Age- and Gender-Specific Prevalence of Intellectually Disabled Population in India.

Intellectual disability in India is substantially under-reported, especially amongst females. This study quantifies the prevalence and gender bias in household reporting of intellectual disability by estimating the age-and-gender specific prevalence of the intellectually disabled by education, Socio-Demographic Index (SDI) score, place of residence, (rural/urban) and income of household head. We estimated prevalence (per 100,000) at 179 (95% CI: 173 to 185) for males and 120 (95% CI: 115 to 125) for females. Gender differences declined sharply with increased education, was higher for lower ages and low income and varied little by state development. Under-identification and under-reporting due to stigma are two plausible reasons for the gender differences in prevalence that increase with age.

Explaining the poor-rich gap in anthropometric failure among children in India: An econometric analysis of the NFHS, 2021 and 2016.

Wealth inequality in anthropometric failure is a persistent concern for policymakers in India. This necessitates a comprehensive analysis and identification of various risk factors that can explain the poor-rich gap in anthropometric failure among children in India. We analyze the fifth and fourth rounds of the Indian National Family Health Survey collected from June 2019 to April 2021 and January 2015 to December 2016, respectively. Two samples of children aged 0-59 and 6-23 months old with singleton birth, alive at the time of the survey with non-pregnant mothers, and with valid data on stunting, severe stunting, underweight, severely underweight, wasting, and severe wasting are included in the analytical samples from both rounds. We estimate the wealth gradients and distribution of wealth among children with anthropometric failure. Wealth gap in anthropometric failure is identified using logistic regression analysis. The contribution of risk factors in explaining the poor-rich gap in AF is estimated by the multivariate decomposition analysis. We observe a negative wealth gradient for each measure of anthropometric failure. Wealth distributions indicate that at least 60% of the population burden of anthropometric failure is among the poor and poorest wealth groups. Even among children with similar modifiable risk factors, children from poor and poorest backgrounds have a higher prevalence of anthropometric failure compared to children from the richest backgrounds. Maternal BMI, exposure to mass media, and access to sanitary facility are the most significant risk factors that explain the poor-rich gap in anthropometric failure. This evidence suggests that the burden of anthropometric failure and its risk factors are unevenly distributed in India. The policy interventions focusing on maternal and child health, implemented with a targeted approach prioritizing the vulnerable groups, can only partially bridge the poor-rich gap in anthropometric failure. The role of anti-poverty programs and growth is essential to narrow this gap in anthropometric failure.

Ethnic representation in interventional clinical trials run in India.

Globally, the need to enhance the diversity of trial participants is receiving increasingly urgent attention. We wanted to know whether trials run in India had adequately sampled the country's enormous ethnic diversity. We accessed the Clinical Trials Registry-India website to determine whether each interventional drug or biologic Phase 2 or 3 study, registered in a recent five-year period had run in each of six geographic zones. As regards Phase 3 trials conducted only in India, 61.4% ran in a single zone and just 6.8% were conducted in all six zones. Multinational Phase 3 trials had a better distribution since 3.6% had run in just one zone and 7.1% in all six. India's diverse ethnic groups are underrepresented in the majority of trials covered in this study. A trial that is conducted on non-representative groups and later discovered to be harmful or ineffective in parts of the population, is unethical. We propose various remedial steps.

Methods for assessing seasonal and annual trends in wasting in Indian surveys (NFHS-3, 4, RSOC & CNNS).

Wasting in children under-five is a form of acute malnutrition, a predictor of under-five child mortality and of increased risk of future episodes of stunting and/or wasting. In India, national estimates of wasting are high compared to international standards with one in five children found to be wasted. National surveys are complex logistical operations and most often not planned or implemented in a manner to control for seasonality. Collection of survey data across differing months across states introduces seasonal bias. Cross-sectional surveys are not designed to collect data on seasonality, thus special methods are needed to analyse the effect of data collection by month. We developed regression models to estimate the mean weight for height (WHZ), prevalence of wasting for every month of the year for an average year and an overall weighted survey estimates controlling for the socio-demographic variation of data collection across states and populations over time. National level analyses show the mean WHZ starts at its highest in January, falls to the lowest in June/August and returns towards peak at year end. The prevalence of wasting is lowest in January and doubles by June/August. After accounting for seasonal patterns in data collection across surveys, the trends are significantly different and indicate a stagnant period followed by a decline in wasting. To avoid biased estimates, direct comparisons of acute malnutrition across surveys should not be made unless seasonality bias is appropriately addressed in planning, implementation or analysis. Eliminating the seasonal variation in wasting would reduce the prevalence by half and provide guidance towards further reduction in acute malnutrition.

Association of maternal history of neonatal death with subsequent neonatal death across 56 low- and middle-income countries.

