Awareness, treatment, and control of diabetes in Bangladesh: a nationwide population-based study.

OBJECTIVES: To examine awareness, treatment, and control of diabetes mellitus among the adult population in Bangladesh. METHODS: The study used data from the 2011 nationally representative Bangladesh Demographic and Health Survey (BDHS). The BDHS sample is comprised of 7,786 adults aged 35 years or older. The primary outcome variables were fasting blood glucose, diagnosis, treatment, and control of diabetes. Multilevel logistic regression models were used to identify the risk factors for diabetes awareness. RESULTS: Overall, age-standardized prevalence of diabetes was 9.2%. Among subjects with diabetes, 41.2% were aware of their condition, 36.9% were treated, and 14.2% controlled their condition. A significant inequality in diabetes management was found from poor to wealthy households: 18.2% to 63.2% (awareness), 15.8% to 56.6% (treatment), and 8.2% to 18.4% (control). Multilevel models suggested that participants who had a lower education and lower economic condition were less likely to be aware of their diabetes. Poor management was observed among non-educated, low-income groups, and those who lived in the northwestern region. CONCLUSIONS: Diabetes has become a national health concern in Bangladesh; however, treatment and control are quite low. Improving detection, awareness, and treatment strategies is urgently needed to prevent the growing burden associated with diabetes.

The influence of birth spacing on child survival in Bangladesh: a life table approach.

In this paper we have attempted to demonstrate the relationship between birth spacing and child survival in Bangladesh using data from the 2004 Bangladesh Demographic Health Survey (BDHS). We used standard life table techniques to estimate the probability of child survival and appropriate spacing of births. Logistic regression models were used to investigate the covariates, along with the birth interval that has significant influence on child survival. Study results showed that the probability of child survival was much lower when the preceding birth interval was less than 12 months, and it may be also impeded by a higher birth interval. Child survival probability was highest for a preceding birth interval of 5 years; thereafter, the probability declined. Results of the logistic regression model clearly showed that preceding birth interval was an important and strongly significant factor in explaining infant and child mortality. While education, current age, breastfeeding status and birth order were substantial and highly significant factors both in infant and child mortality, socio-economic factors such as occupation and socio-economic status showed a significant effect only on child mortality. Postponing another child (for a birth interval of 5 years and above) and proper spacing of births would have a noticeable effect in reducing the level of mortality.