Clinician Adherence to Hypertension Screening and Care Guidelines.

This quality improvement study assesses opportunistic blood pressure measurement, communication of blood pressure reading to adult patients, and recommendation for a follow-up visit at health care facilities in 2 major cities in India.

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].

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.

Patterns of multimorbidity in India: A nationally representative cross-sectional study of individuals aged 15 to 49 years.

There is a dearth of evidence on the epidemiology of multimorbidity in low- and middle-income countries. This study aimed to determine the prevalence of multimorbidity in India and its variation among states and population groups. We analyzed data from a nationally representative household survey conducted in 2015-2016 among individuals aged 15 to 49 years. Multimorbidity was defined as having two or more conditions out of five common chronic morbidities in India: anemia, asthma, diabetes, hypertension, and obesity. We disaggregated multimorbidity prevalence by condition, state, rural versus urban areas, district-level wealth, and individual-level sociodemographic characteristics. 712,822 individuals were included in the analysis. The prevalence of multimorbidity was 7·2% (95% CI, 7·1% - 7·4%), and was higher in urban (9·7% [95% CI, 9·4% - 10·1%]) than in rural (5·8% [95% CI, 5·7% - 6·0%]) areas. The three most prevalent morbidity combinations were hypertension with obesity (2·9% [95% CI, 2·8% - 3·1%]), hypertension with anemia (2·2% [95% CI, 2·1%- 2·3%]), and obesity with anemia (1·2% [95% CI, 1·1%- 1·2%]). The age-standardized multimorbidity prevalence varied from 3·4% (95% CI: 3·0% - 3·8%) in Chhattisgarh to 16·9% (95% CI: 13·2% - 21·5%) in Puducherry. Being a woman, being married, not currently smoking, greater household wealth, and living in urban areas were all associated with a higher risk of multimorbidity. Multimorbidity is common among young and middle-aged adults in India. This study can inform screening guidelines for chronic conditions and the targeting of relevant policies and interventions to those most in need.

Know-do gaps for cardiovascular disease care in Cambodia: Evidence on clinician knowledge and delivery of evidence-based prevention actions.

Cardiovascular diseases (CVD) are the leading cause of death in Cambodia. However, it is unknown whether clinicians in Cambodia provide evidence-based CVD preventive care actions. We address this important gap and provide one of the first assessments of clinical care for CVD prevention in an LMIC context. We determined the proportion of primary care visits by adult patients that resulted in evidence-based CVD preventive care actions, identified which care actions were most frequently missed, and estimated the know-do gap for each clinical action. We used data on 190 direct clinician-patient observations and 337 clinician responses to patient vignettes from 114 public primary care health facilities. Our main outcomes were the proportion of patient consultations and responses to care vignettes where clinicians measured blood pressure, blood glucose, body mass index, and asked questions regarding alcohol, tobacco, physical activity, and diet. There were very large clinical care shortfalls for all CVD care actions. Just 6.4% (95% CI: 3.0%, 13.0%) of patients had their BMI measured, 8.0% (4.6%, 13.6%) their blood pressure measured at least twice, only 4.7% (1.9%, 11.2%) their blood glucose measured. Less than 21% of patients were asked about their physical activity (11.7% [7.0%, 18.9%]), smoking (18.0% [11.8%, 26.5%]), and alcohol-related behaviors (20.2% [13.7%, 28.9%]). We observed the largest know-do gaps for blood glucose and BMI measurements with smaller but important know-do gaps for the other clinical actions. CVD care did not vary across clinician cadre or by years of experience. We find large CVD care delivery gaps in primary-care facilities across Cambodia. Our results suggest that diabetes is being substantially underdiagnosed and that clinicians are losing CVD prevention potential by not identifying individuals who would benefit from behavioral changes. The large overall and know-do gaps suggest that interventions for improving preventive care need to target both clinical knowledge and the bottlenecks between knowledge and care behavior.

Targeting Hypertension Screening in Low- and Middle-Income Countries: A Cross-Sectional Analysis of 1.2 Million Adults in 56 Countries.

