilia S Pedraza, Massimo Cirillo, Alina Rodriguez, Ricky Leung, Farshad Pourmalek, K. Srinath Reddy, Charles D.A. Wolfe, Ulrich O Mueller, Neeraj Bedi, Al Artaman, Lucia Hernandez, Itamar S. Santos, C. Arden Pope, Norlinah Mohamed Ibrahim, Carlo Irwin A. Panelo, Selen Begüm Uzun, Miltiadis K. Tsilimbaris, Anwar Rafay, Daniel Dicker, Melvin Barrientos Marzan, Sajjad Ur Rahman, Mohammed O. Basulaiman, Edgar P. Simard, Mohammad T Mashal, Maysaa El Sayed Zaki, Shiwei Liu, Don C. Des Jarlais, Bo Norrving, Salvador Villalpando, Miia Kivipelto, Yang Liu, Carolina Maria Teixeira, Catalina Medina, Sudha Jayaraman, Josep Maria Haro, Diego De Leo, Angel J Paternina Caicedo, Abigail C. McKay, Eric L. Ding, Mukesh Dherani, Ljiljana Pejin Stokic, Vinay Nangia, Sukanta Saha, Juan Liang, Elisabeth Cardis, Zourkaleini Younoussi, José R Nogueira, Braden Te Ao, Vasco Manuel Pedro Machado, Lionel Racapé, Ting Wu Chuang, Shahab Khatibzadeh, E Filipa de Castro, Barthelemy Kuate Defo, Ulises Trujillo, Alan D. Lopez, Soraya Seedat, Lope H Barrero, Linhong Wang, Daniel Pope, Alexandra Brazinova, Faris Lami, Valentina Colistro, G Anil Kumar, Derek F J Fay, Haidong Wang, Hwashin H. Shin, Raimundas Lunevicius, Suzanne Polinder, Dietrich Plass, David Rojas-Rueda, Stephen S Lim, Tania G Sánchez-Pimienta, K.M. Venkat Narayan, Yuantao Hao, Jung-Chen Chang, Corina Benjet, Seyed-Mohammad Fereshtehnejad, Luciano A. Sposato, Stan Biryukov, Kunihiro Matsushita, Beth E. Ebel, Cleusa P. Ferri, Soumya Swaminathan, K. Ryan Wessells, Gustavo Velasquez-Melendez, Leslie T. Cooper, David O. Carpenter, Nancy Lopez, Bryan L. Sykes, Sandra Nolte, Murray B. Stein, Paul N. Jensen, Fabiola Mejía-Rodríguez, Xiaonong Zou, Bradford D. Gessner, Dhruv S. Kazi, Dragos Virgil Davitoiu, Alejandra Jáuregui, Pouria Heydarpour, Megan Bohensky, Harvey Whiteford, Berrak Bora Basara, Zhengming Chen, Gregory R. Wagner, Paul I. Dargan, Hermann Brenner, Nima Hafezi-Nejad, John Nelson Opio, Scott Weichenthal, Deborah Salvo, Jun She, Tea Lallukka, Carolyn C. Gotay, Stephen G. Waller, Christian Kieling, Shivanthi Balalla, Valery L. Feigin, Qing Lan, Matias Trillini, Adam D M Briggs, Sungroul Kim, Niveen M E Abu-Rmeileh, Renata Micha, Sergey Petrovich Ermakov, Ole Frithjof Norheim, Zulfiqar A Bhutta, Paul S. F. Yip, Grant Nguyen, Ralph L. Sacco, Biju Abraham, Ken Takahashi, Jixiang Ma, Peter A. Meaney, Ayse Abbasoglu Ozgoren, Kimberly Cooperrider, M Rifat Kose, Shams Eldin Ali Hassan Khalifa, Rasmus Havmoeller, Alize J. Ferrari, Kebede Deribe, Nadim E. Karam, George A. Mensah, Bongani M. Mayosi, Konrad Pesudovs, Joanna Moschandreas, Ziad Nahas, James Damsere-Derry, Nsanzimana Sabin, Tonatiuh Barrientos-Gutiérrez, Ying Jiang, Andre Pascal Kengne, Peter Allebeck, Jonas Minet Kinge, Shankuan Zhu, Guy B. Marks, Daniel C Casey, Marco A Avila, Anna Roca, Lalit Dandona, Ami R. Moore, Adansi A. Amankwaa, David Gunnell, Andre Keren, Yohannes Adama Melaku, Nhung T Nguyen, Anthony D. Woolf, Mayuree Rao, Peter J. Allen, Christina Papachristou, Karzan Abdulmuhsin Mohammad, Ravi Kumar Balu, Marie Ng, Marcello Tonelli, Maziar Moradi-Lakeh, Maigeng Zhou, Emmanuela Gakidou, Mohammed K. Ali, Amanda W Pain, Dan J. Stein, Kawkab Shishani, Fortuné Gbètoho Gankpé, Howard J. Hoffman, James Scott, Nadine Steckling, Samia Alhabib, Deborah Jarvis, Kara Estep, Arsène Kouablan Adou, Ricardo Orozco, Holly Hagan, K. C. Astha, Reza Malekzadeh, Klara Dokova, Aliya Naheed, Ernst J. Kuipers, Valeria Caso, Derrick A Bennett, Andrea B. Feigl, Uche S. Uchendu, Holly E. Erskine, Shireen Sindi, Arjun Lakshmana Balaji, Francesco Saverio Violante, Monika Sawhney, Alejandra Cantoral, Ketevan Goginashvili, Raghib Ali, Fan Jiang, Robert G. Weintraub, Homie Razavi, Myriam Tobollik, Howard Hu, Emerito Jose A. Faraon, Irma Khonelidze, Patricia M. Riccio, Eun-Kee Park, Julio Cesar Campuzano, Ibrahim Abubakar, Jürgen C Schmidt, Konstantinos Stroumpoulis, Aref A. Bin Abdulhak, Graeme J. Hankey, Natan M. Bornstein, Mouhanad Hammami, Lee Richardson, Rintaro Mori, Alanur Çavlin, Ruth W Kimokoti, Samir Soneji, Mark J. Nieuwenhuijsen, John Q. Wong, Joseph Frostad, Tom Achoki, Rahman Shiri, Ashish Bhalla, Kurt Straif, Simon I. Hay, Scott B. Patten, Kalpana Balakrishnan, Awoke Misganaw Temesgen, Chandrashekhar T Sreeramareddy, Ryan M Barber, Rosana E. Norman, JianLi Wang, Siyi Shangguan, Luke Nyakarahuka, Kovin Naidoo, Charles D. H. Parry, Mercedes Colomar, H. Ross Anderson, Carlos Magis-Rodriguez, Joan M. Nolla, Muhammad Imran Nisar, Karen Devries, Andrew L. Thorne-Lyman, Denis Nash, Marape Marape, Rajiv Chowdhury, Dima M. Qato, Luca Ronfani, Nobhojit Roy, Daniel Kim, Yuichiro Yano, Luke D. Knibbs, Margaret Robinson, Hilda L Harb, Rogelio Pérez-Padilla, Janet L Leasher, Jonathan L. Wright, Peter Brooks, Cristiana Abbafati, Belinda K Lloyd, Victor Aboyans, Nikhil Tandon, Charles R. Newton, Simón Barquera, Ted R. Miller, Kinnari S. Murthy, Habib Benzian, Glen Mola, Paulo A. Lotufo, Burcu Kucuk Bicer, Peggy Pei-Chia Chiang, Alexander Kraemer, Solomon Meseret Woldeyohannes, Saman Fahimi, Lesley Rushton, Kim Moesgaard Iburg, Vafa Rahimi-Movaghar, Logan Sandar, Bruce Neal, Teresa Shamah Levy, Karen M. Tabb, Jeffrey A. Towbin, Christopher J L Murray, Ramesh Sahathevan, Aaron Cohen, Chanda Kulkarni, Van C. Lansingh, François Alla, Tasara T. Mazorodze, Murugesan Raju, Saeid Shahraz, Uchechukwu K.A. Sampson, Rajeev Gupta, Neil Pearce, Mustafa Z. Younis, Veena S. Kulkarni, Francisco A García-Guerra, Amanda G. Thrift, Stefan Ma, Samaya Ismayilova, Evariste Gasana, Amitava Banerjee, Aslam Pervaiz, Emilie Agardh, Abraham D. Flaxman, Farshad Farzadfar, Peter W. Gething, Ileana Heredia-Pi, Boris Bikbov, Wanqing Chen, Saad B. Omer, Ruben Castro, Neeraj Bhala, Sara Sheikhbahaei, Hilton Lam, Urbano Fra Paleo, Lidia Sanchez-Riera, Alicia Elena Beatriz Lawrynowicz, Kristen Delwiche, Richard G. Ellenbogen, Max Petzold, Yuri Y Varakin, Guilherme Borges, Guohong Jiang, Francis Guillemin, Kyle R. Heuton, Yohannes Kinfu, Victoria F Bachman, Joseph A Wagner, Carlos A Castañeda-Orjuela, Leonardo Trasande, Abbas Ali Mahdi, Josef Coresh, Chuanhua Yu, Kenji Shibuya, Berrin Serdar, Laetitia Huiart, Xiaofeng Liang, Jean de Dieu Ngirabega, Takayoshi Ohkubo, Natalie Stephens, Francis Apolinary Mhimbira, Jefferson Traebert, Amiran Gamkrelidze, Kjetil Søreide, Samath D Dharmaratne, Robert P. Dellavalle, George Mugambage Ruhago, Lakshmi Vijayakumar, Joannie Lortet-Tieulent, Dipan Bose, Tania C Aburto, Saleem M Rana, Miriam Levi, Mohammad Taghi Hedayati, Rodolfo S Pagcatipunan, Ron T. Gansevoort, H. D. Hosgood, Michael Burch, Mohsen Naghavi, Vegard Skirbekk, Ayfer Pekericli, Walter Mendoza, Pengpeng Ye, Gabrielle deVeber, Ali H. Mokdad, David M. Broday, Koranteng Adofo, Zewdie Aderaw Alemu, Shifalika Goenka, Carrie Beth Peterson, Nicolas J. C. Stapelberg, Edson Serván-Mori, Anil Kaul, Foad Abd-Allah, Marek Majdan, Rahul Gupta, Giancarlo Logroscino, Kardiyoloji, Peterson, Carrie B., Laboratoire de Physique des Solides (LPS), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), Wisconsin Division of Public Health, Laboratoire de psychologie sociale et de psychologie cognitive (LAPSCO), Centre National de la Recherche Scientifique (CNRS)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), London South Bank University, Metropolitan Police Service, Hong Kong Baptist University (HKBU), Institut für Informatik [München/Munich] (LMU), Ludwig-Maximilians-Universität München (LMU), Neuroépidémiologie Tropicale (NET), Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM)-CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de Chirurgie Thoracique et Vasculaire - Médecine vasculaire [CHU Limoges], CHU Limoges, Insight Centre for Data Analytics [Galway] (INSIGHT), National University of Ireland [Galway] (NUI Galway), Maladies chroniques, santé perçue, et processus d'adaptation (APEMAC), Université Paris Descartes - Paris 5 (UPD5)-Université de Lorraine (UL), Centre d'Investigation Clinique - Epidemiologie Clinique/essais Cliniques Nancy, Cancéropôle du Grand Est-Institut National de la Santé et de la Recherche Médicale (INSERM), Karolinska Institute, karolinska institute, Department of Molecular Biosciences, Department of Molecular Biosciences [Oslo], Faculty of Mathematics and Natural Sciences [Oslo], University of Oslo (UiO)-University of Oslo (UiO)-Faculty of Mathematics and Natural Sciences [Oslo], University of Oslo (UiO)-University of Oslo (UiO), Centro de Estudios Avanzados en Zonas Aridas (CEAZA), Ecole Polytechnique Fédérale de Lausanne (EPFL), Regional Genetic Service, St Mary's Hospital, Manchester, Laboratoire d'Ingénierie des Matériaux (LIM), Centre National de la Recherche Scientifique (CNRS), Computer Science Department [Bristol], University of Bristol [Bristol], Universität Mannheim [Mannheim], Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Samsung Research &Development Institute India - Bangalore (Groupe Samsung) (SRI-B), Computational Science and Engineering Department [Daresbury] (STFC), Science & Technologie Facilities Council, Multimedia Research Center (MRC), University of Alberta, Division of Biostatistics (Biostat - MINNEAPOLIS), University of Minnesota [Twin Cities], University of Minnesota System-University of Minnesota System, University of Southampton, Imperial College London, Neurology Department, Ichilov Medical Center, Interactions, transferts, ruptures artistiques et culturels - EA 6301 (InTRu), Université de Tours, Institut Jacques Monod (IJM (UMR_7592)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Julius Center for Health Sciences and Primary Care, University Medical Center [Utrecht], Risk Assessment Sciences Institute, Utrecht University [Utrecht], Unité de Biologie Fonctionnelle et Adaptative (BFA (UMR_8251 / U1133)), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Respiratory Epidemiology and Public Health, Imperial College London-Royal Brompton Hospital-National Heart and Lung Institute [UK], CIBER de Epidemiología y Salud Pública (CIBERESP), STAR laboratory, Stanford University [Stanford], Unité de recherche Virologie et Immunologie Moléculaires (VIM), Institut National de la Recherche Agronomique (INRA), Tennent Institute of Ophthalmology, National University of Singapore (NUS), Centre de Robotique (CAOR), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Multidisciplinary Nanotechnology Centre, Swansea University, Cyprus International Institute for the Environment and Public Health, Harvard School of Public Health, Genomics Research Center, Academia Sinica, Neuro Rehab Services LLP [New Delhi], Department of Signal Theory and Communications (TSC), Univ. Politec. de Catalunya, King‘s College London, Dept. Mat. Engn. De Ma, Sao Carlos, Fed. Univ. Sao Carlos UFSCar, RESPEC (RESPEC), RESPEC, Advanced Laboratories on Embedded Systems [Roma] (ALES), Department of Biology [Miami], University of Miami [Coral Gables], Health Care, Minister Of Labour-Ministry of Labor, Health and Social Affairs, Department of Nephrology, University Medical Center, University of Groningen, Division of Human Nutrition, Wageningen University and Research Centre [Wageningen] (WUR), Spatial Ecology and Epidemiology Group, University of Oxford [Oxford], College of Medicine, University of Hail, Saudi Arabia, Laboratory of Neurologic Diseases, Mario Negri Institute, Milan, Department of Civil Engineering [Hamirpur], National Institute of Technology [Hamirpur], GEMMA — Environmental Engineering and Microbiology Research Group, Department of Hydraulic, Maritime and Environmental Engineering, Universitat Politècnica de Catalunya [Barcelona] (UPC), Department of Biosciences and Nutrition, Karolinska Institutet [Stockholm], Institut National de Recherche et d'Analyse Physico-Chimique (INRAP), Institut National de Recherche et d'Analyse Physico-chimique (Ariana, Tunisie) (INRAP), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Technologie de Belfort-Montbeliard (UTBM), Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences [Tehran] (SBUMS), Shahid Beheshti University-Shahid Beheshti University, Center for Applied Medical Research (CIMA), University of Tehran, Secretariat of the Pacific Community, Public Health Division, Sociétés, Acteurs, Gouvernement en Europe (SAGE), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), College of Precision Instrument and Optoelectronics Engineering, Tianjin University, George Washington University (GW), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale (SESSTIM - U912 INSERM - Aix Marseille Univ - IRD), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Universiteit Gent [Ghent], Washington State University (WSU), Laboratoire de Physique de l'ENS Lyon (Phys-ENS), École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées, School of Computer Science - China University of Geosciences (China University of Geosciences (East Area)), Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Université Catholique de Louvain (UCL), Fachbereich Physik [Berlin], Freie Universität Berlin, Div Cyclotron & Radiopharmaceut Sci (DRDO, INMAS), Univ New Delhi, School of Physics and Astronomy, University of St Andrews [Scotland], University of Cape Town, Department of Neuroscience, Department of Computer Science and Engineering [Daejeon] (Chungnam National University), Lawrence University, Gastroenterology & Hepatology, Tata Research Development and Design Center (TRDDC), TCS Innovation Labs, University of Helsinki, Google Inc [Mountain View], Research at Google, Swedish Defense Research Agency (FOI), Servicio de Neurologia (SANTIAGO - Neurologie), Universidad del Desarrollo, Novartis Pharmaceutical Corporation, Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble [1985-2015] (OSUG [1985-2015]), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Department of Mechanical and Automation Engineering (CAD Laboratory), The Chinese University of Hong Kong [Hong Kong], Università degli studi di Bari, Department of Health and Human Services, National Institutes of Health [Bethesda] (NIH), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), College of Information and Electrical Engineering [Beijing] (CIEE), China Agricultural University (CAU), Thales Research and Technology [Palaiseau], THALES, Department of Rheumatology and Connective Tissue Diseases, Medical University of Lublin, Barts and The London School of Medicine and Dentistry, Queen Mary University of London (QMUL), Centre d'économie de la Sorbonne (CES), Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Paris School of Economics (PSE), École supérieure du professorat et de l'éducation - Académie de Grenoble [2013-2019] (ESPE Grenoble [2013-2019]), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Department of Mathematics, University of Iowa [Iowa City], College of Medicine, Alfaisal University, Saudi Ministry of Health, Institut national des recherches agricoles du Bénin, Centre de Recherches agricoles du Sud, Departments of Epidemiology and Nutrition, Unit of Human Nutrition, Agricultural University of Athens, Department of Animal Science, Pennsylvania State University (Penn State), Penn State System-Penn State System, University of Virginia, University of Virginia [Charlottesville], Epidemiology and Biostatistics Unit, Institute for Maternal and Child Health - IRCCS ‘‘Burlo Garofolo', Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Division of Cardiovascular Medicine and Channing Division of Network Medicine, Brigham and Women's Hospital [Boston], American University of Beirut [Beyrouth] (AUB), Department of Chemistry, Scientific Computing Research Unit, Department of dermatology, Milano University-Azienda Ospedaleria Ospedali Riuniti di Bergamo, Mailman School of Public Health, Columbia University [New York], The Georges Institute for International Health, The University of Sydney, Department of epidemiology and Public Health, Faculty of Medicine, Département Optique (OPT), Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT), Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Universitat Pompeu Fabra [Barcelona], Center for Research in Environmental Epidemiology (CREAL), Universitat Pompeu Fabra [Barcelona]-Catalunya ministerio de salud, Nutriments Lipidiques et Prévention des Maladies Métaboliques, Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA)-Université de la Méditerranée - Aix-Marseille 2, Department of Neurology Lunds University Hospital Lund, Unit of Functional Bionanomaterials, School of Biosciences, University of Birmingham [Birmingham], Electrical Engineering and Computer Science Department - Case Western Reserve University, Case Western Reserve University [Cleveland], World Health Organization, Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO), Nordic School of Public Health, The James Hutton Institute, Horia Hulubei National Institute for Physics and Nuclear Engineering, Department of Pediatrics, University of Washington [Seattle], Institute of Public Health, Department of Physics, Clarendon Laboratory, Center for TeleInFrastruktur (CTIF), Aalborg University [Denmark] (AAU), Physikalisches Institut [Freiburg], Albert-Ludwigs-Universität Freiburg, Savoirs, Textes, Langage (STL) - UMR 8163 (STL), Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Dept.of Computer Science, Indian Institute of Technology Madras (IIT Madras), Istituto Mario Negri Bergamo, Centro Ricerche e Trapianti Villa Camozzi, Universidade Estadual Paulista Júlio de Mesquita Filho [São José do Rio Preto] (UNESP), Laboratoire de Génie Informatique et Ingénierie de Production (LGI2P), IMT - MINES ALES (IMT - MINES ALES), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Institut geològic de Catalunya (IGC), Institut Geològic de Catalunya-IGC, Institut Cochin (IC UM3 (UMR 8104 / U1016)), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physiologie et Génomique des Poissons (LPGP), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Institut National de la Recherche Agronomique (INRA), Politecnico di Milano [Milan] (POLIMI), Symantec, University of Oviedo, European Microsoft Innovation Center (EMIC), Microsoft Corporation [Redmond, Wash.], Technion - Israel Institute of Technology [Haifa], Laboratoire de Mécanique, Physique et Géosciences (LMPG), Université Le Havre Normandie (ULH), Normandie Université (NU)-Normandie Université (NU), Department of Physics, Cavendish Laboratory, University of Cambridge [UK] (CAM), Laboratoire de Probabilités et Modèles Aléatoires (LPMA), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Pierre et Marie Curie - Paris 6 (UPMC), Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Departments of Applied Physics [New Haven], Yale University [New Haven], Center for Mathematical Modeling (CMM), Department of Global Health and Development, London School of Hygiene and Tropical Medicine (LSHTM), University of Occupational and Environmental Health [Kitakyushu] (UEOH), Department of Computer Science and Engineering [New Delhi], Indian Institute of Technology Delhi (IIT Delhi), Institut de Recherche sur les Phénomènes Hors Equilibre (IRPHE), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), GlaxoSmithKline, Imperial College London-Clinical Imaging Center, Universidade Federal de Pernambuco [Recife] (UFPE), Maclean Building, Benson Lane, Crowmarsh Gifford, Centre for Ecology and Hydrology, Nanoscience Institute (NEST), Dipartimento di Fisica, Università di Pisa, Aristotle University of Thessaloniki, Laboratory Of Immune Cell Biology (LICB), JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), Institute of Human Genetics, Rheinische Friedrich-Wilhelms-Universität Bonn, Laboratorio Nacional de Computação Cientifica [Rio de Janeiro] (LNCC / MCT), Occupational Health Unit, Bologna University Hospital-Sant'Orsola-Malpighi Polyclinic, Royal Institute of Technology [Stockholm] (KTH ), NICTA [Eveleigh], National ICT Australia [Sydney] (NICTA), Division of Solid Mechanics, Lund University [Lund], University of Calgary, BioWare Corp, Manchester Academic Health Sciences Centre, Institut d'Histoire et de Philosophie des Sciences et des Techniques (IHPST), Université Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS)-Département d'Etudes Cognitives - ENS Paris (DEC), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Ghent University [Belgium] (UGENT), Imaging Sciences and Biomedical Engineering Division [London], Guy's and St Thomas' Hospital [London]-King‘s College London, Children’s Hospital of Philadelphia (CHOP ), Perelman School of Medicine, University of Pennsylvania [Philadelphia], Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique (LHEEA), École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche en Génie Civil et Mécanique (GeM), Université de Nantes - Faculté des Sciences et des Techniques, Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Department of Physiology, Augusta University - Medical College of Georgia, University System of Georgia (USG)-University System of Georgia (USG), Neurorestoration Group, Wolfson Centre for Age-related Diseases-King‘s College London, Electronic Navigation Research Institute (ENRI), Ministry of Land, Infrastructure, Transport and