scholarly journals Short interpregnancy interval and low birth weight births in India: Evidence from National Family Health Survey 2015-16

2020 ◽  
Vol 12 ◽  
pp. 100700
Author(s):  
Ajit Kumar Kannaujiya ◽  
Kaushalendra Kumar ◽  
Ashish Kumar Upadhyay ◽  
Lotus McDougal ◽  
Anita Raj ◽  
...  
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Health Survey ◽  
Family Health ◽  
National Family Health Survey ◽  
Interpregnancy Interval ◽  
National Family ◽  
Short Interpregnancy Interval

scholarly journals Low birth weight among tribal in India: Evidence from National Family Health Survey-4

2021 ◽  
Vol 9 ◽  
pp. 360-366
Author(s):  
Nutan Kumari ◽  
Kisan Algur ◽  
Praveen Kailash Chokhandre ◽  
Pradeep S. Salve
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Health Survey ◽  
Family Health ◽  
National Family Health Survey ◽  
National Family

scholarly journals Maternal determinants of low birth weight among Indian children: Evidence from the National Family Health Survey-4, 2015-16

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244562
Author(s):  
Ankita Zaveri ◽  
Pintu Paul ◽  
Jay Saha ◽  
Bikash Barman ◽  
Pradip Chouhan
Keyword(s):  
Public Health ◽  
Birth Weight ◽  
Low Birth Weight ◽  
Health Survey ◽  
Family Health ◽  
Public Facility ◽  
National Family Health Survey ◽  
Maternal Factors ◽  
Indian Children ◽  
National Family

Objective Low birth weight (LBW) is a serious public health problem in low- and middle-income countries and a leading cause of death in the first month of life. In India, about 18% of children are born with LBW (<2500 grams) in 2015–16. In this study, we aim to examine the influence of maternal factors and socio-demographic covariates on LBW in Indian children. Methods Data were drawn from the fourth round of the National Family Health Survey (NFHS-4), conducted in 2015–16. A cross-sectional study was designed using a stratified two-stage sampling technique. Cross-tabulation, Pearson’s chi-squared test, and multivariate logistic regression analyses were employed to assess the impact of maternal factors and other covariates on children’s LBW. Results Of total participants (n = 147,762), 17.5% of children were found to be born with LBW. The study revealed that women who had prior experience of stillbirth (Adjusted odds ratio [AOR]: 1.20, 95% CI: 1.04–1.38) and any sign of pregnancy complications (AOR: 1.08, 95% CI: 1.05–1.11) were more likely to have LBW children, even after adjusting for a range of covariates. Maternal food diversity was found to a protective factor against children’s LBW. Women with underweight and anemic condition were associated with an increased likelihood of LBW children. Regarding maternity care, women who attended ≥4 ANC visits (AOR: 0.84, 95% CI: 0.80–0.88), took iron tablets/syrup during pregnancy (AOR: 0.94, 95% CI: 0.90–0.98), and delivered in a public health facility (AOR: 0.84, 95% CI: 0.79–0.88) were less likely to have LBW babies. Besides, various socio-demographic factors such as place of residence, caste, religion, education, wealth quintile, and geographical region were significantly associated with LBW of children. Conclusion Interventions are needed for adequate ANC utilization, improvement in public facility-based delivery, providing iron supplementation, and uptake of balanced energy-protein diet among pregnant mothers. Besides, special attention should be given to the socio-economically disadvantaged women to address adverse pregnancy and birth outcomes including LBW.

Comparison of Growth in Children 6 to 59 Months of Age According to Birth Order: Insights From the National Family Health Survey-4 India

2020 ◽  
Author(s):  
Ananta Ghimire ◽  
Aravind Dharmaraj
Keyword(s):  
Birth Weight ◽  
Birth Order ◽  
Health Survey ◽  
Strong Predictor ◽  
Family Health ◽  
Public Health Problem ◽  
Major Public Health Problem ◽  
National Family Health Survey ◽  
Study Results ◽  
National Family

Abstract Background Undernutrition continues to be a major public health problem throughout the world. The present study aimed to understand the prevalence and determinants of undernutrition in India and determine what extent it differs by birth order, other child level, maternal and socioeconomic factors.MethodsThis study used information from a total weighted sample of 128859 mothers from India National Family Health Survey 4. Univariate and Multivariate logistic regression were used to investigate the association between undernutrition with birth order, other child level, maternal and socio-economic factors. Three models were constructed for the study, model 1 as univariate, model 2 adjusting with birth order and socioeconomic predictors and model 3 adjusting with all the predictors included in the study. Results The prevalence of stunting, underweight and wasting were 37.9, 34.0 and 20.7 respectively. The mean age of children was 2.4 years (standard deviation 1.3) of which majority were second order birth (33.6%), males (54.5%), anemic (58.9%) and normal birth weight (87.2%). All three models showed that higher birth order was a strong predictor of a child being stunted and underweight after adjusting for potential confounders. Children with lower wealth quintiles, anemia, male, low birth weight and vaginal delivery had higher odds of being stunted, wasted and underweight in model-3 adjusted analysis.Conclusion The findings from this study provide an important interaction between birth order and child undernutrition status in India. However, further longitudinal studies are required to establish such cause-effect relationship between birth order and undernutrition.

scholarly journals Missed opportunities for delivering nutrition interventions in first 1000 days of life in India: insights from the National Family Health Survey, 2006 and 2016

2021 ◽  
Vol 6 (2) ◽  
pp. e003717
Author(s):  
Phuong Hong Nguyen ◽  
Rasmi Avula ◽  
Lan Mai Tran ◽  
Vani Sethi ◽  
Alok Kumar ◽  
...  
Keyword(s):  
Health Survey ◽  
Urban Areas ◽  
Family Health ◽  
Universal Coverage ◽  
National Family Health Survey ◽  
Nutrition Interventions ◽  
Missed Opportunities ◽  
Health And Nutrition ◽  
National Family ◽  
Opportunity Gaps

ObjectivesExisting health and community nutrition systems have the potential to deliver many nutrition interventions. However, the coverage of nutrition interventions across the delivery platforms of these systems has not been uniform. We (1) examined the opportunity gaps between delivery platforms and corresponding nutrition interventions through the continuum of care in India between 2006 and 2016 and and (2) assessed inequalities in these opportunity gaps.MethodsWe used two rounds of the National Family Health Survey data from 2005 to 2006 and 2015–2016 (n=36 850 and 190 898 mother–child dyads, respectively). We examine the opportunity gaps over time for seven nutrition interventions and their associated delivery platforms at national and state levels. We assessed equality and changes in equality between 2006 and 2016 for opportunity gaps by education, residence, socioeconomic status (SES), public and private platforms.ResultsCoverage of nutrition interventions was consistently lower than the reach of their associated delivery platforms; opportunity gaps ranging from 9 to 32 percentage points (pp) during the pregnancy, 17 pp during delivery and 9–26 pp during childhood in 2006. Between 2006 and 2016, coverage improved for most indicators, but coverage increases for nutrition interventions was lower than for associated delivery platforms. The opportunity gaps were larger among women with higher education (22–57 pp in 2016), higher SES status and living in urban areas (23–57 pp), despite higher coverage of most interventions and the delivery platforms among these groups. Opportunity gaps vary tremendously by state with the highest gaps observed in Tripura, Andaman and Nicobar islands, and Punjab for different indicators.ConclusionsIndia’s progress in coverage of health and nutrition interventions in the last decade is promising, but both opportunity and equality gaps remained. It is critical to close these gaps by addressing policy and programmatic delivery systems bottlenecks to achieve universal coverage for both health and nutrition within the delivery system.

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