Uttar Pradesh Research Articles

Heterogeneous effects of agricultural insurance on agricultural green development: evidence from Sub national economies of India

The current paper aims to assess the relative competitiveness of agricultural green development across 27 Indian states and explore the factors influencing this development. Given India's significant role as a global producer of various crops such as rice, wheat, sugarcane, cotton, and pulses, and with approximately 43.96 percent of the labour force engaged in agriculture, the sector's performance is crucial for achieving Sustainable Development Goals (SDGs). The green development index has been created through the entropy method by using seven variables, where Uttar Pradesh and Telangana demonstrate higher green competitiveness. Conversely, states like Himachal Pradesh, Uttarakhand, and Punjab exhibit lower levels of green competitiveness due to their elevated consumption of fertilizers and pesticides. To understand the determinants of agricultural green development competitiveness, Quantile regression has been employed. The findings highlight a positive relationship between (the endogenous variable) and Per capita income, Bank branches in rural areas, hectares of land insured and capital expenditure on agriculture whereas increased cropping intensity and power availability per capita has negative relationships. Furthermore, employing the Dumitrescu and Hurlin (2012) panel Granger causality test reveals that economic growth at the state level in India precedes and influences agricultural green development. This suggests a dynamic relationship wherein economic progress fosters advancements in agricultural sustainability.

Spider (Araneae: Arachnida) Fauna of Sohagi Barwa Wildlife Sanctuary, District Maharajganj, Uttar Pradesh, India

Spiders are known to be excellent indicators of the diversity and well-being of terrestrial populations, and they are vital components of any ecosystem in which they live. Unfortunately, there is very little information available about the systematics, diversity, and ecology of the spiders found at the Sohagi Barwa Wildlife Sanctuary. The current study was conducted from May 2023 to August 2024 in order to investigate the variety of spider fauna in the Sohagi Barwa Wildlife Sanctuary in Maharajganj, Uttar Pradesh, India. A total of 1012 specimens, representing 55 species across 39 genera and 16 families, have been collected. The South Chowk range has the most species richness, whilst the Nichlaul range had the lowest. Araneidae and Lycosidae were prevalent (17%), with Selenopidae (2%) being uncommon. Based on their guild stucture, the spiders were categorized into seven functional groups: stalkers, ambushers, scattered line weavers, ground runners, foliage runners, orb-web builders, and sheet-web builders. The flora and fauna found in these areas are also associated with the highest species richness. The results of this study offer current and helpful information about the variety of species present in the Sohagi Barwa Wildlife Sanctuary, and the knowledge might be applied to further spider research.

Efficacy of Essential Oils against Purple Blotch of Garlic (Allium sativum L.) Caused by Alternaria porri (Ellis) Cif

A research trial was carried out during Rabi season, 2023-24 at the Central Research Field, Department of Plant Pathology, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology And Sciences, Prayagraj, Uttar Pradesh. The experiment was conducted to evaluate the effect of different essential oils on purple blotch of garlic caused by Alternaria porri on disease intensity and yield. The trial was conducted using seven treatments viz. T1- neem oil (5%), T2- eucalyptus oil (5%), T3- clove oil (5%), T4- castor oil (5%), T5- mustard oil (5%), T6- mancozeb 75 WP (0.2%) and T0- control with each treatment replicating three times to manage the disease and also to evaluate the effect of treatments on the disease intensity and yield. . Results showed that all treatments significantly increased yield of garlic and reduced the intensity of disease. From the study of results, it was concluded that among all the treatments, the most effective in managing the disease was T6- Mancozeb (27.85%) followed by T1- Neem oil (34.76%), T3- Clove oil (37.66%), T2- Eucalyptus oil (37.83%), T4- Castor oil (39.49%) and T5- Mustard oil (40.25%) as compared to T0- Control (49.24%) and for influencing the yield was yield (t/ha.) was T6- Mancozeb (5.41) followed by T1- Neem oil (4.05), T3- Clove oil (3.83), T2- Eucalyptus oil (3.73), T4- Castor oil (3.56) and T5- Mustard oil (3.31) as compared to T0- Control (2.61).

Socioeconomic, Demographic, and Behavioral Factors Associated with Dengue Outbreak: An Observational Study from Eastern Uttar Pradesh, India.