Early identification of high-risk pregnancies can reduce global neonatal mortality rate. Using the most recent Demographic and Health Surveys from 56 low- and middle-income countries, we examined the proportion of mothers with history of neonatal deaths. Logistic regression models were used to assess the association between maternal history of neonatal death and subsequent neonatal mortality. The adjusted models controlled for socioeconomic, child, and pregnancy-related factors. Country-specific analyses were performed to assess heterogeneity in this association across countries. Among the 437,049 live births included in the study, 6910 resulted in neonatal deaths. In general, 22.4% (1549) occurred to mothers with previous history of neonatal death; at the country-level, this proportion ranged from 1.2% (95% confidence interval [CI] 0.0, 2.6) in Dominican Republic to 38.1% (95% CI 26.0, 50.1) in Niger. Maternal history of neonatal death was significantly associated with subsequent neonatal death in both the pooled and the subgroup analyses. In the fully adjusted model, history of neonatal death was associated with 2.1 (95% CI 1.9, 2.4) times higher odds of subsequent neonatal mortality in the pooled analysis. We observed large variation in the associations across countries ranging from fully adjusted odds ratio (FAOR) of 0.4 (95% CI 0.0, 4.0) in Dominican Republic to 16.1 (95% CI 3.6, 42.0) in South Africa. Our study suggests that maternal history of neonatal death could be an effective early identifier of high-risk pregnancies in resource-poor countries. However, country-specific contexts must be considered in national policy discussions.

Crop Fires and Cardiovascular Health - A Study from North India.

We examine the impact of exposure to biomass burning events (primarily crop burning) on the prevalence of hypertension in four North Indian states. We use data from the National Family Health Survey-IV for 2015-16 and employ a multivariate logistic and linear model to estimate the effect of exposure to biomass burning on the prevalence of hypertension and blood pressure, respectively. The adjusted odds ratio of hypertension among individuals living in areas with high intensity of biomass (HIB) burning (defined as exposure to > 100 fire-events during the past 30 days) is 1.15 [95% CI: 1.003-1.32]. The odds ratios further increase at a higher intensity of biomass burning and downwind fires are found to be responsible for the negative effect of fires on cardiovascular health. We also find that the systolic and diastolic blood pressure for older cohorts is significantly higher due to exposure to HIB. We estimate that elimination of HIB would prevent loss of 70-91 thousand DALYs every year and 1.73 to 2.24 Billion USD (in PPP terms) over 5 years by reducing the prevalence of hypertension. Therefore, curbing biomass burning will be associated with significant health and economic benefits in North India.

Precision-weighted estimates of neonatal, post-neonatal and child mortality for 640 districts in India, National Family Health Survey 2016.

BACKGROUND: The conventional indicators of infant and under-five mortality are aggregate deaths occurring in the first year and the first five years, respectively. Monitoring deaths by <1 month (neonatal), 1-11 months (post-neonatal), and 12-59 months (child) can be more informative given various etiological causes that may require different interventions across these three mutually exclusive periods. For optimal resource allocation, it is also necessary to track progress in robust estimates of child survival at a smaller geographic and administrative level. METHODS: Data on 259 627 children came from the 2015-2016 Indian National Family Health Survey. We used a random effects model to account for the complex survey design and sampling variability, and predicted district-specific probabilities of neonatal, post-neonatal, and child mortality. The resulting precision-weighted estimates are more reliable as they pool information and borrow strength from other districts that share the same state membership. The Pearson correlation and Spearman's rank correlation were assessed for the three mortality estimates, and the Moran's I measure was used to detect spatial clustering of high burden districts for each outcome. RESULTS: The majority of under-five deaths was disproportionately concentrated in the neonatal period. Across all districts, the predicted probability of neonatal, post-neonatal, and child mortality varied from 6.0 to 63.9 deaths, 3.8 to 47.6 deaths, and 1.7 to 11.8 deaths per 1000 live births, respectively. The overall correlation between district-wide probabilities of mortality for the three mutually exclusive periods was moderate (Pearson correlation = 0.47-0.58, Spearman's rank correlation = 0.58-0.64). For each outcome, a relatively strong spatial clustering was detected across districts that transcended state boundaries (Moran's I = 0.61-0.76). CONCLUSIONS: Sufficiently breaking down the under-five mortality to distinct age groups and using the precision-weighted estimations to monitor performances at smaller geographic and administrative units can inform more targeted interventions and foster accountability to improve child survival.

Association of Maternal History of Neonatal Death With Subsequent Neonatal Death in India.

