2020
DOI: 10.1136/bmjopen-2019-034321
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Differences in prevalence and associated factors of underweight and overweight/obesity according to rural–urban residence strata among women of reproductive age in Bangladesh: evidence from a cross-sectional national survey

Abstract: ObjectivesThis study aimed to investigate the differences in prevalence and factors influencing underweight and overweight/obesity stratified by region of residence among women of reproductive age in Bangladesh.DesignSecondary analysis of cross-sectional nationwide data.SettingThis study used Bangladesh Demographic and Health Survey 2014 data.ParticipantsA weighted sample of 16 478 women of reproductive age (15–49 years) were included in the analysis.Primary and secondary outcome measuresUsing the Asian-specif… Show more

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Cited by 39 publications
(49 citation statements)
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References 54 publications
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“…Similarly, women whose age group 25-34 years had lower odds of underweight compared to those who have 15-24 years of age. This finding is supported by other studies [33,36,[40][41][42]. The first explanation for this might be different in nutrition requirements.…”
Section: Plos Onesupporting
confidence: 88%
See 1 more Smart Citation
“…Similarly, women whose age group 25-34 years had lower odds of underweight compared to those who have 15-24 years of age. This finding is supported by other studies [33,36,[40][41][42]. The first explanation for this might be different in nutrition requirements.…”
Section: Plos Onesupporting
confidence: 88%
“…According to the 2011 Ethiopian demographic and health survey (EDHS), 27% of childbearing age women had severe or moderate underweight, which is similar to the 2005 DHS data [17]. Small-scale studies in Ethiopia showed that a high number of underweight prevalence among reproductive-age women; which is 47.9% in Tigray [18], 48.6% in Ziway Dugda district [19], 41.1% in Afar [20], and 17.9% in Debretabor [21]. Living in food-insecure households, low consumption of dairy products, have low meal frequency, low education level, unimproved source drinking water, and living in rural residences are responsible for the high levels of women undernutrition [18][19][20]22,23].…”
Section: Introductionmentioning
confidence: 68%
“…This finding aligns with previous studies [ 37 , 41 43 ]. This is expected as ever married women, compared to unmarried, are more exposed to pregnancy and childbirth that often lead to hastened hormonal or physiological body-weight changes that may lead to overweight [ 26 , 44 ]. Besides, literature has linked the rise in overweight to cultural or social perception about ideal body-weight in many sub-Saharan African countries [ 23 ].…”
Section: Discussionmentioning
confidence: 99%
“…For instance, wealth status usually predicts educational attainment [ 47 ]. It may also impact on employment status, contraceptive use or parity [ 44 ], though these are non-significant risk factors of unhealthy weight after accounting for other variables’ effects in this study. The higher educational level attained may boost employment opportunity and lead to rich wealth status, and consequently influence unhealthy weight.…”
Section: Discussionmentioning
confidence: 99%
“…It also varies in different demographic areas within countries and regions [ 11 , 13 ]. Underweight is higher in women residing in rural areas [ 14 , 15 ].…”
Section: Introductionmentioning
confidence: 99%