15 results on '"Seiglie, Jacqueline A"'
Search Results
2. Body-mass index and diabetes risk in 57 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 685 616 adults.
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Teufel, Felix, Seiglie, Jacqueline A, Geldsetzer, Pascal, Theilmann, Michaela, Marcus, Maja E, Ebert, Cara, Arboleda, William Andres Lopez, Agoudavi, Kokou, Andall-Brereton, Glennis, Aryal, Krishna K, Bicaba, Brice Wilfried, Brian, Garry, Bovet, Pascal, Dorobantu, Maria, Gurung, Mongal Singh, Guwatudde, David, Houehanou, Corine, Houinato, Dismand, Jorgensen, Jutta M Adelin, and Kagaruki, Gibson B
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DIABETES , *LOW-income countries , *MIDDLE-income countries , *ADULTS , *BLOOD sugar measurement - Abstract
Background: The prevalence of overweight, obesity, and diabetes is rising rapidly in low-income and middle-income countries (LMICs), but there are scant empirical data on the association between body-mass index (BMI) and diabetes in these settings.Methods: In this cross-sectional study, we pooled individual-level data from nationally representative surveys across 57 LMICs. We identified all countries in which a WHO Stepwise Approach to Surveillance (STEPS) survey had been done during a year in which the country fell into an eligible World Bank income group category. For LMICs that did not have a STEPS survey, did not have valid contact information, or declined our request for data, we did a systematic search for survey datasets. Eligible surveys were done during or after 2008; had individual-level data; were done in a low-income, lower-middle-income, or upper-middle-income country; were nationally representative; had a response rate of 50% or higher; contained a diabetes biomarker (either a blood glucose measurement or glycated haemoglobin [HbA1c]); and contained data on height and weight. Diabetes was defined biologically as a fasting plasma glucose concentration of 7·0 mmol/L (126·0 mg/dL) or higher; a random plasma glucose concentration of 11·1 mmol/L (200·0 mg/dL) or higher; or a HbA1c of 6·5% (48·0 mmol/mol) or higher, or by self-reported use of diabetes medication. We included individuals aged 25 years or older with complete data on diabetes status, BMI (defined as normal [18·5-22·9 kg/m2], upper-normal [23·0-24·9 kg/m2], overweight [25·0-29·9 kg/m2], or obese [≥30·0 kg/m2]), sex, and age. Countries were categorised into six geographical regions: Latin America and the Caribbean, Europe and central Asia, east, south, and southeast Asia, sub-Saharan Africa, Middle East and north Africa, and Oceania. We estimated the association between BMI and diabetes risk by multivariable Poisson regression and receiver operating curve analyses, stratified by sex and geographical region.Findings: Our pooled dataset from 58 nationally representative surveys in 57 LMICs included 685 616 individuals. The overall prevalence of overweight was 27·2% (95% CI 26·6-27·8), of obesity was 21·0% (19·6-22·5), and of diabetes was 9·3% (8·4-10·2). In the pooled analysis, a higher risk of diabetes was observed at a BMI of 23 kg/m2 or higher, with a 43% greater risk of diabetes for men and a 41% greater risk for women compared with a BMI of 18·5-22·9 kg/m2. Diabetes risk also increased steeply in individuals aged 35-44 years and in men aged 25-34 years in sub-Saharan Africa. In the stratified analyses, there was considerable regional variability in this association. Optimal BMI thresholds for diabetes screening ranged from 23·8 kg/m2 among men in east, south, and southeast Asia to 28·3 kg/m2 among women in the Middle East and north Africa and in Latin America and the Caribbean.Interpretation: The association between BMI and diabetes risk in LMICs is subject to substantial regional variability. Diabetes risk is greater at lower BMI thresholds and at younger ages than reflected in currently used BMI cutoffs for assessing diabetes risk. These findings offer an important insight to inform context-specific diabetes screening guidelines.Funding: Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program. [ABSTRACT FROM AUTHOR]- Published
- 2021
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3. Incremental Risk of Developing Severe COVID-19 Among Mexican Patients With Diabetes Attributed to Social and Health Care Access Disadvantages.