Tourism, Department of Computer Science [KAIST] (CS), Korea Advanced Institute of Science and Technology (KAIST), Centre for Undergraduate Studies, University of the Punjab, Siemens Corporate Research, Siemens AG [Munich], University of Massachusetts [Boston] (UMass Boston), University of Massachusetts System (UMASS), Department of Materials Science, Sichuan University [Chengdu] (SCU), Natl Engn Res Ctr Vegetables, Key Lab Biol & Genet Improvement Hort Crops N Chi, Beijing Acad Agr & Forestry Sci, University Hospital Puerta de Hierro, Madrid, Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University (PSL), Université de Franche-Comté (UFC)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Université de Technologie de Belfort-Montbeliard (UTBM), Shahid Beheshti University of Medical Sciences, École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), MOLTECH-ANJOU (MOLTECH-ANJOU), Université d'Angers (UA)-Centre National de la Recherche Scientifique (CNRS), Universidad de Santiago de Chile [Santiago] (USACH)-Universidad del Desarrollo, Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS), École supérieure du professorat et de l'éducation - Académie de Grenoble (ESPE Grenoble), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Grenoble Alpes (UGA), California Institute of Technology (CALTECH)-NASA, Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Sud - Paris 11 (UP11), Université de la Méditerranée - Aix-Marseille 2-Institut National de la Recherche Agronomique (INRA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Lille-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Universidad de Santiago de Chile [Santiago] (USACH), École normale supérieure - Paris (ENS Paris)-École normale supérieure - Paris (ENS Paris), King‘s College London-Wolfson Centre for Age-related Diseases, Sichuan University, Universitat de Barcelona, Interne Geneeskunde, Medische Sociologie, MUMC+: MA Psychiatrie (3), MUMC+: Hersen en Zenuw Centrum (3), Psychiatrie & Neuropsychologie, CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM), Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019] (Grenoble INP [2007-2019])-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut Mines-Télécom [Paris] (IMT)-Télécom Bretagne-Université européenne de Bretagne - European University of Brittany (UEB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5)-Centre National de la Recherche Scientifique (CNRS), Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), RS: MHeNs - R2 - Mental Health, Laboratoire de Physique des Solides ( LPS ), Université Paris-Sud - Paris 11 ( UP11 ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de psychologie sociale et de psychologie cognitive ( LAPSCO ), Université Blaise Pascal - Clermont-Ferrand 2 ( UBP ) -Centre National de la Recherche Scientifique ( CNRS ), Erosion torrentielle neige et avalanches ( UR ETGR ), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture ( IRSTEA ), Hong Kong Baptist University ( HKBU ), Institut für Informatik [München/Munich] ( LMU ), Ludwig-Maximilians-Universität München, Neuroépidémiologie Tropicale ( NET ), CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Institut Génomique, Environnement, Immunité, Santé, Thérapeutique ( GEIST ), Université de Limoges ( UNILIM ) -Université de Limoges ( UNILIM ), Insight Centre for Data Analytics (National University of Ireland Galway (NUIG)) ( INSIGHT ), Maladies chroniques, santé perçue, et processus d'adaptation ( APEMAC ), Université Paris Descartes - Paris 5 ( UPD5 ) -Université de Lorraine ( UL ), Cancéropôle du Grand Est-Institut National de la Santé et de la Recherche Médicale ( INSERM ), University of Oslo ( UiO ) -University of Oslo ( UiO ), Centro de Estudios Avanzados en Zonas Aridas ( CEAZA ), Ecole Polytechnique Fédérale de Lausanne ( EPFL ), Laboratoire d'Ingénierie des Matériaux ( LIM ), Centre National de la Recherche Scientifique ( CNRS ), Lawrence Berkeley National Laboratory [Berkeley] ( LBNL ), Samsung Research &Development Institute India - Bangalore (Groupe Samsung) ( SRI-B ), Computational Science and Engineering Department [Daresbury] ( STFC ), Multimedia Research Center ( MRC ), University of Alberta [Edmonton], Division of Biostatistics ( Biostat - MINNEAPOLIS ), University of Minnesota [Minneapolis], University of Southampton [Southampton], Interactions, transferts, ruptures artistiques et culturels - EA 6301 ( InTRu ), Institut Jacques Monod ( IJM ), Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), University Medical Center Utrecht, Biologie Fonctionnelle et Adaptative ( BFA ), Imperial College London-Royal Brompton Hospital-National Heart and Lung Institute, Unité de recherche Virologie et Immunologie Moléculaires ( VIM ), Institut National de la Recherche Agronomique ( INRA ), National University of Singapore ( NUS ), Centre de Robotique ( CAOR ), MINES ParisTech - École nationale supérieure des mines de Paris-PSL Research University ( PSL ), Department of Signal Theory and Communications ( TSC ), RESPEC ( RESPEC ), Advanced Laboratories on Embedded Systems [Roma] ( ALES ), Wageningen University and Research Centre [Wageningen] ( WUR ), Universitat Politècnica de Catalunya [Barcelona] ( UPC ), Institut National de Recherche et d'Analyse Physico-Chimique ( INRAP ), Institut National de Recherche et d'Analyse Physico-chimique (INRAP-Tunisie), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) ( FEMTO-ST ), Université de Franche-Comté ( UFC ) -Centre National de la Recherche Scientifique ( CNRS ) -Ecole Nationale Supérieure de Mécanique et des Microtechniques ( ENSMM ) -Université de Technologie de Belfort-Montbeliard ( UTBM ), Tehran University, Sociétés, Acteurs, Gouvernement en Europe ( SAGE ), Université de Strasbourg ( UNISTRA ) -Centre National de la Recherche Scientifique ( CNRS ), Sciences Economiques et Sociales de la Santé & Traitement de l'Information Médicale ( SESSTIM - U912 INSERM - AMU - IRD ), Institut de Recherche pour le Développement ( IRD ) -Aix Marseille Université ( AMU ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Washington State University ( WSU ), Laboratoire de Physique de l'ENS Lyon ( Phys-ENS ), École normale supérieure - Lyon ( ENS Lyon ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ), Institut des Sciences Chimiques de Rennes ( ISCR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Ecole Nationale Supérieure de Chimie de Rennes-Institut National des Sciences Appliquées ( INSA ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de recherche en informatique de Toulouse ( IRIT ), Institut National Polytechnique [Toulouse] ( INP ) -Université Toulouse 1 Capitole ( UT1 ) -Université Toulouse - Jean Jaurès ( UT2J ) -Université Toulouse III - Paul Sabatier ( UPS ), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique ( CNRS ), Centre de Recherche en Automatique de Nancy ( CRAN ), Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ), Université Catholique de Louvain ( UCL ), Freie Universität Berlin [Berlin], Div Cyclotron & Radiopharmaceut Sci ( DRDO, INMAS ), Institut de Physique Nucléaire d'Orsay ( IPNO ), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Centre National de la Recherche Scientifique ( CNRS ), Tata Research Development and Design Center ( TRDDC ), Laboratoire MOLTECH-Anjou [Angers] ( MOLTECH ANJOU ), Université d'Angers ( UA ) -Centre National de la Recherche Scientifique ( CNRS ), University of Helsinki [Helsinki], Swedish Defense Research Agency ( FOI ), Servicio de Neurologia ( SANTIAGO - Neurologie ), Universidad de Santiago de Chile [Santiago] ( USACH ) -Universidad del Desarrollo, Novartis Pharmaceutical Corp., East Hanover NJ 07936, USA, Laboratoire de glaciologie et géophysique de l'environnement ( LGGE ), Observatoire des Sciences de l'Univers de Grenoble ( OSUG ), Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Université Joseph Fourier - Grenoble 1 ( UJF ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Grenoble Alpes ( UGA ) -Centre National de la Recherche Scientifique ( CNRS ), Department of Mechanical and Automation Engineering ( CAD Laboratory ), National Institutes of Health ( NIH ), Centre d'étude et de recherche en informatique et communications ( CEDRIC ), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise ( ENSIIE ) -Conservatoire National des Arts et Métiers [CNAM] ( CNAM ), Heuristique et Diagnostic des Systèmes Complexes [Compiègne] ( Heudiasyc ), Université de Technologie de Compiègne ( UTC ) -Centre National de la Recherche Scientifique ( CNRS ), College of Information and Electrical Engineering [Beijing] ( CIEE ), China Agricultural University ( CAU ), Queen Mary University of London ( QMUL ), Centre d'économie de la Sorbonne ( CES ), Université Panthéon-Sorbonne ( UP1 ) -Centre National de la Recherche Scientifique ( CNRS ), Paris School of Economics ( PSE ), École supérieure du professorat et de l'éducation - Académie de Grenoble ( ESPE Grenoble ), Université Savoie Mont Blanc ( USMB [Université de Savoie] [Université de Chambéry] ) -Université Grenoble Alpes ( UGA ), PennState University [Pennsylvania] ( PSU ), Jet Propulsion Laboratory ( JPL ), NASA-California Institute of Technology ( CALTECH ), American University of Beirut [Beyrouth], The University of Sydney [Sydney], Département Optique ( OPT ), Université européenne de Bretagne ( UEB ) -Télécom Bretagne-Institut Mines-Télécom [Paris], Laboratoire des signaux et systèmes ( L2S ), Université Paris-Sud - Paris 11 ( UP11 ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ), Center for Research in Environmental Epidemiology ( CREAL ), Université de la Méditerranée - Aix-Marseille 2-Institut National de la Recherche Agronomique ( INRA ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Center for TeleInFrastruktur ( CTIF ), Aalborg University [Denmark] ( AAU ), Savoirs, Textes, Langage (STL) - UMR 8163 ( STL ), Université de Lille-Centre National de la Recherche Scientifique ( CNRS ), Indian Institute of Technology Madras ( IIT Madras ), Universidade Estadual Paulista Júlio de Mesquita ( UNESP ), Laboratoire de Génie Informatique et Ingénierie de Production ( LGI2P ), IMT - Mines Alès Ecole Mines - Télécom ( IMT - MINES ALES ), Institut geològic de Catalunya ( IGC ), Institut Cochin ( UM3 (UMR 8104 / U1016) ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de Physiologie et Génomique des Poissons ( LPGP ), Institut National de la Recherche Agronomique ( INRA ) -Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Politecnico di Milano [Milan], European Microsoft Innovation Center ( EMIC ), Laboratoire de Mécanique, Physique et Géosciences ( LMPG ), Université Le Havre Normandie ( ULH ), Normandie Université ( NU ) -Normandie Université ( NU ), University of Cambridge [UK] ( CAM ), Laboratoire de Probabilités et Modèles Aléatoires ( LPMA ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de Génétique et de Biologie Moléculaire et Cellulaire ( IGBMC ), Université de Strasbourg ( UNISTRA ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Center for Mathematical Modeling ( CMM ), Universidad de Santiago de Chile [Santiago] ( USACH ), London School of Hygiene and Tropical Medicine ( LSHTM ), University of Occupational and Environmental Health [Kitakyushu] ( UEOH ), Indian Institute of Technology Delhi ( IIT Delhi ), Institut de Recherche sur les Phénomènes Hors Equilibre ( IRPHE ), Aix Marseille Université ( AMU ) -Ecole Centrale de Marseille ( ECM ) -Centre National de la Recherche Scientifique ( CNRS ), Universidade Federal de Pernambuco [Recife] ( UFPE ), Nanoscience Institute ( NEST ), Laboratory Of Immune Cell Biology ( LICB ), JRC Institute for Environment and Sustainability ( IES ), European Commission - Joint Research Centre [Ispra] ( JRC ), Bonn Universität [Bonn], Laboratorio Nacional de Computação Cientifica [Rio de Janeiro] ( LNCC / MCT ), Royal Institute of Technology [Stockholm] ( KTH ), National ICT Australia [Sydney] ( NICTA ), Institut d'Histoire et de Philosophie des Sciences et des Techniques ( IHPST ), Université Panthéon-Sorbonne ( UP1 ) -Département d'Etudes Cognitives - ENS Paris ( DEC ), École normale supérieure - Paris ( ENS Paris ) -École normale supérieure - Paris ( ENS Paris ) -Centre National de la Recherche Scientifique ( CNRS ), Ghent University [Belgium] ( UGENT ), Children’s Hospital of Philadelphia ( CHOP ), Univeristy of Pennsylvania Medical School, Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique ( LHEEA ), École Centrale de Nantes ( ECN ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de Recherche en Génie Civil et Mécanique ( GeM ), Université de Nantes ( UN ) -École Centrale de Nantes ( ECN ) -Centre National de la Recherche Scientifique ( CNRS ), Medical College of Georgia, Electronic Navigation Research Institute ( ENRI ), Department of Computer Science [KAIST] ( CS ), Korea Advanced Institute of Science and Technology ( KAIST ), Laboratoire de l'Accélérateur Linéaire ( LAL ), University of Massachusetts [Boston] ( UMass Boston ), Forouzanfar, Mohammad H, Alexander, Lily, Anderson, H. Ro, Bachman, Victoria F, Biryukov, Stan, Brauer, Michael, Burnett, Richard, Casey, Daniel, Coates, Matthew M, Cohen, Aaron, Delwiche, Kristen, Estep, Kara, Frostad, Joseph J, Kc, Astha, Kyu, Hmwe H, Moradi Lakeh, Maziar, Ng, Marie, Slepak, Erica Leigh, Thomas, Bernadette A, Wagner, Joseph, Aasvang, Gunn Marit, Abbafati, Cristiana, Ozgoren, Ayse Abbasoglu, Abd Allah, Foad, Abera, Semaw F, Aboyans, Victor, Abraham, Biju, Abraham, Jerry Puthenpurakal, Abubakar, Ibrahim, Abu Rmeileh, Niveen M. E, Aburto, Tania C, Achoki, Tom, Adelekan, Ademola, Adofo, Koranteng, Adou, Arsène K, Adsuar, José C, Afshin, Ashkan, Agardh, Emilie E, Al Khabouri, Mazin J, Al Lami, Faris H, Alam, Sayed Saidul, Alasfoor, Deena, Albittar, Mohammed I, Alegretti, Miguel A, Aleman, Alicia V, Alemu, Zewdie A, Alfonso Cristancho, Rafael, Alhabib, Samia, Ali, Raghib, Ali, Mohammed K, Alla, Françoi, Allebeck, Peter, Allen, Peter J, Alsharif, Ubai, Alvarez, Elena, Alvis Guzman, Nelson, Amankwaa, Adansi A, Amare, Azmeraw T, Ameh, Emmanuel A, Ameli, Omid, Amini, Heresh, Ammar, Walid, Anderson, Benjamin O, Antonio, Carl Abelardo T, Anwari, Palwasha, Cunningham, Solveig Argeseanu, Arnlöv, Johan, Arsenijevic, Valentina S. Arsic, Artaman, Al, Asghar, Rana J, Assadi, Reza, Atkins, Lydia S, Atkinson, Charle, Avila, Marco A, Awuah, Baffour, Badawi, Alaa, Bahit, Maria C, Bakfalouni, Talal, Balakrishnan, Kalpana, Balalla, Shivanthi, Balu, Ravi Kumar, Banerjee, Amitava, Barber, Ryan M, Barker Collo, Suzanne L, Barquera, Simon, Barregard, Lar, Barrero, Lope H, Barrientos Gutierrez, Tonatiuh, Basto Abreu, Ana C, Basu, Arindam, Basu, Sanjay, Basulaiman, Mohammed O, Ruvalcaba, Carolina Bati, Beardsley, Justin, Bedi, Neeraj, Bekele, Tolesa, Bell, Michelle L, Benjet, Corina, Bennett, Derrick A, Benzian, Habib, Bernabé, Eduardo, Beyene, Tariku J, Bhala, Neeraj, Bhalla, Ashish, Bhutta, Zulfiqar A, Bikbov, Bori, Abdulhak, Aref A. Bin, Blore, Jed D, Blyth, Fiona M, Bohensky, Megan A, Başara, Berrak Bora, Borges, Guilherme, Bornstein, Natan M, Bose, Dipan, Boufous, Soufiane, Bourne, Rupert R, Brainin, Michael, Brazinova, Alexandra, Breitborde, Nicholas J, Brenner, Hermann, Briggs, Adam D. 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Venkat, Neupane, Sudan P., Newton, Charles R., Ngalesoni, Frida N., Ngirabega, Jean De Dieu, Nguyen, Nhung T., Nieuwenhuijsen, Mark J., Nisar, Muhammad I., Nogueira, José R., Nolla, Joan M., Norheim, Ole F., Norman, Rosana E., Oh, In-Hwan, Olusanya, Bolajoko O., Omer, Saad B., Pagcatipunan, Rodolfo S., Pain, Amanda W., Pandian, Jeyaraj D., Panelo, Carlo Irwin A., Park, Eun-Kee, Parry, Charles D., Paternina Caicedo, Angel J., Patten, Scott B., Paul, Vinod K., Pavlin, Boris I., Pedraza, Lilia S., Pejin Stokic, Ljiljana, Pereira, David M., Perez-Padilla, Rogelio, Perez-Ruiz, Fernando, Perry, Samuel A.L., Phillips, Michael R., Polanczyk, Guilherme V., Pond, Constance D., Prasad, Noela M., Qato, Dima M., Quezada, Amado D., Quistberg, D. Alex A., Rahimi-Movaghar, Vafa, Ur Rahman, Sajjad, Rana, Saleem M., Refaat, Amany H., Ribeiro, Antonio L., Riccio, Patricia M., Rojas-Rueda, David, Ruhago, George M., Sacco, Ralph L., Salomon, Joshua A., Sampson, Uchechukwu K., Sanabria, Juan R., Sánchez-Pimienta, Tania G., Sanchez-Riera, Lidia, Santos, Itamar S., Saunders, James E., Saylan, Mete I., Schmidt, Jürgen C., Schneider, Ione J.C., Schwebel, David C., Scott, James G., Sepanlou, Sadaf G., Servan-Mori, Edson E., Shamah Levy, Teresa, Shin, Hwashin H., Sigfusdottir, Inga D., Silberberg, Donald H., Simard, Edgar P., Singh, Gitanjali M., Singh, Jasvinder A., Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Stapelberg, Nicolas J.C., Stein, Dan J., Stein, Murray B., Sunguya, Bruno F., Sykes, Bryan L., Tabb, Karen M., Talongwa, Roberto T., Te Ao, Braden J., Teixeira, Carolina M., Téllez Rojo, Martha M., Terkawi, Abdullah S., Texcalac-Sangrador, José Lui, Thackway, Sarah V., Thorne-Lyman, Andrew L., Thrift, Amanda G., Thurston, George D., Towbin, Jeffrey A., Tran, Bach X., Tsala Dimbuene, Zacharie, Uchendu, Uche S., Ukwaja, Kingsley N., Uzun, Selen B., Van De Vijver, Steven, Van Gool, Coen H., Van Os, Jim, Varakin, Yuri Y., Vasankari, Tommi J., Vasconcelos, Ana Maria N., Vavilala, Monica S., Veerman, Lennert J., Velasquez-Melendez, Gustavo, Venketasubramanian, N., Violante, Francesco S., Victorovich Vlassov, Vasiliy, Wagner, Gregory R., Waller, Stephen G., Wallin, Mitchell T., Warouw, Tati S., Watts, Charlotte H., Weintraub, Robert G., Whiteford, Harvey A., Wilkinson, James D., Williams, Hywel C., Williams, Thomas N., Woldeyohannes, Solomon M., Wolfe, Charles D.A., Wong, John Q., Woolf, Anthony D., Wright, Jonathan L., Yan, Lijing L., Yentür, Gökalp K., Yoon, Seok-Jun, Younis, Mustafa Z., Zaki, Maysaa E., Zunt, Joseph R., Lopez, Alan D., and Temesgen, A.M.
Subjects: Male, Fine particulate matter, Nutrition and Disease, MESH : Sanitation, Health Behavior, Diseases, MESH: Metabolic Diseases, MESH: Global Health, 030204 cardiovascular system & hematology, MESH: Risk Assessment, Global Health, MESH : Nutritional Status, MESH: Occupational Exposure, 0302 clinical medicine, Unsafe Sex, MESH: Risk Factors, Risk Factors, Voeding en Ziekte, Medicine, Air-pollution, MESH : Female, 030212 general & internal medicine, MESH : Risk Assessment, Sanitation, Wasting, 2. Zero hunger, Factors de risc en les malalties, Medicine (all), [ SDV.SPEE ] Life Sciences [q-bio]/Santé publique et épidémiologie, Public Health, Global Health, Social Medicine and Epidemiology, General Medicine, MESH : Occupational Diseases, MESH: Nutritional Status, All-cause mortality, MESH : Risk Factors, humanities, Environmental Exposure, Female, Humans, Metabolic Diseases, Nutritional Status, Occupational Diseases, Occupational Exposure, Risk Assessment, Tobacco smoking, 3. Good health, Nutritional Statu, MESH : Occupational Exposure, MESH : Metabolic Diseases, Cohort, medicine.symptom, Risk assessment, Blood-pressure, Human, MESH: Occupational Diseases, Risk factors in diseases, Coronary-heart-disease, MESH : Male, MESH: Health Behavior, MESH: Environmental Exposure, Population health, Body-mass index, 03 medical and health sciences, Household cooking, Cardiovascular-disease, Environmental health, General & Internal Medicine, parasitic diseases, Life Science, MESH: Sanitation, Risk factor, MESH : Health Behavior, VLAG, GBD2013, MESH: Humans, business.industry, Risk Factor, Global Burden of Disease Study, 79 behavioural, environmental and occupational, and metabolic risks, Long-term exposure, MESH : Humans, CAUSE-SPECIFIC MORTALITY, MESH: Male, Metabolic Disease, Occupational Disease, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, MALE BRITISH DOCTORS, Years of potential life lost, Relative risk, Malalties, MESH : Global Health, OUTDOOR AIR-POLLUTION, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, MESH : Environmental Exposure, MESH: Female
Abstract: Summary Background The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian metaregression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5−89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks. Funding Bill & Melinda Gates Foundation. Background The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the fi rst of a series of annual updates of the GBD. Risk factor quantifi cation, particularly of modifi able risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk–outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990–2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the fi rst level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular fi ltration rate. For most risks, data for exposure were synthesised with a Bayesian metaregression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8–58·5) of deaths and 41·6% (40·1–43·0) of DALYs. Risks quantified account for 87·9% (86·5−89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks. Funding Bill & Melinda Gates Foundation.
Published: 2015
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30. Obesity and Associated Comorbidities in People and Companion Animals: A One Health Perspective

