Exploring drivers of unsafe disposal of child stool in India using hierarchical regression model.

BACKGROUND: Disposal of children's stools is often neglected in Indian sanitation programs, putting them at higher risk of diseases transmitted through the fecal-oral route. Therefore, the current study aims to identify the socioeconomic and demographic factors associated with the unsafe disposal of child stool in India and to estimate the geographical variation in unsafe disposal. METHODS: The study used 78,074 births under two years from the fifth round of the National Family Health Survey (2019-21). Descriptive statistics, bivariate analysis with the chi-square test, and a four-level hierarchical logistic regression model were applied to accomplish the study objectives. RESULTS: Findings revealed a 61.3% prevalence of unsafe stool disposal nationwide, significantly varying between rural (45%) and urban (67%) areas. Multilevel logistic regression highlighted that mother's education, wealth quintile, and sanitation facility were significant predictors of unsafe disposal of child stools. Random intercept statistics revealed a substantial geographical unit-level variance in unsafe stool practice in India. CONCLUSION: The study emphasizes the widespread unsafe disposal of child stool among Indian mothers with young children below two years, and the study underscores a range of contributing factors, including education, media exposure, prosperity, water availability, and sanitation. It also accentuates the significance of the geographical variance in the unsafe disposal of child stool in India, particularly at the household level, followed by the community level. Hence, the findings underscore the importance of focused interventions, including targeted household-level poverty alleviation programs, initiatives to enhance sanitation and water facilities, and community-level public health awareness programs.

Revisiting the predisposing, enabling, and need factors of unsafe abortion in India using the Heckman Probit model.

Unsafe abortion refers to induced abortions performed without trained medical assistance. While previous studies have investigated predictors of unsafe abortion in India, none have addressed these factors with accounting sample selection bias. This study aims to evaluate the contributors to unsafe abortion in India by using the latest National Family Health Survey data conducted during 2019-2021, incorporating the adjustment of sample selection bias. The study included women aged 15 to 49 who had terminated their most recent pregnancy within five years prior to the survey (total weighted sample (N) = 4,810). Descriptive and bivariate statistics and the Heckman Probit model were employed. The prevalence of unsafe abortion in India was 31%. Key predictors of unsafe abortion included women's age, the gender composition of their living children, gestation stage, family planning status, and geographical region. Unsafe abortions were typically performed in the early stages of gestation, often involving self-administered medication. The primary reasons cited were unintended pregnancies and health complications. This study underscores the urgent need for targeted interventions that take into account regional, demographic, and social dynamics influencing abortion practices in India.

Re-examining the Nexus Between Maternal Smoking Behavior and Under-Five Children's ARI in India: A Comprehensive Study.

Background: The burden of acute respiratory infections (ARIs) among children under-five is a serious concern in lower and middle-income countries (LMICs), including India, where it is positively associated with indoor smoking exposures. This study re-examines the impact of maternal smoking on ARIs among children under 5 in India, considering other indoor air pollutant factors and covariates. The aim is to establish existing findings and capture any differentials in results using comprehensive analytical approaches. Methods: Data from the National Family Health Survey (NFHS-5), 2019 - 21, was used. Descriptive statistics, bivariate analysis, multivariable logistic regression models, and interaction analysis were applied to accomplish the study objective. Results: The adjusted likelihood of ARI was 1.24 (95% CI: 1.04-1.48) times higher in under-five children with smoking mothers than those with non-smoking mothers. The result was also observed to be almost similar across all seasons. Moreover, the combined effect of maternal smoking with other household members smoking and using unclean cooking fuel without a separate ventilated kitchen escalated the risk (AOR: 2.01; 95% CI: 1.98-2.67). Breastfeeding was found to be a preventive measure for reducing the risk of indoor smoking exposure. The children who were never breastfed and were born large or small were more susceptible to maternal smoking. Conclusion: The study highlights the association between maternal smoking and ARIs in Indian under-five children. Interventions include reducing maternal smoking, promoting breastfeeding, and improving respiratory health in fuel-exposed households.

Deepened socioeconomic inequality in clean cooking fuel use in India from 2005-2006 to 2015-2016.

