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India has the highest burden of Tuberculosis (TB) and multidrug-resistant TB (MDR-TB) worldwide. Innovative technology is the need of the hour to identify these cases that remain either undiagnosed or inadequately diagnosed due to the unavailability of appropriate tools at primary healthcare settings. We developed and evaluated 3 kits, namely ‘TB Detect’ (containing BioFM-Filter device), ‘TB Concentration and Transport’ (containing Trans-Filter device) and ‘TB DNA Extraction’ kits. These kits enable bio-safe equipment-free concentration of sputum on filters and improved fluorescence microscopy at primary healthcare centres, ambient temperature transport of dried inactivated sputum filters to central laboratories and molecular detection of drug resistance by PCR and DNA sequencing (Mol-DST). In a 2-site evaluation (n = 1190 sputum specimens) on presumptive TB patients, BioFM-Filter smear exhibited a significant increase in positivity of 7% and 4% over ZN smear and LED-FM smear (p<0.05), respectively and an increment in smear grade status (1+ or 2+ to 3+) of 16% over ZN smear and 20% over LED-FM smear. The sensitivity of Mol-DST in presumptive MDR-TB and XDR-TB cases (n = 148) was 90% for Rifampicin (95% confidence interval [CI], 78–96%), 84% for Isoniazid (95% CI, 72–92%), 83% for Fluoroquinolones (95% CI, 66–93%) and 75% for Aminoglycosides (95% CI, 35–97%), using phenotypic DST as the reference standard. Test specificity was 88–93% and concordance was ~89–92% (κ value 0.8–0.9). The patient-friendly kits described here address several of the existing challenges and are designed to provide ‘Universal Access’ to rapid TB diagnosis, including drug-resistant disease. Their utility was demonstrated by application to sputum at 2 sites in India. Our findings pave the way for larger studies in different point-of-care settings, including high-density urban areas and remote geographical locations. [ABSTRACT FROM AUTHOR]

Introduction: The aim of this paper is to investigate what factors are associated to cardiovascular disease and what differences exists between Asians living in the UK (from the English Longitudinal Study of Ageing) and the Asians living in India (from the Longitudinal Ageing Study in India). Methods: Logistic regression was used to investigate how demographic and physical performance factors were associated with cardiovascular disease using data from Wave 6 of the English Longitudinal Study of Ageing and Wave 1 of the Longitudinal Study of Ageing in India, with the main variable of interest being country of residence, Asians in England or Asians in India. Results: A total of 83,997 participants were included in the analyses. In the primary analysis, 73,396 participants from LASI were compared to 171 Asians in ELSA. After adjusting for age, blood pressure, resting heart rate, sex, waist circumference, gait, handgrip strength and standing balance, there was a statistically significant difference for the outcome of CVD between Whites ELSA (reference) and the participants of LASI (odds ratio = 0.77; 95% confidence interval = 0.60 to 0.99). There were no significant differences in CVD between the LASI participants, Asian ELSA, and the Non-White but not Asian ELSA groups. Discussion: No difference was found between Asians that live in India compared to ethnic minorities living in England, including Asians, after adjusting for confounders, but was found between Whites in ELSA compared to LASI participants. A key limitation was the massive disparity in sample sizes between the ELSA subgroups and LASI. Further work is required where comparable sample sizes and longitudinal analyses allow trends to be identified and to investigate the factors associated with the difference in CVD between two similar ethnicities living in distinct locations. Conclusion: After adjusting for risk factors, there was no difference in CVD between localised Asians and the ethnic minorities in the UK, but there was a difference between the majority ethnicities in the respective countries. [ABSTRACT FROM AUTHOR]

Background: In order for low and middle income countries (LMIC) to transition to Human Papilloma Virus (HPV) test based cervical cancer screening, a greater understanding of how to implement these evidence based interventions (EBI) among vulnerable populations is needed. This paper documents outcomes of an implementation research on HPV screening among women from tribal, rural, urban slum settings in India. Methods: A mixed-method, pragmatic, quasi-experimental trial design was used. HPV screening on self-collected cervical samples was offered to women aged 30–60 years. Implementation strategies were 1) Assessment of contextual factors using both qualitative and quantitative methods like key informant interviews (KII), focus group discussions (FGDs), pre-post population sample surveys, capacity assessment of participating departments 2) enhancing provider capacity through training workshops, access to HPV testing facility, colposcopy, thermal ablation/cryotherapy at the primary health care centers 3) community engagement, counselling for self-sampling and triage process by frontline health care workers (HCWs). Outcomes were assessed using the RE-AIM (Reach, Effectiveness, adoption, implementation, maintenance) framework. Results: Screening rate in 8 months' of study was 31.0%, 26.7%, 32.9%, prevalence of oncogenic HPV was 12.1%, 3.1%, 5.5%, compliance to triage was 53.6%, 45.5%, 84.6% in tribal, urban slum, rural sites respectively. Pre-cancer among triage compliant HPV positive women was 13.6% in tribal, 4% in rural and 0% among urban slum women. Unique challenges faced in the tribal setting led to programme adaptations like increasing honoraria of community health workers for late-evening work and recalling HPV positive women for colposcopy by nurses, thermal ablation by gynaecologist at the outreach camp site. Conclusions: Self-collection of samples combined with HCW led community engagement activities, flexible triage processes and strengthening of health system showed an acceptable screening rate and better compliance to triage, highlighting the importance of identifying the barriers and developing strategies suitable for the setting. Trial registration: CTRI/2021/09/036130. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive analysis of the agriculture trade dynamic between India and China from 2002–2021. It employed the Revealed Comparative Advantage (RCA) and Revealed Symmetric Comparative Advantage (RSCA) indices and various statistical analyses to assess the trade performance and provide an enhanced comprehension of the specialization pattern. The study has selected 45 agricultural commodities, categorized into seven sections according to the HS Nomenclature 2017. The findings revealed that India boasts a more diversified export portfolio compared to China, with a more significant number of agriculture chapters demonstrating a comparative advantage. Conversely, China's export basket is more concentrated, featuring fewer chapters with a comparative advantage but higher values of RCA and RSCA. The paper also identified the prospective areas for agriculture-trade cooperation and collaboration between the two countries and put forward recommendations. This research aims to offer valuable insights for policymakers, researchers, and traders to enhance bilateral ties and mutual benefits in the agriculture sector. [ABSTRACT FROM AUTHOR]

Background: The outbreak of the COVID-19 pandemic compelled the closure of educational institutions and forced students to complete nearly two years of schooling online, impacting their physical and emotional development tremendously. This exploratory study investigates the wide-ranging impact of online education on Indian students during the COVID-19 pandemic and discusses the challenges exacerbated by disparities in access to digital devices and reliable internet service. The paper also focuses on the physical and mental health issues that arose in student cohorts as a result of the abrupt shift to online learning, and investigates the relationship between students' socioeconomic status and the nature and frequency of health issues experienced by them. Methods: A total of 832 respondents completed a 40-item survey that was administered online and through interviews. The paper analysed the impact of access to digital resources and teachers' training in information and communication technology on the perception of the quality of education provided by the institutions. We further analysed the impact of the adoption of online educational platforms on students' mental and physical health. Results: The study found a positive relationship between the number of hours spent online, and the physical and mental health issues experienced by students. Participants reported an overall higher perception of stress and anxiety, loss of concentration, and dissatisfaction with the quality of education. Our data suggest that COVID-19 has exacerbated the digital divide. Discussion: Urgent investments are needed to provide universal access to reliable internet services, and to develop a pedagogy that supports an agile and adaptable educational system, capable of providing effective learning and evaluation, while supporting students' physical and mental health. [ABSTRACT FROM AUTHOR]

Severe acute malnutrition (SAM) can be fatal for children, and potentially limit their cognitive and physical growth. The last three National Family Health Survey (NFHS) in India shows an increase in the prevalence of SAM among under-five children. Given the specific mandates under ICDS (Integrated Child Development Service) for SAM children, it is important to validate the coverage efficiency of ICDS on SAM children. This paper examines a possible association between the coverage efficiency of ICDS on SAM children. The study further aims to identify the determinants of ICDS service utilization among SAM children. We used data from the fifth round of the National Family Health Survey. Descriptive statistics was used to estimate the SAM coverage under ICDS. Multilevel Logistic Regression was used to identify the determinants of ICDS service utilization among SAM children. The burden of SAM is higher among older children (3+ age). Coverage of ICDS was more among younger children and the poorest households in the rural areas. Results from multilevel logistic regression showed that age had a significant relationship with the outcome variable. SAM children living in the rural areas had a significantly higher odds of being covered under ICDS service (OR 1.57; CI: (1.35, 1.82)) than their urban counterparts. Pregnant and lactating mothers who received ICDS services were significant determinants of SAM coverage under ICDS. There is no evidence that ICDS is more efficient in identifying and covering SAM children than non-SAM children. Despite special provisioning in place for SAM children, coverage of different ICDS services was similar to that of non-SAM children, and were in fact lower than non-SAM children for some categories. The study suggests that improving coverage of ICDS services among pregnant and lactating mothers would increase the coverage of ICDS services among SAM children. [ABSTRACT FROM AUTHOR]