Author: Solveig A. Cunningham, E.M. Lund, Michael J. Day, R. Naramore, Alpa V. Patel, C. Khanna, and M. Chandler
Subjects: 0301 basic medicine, Gerontology, Pathology, medicine.medical_specialty, obesity, 040301 veterinary sciences, Psychological intervention, cat, Comorbidity, Cat Diseases, Pathology and Forensic Medicine, 0403 veterinary science, 03 medical and health sciences, Dogs, Risk Factors, Neoplasms, Health care, Prevalence, Medicine, Animals, Humans, human, Dog Diseases, Obesity, One Health, Risk factor, Socioeconomic status, General Veterinary, business.industry, Type 2 Diabetes Mellitus, 04 agricultural and veterinary sciences, Pets, medicine.disease, 030104 developmental biology, Diabetes Mellitus, Type 2, dog, Cats, business
Abstract: This article reviews the biology, prevalence and risks for obesity in people and companion dogs and cats, and explores the links between obesity and diabetes mellitus and cancer across these species. Obesity is a major healthcare problem in both human and veterinary medicine and there is an increasing prevalence of obesity in people and pets. In people and animals, obesity is a complex disorder involving diet, level of physical activity, behavioural factors, socioeconomic factors, environment exposures, genetics, metabolism and the microbiome. Pets and people share a number of obesity-related comorbidities. Obesity is a major risk factor for type 2 diabetes mellitus in people and in cats, but this association is not recognized in dogs. Obesity is a recognized risk factor for a number of human cancers, but there are fewer data available describing this association with canine neoplastic disease. One approach to addressing the problem of obesity is by taking a 'One Health' perspective. Comparative clinical research examining shared lifestyle and environmental risk factors and the reasons underlying species differences should provide new perspectives on the fundamental biology of obesity. One Health programmes involving human healthcare professionals and veterinarians could help address obesity with simple interventions at the community level.
Published: 2017
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31. Participation in a National Lifestyle Change Program is associated with improved diabetes Control outcomes