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Sosa-Rubí, Sandra G., Seiglie, Jacqueline A., Chivardi, Carlos, Manne-Goehler, Jennifer, Meigs, James B., Wexler, Deborah J., Wirtz, Veronika J., Gómez-Dantés, Octavio, and Serván-Mori, Edson
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COVID-19 , *HEALTH services accessibility , *MEXICANS , *PEOPLE with diabetes , *CHRONIC kidney failure - Abstract
Objective: Diabetes is an important risk factor for severe coronavirus disease 2019 (COVID-19), but little is known about the marginal effect of additional risk factors for severe COVID-19 among individuals with diabetes. We tested the hypothesis that sociodemographic, access to health care, and presentation to care characteristics among individuals with diabetes in Mexico confer an additional risk of hospitalization with COVID-19.Research Design and Methods: We conducted a cross-sectional study using public data from the General Directorate of Epidemiology of the Mexican Ministry of Health. We included individuals with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 between 1 March and 31 July 2020. The primary outcome was the predicted probability of hospitalization, inclusive of 8.5% of patients who required intensive care unit admission.Results: Among 373,963 adults with COVID-19, 16.1% (95% CI 16.0-16.3) self-reported diabetes. The predicted probability of hospitalization was 38.4% (37.6-39.2) for patients with diabetes only and 42.9% (42.2-43.7) for patients with diabetes and one or more comorbidities (obesity, hypertension, cardiovascular disease, and chronic kidney disease). High municipality-level of social deprivation and low state-level health care resources were associated with a 9.5% (6.3-12.7) and 17.5% (14.5-20.4) increased probability of hospitalization among patients with diabetes, respectively. In age-, sex-, and comorbidity-adjusted models, living in a context of high social vulnerability and low health care resources was associated with the highest predicted probability of hospitalization.Conclusions: Social vulnerability contributes considerably to the probability of hospitalization among individuals with COVID-19 and diabetes with associated comorbidities. These findings can inform mitigation strategies for populations at the highest risk of severe COVID-19. [ABSTRACT FROM AUTHOR]- Published
- 2021
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4. Diabetes as a Risk Factor for Poor Early Outcomes in Patients Hospitalized With COVID-19.
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Seiglie, Jacqueline, Platt, Jesse, Cromer, Sara Jane, Bunda, Bridget, Foulkes, Andrea S., Bassett, Ingrid V., Hsu, John, Meigs, James B., Leong, Aaron, Putman, Melissa S., Triant, Virginia A., Wexler, Deborah J., and Manne-Goehler, Jennifer
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Objective: Diabetes and obesity are highly prevalent among hospitalized patients with coronavirus disease 2019 (COVID-19), but little is known about their contributions to early COVID-19 outcomes. We tested the hypothesis that diabetes is a risk factor for poor early outcomes, after adjustment for obesity, among a cohort of patients hospitalized with COVID-19.Research Design and Methods: We used data from the Massachusetts General Hospital (MGH) COVID-19 Data Registry of patients hospitalized with COVID-19 between 11 March 2020 and 30 April 2020. Primary outcomes were admission to the intensive care unit (ICU), need for mechanical ventilation, and death within 14 days of presentation to care. Logistic regression models were adjusted for demographic characteristics, obesity, and relevant comorbidities.Results: Among 450 patients, 178 (39.6%) had diabetes-mostly type 2 diabetes. Among patients with diabetes versus patients without diabetes, a higher proportion was admitted to the ICU (42.1% vs. 29.8%, respectively, P = 0.007), required mechanical ventilation (37.1% vs. 23.2%, P = 0.001), and died (15.9% vs. 7.9%, P = 0.009). In multivariable logistic regression models, diabetes was associated with greater odds of ICU admission (odds ratio 1.59 [95% CI 1.01-2.52]), mechanical ventilation (1.97 [1.21-3.20]), and death (2.02 [1.01-4.03]) at 14 days. Obesity was associated with greater odds of ICU admission (2.16 [1.20-3.88]) and mechanical ventilation (2.13 [1.14-4.00]) but not with death.Conclusions: Among hospitalized patients with COVID-19, diabetes was associated with poor early outcomes, after adjustment for obesity. These findings can help inform patient-centered care decision making for people with diabetes at risk for COVID-19. [ABSTRACT FROM AUTHOR]- Published
- 2020
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5. Diabetes Prevalence and Its Relationship With Education, Wealth, and BMI in 29 Low- and Middle-Income Countries.