Postharvest crop residue burning (CRB) is a major policy issue in several developing countries because of harmful environmental and public health consequences. While the literature has extensively examined the reasons for rice CRB, much less is known about wheat residue management. This paper explores the drivers of CRB of wheat in India and relates it to farmers' prior decisions related to CRB of rice in the preceding season. Using primary data on residue management practices of 301 Indian farmers, whom we tracked over two consecutive harvests of rice (2018) and wheat (2019), we find that farmers are significantly more likely to burn wheat residue if they had previously burned rice residue. The possibility of this linkage or spillover increases the likelihood of wheat residue burning by 15.6 to 21 percent. Furthermore, farmers are undertaking wheat CRB despite the positive net benefit of choosing non-burning alternatives to manage crop residue. Our results suggest that ensuring well-functioning markets for crop residue, awareness campaigns, and recognition of spillover effects of residue management across crops over time can enable policies to promote pro-environmental postharvest choices. [ABSTRACT FROM AUTHOR]

Investing in nutrition sensitive sectors such as education can be an effective strategy for combatting malnutrition. In this paper we analyze the role that men's education plays in determining dietary diversity outcomes using primary data from 3600 households across four districts of India. Dietary diversity scores were calculated to reflect the quality of food intake, for households and women. Men's education level was considered as the primary driver of diet diversity. To establish a causal link between men's education and diet diversity, the education level of parents and siblings were used as instrumental variables. We find that men's education levels are associated with significantly higher diet diversity scores both for the household and for women. The role of men's education continues to be a significant determinant of diet quality after controlling for household and individual- level confounding factors including the education level of the woman. The results are consistent across different definitions of the diet diversity score and reference period. Methodologically we extend the evidence on the education–nutrition pathway from being associational to causal in nature. Results from this study point to the benefits of leveraging men's education as an effective pathway for improving nutritional outcomes within households. [ABSTRACT FROM AUTHOR]

Background: The reductions in mortality levels among children under five years are observed in most populations, including populations that were lagging the progress in the past. However, the reduction is not uniform across ages during childhood. The mortality declines within the first month have shown relatively slow progress. Early initiation of breastfeeding and discarding pre-lacteal feed protects the newborn from acquiring infection and, thereby, reduces mortality. This paper assesses the change in the prevalence of early initiation of breastfeeding and pre-lacteal feed along with their associated factors, and their association with neonatal mortality in India. Methods: We used data from the three rounds of National Family Health Surveys conducted during 2005–06, 2015–16 and 2019–21 in India. We used bivariate and multivariate analyses to examine prevalence rates, risk factors, and relationships between breastfeeding practices, including early initiation of breastfeeding and pre-lacteal feed, and neonatal mortality. Results: Early initiation of breastfeeding within one hour after birth increased rapidly from 25% in 2005–06 to 42% in 2019–21, and the pre-lacteal feeding practice declined from 57% in 2005–06 to 15% in 2019–21. Pre-lacteal feed is lower in states/districts where early breastfeeding initiation is predominant and vice versa. The role of health professionals during pregnancy and the first two days after delivery significantly improved breastfeeding practice. Further, the findings suggest that an early breastfeeding initiation is associated with lower neonatal mortality, whereas pre-lacteal feed is not harmful compared to late breastfeeding initiation. Conclusion: Prevalence of pre-lacteal feed reduced, and initiation of early breastfeeding increased considerably after the launch of the National Rural Health Mission in India. However, after 2015–16, early breastfeeding initiation has stagnated, and the decline in pre-lacteal feed has slowed down. The future program needs special attention to emphasize the availability and accessibility of breastfeeding advisers and observers in health facilities to help mitigate adverse neonatal outcomes. [ABSTRACT FROM AUTHOR]

Purpose: The IFA supplementation program under the Anemia Mukt Bharat (AMB) program is one of the most ambitious nutrient supplementation programs in India. The delivery of services often suffers due to frequent stock outs and shortages. It is critical to understand the bottleneck in the supply chain adversely affecting the performance and coverage of the program. The paper attempts to identify the bottlenecks of the IFA supply chain in key areas of supply chain i.e., forecasting, procurement, warehousing and inventory management, transportation, distribution, logistic information system and suggests a plan of action aimed at ensuring uninterrupted supplies to the end beneficiaries. Design/methodology/approach: The data source for the present paper is the nationwide IFA Supply Chain Assessment (2018–19) conducted across 29 Indian states with a total of 58 districts, 116 blocks, 232 Sub-Centres, 232 Anganwadi centres and 232 schools covered under the assessment as a multi-partner collaborative initiative. Field insights from supply chain strengthening interventions under different public health programs in India and other developing countries were taken to arrive at corrective actions and recommendations. Findings were disseminated to government and an action plan was suggested for connecting service delivery points through an app-based system, developing a micro plan for ensuring fixed distribution schedule, followed by continuous monitoring and review meetings identified for follow up. Findings: The average lead time across states was 35 weeks with top three performing states being Goa, Sikkim, and Telangana. The average per unit cost of procurement was Rs 0.35 for IFA Red, Rs 0.25 for IFA Blue, Rs 0.31 for IFA Pink and Rs 7.30 for IFA syrup. Out of the 704 districts in India, only 213 has IFA Red, only 140 had IFA Blue, 152 had IFA Pink and 163 had IFA Syrup available in four quarters of 2018–19. The key issues identified in the assessment were–a lack of standardized forecasting process, absence of inventory management techniques, no fixed distribution schedule, inadequate availability of transport vehicles and an absence of an integrated MIS. Originality/value: The identification of bottlenecks in the IFA supply chain and its impact on the performance of the supply chain would provide policy guidelines for the government as well as development partner agencies to design an effective and efficient supply chain. It would also enable the policy planners to understand the challenges associated with managing different components of a supply chain, their interrelation and impact on the overall performance of the supply chain. The suggested recommendations would equip program managers with the tool to devise and implement field level solutions. [ABSTRACT FROM AUTHOR]

Objectives: This paper describes the methodology of developing and implementation of a youth focused life skills training and counselling services programme (LSTCP) and assessment of factors associated with life skills of participants pre-training. Design: Development of all aspects of LSTCP (modules, methods and evaluation) was through a consultative process. Experiential learning based facilitation was decided as the approach for training participants. A quasi-experimental design with pre, post and follow-up assessment post-training was finalised. Data collection was done using specifically developed semi-structured self-administered questionnaire. Results: Multivariable logistic regression with life skills as outcome and various exposure variables was performed. About 2/3rd of participants had high level of life skills (68%). Increased score of extraversion (AOR = 1.57,95% CI = 1.32–1.85), agreeableness (AOR = 1.42,95% CI = 1.16–1.73), conscientiousness (AOR = 1.9,95% CI = 1.55–2.33), physical (AOR = 1.03,95% CI = 1.01–1.04), environmental (AOR = 1.02,95% CI = 1.004–1.03) and social quality of life (AOR = 1.01,95% CI = 1.006–1.02) were associated with high life skills score. Higher score of neuroticism (AOR = 0.66,95% CI = 0.53–0.79) was associated with low life skills score. Conclusion: The results presented provide an opportunity to understand the evolution of factors affecting life skills during the follow-up of this study. This study throws light on development of LSTCP for apparently healthy population in a setting like India and its states. [ABSTRACT FROM AUTHOR]

For over a decade, improving menstrual hygiene among poor girls and women in low-and-middle-income-countries has been a prominent global goal. Towards this, governments in the Global South have worked to promote the uptake of disposable sanitary pads. Despite this, we continue to see a high prevalence of period poverty mainly because disposable pads require monthly purchasing that may be burdensome for many women. Not only are pads financially unsustainable but also represent a heavy environmental burden which has kindled an interest in re-usable innovations like menstrual cups that present a sustainable solution. However, there is little understanding of factors that promote the take-up of disposable vs. sustainable products at population levels. In this paper, we draw on India's National Family Health Survey-5 to understand the socio-demographic determinants of period product usage among girls and women, differentiated by their sustainability quotient. Our findings suggest that awareness of sustainable products and cultural factors are the key driver to promote their use. Women with exposure to menstrual cups either via education or mass media were more likely to use them. Belonging to urban areas and to disadvantaged social categories are other driving factors, at least partly because taboos of vaginal insertion are less of a concern among these groups. These findings suggest that improving the uptake of menstrual cups requires a paradigm shift in menstrual health policies from the promotion of disposable pads alone to spreading awareness of sustainable period choices among women via innovative use of mass media and community networks. Some micro-level evidence of change supports our conclusions. [ABSTRACT FROM AUTHOR]