Author: Anne Tomolo, Sandra E. Safo, Qi Long, Venkat Narayan, Darin E. Olson, Usha Ramakrishnan, Solveig A. Cunningham, Lawrence S. Phillips, Lisa R. Staimez, Sandra L. Jackson, and Mary K. Rhee
Subjects: Gerontology, Male, Endocrinology, Diabetes and Metabolism, Veterans Health, 030209 endocrinology & metabolism, Weight Reduction Program, Article, Body Mass Index, Diabetes Complications, 03 medical and health sciences, 0302 clinical medicine, Endocrinology, Weight loss, Diabetes mellitus, Preventive Health Services, Internal Medicine, medicine, Diabetes Mellitus, Humans, 030212 general & internal medicine, Longitudinal Studies, skin and connective tissue diseases, Socioeconomic status, Life Style, Aged, Retrospective Studies, Veterans, business.industry, Incidence, Middle Aged, medicine.disease, Clinical trial, Weight Reduction Programs, Diabetes control, Treatment Outcome, Charlson comorbidity index, Lifestyle change, Female, sense organs, medicine.symptom, Patient Participation, business, Risk Reduction Behavior
Abstract: Clinical trials show lifestyle change programs are beneficial, yet large-scale, successful translation of these programs is scarce. We investigated the association between participation in the largest U.S. lifestyle change program, MOVE!, and diabetes control outcomes.This longitudinal, retrospective cohort study used Veterans Health Administration databases of patients with diabetes who participated in MOVE! between 2005 and 2012, or met eligibility criteria (BMI ≥25kg/mThere were 400,170 eligible patients with diabetes, including 87,366 (22%) MOVE!Included patients were 96% male, 77% white, with mean age 58years and BMI 34kg/mIf able to overcome participation challenges, lifestyle change programs in U.S. health systems may improve health among the growing patient population with diabetes.
Published: 2017