Uptake of clean cooking fuels (CCF), such as liquefied petroleum gas (LPG), in place of traditional cooking fuels such as wood, charcoal, and kerosene can improve public health by reducing household air pollution exposures. Though studies have cross-sectionally examined socioeconomic determinants of cooking fuel adoption, little is known about socioeconomic disparities in CCF use over time. Data from the third (2005-06) and fourth (2015-16) rounds of the National Family Health Survey covering 109,041 and 601,509 households, respectively, were used to examine inequities in CCF use in India. While CCF use in India increased nationally from 25% in 2005-06 to 44% in 2015-16, the adoption of CCF varied widely across states and socio-economic groups. Approximately 2% of households in the poorest wealth quintile gained access to LPG during the study period, compared with an increase of 10% or more among households in the middle or richer wealth quintiles; the LPG access gap between the low (0.2%) and middle class (19.2%) was 19% in 2005-06 and nearly doubled to 35% (2.5% vs. 37.4%, respectively) in 2015-16. At the state level, there was a four-fold difference in the uptake of CCF over the two survey periods. The use of CCF increased by less than 10% in Himachal Pradesh, Bihar, Assam, Manipur, Mizoram, and Meghalaya as compared to the increases of at least 30% in Tamil Nadu (42%), undivided Andhra Pradesh (34%), and Kerala (30%). Further, in wealthier states (Delhi, Goa, Punjab, Haryana, Tamil Nadu, Kerala, and undivided Andhra Pradesh), CCF use increased by more than 20% among the poorest individuals compared with less than 1% among the poorest families in lower income states (Tripura, Meghalaya, Madhya Pradesh, Jharkhand, Chhattisgarh, Bihar). To promote a more equitable clean energy transition, poorer and rural Indian households should be prioritized for CCF promotion programs.

Small area variations in four measures of poverty among Indian households: Econometric analysis of National Family Health Survey 2019-2021.

India has seen enormous reductions in poverty in the past few decades. However, much of this progress has been unequal throughout the country. This paper examined the 2019-2021 National Family Health Survey to examine small area variations in four measures of household poverty. Overall, the results show that clusters and states were the largest sources of variation for the four measures of poverty. These findings also show persistent within-district inequality when examining the bottom 10th wealth percentile, bottom 20th wealth percentile, and multidimensional poverty. Thus, these findings pinpoint the precise districts where between-cluster inequality in poverty is most prevalent. This can help guide policy makers in terms of targeting policies aimed at reducing poverty.

EV Hosting Capacity Enhancement in a Community Microgrid Through Dynamic Price Optimization-Based Demand Response.

Community microgrids, as an emerging technology, offer resiliency in operation for smart grids. Microgrids are seeing an increased penetration of eco-friendly electric vehicles (EVs) in recent years. However, the uncontrolled charging of EVs can easily overwhelm such electric networks. In this work, we propose an efficient demand response (DR) scheme based on dynamic pricing to enhance the capacity of the microgrid to securely host a large number of EVs. A hierarchical two-level optimization framework is introduced to realize the DR scheme. At the upper level, the dynamic prices for the participating users in DR are optimized while at the lower level, each user optimizes its energy consumption based on the price signal from the upper level. An evolutionary algorithm and a mixed-integer linear programming model is employed to solve the upper and lower level problems, respectively. Energy scheduling problems of the users are solved in a distributed manner which adds to the scalability of the approach. The proposed DR scheme is tested on a microgrid system adopted from the IEEE European low-voltage distribution network. Numerical experiments confirm the effectiveness of the proposed DR scheme compared to the benchmark pricing policies from the literature.

Examining the predictors of healthcare facility choice for outpatient care among older adults in India using Andersen's revised healthcare utilization framework model.

