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2 "Infant mortality"
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Original Articles
Ecological context of infant mortality in high-focus states of India
Laishram Ladusingh, Ashish Kumar Gupta, Awdhesh Yadav
Epidemiol Health. 2016;38:e2016006.   Published online March 5, 2016
DOI: https://doi.org/10.4178/epih.e2016006
  • 18,623 View
  • 199 Download
  • 8 Web of Science
  • 8 Crossref
AbstractAbstract PDF
Abstract
OBJECTIVES
This goal of this study was to shed light on the ecological context as a potential determinant of the infant mortality rate in nine high-focus states in India.
METHODS
Data from the Annual Health Survey (2010-2011), the Census of India (2011), and the District Level Household and Facility Survey 3 (2007-08) were used in this study. In multiple regression analysis explanatory variable such as underdevelopment is measured by the non-working population, and income inequality, quantified as the proportion of households in the bottom wealth quintile. While, the trickle-down effect of education is measured by female literacy, and investment in health, as reflected by neonatal care facilities in primary health centres.
RESULTS
A high spatial autocorrelation of district infant mortality rates was observed, and ecological factors were found to have a significant impact on district infant mortality rates. The result also revealed that non-working population and income inequality were found to have a negative effect on the district infant mortality rate. Additionally, female literacy and new-born care facilities were found to have an inverse association with the infant mortality rate.
CONCLUSIONS
Interventions at the community level can reduce district infant mortality rates.
Summary

Citations

Citations to this article as recorded by  
  • Does club convergence matter in health outcomes? Evidence from Indian states
    Ajit Nag, Andrej Privara, Beata Gavurova, Jalandhar Pradhan
    BMC Public Health.2023;[Epub]     CrossRef
  • Major Determinants of Infant Mortality: District-level Evidence from Annual Health Survey States of India
    Subhanil Banerjee, Souren Koner, Arshleen Kaur, Charvi Sharma
    Journal of Health Management.2023;[Epub]     CrossRef
  • Does socio-economic inequality in infant mortality still exists in India? An analysis based on National Family Health Survey 2005–06 and 2015–16
    Pradeep Kumar, Ratna Patel, Shekhar Chauhan, Shobhit Srivastava, Ankur Khare, Kamlesh Kumar Patel
    Clinical Epidemiology and Global Health.2021; 9: 116.     CrossRef
  • Sociodemographic correlates of infant mortality in India: A review of national family health survey data
    Ratan Gupta, ManasPratim Roy
    CHRISMED Journal of Health and Research.2020; 7(1): 12.     CrossRef
  • Factors explaining regional variation in under-five mortality in India: An evidence from NFHS-4
    Jayanta Kumar Bora
    Health & Place.2020; 64: 102363.     CrossRef
  • Spatial heterogeneity of the associations of economic and health care factors with infant mortality in China using geographically weighted regression and spatial clustering
    Shaobin Wang, Jun Wu
    Social Science & Medicine.2020; 263: 113287.     CrossRef
  • A spatial analysis of childhood stunting and its contextual correlates in India
    Rupam Bharti, Preeti Dhillon, Pralip Kumar Narzary
    Clinical Epidemiology and Global Health.2019; 7(3): 488.     CrossRef
  • The persistent influence of caste on under-five mortality: Factors that explain the caste-based gap in high focus Indian states
    Jayanta Kumar Bora, Rajesh Raushan, Wolfgang Lutz, William Joe
    PLOS ONE.2019; 14(8): e0211086.     CrossRef
Modeling and forecasting of the under-five mortality rate in Kermanshah province in Iran: a time series analysis
Mehran Rostami, Abdollah Jalilian, Behrooz Hamzeh, Zahra Laghaei
Epidemiol Health. 2015;37:e2015003.   Published online January 22, 2015
DOI: https://doi.org/10.4178/epih/e2015003
  • 17,496 View
  • 213 Download
  • 3 Web of Science
  • 4 Crossref
AbstractAbstract PDF
Abstract
OBJECTIVES
The target of the Fourth Millennium Development Goal (MDG-4) is to reduce the rate of under-five mortality by two-thirds between 1990 and 2015. Despite substantial progress towards achieving the target of the MDG-4 in Iran at the national level, differences at the sub-national levels should be taken into consideration.
METHODS
The under-five mortality data available from the Deputy of Public Health, Kermanshah University of Medical Sciences, was used in order to perform a time series analysis of the monthly under-five mortality rate (U5MR) from 2005 to 2012 in Kermanshah province in the west of Iran. After primary analysis, a seasonal auto-regressive integrated moving average model was chosen as the best fitting model based on model selection criteria.
RESULTS
The model was assessed and proved to be adequate in describing variations in the data. However, the unexpected presence of a stochastic increasing trend and a seasonal component with a periodicity of six months in the fitted model are very likely to be consequences of poor quality of data collection and reporting systems.
CONCLUSIONS
The present work is the first attempt at time series modeling of the U5MR in Iran, and reveals that improvement of under-five mortality data collection in health facilities and their corresponding systems is a major challenge to fully achieving the MGD-4 in Iran. Studies similar to the present work can enhance the understanding of the invisible patterns in U5MR, monitor progress towards the MGD-4, and predict the impact of future variations on the U5MR.
Summary

Citations

Citations to this article as recorded by  
  • Predicting the detection of leprosy in a hyperendemic area of Brazil: Using time series analysis
    Vera Gregório, Dinilson Pedroza, Celivane Barbosa, Gilberto Bezerra, Ulisses Montarroyos, Cristine Bonfim, Zulma Medeiros
    Indian Journal of Dermatology, Venereology and Leprology.2021; 87: 651.     CrossRef
  • Forecasting Malaysia Under-5 Mortality Using State Space Model
    N F Abd Nasir, A N Muzaffar, S N E Rahmat, W Z Wan Husin, N S Zainal Abidin
    Journal of Physics: Conference Series.2020; 1496: 012001.     CrossRef
  • Multivariate Long Memory Cohort Mortality Models
    Hongxuan Yan, Gareth Peters, Jennifer Chan
    SSRN Electronic Journal .2018;[Epub]     CrossRef
  • Forecast analysis of any opportunistic infection among HIV positive individuals on antiretroviral therapy in Uganda
    John Rubaihayo, Nazarius M. Tumwesigye, Joseph Konde-Lule, Fredrick Makumbi
    BMC Public Health.2016;[Epub]     CrossRef
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