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Seiglie, Jacqueline A., Marcus, Maja-Emilia, Ebert, Cara, Prodromidis, Nikolaos, Geldsetzer, Pascal, Theilmann, Michaela, Agoudavi, Kokou, Andall-Brereton, Glennis, Aryal, Krishna K., Bicaba, Brice Wilfried, Bovet, Pascal, Brian, Garry, Dorobantu, Maria, Gathecha, Gladwell, Gurung, Mongal Singh, Guwatudde, David, Msaidié, Mohamed, Houehanou, Corine, Houinato, Dismand, and Jorgensen, Jutta Mari Adelin
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MIDDLE-income countries , *DIABETES , *POISSON regression , *HIGH-income countries , *LOW-income countries - Abstract
Objective: Diabetes is a rapidly growing health problem in low- and middle-income countries (LMICs), but empirical data on its prevalence and relationship to socioeconomic status are scarce. We estimated diabetes prevalence and the subset with undiagnosed diabetes in 29 LMICs and evaluated the relationship of education, household wealth, and BMI with diabetes risk.Research Design and Methods: We pooled individual-level data from 29 nationally representative surveys conducted between 2008 and 2016, totaling 588,574 participants aged ≥25 years. Diabetes prevalence and the subset with undiagnosed diabetes was calculated overall and by country, World Bank income group (WBIG), and geographic region. Multivariable Poisson regression models were used to estimate relative risk (RR).Results: Overall, prevalence of diabetes in 29 LMICs was 7.5% (95% CI 7.1-8.0) and of undiagnosed diabetes 4.9% (4.6-5.3). Diabetes prevalence increased with increasing WBIG: countries with low-income economies (LICs) 6.7% (5.5-8.1), lower-middle-income economies (LMIs) 7.1% (6.6-7.6), and upper-middle-income economies (UMIs) 8.2% (7.5-9.0). Compared with no formal education, greater educational attainment was associated with an increased risk of diabetes across WBIGs, after adjusting for BMI (LICs RR 1.47 [95% CI 1.22-1.78], LMIs 1.14 [1.06-1.23], and UMIs 1.28 [1.02-1.61]).Conclusions: Among 29 LMICs, diabetes prevalence was substantial and increased with increasing WBIG. In contrast to the association seen in high-income countries, diabetes risk was highest among those with greater educational attainment, independent of BMI. LMICs included in this analysis may be at an advanced stage in the nutrition transition but with no reversal in the socioeconomic gradient of diabetes risk. [ABSTRACT FROM AUTHOR]- Published
- 2020
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6. Diabetes mellitus as a risk factor for SARS-CoV-2 test positivity in Mexico: A propensity score matched study.
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Seiglie, Jacqueline A., Serván-Mori, Edson, Manne-Goehler, Jennifer, Meigs, James B., Miranda, J. Jaime, Sosa-Rubí, Sandra G., Silverman-Retana, Omar, Wexler, Deborah J., Wirtz, Veronika J., Jaime Miranda, J, and Silverman, Omar
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PROPENSITY score matching , *DIABETES , *PEOPLE with diabetes , *SARS-CoV-2 , *INFECTION - Abstract
Aims: We sought to investigate whether individuals with diabetes have a higher likelihood of testing positive for SARS-CoV-2, as a proxy for infection risk, than individuals without diabetes.Methods: We conducted a cross-sectional study of publicly available data among a Mexican population, totaling 2,314,022 adults ≥ 18 years who underwent SARS-CoV-2 testing between March 1 and December 20, 2020. We used 1:1 nearest neighborhood propensity score matching by diabetes status to account for confounding among those with and without diabetes.Results: In the overall study population, 1,057,779 (45.7%) individuals tested positive for SARS-CoV-2 and 270,486 (11.7%) self-reported diabetes. After propensity score matching, patient characteristics were well-balanced, with 150,487 patients in the diabetes group (mean [SD] age 55.9 [12.7] years; 51.3% women) and 150,487 patients in the no diabetes group (55.5 [13.3] years; 50.3% women). The strictest matching algorithm (1:1 nearest neighbor) showed that compared to individuals without diabetes, having diabetes was associated with 9.0% higher odds of having a positive SARS-CoV-2 test (OR 1.09 [95% CI: 1.08-1.10]).Conclusions: Presence of diabetes was associated with higher odds of testing positive for SARS-CoV-2, which could have important implications for risk mitigation efforts for people with diabetes at risk of SARS-CoV-2 infection. [ABSTRACT FROM AUTHOR]- Published
- 2021
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7. Regional and state-level patterns of type 2 diabetes prevalence in Mexico over the last three decades.