Background: Clinical and epidemiological aspects of dengue have extensively been studied in India. However, limited data are available on social and behavioral aspects of dengue outbreak. We aimed to fill this gap and wish to study socioeconomic, demographic, and behavioral factors associated with dengue outbreak in the Gorakhpur region of eastern Uttar Pradesh, India. Methods: This retrospective observational study was conducted among dengue patients discharged from hospital. Data on sociodemographic, economic, and behavioral factors of dengue were collected telephonically using a structured questionnaire. Continuous and categorical variables were reported as mean ± SD and numbers (%), respectively. Logistic regression analysis was done to establish association between patient's characteristics, awareness, and preventive behavior. Results: Age group 19-45 years 156/232, males 159/232, urban residents 142/232, residing in pucca house 187/232, and from lower-income families 149/232 were mostly affected in this outbreak. Patients spent a median of Indian national rupees 20,000 on treatment. Only 10.8% of patients had Ayushman health insurance cards. Awareness about dengue infection was found in∼43% patients. Literates, middle income group, and professionals/semiprofessionals were significantly more aware about dengue disease, mosquito bite, and treatment than their counterparts. Travel history was significantly associated with dengue infection in the males of 19-45 years age group belonging to rural areas. Use of mosquito repellent, nets, wearing full sleeve clothes were significantly less in rural residents while barefoot walking was more frequently observed in this population. Use of mosquito repellent was significantly associated with income, and these were observed more in the middle-income group. Conclusion: People with low education level, residing in urban areas, residing in pucca houses, who travel frequently, and who belong to lower-income groups were majorly affected by this dengue outbreak. Less dengue awareness and not following preventive practices were found in them. Targeted health education campaigns in urban setting could prevent dengue and economic burden on these vulnerable groups.

Impact of leguminous crop residues on rice performance in diverse cropping systems in the alluvial soils of eastern Uttar Pradesh

In eastern Uttar Pradesh, the traditional rice-wheat cropping sequence has been identified as a factor contributing to unsustainable agricultural practices, resulting in low productivity and returns for small and marginal farmers. Crop diversification presents a viable solution to enhance productivity and ensure food and nutritional security for these farmers. A field experiment conducted under the All India Coordinated Research Project (AICRP) on Integrated Farming Systems (IFS) at Acharya Narendra Deva University of Agriculture and Technology, Ayodhya, U.P., India, from 2019-20 to 2021-22, evaluated the growth, yield attributes, and production potential of rice under ten rice-based cropping systems under irrigated medium-land conditions. The systems assessed included rice-wheat-fallow, rice-wheat-greengram, rice-frenchbean-greengram, rice-gram-cowpea, rice-mustard-greengram, rice-linseed-blackgram, rice-berseem-sudanchari, rice-oat-maize + cowpea, rice-cauliflower-okra, and rice-potato-cowpea (vegetable). The legume-based systems significantly enhanced plant height, which was attributed to the higher nitrogen availability from the decomposition of legume residues. Legume-based systems showed an increase in the number of leaves per hill and LAI, reflecting improved vegetative growth. Effective tiller production was higher in these systems, which contributed to superior panicle length, grain count, and grain weight. Among these systems, rice-frenchbean-greengram and rice-gram-greengram consistently outperformed the conventional system in terms of yield attributes and the yield of grain and straw. The integration of legume crops into rice-based sequences can improve soil fertility, promote better vegetative growth, and enhance yield, thereby contributing to more sustainable and productive rice cultivation.

Assessing Challenges and Sources of Dissatisfaction among Accredited Social Health Activists Employees

Accredited Social Health Activists (ASHAs) are integral to India’s healthcare system, particularly in rural and underserved areas like those in district Aligarh, Uttar Pradesh. They serve as community health workers who facilitate access to essential health services, but their roles often place them in vulnerable positions. Operating within patriarchal societies and situated at the lower levels of the healthcare hierarchy, ASHAs are prone to various forms of violence and harassment. Despite their crucial role, there is limited understanding of the specific challenges they face, particularly regarding harassment in their work environment. This study aims to identify the key challenges encountered by ASHA workers in the Aligarh district of Uttar Pradesh and sources of dissatisfaction faced by ASHAs. A cross-sectional survey was conducted involving a representative sample 150 of ASHAs across several blocks of in Aligarh of Uttar Pradesh. Data were collected through structured questionnaires and semi-structured interviews. The survey addressed various aspects, including working conditions, support from healthcare systems, remuneration, training, and community relations. In a study of 150 ASHA workers, key challenges include delays in incentives (70%), excessive workload (92%), and unsatisfactory training (71.3%). Many faces harsh working conditions (73.3%), harassment (95.3%), and high stress (89.3%). Issues like inadequate facilities (97%) and transportation difficulties (90.6%) further impact their performance and well-being. This study evaluates ASHA workers’ duties, challenges, and well-being. Despite their critical role, they face financial instability, inadequate facilities, harsh conditions, and harassment, including from hospital staff. Long travel, stigma, and social discrimination further impact their effectiveness and morale, emphasizing the need for better support and protective measures.

