Rapidly Rising Diabetes and Increasing Body Weight: A Counterfactual Analysis in Repeated Cross-sectional Nationally Representative Data from Bangladesh.

BACKGROUND: Diabetes is a growing concern in South Asia but few nationally representative studies identify factors behind this rising disease burden. We studied the nationwide change in diabetes prevalence in Bangladesh, subpopulations disproportionately affected, and the contribution of rising unhealthy weight to the change in diabetes prevalence. METHODS: Based on a sample of 13,959 adults aged 35 years and older with biomarker measurements from the 2011 and 2017/2018 Bangladesh Demographic and Health Surveys, we estimated how the prevalence of diabetes changed nationally and across socioeconomic/geographic groups. Using counterfactual decomposition, we assessed how much the prevalence of diabetes would have grown if body mass index (BMI) had not changed between 2011 and 2017. RESULTS: Diabetes prevalence increased from 12.1% (11.1, 13.1) to 14.4% (13.3, 15.5) between 2011 and 2017/2018. Diabetes grew disproportionately quickly among population groups with higher household wealth, and more education, and in three regions. Over this same period, mean BMI increased from 20.9 (20.8, 21.1) to 22.5 kg/m 2 (22.4, 22.7) and overweight from 25.8 (24.4, 27.3) to 42.1% (40.4, 43.7). Under the counterfactual scenario of constant BMI, diabetes would have risen by only 1.0 (-0.4, 2.4) instead of 2.3 percentage points (0.8, 3.7) nationally, corresponding to a contribution of 58% (-106.3, 221.7). Similarly, group-specific trends were largely attributable to increasing BMI. CONCLUSIONS: Diabetes prevalence in Bangladesh has increased rapidly between 2011 and 2017/2018. Decomposition analysis estimates have wide confidence intervals but are consistent with the hypothesis that this change was driven by the dramatic rise in body weights.

Does Early Childhood BCG Vaccination Improve Survival to Midlife in a Population With a Low Tuberculosis Prevalence? Quasi-experimental Evidence on Nonspecific Effects From 32 Swedish Birth Cohorts.

The Bacillus Calmette-Guérin (BCG) vaccine for tuberculosis (TB) is widely used globally. Many high-income countries discontinued nationwide vaccination policies starting in the 1980s as the TB prevalence decreased. However, there is continued scientific interest in whether the general childhood immunity boost conferred by the BCG vaccination impacts adult health and mortality in low-TB contexts (known as nonspecific effects). While recent studies have found evidence of an association between BCG vaccination and survival to ages 34-45, it is unclear whether these associations are causal or driven by the unobserved characteristics of those who chose to voluntarily vaccinate. We use the abrupt discontinuation of mandatory BCG vaccination in Sweden in 1975 as a natural experiment to estimate the causal nonspecific effect of the BCG vaccine on cohort survival to midlife. Applying two complementary study designs, we find no evidence that survival to age 40 was affected by the discontinuation of childhood BCG vaccination. The results are consistent among both males and females and are robust to several sensitivity tests. Overall, despite prior correlational studies suggesting large nonspecific effects, we do not find any population-level evidence for a nonspecific effect of the BCG vaccine discontinuation on survival to age 40 in Sweden.

Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: evidence from 55,500 individuals from 28 European countries.

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.

Variation in the Proportion of Adults in Need of Blood Pressure-Lowering Medications by Hypertension Care Guideline in Low- and Middle-Income Countries: A Cross-Sectional Study of 1 037 215 Individuals From 50 Nationally Representative Surveys.

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.

Sex differences in the mortality rate for coronavirus disease 2019 compared to other causes of death: an analysis of population-wide data from 63 countries.

Men are more likely than women to die due to coronavirus disease 2019 (COVID-19). An open question is whether these sex differences reflect men's generally poorer health and lower life expectancy compared to women of similar ages or if men face a unique COVID-19 disadvantage. Using age-specific data on COVID-19 mortality as well as cause-specific and all-cause mortality for 63 countries, we compared the sex difference in COVID-19 mortality to sex differences in all-cause mortality and mortality from other common causes of death to determine the magnitude of the excess male mortality disadvantage for COVID-19. We found that sex differences in the age-standardized COVID-19 mortality rate were substantially larger than for the age-standardized all-cause mortality rate and mortality rate for most other common causes of death. The excess male mortality disadvantage for COVID-19 was especially large in the oldest age groups. Our findings suggest that the causal pathways that link male sex to a higher mortality from a SARS-CoV-2 infection may be specific to SARS-CoV-2, rather than shared with the pathways responsible for the shorter life expectancy among men or sex differences for other common causes of death. Understanding these causal chains could assist in the development of therapeutics and preventive measures for COVID-19 and, possibly, other coronavirus diseases.