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Seiglie, Jacqueline A., Franco, Roxana Rodriguez, Wirtz, Veronika J., Meigs, James B., Mendoza, Miguel Angel, Miranda, J. Jaime, Gómez-Dantés, Héctor, Lozano, Rafael, Wexler, Deborah J., Serván-Mori, Edson, Rodriguez Franco, Roxana, Angel Mendoza, Miguel, and Jaime Miranda, J
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TYPE 2 diabetes , *GLOBAL burden of disease , *ADULTS , *HUMAN Development Index , *AGE groups - Abstract
Aims: We aimed to characterize and illustrate the regional and state-level change in type 2 diabetes (T2D) prevalence in Mexico between 1990 and 2017.Methods: We conducted an ecological and secondary analysis using data from the Global Burden of Disease study on T2D prevalence of the adult Mexican population. We estimated the absolute increase and annual growth rate of T2D prevalence between 1990 and 2017, stratified by age group and region.Results: Nationally, between 1990 and 2017, the prevalence of T2D in Mexico increased from 9.5% to 14.3%. The highest increase in T2D prevalence was observed in the East and Southcentral regions, with the lowest absolute change in T2D prevalence observed in Northern states. The highest average annual growth rate in T2D prevalence was observed in Southern Mexico, in the three Southern states with the lowest human development index, and among individuals ages 15-49 years across all regions, compared to those 50 years and older.Conclusions: The prevalence of T2D in Mexico has increased substantially over the past three decades, with a clear shift in T2D prevalence from Northern to Southern states and a faster increase occurring in Southern Mexico among younger adults and in areas with lower economic resources. [ABSTRACT FROM AUTHOR]- Published
- 2021
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8. Erratum to "Predictors of health facility readiness for diabetes service delivery in low- and middle-income countries: The case of Bangladesh" [Diabet. Res. Clin. Pract. 169 (2020) 108417].
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Seiglie, Jacqueline A., Serván-Mori, Edson, Begum, Tahmina, Meigs, James B., Wexler, Deborah J., and Wirtz, Veronika J.
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MIDDLE-income countries , *HEALTH facilities , *DIABETES , *FORECASTING , *PREPAREDNESS , *NON-communicable diseases - Published
- 2021
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9. Predictors of health facility readiness for diabetes service delivery in low- and middle-income countries: The case of Bangladesh.
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Seiglie, Jacqueline A., Serván-Mori, Edson, Begum, Tahmina, Meigs, James B., Wexler, Deborah J., and Wirtz, Veronika J.
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LOW-income countries , *HEALTH facilities , *PREPAREDNESS , *DIABETES , *DIAGNOSTIC equipment - Abstract
Aims: We aimed to evaluate the readiness and predictors of diabetes service capability at the level of primary care in Bangladesh as an illustrative instance of readiness for diabetes care in low- and middle-income countries (LMICs).Methods: We used data from the 2014 Bangladesh Health Facility Survey (BHFS), a cross-sectional, nationally representative survey (n = 1596 health facilities). We constructed a diabetes-specific readiness index to assess diabetes service readiness in facilities with outpatient capability and used multivariable regression analysis to evaluate contextual predictors of diabetes service readiness.Results: Three-hundred and forty-five facilities with outpatient and diabetes service capability were included. Mean readiness for diabetes service capability on a scale of 0-100 was 24.9 (95%CI: 20.8-28.9) and was lowest in rural settings, districts with high social deprivation, and public facilities, where diabetes diagnostic equipment and medications were largely unavailable. Facility type was the strongest, independent predictor of diabetes service readiness.Conclusions: Diabetes service readiness in outpatient facilities in Bangladesh was low, particularly in public facilities, rural settings, and districts with high social deprivation. .These findings could inform policies aimed at improving diabetes care in areas of high unmet need and may serve as a model to assess diabetes service readiness in other LMICs. [ABSTRACT FROM AUTHOR]- Published
- 2020
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10. Visceral Adiposity and Severe COVID-19 Disease: Application of an Artificial Intelligence Algorithm to Improve Clinical Risk Prediction.
