Search

India is one of the most rigidly stratified societies in the world, yet little is known about life expectancy disparities in the country. We provide direct estimates of social differences in life expectancy in India using survey data spanning two decades. We show that individuals from the Scheduled Castes and Scheduled Tribes have drastically and persistently lower life expectancies than high‐caste individuals (between 4.2–4.4 years for women and 6.1–7.0 years for men in 2013–2016). While Muslims had a modest life expectancy disadvantage compared to high castes in 1997–2000, this disadvantage has grown substantially over the past 20 years. Mortality disparities between marginalized and privileged social groups are present across the entire life‐course and are increasingly driven by older‐age mortality. Our findings reveal a pressing need for far greater attention to the health of marginalized populations in India. [ABSTRACT FROM AUTHOR]

Background: Effective equity-focused health policy for hypertension in low- and middle-income countries (LMICs) requires an understanding of the condition's current socioeconomic gradients and how these are likely to change in the future as countries develop economically.Objectives: This cross-sectional study aimed to determine how hypertension prevalence in LMICs varies by individuals' education and household wealth, and how these socioeconomic gradients in hypertension prevalence are associated with a country's gross domestic product (GDP) per capita.Methods: We pooled nationally representative household survey data from 76 LMICs. We disaggregated hypertension prevalence by education and household wealth quintile, and used regression analyses to adjust for age and sex.Results: We included 1,211,386 participants in the analysis. Pooling across all countries, hypertension prevalence tended to be similar between education groups and household wealth quintiles. The only world region with a clear positive association of hypertension with education or household wealth quintile was Southeast Asia. Countries with a lower GDP per capita had, on average, a more positive association of hypertension with education and household wealth quintile than countries with a higher GDP per capita, especially in rural areas and among men.Conclusions: Differences in hypertension prevalence between socioeconomic groups were generally small, with even the least educated and least wealthy groups having a substantial hypertension prevalence. Our cross-sectional interaction analyses of GDP per capita with the socioeconomic gradients of hypertension suggest that hypertension may increasingly affect adults in the lowest socioeconomic groups as LMICs develop economically. [ABSTRACT FROM AUTHOR]

Background: Fear over side-effects is one of the main drivers of COVID-19 vaccine hesitancy. A large literature in the behavioral and communication sciences finds that how risks are framed and presented to individuals affects their judgments of its severity. However, it remains unknown whether such framing changes can affect COVID-19 vaccine behavior and be deployed as policy solutions to reduce hesitancy. Methods: We conducted a pre-registered randomized controlled trial among 8998 participants in the United States and the United Kingdom to examine the effects of different ways of framing and presenting vaccine side-effects on individuals' willingness to get vaccinated and their perceptions of vaccine safety. Results: Adding a descriptive risk label ('very low risk') next to the numerical side-effect and providing a comparison to motor-vehicle mortality increased participants' willingness to take the COVID-19 vaccine by 3.0 percentage points (p=0.003) and 2.4 percentage points (p=0.049), respectively. These effects were independent and additive and combining both framing strategies increased willingness to receive the vaccine by 6.1 percentage points (p<0.001). Mechanistically, we find evidence that these framing effects operate by increasing individuals' perceptions of how safe the vaccine is. Conclusions: Low-cost side-effect framing strategies can meaningfully affect vaccine intentions at a population level. [ABSTRACT FROM AUTHOR]

One key objective of the population health sciences is to understand why one social group has different levels of health and well-being compared with another. Whereas several methods have been developed in economics, sociology, demography, and epidemiology to answer these types of questions, a recent method introduced by Jackson and VanderWeele (2018) provided an update to decompositions by anchoring them within causal inference theory. In this paper, we demonstrate how to implement the causal decomposition using Monte Carlo integration and the parametric g-formula. Causal decomposition can help to identify the sources of differences across populations and provide researchers with a way to move beyond estimating inequalities to explaining them and determining what can be done to reduce health disparities. Our implementation approach can easily and flexibly be applied for different types of outcome and explanatory variables without having to derive decomposition equations. We describe the concepts of the approach and the practical steps and considerations needed to implement it. We then walk through a worked example in which we investigate the contribution of smoking to sex differences in mortality in South Korea. For this example, we provide both pseudocode and R code using our package, cfdecomp. Ultimately, we outline how to implement a very general decomposition algorithm that is grounded in counterfactual theory but still easy to apply to a wide range of situations. [ABSTRACT FROM AUTHOR]

