Physical activity level and its sociodemographic correlates in a peri-urban Nepalese population: a cross-sectional study from the Jhaukhel-Duwakot health demographic surveillance site.

Abhinav Vaidya,Alexandra Krettek

doi:10.1186/1479-5868-11-39

Abstract

BackgroundPhysical inactivity is a leading risk factor for cardiovascular and other noncommunicable diseases in high-, low- and middle-income countries. Nepal, a low-income country in South Asia, is undergoing an epidemiological transition. Although the reported national prevalence of physical inactivity is relatively low, studies in urban and peri-urban localities have always shown higher prevalence. Therefore, this study aimed to measure physical activity in three domains—work, travel and leisure—in a peri-urban community and assess its variations across different sociodemographic correlates.MethodsAdult participants (n = 640) from six randomly selected wards of the Jhaukhel-Duwakot Health Demographic Surveillance Site (JD-HDSS) near Kathmandu responded to the Global Physical Activity Questionnaire. To determine total physical activity, we calculated the metabolic equivalent of task in minutes/week for each domain and combined the results. Respondents were categorized into high, moderate or low physical activity. We also calculated the odds ratio for low physical activity in various sociodemographic variables and self-reported cardiometabolic states.ResultsThe urbanizing JD-HDSS community showed a high prevalence of low physical activity (43.3%; 95% CI 39.4–47.1). Work-related activity contributed most to total physical activity. Furthermore, women and housewives and older, more educated and self-or government-employed respondents showed a greater prevalence of physical inactivity. Respondents with hypertension, diabetes or overweight/obesity reported less physical activity than individuals without those conditions. Only 5% of respondents identified physical inactivity as a cardiovascular risk factor.ConclusionsOur findings reveal a high burden of physical inactivity in a peri-urban community of Nepal. Improving the level of physical activity involves sensitizing people to its importance through appropriate multi-sector strategies that provide encouragement across all sociodemographic groups.

Highlights

With an estimated prevalence of 31%, physical inactivity is the fourth leading cause of death worldwide [1], contributing to premature death (10%), coronary artery disease (6%) and type 2 diabetes mellitus (7%) [2]
In 1953, Jeremy Morris pioneered the epidemiology of physical inactivity by comparing the mortality rate for coronary heart disease (CHD) in bus drivers versus more active bus conductors [3]
Since the American Heart Association recognized physical inactivity as a risk factor for CHD in 1992 [4], longitudinal studies have further consolidated the protective role of physical activity against cardiovascular diseases (CVDs), including CHD and hypertension [5,6]

Summary

Introduction

With an estimated prevalence of 31%, physical inactivity is the fourth leading cause of death worldwide [1], contributing to premature death (10%), coronary artery disease (6%) and type 2 diabetes mellitus (7%) [2]. In 1953, Jeremy Morris pioneered the epidemiology of physical inactivity by comparing the mortality rate for coronary heart disease (CHD) in bus drivers versus more active bus conductors [3]. Physical inactivity occurs more commonly in high-income countries than low-income countries [9]. Physical inactivity varies greatly between different regions of the World Health Organization (WHO), ranging from 17% in Southeast Asia to 43% in the Americas [9]. Physical inactivity is a leading risk factor for cardiovascular and other noncommunicable diseases in high-, low- and middle-income countries. The reported national prevalence of physical inactivity is relatively low, studies in urban and peri-urban localities have always shown higher prevalence. This study aimed to measure physical activity in three domains—work, travel and leisure—in a peri-urban community and assess its variations across different sociodemographic correlates

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