Socioeconomic determinants of hypertension and prehypertension in Peru: Evidence from the Peruvian Demographic and Health Survey

Abstract

Background Peru is a Latin American country with a significant burden of hypertension that presents worrying rates of disparities in socioeconomic determinants. However, there is a lack of studies exploring the association between those determinants, hypertension and prehypertension in Peruvian population. Objective We aimed to assess the association betwgeen socioeconomic determinants, hypertension and prehypertension using a nationally representative survey of Peruvians. Methods We performed a cross-sectional analysis of the Peruvian Demographic and Health Survey (2018), which is a two-staged regional-level representative survey. We used data from 33,336 people aged 15 and older. The dependent variable was blood pressure classification (normal, prehypertension and hypertension) following the Seventh Report of the Joint National Committee (JNC-7) on hypertension management. Independent variables were socioeconomic: age, sex, marital status, wealth index, health insurance, education, region and area of residence. Due to the nature of the dependent variable (more than two categories), we opted to use the multinomial regression model, adjusting the effect of the multistage sample using the svy command. We tested interactions with the adjusted Wald test. Results The prevalence of prehypertension and hypertension was 33.68% and 19.77%, respectively. Awareness was higher in urban than in rural areas (9.61% vs. 8.31%, p = 0.008). Factors associated with a higher prevalence ratio of both prehypertension and hypertension were age (ratios rose with each age group), male sex (prehypertension aRPR 5.15, 95%CI 4.63–5.73; hypertension aRPR 3.85, 95% CI 3.37–4.40) and abdominal obesity (prehypertension aRPR 2.11, 95%CI 1.92–2.31; hypertension aRPR 3.04, 95% CI 2.69–3.43). Factors with a lower prevalence ratio of both diseases were secondary education (prehypertension aRPR 0.76, 95%CI 0.60–0.95; hypertension aRPR 0.75, 95% CI 0.58–0.97), higher education (prehypertension aRPR 0.78, 95%CI 0.61–0.99; hypertension aRPR 0.62, 95% CI 0.46–0.82), being married/cohabiting (prehypertension aRPR 0.87, 95%CI 0.79–0.95; hypertension aRPR 0.77, 95% CI 0.68–0.87), richest wealth index (only prehypertension aRPR 0.76, 95%CI 0.63–0.92) and living in cities different to Lima (rest of the Coastline, Highlands and Jungle). Having health insurance (only hypertension aRPR 1.26, 95%CI 1.03–1.53) and current drinking (only prehypertension aRPR 1.15, 95%CI 1.01–1.32) became significant factors in rural areas. Conclusions We evidenced socioeconomic disparities among people with hypertension and prehypertension. Better health policies on reducing the burden of risk factors are needed, besides, policy decision makers should focus on hypertension preventive strategies in Peru.

Prevalence of Prehypertension and Associated Cardiovascular Risk Profiles among Adults in Peru: Findings from a Nationwide Population-Based Study

“…The prevalence of prehypertension in males was higher than in females. This finding is similar to that reported in studies conducted in China [15], Jamaica [35], Mongolia [36], Nepal [37], Israel [38], United States [39], Peru [17], and Taiwan [40], in which men had a higher prevalence of prehypertension compared to women. It is postulated that this difference may be attributed to biological mechanisms related to sex hormones, which have been evaluated in animal models and in humans [41].…”

“…In South American countries such as Argentina, Uruguay, and Chile, prehypertension affects 32.5% of the general population, with a higher prevalence in men compared to women (36.0% vs. 29.4%) [16]. In Peru, a pattern similar to that of these countries is observed, with prehypertension affecting more than 30% of the general population, and in terms of gender, the male population has a higher prevalence and probability of presenting this condition compared to women [17]. These differences in the prevalence of prehypertension according to sex may be influenced by cardiometabolic and behavioral risk factors that behave differently in men and women [18].…”

“…The potential confounding variables identified in the scientific literature and included in our analysis were the following [17,[28][29][30][31][32][33]: education level (up to primary/secondary/higher education), poverty (non-poor/poorest), health insurance status (yes/no), area of residence (urban/rural) and altitude of residence (0-499/500-1499/1500 or more).…”

Socioeconomic Status and Its Relation to Hypertension in Rural Nepal

“…Moreover, the same meta-analysis study suggested farming to be inversely associated with hypertension [ 44 ]. Similarly, a study in Vietnam reported a lower prevalence of hypertension among farmers compared to traders, construction workers, and government employees [ 14 ]. In high-income countries, an inverse association of education [ 48 ], income [ 11 , 48 , 49 ], and being employed [ 48 , 50 ] with hypertension was reported.…”

“…However, in LMIC, this association is complex. For instance, the prevalence of hypertension was higher among low SES groups in Brazil [ 12 , 13 ] and Peru [ 14 ], while greater among high SES groups in South Asian countries [ 14 – 18 ]. Studies from Nepal have also reported an elevated blood pressure among affluent individuals [ 19 ], whereas highly educated individuals [ 4 , 5 ] and men doing labor-intensive work had normal blood pressure.…”