Under-Five Child Growth and Nutrition Status: Spatial Clustering of Indian Districts

Variation in human growth and the genetic and environmental factors that are influencing it have been described worldwide. The objective of this study is to assess the geographical variance of under-five nutritional status and its related covariates across Indian districts. We use the most recent fourth round of the Indian National Family Health Survey conducted in 2015–2016, which for the first time offers district level information. We employ principal component analysis (PCA) on the demographic and socio-economic determinants of childhood morbidity and conduct hierarchical clustering analysis to identify geographical patterns in nutritional status at the district level. Our results reveal strong geographical clustering among the districts of India, often crossing state borders. Throughout most of Southern India, children are provided with relatively better conditions for growth and improved nutritional status, as compared to districts in the central, particularly rural parts of India along the so called “tribal belt”. Here is also where girls are on average measured to have less weight and height compared to boys. Looking at average weight, as well as the proportion of children that suffer from underweight and wasting, north-eastern Indian districts offer living conditions more conducive to healthy child development. The geographical clustering of malnutrition, as well as below-average child height and weight coincides with high poverty, low female education, lower BMI among mothers, higher prevalence of both parity 4 + and teenage pregnancies. The present study highlights the importance of combining PCA and cluster analysis in studying variation in under-five child growth and of conducting this analysis at the district level. We identify the geographical areas, where children are under severe risk of undernutrition, stunting and wasting and contribute to formulating policies to improve child nutrition in India

Contribution of Education to Infant and Under-Five Mortality Disparities among Caste Groups in India

The level of infant and under-five mortality is high among scheduled castes (SCs) and scheduled tribes (STs) in India. This study intends to quantify the contribution of education in explaining the gap in infant and under-five mortality between SCs/STs and non-SC/ST population in India with a special focus on the effect of maternal education. We used data from three rounds of National Family Health Survey (NFHS): 1992–93, 1998–99 and 2005–06. The synthetic cohort probability approach using full birth histories was used to estimate childhood mortality. We performed binary logistic regression analysis to examine the association of infant mortality (IM) and under-five mortality (U5M) with maternal education and selected other covariates. Further, we applied Fairlie's decomposition technique to understand the relative contribution of maternal education and other covariates on IM and U5M risk between the caste groups. The IM rate (IMR) among children born to illiterate mothers is about 3 times higher than those born to mothers with higher education across all caste groups. Similarly, the U5M rate (U5MR) is 5 times higher among ST population and 3 times higher among SC population during the 14-year observation period (1992–2006). The proportions of secondary and higher educated SC and ST mothers are relatively lower than among non-SC/ST mothers. The regression analysis shows that mother’s education has a statistically significant effect on reducing IM and U5M. A number of socio-economic covariates are found associated with IM and U5M; such as father’s education, mother’s age at first birth, mother’s work status, household wealth, exposure to media and socio-economic empowerment of the mother. A decomposition analysis shows that more than 90 percent of the gap in IM and U5M between social groups is explained by the differences in the distribution of maternal education and household wealth. The findings of this study emphasise the need to provide education to disadvantaged girls and health counselling to women, particularly among SC/STs with more focus on backward regions or states, to further reduce IM and U5M in India

Excess under-5 female mortality across India: a spatial analysis using 2011 census data

Background Excess female mortality causes half of the missing women (estimated deficit of women in countries with suspiciously low proportion of females in their population) today. Globally, most of these avoidable deaths of women occur during childhood in China and India. We aimed to estimate excess female under-5 mortality rate (U5MR) for India’s 35 states and union territories and 640 districts. Methods Using the summary birth history method (or Brass method), we derived district-level estimates of U5MR by sex from 2011 census data. We used data from 46 countries with no evidence of gender bias for mortality to estimate the effects and intensity of excess female mortality at district level. We used a detailed spatial and statistical analysis to highlight the correlates of excess mortality at district level. Findings Excess female U5MR was 18·5 per 1000 livebirths (95% CI 13·1–22·6) in India 2000–2005, which corresponds to an estimated 239 000 excess deaths (169 000–293 000) per year. More than 90% of districts had excess female mortality, but the four largest states in northern India (Uttar Pradesh, Bihar, Rajasthan, and Madhya Pradesh) accounted for two-thirds of India’s total number. Low economic development, gender inequity, and high fertility were the main predictors of excess female mortality. Spatial analysis confirmed the strong spatial clustering of postnatal discrimination against girls in India. Interpretation The considerable effect of gender bias on mortality in India highlights the need for more proactive engagement with the issue of postnatal sex discrimination and a focus on the northern districts. Notably, these regions are not the same as those most affected by skewed sex ratio at birth

Under-Five Child Growth and Nutrition Status: Spatial Clustering of Indian Districts. VID Working Paper 03/2019

Variation in human growth and the genetic and environmental factors that are influencing it have been described worldwide. The objective of this study is to assess the geographical variance of under-five children nutritional status and its related covariates across Indian districts. We use the most recent fourth round of the Indian National Family Health Survey conducted in 2015-2016, which for the first time offers district level information. We employ principal component analysis (PCA) on the demographic and socio-economic determinants of childhood morbidity and conduct hierarchical clustering analysis to identify geographical patterns in nutritional status among children of age under five at the district level. Our results reveal strong geographical clustering among the districts of India. Throughout most of Southern India, children are provided with relatively better conditions for growth and improved nutritional status, as compared to districts in the central, particularly rural parts of India. Looking at average weight, as well as the proportion of children that suffer from underweight and wasting, northeastern Indian districts seem to be offering living conditions more conducive to healthy child development. The geographical clustering of malnutrition, as well as below-average child height and weight coincides with high poverty, low female education, lower BMI among mothers, higher prevalence of both parity 4+ and teenage pregnancies. The present study highlights the importance of combining PCA and cluster analysis methods in studying variation in under-five child growth and nutrition at the district level. We identify the geographical areas, where children are under severe risk of undernutrition, stunting and wasting and contribute to formulating policies to improve child nutrition in India

Population and fertility by age and sex for 195 countries and territories, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Background: Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods: We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings: From 1950 to 2017, TFRs decreased by 49\ub74% (95% uncertainty interval [UI] 46\ub74–52\ub70). The TFR decreased from 4\ub77 livebirths (4\ub75–4\ub79) to 2\ub74 livebirths (2\ub72–2\ub75), and the ASFR of mothers aged 10–19 years decreased from 37 livebirths (34–40) to 22 livebirths (19–24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83\ub78 million people per year since 1985. The global population increased by 197\ub72% (193\ub73–200\ub78) since 1950, from 2\ub76 billion (2\ub75–2\ub76) to 7\ub76 billion (7\ub74–7\ub79) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2\ub70%; this rate then remained nearly constant until 1970 and then decreased to 1\ub71% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2\ub75% in 1963 to 0\ub77% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2\ub77%. The global average age increased from 26\ub76 years in 1950 to 32\ub71 years in 2017, and the proportion of the population that is of working age (age 15–64 years) increased from 59\ub79% to 65\ub73%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1\ub70 livebirths (95% UI 0\ub79–1\ub72) in Cyprus to a high of 7\ub71 livebirths (6\ub78–7\ub74) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0\ub708 livebirths (0\ub707–0\ub709) in South Korea to 2\ub74 livebirths (2\ub72–2\ub76) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0\ub73 livebirths (0\ub73–0\ub74) in Puerto Rico to a high of 3\ub71 livebirths (3\ub70–3\ub72) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2\ub70% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation: Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress. Funding: Bill & Melinda Gates Foundation