Background: Low birth weight (LBW), defined as a live birth weighing less than 2500 g, is a significant public health problem in India. The complex nature of this problem is not fully understood. Moreover, significant disparities in LBW prevalence not only documented across various socio economic groups but across states and districts as well. The identification of spatial patterns of LBW and its determinants is important for understanding epidemiology of this public health challenge. Objective: This paper examines the determinants and spatial patterns of Low birth weight prevalence spatial pattern of LBW and its determinants in India. Methods: Using fourth round of National Family Health Survey data, regression and spatial analysis have been performed through STATA, ArcGIS and GeoDa software. Results: The result indicates lower odds of LBW prevalence among educated mothers, mothers who have more than 4 ANC visit, mothers who took IFA tablets during pregnancy, mothers with normal BMI and mothers with age above 20 years. The Moran's I for LBW is 0.543. It indicates high spatial autocorrelation in LBW over the districts of India The bivariate LISA maps obtained indicate spatial distribution of LBW and independent variables systematically contrasts the districts of central and eastern India (e.g. in Uttar Pradesh) with those of the extreme south (e.g. in Tamil Nadu, Kerala, etc.). Conclusion: Our findings reveal greater attention towards maternal and child health care especially for the backward districts in the states of Uttar Pradesh (UP), Madhya Pradesh (MP), Bihar and Rajasthan are needed. Several maternal and social factors leads to the occurrence of low birth weight. Emphasis should be placed on improving the nutritional status of the mothers.

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Background India suffers from a high burden of diarrhoea and other water-borne diseases due to unsafe water, inadequate sanitation and poor hygiene practices among human population. With age the immune system becomes complex and antibody alone does not determine susceptibility to diseases which increases the chances of waterborne disease among elderly population. Therefore the study examines the prevalence and predictors of water-borne diseases among elderly in India. Method Data for this study was collected from the Longitudinal Ageing Study in India (LASI), 2017–18. Descriptive statistics along with bivariate analysis was used in the present study to reveal the initial results. Proportion test was applied to check the significance level of prevalence of water borne diseases between urban and rural place of residence. Additionally, binary logistic regression analysis was used to estimate the association between the outcome variable (water borne diseases) and the explanatory variables. Results The study finds the prevalence of water borne disease among the elderly is more in the rural (22.5%) areas compared to the urban counterparts (12.2%) due to the use of unimproved water sources. The percentage of population aged 60 years and above with waterborne disease is more in the central Indian states like Chhattisgarh and Madhya Pradesh followed by the North Indian states. Sex of the participate, educational status, work status, BMI, place of residence, type of toilet facility and water source are important determinants of water borne disease among elderly in India. Conclusion Elderly people living in the rural areas are more prone to waterborne diseases. The study also finds state wise variation in prevalence of waterborne diseases. The elderly people might not be aware of the hygiene practices which further adhere to the disease risk. Therefore, there is a need to create awareness on basic hygiene among this population for preventing such bacterial diseases.

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This article seeks to provide an overview of the evolution and analyses the changing composition of trade between India and China over the period 1983–2017. We find that Chinese exports are almost completely concentrated in manufactures, especially finished equipment goods, whereas Indian exports consist of both agriculture and manufactures and over time have shifted predominantly to intermediate goods. Further, both the countries are exporting those commodities to each other in which they have a revealed comparative advantage, with China’s exports being more diversified. We employ vector error correction estimation and show that China’s exports to India are dependent on India’s household consumption expenditure, while India’ exports to China are correlated to Chinese manufacturing value added. Finally, we calculate the share of each country’s commodity-wise export to the partner in their respective total exports with a view to studying prospects for India–China trade. We conclude that for further trade expansion, diversification is extremely necessary, and Indian exports of inputs to Chinese industries need to change substantially to accommodate the changing nature of China’s industrial structure. JEL: F14, F15, O24

Introduction The continuum of care (CoC) throughout pregnancy, delivery and post-delivery has recently been highlighted as an integrated intervention programme for maternal, new-born, and child health. Existing literature suggests the importance of continuum of care (CoC) for improved maternal and child health outcomes. However due to unavailability of data at the lowest administrative levels, literature on spatial pattern of uptake of full CoC is lacking. The present study attempts to focus on the spatial analysis of CoC in maternal health care in India. Data and methods The study is based on the fourth round of National Family Health Survey data conducted in 2015–16 in India. The outcome variable used is maternal health continuum of care which includes- at least 4 ANC visits, delivery through skilled birth attendant and postnatal check-up within 48 hours of delivery. Univariate and bivariate Local Indicator of Spatial Association (LISA) maps have been generated to show the spatial pattern of CoC across 640 districts in India. We also employed spatial regression techniques to explore the determinants of CoC. Findings Percentage of women who followed full CoC was observed to be least for East Kameng (0.0%) district of Arunachal Pradesh and highest in North Goa district (90.4%). Majority of districts where uptake of full CoC was more than 80 percent were found concentrated in southern region on India. Equivalently, findings indicated a strong spatial clustering of full CoC with high-high clusters mostly concentrated in southern districts. Low-low district clusters are concentrated in the states of Uttar Pradesh, Bihar and Madhya Pradesh. For complete CoC the global Moran’s I is 0.73 indicating the spatial dependence. The spatial regression analysis suggested that modern contraceptive use, meeting with health worker, urbanization and secondary or above education for women have positive impact on the utilisation of CoC. Conclusion The spatial pattern indicates district level clustering in uptake of CoC among women. The study suggests policymakers and stakeholders to implement comprehensive interventions at sub-regional levels for ensuring the completion of CoC for women which acts as a preventive measure for adverse outcomes such as-maternal and child mortality.

Background: Work-related musculoskeletal disorders are widespread among workers in the weaving industry. The most affected body regions are the neck, shoulders, back, and wrist. The present study attempts to understand risk factors for MSDs in various body region among handloom and power loom weavers. Method: A cross-sectional household survey was conducted on a sample of 364 weavers during November 2019 to February 2020. The survey instrument for measuring musculoskeletal symptoms was adopted from a standardised Nordic questionnaire. The impact of the occupation of weaving on MSDs was analysed using binary logistics regression. Results: The 12-month prevalence of MSDs was higher among handloom weavers compared to power loom weavers, particularly in the upper back (84-45%), lower back (82-50%), knee (60-35%), and shoulder (76-42%) respectively. Similar patterns were observed in the 12-month prevalence of MSDs, which prevented regular activity inside or outside the home. Analysis suggests that the occupation of weaving raises the risk of MSDs particularly in the shoulder (OR: 4.52, C.I.: 2.63-7.76), lower (OR: 6.9, C.I.: 3.79-12.54) and upper back (OR: 5.63, C.I.: 3.19-9.95). Older age and long years of working are significant risk factors for MSDs. Conclusions: The findings suggest a relatively higher prevalence of MSDs among handloom weavers, particularly in the upper back, lower back and shoulder, compared to Powerloom weavers. Preventive measures and treatment to minimise the burden of MSDs among handloom weavers are strongly recommended.