Background As screening programs in low- and middle-income countries (LMICs) often do not have the resources to screen the entire population, there is frequently a need to target such efforts to easily identifiable priority groups. This study aimed to determine (1) how hypertension prevalence in LMICs varies by age, sex, body mass index, and smoking status, and (2) the ability of different combinations of these variables to accurately predict hypertension. Methods and Results We analyzed individual-level, nationally representative data from 1 170 629 participants in 56 LMICs, of whom 220 636 (18.8%) had hypertension. Hypertension was defined as systolic blood pressure ≥140 mm Hg, diastolic blood pressure ≥90 mm Hg, or reporting to be taking blood pressure-lowering medication. The shape of the positive association of hypertension with age and body mass index varied across world regions. We used logistic regression and random forest models to compute the area under the receiver operating characteristic curve in each country for different combinations of age, body mass index, sex, and smoking status. The area under the receiver operating characteristic curve for the model with all 4 predictors ranged from 0.64 to 0.85 between countries, with a country-level mean of 0.76 across LMICs globally. The mean absolute increase in the area under the receiver operating characteristic curve from the model including only age to the model including all 4 predictors was 0.05. Conclusions Adding body mass index, sex, and smoking status to age led to only a minor increase in the ability to distinguish between adults with and without hypertension compared with using age alone. Hypertension screening programs in LMICs could use age as the primary variable to target their efforts.

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.

Education and adult mortality in middle-income countries: Surprising gradients in six nationally-representative longitudinal surveys.

BACKGROUND: There are large differences in adult mortality across schooling groups in many high-income countries (HICs). An important open question is whether there are similar gradients in adult mortality in middle-income countries (MICs), where schooling and healthcare quality tends to be lower and health-related behaviors are often not strongly patterned by schooling. METHODS: We present one of the first international-comparative studies on schooling differences in adult mortality across MICs using harmonizedlongitudinal data on adults ages 50+ from China, Costa Rica, Indonesia, Mexico, South Africa, and South Korea. We use Cox proportional hazards models to estimate differences in the hazard of mortality across schooling groups overall and separately by sex and broad age groups. We also estimate schooling gradients in smoking and body mass index to determine whether risk factor gradients potentially explain mortality patterns. RESULTS: Only adults with tertiary schooling have a consistent adult mortality advantage compared to those with no schooling. We do not find evidence that individuals with primary schooling have a lower hazard of mortality compared to individuals with no schooling in five of the six countries. The mortality advantage for individuals with secondary schooling is mixed, with evidence of lower mortality relative to those with no schooling in Mexico, South Africa, and South Korea. Gradients in BMI and smoking are inconsistent across countries and unlikely to explain mortality differences. CONCLUSIONS: We find that adult mortality and risk factor gradients in MICs can be much different than the established patterns seen in modern HICs. Our results highlight that adult mortality gradients are not an inevitability and are not found in all populations. Understanding what factors give rise to inequalities in adult mortality and what can be done to minimize gradients while still ensuring continued mortality improvements in MICs is a crucial focus for research and policy.

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.

The Effect Of Home-Based Hypertension Screening On Blood Pressure Change Over Time In South Africa.

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.

Impact of community based screening for hypertension on blood pressure after two years: regression discontinuity analysis in a national cohort of older adults in China.

OBJECTIVE: To estimate the causal impact of community based blood pressure screening on subsequent blood pressure levels among older adults in China. DESIGN: Regression discontinuity analysis using data from a national cohort study. SETTING: 2011-12 and 2014 waves of the Chinese Longitudinal Healthy Longevity Survey, a national cohort of older adults in China. PARTICIPANTS: 3899 older adults who had previously undiagnosed hypertension. INTERVENTION: Community based hypertension screening among older adults in 2011-12. MAIN OUTCOME MEASURE: Blood pressure two years after initial screening. RESULTS: The intervention reduced systolic blood pressure: -6.3 mm Hg in the model without covariates (95% confidence interval -11.2 to -1.3) and -8.3 mm Hg (-13.6 to -3.1) in the model that adjusts additionally for demographic, social, and behavioural covariates. The impact on diastolic blood pressure was smaller and non-significant in all models. The results were similar when alternative functional forms were used to estimate the impact and the bandwidths around the intervention threshold were changed. The results did not vary by demographic and social subgroups. CONCLUSIONS: Community based hypertension screening and encouraging people with raised blood pressure to seek care and adopt blood pressure lowering behaviour changes could have important long term impact on systolic blood pressure at the population level. This approach could address the high burden of cardiovascular diseases in China and other countries with large unmet need for hypertension diagnosis and care.

Limited common origins of multiple adult health-related behaviors: Evidence from U.S. twins.

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.