The impact of COVID-19 pandemic on fertility behaviour in Indian states: Evidence from the National Family Health Survey (2019/21).

The COVID-19 pandemic affected a broad spectrum of people's lives very quickly. Although the pandemic could influence people's fertility behaviours in several ways, there is little knowledge about such influence in diverse socioeconomic and cultural settings. This study investigated the impact of the COVID-19 pandemic on fertility behaviours and desires among women in a lower-middle-income country, India. Our study analyzed cross-sectional data from 13 states and union territories (UTs) in India that were surveyed in pre- and post-lockdown periods by the 2019/21 National Family Health Survey (NFHS). The data were analysed using the descriptive analysis technique and the multilevel logit model. All these analyses were performed using the technique developed for complex sample design. The poverty-stricken states of Uttar Pradesh and Jharkhand and the Odisha state with moderate socioeconomic status experienced a significant decrease in contraceptive use and non-significant changes in the desire for birth and sexual activities after the lockdown. Contraceptive use significantly increased after the lockdown in the rich states of Punjab, Delhi, and Tamil Nadu, as well as in the Arunachal Pradesh state with moderate socioeconomic status. The changes in fertility behaviours in Uttar Pradesh, Jharkhand, and Odisha may influence fertility positively, while those changes in Punjab, Delhi, Tamil Nadu, and Arunachal Pradesh may influence fertility negatively. At the aggregate level, there was a significant increase in desire for another child and a decrease in contraceptive use after the lockdown, which may influence fertility positively but can be compensated by reduced sexual activities. The influence of the fertility trends in the states with pro-natalist changes on India's recent fertility trend could be greater than those with anti-natalist changes, which can be better understood by analyzing reliable data from a couple of years following the 2019/21 NFHS.

Geographic disparities and determinants of full utilization of the continuum of maternal and newborn healthcare services in rural India

BackgroundTo further reduce maternal and neonatal mortality, it is essential for mothers and newborns to fully utilize all essential services within the continuum of maternal and newborn care. However, research on maternal and child health services in India has not sufficiently examined geographical disparities in the full utilization of these services and the factors influencing the full utilization, particularly in rural areas. This study aims to address this critical gap.MethodsUtilizing data from 130,312 mothers collected in the National Family Health Survey-5 (2019–21), this study employed spatial analysis to uncover geographical disparities in the full utilization of the continuum of maternal and newborn healthcare services in rural India. Additionally, binary logistic regression was used to identify the factors associated with this utilization.ResultsIn rural India, 54.3% mothers recieved four or more antenatal care visits, 88.6% received skilled birth attendance, and 75.5% of mothers and 79.8% of newborns received postnatal care within 48 hours of birth. However, only 43.5% mothers-newborn dyads in rural India utilized all four services of the continuum of maternal and newborn healthcare. There were significant geographical disparities in the full utilization of the continuum of maternal and newborn healthcare services. Hotspots were primarily identified in districts of southern states, western Maharashtra, and central Odisha, while cold spots were evident in the northeastern states of Arunachal Pradesh, Meghalaya, Assam, and Nagaland, as well as in the Empowered Action Group states of Bihar, Uttar Pradesh, and Jharkhand. Key determinants influencing the full utilization of the continuum of care in rural India included maternal education, household wealth, parity, health insurance coverage, and exposure to mass media. Specifically, the odds of fully utilizing the continuum of care were significantly lower among women without formal education (adjusted odds ratio = 0.60, 95% CI = 0.56–0.65), those from the poorest wealth quintile (0.65, 0.61–0.69), and mothers with six or more children (0.42, 0.37–0.47), compared to mothers with higher education, those in the richest wealth quintile, and mothers with a single child, respectively. Additionally, mothers from the southern region were more than twice as likely (2.11, 1.99–2.20) to fully utilize the continuum of healthcare services compared to mothers from the northern region.ConclusionThe significant geographical disparities in the full utilization of maternal and newborn healthcare services in rural India highlight the necessity for tailored, region-specific interventions. Future programs should focus on addressing the barriers to care by prioritizing vulnerable groups, including those who are poor, uninsured, less educated, adolescents, and women with high parity.