Background: The adoption of maternity services and postpartum modern contraception are the two most crucial components that help in reducing maternal and infant mortality; still, India is consistently struggling with it. This paper, therefore, aimed to examine the linkages between use of maternity services and postpartum modern contraceptive adoption. Data and methods: The required reproductive calendar data were extracted from the 2015–16 and 2019–21 National Family Health Survey (NFHS) datasets. The assessment was made based on a sample of currently married women aged 15–24 years who had given most recent childbirth in five years preceding the survey. For the analysis, a time-to-event approach was applied using the Kaplan-Meier survival statistic, Log-Rank Chi-square test and Cox-Proportional Hazard (Cox-PH) models. Results: The results revealed that the proportion of postpartum modern contraceptive uptake among young users increased by 9%, from 33% in 2015–16 to 42% in 2019–21. The Cox-PH models revealed that, in both NFHS waves, the associations between various components of maternity services and postpartum modern contraceptive uptake were strongly significant, even after controlling for selected socio-economic and demographic correlates. Conclusions: The findings of this study reinforced urgent need for implementing integrated maternal-child health and family planning programmes and for boosting effective family planning counselling by health professionals to promote and motivate young women with a desire to early adoption of modern contraception in subsequent months after a recent childbirth. [ABSTRACT FROM AUTHOR]

Topic modelling with innovative deep learning methods has gained interest for a wide range of applications that includes COVID-19. It can provide, psychological, social and cultural insights for understanding human behaviour in extreme events such as the COVID-19 pandemic. In this paper, we use prominent deep learning-based language models for COVID-19 topic modelling taking into account data from the emergence (Alpha) to the Omicron variant in India. Our results show that the topics extracted for the subsequent waves had certain overlapping themes such as governance, vaccination, and pandemic management while novel issues aroused in political, social and economic situations during the COVID-19 pandemic. We also find a strong correlation between the major topics with news media prevalent during the respective time period. Hence, our framework has the potential to capture major issues arising during different phases of the COVID-19 pandemic which can be extended to other countries and regions. [ABSTRACT FROM AUTHOR]

Social equity is a critical component of social justice and is measured in multiple ways. Conventionally, researchers use literacy levels, workforce participation, political participation and representation, corporate presence, and demographic parity as indicators of social and economic equity. We add law enforcement outcomes to this literature by examining the demographic profiles of convicts in prisons in India for each state and compare it with that of the population of the respective state. To test whether entrenched social inequities have permeated into the law enforcement system, we use three indicators of social identity–religion, caste, and domicile–to create a social equity index (SEI). This is a composite index combining caste, religion and domicile similar in method to the Human Development Index which combines income, education and health. Our indicators are not considered in other popular development indices and is a conceptual innovation. Our paper innovates by combining prison data and census data at the state level over the two latest census rounds (2001 and 2011). We use a spatial panel analysis as well as a distributional dynamics approach to test for bias and transitions over time at the state level. We find that entrenched social hierarchies are mirrored in conviction outcomes and that social identities influence law enforcement. In contrast to earlier studies, we find that states that are conventionally considered to perform poorly in terms of economic and human development have done better in terms of social equity than economically advanced states. [ABSTRACT FROM AUTHOR]

Introduction: Older adults are always at a greater risk of physical and functional health challenges. These complications result into morbidity, disability and death making them more vulnerable at later ages. Therefore, this paper will examine the functional health status among older adults and its gender perspective, along with associated risk factors. Materials and methods: Using the first round of Longitudinal ageing survey of India (2017–18). Functional disability was computed based on general and instrumental activities of daily living (ADL and IADL) (n = 20910). Functional disability was coined with individual having at least one of the limitations of these activities. Applying bivariate and multivariate analysis the present paper studied the association, gender perspective and risk factors of functional disability among older adults aged 50 and above in India. Results: Our results clearly showed the gender bias in functional disability, with greater proportion of women (52%) at risk for functional disability then men (35%). Factors like multimorbidity, depression and life satisfaction are key risk factors identified by this study that increase the likelihood of disability. Conclusion: Functional disability is key to healthy ageing and needs immediate attention given its greater concentration among the elderly, particularly women. The results reflect the substantial burden of functional disability than self-care among older adults in India and therefore indicates some significant policy interventions to reduce the likely impact of functional disability. [ABSTRACT FROM AUTHOR]

Different diseases are observed in vegetables, fruits, cereals, and commercial crops by farmers and agricultural experts. Nonetheless, this evaluation process is time-consuming, and initial symptoms are primarily visible at microscopic levels, limiting the possibility of an accurate diagnosis. This paper proposes an innovative method for identifying and classifying infected brinjal leaves using Deep Convolutional Neural Networks (DCNN) and Radial Basis Feed Forward Neural Networks (RBFNN). We collected 1100 images of brinjal leaf disease that were caused by five different species (Pseudomonas solanacearum, Cercospora solani, Alternaria melongenea, Pythium aphanidermatum, and Tobacco Mosaic Virus) and 400 images of healthy leaves from India's agricultural form. First, the original plant leaf is preprocessed by a Gaussian filter to reduce the noise and improve the quality of the image through image enhancement. A segmentation method based on expectation and maximization (EM) is then utilized to segment the leaf's-diseased regions. Next, the discrete Shearlet transform is used to extract the main features of the images such as texture, color, and structure, which are then merged to produce vectors. Lastly, DCNN and RBFNN are used to classify brinjal leaves based on their disease types. The DCNN achieved a mean accuracy of 93.30% (with fusion) and 76.70% (without fusion) compared to the RBFNN (82%—without fusion, 87%—with fusion) in classifying leaf diseases. [ABSTRACT FROM AUTHOR]

The absence of reliable registration of Covid-19 deaths in India has prevented proper assessment and monitoring of the coronavirus pandemic. In addition, India's relatively young age structure tends to conceal the severity of Covid-19 mortality, which is concentrated in older age groups. In this paper, we present four different demographic samples of Indian populations for which we have information on both their demographic structures and death outcomes. We show that we can model the age distribution of Covid-19 mortality in India and use this modeling to estimate Covid-19 mortality in the country. Our findings point to a death toll of approximately 3.2–3.7 million persons by early November 2021. Once India's age structure is factored in, these figures correspond to one of the most severe cases of Covid-19 mortality in the world. India has recorded after February 2021 the second outbreak of coronavirus that has affected the entire country. The accuracy of official statistics of Covid-19 mortality has been questioned, and the real number of Covid-19 deaths is thought to be several times higher than reported. In this paper, we assembled four independent population samples to model and estimate the level of Covid-19 mortality in India. We first used a population sample with the age and sex of Covid-19 victims to develop a Gompertz model of Covid-19 mortality in India. We applied and adjusted this mortality model on two other national population samples after factoring in the demographic characteristics of these samples. We finally derive from these samples the most reasonable estimate of Covid-19 mortality level in India and confirm this result using a fourth population sample. Our findings point to a death toll of about 3.2–3.7 million persons by late May 2021. This is by far the largest number of Covid-19 deaths in the world. Once standardized for age and sex structure, India's Covid-19 mortality rate is above Brazil and the USA. Our analysis shows that existing population samples allow an alternative estimation of deaths due to Covid-19 in India. The results imply that only one out of 7–8 deaths appear to have been recorded as a Covid-19 death in India. The estimates also point to a very high Covid-19 mortality rate, which is even higher after age and sex standardization. The magnitude of the pandemic in India requires immediate attention. In the absence of effective remedies, this calls for a strong response based on a combination of non-pharmaceutical interventions and the scale-up of vaccination to make them accessible to all, with an improved surveillance system to monitor the progression of the pandemic and its spread across India's regions and social groups. [ABSTRACT FROM AUTHOR]

Objective: To determine the clinical manifestations, risk factors, treatment modalities and maternal outcomes in pregnant women with lab-confirmed COVID-19 and compare it with COVID-19 negative pregnant women in same age group. Design: Multicentric case-control study. Data sources: Ambispective primary data collection through paper-based forms from 20 tertiary care centres across India between April and November 2020. Study population: All pregnant women reporting to the centres with a lab-confirmed COVID-19 positive result matched with controls. Data quality: Dedicated research officers extracted hospital records, using modified WHO Case Record Forms (CRF) and verified for completeness and accuracy. Statistical analysis: Data converted to excel files and statistical analyses done using STATA 16 (StataCorp, TX, USA). Odds ratios (ORs) with 95% confidence intervals (CI) estimated using unconditional logistic regression. Results: A total of 76,264 women delivered across 20 centres during the study period. Data of 3723 COVID positive pregnant women and 3744 age-matched controls was analyzed. Of the positive cases 56·9% were asymptomatic. Antenatal complications like preeclampsia and abruptio placentae were seen more among the cases. Induction and caesarean delivery rates were also higher among Covid positive women. Pre-existing maternal co-morbidities increased need for supportive care. There were 34 maternal deaths out of the 3723(0.9%) positive mothers, while covid negative deaths reported from all the centres were 449 of 72,541 (0·6%). Conclusion: Covid-19 infection predisposed to adverse maternal outcomes in a large cohort of Covid positive pregnant women as compared to the negative controls. [ABSTRACT FROM AUTHOR]