Objectives: Vaccine hesitancy is a major hurdle for stopping the COVID-19 pandemic. Recently, fear of vaccine side effects created widespread concern and paused global vaccination efforts. Many studies find that how medical risks are framed and communicated can influence individuals' perceptions and behavior, yet there is little evidence on how the communication of COVID-19 vaccine side-effect risks influences vaccine intentions. The primary objective of our study is to evaluate how the framing of vaccine-side effect risks impacts individuals' vaccine intentions and perceptions of vaccine safety. The study will assess the impact of 3 dimensions of side-effect framing: 1. Qualitative risk labels: Determine whether attaching a qualitative risk label (e.g. adding "very low risk" next to the actual numerical risk) impacts individuals' willingness to take a vaccine and their perceptions of its safety. 2. Comparison groups: Determine how framing side-effect risks in comparison to other causes of mortality (COVID-19 mortality and motor vehicle mortality) impacts individuals' willingness to take a vaccine and their perceptions of its safety. 3. How the comparison risks are presented: Determine whether comparisons to other causes of mortality are presented on an absolute or relative scale impacts individuals' willingness to take a vaccine and their perceptions of its safety. Secondarily, we will also randomize a subset of individuals to receive the "status-quo" framing, where the vaccine side-effect risks are presented like how they were presented in the media. We will then compare vaccine intentions and perceptions of vaccine safety between the status-quo and the pooled intervention group samples to provide some insight into how "harmful" the status-quo framing was. Ultimately, we believe that our results will provide the some of the first experimental evidence on how the communication of COVID-19 vaccine risks may impact the public's willingness to be vaccinated and can inform future efforts to increase vaccination rates.Trial Design: Our study is an online-based randomized controlled trial designed to evaluate the effect of different vaccine side-effect framings on COVID-19 vaccine intentions and perceived safety for a hypothetical COVID-19 vaccine. Using a factorial design, we will experimentally assess the impact of 3 risk framing strategies, varying whether the risk is presented: (1) with a qualitative label, (2) whether the risk is presented with a comparison risk, and (3) for comparison cases, whether the comparison is in absolute or relative terms. We will also randomize a portion of respondents to a status quo framing where the side effect risk mimics the media's communication in early April 2021.Participants: This will be an online study setting. We will use Prolific to recruit participants and host our study on the Gorilla platform. To be eligible, participants must be 18 years old or over (male, female, or other), have current residence in the US or UK, and be able to speak English. Participants will be excluded from the study if they do not meet our inclusion criteria.Intervention and Comparator: Our study content will consist of five pages presented to individuals online. Page 1 will explain the purpose of the study and contain the consent information. Page 2 will contain basic sociodemographic questions, including participants' age, sex, and schooling level. Page 3 will set up the experiment by telling individuals that we will describe a hypothetical new COVID-19 vaccine and that we would like to know how likely they would be to take the vaccine and how safe they think the vaccine is. On this page, we will also encourage individuals to respond truthfully and remind them that their answers are confidential and cannot be linked back to any personal identifying information. Page 4 will be the main experimental slide, where we will present individuals with information on the vaccine, varying how the vaccination risk is communicated based on which experimental framing arm they are randomized to. We will factorially randomize across the following factors in the following order (separately by country). First, we will determine whether individuals are randomized to the status quo framing, or the intervention framings (1500 respondents to the status quo, and 4500 to the intervention). Among those randomized to the intervention framing, we will randomize (equal allocation) whether the side effect is presented without a comparison, with a comparison to COVID-19 mortality, or with a comparison to motor vehicle mortality. We will then factorially randomize (equal allocation) whether the risk is presented with a qualitative risk label or not (e.g. "very low risk"). To ensure that the factors are independent of one another, we will do this by randomizing individuals to the risk labels within strata of the comparison group factor. Lastly, among those randomized to the comparison group, we will factorially randomize whether the risk is presented as an absolute or relative comparison. As previously, we will ensure independence by doing this randomization within strata of comparison group*risk labelling. This entire design is visualized in the full protocol. The experimental text for each arm is: Arm 1: With regards to side effects, so far 8 individuals have developed potentially life-threatening blood clots. This is among the approximately 7 million adults that have received the vaccine so far. Arm 2: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots. Arm 3: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots (very low risk). Arm 4: Text for USA participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots. As a reference, 170 out of every 100,000 unvaccinated Americans died of COVID-19 based on data from the past year. Text for UK participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots. As a reference, 108 out of every 100,000 unvaccinated individuals in the UK died of COVID-19 based on data from the past year. Arm 5: Text for USA participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots. As a reference, this is 1/170th of the risk of COVID-19 mortality among unvaccinated Americans based on data from the past year. Text for UK participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots. As a reference, this is 1/108th of the risk of COVID-19 mortality among unvaccinated individuals in the UK based on data from the past year. Arm 6: Text for USA participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots (very low risk). As a reference, 170 out of every 100,000 unvaccinated Americans died of COVID-19 based on data from the past year. Text for UK participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots (very low risk). As a reference, 108 out of every 100,000 unvaccinated individuals in the UK died of COVID-19 based on data from the past year. Arm 7: Text for USA participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots (very low risk). As a reference, this is 1/170th of the risk of COVID-19 mortality among unvaccinated Americans based on data from the past year. Text for UK participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots (very low risk). As a reference, this is 1/108th of the risk of COVID-19 mortality among unvaccinated individuals in the UK based on data from the past year. Arm 8: Text for USA participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots. As a reference, 12 out of every 100,000 Americans died in a motor vehicle accident based on data from the past year. Text for UK participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots. As a reference, 2.6 out of every 100,000 individuals in the UK died in a motor vehicle accident based on data from the past year. Arm 9: Text for USA participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots. As a reference, this is 1/12th of the risk of dying in a motor vehicle accident based on data from the past year. Text for UK participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots. As a reference, this is almost 1/4th of the risk of dying in a motor vehicle accident based on data from the past year. Arm 10: Text for USA participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots (very low risk). As a reference, 12 out of every 100,000 Americans died in a motor vehicle accident based on data from the past year. Text for UK participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots (very low risk). As a reference, 2.6 out of every 100,000 individuals in the UK died in a motor vehicle accident based on data from the past year. Arm 11: Text for USA participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots (very low risk). As a reference, this is 1/12th of the risk of dying in a motor vehicle accident based on data from the past year. Text for UK participants: With regards to side effects, 1 out of 100,000 vaccinated individuals may develop serious blood clots (very low risk). As a reference, this is nearly 1/4th of the risk of dying in a motor vehicle accident based on data from the past year. The risk information will be presented on a single page along with the two main outcome questions. Lastly, for individuals that reported that they are unlikely or unsure about whether they would take the vaccine, the final page will ask them their reason (question based on a recently published study of COVID-19 vaccine hesitancy).Main Outcomes: Our primary outcome is individuals' willingness to take the hypothetical COVID-19 vaccine. We will measure this outcome by asking, "How likely would you be to take this vaccine?" allowing individuals to choose from a four-point Likert response of "Unlikely, Unsure leaning towards unlikely, Unsure leaning towards likely, Very likely." This outcome variable, including the categories and phrasing, is based on a recently published study on COVID-19 vaccine hesitancy conducted by researchers with the Vaccine Hesitance Project at the London School of Hygiene and Tropical Medicine. Our secondary outcome is individuals' perceived safety of the vaccine. We will assess this outcome by asking individuals, "How safe do you feel this vaccine is?" allowing them to choose answers ranging from 1-10 where 1 is extremely unsafe, and 10 is extremely safe. Both outcomes will be measured at the time of the questionnaire. Participants can take up to 45 min to complete the questions but will not be able to go back and change their responses after submitting their questionnaire.Randomization: Using a web-based randomization algorithm, Gorilla will randomly allocate participants to each of the experimental arms. Gorilla allows for two randomization options - independent randomization of each individual based on a probability draw and balanced randomization, which randomizes without replacement such that among groups of respondents a fixed proportion will end up in each experimental arm. We will use the "balanced randomization" option to ensure that our experimental arms are balanced. Participants will be randomized based on the allocations described above.Blinding: Because Prolific handles the interaction between the study investigators and participants, the participants will be completely anonymous to the study investigators. The outcome measures will be self-reported and submitted anonymously. All persons in the study team will be blinded to the group allocation.Numbers To Be Randomized: We will randomize 6000 participants per country for a total sample of 12000 individuals.Trial Status: The protocol version number is 1.0 and the date is July 14, 2021. Recruitment is expected to begin on 26 July 2021 and end by August 10, 2021.Trial Registration: The study and its outcomes were registered at the German Clinical Trials Register ( www.drks.de ) on July 12th, 2021: # DRKS00025551 .Full Protocol: The full protocol is attached as an additional file, accessible from the Trials website (Full_Protocol_20Jul2021) In the interest of expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol. [ABSTRACT FROM AUTHOR]

