Association of child health and household amenities in high focus states in India: a district-level analysis

Gouda, Jitendra; Gupta, Ashish Kumar; Yadav, Ajit Kumar

doi:10.1136/bmjopen-2015-007589

Cited by 10 publications

(7 citation statements)

References 19 publications

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“…Finding of the present study shows the inverse relationship between district’s economic development with nutritional outcomes and also highlighted that the poor nutritional status of children was more concentrated in less developed districts of India. A similar finding was also reported by study from India along with other child health related indicators [35–37]. However, the majority of the existing literatures examined the socioeconomic inequality at household level.…”

Section: Discussionsupporting

confidence: 86%

Socio-economic inequality in malnutrition among children in India: an analysis of 640 districts from National Family Health Survey (2015–16)

Singh

Srivastava

Upadhyay

2019

Int J Equity Health

102

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BackgroundDespite a fast-growing economy and the largest anti-malnutrition programme, India has the world’s worst level of child malnutrition. Despite India’s 50% increase in GDP since 1991, more than one third of the world’s malnourished children live in India. Among these, half of the children under age 3 years are underweight and a third of wealthiest children are over-nutrient. One of the major causes for malnutrition in India is economic inequality. Therefore, using the data from the fourth round of National Family Health Survey (2015–16), present study aims to examine the socio-economic inequality in childhood malnutrition across 640 districts of India.MethodConcentration curve and generalized concentration index were used to examine the socioeconomic inequalities in malnutrition. However, regression-based decomposition methodology was used to decomposes the causes of inequality in childhood malnutrition.ResultResult shows that about 38% children in India were stunted and 35% were underweight during 2015–16. Prevalence of stunting and underweight children varies considerably across Indian districts (13 to 65% and 7 to 67% respectively). Districts having the higher share of undernourished children is coming from the particular regions like central, east and west part of the country. On an average about 35% of household in a district having the access of safe drinking water and 42% of household in a district exposed to open defecation. The study found the inverse relationship between district’s economic development with childhood stunting and underweight. The concentration of stunted as well as underweight children were found in least developed districts of India. Decomposition approach found that practice of open defecation is positively influenced the inequality in stunting and underweight. Further, inequality in undernutrition is accelerated by the height and education of the mother, and availability of safe drinking water in a district.ConclusionsThe districts that lied out in a spectrum of developmental diversity are required some specific set of information’s that covering socio-economic, demographic and health-related quality of life of people in those backward districts. More generally, policies to avail improved water and sanitation facility to public and female literacy should be continued. It is also important to see that the benefits of both infrastructure and more general economic development are spread more evenly across districts.

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Section: Discussionsupporting

confidence: 86%

Socio-economic inequality in malnutrition among children in India: an analysis of 640 districts from National Family Health Survey (2015–16)

Singh

Srivastava

Upadhyay

2019

Int J Equity Health

102

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“…Intervention to increase access to livelihood can pave the way for reducing income inequality and reduce IMR. Factors related to pre-and postnatal care, e.g., ANC, safe delivery, PNC, and variables related to personal illness control such as recent episodes of ARI and diarrhea among children have statistically significant association with infant mortality, which is in concordance with other studies in India (Gokhale et al 2002;Gouda et al 2015). Interestingly, analysis reveals that labor force participation, birth weight, and birth interval were not associated with IMR in the spatial lag as well as error models.…”

Section: Discussionsupporting

confidence: 82%

“…Our attempt is consistent with recent studies that focused on exploring macro-level determinants of child health (Gouda et al 2015;Goli and Jaleel 2014;Bhattacharya and Cornilius 2011). We have tried to show that there is a high degree of spatial clustering in IMR.…”

Section: Introductionsupporting

confidence: 71%

Spatial clustering and risk factors of infant mortality: district-level assessment of high-focus states in India

Gupta

Ladusingh

Borkotoky

2016

Genus

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The study analyzes the spatial clustering and risk factors of infant mortality across high-focus states of India, using the Annual Health Survey (2010-2011), Census of India (2011), and District Level Household and Facility Survey-3 (2007-2008. Research has found substantial spatial autocorrelation across the districts and identified the "hot spots" characterized by higher infant mortality rate (IMR) in the districts of the central region (Uttar Pradesh and Madhya Pradesh) of India. This study has considered several theoretical perspectives and implements a series of spatial regression models that allows accounting for household amenities and mother/child and health facility variables to determine the key risk factors of infant mortality. Our empirical analysis underscores the importance of the infrastructure of the health facility in improving the infant mortality scenario of the districts. The regression results show that the districts with a higher proportion of 24-h functioning primary healthcare centers have overall less infant mortality. In addition, the absence of drinking water from a treated source, unavailability of toilet facilities, and higher proportion of people in the bottom wealth quintile in the household were adversely associated with the IMR. In conclusion, reduction of infant mortality would be possible only if area-specific measures would be adopted on those clusters of districts where infant mortality is high irrespective of the state they belong to.

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“…A study in rural India reported that the odds of neonatal death were lower for infants born to unemployed mothers (OR=0.89) ( 29 ). A negative association was also found with infant and under-five mortality and female labour force participation in India ( 45 ). In addition our study did not find any significant association between child mortality and housing infrastructure as measured by access to safe water, clean fuel, and electricity; however, several other studies have established strong associations between poor health and poor housing and housing infrastructure ( 16 , 17 , 33 , 45 ).…”

Section: Discussionmentioning

confidence: 96%

The importance of intersectoral factors in promoting equity-oriented universal health coverage: a multilevel analysis of social determinants affecting neonatal infant and under-five mortality in Bangladesh

Huda

Tahsina

Arifeen

et al. 2016

Global Health Action

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IntroductionHealth is multidimensional and affected by a wide range of factors, many of which are outside the health sector. To improve population health and reduce health inequality, it is important that we take into account the complex interactions among social, environmental, behavioural, and biological factors and design our health interventions accordingly.ObjectivesThis study examines mortality differentials in children of different age groups by key social determinants of health (SDH) including parental education and employment, mother's level of autonomy, age, asset index, living arrangements (utilities), and other geographical contextual factors (area of residence, road conditions).DesignWe used data from the two rounds of Bangladesh Health and Demographic Survey, a nationally representative sample survey of the population residing in Bangladesh. Multilevel logistic models were used to study the impact of SDH on child mortality.ResultsThe study found that the mother's age, the education of both parents, the mother's autonomy to take decisions about matters linked to the health of her child, the household socio-economic conditions, the geographical region of residence, and the condition of the roads were significantly associated with higher risks of neonatal, infant, and under-five mortality in Bangladesh.ConclusionThe study findings suggest there are complex relationships among different SDH. Thus larger intersectoral actions will be needed to reduce disparities in child health and mortality and achieve meaningful progress towards equity-oriented universal health coverage.

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Association of child health and household amenities in high focus states in India: a district-level analysis

Cited by 10 publications

References 19 publications

Socio-economic inequality in malnutrition among children in India: an analysis of 640 districts from National Family Health Survey (2015–16)

Socio-economic inequality in malnutrition among children in India: an analysis of 640 districts from National Family Health Survey (2015–16)

Spatial clustering and risk factors of infant mortality: district-level assessment of high-focus states in India

The importance of intersectoral factors in promoting equity-oriented universal health coverage: a multilevel analysis of social determinants affecting neonatal infant and under-five mortality in Bangladesh

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