J Korean Acad Nurs.  2024 Feb;54(1):18-31. 10.4040/jkan.23067.

Impact of Anthropometric Indices of Obesity on the Risk of Incident Hypertension in Adults with Prehypertension: A Secondary Analysis of a Cohort Study

Affiliations
  • 1Department of Nursing, Jeonbuk National University Hospital, Jeonju
  • 2Department of Nursing, Graduate School, Jeonbuk National University, Jeonju, Korea

Abstract

Purpose
This study aimed to investigate the impact of anthropometric indices of obesity (body mass index [BMI], waist circumference, waist hip ratio, and body fat percentage) on the incidence of hypertension in adults with prehypertension.
Methods
A longitudinal study design using secondary data form the Korean Genome and Epidemiology Study was employed. The study included 1,838 adults with prehypertension tracked every two years from 2001 to 2018. Statistical analyses, including frequency assessments, number of cases per 1,000 person-years, log-rank tests, Kaplan-Meier curves, and Cox’s proportional hazards regression, were conducted using SPSS version 25.
Results
Over the observation period (15,783.6 person-years), 1,136 individuals developed hypertension. The incidence of hypertension was significantly higher in the obesity groups defined by BMI (hazard ratio [HR] = 1.33), waist circumference (HR = 1.34), waist hip ratio (HR = 1.29), and body fat percentage (HR = 1.31) compared to the non-obese group. These findings indicate an increased risk of hypertension associated with obesity as measured by these indices.
Conclusion
The study underscores the importance of avoiding obesity to prevent hypertension in individuals with prehypertension. Specifically, BMI, waist circumference, waist hip circumference, and body fat percentage were identified as significant risk factors for hypertension. The results suggest the need for individualized weight control interventions, emphasizing the role of health professionals in addressing the heightened hypertension risk in this population.

Keyword

Prehypertension; Hypertension; Obesity; Secondary Data Analysis
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