BACKGROUND: In India, the demand for outpatient care is substantially higher than inpatient care among older adults. Therefore, the current study examines the level, patterns, and factors associated with outpatient care use. METHODS: The present research used data from the first wave of the Longitudinal Ageing Study in India (LASI, 2017-18). A total of 34,588 older adults (45 years and above) who accessed outpatient healthcare services in one year prior to the survey were included in this study. A bivariate chi-square test was applied to present the percentage distribution of types of outpatient healthcare utilization by background characteristics and healthcare responsiveness. Multinomial logistic regression analyses were employed to explore the interplay of outpatient healthcare utilization and allied predisposing, enabling, and need factors. RESULTS: About 63.7% of total older adults used a private facility, followed by 22.8% used a public facility, and 13.5% used other facilities. Years of schooling, household wealth status, place of residence, self-rated health, and health insurance were all found to be significant determinants of public or private facility use. In contrast, respondents' sex was found to be a significant determinant of private healthcare use only. The study finds that there was inadequate healthcare reaction to public health facilities. CONCLUSION: The current study revealed that the use of private facility for outpatient care is noticeably high in India. Older adults' educational attainments, health insurance coverage, and household level economic background were found to be significant factors in healthcare choice. The current study emphasizes the need to strengthen public healthcare services for outpatient care.

Small Area Variation in the Quality of Maternal and Newborn Care in India.

Importance: In India, the district serves as the primary policy unit for implementing and allocating resources for various programs aimed at improving key developmental and health indicators. Recent evidence highlights that high-quality care for mothers and newborns is critical to reduce preventable mortality. However, the geographic variation in maternal and newborn health service quality has never been investigated. Objective: To examine the variation between smaller areas within districts in the quality of maternal and newborn care in India. Design, Setting, and Participants: This cross-sectional study assessed data from women aged 15 to 49 years on the most recent birth (singleton or multiples) in the 5 years that preceded the fifth National Family Health Survey (June 17, 2019, to April 30, 2021). Exposures: Maternal and newborn care in 36 states and union territories (UTs), 707 districts, and 28 113 clusters (small areas) in India. Main Outcomes and Measures: The composite quality score of maternal and newborn care was defined as the proportion of components of care received of the total 11 essential components of antenatal and postnatal care. Four-level logistic and linear regression was used for analyses of individual components of care and composite score, respectively. Precision-weighted prevalence of each component of care and mean composite score across districts as well as their between-small area SD were calculated. Results: The final analytic sample for the composite score was composed of 123 257 births nested in 28 113 small areas, 707 districts, and 36 states/UTs. For the composite score, 58.3% of the total geographic variance was attributable to small areas, 29.3% to states and UTs, and 12.4% to districts. Of 11 individual components of care, the small areas accounted for the largest proportion of geographic variation for 6 individual components of care (ranging from 42.3% for blood pressure taken to 73.0% for tetanus injection), and the state/UT was the largest contributor for 4 components of care (ranging from 41.7% for being weighed to 52.3% for ultrasound test taken). District-level composite score and prevalence of individual care components and their variation across small areas within the districts showed a consistently strong negative correlation (Spearman rank correlation ρ = -0.981 to -0.886). Low-quality scores and large between-small area disparities were not necessarily concentrated in aspirational districts (mean district composite score [SD within districts], 92.7% [2.1%] among aspirational districts and 93.7% [1.8%] among nonaspirational districts). Conclusions and Relevance: The findings of this cross-sectional study suggest that the policy around maternal and child health care needs to be designed more precisely to consider district mean and between-small area heterogeneity in India. This study may have implications for other low- and middle-income countries seeking to improve maternal and newborn outcomes, particularly for large countries with geographic heterogeneity.

Effectiveness of modular approach in ensuring data quality in large-scale surveys: Evidence from National Family Health Survey - 4 (2015-2016).