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Goehler, Alexander, Hsu, Tzu-Ming Harry, Seiglie, Jacqueline A, Siedner, Mark J, Lo, Janet, Triant, Virginia, Hsu, John, Foulkes, Andrea, Bassett, Ingrid, Khorasani, Ramin, Wexler, Deborah J, Szolovits, Peter, Meigs, James B, and Manne-Goehler, Jennifer
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COVID-19 , *ARTIFICIAL intelligence , *COMPUTED tomography , *MEDICAL protocols , *OBESITY - Abstract
Background Obesity has been linked to severe clinical outcomes among people who are hospitalized with coronavirus disease 2019 (COVID-19). We tested the hypothesis that visceral adipose tissue (VAT) is associated with severe outcomes in patients hospitalized with COVID-19, independent of body mass index (BMI). Methods We analyzed data from the Massachusetts General Hospital COVID-19 Data Registry, which included patients admitted with polymerase chain reaction–confirmed severe acute respiratory syndrome coronavirus 2 infection from March 11 to May 4, 2020. We used a validated, fully automated artificial intelligence (AI) algorithm to quantify VAT from computed tomography (CT) scans during or before the hospital admission. VAT quantification took an average of 2 ± 0.5 seconds per patient. We dichotomized VAT as high and low at a threshold of ≥100 cm2 and used Kaplan-Meier curves and Cox proportional hazards regression to assess the relationship between VAT and death or intubation over 28 days, adjusting for age, sex, race, BMI, and diabetes status. Results A total of 378 participants had CT imaging. Kaplan-Meier curves showed that participants with high VAT had a greater risk of the outcome compared with those with low VAT (P < .005), especially in those with BMI <30 kg/m2 (P < .005). In multivariable models, the adjusted hazard ratio (aHR) for high vs low VAT was unchanged (aHR, 1.97; 95% CI, 1.24–3.09), whereas BMI was no longer significant (aHR for obese vs normal BMI, 1.14; 95% CI, 0.71–1.82). Conclusions High VAT is associated with a greater risk of severe disease or death in COVID-19 and can offer more precise information to risk-stratify individuals beyond BMI. AI offers a promising approach to routinely ascertain VAT and improve clinical risk prediction in COVID-19. [ABSTRACT FROM AUTHOR]
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- 2021
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11. Socio-demographic inequalities and excess non-COVID-19 mortality during the COVID-19 pandemic: a data-driven analysis of 1 069 174 death certificates in Mexico.
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Antonio-Villa, Neftali Eduardo, Bello-Chavolla, Omar Yaxmehen, Fermín-Martínez, Carlos A, Aburto, José Manuel, Fernández-Chirino, Luisa, Ramírez-García, Daniel, Pisanty-Alatorre, Julio, González-Díaz, Armando, Vargas-Vázquez, Arsenio, Barquera, Simón, Gutiérrez-Robledo, Luis Miguel, and Seiglie, Jacqueline A
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COVID-19 , *DEATH certificates , *COVID-19 pandemic , *MYOCARDIAL infarction , *SOCIAL marginality , *TYPE 2 diabetes - Abstract
Background: In 2020, Mexico experienced one of the highest rates of excess mortality globally. However, the extent of non-COVID deaths on excess mortality, its regional distribution and the association between socio-demographic inequalities have not been characterized.Methods: We conducted a retrospective municipal and individual-level study using 1 069 174 death certificates to analyse COVID-19 and non-COVID-19 deaths classified by ICD-10 codes. Excess mortality was estimated as the increase in cause-specific mortality in 2020 compared with the average of 2015-2019, disaggregated by primary cause of death, death setting (in-hospital and out-of-hospital) and geographical location. Correlates of individual and municipal non-COVID-19 mortality were assessed using mixed effects logistic regression and negative binomial regression models, respectively.Results: We identified a 51% higher mortality rate (276.11 deaths per 100 000 inhabitants) compared with the 2015-2019 average period, largely attributable to COVID-19. Non-COVID-19 causes comprised one-fifth of excess deaths, with acute myocardial infarction and type 2 diabetes as the two leading non-COVID-19 causes of excess mortality. COVID-19 deaths occurred primarily in-hospital, whereas excess non-COVID-19 deaths occurred in out-of-hospital settings. Municipal-level predictors of non-COVID-19 excess mortality included levels of social security coverage, higher rates of COVID-19 hospitalization and social marginalization. At the individual level, lower educational attainment, blue-collar employment and lack of medical care assistance prior to death were associated with non-COVID-19 deaths.Conclusion: Non-COVID-19 causes of death, largely chronic cardiometabolic conditions, comprised up to one-fifth of excess deaths in Mexico during 2020. Non-COVID-19 excess deaths occurred disproportionately out-of-hospital and were associated with both individual- and municipal-level socio-demographic inequalities. [ABSTRACT FROM AUTHOR]- Published
- 2022
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12. Diabetes-Related Excess Mortality in Mexico: A Comparative Analysis of National Death Registries Between 2017-2019 and 2020.
