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

Abstract

Background: Numerous 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.

Methods: The 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.

Results: The 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.

Conclusion: Despite 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.

Keywords: HRFB; India; Multinomial logistic regression; NFHS; Reproductive health.

Fig. 1

Trends in the prevalence of high-risk fertility behaviours among married women in India, NFHS-1 (1992–93) to NFHS-5 (2019–21)

Fig. 2

Prevalence of any HRFB among women by states/UTs of India, NFHS-5 (2019–21). Abbreviations : Andaman and Nicobar Islands = AN, Andhra Pradesh = AP, Arunachal Pradesh = AR, Assam = AS, Bihar = BR, Chandigarh = CH , Chhattisgarh = CT, Delhi = DL , Daman and Diu and Dadra & Nagar Haveli = DD & DN, Goa = GA, Gujarat = GJ, Haryana = HR, Himachal Pradesh = HP, Jammu and Kashmir = JK , Jharkhand = JH, Karnataka = KA, Kerala = KL, Ladakh = LA, Lakshadweep = LD, Madhya Pradesh = MP, Maharashtra = MH, Manipur = MN, Meghalaya = ML, Mizoram = MZ, Nagaland = NL, Odisha = OD, Puducherry = PY , Punjab = PB, Rajasthan = RJ, Sikkim = SK, Tamil Nadu = TN, Telangana = TG, Tripura = TR, Uttarakhand = U K, Uttar Pradesh = UP, West Bengal = WB

Fig. 3

Prevalence of single HRFB among women by states/UTs of India, NFHS-5 (2019–21).  Abbreviations : Andaman and Nicobar Islands = AN, Andhra Pradesh = AP, Arunachal Pradesh = AR, Assam = AS, Bihar = BR, Chandigarh = CH , Chhattisgarh = CT, Delhi = DL , Daman and Diu and Dadra & Nagar Haveli = DD & DN, Goa = GA, Gujarat = GJ, Haryana = HR, Himachal Pradesh = HP, Jammu and Kashmir = JK , Jharkhand = JH, Karnataka = KA, Kerala = KL, Ladakh = LA, Lakshadweep = LD, Madhya Pradesh = MP, Maharashtra = MH, Manipur = MN, Meghalaya = ML, Mizoram = MZ, Nagaland = NL, Odisha = OD, Puducherry = PY , Punjab = PB, Rajasthan = RJ, Sikkim = SK, Tamil Nadu = TN, Telangana = TG, Tripura = TR, Uttarakhand = U K, Uttar Pradesh = UP, West Bengal = WB

Fig. 4

Prevalence of multiple HRFB among women by states/UTs of India, NFHS-5 (2019–21). Abbreviations : Andaman and Nicobar Islands = AN, Andhra Pradesh = AP, Arunachal Pradesh = AR, Assam = AS, Bihar = BR, Chandigarh = CH , Chhattisgarh = CT, Delhi = DL , Daman and Diu and Dadra & Nagar Haveli = DD & DN, Goa = GA, Gujarat = GJ, Haryana = HR, Himachal Pradesh = HP, Jammu and Kashmir = JK , Jharkhand = JH, Karnataka = KA, Kerala = KL, Ladakh = LA, Lakshadweep = LD, Madhya Pradesh = MP, Maharashtra = MH, Manipur = MN, Meghalaya = ML, Mizoram = MZ, Nagaland = NL, Odisha = OD, Puducherry = PY , Punjab = PB, Rajasthan = RJ, Sikkim = SK, Tamil Nadu = TN, Telangana = TG, Tripura = TR, Uttarakhand = U K, Uttar Pradesh = UP, West Bengal = WB