The Association between Altitude and Waist–Height Ratio in Peruvian Adults: A Cross-Sectional Data Analysis of a Population-Based Survey

Research output: Contribution to journalArticlepeer-review

Abstract

To evaluate the association between altitude and cardiometabolic risk calculated with the weight–height ratio (WHtR) in the Peruvian adult population via the cross-sectional data analysis of the Peruvian Demographic and Health Survey 2021. A total of 26,117 adults from 18 to 64 years of age were included in the analysis. The dependent variable was cardiometabolic risk, defined as “Yes” if the WHtR was ≥0.5 and “No” if the WHtR was <0.5. Exposure was altitude of residence categorized as: <1500 meters above sea level (masl); 1500 to 2499 masl; 2500 to 3499 masl; and ≥3500 masl. Crude and adjusted Poisson regression models were used to calculate prevalence ratios (PR) with 95% confidence intervals (CI). The mean WHtR in the population was 0.59 (standard deviation: 0.08), and 87.6% (95% CI: 86.9–88.2) were classified as at risk. After adjusting for sex, age, education level, well-being index, and area of residence, living at altitudes between 2500 and 3499 masl (aPR: 0.98; 95% CI: 0.96–1.00) and ≥3500 masl (aPR: 0.95; 95% CI: 0.93–0.97) were associated with lower cardiometabolic risk in comparison with living at <1500 masl. An inverse association was identified between living at a higher altitude and the proportion of cardiometabolic risk in the Peruvian adult population. However, at least 8 out of 10 people were identified as at risk in all categories of altitude.

Original languageEnglish
Article number11494
JournalInternational Journal of Environmental Research and Public Health
Volume19
Issue number18
DOIs
StatePublished - Sep 2022

Keywords

  • Peru
  • altitude
  • cardiometabolic risk factors
  • cross-sectional studies
  • weight–height ratio

Fingerprint

Dive into the research topics of 'The Association between Altitude and Waist–Height Ratio in Peruvian Adults: A Cross-Sectional Data Analysis of a Population-Based Survey'. Together they form a unique fingerprint.

Cite this