Background: Building on a distinguished history of community medicine training, public health programs have been expanding in India in recent years. The COVID-19 pandemic has brought additional attention to the importance of public health programs and the need for a strong workforce. This paper aims to assess the current capacity for public health education and training in India and provide recommendations for improved approaches to meet current and future public health needs. Methods: We conducted a desk review of public health training programs via extensive internet searches, literature reviews, and expert faculty consultations. Among those programs, we purposively selected faculty members to participate in in-depth interviews. We developed summary statistics based on the desk review. For qualitative analysis, we utilized a combination of deductive and inductive coding to identify key themes and systematically reviewed the strengths and weaknesses of each theme. Results: The desk review captured 59 institutions offering public health training across India. The majority of training programs were graduate level degrees including Master of Public Health and Master of Science degrees. Key factors impacting these programs included collaborations, mentorship, curriculum standardization, tuition and funding, and student demand for public health education and careers. Collaborations and mentorship were highly valued but varied in quality across institutions. Curricula lacked standardization but also contained substantial flexibility and innovation as a result. Public sector programs were perceived to be affordable though fees and stipends varied across institutions. Further development of career opportunities in public health is needed. Conclusion: Public health education and training in India have a strong foothold. There are numerous opportunities for continued expansion and strengthening of this field, to support a robust multi-disciplinary public health workforce that will contribute towards achieving the sustainable development goals. [ABSTRACT FROM AUTHOR]

Background: Despite the progress in achieving gender equality to a certain extent, women are found to be more susceptible to health disadvantages compared to men in the older ages. However, research in the Indian context has mainly remained restricted to subjective health that heavily depends on the individual's perception, which may affect the validity of results. This study addresses this gap by complementing the investigation of the gender differentials in self-reported health outcomes (mobility and functional limitations) with that of objectively measured health status (hand-grip strength and static balance) among the older population of India. Besides, there is a dearth of literature that considers financial empowerment in explaining the gender differentials in health. Women's ability to participate in household decision-making, especially for important matters like major purchases, including property, indicates their empowerment status. Furthermore, the ability to extend financial support can be considered an important 'non-altruistic' driver for kins to care for older adults, indirectly affecting their health and well-being. Thus, the present paper explores the influence of financial empowerment on gender differentials in poor health outcomes. Methods: Using the Longitudinal Aging Study in India, Wave-1 (2017–18), six logistic regression models have been specified to capture the adjusted association between gender and poor health outcomes. The first three models successively control for the demographic and social support factors; socioeconomic factors and pre-existing health conditions; and financial empowerment indicators. The last three models investigate the interactions between gender and marital status, living arrangement and involvement in financial decisions, respectively. Results: The findings reveal that women tend to be more perceptive about their physical discomfort than men and reported a higher prevalence of poor subjective health. In terms of objectively measured health status, older men had a higher prevalence of low hand-grip strength but a lower prevalence of poor balance. Gender demonstrated a strong, adjusted association with poor health outcomes among older adults. However, the magnitude of gender difference either shrunk considerably or became statistically insignificant for all the poor health outcomes after controlling the effect of indicators of financial empowerment. Further, the interaction between gender and involvement in financial matters demonstrated a stronger effect for men in reversing poor subjective health. Conclusion: The study reinforced the positive effect of financial empowerment in mitigating gender disparity in health among older adults. [ABSTRACT FROM AUTHOR]

School dropout is a significant concern universally. This paper investigates the incorporation of spatial dependency in estimating the topographical effect of school dropout rates in India. This study utilizes the secondary data on primary, upper primary, and secondary school dropout rates of the different districts of India available at the Unified District Information System for Education plus (UDISE+) for the year 2020 to contemplate the impact of these dropouts from one region to different regions in molding with promotion rate and repetition rate. The Global Moran's I, Univariate and Bivariate Local Indicators of Spatial Association, and spatial models are utilized to investigate the geographical variability and to find the possible relationship between dropout rates and the school-level factors at the district level. The outcomes provide clear spatial clustering and precisely highlight the hot zone dropout regions with high repetition and low promotion rates. Based on this study's results, educational administrators can make evidence-based decisions to reduce dropout rates in hot zones of various regions of India. Furthermore, futuristic studies focusing on linking spatial hot zones with causal factors will add consistent data in assisting policymakers in taking necessary measures to develop a sound education management system. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to investigate the utilization of Lean & Six Sigma quality initiatives in healthcare sector in India. Methodology: The survey questionnaires were sent to 454 hospitals through registered postal in all the states of India. The survey questionnaire was designed to assess different quality initiatives; currently implemented in Indian hospitals, factors align with organization's objectives, reasons for not implementing Lean & Six Sigma and contribution of Lean & Six Sigma projects in healthcare improvement projects etc. A separate section in the questionnaire provides the feedback on implementation of Lean & Six Sigma in various hospitals. The relationships between Lean & Six Sigma and healthcare performance have also been established in this paper. Findings: It is found that 15 Nos. of hospitals have implemented the Lean tools while 14 Nos. have implemented the Six Sigma tools out of 109 collected responses. This shows the utilization of Lean & Six Sigma in Indian healthcare sector. The 'Lack of knowledge' and 'Availability of resources' are the major reasons for not implementing Lean & Six Sigma. It is also observed that 22% running projects were related to Lean & Six Sigma out of various improvement projects running in various hospitals. Originality: There is lack of evidences of similar studies that determines the utilization of Lean & Six Sigma in Indian healthcare sector at the national level. This paper will provide important breakthrough to academicians and healthcare practitioners, who are involved in Lean & Six Sigma research. Social implications: The present study will create awareness among healthcare practitioners across India for utilization of quality tools that will provide direct benefits to the society. [ABSTRACT FROM AUTHOR]

Background: Development assistance for health (DAH) is an important source of financing for health for many low-income and some middle-income countries. Most DAH has predominantly been contributed by high-income countries. However, in the context of economic progress and changing global priorities, DAH contributions from countries of the Global South such as India have gained importance. In this paper, we estimate DAH contributed by India between 2009 and 2020. Methods: We leveraged data from budgetary documents, databases, and financial reports of the Ministry of External Affairs and multilateral organizations to estimate DAH contributions. The proportions of development assistance that go towards health in major recipient countries were estimated and reported by recipient country and year. Results: Between 2009 and 2020, DAH contributed by India to bilateral and multilateral partners totaled $206.0 million. South Asian countries including Bangladesh, Bhutan, Nepal, Sri Lanka, and Myanmar received the most DAH from India. DAH contributed relative to DAH received ranged from 1.42% in 2009 to 5.26% in 2018, the latest year with country-level data. Health focus areas prioritized by India included technical training and innovation, health care infrastructure support, and supply of medications and medical equipment. Conclusion: India is an important development partner to many countries–particularly to those in the South Asian region. India's DAH allocation strategy prioritizes contributions toward neighboring countries in the South Asia region in several health focus areas. Detailed project-level data are needed to estimate DAH contributions from India with greater precision and accuracy. [ABSTRACT FROM AUTHOR]

Introduction: Ayushman Bharat Pradhan Mantri Jan Aarogya Yojana (AB PM-JAY) has enabled the Government of India to become a strategic purchaser of health care services from private providers. To generate base cost evidence for evidence-based policymaking the Costing of Health Services in India (CHSI) study was commissioned in 2018 for the price setting of health benefit packages. This paper reports the findings of a process evaluation of the cost data collection in the private hospitals. Methods: The process evaluation of health system costing in private hospitals was an exploratory survey with mixed methods (quantitative and qualitative). We used three approaches–an online survey using a semi-structured questionnaire, in-depth interviews, and a review of monitoring data. The process of data collection was assessed in terms of time taken for different aspects, resources used, level and nature of difficulty encountered, challenges and solutions. Results: The mean time taken for data collection in a private hospital was 9.31 (± 1.0) person months including time for obtaining permissions, actual data collection and entry, and addressing queries for data completeness and quality. The longest time was taken to collect data on human resources (30%), while it took the least time for collecting information on building and space (5%). On a scale of 1 (lowest) to 10 (highest) difficulty levels, the data on human resources was the most difficult to collect. This included data on salaries (8), time allocation (5.5) and leaves (5). Discussion: Cost data from private hospitals is crucial for mixed health systems. Developing formal mechanisms of cost accounting data and data sharing as pre-requisites for empanelment under a national insurance scheme can significantly ease the process of cost data collection. [ABSTRACT FROM AUTHOR]

