Assessing the double burden of malnutrition among Bangladeshi reproductive‐aged women: A comparison between unconditional and conditional quantile regression

BACKGROUND AND AIMS: The coexistence of undernutrition and overnutrition creates a double burden of malnutrition (DBM) among women in Bangladesh. This study aimed to assess heterogeneous effects of sociodemographic factors on women's nutritional status using quantile regression (QR) models and to investigate the differences between the results of unconditional QR (UQR) and conditional QR (CQR) models. METHODS: A sample of 17 285 nonpregnant women aged 15 to 49 years was extracted from the latest Bangladesh Demographic and Health Survey, 2017‐2018. Women's nutritional status was determined using body mass index (BMI). The UQR and CQR were used to estimate the heterogeneous effects of sociodemographic factors on women's BMI. RESULTS: Results show that the estimated effects of sociodemographic factors varied across the BMI distribution. For the same quantile, the effects differed between UQR and CQR. For instance, education was significantly positively associated with BMI. In UQR, secondary educated women achieved an increase of 0.996 and 1.720 in BMI at 10th and 90th quantiles, respectively, compared to noneducated women, whereas conditional effects were 1.336 and 1.492 at 10th and 90th quantiles, respectively, in CQR. These results also indicate secondary education appeared to have a lesser (or higher) impact in the lower (or upper) tail of BMI distribution, and unconditional and conditional effects for the same quantile varied notably. Other factors such as women's age, occupation, household wealth, number of children ever born and household size, religion, and place of residence were significantly associated with BMI and showed heterogeneous effects. CONCLUSION: Overall, there is a need to focus on heterogeneous effects of factors on women's nutritional status. Patterns of unconditional heterogeneous effects would be more informative than conditional heterogeneous effects while studying factors' effects. These findings may aid in developing strategies targeting high‐risk groups to combat the double burden of malnutrition.