OBJECTIVES: To assess in-hospital mortality, length of stay, and costs associated with interhospital fragmentation in 30-day readmissions and to determine whether these associations were more or less pronounced for patients with specific high-prevalence conditions. STUDY DESIGN: Cross-sectional analysis using the Agency for Healthcare Research and Quality's National Readmissions Database for 2013 and 2014. METHODS: All patients 18 years and older with a 30-day readmission in 2014 were included. We assessed if readmission to a hospital different from that of the index admission was associated with in-hospital mortality, length of stay, and costs of readmission, separately by whether the readmission occurred for the same or different major diagnostic category. Patients with 1 of 3 common diagnoses (congestive heart failure [CHF], chronic obstructive pulmonary disease [COPD], or myocardial infarction) were studied for disease-specific trends. The same analyses were performed on 2013 data as a sensitivity analysis. RESULTS: In 2014, among 792,596 patients with a 30-day readmission, 22.2% experienced fragmentation. Compared with patients whose readmission occurred at the index hospital, patients readmitted to a different hospital experienced 20% higher odds of dying in hospital (P = .02 for same diagnosis readmission; P = .03 for different diagnosis readmission), a half-a-day longer length of stay (P < .001 for both same and different diagnosis readmissions), and more than $1000 higher costs (P < .001 for both same and different diagnosis readmissions). For patients with a CHF or COPD index admission, mortality was consistently higher for fragmented readmissions for a different condition. CONCLUSIONS: Fragmented readmissions were associated with higher in-hospital mortality and cost. Clinical variation across conditions warrants further investigation to optimize pre- and postdischarge operations and policy. [ABSTRACT FROM AUTHOR]