The Contribution of the Age Distribution of Cases to COVID-19 Case Fatality Across Countries : A Nine-Country Demographic Study.

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.

Children's education and parental old-age health: Evidence from a population-based, nationally representative study in India.

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.

Rural-Urban Differences in Adult Life Expectancy in Indonesia: A Parametric g-formula-based Decomposition Approach.

BACKGROUND: Evidence on rural-urban differences in adult mortality in low- and middle-income countries (LMICs) is limited and mixed. We examined the size of and factors contributing to rural-urban life expectancy differences among adults in Indonesia, the third most populous LMIC. METHODS: Data come from the 2000, 2007, and 2014/2015 waves of the Indonesian Family Life Survey, a population-representative longitudinal study with mortality follow-up. We used Poisson regression and life tables to estimate rural-urban differences in life expectancy among 18,867 adult respondents ≥30 years. We then used a novel g-formula-based decomposition to quantify the contribution of rural-urban differences in blood pressure (BP), body mass index (BMI), and smoking to life expectancy differences. RESULTS: Compared with urban adults, life expectancy at age 30 was 2.2 (95% confidence interval [CI] = 0.4, 3.9) years higher for rural men and 1.2 (95% CI = -0.4, 2.7) years higher for rural women. Setting the BMI and systolic BP distribution equal in urban and rural adults reduced the urban mortality penalty by 22% for men and 78% for women, with the majority of this reduction coming from the contribution of rural-urban differences in BMI. Smoking did not contribute to the urban mortality penalty for either men or women. CONCLUSIONS: Adult life expectancy is lower in urban than in rural areas in Indonesia and we estimate that this difference is partly related to differences in BMI and systolic BP.

Population aging, macroeconomic changes, and global diabetes prevalence, 1990-2008.

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.

Interviewer biases in medical survey data: The example of blood pressure measurements.

Health agencies rely upon survey-based physical measures to estimate the prevalence of key global health indicators such as hypertension. Such measures are usually collected by nonhealthcare worker personnel and are potentially subject to measurement error due to variations in interviewer technique and setting, termed "interviewer effects." In the context of physical measurements, particularly in low- and middle-income countries, interviewer-induced biases have not yet been examined. Using blood pressure as a case study, we aimed to determine the relative contribution of interviewer effects on the total variance of blood pressure measurements in three large nationally representative health surveys from the Global South. We utilized 169,681 observations between 2008 and 2019 from three health surveys (Indonesia Family Life Survey, National Income Dynamics Study of South Africa, and Longitudinal Aging Study in India). In a linear mixed model, we modeled systolic blood pressure as a continuous dependent variable and interviewer effects as random effects alongside individual factors as covariates. To quantify the interviewer effect-induced uncertainty in hypertension prevalence, we utilized a bootstrap approach comparing subsamples of observed blood pressure measurements to their adjusted counterparts. Our analysis revealed that the proportion of variation contributed by interviewers to blood pressure measurements was statistically significant but small: ∼0.24--2.2% depending on the cohort. Thus, hypertension prevalence estimates were not substantially impacted at national scales. However, individual extreme interviewers could account for measurement divergences as high as 12%. Thus, highly biased interviewers could have important impacts on hypertension estimates at the subdistrict level.

Hypertension care cascades and reducing inequities in cardiovascular disease in low- and middle-income countries.

Improving hypertension control in low- and middle-income countries has uncertain implications across socioeconomic groups. In this study, we simulated improvements in the hypertension care cascade and evaluated the distributional benefits across wealth quintiles in 44 low- and middle-income countries using individual-level data from nationally representative, cross-sectional surveys. We raised diagnosis (diagnosis scenario) and treatment (treatment scenario) levels for all wealth quintiles to match the best-performing country quintile and estimated the change in 10-year cardiovascular disease (CVD) risk of individuals initiated on treatment. We observed greater health benefits among bottom wealth quintiles in middle-income countries and in countries with larger baseline disparities in hypertension management. Lower-middle-income countries would see the greatest absolute benefits among the bottom quintiles under the treatment scenario (29.1 CVD cases averted per 1,000 people living with hypertension in the bottom quintile (Q1) versus 17.2 in the top quintile (Q5)), and the proportion of total CVD cases averted would be largest among the lowest quintiles in upper-middle-income countries under both diagnosis (32.0% of averted cases in Q1 versus 11.9% in Q5) and treatment (29.7% of averted cases in Q1 versus 14.0% in Q5) scenarios. Targeted improvements in hypertension diagnosis and treatment could substantially reduce socioeconomic-based inequalities in CVD burden in low- and middle-income countries.

