Socio-demographic and infrastructural variables influencing maternal risk concentration among ever-married women of reproductive age in rural West Bengal, India.

BACKGROUND: The risk of a woman dying as a result of pregnancy or childbirth during her lifetime is about one in six in the poorest parts of the world. OBJECTIVES: The present study aims to determine prevalence of maternal risk and the influencing variables among ever-married women belonging to the reproductive age group (15-49) of Birbhum district, West Bengal. METHODS: A cohort-based retrospective cross-sectional study was carried out among the sample of 229 respondents through a purposive stratified random sampling method and a pre-designed semi-structured questionnaire. The ordinal logistic regression (OLR) model was taken as a tool of assessment. Before developing the proportional OLR model, we have checked the multicollinearity effect among the predictors and the first-order effect modifier was evaluated as well. We performed data analysis using SPSS version 26. RESULTS: The result shows that illiterate women (Odds ratios [OR] = 2.81, 95% CI, 0.277-1.791), from lower standard of living (OR = 1.14, 95% CI, -0.845-1.116), married before the age of 15 years (OR = 21.96, 95% CI, -0.55-6.73) and between the age of 15-18 years (OR = 24.51. 95% CI, -0.45-6.85) are more likely to be affected by the higher concentration of maternal risk. Other important predictor is the time of pregnancy registration. Considering the transport and related en-route causalities, the result portraying a clear picture where the distance and travel time becoming significant factors in determining the concentration of maternal risk. CONCLUSION: Incidences of child marriages should be restricted. Eradicating factors influencing an individual's decision to seek care would be an essential contribution in excluding the dominant maternal risk factors.

Comparative assessment of soil quality dynamics using SQI modelling approach: a study in rice bowl of West Bengal, India.

The study attempted to evaluate the agricultural soil quality using the Soil Quality Index (SQI) model in two Community Development Blocks, Ausgram-II and Memari-II of Purba Bardhaman District. Total 104 soil samples were collected (0-20 cm depth) from each Block to analyse 13 parameters (bulk density, soil porosity, soil aggregate stability, water holding capacity, infiltration rate, available nitrogen, available phosphorous, available potassium, soil pH, soil organic carbon, electrical conductivity, soil respiration and microbial biomass carbon) in this study. The Integrated Quality Index (IQI) was applied using the weighted additive approach and non-linear scoring technique to retain the Minimum Data Set (MDS). Principal Component Analysis (PCA) identified that SAS, BD, available K, pH, available N, and available P were the key contributing parameters to SQI in Ausgram-II. In contrast, WHC, SR, available N, pH, and SAS contributed the most to SQI in Memari-II. Results revealed that Ausgram-II (0.97) is notably higher SQI than Memari-II (0.69). In Ausgram-II, 99.72% of agricultural lands showed very high SQI (Grade I), whereas, in Memari-II, 49.95% of lands exhibited a moderate SQI (Grade III) and 49.90% showed a high SQI (Grade II). Sustainable Yield Index (SYI), Sensitivity Index (SI) and Efficiency Ratio (ER) were used to validate the SQIs. A positive correlation was observed between SQI and paddy ( R2 = 0.82 & 0.72) and potato yield (R2 = 0.71 & 0.78) in Ausgram-II and Memari-II Block, respectively. This study could evaluate the agricultural soil quality and provide insights for decision-making in fertiliser management practices to promote agricultural sustainability.

Determination of Soil Quality Index of agricultural land adjacent to industrial sites of Jamuria C.D.Block, Paschim Bardhaman District, West Bengal.

A healthy soil is crucial for food security, but human activities, particularly industrialization, are degrading the soil's quality. This study aims to assess and compare the Soil Quality Index (SQI) at three industrial sites: the iron and steel industry, the open cast coal mining industry, and the brick kiln industry, along with a control field. To measure the SQI, the weighted additive method was applied to the nine selected physico-chemical properties of soil: soil temperature, soil moisture, Bulk Density, pH, N, P, K, OC, and EC. Principal Component Analysis coupled with multiple correlation methods was used to determine the Minimum Data Set. The most dominant factors near the iron and steel industrial site are soil temperature, N, K, and EC, while N, OC, soil moisture, P, K, and EC are the most significant factors near the open cast coal mine. In the case of the brick kiln industrial site, soil moisture, OC, K, soil temperature, and P have the highest loadings. The calculated SQI indicates that the quality of soil is in better condition in the control field (0.6475), while the soil adjacent to the coal mining industrial site (0.1426) is in the worst state, followed by the iron and steel industrial site (0.1611) and the brick kiln industrial site (0.289). To attain sustainable agricultural practices in industrial landscapes, efficient management of nutrient contents and phytoremediation can be helpful.

Cyclone-induced coastal vulnerability, livelihood challenges and mitigation measures of Matla-Bidya inter-estuarine area, Indian Sundarban.

Indian Sundarban is highly susceptible to tropical cyclones and resultant impacts such as storm surge-induced floods, embankment breaching, and saline water intrusion. It affects life and livelihood in severe ways. Mitigation and policy measures are therefore very important, based on information gathered at the grassroots level. Hence, this study is designed to assess inter-village variation in cyclone vulnerability, considering physical vulnerability, social vulnerability, and mitigation capacity. This study also highlights livelihood challenges faced by coastal dwellers. Geospatial and quantitative methods were used to assess the composite vulnerability index (CVI). Remote sensing data and climatic data were integrated to assess physical vulnerability and various socioeconomic data were incorporated to determine the social vulnerability. Moreover, an intensive field survey (2020-2021) was also conducted to understand the livelihood challenges of local people and accordingly suggest mitigation measures to cope with natural hazards. According to this analysis, nearly 18% of the total population living in the southern and eastern parts of the Matla-Bidya inter-estuarine area (MBI) are extremely vulnerable (CVI > 0.544) due to their geographical location and high exposure to coastal hazards. Almost 51% of the total populations inhabited in 46% of the total MBI villages are experiencing high to moderate vulnerability. Conversely, MBI villages in the northern part, where 32% of the total population lives, show low vulnerability (CVI < 0.387) due to less exposure and high resilience. Coastal low-lying villages are often hardest hit by tropical cyclones. Therefore, effective mitigation strategies and coping mechanisms are essentially needed to reduce the adverse impacts of cyclones.