Background: Current hypertension guidelines vary substantially in their definition of who should be offered blood pressure-lowering medications. Understanding the effect of guideline choice on the proportion of adults who require treatment is crucial for planning and scaling up hypertension care in low- and middle-income countries.Methods: We extracted cross-sectional data on age, sex, blood pressure, hypertension treatment and diagnosis status, smoking, and body mass index for adults 30 to 70 years of age from nationally representative surveys in 50 low- and middle-income countries (N = 1 037 215). We aimed to determine the effect of hypertension guideline choice on the proportion of adults in need of blood pressure-lowering medications. We considered 4 hypertension guidelines: the 2017 American College of Cardiology/American Heart Association guideline, the commonly used 140/90 mm Hg threshold, the 2016 World Health Organization HEARTS guideline, and the 2019 UK National Institute for Health and Care Excellence guideline.Results: The proportion of adults in need of blood pressure-lowering medications was highest under the American College of Cardiology/American Heart Association, followed by the 140/90 mm Hg, National Institute for Health and Care Excellence, and World Health Organization guidelines (American College of Cardiology/American Heart Association: women, 27.7% [95% CI, 27.2-28.2], men, 35.0% [95% CI, 34.4-35.7]; 140/90 mm Hg: women, 26.1% [95% CI, 25.5-26.6], men, 31.2% [95% CI, 30.6-31.9]; National Institute for Health and Care Excellence: women, 11.8% [95% CI, 11.4-12.1], men, 15.7% [95% CI, 15.3-16.2]; World Health Organization: women, 9.2% [95% CI, 8.9-9.5], men, 11.0% [95% CI, 10.6-11.4]). Individuals who were unaware that they have hypertension were the primary contributor to differences in the proportion needing treatment under different guideline criteria. Differences in the proportion needing blood pressure-lowering medications were largest in the oldest (65-69 years) age group (American College of Cardiology/American Heart Association: women, 60.2% [95% CI, 58.8-61.6], men, 70.1% [95% CI, 68.8-71.3]; World Health Organization: women, 20.1% [95% CI, 18.8-21.3], men, 24.1.0% [95% CI, 22.3-25.9]). For both women and men and across all guidelines, countries in the European and Eastern Mediterranean regions had the highest proportion of adults in need of blood pressure-lowering medicines, whereas the South and Central Americas had the lowest.Conclusions: There was substantial variation in the proportion of adults in need of blood pressure-lowering medications depending on which hypertension guideline was used. Given the great implications of this choice for health system capacity, policy makers will need to carefully consider which guideline they should adopt when scaling up hypertension care in their country. [ABSTRACT FROM AUTHOR]