This study aims to examine the effect of administration of shorter and longer versions of questionnaires on key indicators such as age displacement, birth displacement, age heaping, and skipping questions on antenatal care (ANC) visits and use of contraceptive methods in India using National Family Health Survey (NFHS)-4 data. At the individual level, the effect of the adoption of the shorter and longer versions of the questionnaires on the age displacement of women and children and skipping of the key questions is insignificant. However, the results from the two-level logistic regression model reveal that at the primary sampling unit (PSU) level, work pressure, depending on the number of eligible women in a household, emerges as a confounder in skipping certain questions, namely ANC [1.18 (p < 0.09)] and contraceptive use [AOR = 1.17 (p < 0.05)]. To expand the coverage of NFHS in providing state- and district-level estimates since 2015, the overall sample size was increased from 88,562 households and 89,777 eligible women in 1992-93 to 6,01,509 households and 6,99,686 eligible women in 2015-16. As a strategy to reduce workload and non-sampling errors during the survey, a nested design and modular approach were adopted to provide estimates of maternal and child health indicators at the district/state level and sexual behaviour, HIV/AIDS, and women's empowerment at the state level. It was hypothesised that a longer version of the questionnaire canvassed in the state module may be detrimental to data quality issues. The findings of this study establish the effectiveness of adopting a modular approach in large-scale surveys, depending on the scale of investigation. However, the differential workload calls for expanding the duration of surveys in PSUs, where the number of eligible women is higher. State level variation in the key data quality indicators may be partially explained by differentials in the training of investigators by the agency and use of translators.

Small area variation in severe, moderate, and mild anemia among women and children: A multilevel analysis of 707 districts in India.

India is home to the highest global number of women and children suffering from anemia, with one in every two women impacted. India's current strategy for targeting areas with a high anemia burden is based on district-level averages, yet this fails to capture the substantial small area variation in micro-geographical (small area) units such as villages. We conducted statistical and econometric analyses to quantify the extent of small area variation in the three grades of anemia (severe, moderate, and mild) among women and children across 36 states/union territories and 707 districts of India. We utilized data from the fifth round of the National Family Health Survey conducted in 2019-21. The final analytic sample for analyses was 183,883 children aged 6-59 months and 690,153 women aged 15-49 years. The primary outcome variable for the analysis was the three anemia grades among women and children. We adopted a three-level and four-level logistic regression model to compute variance partitioning of anemia among women and children. We also computed precision-weighted prevalence estimates of women and childhood anemia across 707 districts and within-district, between-cluster variation using standard deviation (SD). For severe anemia among women, small area (villages or urban blocks) account for highest share (46.1%; Var: 0.494; SE: 0.150) in total variation followed by states (39.4%; Var: 0.422; SE: 0.134) and districts (12.8%; Var: 0.156; SE: 0.012). Similarly, clusters account for the highest share in the variation in severe (61.3%; Var: 0.899; SE: 0.069) and moderate (46.4%: Var: 0.398; SE: 0.011) anemia among children. For mild and moderate anemia among women, however, states were the highest source of variation. Additionally, we found a high and positive correlation between mean prevalence and inter-cluster SD of moderate and severe anemia among women and children. In contrast, the correlation was weaker for mild anemia among women (r = 0.61) and children (0.66). In this analysis, we are positing the critical importance of small area variation within districts when designing strategies for targeting high burden areas for anemia interventions.

Small area variations in low birth weight and small size of births in India.

The states and districts are the primary focal points for policy formulation and programme intervention in India. The within-districts variation of key health indicators is not well understood and consequently underemphasised. This study aims to partition geographic variation in low birthweight (LBW) and small birth size (SBS) in India and geovisualize the distribution of small area estimates. Applying a four-level logistic regression model to the latest round of the National Family Health Survey (2015-2016) covering 640 districts within 36 states and union territories of India, the variance partitioning coefficient and precision-weighted prevalence of LBW (<2.5 kg) and SBS (mother's self-report) were estimated. For each outcome, the spatial distribution by districts of mean prevalence and small area variation (as measured by standard deviation) and the correlation between them were computed. Of the total valid sample, 17.6% (out of 193,345 children) had LBW and 12.4% (out of 253,213 children) had SBS. The small areas contributed the highest share of total geographic variance in LBW (52%) and SBS (78%). The variance of LBW attributed to small areas was unevenly distributed across the regions of India. While a strong correlation between district-wide percent and within-district standard deviation was identified in both LBW (r = 0.88) and SBS (r = 0.87), they were not necessarily concentrated in the aspirational districts. We find the necessity of precise policy attention specifically to the small areas in the districts of India with a high prevalence of LBW and SBS in programme formulation and intervention that may be beneficial to improve childbirth outcomes.

