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Saving Lives With Better Gestational Age Estimation
Background (brief): 1. Burden: Bangladesh has a high maternal (194 per 100,000 live births) and newborn mortality (28 per 1000 live births). In 2010, prematurity represented \~14% of all births and directly and indirectly contributed to 45% of all neonatal deaths. Gestational age (GA) is a key determinant of newborn survival and long-term impairment. Accurate estimation of GA facilitates timely provision of essential interventions to improve maternal and newborn outcomes. 2. Knowledge gap: Last menstrual period (LMP) is a simple, low-cost self reported information, recommended by the World Health Organization for estimating gestational age but has issues of recall mainly among poorer, less educated women and women with irregular menstruation, undiagnosed abortion, and spotting during early pregnancy. Several studies have noted that about 20-50% of women cannot accurately recall the date of LMP. 3. Relevance: The goal of this study is to improve maternal and newborn outcomes by increasing the accuracy of gestational age estimation, using menstrual based dating, that is vital for providing timely and necessary obstetric and newborn care interventions. The study will determine the efficacy of three community based interventions using e-platform targeted to improve the recall and reporting of the date of last menstrual period in a rural resource poor setting. The innovative e-platform based interventions, if successful, can provide substantial evidence to scale-up in a low resource setting where e-Health and m-Health initiatives are proliferating with active support from all sectors in policy and implementation. Hypothesis : 1. Implementation of conventional and e-platform based interventions will lead to a 30% improvement in recall of the date of the LMP in adolescent girls and married women in rural Bangladesh. 2. Intervention triggered improvement in LMP date recall among pregnant women in rural Bangladesh will improve the accuracy in GA estimation. Objectives: T
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