Previous research has documented intergenerational transmission of human capital from children to parents. Less is known, however, about heterogeneity in this 'upward transmission' in low-resource settings. We examine whether co-resident adult children's education is associated with improved health among older parents in India, using nationally representative data from the 2014 Indian National Sample Survey. Parents of children with tertiary education had a lower probability of reporting poor health than parents of children with less than primary education. The benefits of children's education persisted after controlling for economic factors, suggesting that non-pecuniary pathways—such as health knowledge or skills—may play an important role. The association was more pronounced among economically dependent parents and those living in the North and West regions. Taken together, our results point to a strong positive association between children's education and parental health, the role of non-pecuniary pathways, and the importance of subnational heterogeneity in India. [ABSTRACT FROM AUTHOR]

Background: There is wide variation in coronavirus disease 2019 (COVID-19) case-fatality rates (CFRs) across countries, leading to uncertainty about the true lethality of the disease. A large part of this variation may be due to the ages of individuals who are tested and identified.Objective: To measure the contribution of distortions from the age distributions of confirmed cases to CFRs within and across populations.Design: Cross-sectional demographic study using aggregate data on COVID-19 cases and deaths by age.Setting: Population-based data from China, France, Germany, Italy, the Netherlands, South Korea, Spain, Switzerland, and the United States.Participants: All individuals with confirmed COVID-19, as reported by each country as of 19 April 2020 (n = 1 223 261).Measurements: Age-specific COVID-19 CFRs and age-specific population shares by country.Results: The overall observed CFR varies widely, with the highest rates in Italy (9.3%) and the Netherlands (7.4%) and the lowest rates in South Korea (1.6%) and Germany (0.7%). Adjustment for the age distribution of cases explains 66% of the variation across countries, with a resulting age-standardized median CFR of 1.9%. Among a larger sample of 95 countries, the observed variation in COVID-19 CFRs is 13 times larger than what would be expected on the basis of just differences in the age composition of countries.Limitation: The age-adjusted rates assume that, conditional on age, COVID-19 mortality among diagnosed cases is the same as that among undiagnosed cases and that individuals of all ages are equally susceptible to severe acute respiratory syndrome coronavirus 2 infection.Conclusion: Selective testing and identification of older cases considerably warps estimates of the lethality of COVID-19 within populations and comparisons across countries. Removing age distortions and focusing on differences in age-adjusted case fatality will be essential for accurately comparing countries' performance in caring for patients with COVID-19 and for monitoring the epidemic over time.Primary Funding Source: Alexander von Humboldt Foundation. [ABSTRACT FROM AUTHOR]

There is considerable policy interest in home-based screening campaigns for hypertension in many low- and middle-income countries. However, it is unclear whether such efforts will result in long-term population-level blood pressure improvements without more comprehensive interventions that strengthen the entire hypertension care continuum. Using multiple waves of the South African National Income Dynamics Study and the regression discontinuity design, we evaluated the impact of home-based hypertension screening on two-year change in blood pressure. We found that the home-based screening intervention resulted in important reductions in systolic blood pressure for women and younger men. We did not find evidence of an effect on systolic blood pressure for older men or on diastolic blood pressure for either sex. Our results suggest that home-based hypertension screening may be a promising strategy for reducing high blood pressure in low- and middle- income countries, but additional research and policy efforts are needed to ensure that such strategies have maximum reach and impact. [ABSTRACT FROM AUTHOR]

