Preterm birth and neonatal mortality in selected slums in and around Dhaka City of Bangladesh: A cohort study.

BACKGROUND: Although under-five mortality has declined appreciably in Bangladesh over the last few decades, neonatal mortality still remains high. The objective of the study is to assess the level and determinants of preterm birth and the contribution of preterm birth to neonatal mortality. METHODS: Data for this study came from selected slums in and around Dhaka city, where; since 2015, icddr,b has been maintaining the Health and Demographic Surveillance System (HDSS). The HDSS data were collected by female Field Workers by visiting each household every three months; however, during the visit, data on the Last Menstrual Period (LMP) were also collected by asking each eligible woman to ascertain the date of conception. Gestational age was estimated in complete weeks by subtracting LMP from the date of the pregnancy outcome. In this study, 6,989 livebirths were recorded by HDSS during 2016-2018, and these births were followed for neonatal survival; both bivariate and multivariate analyses were performed. RESULTS: Out of total births, 21.7% were born preterm (before 37 weeks of gestation), and sub-categories were: 2.19% for very preterm (28 to 31 weeks), 3.81% for moderate preterm (32 to 33 weeks), and 15.71% for late preterm (34 to 36 weeks). The study revealed that preterm babies contributed to 39.6% of neonatal deaths; however, the probability of death was very high on the 1st day of birth (0.124 for very preterm, 0.048 for moderate preterm, 0.024 for late preterm, and 0.013 for term birth), and continued until the 3rd day. In the regression analysis, compared to the term neonates, the odds of neonatal mortality were 8.66 (CI: 5.63, 13.32, p<0.01), 4.13 (CI: 2.69, 6.34, p<0.01) and 1.48 (CI: 1.05, 2.08, p<0.05) respectively for very, moderate, and late preterm birth categories. The population attributable fraction for neonatal mortality was 23%, and sub-categories were 14% for very preterm, 10% for moderate preterm, and 6% for late preterm. CONCLUSIONS: Although urban slums are in proximity to many health facilities, a substantial proportion of preterm births contribute to neonatal deaths. So, pregnant women should be targeted, to ensure timely care during pregnancy, delivery, and post-partum periods to improve the survival of new-borns in general and preterm birth in particular.

COVID-19 Vaccine Hesitancy among Temporary Foreign Workers from Bangladesh.

The COVID-19 pandemic poses an extraordinary threat to the health, safety, and freedom of temporary foreign workers (TFWs). Highly effective vaccines against COVID-19 may hold an outsized benefit for TFWs, particularly those living in congregate settings where protective measures such as social distancing are not possible. While some studies of migrant destination countries have included migrants, no study to date has sought to understand variations in vaccine hesitancy among individuals in a single migrant source population across different destinations. Such a design is critical for understanding how the context of immigration affects levels of hesitancy among migrants from similar conditions of origin. This observational study leverages longitudinal data from an ongoing monthly rapid-response survey of TFWs from Bangladesh (n = 360). Overall vaccine hesitancy was 25%, with significant variation by host country. Multivariate analyses confirmed that immigration system factors and threat perception are the strongest predictors of COVID-19 vaccine hesitancy for TFWs. The predicted probability of hesitancy for an undocumented TFW was 0.405, while the predicted probability for those with valid visas was 0.207 (p < .01). The probability of being hesitant for TFWs who were worried about getting COVID-19 was 0.129 compared to 0.305 (p < .01) for those who were not worried. Results reveal low vaccine hesitancy among TFWs from Bangladesh with differences in location, undocumented status, COVID-19 threat perception, and level of worry about side effects. There could be relatively high returns for targeting vaccine access and distribution to TFWs because of their high levels of vaccine acceptance.

Selection bias in the link between child wantedness and child survival: theory and data from Matlab, Bangladesh.

We examine the potential effects of selection bias on the association between unwanted births and child mortality from 7,942 women from Matlab, Bangladesh who declared birth intentions in 1990 prior to conceiving pregnancies. We explore and test two opposing reasons for bias in the distribution of observed births. First, some women who report not wanting more children could face starvation or frailty; and if these women are infecund, the remaining unwanted births would appear more healthy. Second, some women who report not wanting more children could have social privileges in acquiring medical services, abortion, and contraceptives; and if these women avoid births, the remaining unwanted births would appear less healthy. We find (1) no overall effect of unwantedness on child survival in rural Bangladesh in the 1990s, (2) no evidence that biological processes are spuriously making the birth cohort look more healthy, and (3) some evidence that higher schooling for women who avoid unwanted births is biasing the observed sample to make unwanted births look less healthy. Efforts to understand the effect of unwantedness in data sets that do not control for complex patterns of selective birth may be misleading and require more cautious interpretation.