Correlates and inequality of underweight and overweight among women of reproductive age: Evidence from the 2016 Nepal Demographic Health Survey

Abstract

Introduction Understanding socio-economic correlates and inequality of underweight and overweight is crucial to develop interventions to prevent adverse health outcomes. Materials and methods We analysed Nepal Demographic and Health Survey 2016 data from 6,069 women aged 15–49 years. WHO cut-offs for Body Mass Index categorised as: underweight (<18.5 kg/m 2 ), normal weight (18.5kg/m 2 to 24.9kg/m 2 ) and overweight/ obesity (> = 25.0 kg/m 2 ) were used. We used multinomial logistic regression to explore associations of factors with Body Mass Index and concentration indices to estimate socio-economic inequalities. Results Higher risk of underweight was found in age group 15–19 (RRR 3.08, 95% CI: 2.29–4.15), 20–29 (RRR 1.64, 95% CI: 1.29–2.08) and in lowest (RRR 1.60, 95% CI: 1.03–2.47) and second wealth quintiles (RRR 1.77 (95% CI: 1.18–2.64). Education, occupation, urban/rural residence and food security were not associated with underweight (p>0.05). Lower risk of overweight/obesity was found in age group 15–19 (RRR 0.07, 95% CI: 0.05–0.10), 20–29 (RRR 0.40, 95% CI: 0.32–0.51), in manual occupation (RRR 0.58, 95% CI: 0.46–0.74) and in lower quintiles. Women with primary (RRR 1.91, 95% CI: 1.36–2.67), secondary education (RRR 1.42, 95% CI 1.00, 2.01) were at increased risk of overweight/obesity. Household food security and urban/rural residence were not associated with overweight/obesity (p>0.05). Socioeconomic inequalities were detected, with overweight/obesity strongly concentrated (concentration index: 0.380) amongst the higher quintiles and underweight concentrated (concentration index: -0.052) amongst the poorest. Conclusion Nutrition programmes should target younger and poor women to address undernutrition and higher wealth group women to address overnutrition. Equity based nutrition interventions improving socio-economic status of poor households may benefit undernourished women. Interventions to encourage physical activity as women age and among wealthier women as well as healthy eating for prevention of under- and over-nutrition are needed.

Prevalence and factors associated with double and triple burden of malnutrition among mothers and children in Nepal: evidence from 2016 Nepal demographic and health survey

“…Mothers who attended at least a secondary level of education had a higher risk of experiencing a double burden of malnutrition. This finding is supported by Rai et al, [33] who revealed that women who had primary/ secondary levels of education were more likely to be at risk of overweight/obesity. In contrast, various studies have also reported that the double burden of malnutrition is associated with a higher level of maternal education and wealth status [14,19,20].…”

Prevalence and factors associated with double and triple burden of malnutrition among mothers and children in Nepal: evidence from 2016 Nepal Demographic and Health Survey

“…Mothers who attended at least a secondary level of education had a higher risk of experiencing a double burden of malnutrition. This finding is supported by Rai et al, [36] who revealed that women who had primary/secondary levels of education were more likely to be at risk of overweight/obesity. In contrast, various studies have also reported that the double burden of malnutrition is associated with a higher level of maternal education and wealth status [16,21,22].…”

“…This study found that mothers from province number 2 were less likely to experience DBM compared with mothers from province 3. A possible reason could be that mothers from province number 2 are more likely to be of a lower socioeconomic status and consuming a less diverse diet with an estimated 29 % of minimum dietary diversity (MDD) [15] resulting in decreased likelihood of being overweight or obsese (11 %) [36,40]. According to the NDHS 2016 report, the prevalence of overweight/obesity was higher (35 %) in province number 3, as well as a higher consumption of diverse food groups with an estimated 64 % of MDD.…”

“…This province is Kathmandu, the largest city (and capital) of the country [40]. Overweight/obesity among mothers could be attributable to the shifting of the Nepalese diet away from locally available staple based foods, to modern fast food and processed food [41], in addition to sedentary lifestyles [36] which contributes to the highest prevalence of overweight and obesity in province number 3.…”

Association between the frequency of television watching and overweight and obesity among women of reproductive age in Nepal: Analysis of data from the Nepal Demographic and Health Survey 2016

“…Frequency of watching television was the main independent variable of this study, which was divided into the following three categories: (1) not watching television at all, (2) watching television less than once a week, and (3) watching television at least once a week [22]. The other covariates considered based on the literature review (which were found to be associated with overweight and obesity in previous studies) were age group [20], place of residence, province of residence [20], ecological region of residence [21], marital status [20], highest educational attainment [21], household wealth status [20], current employment status [24], parity [25], and number of household members in the family [26]. The categories of the covariates are mentioned in Table 1.…”