Household Wealth Gradient in Low Birthweight in India: A Cross-Sectional Analysis

被引:1
|
作者
Ghose, Bishwajit [1 ]
机构
[1] Ctr Social Capital & Environm Res, Ottawa, ON K1M OZ2, Canada
来源
CHILDREN-BASEL | 2023年 / 10卷 / 07期
关键词
birthweight; household wealth; maternal and child health; India; HEALTH; IMPACT; RISK;
D O I
10.3390/children10071271
中图分类号
R72 [儿科学];
学科分类号
100202 ;
摘要
A low birthweight is a common complication that can result from numerous physiological, environmental, and socioeconomic factors, and can put babies at an increased risk for health issues such as breathing difficulties, developmental delays, and even death in severe cases. In this analysis, I aim to assess the differences in the burden of low birthweight based on household wealth status in India using data from the latest National Family Health Survey (NFHS 2019-21). The sample population includes 161,596 mother-child dyads. A low birthweight is defined as a weight that is <2500 g at birth. I used descriptive and multivariate regression analyses in R studio to analyse the data. The findings show that 16.86% of the babies had a low birthweight. At the state level, the percentage of low birthweights ranges from 3.85% in Nagaland to 21.81% in Punjab. The mean birthweights range from 2759.68 g in the poorest, 2808.01 g in the poorer, 2838.17 g in the middle, 2855.06 g in the richer, and 2871.30 g in the richest wealth quintile households. The regression analysis indicates that higher wealth index quintiles have progressively lower risks of low birthweight, with the association being stronger in the rural areas. Compared with the poorest wealth quintile households, the risk ratio of low birthweight was 0.90 times lower for the poorer households and 0.74 times lower for the richest households. These findings indicate that household wealth condition is an important predictor of low birthweight by which low-income households are disproportionately affected. As wealth inequality continues to rise in India, health policymakers must take the necessary measures to support the vulnerable populations in order to improve maternal and infant health outcomes.
引用
收藏
页数:10
相关论文
共 50 条
  • [31] The implementation of cross-sectional weights in household panel surveys
    Schonlau, Matthias
    Kroh, Martin
    Watson, Nicole
    STATISTICS SURVEYS, 2013, 7 : 37 - 57
  • [32] The impact of IVF on birthweight from 1991 to 2015: a cross-sectional study
    Castillo, Catherine M.
    Horne, Gregory
    Fitzgerald, Cheryl T.
    Johnstone, Edward D.
    Brison, Daniel R.
    Roberts, Stephen A.
    HUMAN REPRODUCTION, 2019, 34 (05) : 920 - 931
  • [34] Economic burden of cancer in India: Evidence from cross-sectional nationally representative household survey, 2014
    Rajpal, Sunil
    Kumar, Abhishek
    Joe, William
    PLOS ONE, 2018, 13 (02):
  • [35] Shared Sanitation versus Individual Household Latrines in Urban Slums: A Cross-Sectional Study in Orissa, India
    Heijnen, Marieke
    Routray, Parimita
    Torondel, Belen
    Clasen, Thomas
    AMERICAN JOURNAL OF TROPICAL MEDICINE AND HYGIENE, 2015, 93 (02): : 263 - 268
  • [36] The association between household wealth and the prevalence of child disability and specific functional limitations: Analysis of nationally representative cross-sectional surveys in 40 low- and middle-income countries
    Emerson, Eric
    Llewellyn, Gwynnyth
    DISABILITY AND HEALTH JOURNAL, 2022, 15 (04)
  • [37] NGOs in India: A cross-sectional study.
    Zachariah, M
    PACIFIC AFFAIRS, 2003, 76 (03) : 486 - 488
  • [38] Hypertension: A National Cross-Sectional Study in India
    Chakraborty, Sayantan
    Ussatayeva, Gainel
    Lee, Ming-Shinn
    Dalal, Koustuv
    TURK KARDIYOLOJI DERNEGI ARSIVI-ARCHIVES OF THE TURKISH SOCIETY OF CARDIOLOGY, 2022, 50 (04): : 276 - 283
  • [39] Household wellbeing and health risks in Mexican households with and without migrants: a cross-sectional analysis
    Leyva-Flores, Rene
    Pablo Gutierrez, Juan
    Infante, Cesar
    Gonzalez-Vazquez, Tonatiuh
    Magana-Valladares, Laura
    PUBLIC HEALTH REVIEWS, 2018, 39
  • [40] Large household reduces dementia mortality: A cross-sectional data analysis of 183 populations
    You, Wenpeng
    Henneberg, Maciej
    PLOS ONE, 2022, 17 (03):