Can training over phone calls help improve outcomes for COVID-19 positive patients under home isolation? An analysis of the COVID-19 Care Companion Program in Punjab, India.

Background: Phone-supported recovery of COVID-19 patients in home isolation could be an effective way of addressing COVID-19 in contexts with limited resources. The COVID-19 Care Companion Program (CCP) is one such intervention, designed to support patients and their caregivers in remote, evidence-based management of COVID-19 symptoms. Objective: To estimate the effect of providing phone-based training to COVID-19 patients and their caregivers on the likelihood of hospitalizations and mortality. Methods: A pragmatic randomized trial was conducted to assess the effect of a novel phone-based training program on COVID-19 home-isolated patient outcomes. The analysis compared the outcomes of death and hospitalizations in the teletraining intervention group (CCP) to those receiving standard of care (SoC). Results: Logistic regression models adjusted for age, gender, education, occupation, and poverty, as measured by family possession of Below Poverty Line (BPL) card, were used to look at the effect of intervention on hospitalization and mortality. While the CCP intervention had no effect on 21-day mortality (OR 0.64; 95% CI, 0.19 to 2.12), it was associated with a 48% reduction in 21-day hospitalization (OR 0.52; 95% CI, 0.31 to 0.90). Conclusion: COVID-19 CCP teletraining intervention reduced the rate of hospitalization, potentially reducing the burden on hospitals.

Changing socioeconomic and geographic gradients in cardiovascular disease risk factors among Indians aged 15-49 years - evidence from nationally representative household surveys.

Background: Cardiovascular diseases (CVDs) are the leading cause of death in most low- and middle-income countries (LMICs). CVDs and their metabolic risk factors have historically been concentrated among urban residents with higher socioeconomic status (SES) in LMICs such as India. However, as India develops, it is unclear whether these socioeconomic and geographic gradients will persist or change. Understanding these social dynamics in CVD risk is essential for mitigating the rising burden of CVDs and to reach those with the greatest needs. Methods: Using nationally representative data with biomarker measurements from the fourth (2015-16) and fifth (2019-21) Indian National Family and Health Surveys, we investigated trends in the prevalence of four CVD risk factors: smoking (self-reported), unhealthy weight (BMI ≥25 kgm2), diabetes (random plasma glucose concentration ≥200 mg/dL or self-reported diabetes), and hypertension (one of: average systolic blood pressure ≥140 mmHg, average diastolic blood pressure ≥90 mmHg, self-reported past diagnosis, or self-reported current antihypertensive medication use) among adults aged 15-49 years. We first described changes at the national level and then trends stratified by place of residence (urban versus rural), geographic region (northern, northeastern, central, eastern, western, southern), regional level of development (Empowered Action Group member state or not), and two measures of socioeconomic status: level of education (no education, primary incomplete, primary complete, secondary incomplete, secondary complete, higher) and wealth (quintiles). Findings: Unhealthy weight increased among all social and geographic groups but both the absolute and the relative changes were substantially higher among people with low SES (as measured by education or wealth) and in rural areas. For diabetes and hypertension, the prevalence increased for those from disadvantaged groups while staying constant or even decreasing among the wealthier and more educated. In contrast, smoking consumption declined for all social and geographic groups. Interpretation: In 2015-16, CVD risk factors were higher among more advantaged subpopulations in India. However, between 2015-16 and 2019-21, the prevalence of these risk factors grew more rapidly for less wealthy and less educated subpopulations and those living in rural areas. These trends have resulted in CVD risk becoming far more widespread throughout the population; CVD can no longer be characterized as a wealthy urban phenomenon. Funding: This work was supported by the Alexander von Humboldt Foundation (grant received by NS); the Stanford Diabetes Research Center [grant received by PG] and the Chan Zuckerberg Biohub [grant received by PG].

National Estimates of the Adult Diabetes Care Continuum in India, 2019-2021.

