Hypertension subtypes at high altitude in Peru: Analysis of the Demographic and Family Health Survey 2016–2019

Background
The prevalence of hypertension in Peru has increased over the years. Approximately one third of the Peruvian population lives at high altitudes. This population presents particular physiological, genetic and environmental characteristics that could be related to the prevalence of hypertension and its subtypes.

Objective
To assess the association between altitude and hypertension in the Peruvian population through an analysis of a nationally representative survey.

Methods
We conducted a cross-sectional analysis of the Demographic and Family Health Survey for the period 2016–2019. We included 122,336 individuals aged 18 years and older. Hypertension was defined according to the JNC-7 guidelines. High-altitude location was defined as a residential cluster located above 2,500 meters above sea level. We utilized generalized linear models from the Poisson family with a log-link function to assess the magnitude of the association between high altitude and hypertension. Additionally, we employed multinomial regression models to analyze the association between high altitude and subtypes of hypertension, including isolated systolic hypertension (ISH), isolated diastolic hypertension (IDH), and systolic-diastolic hypertension (SDH).

Results
In the adjusted Poisson regression model, we found that the prevalence of hypertension among participants living at high altitudes was lower compared to those living at low altitudes (aPR: 0.89; 95% CI: 0.86–0.93). In the adjusted multinomial regression model, we observed a lower prevalence rate of ISH among participants residing at high altitudes (aRPR: 0.68; 95% CI: 0.61–0.73) and a higher prevalence rate of IDH among participants residing at high altitudes (aRPR: 1.60; 95% CI: 1.32–1.94).

Conclusions
Residents at high altitudes in Peru have a lower prevalence rate of ISH and a higher prevalence rate of IDH compared to those living at low altitudes. Further studies are needed to determine the influence of other biological, environmental, and healthcare access factors on this relationship.