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Bello-Chavolla, Omar Yaxmehen, Antonio-Villa, Neftali Eduardo, Fermín-Martínez, Carlos A., Fernández-Chirino, Luisa, Vargas-Vázquez, Arsenio, Ramírez-García, Daniel, Basile-Alvarez, Martín Roberto, Hoyos-Lázaro, Ana Elena, Carrillo-Larco, Rodrigo M., Wexler, Deborah J., Manne-Goehler, Jennifer, and Seiglie, Jacqueline A.
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Objective: To estimate diabetes-related mortality in Mexico in 2020 compared with 2017-2019 after the onset of the coronavirus disease 2019 (COVID-19) pandemic.Research Design and Methods: This retrospective, state-level study used national death registries of Mexican adults aged ≥20 years for the 2017-2020 period. Diabetes-related death was defined using ICD-10 codes listing diabetes as the primary cause of death, excluding certificates with COVID-19 as the primary cause of death. Spatial and negative binomial regression models were used to characterize the geographic distribution and sociodemographic and epidemiologic correlates of diabetes-related excess mortality, estimated as increases in diabetes-related mortality in 2020 compared with average 2017-2019 rates.Results: We identified 148,437 diabetes-related deaths in 2020 (177 per 100,000 inhabitants) vs. an average of 101,496 deaths in 2017-2019 (125 per 100,000 inhabitants). In-hospital diabetes-related deaths decreased by 17.8% in 2020 versus 2017-2019, whereas out-of-hospital deaths increased by 89.4%. Most deaths were attributable to type 2 diabetes (130 per 100,000 inhabitants). Compared with 2018-2019 data, hyperglycemic hyperosmolar state and diabetic ketoacidosis were the two contributing causes with the highest increase in mortality (128% and 116% increase, respectively). Diabetes-related excess mortality clustered in southern Mexico and was highest in states with higher social lag, rates of COVID-19 hospitalization, and prevalence of HbA1c ≥7.5%.Conclusions: Diabetes-related deaths increased among Mexican adults by 41.6% in 2020 after the onset of the COVID-19 pandemic, occurred disproportionately outside the hospital, and were largely attributable to type 2 diabetes and hyperglycemic emergencies. Disruptions in diabetes care and strained hospital capacity may have contributed to diabetes-related excess mortality in Mexico during 2020. [ABSTRACT FROM AUTHOR]- Published
- 2022
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13. Assessing the continuum of care for maternal health in Mexico, 1994-2018.