32. Entrenched obesity in childhood: findings from a national cohort study

Author: Ashlesha Datar, K.M. Venkat Narayan, Solveig A. Cunningham, and Michael R. Kramer
Subjects: Gerontology, Male, Pediatrics, medicine.medical_specialty, Longitudinal study, Pediatric Obesity, Adolescent, Epidemiology, 030209 endocrinology & metabolism, School entry, Overweight, Article, National cohort, Body Mass Index, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, medicine, Humans, 030212 general & internal medicine, Early childhood, Longitudinal Studies, Prospective Studies, Child, Socioeconomic status, Schools, business.industry, Incidence, Anthropometry, medicine.disease, Obesity, United States, Social Class, Socioeconomic Factors, Child, Preschool, Female, medicine.symptom, business
Abstract: Purpose Given the high levels of obesity among U.S. children, we examine whether obesity in childhood is a passing phenomenon or remains entrenched into adolescence. Methods Data are from the prospective nationally representative Early Childhood Longitudinal Study, Kindergarten Class of 1998–1999 (analytic sample = 6600). Anthropometrics were measured six times during 1998–2007. Overweight and obesity were defined using CDC cut-points. Entrenched obesity was defined as obesity between ages 5–9 coupled with persistent obesity at ages 11 and 14. Results Almost 30% of children experienced obesity at some point between ages 5.6 and 14.1 years; 63% of children who ever had obesity between ages 5.6 and 9.1 and 72% of those who had obesity at kindergarten entry experienced entrenched obesity. Children with severe obesity in kindergarten or who had obesity at more than 1 year during early elementary were very likely to experience obesity through age 14, regardless of their sex, race, or socioeconomic backgrounds. Conclusions Prevention should focus on early childhood, as obesity at school entry is not often a passing phenomenon. Even one timepoint of obesity measured during the early elementary school years may be an indicator of risk for long-term obesity.
Published: 2016

33. Globalization and Food Prestige among Indian Adolescents

Author: Amanda Maxfield, Solveig A. Cunningham, and Shailaja S Patil
Subjects: 0301 basic medicine, Male, Cognitive anthropology, Internationality, Adolescent, Medicine (miscellaneous), Developing country, India, Models, Psychological, Food Supply, 03 medical and health sciences, Globalization, Food Preferences, 0302 clinical medicine, Cultural models, Food supply, Cluster Analysis, Humans, 030212 general & internal medicine, Cooking, Self report, Developing Countries, Anthropology, Cultural, Qualitative Research, Family Characteristics, 030109 nutrition & dietetics, Ecology, Prestige, Diet, Vegetarian, Advertising, General Medicine, Diet, Socioeconomic Factors, Adolescent Behavior, Fast Foods, Female, Television, Self Report, Psychology, Food Science, Qualitative research
Abstract: This study provides a foundation for understanding how globalization and changing food environments are linked to cultural models of food prestige in adolescents. We used methods from cognitive anthropology, including free lists, pile sorts, and consensus modeling, to explore the meanings that Indian adolescents attribute to foods. Adolescents (n = 29) were asked to free list foods eaten outside and inside the home. Different adolescents (n = 65) were asked to pile sort and rank 30 foods identified during the free lists according to which foods are the most prestigious, traditional, routine, and advertised on television. We found that adolescents overwhelmingly believed nontraditional foods to be the most prestigious. Nonlocal foods, both from foreign countries and other regions of India, as well as foods eaten outside the home, were also considered prestigious.
Published: 2016

34. Reduced Cardiovascular Disease Incidence With a National Lifestyle Change Program

Author: Lisa R. Staimez, Sandra E. Safo, Venkat Narayan, Mary K. Rhee, Solveig A. Cunningham, Anne Tomolo, Lawrence S. Phillips, Sandra L. Jackson, Qi Long, Darin E. Olson, Usha Ramakrishnan, Sociology, and Interface Demography
Subjects: Adult, Male, medicine.medical_specialty, Epidemiology, Veterans Health, Disease, 030204 cardiovascular system & hematology, Overweight, Article, Coronary artery disease, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine, Humans, 030212 general & internal medicine, Life Style, Retrospective Studies, business.industry, Vascular disease, Incidence (epidemiology), Incidence, Hazard ratio, Public Health, Environmental and Occupational Health, Retrospective cohort study, Middle Aged, medicine.disease, United States, Weight Reduction Programs, United States Department of Veterans Affairs, Cardiovascular Diseases, Heart failure, Physical therapy, Female, medicine.symptom, business
Abstract: Introduction Lifestyle change programs implemented within healthcare systems could reach many Americans, but their impact on cardiovascular disease (CVD) remains unclear. The MOVE! program is the largest lifestyle change program implemented in a healthcare setting in the U.S. This study aimed to determine whether MOVE! participation was associated with reduced CVD incidence. Methods This retrospective cohort study, analyzed in 2013–2015, used national Veterans Health Administration databases to identify MOVE! participants and eligible non-participants for comparison (2005–2012). Patients eligible for MOVE!—obese or overweight with a weight-related health condition, and no baseline CVD—were examined (N=1,463,003). Of these, 169,248 (12%) were MOVE! participants. Patients were 92% male, 76% white, with mean age 52 years and BMI of 32. The main outcome was incidence of CVD (ICD-9 and procedure codes for coronary artery disease, cerebrovascular disease, peripheral vascular disease, and heart failure). Results Adjusting for age, race, sex, BMI, statin use, and baseline comorbidities, over a mean 4.9 years of follow-up, MOVE! participation was associated with lower incidence of total CVD (hazard ratio [HR]=0.83, 95% CI=0.80, 0.86); coronary artery disease (HR=0.81, 95% CI=0.77, 0.86); cerebrovascular disease (HR=0.87, 95% CI=0.82, 0.92); peripheral vascular disease (HR=0.89, 95% CI=0.83, 0.94); and heart failure (HR=0.78, 95% CI=0.74, 0.83). The association between MOVE! participation and CVD incidence remained significant when examined across categories of race/ethnicity, BMI, diabetes, hypertension, smoking status, and statin use. Conclusions Although participation was limited, MOVE! was associated with reduced CVD incidence in a nationwide healthcare setting.
Published: 2016