Vast stretches of India comes under meteorological drought this year or the other. A huge population base in rural India are rendered highly vulnerable to this drought because of their primary dependency on agriculture and in turn they may respond through temporary migration out of the drought affected rural areas in search of alternative livelihoods. This study aims to investigate the association between drought and temporary migration in rural India by fitting binary logistic regression models on a cross-sectional dataset involving both National Sample Survey Organization (NSSO) 64th round data and India Meteorological Department (IMD) rainfall data. The paper also examines whether this association varies across the different socio-economic groups. Out of the total temporary migrants generated in rural India in the study period, 99.46% migrated internally and 67.12% were rural to urban migrants. The study finds that there is a positive association between drought instances and probability of a household to have at least one temporary migrant member in rural India (OR 1.64 with p<0.001) while controlling all other covariates. The study also concludes that the probability of temporary migration on account of drought is more severe among the socio-economically marginalised sections of the rural population compared to their better-off counterparts. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has impacted almost all the sectors including agriculture in the country. The present paper investigates the impact of COVID-19 induced lockdown on both wholesale and retail prices of major pulses in India. The daily wholesale and retail price data on five major pulses namely Lentil, Moong, Arhar, Urad and Gram are collected for five major markets in India namely Delhi, Mumbai, Kolkata, Chennai and Hyderabad during the period January, 2019 to September, 2020 from Ministry of Consumer Affairs, Food & Public Distribution, Government of India. The Government of India declared nationwide lockdown since March, 24, to May, 31, 2020 in different phases in order to restrict the spread of the infection due to COVID-19. To see the impact of lockdown on price and price volatility, time series model namely Autoregressive integrated moving average (ARIMA) model with error following Generalized autoregressive conditional heteroscedastic (GARCH) model incorporating exogenous variable as lockdown dummy in both mean as well variance equations. It is observed that in almost all the markets, lockdown has significant impact on price of the pulses whereas in few cases, it has significant impact on price volatility. [ABSTRACT FROM AUTHOR]

A growing number of organisations, including medical associations, recommend that research subjects should be given the option of being informed about the general outcome and results of the study. We recently completed a study involving nine serosurveys from 2018 to 2020 in five districts of India among three age groups (children 9 months to < 5 years; 5 to < 15 years of age, and women 15 to < 50 years of age before and after the measles and rubella (MR) vaccination campaigns). In Palghar district of Maharashtra all individuals in 30 selected clusters were enumerated, and 13 individuals per age group were randomly sampled. We established the procedures to return the results to the respondents for each stage of the survey. Of the 1,166 individuals selected for the measles and rubella serosurvey, 971 (83%) agreed to participate and were enrolled. Participants were informed that they will only be contacted if they test seronegative for measles and/or rubella antibodies. Overall, 140 individuals enrolled in the survey tested seronegative for IgG antibodies to measles and/or rubella viruses; were provided the reports and informed to seek medical advice. Upon follow up by phone, 10% (14) of the 140 participants reported to have been vaccinated. In this paper we discuss the procedures, experiences and considerations in returning results to participants in a community-based measles and rubella serosurvey. Although the lessons learned are specific to post measles-rubella vaccine campaign serosurvey in India, they might be helpful to those contemplating sharing results to participants of large scale survey settings. [ABSTRACT FROM AUTHOR]

Background: The Joint United Nations Programme on AIDS (UNAIDS) has emphasized on the incidence-prevalence ratio (IPR) and incidence-mortality ratio (IMR) to measure the progress in HIV epidemic control. In this paper, we describe the status of epidemic control in India and in various states in terms of UNAIDS's recommended metrices. Method: The National AIDS Control Programme (NACP) of India spearheads work on mathematical modelling to estimate HIV burden based on periodically conducted sentinel surveillance for providing guidance to program implementation and policymaking. Using the results of the latest round of HIV Estimations in 2019, IPR and IMR were calculated. Results: National level IPR was 0.029 [0.022–0.037] in 2019 and ranged from 0.01 to 0.15 in various States and Union Territories (UTs). Corresponding Incidence-Mortality Ratio was at 0.881 [0.754–1.014] nationally and ranged between 0.20 and 12.90 across the States/UTs. Conclusions: Based on UNAIDS recommended indicators for HIV epidemic control, namely IPR and IMR; national AIDS response in India appears on track. However, the program success is not uniform and significant heterogeneity as well as expanding epidemic was observed at the level of States or UTs. Reinforcing States/UTs specific and focused HIV prevention, testing and treatment initiatives may help in the attainment of 2030 Sustainable Development Goals of ending AIDS as a public health threat by 2030. [ABSTRACT FROM AUTHOR]

Anemia is one of the most pressing public health issues in the world with iron deficiency a major public health issue worldwide. The highest prevalence of anemia is in developing countries. The complete blood count is a blood test used to diagnose the prevalence of anemia. While earlier studies have framed the problem of diagnosis as a binary classification problem, this paper frames it as a multi class (three classes) classification problem with mild, moderate and severe classes. The three classes for the anemia classification (mild, moderate, severe) are so chosen as the world health organization (WHO) guidelines formalize this categorization based on the Haemoglobin (HGB) values of the chosen sample of patients in the Complete Blood Count (CBC) patient data set. Complete blood count test data was collected in an outpatient clinical setting in India. We used Feature selection with Majority voting to identify the key attributes in the input patient data set. In addition, since the original data set was imbalanced we used Synthetic Minority Oversampling Technique (SMOTE) to balance the data set. Four data sets including the original data set were used to perform the data experiments. Six standard machine learning algorithms were utilised to test our four data sets, performing multi class classification. Benchmarking these algorithms was performed and tabulated using both10 fold cross validation and hold out methods. The experimental results indicated that multilayer perceptron network was predominantly giving good recall values across mild and moderate class which are early and middle stages of the disease. With a good prediction model at early stages, medical intervention can provide preventive measure from further deterioration into severe stage or recommend the use of supplements to overcome this problem. [ABSTRACT FROM AUTHOR]

Introduction: The role of gender norms in shaping education and work opportunities, distribution of power and resources, and health and wellbeing is well recognised. However, rigorous studies in low- and middle-income countries on when and how norms change over time and what factors shape adolescents' and young adult's gender attitudes are limited. This paper explores the factors that determine adolescents' gender attitudes, as well as patterns in gender attitude shifts over time among younger and older adolescent boys and girls in India. Data and methods: Data presented in this paper were drawn from a unique longitudinal study of adolescents aged 10–19 (Understanding the lives of adolescent and young adults–UDAYA study) in the states of Bihar and Uttar Pradesh in India, conducted during 2015–2016 (wave 1) and 2018–2019 (wave 2). The analysis presented in this paper drew on data from 4,428 boys and 7,607 girls who were aged 10–19 and unmarried at wave 1 and interviewed at both rounds of the survey. We used univariate and bivariate analyses to examine changes in adolescents' gender role attitudes over time and the association between explanatory variables and gender role attitudes. We also used linear fixed effects regression models to identify factors that shape adolescents' gender role attitudes. Results: Gender role attitudes became more egalitarian over time among boys and girls, except among the older cohort of boys in our study. Among both younger and older cohorts, girls/young women held more egalitarian views than boys/young men and this pattern held over time for both cohorts. Factors that influenced gender role attitudes differed for younger and older adolescents, particularly among boys. While some predictors differed for boys and girls, there were substantial similarities as well. Gender attitudes were affected by factors at the individual, family, peer, and societal levels, as well as by community engagement. Conclusions: Our findings show that it is possible to shift gender attitudes toward greater equity and, in so doing, contribute to improved health and rights. [ABSTRACT FROM AUTHOR]

Background: Caste plays a significant role in Indian society and it influences women to health care access in the community. The implementation of the maternal health benefits scheme in India is biased due to caste identity. In this context, the paper investigates access to Janani Suraksha Yojana (JSY) among social groups to establish that caste still plays a pivotal role in Indian society. Also, this paper aims to quantify the discrimination against Scheduled Castes/Scheduled Tribes (SCs/STs) in accessing JSY. Methods: This paper uses a national-level data set of both NFHS-3 (2005–06) and NFHS-4 (2015–16). Both descriptive statistics and the Fairlie decomposition econometric model have been used to measure the explained and unexplained differences in access to JSY between SCs/STs and non-SCs/STs groups. Results: Overall, the total coverage of JSY in India is still, 36.4%. Further, it is found that 72% of access to JSY is explained by endowment variables. The remaining unexplained percentage (28%) indicates that there is caste discrimination (inequity associated social-discrimination) against SCs/STs in access to JSY. The highest difference (54%) between SCs/STs and non-SCs/STs in access to JSY comes from the wealth quintile, with the positive sign indicating that the gap between the two social groups is widening. Discussion and conclusion: It is necessary for the government to implement a better way to counter the caste-based discrimination in access to maternal health benefits scheme. In this regard, ASHA and Anganwadi workers must be trained to reduce the influence of dominant caste groups as well as they must be recruited from the same community to identify the right beneficiaries of JSY and in order to reduce inequity associated with social-discrimination. [ABSTRACT FROM AUTHOR]

