Evidence map›Paper›PMID 38413929›Full record

ArticleBMC public health2024

Trends, patterns and predictors of high-risk fertility behaviour among Indian women: evidence from National Family Health Survey.

Pooja Singh, Kaushalendra Kumar Singh

Open access · goldAbstract read
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Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
6.7field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Pooja SinghDepartment of Statistics, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, India. pooja.singh04@bhu.ac.in.
Kaushalendra Kumar SinghDepartment of Statistics, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, India.
Banaras Hindu University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNumerous studies have demonstrated that high-risk fertility behaviour (HRFB), which includes maternal age below 18 or above 34 years, short birth intervals (less than 24 months), and high parity (birth order above 4), is associated with adverse maternal and child health outcomes. There is a substantial research gap in the domain of high-risk fertility behaviour in the Indian context. Therefore, this study is designed to investigate the current trends and patterns in the prevalence of high-risk births among Indian women, with a primary focus on identifying contributing factors associated with this prevalence.

methodsThe study utilized data from the nationally representative National Family Health Survey (NFHS), which has been conducted in five rounds since 1992-93. Data from all rounds were used to assess the overall trend. However, data from the most recent round of NFHS, conducted during 2019-21, were employed to evaluate current levels and patterns of HRFB prevalence and to identify socio-economic and demographic predictors of HRFB using binomial and multinomial logistic regression models.

resultsThe prevalence of HRFB has exhibited a consistent decreasing pattern from 1992 to 93 to 2019-21 in India. However, 29.56% of married women continue to experience high-risk births with notably higher rates in several states (e.g., 49.85% in Meghalaya and 46.41% in Bihar). Furthermore, socio-demographic factors like wealth index, educational level, social group, religion, mass media exposure, family size, age at marriage, type and region of residence, and reproductive factors like birth intention, place and type of delivery, ANC visits and current contraceptive use were identified as significant predictors of high-risk births among women in India.

conclusionDespite a 20.4 percentage point decline in HRFB prevalence over the past three decades, a significant proportion of women in specific regions and demographic subgroups continue to experience high-risk births. Therefore, the present study recommends interventions aimed at preventing high-risk births among women in India, with particular emphasis on states with high HRFB prevalence and women from socioeconomically disadvantaged backgrounds.

Indexed as

FertilityMarriageAdultChildFamily CharacteristicsFemaleHealth SurveysHumansIndiaMaternal AgeHRFBIndiaMultinomial logistic regressionNFHSReproductive health

Identifiers

PMID38413929
PMCPMC10900591
OpenAlexW4392200115

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.