Background/Objectives: This study aims at examining the urban–rural differentials in the effects of socioeconomic predictors on underweight and obesity of ever-married women in Bangladesh. The effect of malnutrition and other risk factors on non-communicable diseases is also examined. Subjects/Methods: The information regarding nutritional status, socioeconomic and demographic background, and non-communicable diseases of ever-married women was extracted from the nationally representative, cross-sectional Bangladesh Demographic and Health Survey (BDHS 2011) data set. Both bivariate (χ² test) and multivariate (multinomial logistic regression model) analyses were performed in determining the risk factors of malnutrition. The effect of malnutrition and associated risk factors on non-communicable diseases was determined using binary logistic regression models. Results: The overall prevalence as well as the effects of individual risk factors of malnutrition differ in urban and rural settings. Regional differentials in the prevalence of underweight were statistically significant only for rural areas. In rural and urban settings, women from households with poor economic status were 67% (odds ratio (OR) 0.33, 95% CI 0.26–0.43) and 81% (OR=0.19, 95% CI 0.13–0.29) less likely to be overweight, respectively, with respect to those from affluent households. Women from the Rangpur division were significantly more likely to suffer from anemia (OR=1.41, 95% CI 1.13–1.77) and hypertension (OR=1.67, 95% CI 1.19–2.34) than those from the Sylhet division (reference division). With respect to those considered as underweight, women who were categorized as overweight were 0.47 (OR=0.53, 95% CI 0.43–0.65) times less likely to suffer from anemia, and 1.83 (OR=2.83, 95% CI 1.99–4.02) and 1.70 (OR=2.70, 95% CI 2.09–3.50) times more likely to suffer from diabetes and hypertension, respectively. Conclusions: Rural–urban differentials in the effects of individual risk factors of malnutrition were observed. Wealth status of households and nutritional status of women showed significant effect on the prevalence of anemia, diabetes and hypertension.

Understanding the historical and future spatio-temporal changes in climate extremes and their potential risk to rice production is crucial for achieving food security in Bangladesh. This paper presents results from a study on trend analysis for 13 climate metrics that significantly influence rice production. The analysis was conducted using the non-parametric Mann-Kendall test and the Theil-Sen slope estimator methods. The study included data from all available weather stations in Bangladesh and the assessment was done for both the wet (May to October) and dry (November to April) seasons, which cover the growing seasons of the country’s three types of rice: Aus, Aman and Boro. Results show significant decreasing trends for wet season rainfall (>12 mm/season/year in some stations) in the central and north regions. In addition, dry season rainfall is decreasing significantly in many areas, whilst dry season dry spells are increasing throughout Bangladesh. Decrease in rainfall in some of these areas are of concern because of its impacts on rainfed Aus rice and in the sowing/planting of rainfed Aman rice and irrigated dry season Boro rice. The maximum temperatures in the wet season are increasing throughout the country at 0.5°C every ten years, significantly at most of the climate stations. The analysis shows that the number of days with temperature >36°C has significantly increased in 18 stations over the last three decades, which implies a serious risk to Aman rice yield. The current maximum temperatures (both in the wet and dry seasons) are higher than the optimum temperature ranges for rice production, and this will have likely adverse effects on yield in the face of climate change with increasing temperatures. The results herein have practical implications for planning appropriate adaptation policies to ensure food security in the country.

Objectives The present study aims to estimate the incidence of preventable infectious diseases or associated symptoms among young children in Bangladesh and also determine the factors affecting these conditions. The study hypothesised that various background characteristics of children as well as their parents influence the incidence of morbidity of children aged below 5 years. Setting The study used data from the most recent nationally representative cross-sectional Bangladesh Demographic and Health Survey (BDHS) conducted in 2011. Participants A total of 7550 children aged below 5 years during the survey from mothers aged between 12 and 49 years are the participants of the study. Results In general, younger children were more likely to suffer from multiple health conditions than their older counterparts. Children belonging to households classified as poor (OR=1.425, 95% CI (1.130 to 1.796)) or middle (OR=1.349, 95% CI (1.113 to 1.636)) faced greater risk of illness than those from well-off households. A combination of source and treatment practices of drinking water showed a significant impact on incidence of childhood morbidity. Children from households using untreated non-piped water were 85.8% (OR=1.860, 95% CI (1.269 to 2.728)) more likely to suffer from comorbidity than those who treat their piped drinking water. However, we observed that water treatment alone has no impact unless the water itself was sourced from a pipe. Conclusions Accelerated programmes promoting access to safe drinking water along with water treatment practices, and better household environment may prove effective in reducing the incidence of childhood morbidity in Bangladesh.

Statistical models for total monthly rainfall used for forecasting, risk management and agricultural simulations are usually based on gamma distributions and variations. In this study, we examine a family of distributions (called the Tweedie family of distributions) to determine if the choice of the gamma distribution is optimal within the family. We restrict ourselves to the exponential family of distributions as they are the response distributions used for generalized linear models (GLMs), which has numerous advantages. Further, we restrict ourselves to distributions where the variance is proportional to some power of the mean, as these distributions also have desirable properties. Under these restrictions, an infinite number of distributions exist for modelling positive continuous data and include the gamma distribution as a special case. Results show that for positive monthly rainfall totals in the data history for a particular station, monthly rainfall is optimally or near‐optimally modelled using the gamma distribution by varying the parameters of the gamma distribution; using different distributions for each month cannot improve on this approach. In addition, under the same model restrictions, monthly rainfall totals that include zeros are also well modelled by the same family of distributions. Hence monthly rainfall can be suitably modelled using one of two Tweedie distributions depending on whether exact zeros appear in the rainfall history. We propose a slight variation of the gamma distribution for use in practice. This model fits the data almost as well as the gamma distribution but admits the possibility that future months may have zero rainfall. Copyright © 2010 Royal Meteorological Society

Aim: The high incidence of acute respiratory infection (ARI)-related morbidity and mortality is a major public health concern in developing countries. This study aimed to quantify regional inequalities and the degree of association between childhood ARI and background factors. Methods: This study utilised information of 238 945 children aged below five years extracted from the Fourth Indian National Family Health Survey conducted in 2015–16. Inter-state and regional inequality in the prevalence of ARI were quantified and presented using a map of India and forest plot. The association of background characteristics and ARI was quantified using bivariate and multivariable binary logistic regression models. Results: Significant inequalities in the prevalence of childhood ARI were observed across the six regions of India. Considering the children from north-east region as a reference, those from north, central and east regions were 0.68, 1.02 and 0.57 times more likely to suffer from ARI. Comorbidity, sex, age and nutritional status of children were significantly associated with the prevalence of ARI. Conclusions: ARI remains a significant public health concern among Indian children. The results of this study showed that significant regional disparities in the prevalence of ARI exist in India. This study adds value to the better understanding of inequality patterns and quantifies within- and intra-region inequalities in the prevalence of ARI in India.