Background: There are few estimates of the potential gains in adult mortality from population-level improvements in systolic blood pressure (SBP) in a major low-and-middle income country (LMIC). Using nationally representative cohort data from Indonesia-the third most populous LMIC- I estimated the gains in adult life expectancy from improving SBP control among adults ages 40 and above and assessed the benefits among richer and poorer subpopulations.Methods: I used longitudinal data from 10 085 adults ages 40 and above (75 288 person-age observations) enrolled in the 2007 and 2014/15 waves of the Indonesian Family Life Survey. Next, I used Poisson-regression parametric g-formulas to directly estimate age-specific mortality rates under different blood pressure control strategies and constructed period life expectancies using the observed and counterfactual mortality rates.Results: Fully controlling SBP to a population mean of under 125 mmHg was associated with a life expectancy gain at age 40 of 5.3 years [95% confidence interval (CI): 3.2, 7.4] for men and 6.0 years (95% CI: 3.6, 8.4) for women. The gains associated with blood pressure control were similar for both rich and poor subpopulations. The life expectancy gains under scenarios with imperfect blood pressure control and coverage were more modest in size and ranged between 1 and 2.5 years for a large fraction of the scenarios.Conclusions: In Indonesia, elevated SBP carries a large mortality burden, though the results suggest that realistic efforts to address hypertension will likely produce more modest gains in life expectancy. Comparing improvements from different strategies and identifying the most cost-effective ways to introduce and scale up hypertension interventions is a critical focus for both research and policy. [ABSTRACT FROM AUTHOR]

Objectives To estimate the association between socioeconomic status (SES) and adult mortality in Indonesia and determine the contribution of adult behavioral risk factors to SES differences in mortality. Methods Discrete failure-time regression models and period life tables were used to estimate life expectancy at age 30 (e 30) across wealth and consumption groups by sex and urban/rural residence. Results For urban men, e 30 increases by an average of 1.10 years per wealth quartile (p =.014) from 38.7 years (95% confidence interval (CI): 37.4–40.5) in the bottom wealth quartile to 42.1 years (95% CI: 40.3–44.1) in the top quartile; for rural men, e 30 increases by an average of 1.35 years per quartile (p =.007) from 40.6 years (95% CI: 39.2–42.5) in the bottom wealth quartile to 44.3 years (95% CI: 42.4–46.6) in the top quartile. SES differences are smaller for women. Behavioral risk factors are inconsistently patterned across SES and do not explain SES differences in mortality. Discussion The associations between SES and adult life expectancy in Indonesia are moderate when compared with developed countries and are not explained by traditional behavioral risk factors. In a context where behavioral risk factors are inconsistent across SES groups, mortality inequality may be driven by inequalities in health care access or other social factors. [ABSTRACT FROM AUTHOR]

Health-related behaviors are significant contributors to morbidity and mortality in the United States, yet evidence on the underlying causes of the vast within-population variation in behaviors is mixed. While many potential causes of health-related behaviors have been identified—such as schooling, genetics, and environments—little is known on how much of the variation across multiple behaviors is due to a common set of causes. We use three separate datasets on U.S. twins to investigate the degree to which multiple health-related behaviors correlate and can be explained by a common set of factors. We find that aside from smoking and drinking, most behaviors are not strongly correlated among individuals. Based on the results of both within-identical-twins regressions and multivariate behavioral genetics models, we find some evidence that schooling may be related to smoking but not to the covariation between multiple behaviors. Similarly, we find that a large fraction of the variance in each of the behaviors is consistent with genetic factors; however, we do not find strong evidence that a single common set of genes explains variation in multiple behaviors. We find, however, that a large portion of the correlation between smoking and heavy drinking is consistent with common, mostly childhood, environments. This suggests that the initiation and patterns of these two behaviors might arise from a common childhood origin. Research and policy to identify and modify this source may provide a strong way to reduce the population health burden of smoking and heavy drinking. [ABSTRACT FROM AUTHOR]

