Factors associated with underweight, overweight, and obesity in reproductive age Tanzanian women

Abstract

Background Underweight, overweight, and obesity are major public health challenges among reproductive-age women of lower-and middle-income countries (including Tanzania). In those settings, obesogenic factors (attributes that promote excessive body weight gain) are increasing in the context of an existing high burden of undernutrition. The present study investigated factors associated with underweight, overweight, and obesity among reproductive age women in Tanzania. Methods This study used 2015-16 Tanzania Demographic and Health Survey data (n = 11735). To account for the hierarchical nature of the data (i.e., reproductive age women nested within clusters), multilevel multinomial logistic regression models were used to investigate the association between individual-level (socioeconomic, demographic and behavioural) and community-level factors with underweight, overweight, and obesity. Results Reproductive age women who were informally employed (relative risk ratio [RRR] = 0.79; 95% confidence interval [CI]: 0.64, 0.96), those who were currently married (RRR = 0.59;

Multilevel exploration of individual- and community-level factors contributing to overweight and obesity among reproductive-aged women: a pooled analysis of Bangladesh Demographic and Health Survey, 2004–2018

“…Women's education has a positive relationship with the risk of being overweight/obese. Similar results have been reported in Bangladesh (23,26) and other countries such as Tanzania (22) , Nepal (9) , Malawi (19) and Ghana (27) . A possible reason could be that highly educated people lead a sedentary lifestyle (26) .…”

“…In this study, the overall pooled prevalence of overweight/obesity in the nationally representative Bangladeshi non-pregnant women was 35•2 %, and the prevalence rates of overweight and obesity were 24•3 % and 10•9 %, respectively. These values are higher than those in Nepal (9) and Tanzania (22) . Therefore, overweight/obesity among women remains a serious concern in Bangladesh.…”

“…In the context of residence, women who lived in a rural area were less likely to be overweight/obese than those who lived in an urban area. The association between place of residence and overweight and obesity is evident in past studies conducted in India (36) , Senegal (37) and low-and middle-income countries (22,38) . A possible reason could be that rural women are highly engaged in physical activities such as agricultural activities, homework and other manual work as their occupation.…”

“…These physical activities helped them reduce weight and hinder excessive weight gain (39) . Another possible reason could be that the availability of fast-food consumption, processed, packed and refrigerated foods is lower among rural women than among urban women (22) . Women from communities with high literacy were likely to be overweight/obese.…”

Socioeconomic Inequalities in Women’s Undernutrition: Evidence from Nationally Representative Cross-Sectional Bangladesh Demographic and Health Survey 2017–2018

“…To select the covariates relevant to the nutritional status of ever-married women, an extensive literature review was carried out [18,19,[21][22][23][24][25][26]. In this study, the covariates were as follows: household size was categorized into <5 members and ≥5 members; respondents' ages were categorized as 15-19 years, 20-24 years, 25-29 years, 30-34 years, 35-39 years, 40-44 years, and 45-49 years; respondents' marital statuses were categorized as "others (widowed/divorced/separated)" and "married"; the number of living children was categorized as "no child", "one child", "two children", and "three or more children"; the type of place of residence was categorized as "urban" and "rural"; respondents' current employment statuses were categorized as "unemployed" and "employed", respondents' education levels were categorized as "no formal education", "primary", and "secondary or higher", and administrative divisions (Barisal, Chattogram, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, and Sylhet) and wealth quintile (poorest, poorer, middle, richer, and richest) were also used.…”