Background and objectives: Studies in low-and middle-income countries where nutrition transition is underway provides mixed evidence of double burden of maternal overnutrition and child undernutrition among mother-child pairs. Shifting dietary pattern and rapid increase in overweight/obesity among adults with persistent child undernutrition indicate that India is experiencing nutrition transition and double burden of malnutrition. Hence, the study explores the presence of and the factors associated with mother-child dyads of over- and undernutrition in India. Methods and materials: The study uses National Family Health Survey 2015–16 data. The analytic sample consists of 28,817 weighted mother-child pairs where an overweight/obese mother is paired with an undernourished child. The nutritional status of children is defined according to WHO 2006 child growth standards as underweight (i.e., low weight-for-age), stunting (i.e., low height-for-age) and wasting (i.e., low weight-for-height). Maternal overweight/obesity (i.e., BMI ≥ 25 kg/m2) is defined using adult BMI criterion. Descriptive, bivariate, and adjusted multivariable logistic regression analysis are conducted. Results: Of the overweight/obese mothers, 21.3%, 26.5%, and 14% have underweight, stunted, and wasted children respectively. In adjusted models, maternal short stature (aOR: 2.94, 95% CI: 2.30–3.75), age of child (aOR: 3.29, 95% CI: 2.76–3.92), and poorest wealth status (aOR: 2.01, 95% CI: 1.59–2.54) are significant predictors of overweight/obese mothers and stunted child pairs. Similarly, poor wealth status (aOR: 1.68, 95% CI:1.32–2.14), maternal stature (aOR: 2.70, 95% CI: 2.08–3.52), and child aged 2–5 years (aOR: 1.77, 95% CI:1.51–2.08) are also significantly associated with higher occurrence of overweight/obese mother and-underweight child pairs. Conclusion: Findings of the study are consistent with the phase of nutrition transition and double burden of malnutrition. The paper concludes with suggestions to improve the socioeconomic condition, more strategic nutrition specific investments and policy interventions to eliminate all forms of malnutrition for achieving SDGs. [ABSTRACT FROM AUTHOR]

Effective and culturally appropriate hand-hygiene education is essential to promote health-related practices to control and prevent diseases such as Diarrhoea, Ebola and COVID-19. In this paper we outline and evaluate the Co-Creation processes underpinning a handwashing intervention for young children (A Germ's Journey) developed and delivered in India, Sierra Leone and the UK, and consider the implications surrounding Imperialist/Colonial discourse and the White Saviour Complex. The paper focuses both on the ways Co-Creation was conceptualised by our collaborators in all three countries and the catalysts and challenges encountered. Qualitative data have been drawn from in-depth interviews with five key stakeholders, focus group data from 37 teachers in Sierra Leone and responses to open-ended questionnaires completed by teachers in India (N = 66) and UK (N = 63). Data were analysed using thematic analysis and three themes, each with three constituent subthemes are presented. In the theme 'Representations of and Unique Approaches to Co-Creation' we explore the ways in which Co-Creation was constructed in relation to teamwork, innovative practice and more continuous models of evaluation. In 'Advantages of Co-Creation' we consider issues around shared ownership, improved outcomes and more meaningful insights alongside the mitigation of risks and short-circuiting of problems. In 'Challenges of Co-Creation' we discuss issues around timing and organisation, attracting and working with appropriate partners and understanding the importance of local context with inherent social, economic and structural barriers, especially in low-and-middle-income countries. We consider how theoretical elements of Co-Creation can inform effective international public health interventions; crucial during a global pandemic in which handwashing is the most effective method to control the transmission of COVID-19. Finally we reflect on some of the methodological challenges of our own work and in managing the potentially conflicting goals of the ethical and participatory values of Co-Creation with pragmatic considerations about ensuring an effective final 'product'. [ABSTRACT FROM AUTHOR]

Despite rapid macro-economic growth, one-third of the global burden of childhood stunting is contributed by India. This burden is characterized by wide-spread geographical variation within the country. This paper explores two research questions: (i) are the drivers of severe and moderate stunting similar? (ii) differential endowments or policy-effect, how do community-level nutrition and sanitary practices affect inter-state differences? Using data from Indian National Family and Health Survey 4, 2015–16, six states holding different ranks in the stunting continuum are compared to Tamil Nadu, taken as the benchmark state due to its laudable performance in the health care sector. Applying quantile regression approaches, the difference in state-level performance is decomposed into detailed covariate effects (differential endowments) and coefficient effects (differential strength of association between the drivers and outcome). The explanatory variables are not similarly associated with severe and moderate stunting. Decomposition results demonstrate a significant role of community-level sanitation practices compared to child nutrition behaviour in explaining the inter-state disparity. Coefficient effects play a dominant role in the lower tail of HAZ distribution for the poor performing states indicating that the worse outcomes of these states are due to weaker policy effects of the control variables on stunting. Multi-sectoral approach, identification and differentiation between severe and moderate stunting cases can be more instrumental in managing and reducing the scourge. This paper also advocates the potential benefits of customizing centrally-launched policies as per the state's performance and introducing the concept coproduction in the existing nutrition and health policy framework. This will instigate a feeling of ownership of the problem of childhood stunting among the policy consumers and strengthen the influence of policies on the outcomes. [ABSTRACT FROM AUTHOR]

Objectives: The transition to small family size is at an advanced phase in India, with a national TFR of 2.2 in 2015–16. This paper examines the roles of four key determinants of fertility—marriage, contraception, abortion and postpartum infecundability—for India, all 29 states and population subgroups. Methods: Data from the most recent available national survey, the National Family Health Survey, conducted in 2015–16, were used. The Bongaarts proximate determinants model was used to quantify the roles of the four key factors that largely determine fertility. Methodological contributions of this analysis are: adaptations of the model to the Indian context; measurement of the role of abortion; and provision of estimates for sub-groups nationally and by state: age, education, residence, wealth status and caste. Results: Nationally, marriage is the most important determinant of the reduction in fertility from the biological maximum, contributing 36%, followed by contraception and abortion, contributing 24% and 23% respectively, and post-partum infecundability contributed 16%. This national pattern of contributions characterizes most states and subgroups. Abortion makes a larger contribution than contraception among young women and better educated women. Findings suggest that sterility and infertility play a greater than average role in Southern states; marriage practices in some Northeastern states; and male migration for less-educated women. The absence of stronger relationships between the key proximate fertility determinants and geography or socio-economic status suggests that as family size declined, the role of these determinants is increasingly homogenous. Conclusions: Findings argue for improvements across all states and subgroups, in provision of contraceptive care and safe abortion services, given the importance of these mechanisms for implementing fertility preferences. In-depth studies are needed to identify policy and program needs that depend on the barriers and vulnerabilities that exist in specific areas and population groups. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic continues to have major impact to health and medical infrastructure, economy, and agriculture. Prominent computational and mathematical models have been unreliable due to the complexity of the spread of infections. Moreover, lack of data collection and reporting makes modelling attempts difficult and unreliable. Hence, we need to re-look at the situation with reliable data sources and innovative forecasting models. Deep learning models such as recurrent neural networks are well suited for modelling spatiotemporal sequences. In this paper, we apply recurrent neural networks such as long short term memory (LSTM), bidirectional LSTM, and encoder-decoder LSTM models for multi-step (short-term) COVID-19 infection forecasting. We select Indian states with COVID-19 hotpots and capture the first (2020) and second (2021) wave of infections and provide two months ahead forecast. Our model predicts that the likelihood of another wave of infections in October and November 2021 is low; however, the authorities need to be vigilant given emerging variants of the virus. The accuracy of the predictions motivate the application of the method in other countries and regions. Nevertheless, the challenges in modelling remain due to the reliability of data and difficulties in capturing factors such as population density, logistics, and social aspects such as culture and lifestyle. [ABSTRACT FROM AUTHOR]

Background: Multiple factors are associated with the risk of diabetes and hypertension. In India, they vary widely even from one district to another. Therefore, strategies for controlling diabetes and hypertension should appropriately address local risk factors and take into account the specific causes of the prevalence of diabetes and hypertension at sub-population levels and in specific settings. This paper examines the demographic and socioeconomic risk factors as well as the spatial disparity of diabetes and hypertension among adults aged 15–49 years in Northeast India. Methods: The study used data from the Indian Demographic Health Survey, which was conducted across the country between 2015 and 2016. All men and women between the ages of 15 and 49 years were tested for diabetes and hypertension as part of the survey. A Bayesian geo-additive model was used to determine the risk factors of diabetes and hypertension. Results: The prevalence rates of diabetes and hypertension in Northeast India were, respectively, 6.38% and 16.21%. The prevalence was higher among males, urban residents, and those who were widowed/divorced/separated. The functional relationship between household wealth index and diabetes and hypertension was found to be an inverted U-shape. As the household wealth status increased, its effect on diabetes also increased. However, interestingly, the inverse was observed in the case of hypertension, that is, as the household wealth status increased, its effect on hypertension decreased. The unstructured spatial variation in diabetes was mainly due to the unobserved risk factors present within a district that were not related to the nearby districts, while for hypertension, the structured spatial variation was due to the unobserved factors that were related to the nearby districts. Conclusion: Diabetes and hypertension control measures should consider both local and non-local factors that contribute to the spatial heterogeneity. More importance should be given to efforts aimed at evaluating district-specific factors in the prevalence of diabetes within a region. [ABSTRACT FROM AUTHOR]