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Serván-Mori, Edson, Heredia-Pi, Ileana, Cerecero García, Diego, Nigenda, Gustavo, Sosa-Rubí, Sandra G., Seiglie, Jacqueline A., and Lozano, Rafael
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MATERNAL health services , *HEALTH services accessibility , *CROSS-sectional method , *POPULATION geography , *HEALTH status indicators , *CONTINUUM of care , *SOCIOECONOMIC factors , *DESCRIPTIVE statistics , *PRENATAL care , *LOGISTIC regression analysis , *WOMEN'S health - Abstract
Objective To describe the temporal and geographical patterns of the continuum of maternal health care in Mexico, as well as the sociodemographic characteristics that affect the likelihood of receiving this care. Methods We conducted a pooled cross-sectional analysis using the 1997, 2009, 2014 and 2018 waves of the National Survey of Demographic Dynamics, collating sociodemographic and obstetric characteristics of 93 745 women aged 12--54 years at last delivery. We defined eight variables along the antenatal--postnatal continuum, both independently and conditionally. We used a pooled fixed-effects multivariable logistic model to determine the likelihood of receiving the continuum of care for various properties. We also mapped the quintiles of adjusted state-level absolute change in continuum of care coverage during 1994--2018. Findings We observed large absolute increases in the proportion of women receiving timely antenatal and postnatal care (from 48.9% to 88.2% and from 39.1% to 68.7%, respectively). In our conditional analysis, we found that the proportion of women receiving adequate antenatal care doubled over this period. We showed that having social security and a higher level of education is positively associated with receiving the continuum of care. We observed the largest relative increases in continuum of care coverage in Chiapas (181.5%) and Durango (160.6%), assigned human development index categories of low and medium, respectively. Conclusion Despite significant progress in coverage of the continuum of maternal health care, disparities remain. While ensuring progress towards achievement of the health-related sustainable development goal, government intervention must also target underserved populations. [ABSTRACT FROM AUTHOR]
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- 2021
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14. Association between country preparedness indicators and quality clinical care for cardiovascular disease risk factors in 44 lower- and middle-income countries: A multicountry analysis of survey data.
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Davies, Justine I., Reddiar, Sumithra Krishnamurthy, Hirschhorn, Lisa R., Ebert, Cara, Marcus, Maja-Emilia, Seiglie, Jacqueline A., Zhumadilov, Zhaxybay, Supiyev, Adil, Sturua, Lela, Silver, Bahendeka K., Sibai, Abla M., Quesnel-Crooks, Sarah, Norov, Bolormaa, Mwangi, Joseph K., Omar, Omar Mwalim, Wong-McClure, Roy, Mayige, Mary T., Martins, Joao S., Lunet, Nuno, and Labadarios, Demetre
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CARDIOVASCULAR diseases risk factors , *MIDDLE-income countries , *BLOOD sugar measurement , *DISEASE risk factors , *NON-communicable diseases - Abstract
Background: Cardiovascular diseases are leading causes of death, globally, and health systems that deliver quality clinical care are needed to manage an increasing number of people with risk factors for these diseases. Indicators of preparedness of countries to manage cardiovascular disease risk factors (CVDRFs) are regularly collected by ministries of health and global health agencies. We aimed to assess whether these indicators are associated with patient receipt of quality clinical care.Methods and Findings: We did a secondary analysis of cross-sectional, nationally representative, individual-patient data from 187,552 people with hypertension (mean age 48.1 years, 53.5% female) living in 43 low- and middle-income countries (LMICs) and 40,795 people with diabetes (mean age 52.2 years, 57.7% female) living in 28 LMICs on progress through cascades of care (condition diagnosed, treated, or controlled) for diabetes or hypertension, to indicate outcomes of provision of quality clinical care. Data were extracted from national-level World Health Organization (WHO) Stepwise Approach to Surveillance (STEPS), or other similar household surveys, conducted between July 2005 and November 2016. We used mixed-effects logistic regression to estimate associations between each quality clinical care outcome and indicators of country development (gross domestic product [GDP] per capita or Human Development Index [HDI]); national capacity for the prevention and control of noncommunicable diseases ('NCD readiness indicators' from surveys done by WHO); health system finance (domestic government expenditure on health [as percentage of GDP], private, and out-of-pocket expenditure on health [both as percentage of current]); and health service readiness (number of physicians, nurses, or hospital beds per 1,000 people) and performance (neonatal mortality rate). All models were adjusted for individual-level predictors including age, sex, and education. In an exploratory analysis, we