35. Ominous Reversal of Health Gains in the United States: Time to Rethink Research Priorities?

Author: James Curran, Shivani A. Patel, Solveig A. Cunningham, and K.M. Venkat Narayan
Subjects: Biomedical Research, Cancer prevention, Population statistics, Health Priorities, business.industry, Research, Mortality rate, 010102 general mathematics, General Medicine, Population health, 01 natural sciences, United States, 03 medical and health sciences, 0302 clinical medicine, Homicide, Health care, Internal Medicine, Global health, Life expectancy, Humans, Medicine, 030212 general & internal medicine, 0101 mathematics, business, Demography
Abstract: This commentary describes the recent reversal of health gains in the United States due to increases in midlife mortality rates among many groups. The authors' solution is to equally emphasize resea...
Published: 2019
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36. Childhood Obesity Incidence in the United States: A Systematic Review

Author: Patricia C. Cheung, Michael R. Kramer, Solveig A. Cunningham, and K.M.V. Narayan
Subjects: Male, Pediatrics, medicine.medical_specialty, Pediatric Obesity, Endocrinology, Diabetes and Metabolism, MEDLINE, 030209 endocrinology & metabolism, CINAHL, Disease, Childhood obesity, 03 medical and health sciences, 0302 clinical medicine, medicine, Humans, 030212 general & internal medicine, Child, Nutrition and Dietetics, business.industry, Incidence (epidemiology), Public health, Incidence, Correction, medicine.disease, Obesity, United States, Sample size determination, Pediatrics, Perinatology and Child Health, Female, Public Health, business, Demography
Abstract: This systematic review synthesizes the literature on incidence of obesity during childhood.We searched PubMed, Excerpta Medica database (EMBASE), and Cumulative Index to Nursing and Allied Health Literature (CINAHL), and used the Web of Science tool in June 2015. Studies were included if they were published in English, presented results from primary or secondary analyses, used data about children in the US, provided obesity incidence data on children 0 to 18 years born after 1970, and did not pertain to clinically defined populations (disease, medication use, etc.). Author(s), study year, study design, location, sample size, age, and obesity incidence estimates were abstracted.Nineteen studies were included, three of which used nationally representative data. The median study-specific annual obesity incidences among studies using U.S. Centers for Disease Control and Prevention (CDC) growth charts were 4.0%, 3.2%, and 1.8% for preschool (2.0-4.9 years), school aged (5.0-12.9 years), and adolescence (13.0-18.0 years), respectively. This pattern of declining obesity incidence with age was consistent between and within studies.Studies of childhood obesity in the US indicate declining incidence with age. Childhood obesity prevention efforts should be targeted to ages before obesity onset. Longitudinal data and consistent obesity definitions that correlate with long-term morbidity are needed to better characterize the life history of obesity.
Published: 2015

37. County-level contextual factors associated with diabetes incidence in the United States

Author: Gloria L. Beckles, Linda S. Geiss, Solveig A. Cunningham, Shivani A. Patel, Giuseppina Imperatore, Neil Mehta, and Hui Xie
Subjects: Male, medicine.medical_specialty, Social Determinants of Health, Epidemiology, Prevalence, Article, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Health care, Diabetes Mellitus, medicine, Humans, 030212 general & internal medicine, Social determinants of health, Built Environment, Poverty, Socioeconomic status, Aged, 030505 public health, business.industry, Incidence, Incidence (epidemiology), Health Status Disparities, Middle Aged, United States, Health equity, Socioeconomic Factors, Female, 0305 other medical science, business, Demography
Abstract: Purpose Health and administrative systems are facing spatial clustering in chronic diseases such as diabetes. This study explores how geographic distribution of diabetes in the United States is associated with socioeconomic and built environment characteristics and health-relevant policies. Methods We compiled nationally representative county-level data from multiple data sources. We standardized characteristics to a mean = 0 and a SD = 1 and modeled county-level age-adjusted diagnosed diabetes incidence in 2013 using 2-level hierarchical linear regression. Results Incidence of age-standardized diagnosed diabetes in 2013 varied across U.S. counties (n = 3109), ranging from 310 to 2190 new cases/100,000, with an average of 856.4/100,000. Socioeconomic and health-related characteristics explained ∼42% of the variation in diabetes incidence across counties. After accounting for other characteristics, counties with higher unemployment, higher poverty, and longer commutes had higher incidence rates than counties with lower levels. Counties with more exercise opportunities, access to healthy food, and primary care physicians had fewer diabetes cases. Conclusions Features of the socioeconomic and built environment were associated with diabetes incidence; identifying the salient modifiable features of counties can inform targeted policies to reduce diabetes incidence.
Published: 2018
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38. Global, regional, and national levels of neonatal, infant, and under-5 mortality during 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013