Levels, patterns and determinants of using reversible contraceptives for limiting family planning in India: evidence from National Family Health Survey, 2015-16.

BACKGROUND: Demand for family planning is predominantly for birth limiting rather than birth spacing in India. Despite several family planning programmes in India, the use of reversible contraception for limiting family planning has been stagnant and largely depends on female sterilization. Though many researchers have examined patterns and determinants of using modern contraception for total family planning, studies on patterns and determinants of contraceptive use for birth limiting are limited in India. This paper examines the patterns of contraceptive use for liming demand and its determinants in India. METHODS: The National Family Health Survey-4, 2015-16 data was used. Bivariate chi-square significant test and multivariate binary logistic regression model used to accomplish the study objectives. RESULTS: Majority of women (86.5%) satisfied limiting demand (SLD) in India; the SLD was found significantly low among the women's age 15-19 years (53.1%) and parity 0 (42%). The satisfied limiting demand by modern reversible contraception (mrSLD) was found significantly high in age group 15-19 years (49.1%), Muslims (30.6%) and North-east region (45.4%). The satisfied limiting demand by traditional contraception (tSLD) was almost three times higher in North-east region (26.1%) than national average of India (8.7%). The women's years of schooling, wealth status, religion and presence of son child found to be significant determinants of mrSLD. The likelihood of tSLD was found significantly high among the women who had no son child (AOR = 1.41; 95% CI:1.34, 1.48), Muslim (AOR = 1.78; 95% CI:1.70, 1.87). A considerable regional variability in levels of SLD, mrSLD and tSLD was found in India. CONCLUSION: Public investment in family planning is required to promote and provide subsidized modern reversible contraception (MRC) services, especially to women from North-east region, Muslim, Scheduled tribe, poor household and who had no son child. Improving the quality and availability of MRC services in public health centre will be helpful to increase SLD among the above mentioned women. Besides, the promotion of MRC will be supportive to overcome the issues of sterilization regrets in India.

Is consanguineous marriage related to spousal violence in India? Evidence from the National Family Health Survey, 2015-16.

Violence against women is a global phenomenon, and intimate partner violence is the most common form of violence faced by women in the world. Around 30% of women in the world, on average, and 33% in India experience intimate partner violence during their lifetime. The main aim of this study was to investigate whether consanguinity protects women from spousal violence. National Family Health Survey 2015-16 (NFHS-4) data were used. The study sample comprised 60,824 currently married women aged 15-49 years. The results of the logistic regression model showed that the likelihood of all types of spousal violence against women was higher among consanguineous unions compared with non-consanguineous unions in India. The association between consanguineous marriage and spousal violence was found to be positive and significant in the southern and eastern regions of India and among Scheduled Castes and Scheduled Tribes. The association was not significant among Muslims. Differences in socio-cultural norms and practices across the regions of India, and among different socio-cultural groups, can perhaps explain these variations. Women belonging in higher age groups, from Other Backward Castes, those who were working and those with a low level of educational attainment and socioeconomic standing had a higher risk of experiencing intimate partner violence. Couples in a consanguineous marriage should be given adequate counselling to reduce intimate partner violence in India, and similarly culturally diverse countries. This would also help reach Target 5.2 of the Sustainable Development Goals by 2030.

Climatic influence on the magnitude of COVID-19 outbreak: a stochastic model-based global analysis.

We investigate the climatic influence on COVID-19 transmission risks in 228 cities globally across three climatic zones. The results, based on the application of a Boosted Regression Tree algorithm method, show that average temperature and average relative humidity explain significant variations in COVID-19 transmission across temperate and subtropical regions, whereas in the tropical region, the average diurnal temperature range and temperature seasonality significantly predict the infection outbreak. The number of positive cases showed a decrease sharply above an average temperature of 10°C in the cities of France, Turkey, the US, the UK, and Germany. Among the tropical countries, COVID-19 in Indian cities is most affected by mean diurnal temperature, and those in Brazil by temperature seasonality. The findings have implications on public health interventions, and contribute to the ongoing scientific and policy discourse on the complex interplay of climatic factors determining the risks of COVID-19 transmission.

