Impact of contraceptive counselling training among counsellors participating in the FIGO postpartum intrauterine device initiative in Bangladesh.

OBJECTIVE: To evaluate the impact of structured training given to dedicated family planning counsellors on postpartum intrauterine device (PPIUD) services across six tertiary hospitals in Bangladesh. METHODS: Family planning counsellors underwent structured training on postpartum family planning, PPIUD in particular, over a four-day period. Impact of training was evaluated by comparing PPIUD counselling rates, consent rates, insertion rates, and removal rates five months before and five months after the training, using data from women delivering in the participating facilities. RESULTS: A total of 27 622 women were included in this analysis: 11 263 (40.8%) before the training intervention and 16 359 (59.2%) after it. There was an increase in the proportion of women who were counselled (from 75.3% to 83.8%, P<0.001), and a small decrease in the proportion of women agreeing to have a PPIUD inserted following counselling (13.7% vs 12.9%, P=0.03). Overall insertion rate was similar before and after training (9.5% vs 9.8%, P=0.42), while removal rate reduced from 2.8% to 1.8% (P=0.41). CONCLUSION: Structured training had no impact on overall PPIUD insertion rate. However, it did impact numbers of women receiving counselling, perceived quality of the counselling received, and overall removal rates

Factors associated with teenage marital pregnancy among Bangladeshi women

<p>Abstract</p> <p>Background</p> <p>Teenage pregnancy is a public health concern both in developed and developing world. In Bangladesh, most of the first pregnancies occur immediately after marriage, especially among teenagers. Although women aged 15-29 years are the most fertility contributing women in Bangladesh, studies are not yet conducted on teenage pregnancy within this group of women. In the current study, an attempt had been made to identify the factors affecting teenage marital pregnancy in women aged 15-29 years.</p> <p>Methods</p> <p>A cross sectional survey was carried out in 389 women, selected with a convenience sampling technique. Participants were selected on the basis of two criteria, such as married women and age within 15-29 years. We excluded women aged more than 29 years as we attempted to conduct study within high fertility contributing women and with the assumption that they may provide data subjected to relatively high level of recall bias as marital pregnancy may be a longer past event to them. In the analysis, we applied bi-variate and multi-variate logistic regression technique to find out odds ratio of teenage marital pregnancy.</p> <p>Results</p> <p>Result revealed that 72.5% of the participants experienced first marital pregnancy during their teenage, with a mean age of 17.88 years (SD = 2.813). Multivariate logistic regression analysis revealed that participants aged 20-24 years had higher likelihood (OR 1.971, 95% CI 1.132 to 3.434), whereas participants aged 25-29 years had lower likelihood (OR 0.054, 95% CI 0.016 to 0.190) of experiencing teenage marital pregnancy compared to participants aged 15-19 years. In addition, participants desired for >2 children had significant higher odds (OR 3.573, 95% CI 1.910 to 6.684) and participants born in urban area had significant lower odds (OR 0.458, 95% CI 0.228 to 0.919) for teenage marital pregnancy.</p> <p>Conclusions</p> <p>Based on the findings, we conclude that in order to reduce teenage marital pregnancy, consideration should be given on women's desired number of children and birth place so that women's desired number of children is limited to within two children, and that rural women get increased working and other related opportunities that may contribute in delaying teenage pregnancy.</p

Bangladesh Health Service Delivery: Innovative NGO and Private Sector Partnerships

The recent health service delivery achievements in Bangladesh have been attributed, in part, to partnerships between the government and non?state actors and the early and rapid adoption of innovations. Through the analysis of two case studies, this article examines the factors contributing to successful partnerships for health market innovations in Bangladesh and the extent to which these innovations can contribute to market systems changes that benefit the poor. The first case examines an innovation which aims to address maternal and child health issues by creating access to information on prenatal and post?natal care through mobile phones. The other case illustrates how Bangladesh's leading NGO partnered with one of the largest pharmaceutical companies in Bangladesh to develop a model for rural distribution of a micronutrient food supplement, ‘sprinkles’, to tackle the problem of micronutrient deficiency in young children

Application of ordinal logistic regression analysis in determining risk factors of child malnutrition in Bangladesh

<p>Abstract</p> <p>Background</p> <p>The study attempts to develop an ordinal logistic regression (OLR) model to identify the determinants of child malnutrition instead of developing traditional binary logistic regression (BLR) model using the data of Bangladesh Demographic and Health Survey 2004.</p> <p>Methods</p> <p>Based on weight-for-age anthropometric index (Z-score) child nutrition status is categorized into three groups-severely undernourished (< -3.0), moderately undernourished (-3.0 to -2.01) and nourished (≥-2.0). Since nutrition status is ordinal, an OLR model-proportional odds model (POM) can be developed instead of two separate BLR models to find predictors of both malnutrition and severe malnutrition if the proportional odds assumption satisfies. The assumption is satisfied with low p-value (0.144) due to violation of the assumption for one co-variate. So partial proportional odds model (PPOM) and two BLR models have also been developed to check the applicability of the OLR model. Graphical test has also been adopted for checking the proportional odds assumption.</p> <p>Results</p> <p>All the models determine that age of child, birth interval, mothers' education, maternal nutrition, household wealth status, child feeding index, and incidence of fever, ARI & diarrhoea were the significant predictors of child malnutrition; however, results of PPOM were more precise than those of other models.</p> <p>Conclusion</p> <p>These findings clearly justify that OLR models (POM and PPOM) are appropriate to find predictors of malnutrition instead of BLR models.</p