Importance: Diabetes is widespread and treatable, but little is known about the diabetes care continuum (diagnosis, treatment, and control) in India and how it varies at the national, state, and district levels. Objective: To estimate the adult population levels of diabetes diagnosis, treatment, and control in India at national, state, and district levels and by sociodemographic characteristics. Design, Setting, and Participants: In this cross-sectional, nationally representative survey study from 2019 to 2021, adults in India from 28 states, 8 union territories, and 707 districts were surveyed for India's Fifth National Family Health Survey (NFHS-5). The survey team collected data on blood glucose among all adults (18-98 years) who were living in the same household as eligible participants (pregnant or nonpregnant female individuals aged 15-49 years and male individuals aged 15-54 years). The overall sample consisted of 1 895 287 adults. The analytic sample was restricted to those who either self-reported having diabetes or who had a valid measurement of blood glucose. Exposures: The exposures in this survey study were district and state residence; urban vs rural residence; age (18-39 years, 40-64 years, or ≥65 years); sex; and household wealth quintile. Main Outcomes and Measures: Diabetes was defined by self-report or high capillary blood glucose (fasting: ≥126 mg/dL [to convert to mmol/L, multiply by 0.0555]; nonfasting: ≥220 mg/dL). Among respondents who had previously been diagnosed with diabetes, the main outcome was the proportion treated based on self-reported medication use and the proportion controlled (fasting: blood glucose <126 mg/dL; nonfasting: ≤180 mg/dL). The findings were benchmarked against the World Health Organization (WHO) Global Diabetes Compact targets (80% diagnosis; 80% control among those diagnosed). The variance in indicators between and within states was partitioned using variance partition coefficients (VPCs). Results: Among 1 651 176 adult respondents (mean [SD] age, 41.6 [16.4] years; 867 896 [52.6%] female) with blood glucose measures, the proportion of individuals with diabetes was 6.5% (95% CI, 6.4%-6.6%). Among adults with diabetes, 74.2% (95% CI, 73.3%-75.0%) were diagnosed. Among those diagnosed, 59.4% (95% CI, 58.1%-60.6%) reported taking medication, and 65.5% (95% CI, 64.5%-66.4%) achieved control. Diagnosis and treatment were higher in urban areas, older age groups, and wealthier households. Among those diagnosed in the 707 districts surveyed, 246 (34.8%) districts met the WHO diagnosis target, while 76 (10.7%) districts met the WHO control target. Most of the variability in diabetes diagnosis (VPC, 89.1%), treatment (VPC, 85.9%), and control (VPC, 95.6%) were within states, not between states. Conclusions and Relevance: In this survey study, the diabetes care continuum in India is represented by considerable district-level variation, age-related disparities, and rural-urban differences. Surveillance at the district level can guide state health administrators to prioritize interventions and monitor achievement of global targets.

Health systems performance for hypertension control using a cascade of care approach in South Africa, 2011-2017.

Hypertension is a major contributor to global morbidity and mortality. In South Africa, the government has employed a whole systems approach to address the growing burden of non-communicable diseases. We used a novel incident care cascade approach to measure changes in the South African health system's ability to manage hypertension between 2011 and 2017. We used data from Waves 1-5 of the National Income Dynamics Study (NIDS) to estimate trends in the hypertension care cascade and unmet treatment need across four successive cohorts with incident hypertension. We used a negative binomial regression to identify factors that may predict higher rates of hypertension control, controlling for socio-demographic and healthcare factors. In 2011, 19.6% (95%CI 14.2, 26.2) of individuals with incident hypertension were diagnosed, 15.4% (95%CI 10.8, 21.4) were on treatment and 7.1% had controlled blood pressure. By 2017, the proportion of individuals with diagnosed incident hypertension had increased to 24.4% (95%CI 15.9, 35.4). Increases in treatment (23.3%, 95%CI 15.0, 34.3) and control (22.1%, 95%CI 14.1, 33.0) were also observed, translating to a decrease in unmet need for hypertension care from 92.9% in 2011 to 77.9% in 2017. Multivariable regression showed that participants with incident hypertension in 2017 were 3.01 (95%CI 1.77, 5.13) times more likely to have a controlled blood pressure compared to those in 2011. Our data show that while substantial improvements in the hypertension care cascade occurred between 2011 and 2017, a large burden of unmet need remains. The greatest losses in the incident hypertension care cascades came before diagnosis. Nevertheless, whole system programming will be needed to sufficiently address significant morbidity and mortality related to having an elevated blood pressure.

Hypertension Diagnosis, Treatment, and Control in India.