Author: Karen Sliwa, Xiaofeng Liang, Vivekanand Jha, Dorairaj Prabhakaran, Rakhi Dandona, Gonghuan Yang, Xuan Che, Soewarta Kosen, Sergei Petrovich Ermakov, Ted R. Miller, Samath D Dharmaratne, Philimon Gona, Sergey Soshnikov, Atsushi Goto, Costas A. Christophi, Zacharie Tsala Dimbuene, Elena Alvarez, Yanping Wang, Peggy Pei-Chia Chiang, Mohammad H. Forouzanfar, Giancarlo Logroscino, Massimo Cirillo, Knud Juel, Johanna M. Geleijnse, Stefan Ma, Samaya Ismayilova, Karen Fern Greenwell, Michelle L. Bell, Saad B. Omer, Ademola Lukman Adelekan, Joshua A. Salomon, Dhruv S. Kazi, Jed D. Blore, Walid Ammar, Carly E Levitz, Kovin Naidoo, Solveig A. Cunningham, Stephen G. Waller, Anand Dayama, James D. Wilkinson, Vasiliki Stathopoulou, Meghan D. Mooney, Mall Leinsalu, Jonathan R. Carapetis, Paul S. F. Yip, Anders Larsson, Abbas Ali Mahdi, Hideaki Toyoshima, Guohong Jiang, Xia Wan, Chuanhua Yu, Soufiane Boufous, Ivy Shiue, Bulat Idrisov, Qing Lan, Chelsea A. Liddell, Austin E Schumacher, Valeria Caso, Nigel Bruce, Paulo A. Lotufo, Ibrahim Abubakar, Roberto Tchio Talongwa, Luke Nyakarahuka, Edward J Mills, Iuri da Costa Leite, Semaw Ferede Abera, Ana C. Garcia, Ayse Abbasoglu Ozgoren, Matthew M Coates, Konstantinos Stroumpoulis, Bradford D. Gessner, Kebede Deribe, Tommi Vasankari, Logan Sandar, Kenji Shibuya, Karen M. Tabb, Troy Jacobs, Christopher J L Murray, Chakib Nejjari, Katherine T. Lofgren, Melvin Barrientos Marzan, Haidong Wang, Joanna Moschandreas, Raimundas Lunevicius, Nataliya Foigt, Rashmi Gupta, Ziad A. Memish, Victoria Pillay-van Wyk, Randah R. Hamadeh, Azmeraw T. Amare, Lalit Dandona, Uchechukwu K.A. Sampson, Monika Sawhney, Vasiliy Victorovich Vlassov, Farhad Islami, Palwasha Anwari, Mustafa Z. Younis, Amitava Banerjee, Ruben Castro, David O. Carpenter, Karzan Abdulmuhsin Mohammad, Taavi Lai, Yousef Khader, Sara Sheikhbahaei, Atte Meretoja, Zanfina Ademi, Ivo Rakovac, Yang Yang, Hilda L Harb, Daniel Pope, Jun She, Yichong Li, Andrew L. Thorne-Lyman, Adrian Davis, Stein Emil Vollset, Andre Pascal Kengne, Henry Apfel, Mark J. Nieuwenhuijsen, John J. McGrath, Yoshihiro Kokubo, Jonas Minet Kinge, Elisabete Weiderpass, Rajiv Chowdhury, Damian G Hoy, Jürgen C Schmidt, Seyed-Mohammad Fereshtehnejad, Harish Chander Gugnani, Hywel C Williams, Karen Edmond, Peter J. Allen, Marina Shakh-Nazarova, Tom Achoki, Edmond K. Kabagambe, Naohiro Yonemoto, Jun Zhu, Simon I. Hay, Karen J. Courville, Ketevan Goginashvili, Theo Vos, Kim Yun Jin, Kawkab Shishani, Lorenzo Monasta, H. Dean Hosgood, Uʇur Dilmen, Marcella Montico, Shankuan Zhu, Ami R. Moore, Marie Ng, Maigeng Zhou, Hebe N. Gouda, Linh N Bui, Sanjay Basu, Mouhanad Hammami, Mohammad T Mashal, Bryan K. Phillips, Marissa Iannarone, Ronan A Lyons, Young-Ho Khang, Robert G. Weintraub, Luca Ronfani, Daniel Kim, Alanur Çavlin, Ferrán Catalá-López, Ronny Westerman, Maia Kereselidze, Itamar S. Santos, Reza Assadi, Hwashin Hyun Shin, Carolina Maria Teixeira, Berrak Bora Basara, David Rojas-Rueda, Abdullah Sulieman Terkawi, Adansi A. Amankwaa, Nicholas J K Breitborde, Gokalp Kadri Yentur, Kaushalendra Kumar, Daniel Obadare Fijabi, Neeraj Bedi, Robert Quentin Reilly, Ana Maria Nogales Vasconcelos, Scott Weichenthal, Mark A. Green, Selen Begüm Uzun, Mukesh Dherani, Shams Eldin Ali Hassan Khalifa, Majed Asad, Jasvinder A. Singh, Angel J Paternina Caicedo, Eric L. Ding, Jost B. Jonas, Tolesa Bekele, Alan J Thomson, Steven E. Lipshultz, Rosario Cárdenas, Sajjad Ur Rahman, George A. Mensah, Jongmin Lee, Inga Dora Sigfusdottir, Mohammad Yahya Saeedi, Magdalena M. Muszyńska, Ulrich O Mueller, Stephen S Lim, Barthelemy Kuate Defo, Alan D. Lopez, Luciano A. Sposato, G Anil Kumar, Farshad Pourmalek, Zulfiqar A Bhutta, Maysaa El Sayed Zaki, Shiwei Liu, K.M. Venkat Narayan, William Msemburi, Ting Wu Chuang, Zewdie Aderaw Alemu, Saleem M Rana, Mohammad Taghi Hedayati, Mohsen Naghavi, Vegard Skirbekk, Walter Mendoza, Ali H. Mokdad, Yohannes Kinfu, Jean de Dieu Ngirabega, Takayoshi Ohkubo, Parfait Uwaliraye, Tasara T. Mazorodze, Farshad Farzadfar, Rob E. Dorrington, Mohammad A. AlMazroa, R. Kumar, Lesley Rushton, Wang, H, Liddell, Ca, Coates, Mm, Mooney, Md, Levitz, Ce, Schumacher, Ae, Apfel, H, Iannarone, M, Phillips, B, Lofgren, Kt, Sandar, L, Dorrington, Re, Rakovac, I, Jacobs, Ta, Liang, X, Zhou, M, Zhu, J, Yang, G, Wang, Y, Liu, S, Li, Y, Ozgoren, Aa, Abera, Sf, Abubakar, I, Achoki, T, Adelekan, A, Ademi, Z, Alemu, Za, Allen, Pj, Almazroa, Ma, Alvarez, E, Amankwaa, Aa, Amare, At, Ammar, W, Anwari, P, Cunningham, Sa, Asad, Mm, Assadi, R, Banerjee, A, Basu, S, Bedi, N, Bekele, T, Bell, Ml, Bhutta, Z, Blore, J, Basara, Bb, Boufous, S, Breitborde, N, Bruce, Ng, Bui, Ln, Carapetis, Jr, Cárdenas, R, Carpenter, Do, Caso, V, Castro, Re, Catalá Lopéz, F, Cavlin, A, Che, X, Chiang, Pp, Chowdhury, R, Christophi, Ca, Chuang, Tw, Cirillo, Massimo, da Costa Leite, I, Courville, Kj, Dandona, L, Dandona, R, Davis, A, Dayama, A, Deribe, K, Dharmaratne, Sd, Dherani, Mk, Dilmen, U, Ding, El, Edmond, Km, Ermakov, Sp, Farzadfar, F, Fereshtehnejad, Sm, Fijabi, Do, Foigt, N, Forouzanfar, Mh, Garcia, Ac, Geleijnse, Jm, Gessner, Bd, Goginashvili, K, Gona, P, Goto, A, Gouda, Hn, Green, Ma, Greenwell, Kf, Gugnani, Hc, Gupta, R, Hamadeh, Rr, Hammami, M, Harb, Hl, Hay, S, Hedayati, Mt, Hosgood, Hd, Hoy, Dg, Idrisov, Bt, Islami, F, Ismayilova, S, Jha, V, Jiang, G, Jonas, Jb, Juel, K, Kabagambe, Ek, Kazi, D, Kengne, Ap, Kereselidze, M, Khader, Y, Khalifa, Se, Khang, Yh, Kim, D, Kinfu, Y, Kinge, Jm, Kokubo, Y, Kosen, S, Defo, Bk, Kumar, Ga, Kumar, K, Kumar, Rb, Lai, T, Lan, Q, Larsson, A, Lee, Jt, Leinsalu, M, Lim, S, Lipshultz, Se, Logroscino, G, Lotufo, Pa, Lunevicius, R, Lyons, Ra, Ma, S, Mahdi, Aa, Marzan, Mb, Mashal, Mt, Mazorodze, Tt, Mcgrath, Jj, Memish, Za, Mendoza, W, Mensah, Ga, Meretoja, A, Miller, Tr, Mills, Ej, Mohammad, Ka, Mokdad, Ah, Monasta, L, Montico, M, Moore, Ar, Moschandreas, J, Msemburi, Wt, Mueller, Uo, Muszynska, Mm, Naghavi, M, Naidoo, K, Narayan, Kv, Nejjari, C, Ng, M, de Dieu Ngirabega, J, Nieuwenhuijsen, Mj, Nyakarahuka, L, Ohkubo, T, Omer, Sb, Caicedo, Aj, Wyk, Vp, Pope, D, Prabhakaran, D, Rahman, Su, Rana, Sm, Reilly, Rq, Rojas Rueda, D, Ronfani, L, Rushton, L, Saeedi, My, Salomon, J, Sampson, U, Santos, I, Sawhney, M, Schmidt, Jc, Shakh Nazarova, M, She, J, Sheikhbahaei, S, Shibuya, K, Shin, Hh, Shishani, K, Shiue, I, Sigfusdottir, Id, Singh, Ja, Skirbekk, V, Sliwa, K, Soshnikov, S, Sposato, La, Stathopoulou, Vk, Stroumpoulis, K, Tabb, Km, Talongwa, Rt, Teixeira, Cm, Terkawi, A, Thomson, Aj, Thorne Lyman, Al, Toyoshima, H, Dimbuene, Zt, Uwaliraye, P, Uzun, Sb, Vasankari, Tj, Vasconcelos, Am, Vlassov, Vv, Vollset, Se, Vos, T, Waller, S, Wan, X, Weichenthal, S, Weiderpass, E, Weintraub, Rg, Westerman, R, Wilkinson, Jd, Williams, Hc, Yang, Yc, Yentur, Gk, Yip, P, Yonemoto, N, Younis, M, Yu, C, Jin, Ky, El Sayed Zaki, M, Zhu, S, Lopez, Ad, and Murray, C. J.
Subjects: trends, Pediatrics, medicine.medical_specialty, Nutrition and Disease, democracy, Developing country, coverage, VDP::Medisinske fag: 700::Helsefag: 800::Epidemiologi medisinsk og odontologisk statistikk: 803, millennium development goals, Global Health, survival, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, 030225 pediatrics, Voeding en Ziekte, Infant Mortality, Global health, Humans, Organizational Objectives, Medicine, 030212 general & internal medicine, 10. No inequality, VLAG, business.industry, Mortality rate, Infant, Newborn, 1. No poverty, Infant, health, General Medicine, Millennium Development Goals, Infant mortality, maternal education, 3. Good health, Secular variation, Child mortality, Socioeconomic Factors, income countries, Child, Preschool, Child Mortality, developing-countries, VDP::Midical sciences: 700::Health sciences: 800::Epidemiology, medical and dental statistics: 803, International development, business, Demography, child-mortality
Abstract: Summary Background Remarkable financial and political efforts have been focused on the reduction of child mortality during the past few decades. Timely measurements of levels and trends in under-5 mortality are important to assess progress towards the Millennium Development Goal 4 (MDG 4) target of reduction of child mortality by two thirds from 1990 to 2015, and to identify models of success. Methods We generated updated estimates of child mortality in early neonatal (age 0–6 days), late neonatal (7–28 days), postneonatal (29–364 days), childhood (1–4 years), and under-5 (0–4 years) age groups for 188 countries from 1970 to 2013, with more than 29 000 survey, census, vital registration, and sample registration datapoints. We used Gaussian process regression with adjustments for bias and non-sampling error to synthesise the data for under-5 mortality for each country, and a separate model to estimate mortality for more detailed age groups. We used explanatory mixed effects regression models to assess the association between under-5 mortality and income per person, maternal education, HIV child death rates, secular shifts, and other factors. To quantify the contribution of these different factors and birth numbers to the change in numbers of deaths in under-5 age groups from 1990 to 2013, we used Shapley decomposition. We used estimated rates of change between 2000 and 2013 to construct under-5 mortality rate scenarios out to 2030. Findings We estimated that 6·3 million (95% UI 6·0–6·6) children under-5 died in 2013, a 64% reduction from 17·6 million (17·1–18·1) in 1970. In 2013, child mortality rates ranged from 152·5 per 1000 livebirths (130·6–177·4) in Guinea-Bissau to 2·3 (1·8–2·9) per 1000 in Singapore. The annualised rates of change from 1990 to 2013 ranged from −6·8% to 0·1%. 99 of 188 countries, including 43 of 48 countries in sub-Saharan Africa, had faster decreases in child mortality during 2000–13 than during 1990–2000. In 2013, neonatal deaths accounted for 41·6% of under-5 deaths compared with 37·4% in 1990. Compared with 1990, in 2013, rising numbers of births, especially in sub-Saharan Africa, led to 1·4 million more child deaths, and rising income per person and maternal education led to 0·9 million and 2·2 million fewer deaths, respectively. Changes in secular trends led to 4·2 million fewer deaths. Unexplained factors accounted for only −1% of the change in child deaths. In 30 developing countries, decreases since 2000 have been faster than predicted attributable to income, education, and secular shift alone. Interpretation Only 27 developing countries are expected to achieve MDG 4. Decreases since 2000 in under-5 mortality rates are accelerating in many developing countries, especially in sub-Saharan Africa. The Millennium Declaration and increased development assistance for health might have been a factor in faster decreases in some developing countries. Without further accelerated progress, many countries in west and central Africa will still have high levels of under-5 mortality in 2030. Funding Bill & Melinda Gates Foundation, US Agency for International Development.
Published: 2014
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39. School Breakfast Receipt and Obesity among American Fifth- and Eighth-Graders

Author: Sebastian Romano, Nikkil Sudharsanan, and Solveig A. Cunningham
Subjects: Male, 0301 basic medicine, Pediatrics, medicine.medical_specialty, Longitudinal study, Adolescent, education, Weight Gain, Article, Childhood obesity, Odds, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Ethnicity, medicine, Humans, Longitudinal Studies, Obesity, Prospective Studies, 030212 general & internal medicine, Early childhood, Child, Poverty, Socioeconomic status, Breakfast, Schools, 030109 nutrition & dietetics, Nutrition and Dietetics, business.industry, digestive, oral, and skin physiology, Food Services, General Medicine, Odds ratio, medicine.disease, United States, Logistic Models, Socioeconomic Factors, Propensity score matching, Female, Child Nutritional Physiological Phenomena, business, Food Science, Cohort study, Demography
Abstract: Background School breakfast consumption can improve children's nutrition, but the implications of breakfast at school for children's weight remains unclear. Objective The aim of this study was to determine whether receiving breakfast at school is related to changes in children's weight between the fifth and eighth grades, and whether the relationship between school breakfasts and obesity varies for children of different socioeconomic backgrounds. Design This was a longitudinal study of children observed in the fifth and eighth grades. Participants Data are from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99, a nationally representative prospective cohort of children in the United States. The analytic sample consisted of 6,495 children interviewed in the fifth and eighth grades. Main outcome measure Standard thresholds from the Centers for Disease Control and Prevention were used to classify children as not obese or obese based on direct-measured height and weight. Statistical analyses performed Difference-in-difference propensity score matching and fixed-effect logistic regression models were used to estimate the relationship between receipt of school breakfast and change in obesity between the fifth and eighth grades, adjusting for child, household, and school characteristics. Results School breakfast receipt was not associated with a change in obesity status between the fifth and eighth grades for children overall (odds ratio=1.31; P =0.129). In the propensity score model, receiving school breakfasts more than doubled the odds of becoming obese (odds ratio=2.31; P =0.0108) for children from families below the federal poverty line compared with children of similar socioeconomic backgrounds who did not regularly receive school breakfasts. Conclusions School breakfast receipt was not independently related to obesity for most children. Receiving school breakfasts in the fifth grade may be associated with weight gain between the fifth and eighth grades for children from families below the federal poverty line compared with children of similar socioeconomic status who did not receive breakfasts.
Published: 2016
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40. Prenatal development in rural South Africa: relationship between birth weight and access to fathers and grandparents

