Suchergebnisse

AbstractUrban poverty is complex and conventional money‐metric poverty fails to measure the multiple deprivations of the urban population. Though recent estimates of multidimensional poverty do capture multiple deprivations, they do not capture the extent of multidimensional poverty in urban India. Using the urban sample from the National Family Health Survey, 2015–16, this paper estimates and decomposes multidimensional poverty in urban India. Urban poverty is measured in four key domains: Education, health, standard of living, and housing. A multilevel logistic model is used to decompose the variations in multidimensional poverty across geographical regions. Results suggest that about one‐third of the urban Indian population is multidimensionally poor and one‐sixth is vulnerable to multidimensional poverty. The state patterns of multidimensional poverty were diverse, with more than half of the urban population in Manipur and Bihar being multidimensionally poor, followed by Nagaland and Uttar Pradesh. On controlling for household characteristics, 17.5% of the total variation in multidimensional poverty was attributable to census enumeration blocks, 6.6% to districts, 1.8% to regions, and 9.9% to states. The odds of multidimensional poverty were higher among large households, female‐headed households, widowed, and scheduled tribes. Contextualizing multidimensional poverty and prioritizing vulnerable groups and regions are essential for reducing multidimensional poverty in urban India.

AbstractThe fertility–development relationship is bi-directional, context-specific, multi-phased and inconsistent over time. Indian districts provide an ideal setting to study this association due to their size, diversity and disparity in socioeconomic development. The objective of this study was to understand the association of fertility and socioeconomic development among the 640 districts of India. Data were drawn from multiple sources: Censuses of India 2001 and 2011; DLHS-2; NFHS-4; and other published sources. A district-level data file for Total Fertility Rate (TFR) and a set of developmental indices were prepared for the 640 districts for 2001 and 2016. Computation of a composite index (District Development Index, DDI), Ordinary Least Squares, Two Stage Least Squares and panel regressions were employed. By 2016, almost half of all Indian districts had attained below-replacement fertility, and 15% had a TFR of above 3.0. The DDI of India increased from 0.399 in 2001 to 0.511 by 2016 and showed large variations across districts. The correlation coefficient between TFR and DDI was –0.658 in 2001 and –0.640 in 2016. Districts with a DDI of between 0.3 and 0.6 in 2001 had experienced a fertility decline of more than 20%. The fertility–development relationship was found to be strongly negative, convex and consistent over time, but the level of association varied regionally. For any given level of DDI, fertility in 2016 was lower than in 2001; and the association was stronger in districts with a DDI below 0.45. The negative convex association between the two was prominent in the northern, central and eastern regions and the curves were flatter in the west, south and north-east. The increasing number of districts with low fertility and low development draws much attention. Some outlying districts in the north-eastern states had high TFR and high DDI (>0.6). Based on the findings, a multi-layered strategy in districts with low socioeconomic development is recommended. Additional investment in education, child health, employment generation and provisioning of contraceptives would improve the human development to achieve India's demographic goals.

SummaryDemographic research in India over the last two decades has focused extensively on fertility change and gender bias at the micro-level, and less has been done at the district level. Using data from the Census of India 1991–2011 and other sources, this paper shows the broad pattern of fertility transition and trends in the child sex ratio in India, and examines the determinants of the child sex ratio at the district level. During 1991–2011, while the Total Fertility Rate (TFR) declined by 1.2 children per woman, the child sex ratio fell by 30 points in the districts of India. However, the reduction in fertility was slower in the high-fertility compared with the low-fertility districts. The gender differential in under-five mortality increased in many districts of India over the study period. The decline in the child sex ratio was higher in the transitional compared with the low-fertility districts. The transitional districts are at higher risk of a low child sex ratio due to an increased gender differential in mortality and increase in the practice of sex-selective abortions. The sex ratio at birth and gender differential in mortality explains one-third of the variation, while region alone explains a quarter of the variation in the child sex ratio in the districts of India.

BACKGROUND: Estimates of catastrophic health expenditure (CHE) are counterintuitive to researchers, policy makers, and developmental partners due to data and methodological limitation. While inferences drawn from use of capacity-to-pay (CTP) and budget share (BS) approaches are inconsistent, the non-availability of data on food expenditure in the health survey in India is an added limitation. METHODS: Using data from the health and consumption surveys of National Sample Surveys over 14 years, we have overcome these limitations and estimated the incidence and intensity of CHE and impoverishment using the CTP approach. RESULTS: The incidence of CHE for health services in India was 12.5% in 2004, 13.4% in 2014 and 9.1% by 2018. Among those households incurring CHE, they spent 1.25 times of their capacity to pay in 2004 (intensity of CHE), 1.71 times in 2014 and 1.31 times by 2018. The impoverishment due to health spending was 4.8% in 2004, 5.1% in 2014 and 3.3% in 2018. The state variations in incidence and intensity of CHE and incidence of impoverishment is large. The concentration index (CI) of CHE was − 0.16 in 2004, − 0.18 in 2014 and − 0.22 in 2018 suggesting increasing inequality over time. The concentration curves based on CTP approach suggests that the CHE was concentrated among poor. The odds of incurring CHE were lowest among the richest households [OR 0.22; 95% CI: 0.21, 0.24], households with elderly members [OR 1.20; 95% CI:1.12, 1.18] and households using both inpatient and outpatient services [OR 2.80, 95% CI 2.66, 2.95]. Access to health insurance reduced the chance of CHE and impoverishment among the richest households. The pattern of impoverishment was similar to that of CHE. CONCLUSION: In the last 14 years, the CHE and impoverishment in India has declined while inequality in CHE has increased. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12939-021-01421-6.

SummaryThe Sustainable Development Goals (SDGs) are increasingly being used to measure developmental progress among and within countries. Achieving the health-related SDGs remains a primary concern of many developing countries. This study measured the progress in selected health-related indicators of SDGs in the states of India by social and economic groups, and predicted their likely progress by 2030. The health indicators analysed included health outcomes, nutrition, health care utilization and determinants of health. Data from the Census of India, Sample Registration System (SRS), National Family and Health Surveys (NFHSs) and National Sample Survey Organization (NSSO) were used in the analysis. Annual rate of progress (ARP) and the required rate of progress (RRP) were computed for selected indicators over the period 2005–06 to 2015–16. A Composite Index of Health (CIH) was used to understand the state of health of populations. The ARP was higher than the RRP in maternal care and reduction of under-five mortality, while ARP was lower than the RRP in undernutrition and sanitation. The ARP for health-related indicators showed a mixed pattern across religion and caste groups. The ARP for medical assistance at birth and immunization was highest among Scheduled Castes and that for reduction of under-five mortality was highest among Scheduled Tribes. The CIH was lowest in Uttar Pradesh (0.26) and highest in Goa (0.81). The association between the CIH and the Human Development Index (HDI) was significant, suggesting interlinkage between health and development. Notable improvements were observed in maternal and child health and maternal health care utilization across social groups in India over the period 2005–06 to 2015–16, and if the trends continue the country can achieve the SDG target in maternal health by 2030. However, progress in nutrition and other health indicators has been slow and uneven.