ArticleAJPM focus2024
Lifestyle Differences in the Metabolic Comorbidity Score of Adult Population From South Asian Countries: A Cross-Sectional Study.
Article in AJPM focus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
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4 authors.
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Abstract
Introduction: Metabolic comorbidities are involved in the development and progression of noncommunicable diseases. There is convincing evidence that lifestyles are important contributors to metabolic comorbidities. This study measured the metabolic comorbidity score of South Asian adults and identified its relationship with lifestyles. Methods: The authors studied 5 South Asian countries, including Afghanistan, Bangladesh, Bhutan, Nepal, and Sri Lanka, using the World Health Organization's STEPwise approach to noncommunicable disease risk factor surveillance data between 2014 and 2019. This was a nationally representative and cross-sectional survey on participants aged 15-69 years. The sample size was 27,616. The outcome was metabolic comorbidity score, calculated on the basis of total cholesterol, fasting plasma glucose, blood pressure, and abdominal obesity. Total metabolic comorbidity score of each participant varied between 0 and 8. It was then divided into 3 ranges: the lowest range (total metabolic comorbidity score <3), medium range (total metabolic comorbidity score ≥3 and ≤5), and the highest range (total metabolic comorbidity score ≥6). On the basis of the outcome of nonparametric receiver operating characteristics analysis, the medium and the highest ranges together were considered as higher metabolic comorbidity score. The lowest range was considered as lower metabolic comorbidity score. The higher metabolic comorbidity score was coded as 1, and the lower metabolic comorbidity score was coded as 0. Thus, the outcome variable, metabolic comorbidity score, became a binary variable. Exposures included physical inactivity (<150 minutes of medium-to-vigorous physical activity/week), high daily sedentary time (≥9 hours/day), use of tobacco (present or past smoking or daily use of smokeless tobacco products), and consumption of alcohol (at least once per month in the last 1 year). Binomial logistic regression model produced the OR with corresponding 95% CIs. Results: The prevalence of higher metabolic comorbidity score was 34% among South Asian adults, 25% among the male respondents, and 41% among the female respondents. Participants who were physically inactive (OR=1.26; 95% CI= 1.17, 1.36), had high sedentary time (OR=1.24; 95% CI=1.11, 1.33), and consumed alcohol (OR=1.40; 95% CI=1.23, 1.53) showed higher metabolic comorbidity score than participants who were physically active, had low sedentary time, and did not consume alcohol respectively. However, the authors found an inverse association (OR=0.75; 95% CI=0.71, 0.81) between the use of tobacco and metabolic comorbidity score. Conclusions: One third of South Asian adults had higher metabolic comorbidity score. Physical inactivity, daily sedentary hours, and minimal alcohol consumption were associated with higher metabolic comorbidity score.
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