Nutritional status of tribal and non-tribal adults in rural Bangladesh: A comparative study.

BACKGROUND: Nutritional status is an important indicator of health status among adults. However, to date, there exists scanty information on the nutritional status of tribal populations of Bangladesh. The aim of the study was to investigate the nutritional status of tribal (T) and non-tribal (NT) adult people living in the rural area of Rajshahi district, Bangladesh. METHODS: A total of 420 (72 T and 348 NT) households were studied. The samples were selected using multistage stratified sampling with proportional allocation. The nutritional status of adults was measured using body mass index (BMI). Descriptive statistics, t-test, ANOVA and Z-proportional test were utilized for data analysis. RESULTS: The study revealed that 8.3% and 9.2% of T and NT men were suffering from under nutrition respectively, while the corresponding figures in women were 12.5% and 10.1% respectively. Overall, 11.1% and 27.0% men, and 13.9% and 29.3% women T and NT were over-nourished respectively. The rate of over nutrition among T was significantly (p<0.05) higher than NT for both sexes. The mean weight and BMI of the NT men were significantly (p<0.01) higher than T men. The mean weight, height and BMI of NT women were higher (p<0.05) than T women. ANOVA demonstrated that the variation in BMI among education levels of NT men and the variation among occupation for both ethnicities were significant (p<0.01). The variation in BMI among education levels and occupation of T and NT women were significant (p<0.05), moreover ordinal logistic regression model demonstrated that hygienic toilet facilities and father's occupation were predictors of nutritional status. The interaction effects of education and occupation, and education and household monthly income on BMI were significant (p<0.01) for T men and both T and NT women (p<0.05). CONCLUSIONS: The prevalence of over-nutrition among NT is higher than T for both sexes. Some socio-economic and demographic factors were found as predictors of malnutrition. At least 12 of the 17 Sustainable Development Goals (SDGs) contain indicators that are highly related to nutrition, our findings can help Bangladesh Government for achieving SDGs by 2030. Appropriate nutritional intervention and awareness programmes can be initiated by the Government to ameliorate the burden of malnutrition among adults in the country.

Robust regression based genome-wide multi-trait QTL analysis.

In genome-wide quantitative trait locus (QTL) mapping studies, multiple quantitative traits are often measured along with the marker genotypes. Multi-trait QTL (MtQTL) analysis, which includes multiple quantitative traits together in a single model, is an efficient technique to increase the power of QTL identification. The two most widely used classical approaches for MtQTL mapping are Gaussian Mixture Model-based MtQTL (GMM-MtQTL) and Linear Regression Model-based MtQTL (LRM-MtQTL) analyses. There are two types of LRM-MtQTL approach known as least squares-based LRM-MtQTL (LS-LRM-MtQTL) and maximum likelihood-based LRM-MtQTL (ML-LRM-MtQTL). These three classical approaches are equivalent alternatives for QTL detection, but ML-LRM-MtQTL is computationally faster than GMM-MtQTL and LS-LRM-MtQTL. However, one major limitation common to all the above classical approaches is that they are very sensitive to outliers, which leads to misleading results. Therefore, in this study, we developed an LRM-based robust MtQTL approach, called LRM-RobMtQTL, for the backcross population based on the robust estimation of regression parameters by maximizing the ß-likelihood function induced from the ß-divergence with multivariate normal distribution. When ß = 0, the proposed LRM-RobMtQTL method reduces to the classical ML-LRM-MtQTL approach. Simulation studies showed that both ML-LRM-MtQTL and LRM-RobMtQTL methods identified the same QTL positions in the absence of outliers. However, in the presence of outliers, only the proposed method was able to identify all the true QTL positions. Real data analysis results revealed that in the presence of outliers only our LRM-RobMtQTL approach can identify all the QTL positions as those identified in the absence of outliers by both methods. We conclude that our proposed LRM-RobMtQTL analysis approach outperforms the classical MtQTL analysis methods.

Regression based fast multi-trait genome-wide QTL analysis.

Multivariate simple interval mapping (SIM) is one of the most popular approaches for multiple quantitative trait locus (QTL) analysis. Both maximum likelihood (ML) and least squares (LS) multivariate regression (MVR) are widely used methods for multi-trait SIM. ML-based MVR (MVR-ML) is an expectation maximization (EM) algorithm based iterative and complex time-consuming approach. Although the LS-based MVR (MVR-LS) approach is not an iterative process, the calculation of likelihood ratio (LR) statistic in MVR-LS is also a time-consuming complex process. We have introduced a new approach (called FastMtQTL) for multi-trait QTL analysis based on the assumption of multivariate normal distribution of phenotypic observations. Our proposed method can identify almost the same QTL positions as those identified by the existing methods. Moreover, the proposed method takes comparatively less computation time because of the simplicity in the calculation of LR statistic by this method. In the proposed method, LR statistic is calculated only using the sample variance-covariance matrix of phenotypes and the conditional probability of QTL genotype given the marker genotypes. This improvement in computation time is advantageous when the numbers of phenotypes and individuals are larger, and the markers are very dense resulting in a QTL mapping with a bigger dataset.

Prevalence and associated factors of contraceptive discontinuation and switching among Bangladeshi married women of reproductive age.

INTRODUCTION: Contraceptive discontinuation is a worldwide incident that may be connected with low incentive to avoid pregnancy. Contraceptive discontinuation highly contributes to unplanned pregnancy and unwanted births. OBJECTIVES: The objective of this study was to observe the prevalence of discontinuation and switching of contraceptive methods among Bangladeshi married women. In addition, the sociodemographic factors associated with contraceptive discontinuation and switching were assessed. METHODS: Secondary cross-sectional data was used in this study. A total of 16,273 married Bangladeshi women of reproductive age (15-49 years) were considered in the present study, from the Bangladesh Demographic and Health Survey, 2011. Logistic regression models were used to determine the relationships between key sociodemographic factors and user status. RESULTS: The prevalence of discontinuation and switching of contraceptive method among women were 38.4% and 15.4%, respectively. The logistic regression model demonstrated that women in early reproductive years (25-29 years and 30-34 years) significantly more often (odds ratio [OR] =0.84 and 0.71, respectively) discontinued use of contraceptives. Significantly higher rates of discontinuation were pronounced among women who used the pill (OR =0.72) and injectable contraception users (OR =0.60), had small family size (OR =0.49), lived in a rural community (OR =1.65), and who were less educated (OR =1.55). CONCLUSION: Contraceptive discontinuation may reflect an association among less education, currently married, and smaller family size. Awareness of contraceptive methods can decrease the burden of unplanned pregnancies and thus progresses the family planning program.