Importance: Hypertension is a major cause of morbidity and mortality worldwide. Previous efforts to characterize gaps in the hypertension care continuum-including diagnosis, treatment, and control-in India did not assess district-level variation. Local data are critical for planning, implementation, and monitoring efforts to curb the burden of hypertension. Objective: To examine the hypertension care continuum in India among individuals aged 18 to 98 years. Design, Setting, and Participants: The nationally representative Fifth National Family Health Survey study was conducted in 2 phases from June 17, 2019, to March 21, 2020, and from November 21, 2020, to April 30, 2021, among 1 895 297 individuals in 28 states, 8 union territories, and 707 districts of India. Exposures: District and state of residence, urban classification, age (18-39, 40-64, and ≥65 years), sex, and household wealth quintile. Main Outcomes and Measures: Hypertension was defined as a self-reported diagnosis or a newly measured blood pressure of 140/90 mm Hg or more. The proportion of individuals diagnosed (self-reported), the proportion of individuals treated among those diagnosed (self-reported medication use), and the proportion of individuals with blood pressure control among those treated (blood pressure <140/90 mm Hg [aged 18-79 years] or <150/90 mm Hg [aged ≥80 years]) were calculated based on national guidelines. Age-standardized estimates of treatment and control were also provided among the total with hypertension. To assess differences in the care continuum between or within states (ie, between districts), the variance was partitioned using generalized linear mixed models. Results: Of the 1 691 036 adult respondents (52.6% women; mean [SD] age, 41.6 [16.5] years), 28.1% (95% CI, 27.9%-28.3%) had hypertension, of whom 36.9% (95% CI, 36.4%-37.3%) received a diagnosis. Among those who received a diagnosis, 44.7% (95% CI, 44.1%-45.3%) reported taking medication (corresponding to 17.7% [95% CI, 17.5%-17.9%] of the total with hypertension). Among those treated, 52.5% (95% CI, 51.7%-53.4%) had blood pressure control (corresponding to 8.5% [95% CI, 8.3%-8.6%] of the total with hypertension). There were substantial variations across districts in blood pressure diagnosis (range, 6.3%-77.5%), treatment (range, 8.7%-97.1%), and control (range, 2.7%-76.6%). Large proportions of the variation in hypertension diagnosis (94.7%), treatment (93.6%), and control (97.3%) were within states, not just between states. Conclusions and Relevance: In this cross-sectional survey study of Indian adults, more than 1 in 4 people had hypertension, and of these, only 1 in 3 received a diagnosis, less than 1 in 5 were treated, and only 1 in 12 had blood pressure control. National mean values hide considerable state-level and district-level variation in the care continuum, suggesting the need for targeted, decentralized solutions to improve the hypertension care continuum in India.

Design Research to Embed mHealth into a Community-Led Blood Pressure Management System in Uganda: Protocol for a Mixed Methods Study.

BACKGROUND: Uncontrolled hypertension is a leading risk factor for cardiovascular diseases. In Uganda, such diseases account for approximately 10% of all deaths, with 1 in 5 adults having hypertension (>90% of the hypertensive cases are uncontrolled). Although basic health care in the country is available free of cost at government facilities, regularly accessing medication to control hypertension is difficult because supply chain challenges impede availability. Clients therefore frequently suspend treatment or buy medication individually at private facilities or pharmacies (incurring significant costs). In recent years, mobile health (mHealth) interventions have shown increasing potential in addressing health system challenges in sub-Saharan Africa, but the acceptability, feasibility, and uptake conditions of mobile money approaches to chronic disease management remain understudied. OBJECTIVE: This study aims to design and pilot-test a mobile money-based intervention to increase the availability of antihypertensive medication and lower clients' out-of-pocket payments. We will build on existing local approaches and assess the acceptability, feasibility, and uptake of the designed intervention. Furthermore, rather than entering the study setting with a ready-made intervention, this research will place emphasis on gathering applied ethnographic insights early, which can then inform the parameters of the intervention prototype and concurrent trial. METHODS: We will conduct a mixed methods study following a human-centered design approach. We will begin by conducting extensive qualitative research with a range of stakeholders (clients; health care providers; religious, cultural, and community leaders; academics; and policy makers at district and national levels) on their perceptions of hypertension management, money-saving systems, and mobile money in the context of health care. Our results will inform the design, iterative adaptation, and implementation of an mHealth-facilitated pooled financing intervention prototype. At study conclusion, the finalized prototype will be evaluated quantitatively via a randomized controlled trial. RESULTS: As of August 2023, qualitative data collection, which started in November 2022, is ongoing, with data analysis of the first qualitative interviews underway to inform platform and implementation design. Recruitment for the quantitative part of this study began in August 2023. CONCLUSIONS: Our results aim to inform the ongoing discourse on novel and sustainable pathways to facilitate access to medication for the management of hypertension in resource-constrained settings. TRIAL REGISTRATION: German registry of clinical trials DRKS00030922; https://drks.de/search/en/trial/DRKS00030922. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46614.

Educational note: causal decomposition of population health differences using Monte Carlo integration and the g-formula.

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.

Alcohol-Attributable Deaths Help Drive Growing Socioeconomic Inequalities In US Life Expectancy, 2000-18.

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.