Background: Diabetes is an important contributor to global morbidity and mortality. The contributions of population aging and macroeconomic changes to the growth in diabetes prevalence over the past 20 years are unclear. Methods: We used cross-sectional data on age- and sex-specific counts of people with diabetes by country, national population estimates, and country-specific macroeconomic variables for the years 1990, 2000, and 2008. Decomposition analysis was performed to quantify the contribution of population aging to the change in global diabetes prevalence between 1990 and 2008. Next, age-standardization was used to estimate the contribution of age composition to differences in diabetes prevalence between high-income (HIC) and low-to-middle-income countries (LMICs). Finally, we used non-parametric correlation and multivariate first-difference regression estimates to examine the relationship between macroeconomic changes and the change in diabetes prevalence between 1990 and 2008. Results: Globally, diabetes prevalence grew by two percentage points between 1990 (7.4 %) and 2008 (9.4 %). Population aging was responsible for 19 % of the growth, with 81 % attributable to increases in the age-specific prevalences. In both LMICs and HICs, about half the growth in age-specific prevalences was from increasing levels of diabetes between ages 45-65 (51 % in HICs and 46 % in LMICs). After age-standardization, the difference in the prevalence of diabetes between LMICs and HICs was larger (1.9 % point difference in 1990; 1.5 % point difference in 2008). We found no evidence that macroeconomic changes were associated with the growth in diabetes prevalence. Conclusions: Population aging explains a minority of the recent growth in global diabetes prevalence. The increase in global diabetes between 1990 and 2008 was primarily due to an increase in the prevalence of diabetes at ages 45-65. We do not find evidence that basic indicators of economic growth, development, globalization, or urbanization were related to rising levels of diabetes between 1990 and 2008. [ABSTRACT FROM AUTHOR]

Background: At the individual level, it is well known that pregnancies have a short-term effect on a woman's cardiovascular system and blood pressure. The long-term effect of having children on maternal blood pressure, however, is unknown. We thus estimated the causal effect of having children on blood pressure among mothers in India, a country with a history of high fertility rates.Methods: We used nationally representative cross-sectional data from the 2015-16 India National Family and Health Survey (NFHS-4). The study population comprised 444 611 mothers aged 15-49 years. We used the sex of the first-born child as an instrumental variable (IV) for the total number of a woman's children. We estimated the effect of an additional child on systolic and diastolic blood pressure in IV (two-stage least squares) regressions. In additional analyses, we stratified the IV regressions by time since a mother last gave birth. Furthermore, we repeated our analyses using mothers' husbands and partners as the regression sample.Results: On average, mothers had 2.7 children [standard deviation (SD): 1.5], a systolic blood pressure of 116.4 mmHg (SD: 14.4) and diastolic blood pressure of 78.5 mmHg (SD: 9.4). One in seven mothers was hypertensive. In conventional ordinary least squares regression, each child was associated with 0.42 mmHg lower systolic [95% confidence interval (CI): -0.46 to -0.39, P < 0.001] and 0.13 mmHg lower diastolic (95% CI: -0.15 to -0.11, P < 0.001) blood pressure. In the IV regressions, each child decreased a mother's systolic blood pressure by an average of 1.00 mmHg (95% CI: -1.26 to -0.74, P < 0.001) and diastolic blood pressure by an average of 0.35 mmHg (95% CI: -0.52 to -0.17, P < 0.001). These decreases were sustained over more than a decade after childbirth, with effect sizes slightly declining as the time since last birth increased. Having children did not influence blood pressure in men.Conclusions: Bearing and rearing a child decreases blood pressure among mothers in India. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Pandemics such as the COVID-19 pandemic and other severe health care disruptions endanger individuals to miss essential care. Machine learning models that predict which patients are at greatest risk of missing care visits can help health administrators prioritize retentions efforts towards patients with the most need. Such approaches may be especially useful for efficiently targeting interventions for health systems overburdened during states of emergency. Methods: We use data on missed health care visits from over 55,500 respondents of the Survey of Health, Ageing and Retirement in Europe (SHARE) COVID-19 surveys (June – August 2020 and June – August 2021) with longitudinal data from waves 1–8 (April 2004 – March 2020). We compare the performance of four machine learning algorithms (stepwise selection, lasso, random forest, and neural networks) to predict missed health care visits during the first COVID-19 survey based on common patient characteristics available to most health care providers. We test the prediction accuracy, sensitivity, and specificity of the selected models for the first COVID-19 survey by employing 5-fold cross-validation, and test the out-of-sample performance of the models by applying them to the data from the second COVID-19 survey. Results: Within our sample, 15.5% of the respondents reported any missed essential health care visit due to the COVID-19 pandemic. All four machine learning methods perform similarly in their predictive power. All models have an area under the curve (AUC) of around 0.61, outperforming random prediction. This performance is sustained for data from the second COVID-19 wave one year later, with an AUC of 0.59 for men and 0.61 for women. When classifying all men (women) with a predicted risk of 0.135 (0.170) or higher as being at risk of missing care, the neural network model correctly identifies 59% (58%) of the individuals with missed care visits, and 57% (58%) of the individuals without missed care visits. As the sensitivity and specificity of the models are strongly related to the risk threshold used to classify individuals, the models can be calibrated depending on users' resource constraints and targeting approach. Conclusions: Pandemics such as COVID-19 require rapid and efficient responses to reduce disruptions in health care. Based on characteristics available to health administrators or insurance providers, simple machine learning algorithms can be used to efficiently target efforts to reduce missed essential care. [ABSTRACT FROM AUTHOR]