Importance: Among the United Nations' Sustainable Development Goals is to reduce the neonatal mortality rate to 12 per 1000 live births by 2030. Identifying high-risk pregnancies can help achieve this target in low-resource countries, such as India, which accounts for one-fourth of global neonatal deaths. Objective: To analyze the association of maternal history of neonatal death with subsequent neonatal mortality. Design, Setting, and Participants: This cross-sectional study included a nationally representative sample of singleton live births from multiparous women. Data were obtained from the 2016 National Family Health Survey in India. Data were analyzed from November 2018 to January 2020. Exposures: Maternal history of neonatal death and a comprehensive set of covariates, including socioeconomic environment, maternal anthropometry, and pregnancy care. Main Outcomes and Measures: Subsequent neonatal mortality. Population-attributable risk associated with history of neonatal death was calculated, and sensitivity analyses were performed. Results: The overall study population consisted of 127 336 singleton live births from multiparous women aged 15 to 49 (mean [SD] age, 28.8 [5.2] years) years when the survey was undertaken. In our analytic sample, 11 101 (8.7%) mothers had a history of neonatal death, and 506 of 2224 total neonatal deaths (22.8%) were attributed to women with history of neonatal death. The prevalence of history of neonatal death differed by selected covariates and across states or union territories. Maternal history of neonatal death was associated with significantly higher odds of neonatal mortality (adjusted odds ratio, 2.23; 95% CI, 1.96-2.55), and this remained consistent across different subgroups. The population-attributable risk associated with maternal history of neonatal death was 11.8%. Stronger associations were found for maternal history of multiple neonatal deaths (adjusted odds ratio, 3.50; 95% CI, 2.78-4.41) and in respect to the risk of mortality in early neonatal period (ie, 0-2 completed days) (adjusted odds ratio, 2.45; 95% CI, 2.09-2.86). Conclusions and Relevance: These findings suggest that maternal history of neonatal death is a potentially useful risk factor to identify women and neonates who may need extended and enhanced pregnancy care.

Missing female patients: an observational analysis of sex ratio among outpatients in a referral tertiary care public hospital in India.

OBJECTIVE: To investigate gender discrimination in access to healthcare and its relationship with the patient's age and distance from the healthcare facility. DESIGN AND SETTING: An observational study based on outpatient data from a large referral public hospital in Delhi, India. PARTICIPANTS: Confirmed clinical appointments. PRIMARY AND SECONDARY OUTCOME MEASURES: Estimates from the logistic regression are used to compute sex ratios (male/female) of patient visits with respect to distance from the hospital and age. Missing female patients for each state-a measure of the extent of gender discrimination-is computed as the difference in the actual number of female patients who came from each state and the number of female patients that should have visited the hospital had male and female patients come in the same proportion as the sex ratio of the overall population from the 2011 census. RESULTS: Of 2377028 outpatient visits, excluding obstetrics and gynaecology patients, the overall sex ratio was 1.69 male to one female visit. Sex ratios, adjusted for age and hospital department, increased with distance. The ratio was 1.41 for Delhi, where the facility is located; 1.70 for Haryana, an adjoining state; 1.98 for Uttar Pradesh, a state further away; and 2.37 for Bihar, the state furthest from Delhi. The sex ratios had a U-shaped relationship with age: 1.93 for 0-18 years, 2.01 for 19-30 years, and 1.75 for 60 years or over compared with 1.43 and 1.40 for the age groups 31-44 and 45-59 years, respectively. We estimate there were 402 722 missing female outpatient visits from these four states, which is 49% of the total female outpatient visits for these four states. CONCLUSION: We found gender discrimination in access to healthcare, which was worse for female patients who were in the younger and older age groups, and for those who lived at increasing distances from the hospital.

Impact of repeated blood pressure measurement on blood pressure categorization in a population-based study from India.

Often a single blood pressure (BP) measurement is used to diagnose and manage hypertension in busy clinics. However, repeated BP measurements have been shown to be more representative of the true BP status of the individual. Improper measurement of office BP can lead to inaccurate classification, overestimation of a patient's true BP, unnecessary treatment, and misinterpretation of the true prevalence of hypertension. There is no consensus among major guidelines on the number of recommended measurements at a single visit or the method of arriving at final clinic BP reading. The participants of the National Family Health Survey (NFHS-4), a nationwide survey conducted in India from 2015 to 2016, were used for the analysis. The prevalence and median difference in systolic blood pressure (SBP) and diastolic blood pressure (DBP) for single as well as combinations of two or more readings were calculated. Cross-tabulation was used to assess classification of individuals based on first BP reading compared with the mean of two or more BP measurements. There was a 63% higher prevalence of hypertension when only the first reading was considered for diagnosis in comparison to the mean of the second and third readings. A decrease of 3.6 mmHg and 2.4 mm Hg in mean SBP and DBP, respectively, was observed when the mean of the second and third readings was compared to the first reading. In those who are identified to have grade 1 or higher categories of hypertension, we recommend three BP measurements, with the mean of the second and third measurements being the clinic BP.