Quantitative Analysis of Entrepreneurial Attitudes in Technical (Engineering) Students: Evidence from Uttar Pradesh

Quantitative Analysis of Entrepreneurial Attitudes in Technical (Engineering) Students: Evidence from Uttar Pradesh

Application of Six Sigma metrics for assessing the quality management of biochemical analytes in the clinical laboratory

Background: Quality control (QC) is an important part of clinical laboratory management which evaluates and maintains the performance of the clinical laboratory. Six Sigma is a continuous quality improvement process which is widely applied in the health care industry mainly in clinical laboratories. Aims and Objectives: The study aimed to evaluate the performance of biochemical analytes in a clinical laboratory using Six Sigma metrics and to implement quality improvement interventions. Sigma value was analyzed using bias, coefficient of variation (CV), and total allowable error (TEa) for each analyte. The quality goal index ratio was calculated to identify specific types of errors to introduce targeted quality interventions. Materials and Methods: This quasi-experimental study was carried out at the Government Institute of Medical Sciences, Greater Noida, Uttar Pradesh. Internal QC (IQC) and external QC data were collected during the study period and analyzed. The CV, Bias, and TEa were used to calculate the sigma (σ) values for 20 biochemical analytes. Results: On retrospective data analysis, triglycerides-Level 1 (L1) and Level 2 (L2), and direct bilirubin-L2 showed a world-class performance (above 6σ) while 14 parameters were placed below average (<3σ) on sigma metrics. Prospective data analysis was performed following quality improvement intervention. Amylase, direct bilirubin, triglycerides and alanine transferase performed at world-class sigma metric for both the control levels (L1 and L2) whereas, Albumin and aspartate transferase showed above six sigma values for L2 control only. Five analytes out of 20 performed below average (<3σ) on sigma metrics, for which further continuous intervention will be carried out. Conclusion: Six Sigma metrics is a continuous improvement and monitoring program that should be implemented to achieve world-class quality performance.

Early identification of potentially low performing community health workers using an ensemble classification model

PurposeCommunity health workers (CHWs) are vital to addressing public health system limitations in developing countries. However, effective identification and support of underperforming CHWs remains a challenge. This study develops a predictive model to proactively identify underperforming CHWs, facilitating targeted interventions for improved CHW programmes.Design/methodology/approachWe developed a predictive model to identify underperforming CHWs in Uttar Pradesh, India. Data from 140,101 CHWs over a 12-month period was used to build, test and validate the model. Classification techniques, ensemble modeling and a model tuning algorithm were employed for accuracy optimization and early identification.FindingsLogistic regression, decision trees and random forests yielded the best performance. While ensemble models offered no significant performance improvements over the base models, the model tuning algorithm effectively increased prediction accuracy by 19 percentage points. This enabled early identification of poor-performing CHWs and high-risk CHW clusters early in the year.Practical implicationsThe developed model has significant potential to improve CHW programmes. It enables targeted support, feedback and resource allocation, leading to enhanced CHW performance, motivation and healthcare outcomes in the communities they serve. The model can provide personalised feedback to help CHWs overcome challenges and dynamic clustering facilitates proactive identification and tailored support for those at risk of underperformance.Originality/valueThis study is the first attempt to use predictive modelling to identify underperforming CHWs, advancing the nascent field of CHW performance analytics. It underscores the effectiveness of digital technologies and data in improving CHW programmes.