Author: Solveig A. Cunningham, Irma T. Elo, Kobus Herbst, and Victoria Hosegood
Subjects: Rural Population, History, Pediatrics, family, partnership, Health Services Accessibility, Fathers, South Africa, 0302 clinical medicine, Child Development, Pregnancy, Risk Factors, father, Birth Weight, 030212 general & internal medicine, 050207 economics, Cooperative Behavior, education.field_of_study, 05 social sciences, Infant Welfare, Grandparent, Prenatal Care, Prenatal development, Child, Preschool, Intergenerational Relations, child health, Marital status, Regression Analysis, Female, grandmother, Adult, medicine.medical_specialty, Birth weight, Population, Child Welfare, Article, 03 medical and health sciences, Young Adult, 0502 economics and business, medicine, Humans, education, Demography, Health Services Needs and Demand, Biological Father, business.industry, Infant, Newborn, Infant, Social Support, Health Status Disparities, medicine.disease, Socioeconomic Factors, Multivariate Analysis, Rural area, business
Abstract: Birth weight is an indicator of prenatal development associated with health in infancy and childhood, and may be affected by the family environment experienced by the mother during pregnancy. Using data from KwaZulu-Natal, South Africa, we explore the importance of the mother's access to the father and grandparents of the child during pregnancy. Controlling for household socio-economic indicators and maternal characteristics, the survival and residence of the biological father with the mother are positively associated with birth weight. The type of relationship seems to matter: married women have the heaviest newborns, but co-residence with a non-marital partner is also associated with higher birth weight. Access to the maternal grandmother may also be important: women whose mothers are alive have heavier newborns, but no additional benefit is observed from residing together. Co-residence with any grandparent is not associated with birth weight after controlling for the mother's partnership.
Published: 2010

41. Tackling NCD in LMIC: Achievements and Lessons Learned From the NHLBI—UnitedHealth Global Health Centers of Excellence Program

Author: Michael M. Engelgau, Uchechukwu K. Sampson, Cristina Rabadan-Diehl, Richard Smith, Jaime Miranda, Gerald S. Bloomfield, Deshiree Belis, K.M. Venkat Narayan, Adolfo Rubinstein, Jiang He, Dewan S. Alam, David H. Peters, Yangfeng Wu, Lijing L. Yan, Michael Merson, Manuel Ramirez, Benjamin Caballero, Denis Xavier, Salim Yusuf, Dorairaj Prabhakaran, Sylvester Kimaiyo, Eric Velazquez, Catalina A. Denman, Elsa Cornejo, Jill De Zapien, Cecilia Rosales, J. Jaime Miranda, Robert H. Gilman, Naomi Levitt, Thomas A. Gaziano, Hassen Ghannem, Tiina Laatikainen, Uchechukwu Sampson, Nancy L. Dianis, Tracy L. Wolbach, Gabriela Matta, Laura Gutierrez, Natalia Elorriaga, Rosana Poggio, Vilma Irazola, Lydia Bazzano, Abbas Bhuiya, Abdul Wazed, Alfazal Khan, Ali T. Siddiquee, Anwar Islam, Jahangir A.M. Khan, Jasim Uddin, Khaled Hasan, Masuma A. Khanam, Mohammad Yunus, Muhammad A.H. Chowdhury, Nazratun N. Monalisa, Nurul Alam, Peter K. Streatfield, Shyfuddin Ahmed, Sonia Parvin, Taslim Ali, Louis W. Niessen, Mohammad D. Hossain, Tracey L.P. Koehlmoos, Hilary Standing, Henry Lucas, Sara N. Bleich, Gerard F. Anderson, Antonio J. Trujillo, Andrew J. Mirelman, Jesse Hao, Jing Zhang, Maoyi Tian, Polly Huang, Rong Luo, Weigang Fang, Xian Li, Xiangxian Feng, Zhifang Li, Kelly Deal, Eric Peterson, Elizabeth DeLong, Bo Zhou, Jingpu Shi, Bruce Neal, Stephen Jan, Nicole Li, Stephen McMahon, Jianxin Zhang, Jixin Sun, Paul Elliot, Yi Zhao, Yuhong Zhang, Chen Yao, Ningling Huang Sun, Qide Han, Ruqun Shen, Wenyi Niu, Yanfang Wang, Yang Ke, Yining Huang, Stephen Leeder, Alan Lopez, Ruijuan Zhang, Yan Yu, Ana V. Roman, Carlos Mendoza, Dina Roche, Gabriela Mejicano, Maria A. Cordova, Maria F. Kroker, Meredith Fort, Paola Letona, Rebecca Kanter, Regina Garcia, Sandra Murillo, Violeta Chacon, Rafael Montero, Erika J. Lopez, Liz Peña, Maricruz Castro, Ana L. Dengo, Emilce Ulate, Nadia Alvarado, Josefina Sibrian, Astarte Alegria, Ana M. Gutierrez, Flavia Fontes, Alben Sigamani, Deepak Kamath, Freeda Xavier, K.B. Deepthi, M. Anupama, Nandini Mathu, Nisha George, Pranjali Rahul, Prem Pais, Preeti Girish, Seena Thomas, T. Usha, Tinku Thomas, Rajnish Joshi, N. Chidambaram, Rajeev Gupta, Clara Chow, Janice Pogue, Martin O'Donnell, P.J. Devereaux, Dominic Misquith, Twinkle Agrawal, Farah N. Fathima, Kolli Srinath Reddy, Roopa Shivashankar, Vamadevan S. Ajay, Hassan M. Khan, M. Masood Kadir, Muhammad Q. Masood, Zafar Fatmi, Anand Krishnan, Kavita Singh, Nikhil Tandon, Rajesh Khadgawat, V. Usha Menon, Bipin Kumar Sethi, A.G. Unnikrishnan, Mark L. Hutcheson, Mohammed K. Ali, Solveig A. Cunningham, Shivani A. Patel, Unjali Gujral, Ankush Desai, Deepa Mohan, R. Guha Pradeepa, V. Mohan, Vijay Viswanathan, Rakesh Sahay, Seema Shah, Ganapathi Bantwal, Premlata K. Varthakavi, Manisha Nair, Constantine Akwanalo, David Lagat, Felix Barasa, Myra Koech, Wilson Sugut, Belinda Korir, Priscah Mosol, Shamim Ali, Charles B. Sherman, Jane Carter, Gerald Bloomfield, Cynthia Binanay, Rajesh Vedanthan, A. Bernabé-Ortiz, F. León-Velarde, George D. Smith, Germán Málaga, Héctor H. García, Juan P. Casas, Katherine Sacksteder, Liam Smeeth, Luis Huicho, María Rivera, Raúl Gamboa, Shah Ebrahim, Víctor M. Montori, Robert A. Wise, William Checkley, Gregory B. Diette, Beatrice Nojilana, Buyelwa Majikela-Dlangamandla, Carmelita Sylvester, Johanna Malan, Katherine Murphy, Krisela Steyn, Lindi Van Niekerk, Robert Mash, Thandi Puoane, Grace Kim, Ankur Pandya, Shafika Abrahams-Gessel, Hilary Rhode, Michael Pather, Alvaro R. Andrade, Beatriz Garcia, Carlos Velasco, David Medina, Delia Bravo, Diana Munguia, Eric Bateman, Francisco Castro, Helen Schneider, Ilse Ibarra, Jabulisiwe Zulu, Joel Felix, Karla Tribe, Kirsten Bobrow, Lara Fairall, Naomi Folb, Norma Murillo, Norma Pacheco, Paloma Rodriguez, Paola Navarro, Reyna Flores, Richard Van Zyl Smit, Rosario Meddoza, Sameer Surka, Serena Van Haght, Yanira Hernandez, Lungiswa Tsolekile, Gouider Jeridi, Imed Harrabi, Jihen Maatoug, Lamia Boughammoura, Larbi Chaieb, Nejib Mrizek, Rafika Gaha, Khalifa Limam, Souad Amimi, Karima Gaha, Habib Gamra, Mustafa Al'Absi, Erkki Vartiainen, Cornelius Moore, Debi Spillan, Kristiane Cooper, Megan Mitchell, Ruth Kirby, Yunling Gao, and Emmanuel Aluko
Subjects: Gerontology, Economic growth, Biomedical Research, Epidemiology, media_common.quotation_subject, Developing country, 030204 cardiovascular system & hematology, Global Health, Public-Private Sector Partnerships, Article, 03 medical and health sciences, 0302 clinical medicine, Excellence, Global network, Global health, Humans, Medicine, 030212 general & internal medicine, Developing Countries, media_common, Community and Home Care, business.industry, Academies and Institutes, Achievement, United States, Noncommunicable disease, Lung disease, General partnership, National Heart, Lung, and Blood Institute (U.S.), Cardiology and Cardiovascular Medicine, business, Commons
Abstract: Effectively tackling the growing noncommunicable disease (NCD) burden in low- and middle-income countries (LMIC) is a major challenge. To address research needs in this setting for NCDs, in 2009, National Heart, Lung, and Blood Institute (NHLBI) and UnitedHealth Group (UHG) engaged in a public-private partnership that supported a network of 11 LMIC-based research centers and created the NHLBI-UnitedHealth Global Health Centers of Excellence (COE) Program. The Program’s overall goal was to contribute to reducing the cardiovascular and lung disease burdens by catalyzing in-country research institutions to develop a global network of biomedical research centers. Key elements of the Program included team science and collaborative approaches, developing research and training platforms for future investigators, and creating a data commons. This Program embraced a strategic approach for tackling NCDs in LMICs and will provide capacity for locally driven research efforts that can identify and address priority health issues in specific countries’ settings.HighlightsA public-private partnership created the Program.Forming the Program captured all the elements of team science.The Program used best practices of collaborative science.Research training for future investigators was a high priority.
Published: 2016
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42. Data cleaning: detecting, diagnosing, and editing data abnormalities

Author: Solveig A. Cunningham, Jan Van den Broeck, Kobus Herbst, and Roger Eeckels
Subjects: Research design, Data management, Statistics as Topic, Guidelines as Topic, Ethics, Professional, 03 medical and health sciences, 0302 clinical medicine, Research Methods, Medicine, Humans, 030212 general & internal medicine, Policy Forum, business.industry, Statistics, Reproducibility of Results, General Medicine, Research process, Data science, Clinical trial, Epidemiologic Studies, business, Quality assurance, 030217 neurology & neurosurgery
Abstract: In this policy forum the authors argue that data cleaning is an essential part of the research process, and should be incorporated into study design.
Published: 2005

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