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

Abstract

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.

Keywords: cardiovascular disease; epidemiology; low‐ and middle‐income countries; noncommunicable diseases; prevention.

Figure 1. Hypertension prevalence by 5‐year age group, sex, and region.

AFR indicates Africa; EME, Eastern Mediterranean; EUR, Europe; LAC, Latin America and the Caribbean; SEA, Southeast Asia; and WPA, Western Pacific.

Figure 2. Average adjusted predictions of hypertension by body mass index (BMI) group, age group, and region.

CIs were computed using the Δ method. We only show one side of each CI for visual clarity. Figure S10 and Table S13 show the full CIs. All countries were weighted equally for this analysis. These average adjusted predictions were obtained from Poisson regressions that included age group, BMI group, sex, smoking status, a binary variable for each country, and an interaction term between age group and BMI group as independent variables. AFR indicates Africa; EME, Eastern Mediterranean; EUR, Europe; LAC, Latin America and the Caribbean; SEA, Southeast Asia; and WPA, Western Pacific.

Figure 3. Smoothed age‐specific prevalence of hypertension, by country.

The gray curve represents the percentage of a country's population that is under the given age. The curve for hypertension was plotted using locally estimated scatterplot smoothing regression with a span of 1.0 years. Burk. Faso indicates Burkina Faso; Mozamb., Mozambique; S. Africa, South Africa; SVG, St. Vincent and the Grenadines; and Timor‐L., Timor‐Leste.