This paper re-examines the relationships between night-time light (NTL) and gross domestic product (GDP), population, road networks, and carbon emissions in China and India. Two treatments are carried out to those factors and NTL, which include simple summation in each administrative region (total data), and summation normalized by region area (density data). A series of univariate regression and multiple regression experiments are conducted in different countries and at different scales, in order to find the changes in the relationship between NTL and every parameter in different situations. Several statistical metrics, such as R2, Mean Relative Error (MRE), multiple regression weight coefficient, and Pearson's correlation coefficient are given special attention. We found that GDP, as a comprehensive indicator, is more representative of NTL when the administrative region is relatively comprehensive or highly developed. However, when these regions are unbalanced or undeveloped, the representation of GDP becomes weak and other factors can have a more important influence on the multiple regression. Differences in the relationship between NTL and GDP in China and India can also be reflected in some other factors. In many cases, regression after normalization with the administrative area has a higher R2 value than the total regression. But it is highly influenced by a few highly developed regions like Beijing in China or Chandigarh in India. After the scale of the administrative region becomes fragmented, it is necessary to adjust the model to make the regression more meaningful. The relationship between NTL and carbon emissions shows obvious difference between China and India, and among provinces and counties in China, which may be caused by the different electric power generation and transmission in China and India. From these results, we can know how the NTL is reflected by GDP and other factors in different situations, and then we can make some adjustments. [ABSTRACT FROM AUTHOR]

The literature on growth convergence has focused to a great extent on the role of initial incomes as a primary determinant of long-term growth outcomes. Expanded versions of growth models have used other explanators to unpack the growth process. In this paper we add to the literature in two significant ways: (a) we use socioeconomic variables that are sometimes overlooked in explaining growth (such as, political stability and political alliance, social heterogeneity, and demographic distribution), and (b) we demonstrate that earlier analyses may be overlooking the problem of normality and endogeneity in regression models (and we provide alternate methods like instrumental variable and distribution dynamics to control for these). In this paper we analyze the per capita income growth at the subnational level in India for the period 1981–82 to 2010–11 using an expanded growth framework. We find that initial incomes, the ratio of working age group to total population, political stability and alliance, and the extent of development expenditure play a positive and significant role in predicting growth. We also find that, contrary to popular belief, the presence of marginalized groups—namely Scheduled Castes and Scheduled Tribes—have not been a hindrance to growth of per capita incomes in states. Our findings on the influence of social institutions may have significant implications for a public policy of affirmative action in India. The results on the impact of development expenditure on growth is also important for states seeking to increase their growth rates through policy intervention. [ABSTRACT FROM AUTHOR]

Dietary adequacy and diversity during the lactation period are necessary to ensure good health and nutrition among women and children. Behavioral interventions pertaining to health and nutrition counselling during pregnancy and lactation are critical for awareness about dietary diversity. The issue assumes salience for marginalized communities because of the Covid-19 pandemic and associated economic and societal disruptions. This paper assesses the dietary patterns among 400 lactating mothers in the tribal-dominated district of Palghar in Maharashtra, India in 2020. The study is based on primary data regarding consumption of 10 food groups among women across 10 food groups based on 24-hour recall period. The primary outcome variable was binary information regarding Minimum Dietary Diversity defined as consumption from at least 5 food groups. Econometric analysis based on multilevel models and item-response theory is applied to identify food groups that were most difficult to be received by mothers during the early and late lactation period. We find that the daily diet of lactating mothers in Palghar primarily consists of grains, white roots, tubers, and pulses. In contrast, the intake of dairy, eggs, and non-vegetarian food items is much lower. Only Half of the lactating women (56.5 percent; 95% CI: 37.4; 73.8) have a minimum diversified diet (MDD). The prevalence of lactating women with MDD was higher among households with higher income (73.1 percent; 95% CI: 45.2; 89.9) than those in lower income group (50.7 percent; 95% CI: 42.3; 58.9). Lactating Women (in early phase) who received health and nutrition counseling services are more likely (OR: 2.37; 95% CI: 0.90; 6.26) to consume a diversified diet. Food groups such as fruits, meat, poultry, fish, nuts, and seeds were among the rare food items in daily diet. The dietary pattern lacking in fruits, nuts, and heme (iron) sources indicates more significant risks of micronutrient deficiencies. The findings call for improving dietary diversity among lactating mothers, particularly from the marginalized communities, and are driven by low consumption of dairy products or various fruits and vegetables. Among the different food items, the consumption of micronutrient-rich seeds and nuts is most difficult to be accessed by lactating mothers. Also, diet-centric counseling and informing lactating mothers of its benefits are necessary to increase dietary diversity for improving maternal and child nutrition. [ABSTRACT FROM AUTHOR]

Background: With the increase in elderly population, the risk of cardiovascular diseases (CVD) among Indian older adults is also increasing. The present paper tries to assess how different anthropometric measures of obesity and physical activity affects cardiovascular disease risk among older adults in India. Methods: The data from Longitudinal Ageing Study in India (LASI) has been used. The total sample size for the present study is 31,464 older adults aged 60 years and above. Chi-square test and binary logistic regression has been used to measure the association of obesity measures and CVD prevalence. Results: About 35.2% (n = 11,058) of the older adults suffered from CVD. Moreover, 22.2% (n = 6,217) of the older adults were obese/overweight, 23.7% (n = 6,651) had high risk waist circumference and 77.0% (n = 21,593) had high risk waist-Hip ratio. The likelihood of CVD was 60%, 50%, and 34% significantly higher among older adults who were obese/overweight [Adjusted odds ratio (AOR): 1.60; CI: 1.48–1.72], had high risk waist circumference [AOR: 1.50; CI: 1.39–1.62] and high risk waist-Hip ratio [AOR: 1.34; CI: 1.25–1.44], respectively compared to older adults with normal BMI and those who do not have a high risk waist circumference and high risk waist hip ratio. Moreover, older adults who never did physical activity had 22 per cent higher risk of CVD than those who did frequent [AOR: 1.22; CI: 1.13–1.32] physical activity. Conclusion: The burden of overweight and obesity along with physical inactivity increases the risk of CVD in older adults. These findings highlight the urgent need for framing direct and indirect strategies to control obesity in order to reduce the burden of CVD among older adults in India. [ABSTRACT FROM AUTHOR]

Background: The present study aims to estimate the prevalence and correlates of multimorbidity among women aged 15–49 years in India. Additionally, the population attributable risk for multi-morbidity in reference to those women who smoke tobacco, chew tobacco, and consume alcohol is estimated. Methods: The data was derived from the National Family Health Survey which was conducted in 2015–16. The effective sample size for the present paper 699,686 women aged 15–49 years in India. Descriptive statistics along with bivariate analysis were used to do the preliminary analysis. Additionally, binary logistic regression analysis was used to fulfil the objectives. Results: About 1.6% of women had multimorbidity in India. The prevalence of multimorbidity was high among women from southern region of India. Women who smoke tobacco, chew tobacco and consume alcohol had 87% [AOR: 1.87CI: 1.65, 2.10], 18% [AOR: 1.18; CI: 1.10, 1.26] and 18% [AOR: 1.18; CI: 1.04, 1.33] significantly higher likelihood to suffer from multi-morbidity than their counterparts respectively. Population Attributable Risk for women who smoke tobacco was 1.2% (p<0.001), chew tobacco was 0.2% (p<0.001) and it was 0.2% (p<0.001) among women who consumed alcohol. Conclusion: The findings indicate the important role of lifestyle and behavioural factors such as smoking and chewing tobacco and consuming alcohol in the prevalence of multimorbidity among adult Indian women. The subgroups identified as at increased risk in the present study can be targeted while making policies and health decisions and appropriate comorbidity management can be implemented. [ABSTRACT FROM AUTHOR]

Social scientists and psychologists take interest in understanding how people express emotions and sentiments when dealing with catastrophic events such as natural disasters, political unrest, and terrorism. The COVID-19 pandemic is a catastrophic event that has raised a number of psychological issues such as depression given abrupt social changes and lack of employment. Advancements of deep learning-based language models have been promising for sentiment analysis with data from social networks such as Twitter. Given the situation with COVID-19 pandemic, different countries had different peaks where rise and fall of new cases affected lock-downs which directly affected the economy and employment. During the rise of COVID-19 cases with stricter lock-downs, people have been expressing their sentiments in social media. This can provide a deep understanding of human psychology during catastrophic events. In this paper, we present a framework that employs deep learning-based language models via long short-term memory (LSTM) recurrent neural networks for sentiment analysis during the rise of novel COVID-19 cases in India. The framework features LSTM language model with a global vector embedding and state-of-art BERT language model. We review the sentiments expressed for selective months in 2020 which covers the major peak of novel cases in India. Our framework utilises multi-label sentiment classification where more than one sentiment can be expressed at once. Our results indicate that the majority of the tweets have been positive with high levels of optimism during the rise of the novel COVID-19 cases and the number of tweets significantly lowered towards the peak. We find that the optimistic, annoyed and joking tweets mostly dominate the monthly tweets with much lower portion of negative sentiments. The predictions generally indicate that although the majority have been optimistic, a significant group of population has been annoyed towards the way the pandemic was handled by the authorities. [ABSTRACT FROM AUTHOR]

