Obesity and associated type 2 diabetes and hypertension in factory workers of Bangladesh

Abstract

BackgroundRecent data suggest that the prevalence of obesity and its associate cardiometabolic risks are increasing in Bangladesh. Published data of obesity in Bangladeshi industry workers is scarce. The purpose of this study was to assess the prevalence of general and central obesity in Bangladeshi factory workers and their associations with diabetes and hypertension.MethodsA total of 791 male factory workers aged ≥20 years in capital Dhaka city of Bangladesh were investigated in a population-based cross-sectional survey. According to the International Association for the Study of Obesity and the International Obesity Task Force guidelines for Asian population, general obesity was defined as body mass index (BMI) ≥25 kg/m2, central obesity was defined as a waist circumference (WC) of ≥90 cm and waist hip ratio (WHR) of ≥0.90. Pearson’s correlation coefficient and logistic regression analysis were used to observe the association between anthropometric indices (BMI, WC and WHR) and cardiometabolic risk indicators (FBG, 2hBG, SBP and DBP).ResultsThe prevalence of overweight (BMI 23–24.9 kg/m2) and general obesity (BMI ≥25 kg/m2) in this study population was 29.8 and 43.5 % respectively. Central obesity defined by WC and WHR was 35.3 and 78.3 % respectively. Both general and central obesity were found to be significantly associated with diabetes and hypertension in separate logistic regression analyses.ConclusionThe prevalence of general and central obesity in Bangladeshi factory workers was high, and it was associated with diabetes and hypertension.

A comparison of Obesity and Some Cardiovascular Risk Factors between Male Employees of Gas Refinery, Petrochemical Plant, and Non-Industrial Workplaces

“…Also, the associations between BMI and FBG, serum TG and blood pressure in industrial employees were found to be higher than non-industrial employees. Thus, the results of this research agree with the findings of Bhowmik et al (18). Vangelova et al, assessed the prevalence of hypertension and dyslipidemia among male industrial workers (19).…”

“…Thus, the prevention of obesity among industrial staff of Iran can be useful for developing the associated diseases with obesity and the subsequent mortality in future (17). Bhowmik et al assessed the prevalence of obesity in 791 Bangladeshi male factory workers and its association with diabetes and hypertension (18). They reported a high prevalence of obesity (43.5%) and abdominal obesity (35%), and significant association between obesity and prevalence of diabetes and hypertension.…”

Prevalence of hypertension and its risk factor among textile workers in low-and-middle-income countries: A systematic review protocol

“…Furthermore, increasing age, alcohol consumption, family history of hypertension, BMI >25 kg/m2 and high waist-hip ratio were identified as a strong factor of hypertension among cotton workers (17). Similarly, a study conducted in Dhaka, Bangladesh notified that both general and central obesity were found to be significantly associated with hypertension (18).…”

“…These factors have negative impact on worker's cardiovascular health that will in turn effect their job performance (9). Chronic diseases make workers less productive, more prone to injury that leads to high suffering and adds huge financial and service challenges on health care systems (18,(24)(25)(26). Furthermore, it is witnessed that collective monetary losses related with the hypertension, & DM, in low and middleincome countries are estimated to be over $7 trillion during the years 2011-2025 that move millions of individuals underneath the poverty line (27).…”

Prevalence of hypertension and its risk factor among cotton textile workers in low-and-middle-income countries: A systematic review protocol

“…While, stress in job also have a negative impact on worker's cardiovascular health which in turn will affect their job performance [28]. However, the association between cotton dust and increased blood pressure may not be strong, as confounding factors and bias impact could not be excluded [18,29] Chronic diseases make workers less productive, more prone to injury that leads to significant suffering and, add huge financial and service challenges on health care systems [23,[30][31][32].…”