Factors affecting seasonal changes in blood pressure in North India: A population based four-seasons study

Indian Heart J. 2018 May-Jun;70(3):360-367. doi: 10.1016/j.ihj.2017.09.012. Epub 2017 Sep 20.

Abstract

Objective: There are no community based, longitudinal, intra individual epidemiological studies on effect of weather and season on blood pressure (BP). We evaluated the effect of season and temperature on prevalence and epidemiology of BP in tropical climate.

Methods and results: It was a longitudinal cross sectional survey of rural and urban subjects in their native surroundings. BP was measured in four different seasons in same subjects. A total of 978 subjects (452 rural and 521 urban) were included in the current analysis. Demographic characteristics such as age, gender, education, occupational based physical activity and body mass index (BMI) were recorded. Mean BP, both systolic and diastolic were significantly higher in winter season as compared to summer season. Mean difference between winter and summer was 9.01 (95% CI: 7.74-10.28, p<0.001) in systolic BP and 5.61 (95% CI: 4.75-6.47, p<0.001) in diastolic BP. This increase in BP was more marked in rural areas and elderly subjects. Prevalence of hypertension was significantly higher during winter (23.72%) than in summer (10.12%).

Conclusion: BP increases significantly during winter season as compared to summer season. Increase is more marked in rural areas and elderly subjects. Seasonal variation in BP should be taken into account while looking at prevalence of hypertension in epidemiological studies.

Keywords: Blood pressure; Hypertension prevalence; North India; Rural urban difference; Seasonal variation; Tropical climate.

Publication types

  • Multicenter Study

MeSH terms

  • Adult
  • Blood Pressure / physiology
  • Body Mass Index
  • Cross-Sectional Studies
  • Female
  • Follow-Up Studies
  • Humans
  • Hypertension / epidemiology*
  • Hypertension / physiopathology
  • India / epidemiology
  • Male
  • Middle Aged
  • Morbidity / trends
  • Prospective Studies
  • Risk Assessment*
  • Rural Population*
  • Seasons*
  • Time Factors
  • Urban Population*