Risk of COVID-19 Transmission and Livelihood Challenges of Stranded Migrant Labourers during Lockdown in India.

The lockdown during the first phase of COVID-19 pandemic in India triggered an unprecedented humanitarian crisis. Labourers in the informal sector lost their jobs overnight and were stuck at their work places. The present study examines the risk of COVID-19 transmission among stranded migrant labourers and their livelihood challenges during  the lockdown. A telephonic survey was conducted during the lockdown of first wave of COVID-19 pandemic to collect information from the stranded migrant labourers. The non-probability snowball sampling technique and structured questionnaire were used to draw the sample. Simple frequency distribution and standard statistical methods were used to accomplish the study objectives. The factors of COVID-19 transmission such as poor housing, co-morbidities, poor practice of WASH and COVID-19 precautions were significantly high among the migrant labourers. The lockdown created livelihood crisis among them. For instance, ration shortage (86%), financial distress (82%), reduction of wages (13%), job loss (86%) and anxiety for COVID-19 infection (81%) were often seen. Many of the labourers did not receive any ration kits (30%) and financial assistance (86%) during lockdown. The governmental assistance to overcome the stranded migrant labourers' challenges during lockdown was less than desirable. India needs to frame a sustainable and effective policy for social security for labourers, particularly in emergency situations.

Nutritional status and concomitant factors of stunting among pre-school children in Malda, India: A micro-level study using a multilevel approach.

BACKGROUND: Malnutrition was the main cause of death among children below 5 years in every state of India in 2017. Despite several flagship programmes and schemes implemented by the Government of India, the latest edition of the Global Nutrition Report 2018 addressed that India tops in the number of stunted children, which is a matter of concern. Thus, a micro-level study was designed to know the level of nutritional status and to study this by various disaggregate levels, as well as to examine the risk factors of stunting among pre-school children aged 36-59 months in Malda. METHOD: A primary cross-sectional quantitative survey was conducted using structured questionnaires following a multi-stage, stratified simple random sampling procedure in 2018. A sum of 731 mothers with at least one eligible child aged 36-59 months were the study participants. Anthropometric measures of children were collected following the WHO child growth standard. Children were classified as stunted, wasted, and underweight if their HAZ, WHZ, and WAZ scores, respectively, were less than -2SD. The random intercept multilevel logistic regression model has been employed to estimate the effects of possible risk factors on childhood stunting. RESULTS: The prevalence of stunting in the study area is 40% among children aged 36-59 months, which is a very high prevalence as per the WHO's cut-off values (≥40%) for public health significance. Results of the multilevel analysis revealed that preceding birth interval, low birth weight, duration of breastfeeding, mother's age at birth, mother's education, and occupation are the associated risk factors of stunting. Among them, low birth weight (OR 2.22, 95% CI: 1.44-3.41) and bidi worker as mothers' occupation (OR 1.92, 95% CI: 1.18-3.12) are the most influencing factors of stunting. Further, about 14 and 86% variation in stunting lie at community and child/household level, respectively. CONCLUSION: Special attention needs to be placed on the modifiable risk factors of childhood stunting. Policy interventions should direct community health workers to encourage women as well as their male partners to increase birth interval using various family planning practices, provide extra care for low birth weight baby, that can help to reduce childhood stunting.

The road from ICPD to SDGs: Health returns of reducing the unmet need for family planning in India.