Socioeconomic gaps in life expectancy have widened substantially in the United States since 2000. Yet the contribution of specific causes to these growing disparities remains unknown. We used death records from the National Vital Statistics System and population data from Current Population Surveys to quantify the contribution of alcohol-attributable causes of death to changes in US life expectancy between 2000 and 2018 by sex and socioeconomic status (as measured by educational attainment). During the study period, the gap in life expectancy between people with low (high school diploma or less) compared with high (college degree) levels of education increased by three years among men and five years among women. Between 2000 and 2010 declines in cardiovascular disease mortality among people with high education made major contributions to growing inequalities. In contrast, between 2010 and 2018 deaths from a cause with an alcohol-attributable fraction of 20 percent or more were a dominant driver of socioeconomic divergence. Increased efforts to implement cost-effective alcohol control policies will be essential for reducing health disparities. [ABSTRACT FROM AUTHOR]

There is low civil society mobilization for NCD policies in low- and middle-income countries (LMICs) despite a growing NCD burden. While existing research explains low mobilization largely through constraints such as inadequate funding and capacity at the organizational level, we explore the issue from the perspective of people living with NCDs and ask how lay understandings of hypertension may inform potential mobilization for multisectoral policy actions by people living with hypertension. To explore this question, we develop a theoretical framework that casts mobilization as a function of people's recognition of disease importance, attribution of NCD risk factors to government policies, beliefs about who bears responsibility for NCD prevention and management, and beliefs around efficacy of multisectoral policies. We present findings from 45 semi-structured interviews with people living with hypertension in a qualitative study in Chennai, India. Our thematic analysis reveals that respondents can dedicate limited time and resources to actions around hypertension. People living with hypertension also strongly internalize responsibility for developing and managing their condition and focus primarily on achieving lifestyle changes. Instead of demanding multisectoral policy action around hypertension, respondents recommend that government actions focus on measures that enable their lifestyle changes, such as increasing awareness and health care capacities, and express doubts about the efficacy of government policies. Our findings expand existing theories around mobilization by revealing how people's own understanding of their illness, its risk factors and their underlying drivers, as well as their perception of challenges in NCD policy making can present barriers to mobilization around multisectoral policies. Theory on health social movements would benefit from a deeper integration of individual perspectives and a closer consideration of the specific challenges of living with NCDs given the local context. • Individual beliefs among hypertensive adults in Chennai may limit willingness to demand policy action on hypertension. • Limited resources and competing priorities may limit actions on hypertension even if individuals recognize risk factors. • People may struggle to recognize non-communicable disease risk factors and see challenges in policymaking. • Among urban Indian adults, a strong sense of self-responsibility may lead to focus on lifestyle changes. • Disease-specific illness experience and local context inform beliefs and actions. [ABSTRACT FROM AUTHOR]