tested whether national-level data on facility preparedness for diabetes were positively associated with outcomes. Associations were inconsistent between indicators and quality clinical care outcomes. For hypertension, GDP and HDI were both positively associated with each outcome. Of the 33 relationships tested between NCD readiness indicators and outcomes, only two showed a significant positive association: presence of guidelines with being diagnosed (odds ratio [OR], 1.86 [95% CI 1.08-3.21], p = 0.03) and availability of funding with being controlled (OR, 2.26 [95% CI 1.09-4.69], p = 0.03). Hospital beds (OR, 1.14 [95% CI 1.02-1.27], p = 0.02), nurses/midwives (OR, 1.24 [95% CI 1.06-1.44], p = 0.006), and physicians (OR, 1.21 [95% CI 1.11-1.32], p < 0.001) per 1,000 people were positively associated with being diagnosed and, similarly, with being treated; and the number of physicians was additionally associated with being controlled (OR, 1.12 [95% CI 1.01-1.23], p = 0.03). For diabetes, no positive associations were seen between NCD readiness indicators and outcomes. There was no association between country development, health service finance, or health service performance and readiness indicators and any outcome, apart from GDP (OR, 1.70 [95% CI 1.12-2.59], p = 0.01), HDI (OR, 1.21 [95% CI 1.01-1.44], p = 0.04), and number of physicians per 1,000 people (OR, 1.28 [95% CI 1.09-1.51], p = 0.003), which were associated with being diagnosed. Six countries had data on cascades of care and nationwide-level data on facility preparedness. Of the 27 associations tested between facility preparedness indicators and outcomes, the only association that was significant was having metformin available, which was positively associated with treatment (OR, 1.35 [95% CI 1.01-1.81], p = 0.04). The main limitation was use of blood pressure measurement on a single occasion to diagnose hypertension and a single blood glucose measurement to diagnose diabetes.Conclusion: In this study, we observed that indicators of country preparedness to deal with CVDRFs are poor proxies for quality clinical care received by patients for hypertension and diabetes. The major implication is that assessments of countries' preparedness to manage CVDRFs should not rely on proxies; rather, it should involve direct assessment of quality clinical care. [ABSTRACT FROM AUTHOR]- Published
- 2020
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15. Analysis of Attained Height and Diabetes Among 554,122 Adults Across 25 Low- and Middle-Income Countries.
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Teufel, Felix, Geldsetzer, Pascal, Manne-Goehler, Jennifer, Karlsson, Omar, Koncz, Viola, Deckert, Andreas, Theilmann, Michaela, Marcus, Maja-Emilia, Ebert, Cara, Seiglie, Jacqueline A., Agoudavi, Kokou, Andall-Brereton, Glennis, Gathecha, Gladwell, Gurung, Mongal S., Guwatudde, David, Houehanou, Corine, Hwalla, Nahla, Kagaruki, Gibson B., Karki, Khem B., and Labadarios, Demetre
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MIDDLE-income countries , *TYPE 2 diabetes , *DIABETES , *ALTITUDES , *LOW-income countries , *STATURE , *RESEARCH , *CROSS-sectional method , *RESEARCH methodology , *MEDICAL cooperation , *EVALUATION research , *SOCIOECONOMIC factors , *INCOME , *COMPARATIVE studies , *DISEASE prevalence , *RESEARCH funding , *POVERTY ,DEVELOPING countries - Abstract
Objective: The prevalence of type 2 diabetes is rising rapidly in low-income and middle-income countries (LMICs), but the factors driving this rapid increase are not well understood. Adult height, in particular shorter height, has been suggested to contribute to the pathophysiology and epidemiology of diabetes and may inform how adverse environmental conditions in early life affect diabetes risk. We therefore systematically analyzed the association of adult height and diabetes across LMICs, where such conditions are prominent.Research Design and Methods: We pooled individual-level data from nationally representative surveys in LMICs that included anthropometric measurements and diabetes biomarkers. We calculated odds ratios (ORs) for the relationship between attained adult height and diabetes using multilevel mixed-effects logistic regression models. We estimated ORs for the pooled sample, major world regions, and individual countries, in addition to stratifying all analyses by sex. We examined heterogeneity by individual-level characteristics.Results: Our sample included 554,122 individuals across 25 population-based surveys. Average height was 161.7 cm (95% CI 161.2-162.3), and the crude prevalence of diabetes was 7.5% (95% CI 6.9-8.2). We found no relationship between adult height and diabetes across LMICs globally or in most world regions. When stratifying our sample by country and sex, we found an inverse association between adult height and diabetes in 5% of analyses (2 out of 50). Results were robust to alternative model specifications.Conclusions: Adult height is not associated with diabetes across LMICs. Environmental factors in early life reflected in attained adult height likely differ from those predisposing individuals for diabetes. [ABSTRACT FROM AUTHOR]- Published
- 2020
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