Effect of Integrated Sources of Nutrients on Growth, Yield and Economics of Cowpea (Vigna unguculata L.) var Ankur Gomati

A field experiment was conducted in randomized block design with 7 treatments and 3 replications to study the effect of fertilizers, organic manures, biochar and crop residues on growth. yield and economics of cowpea (Vigna unguiculata L.) in Inceptisols of Prayagraj, Uttar Pradesh, India in 2022. A research variety Ankur Gomati was taken for this research trial. Recommended doses of fertilizers (N, P2O5 and K2O @ 25, 75 and 60 kg ha-1) was applied with inorganic fertilizers (Zn and B), organic manures (FYM, vermicompost, neem cake and poultry manure), biochar and crop residues (rice straw and wheat straw). Growth parameters such as the maximum plant height 46.96 cm, 70.21 cm and 92.22 cm, maximum number of branch plant-1 5.82, 7.56 and 9.79, highest number of leaf plant-1 28.32, 30.56 and 32.22, highest length of leaf as 5.37 cm, 7.31 cm and 9.18 cm were recorded in T7 [RDF + Poultry Manure @2 t ha-1 + Biochar @2.5 t ha-1 + Vermicompost @2 t ha-1 + Neem Cake @500 kg ha-1] at 30 DAS, 55 DAS and 70 DAS respectively. And yield parameters such as high pod length as 21.72 cm and 20.01 cm, highest number of pods plant-1 35.52 and 35.75, highest number of seed pod-1 10.01 and 10.21 and highest test weight 27.12 g and 26.23 g were recorded in T7 [RDF + Poultry Manure @2 t ha-1 + Biochar @2.5 t ha-1 + Vermicompost @2 t ha-1+ Neem Cake @500 kg ha-1] at 55 DAS and 70 DAS respectively. Highest yield 160.12 q ha-1 were obtained in treatment T7 [RDF + Poultry Manure @2 t ha-1 + Biochar @2.5 t ha-1 + Vermicompost @2 t ha-1+ Neem Cake @500 kg ha-1]. Maximum gross return ₹ 2,41,680 was recorded in treatment T7 [RDF + Poultry Manure @2 t ha-1 + Biochar @2.5 t ha-1 + Vermicompost @2 t ha-1+ Neem Cake @500 kg ha-1]. Maximum B:C ratio (2.80) was recorded in T4 [RDF + Vermicompost @ 2 t ha-1 + Rice Straw @ 6 t ha-1]. But maximum net return (₹ 1,47,624.1) was recorded in treatment T4 [RDF + Vermicompost @ 2 t ha-1 + Rice Straw @ 6 t ha-1]. The yield and growth parameters also significantly increased with the application of the combination of organic and inorganic fertilizers.

Two decades of aerosol trends over India: seasonal characteristics and urban-rural dynamics

Abstract India faces significant air quality challenges, with one of the highest air pollution levels of any country in the world. Here, we examine two decades (2001–2019) of both particulate matter (PM2.5) concentration and aerosol optical depth (AOD) over the country. Increases are seen between the two decadal averages, for 2001–2010 and 2011–2019, in western India, particularly in the Indo-Gangetic Plain (IGP). IGP region, including Bihar, West Bengal, Jharkhand, and Uttar Pradesh, shows the highest increases in AOD (+0.03, 13%) and PM2.5, s (+8 µg m−3). Seasonal AOD patterns fluctuate, with the IGP experiencing the highest wintertime increase, especially in Bihar (+0.07). In summer, there are increases in AOD along the southern and eastern coastal areas. Monsoons cause a slight rise in AOD, except in Rajasthan. In the post-monsoon season, the IGP experiences a notable increase in AOD (+0.057, 25%), potentially driven by biomass burning in Bihar (+0.11) and Uttar Pradesh (+0.075). Dividing our study area into urban and peri-urban clusters (n = 2791), AOD is found to be similar, possibly due to advective mixing. However, the differences between urban and rural areas become more noticeable, especially in the second decade. Correlations between AOD and PM2.5, g vary across locations, with the highest found in Kanpur (R 2 = 0.61) and weaker in Delhi (R 2 = 0.42), highlighting the need for more ground monitoring. However, it suggests that satellite-derived AOD can generally be used to examine trends in PM2.5 over longer time frames.