Introduction: Suicide is a major social and health issue in India. Yearly statistics show a concerning increasing pattern of suicidal deaths in India which is higher in comparison to the global trend. There is limited evidence regarding historical analysis of suicide or any forecasting for suicide in India towards predicting the possible risks of death due to suicide. Methods: This paper examines the trend of suicide rate and characteristics of suicide victims in India, based on the longitudinal time series data over the last 50 years—collected from the National Crime Record Bureau Reports (1969 to 2018) of the Government of India. In our analysis, we have used the time series model to forecast the suicide rates in India for the next decade. ARIMA (4,1,0) model is found to be the best fit model for forecasting the data. Findings: There has been an observable and rising trend of suicide rates in India over the last five decades. The forecast indicates a continuance of rising suicide cases for an upcoming couple of years in India with a limited decline in the following years. The prediction model indicates a future relatively consistent pattern of suicide in India which does not seem to be a very encouraging trend. As we have not included the period staring the year 2020 onwards affected by Covid-19 and which has several disruptions in personal and family spaces, the projected suicide trend during the period of next two to three years (2020–22) may rise far high and then it may show a declining path. Along with this, there is a shift in means of suicide in the last couple of decades. Constituting the second-highest number of cases, Illness associated suicide was visibly a serious concern. Conclusion: The present analysis finds that there is no visible substantial relief for suicide deaths during the coming years in India. On the other hand, more extensive exploration of sample cases may provide important information for suicide prevention. Availability of detailed and more inclusive data will be highly useful for analysis and suicide preventive policies. Investment in public health care and other welfare activities like education and employment generation will yield visible positive results in suicide control. [ABSTRACT FROM AUTHOR]

Since the inception of the National Programme for Family Planning, messages on family planning (FP) have been promoted across India using different mass media platforms. Mass media plays an important role in disseminating important information among the masses, such as how reversible modern methods give women more reproductive choices than opting for permanent methods that limit their child-bearing capacity. Mass media can provide a continuous flow of information and motivation to deter women from discontinuing the methods they have opted for. However, very few studies have been conducted on this issue, especially using recently available data. This study particularly focuses on exposure to mass media and the use of reversible modern methods of family planning among married women in India. The data for this study was obtained from the National Family Health Survey (2015–16) on currently married women aged 15–49 years. The association of reversible modern method use with media exposure variables was examined, controlling for a set of independent variables from multiple levels—individual, district, state, and region. The findings from this study showed that television was the most important medium for disseminating information on FP among married women in India. Spatial analysis revealed that some districts in the north, parts of the northeast, and Kerala in South India lacked any television exposure. The results from the decomposition analysis showed that mass media exposure was associated with a 14% increase in the use of reversible modern methods. Results from the multilevel analyses showed that exposure to TV along with other media (AOR 1.57 95% CI 1.49–1.65) and exposure to FP messages through different media (AOR 1.22 95% CI 1.12–1.32) had a significant positive effect on the use of reversible modern methods even when various individual, district, state, and regional-level factors were controlled. The findings of this paper provide evidence supporting the use of mass media to promote and increase awareness of voluntary contraceptive use in India. An increase in mass media exposure coupled with improvement in coverage and services of the FP program can significantly increase the use of reversible modern methods in a cost-effective yet efficient manner among women in need of FP services. [ABSTRACT FROM AUTHOR]

In this paper, we explore mutual information based stock networks to build regular vine copula structure on high frequency log returns of stocks and use it for the estimation of Value at Risk (VaR) of a portfolio of stocks. Our model is a data driven model that learns from a high frequency time series data of log returns of top 50 stocks listed on the National Stock Exchange (NSE) in India for the year 2014. The Ljung-Box test revealed the presence of Autocorrelation as well as Heteroscedasticity in the underlying time series data. Analysing the goodness of fit of a number of variants of the GARCH model on each working day of the year 2014, that is, 229 days in all, it was observed that ARMA(1,1)-EGARCH(1,1) demonstrated the best fit. The joint probability distribution of the portfolio is computed by constructed an R-Vine copula structure on the data with the mutual information guided minimum spanning tree as the key building block. The joint PDF is then fed into the Monte-Carlo simulation procedure to compute the VaR. If we replace the mutual information by the Kendall's Tau in the construction of the R-Vine copula structure, the resulting VaR estimations were found to be inferior suggesting the presence of non-linear relationships among stock returns. [ABSTRACT FROM AUTHOR]

Background: More than half of women of reproductive age in India have anemia. Over the last decade, India has made some progress towards reducing anemia in pregnant women, but non-pregnant women, who make up the largest sub group of people with anemia, are largely disregarded. Objectives: The objective of this paper is to examine intentions to take iron supplements and factors associated with intentions to inform a social norms-based behavioral intervention to increase uptake of iron supplements and reduce anemia in Odisha, India. Methods: We collected data from 3,914 randomly sampled non-pregnant women of reproductive age in 81 villages. We conducted a survey and took hemocue (anemia level) readings from each participant. We analyzed data using linear regression models beginning with demographics and social norms and adding other factors such as self-efficacy to take iron supplements, anemia risk perception, and knowledge about anemia in a subsequent model. Results: 63% of women in our sample were anemic but less than 5% knew they were anemic. Despite national guidelines that all women of reproductive age should take weekly iron supplements to prevent anemia, less than 3% of women in our sample were currently taking them. While actual use was low, intentions were rather high. On a five point Likert scale where higher numbers meant more intentions to take supplements, average intentions were above the midpoint (M = 3.48, SD = 1.27) and intentions and iron supplement use were significantly correlated (r =.10, p <.001). Both injunctive norms and collective norms were associated with intentions to take iron supplements but descriptive norms were not. Other significant factors included age, breastfeeding, knowledge, self-efficacy, and outcome expectations. The final model accounted for 74% of the variance in iron supplement intentions. Conclusions: In this context, where the actual behavior is low but intentions to enact the behavior are high, starting an intervention with injunctive norms messaging (expectations around the behavior) and self-efficacy to enact the behavior is the step we recommend based on our results. As an intervention unfolds and iron supplement use increases, descriptive norms messaging (that people are indeed taking iron supplements) may add value. [ABSTRACT FROM AUTHOR]

Introduction: The living arrangements among the older population form a basic pointer to the care and support of older adults in India, and living with extended kin is clearly differentiated from living separately. This paper attempts to understand the associations between socio-economic and health-related variables with preference for the separate living among older adults in India. Materials and methods: Using data from Building Knowledge Base on Population Ageing in India (BKPAI), we employed bivariate and probit regressions on a sample of 9540 older adults to fulfil the study objective. Results: Nearly 21% of older adults were living alone/with a spouse. Additionally, those older adults who lived alone/with spouse had specific reasons, i.e. about 14.6% reported that they had no children, 47.3% of older adults had their children away and 15.9% of older adults reported a family conflict. Availability of children is consistently found to be negatively associated with the preference of separate living. Besides, better self-rated health, independence in daily activities, and facing any type of violence were the strongest predictors of preference for separate living. In addition, the background characteristics, including age, sex, education, religion, and ethnicity, were found as significant predictors of living arrangement preference. Preference for co-residential arrangements emerges among older persons who have a feeling of importance within their family. Conclusion: Physical proximity to kin and health conditions, in addition to economic conditions, substantially determine the swing towards separate living among older adults in India. This suggests that attention has to be paid to the demand for specialized care and health services among older adults living separately. [ABSTRACT FROM AUTHOR]

The changing population age structure has a significant influence on the economy, society, and numerous other aspects of a country. This paper has innovatively applied the method of compositional data forecasting for the prediction of population age changes of the young (aged 0–14), the middle-aged (aged 15–64), and the elderly (aged older than 65) in China, India, and Vietnam by 2030 based on data from 1960 to 2016. To select the best-suited forecasting model, an array of data transformation approaches and forecasting models have been extensively employed, and a large number of comparisons have been made between the aforementioned methods. The best-suited model for each country is identified considering the root mean squared error and mean absolute percent error values from the compositional data. As noted in this study, first and foremost, it is predicted that by the year 2030, China will witness the disappearance of population dividend and get mired in an aging problem far more severe than that of India or Vietnam. Second, Vietnam’s trend of change in population age structure resembles that of China, but the country will sustain its good health as a whole. Finally, the working population of India demonstrates a strong rising trend, indicating that the age structure of the Indian population still remains relatively “young”. Meanwhile, the continuous rise in the proportion of elderly population and the gradual leveling off growth of the young population have nevertheless become serious problems in the world. The present paper attempts to offer crucial insights into the Asian population size, labor market and urbanization, and, moreover, provides suggestions for a sustainable global demographic development. [ABSTRACT FROM AUTHOR]