OBJECTIVE: This study attempts to estimate the impact of reducing the unmet need for family planning on the key maternal and child health indicators in India from 1993 to 2016, and projecting this for the period from 2016 to 2030. DATA AND METHODS: The data have been compiled from various sources such as the United Nations' World Population prospects, national family health surveys and the sample registration system. The family planning and demographic projection modules of 'Spectrum', a modular computer simulation program, were used to estimate the impact of family planning programmes on reproductive, maternal and child health outcomes in India from 1993 to 2030. RESULTS: Reduction of the unmet need for family planning averted approximately 56 million unintended pregnancies, 7 million unsafe abortions and 167,000 maternal deaths between 1993 and 2016. It is expected that an additional 41 million unintended pregnancies, 5 million unsafe abortions and 124,000 maternal deaths can be avoided by reducing the unmet need for family planning to 5% by 2030. Similarly, the declining unmet need for family planning between 1993 and 2016 led to a reduction in the pregnancy rate, abortion rate, and risk-adjusted infant and under-five mortality rates by 27 per 1000 married women, 1.8 per million married women, 10 per 1000 live births and 15 per 1000 live births, respectively. It is expected that approximately 24 pregnancies per 1000 married women, 1.6 abortions per million married women, 10 risk adjusted infant deaths per 1000 live births, and 14 under-five deaths per 1000 live births can be avoided by reducing the unmet need for family planning to 5% by 2030. CONCLUSIONS: The findings of this study advocate that family planning is one of the best return on-investment strategies for India to achieve several targets under the reproductive, maternal and child health-related sustainable development goals.

A district-level susceptibility and vulnerability assessment of the COVID-19 pandemic's footprint in India.

In this study, we trace the COVID-19 pandemic's footprint across India's districts. We identify its primary epicentres and the outbreak's imprint in India's hinterlands in four separate time-steps, signifying the different lockdown stages. We also identify hotspots and predict areas where the pandemic may spread next. Significant clusters in the country's western and northern parts pose risk, along with the threat of rising numbers in the east. We also perform epidemiological and socioeconomic susceptibility and vulnerability analyses, identifying resident populations that may be physiologically weaker, leading to a high incidence of cases and pinpoint regions that may report high fatalities due to ambient poor demographic and health-related factors. Districts with a high share of urban population and high population density face elevated COVID-19 risks. Aspirational districts have a higher magnitude of transmission and fatality. Discerning such locations can allow targeted resource allocation to combat the pandemic's next phase in India.

Cooking, smoking, and stunting: Effects of household air pollution sources on childhood growth in India.

This paper investigates the effects of household air pollution (HAP) on child stunting in India using a sample of 206, 898 under-five children from the latest National Family Health Survey (2015-16). Descriptive statistics and multivariate analysis were used to understand the association of stunting by type of cooking fuel, separate kitchen, and indoor smoking in the household. Using clean cooking fuels (CCFs), having a separate kitchen, and being unexposed to smoking can reduce the prevalence of stunting by 4%, 1%, and 1%, respectively, from the current prevalence of stunting (38%). The probability of childhood stunting among children living in households using unclean cooking fuel (UCF) was significantly higher (OR-1.16; 95% CI: 1.13-1.19) than those living in households using CCF. Findings were similar results in the absence of separate kitchen (OR-1.08; 95% CI: 1.05-1.10) and exposure to environmental tobacco smoke (OR-1.06; 95% CI: 1.04-1.08). Households using UCF had a 16% higher likelihood of stunting, while there was a strong gradient of HAP with stunting after controlling socioeconomic and demographic factors. Therefore, the LPG programs, such as the Pradhan Mantri Ujjwala Yojana, may be crucial to reduce HAP and its adverse impact on stunting, and successively to achieve sustainable development goals.

Disentangling the effects of reproductive behaviours and fertility preferences on child growth in India.

We analysed population data from the 2015-16 National Family Health Survey to disentangle the intricate underlying effects of reproductive behaviours and fertility preferences on child growth. We expected birth interval length to be more strongly associated with stunting than sibsize and these effects to be moderated by whether the child was wanted or unintended (mistimed/unwanted). Regression analyses showed strong and equal effects of short birth interval and sibsize on stunting, when adjusted for potential confounders and unobserved between-mother heterogeneity. There were no statistical associations between stunting and mistiming/unwantedness of index children, suggesting the absence of discrimination against such children. We conclude that while fertility preferences have no effect, reproductive behaviours exert significant influence on child growth. Sibsize has been falling for many years in India but birth interval lengths have remained largely unchanged. The results underscore the need for strengthening uptake of reversible contraceptives to enable longer birth intervals.