A Strategic Health Index for Maternal and Child Wellbeing in Uttar Pradesh using MCDM

Maternal and child health (MCH) is a critical indicator of overall societal well-being, particularly in developing countries. The study presents a comprehensive analysis to evaluate MCH in Uttar Pradesh (UP), a state facing significant public health challenges. Using National Family Health Survey (NFHS-5) data on MCH indicators, we developed a health index to systematically assess and compare health status across various districts. The multi-criteria decision-making (MCDM) technique, specifically Criteria Importance Through Inter-criteria Correlation (CRITIC) and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is used to determine the importance of closeness of various criteria affecting MCH care, such as antenatal care, institutional delivery, postnatal care, immunization coverage and nutritional status. The overall performance of each district in terms of MCH was measured to develop a composite index based on the MCDM approach. In contrast, the indicator weights were determined by the CRITIC method. Some districts showed better performance on specific indicators, while others lagged. The resulting index provides a nuanced understanding of the regional disparities within UP, highlighting areas of urgent need for healthcare interventions. The findings underscore the importance of targeted policies and programs to improve MCH outcomes, contributing to the broader goals of sustainable development and public health enhancement in the region.. KEYWORDS :Maternal and child health, CRITIC, TOPSIS, Index.

Application of Mont Carlo Simulation and Artificial Neural Network Model to Probabilistic Health Risk Assessment in Fluoride-Endemic Areas

Groundwater contamination with fluoride is a considerable public health concern that affects millions of people worldwide. The rapid growth of urbanization has led to increase in groundwater contamination. The health risk assessment focuses on both acute and chronic health consequences as it investigates the extent and effects of fluoride exposure through contaminated groundwater. Fluoride exposure, especially in endemic locations, has serious health consequences, including dental and skeletal fluorosis. An accurate assessment of these hazards is essential for public health planning and mitigation actions. The present study uses Monte Carlo Simulation (MCS) and an Artificial Neural Network (ANN) model to perform a Probabilistic Health Risk Assessment on populations in fluoride-endemic areas. Analysis of the results of the study reveals that the concentration of fluoride ranged from 0.58 to 3.80 mg/L with an average of 2.30 mg/L across the Kasganj district, which was higher than permissible limits given by BIS and WHO. The highest value of hazard quotient of 3.29 for Children is found to be in the Durga Colony area, while the lowest value of the hazard quotient of 0.31 for adults is found to be in the Nadrai Gate area. The assessment of health risks revealed a high probability of non-carcinogenic disease from the consumption of groundwater containing fluoride. The ANN model has the R2 value of 0.9989 in training and 0.9870 in testing while RMSE value in training and testing was 0.02230 and 0.0267. The findings suggest that before being used, the groundwater in Kasganj, Uttar Pradesh, India, needs to be treated and made drinkable. The results emphasize the critical need for ongoing monitoring, public education initiatives, and implementing feasible mitigating techniques to lower fluoride exposure. The findings show that this hybrid model is excellent at addressing the numerous uncertainties associated with fluoride use, hence improving the reliability of health risk estimates in fluoride-endemic locations. The results offer vital information to help policymakers and local health officials create focused measures to safeguard public health in Kasganj.

Spatial Clustering of Infant Mortality in Uttar Pradesh, India

Infant mortality in India has significantly decreased over the past decade. Improvements in educational status, health, wealth and occupation have contributed to this reduction in infant mortality. Despite this decreasing trend, further reduction remains a major concern. Infant mortality serves as a prime indicator of sustainable development goals (SDGs). To accelerate the achievement of these goals, authorities need to focus on the effective deployment of resources. The purpose of this study is to determine the spatial distribution of infant mortality and understand the factors responsible for higher infant mortality rates. The study contains data from 8627 sampling units (as provided in Civil Registration System (CRS) records), representing the number of children born. Infant mortality rates were calculated, and a spatial statistic was used to identify clusters of total infant mortalities in space. A clustered pattern of areas with higher Infant mortality was observed. Hence, prioritizing these areas with higher Infant mortality and considering the responsible factors for interventions is advisable.. KEYWORDS :Spatial, Spatial-temporal, Clustering, Infant mortality.

Prevalence of metabolic syndrome and its risk factors among the government bank’s employees of district Bijnor, Uttar Pradesh: A cross-sectional study

