Individual and cumulative effects of socioeconomic factors on hypertension in low- and middle-income countries: a cross-sectional study of 1,071,070 individuals from 26 nationally representative surve
Authors: Mishra S R , Satheesh G , Ghimire K , Zhu D , Shrestha N , Panda R , Khanal V 
Published: October 2024

Background/Introduction

Addressing current gaps in hypertension care in low- and middle-income countries (LMICs) requires better understanding of socioeconomic disparities. Variation of the effects of socioeconomic status on hypertension across geographic regions and the shape of the relationship with individual markers of socioeconomic status remains unclear.

Purpose

This cross-sectional study aims to determine the effect of individual and cumulative effect of socioeconomic disadvantages (poor household wealth, low or no education, and rurality) on hypertension burden across geographic regions.

Methods

We pooled nationally representative individual level population-based data from Demographic and Health Surveys (DHS) in 26 LMICs. We included surveys conducted after 2002, with at least 50% response rate, and those with information on BP measurement and hypertension status. We included adults aged 15 years and above with hypertension (systolic BP ≥140 mm Hg, diastolic BP ≥90 mm Hg) or those who reported using BP-lowering medication. We excluded individuals with missing information on age, sex, education, hypertension information, rurality, and socioeconomic status. We examined the relationship of hypertension prevalence by education, household wealth, and rurality using regression analyses. Binary categories of household wealth, education, and rurality were summed to create composite socioeconomic disadvantages score (range: 0–3) as a measure of multiple disadvantages.

Results

We included 1,071,070 participants in the analysis, and majority (81%) belonged to Southeast Asia region. Positive gradients were found by household wealth, educational attainment and rurality. The odds of developing hypertension increased by per quintile increase in household wealth in Southeast Asia (aOR for poorest vs richest, 1·51; 95% CI: 1·47-1·55, P-trend &lt;0.001) contrarily to decreasing prevalence by increasing wealth in Central Asia (aOR 0·67; 95% CI: 0·57-0·79, P-trend &lt;0.001) and Europe (aOR 0·69; 95% CI:0·63-0·76, P-trend &lt;0.001) (P-interaction &lt;0·001). Having multiple socioeconomic disadvantages was associated with lower odds of hypertension in Southeast Asia (aOR for none vs three disadvantages, 0·75; 95% CI, 0·74-0·77) and Africa (aOR 0·47; 95% CI: 0·45-0·50), and higher odds in Europe (aOR 1·41; 95% CI: 1·31-1·51), and Central America (aOR 1·37; 95% CI: 1·20-1·57) (P-interaction &lt;0·001). Household wealth and socio-economic disadvantages can be attributed to 19·4% and 36·9% of hypertension burden respectively.

Conclusion

This is one of the few studies examining the effect of individual as well as cumulative effect of socioeconomic status markers in hypertension. The shape of the socioeconomic gradient in hypertension varies across regions depending on demographic and epidemiological profile. This calls for context-specific interventions focusing on the most-at-risk population, redressing socioeconomic disparities in hypertension burden.Association between Hypertension and SES