ABSTRACT Background: Metabolic syndrome (MetS) involves having at least 3 out of 5 health conditions that increase the risk of cardiovascular disease, stroke, and type 2 diabetes mellitus. These conditions include increased blood pressure (BP), high blood sugar, excess body fat around the waist, and abnormal cholesterol or triglyceride levels. Each of these conditions is treatable with lifestyle changes and/or medication. Objective: 1). To find out the prevalence of MetS and various risk factors associated with it through MetS’s screening criteria. 2) To find out the health risk status and stress level among bank’s employees in the government sector. Material and Methods: A medical health camp was organised for all bank’s employees to rule out the various health-related disorders. Thus, 64 beneficiaries were participated. A detailed history was taken regarding their socio-demographic profile, risk factors affecting the MetS, and stress levels among each individual through the direct personal interview method. Results: As per MetS’s screening criteria (NCEP-ATP III), the prevalence of MetS was 7.81% among the bank’s employees. The various risk factors affecting the MetS are elevated serum triglyceride level, elevated fasting blood glucose (FBG), raised BP, enlarged WC, etc., The majority of individuals had a high risk of health status 27 (42.1%) and a moderate level of stress, i.e., 38 (59.4%), respectively. Most of the participants were hypertensive 49 (76.6%), diabetic 16 (28.6%), and obese 37 (57.8%). Conclusion: Common concerns of male gender, increasing age and BMI, sedentary lifestyle, stress and positive family history should be considered for early identification and appropriate intervention to fight against the growing MetS epidemic.

Fluoride and nitrate contamination in groundwater of Naini Industrial Area, Uttar Pradesh: assessing non-carcinogenic human health risk

Groundwater is the main source of drinking water globally; however, its quality has been deteriorated due to various geogenic and anthropogenic activities. The groundwater quality of Naini Industrial Area, Prayagraj was studied seasonally to evaluate the fluoride and nitrate contamination pertaining to human health risk assessment. The samples were collected from 60 locations in the pre- monsoon, monsoon, and post-monsoon season. The fluoride and nitrate were assessed with the help of Ion chromatography. The NO3– concentration exceeded the Indian drinking water quality standards in 27% of the groundwater samples. The NO₃⁻ contamination is predominantly associated with agricultural practices, while F⁻ can be linked to natural geological sources. The non-carcinogenic human health risk assessment was quantified by calculating the Hazard Quotient (HQ) and Hazard Index (HI) were calculated as per USEPA methodology for male, female and child population. The findings indicate that the child population is particularly susceptible to health risks associated with the ingestion of F– and NO₃⁻ through the drinking water pathway. Across all the sampled sites, the Hazard Index (HI) values varied from 0.10 to 12.3 for males, 0.09 to 10.6 for females, and 0.16 to 19.7 for children suggesting substantial risk to the local populace at more than half of the locations which is largely related to nitrate contamination. Thus, the study suggests that groundwater at many locations is unsuitable for drinking without treatment pertaining to the probable health risk they pose to consumers advocating upgraded water management plan for the residents.

Strategies to scale up the Technical, Allocative and Economic Efficiency of Major Millet Growing Farmers in India – A Primal System Approach

Millet farming, a sustainable and economically viable option for farmers, providing resilience against climate variability and market fluctuations. Despite the increasing significance of millets in agriculture, there is a notable research gap concerning the efficiency of their cultivation and its impact on input demand and costs. This study leverages data from CCPC for the AY 2021-22, focusing on major millets—Bajra, Jowar, and Ragi cultivated across various Indian states. The research aims to understand the technical, allocative, and economic inefficiencies in millet farming to enhance productivity and resource utilization. It is hypothesized that inefficiencies in millet cultivation significantly impact input demand and cultivation costs, and addressing these inefficiencies can lead to improved agricultural practices and yields. Employing primal Cobb-Douglas production function showed that human labor, seed quantity, and fertilizers positively impact millet cultivation. Technical inefficiency is a major issue with Bajra farmers in Gujarat, Haryana, Maharashtra, Rajasthan and Uttar Pradesh. For Jowar, farmers in Andhra Pradesh, Karnataka, Madhya Pradesh, Maharashtra, Rajasthan and Tamil Nadu are facing significant inefficiencies. In contrast, Karnataka and Odisha efficiently produce Ragi. Allocative inefficiency is noted in the over-utilization of animal and machine labor and fertilizers in Bajra cultivation, while these inputs are under-utilized in Jowar and Ragi cultivation. Both technical and allocative inefficiencies lead to increased input demand and higher cultivation costs across all three millets. The findings underscore the importance of state-specific strategies to address inefficiencies. These insights can guide policymakers in developing customized strategies to optimize millet cultivation, enhance yields and reduce costs.

Application of discriminant function analysis for forecasting wheat yield in Jaunpur district, Uttar Pradesh

Application of discriminant function analysis for forecasting wheat yield in Jaunpur district, Uttar Pradesh