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Probabilistic projection of the sex ratio at birth and missing female births by State and Union Territory in India.

ABSTRACT: The sex ratio at birth (SRB) in India has been reported to be imbalanced since the 1970s. Previous studies have shown there is a great variation in the SRB between geographic locations across India till 2016. Considering the enormous population and regional heterogeneity of India, producing probabilistic SRB projections at the state level is crucial for policy planning and population projection. In this paper, we implement a Bayesian hierarchical time series model to project the SRB across India by state. We generate SRB probabilistic projections from 2017 to 2030 for 29 States and Union Territories (UTs) in India, and present results for 21 States/UTs with data available from the Sample Registration System. Our analysis takes into account two state-specific factors that contribute to sex-selective abortion in India, resulting in sex imbalances at birth: the intensity of son preference and fertility squeeze. We project that the highest deficits in female births will occur in Uttar Pradesh, with a cumulative number of missing female births of 2.0 (95% credible interval [1.9; 2.2]) million from 2017 to 2030. The total female birth deficits during 2017-2030 for the whole of India is projected to be 6.8 [6.6; 7.0] million.

SUBMITTER: Chao F

PROVIDER: S-EPMC7446920 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Probabilistic projection of the sex ratio at birth and missing female births by State and Union Territory in India.

Chao Fengqing F Guilmoto Christophe Z CZ K C Samir S Ombao Hernando H

PloS one 20200819 8

The sex ratio at birth (SRB) in India has been reported to be imbalanced since the 1970s. Previous studies have shown there is a great variation in the SRB between geographic locations across India till 2016. Considering the enormous population and regional heterogeneity of India, producing probabilistic SRB projections at the state level is crucial for policy planning and population projection. In this paper, we implement a Bayesian hierarchical time series model to project the SRB across India ...[more]

PMID: 32813704

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Project description:BackgroundThe sex ratio at birth (SRB; ratio of male to female births) in Nepal has been reported around the normal level on the national level. However, the national SRB could mask the disparity within the country. Given the demographic and cultural heterogeneities in Nepal, it is crucial to model Nepal SRB on the subnational level. Prior studies on subnational SRB in Nepal are mostly based on reporting observed values from surveys and census, and no study has provided probabilistic projections. We aim to estimate and project SRB for the seven provinces of Nepal from 1980 to 2050 using a Bayesian modeling approach.MethodsWe compiled an extensive database on provincial SRB of Nepal, consisting 2001, 2006, 2011, and 2016 Nepal Demographic and Health Surveys and 2011 Census. We adopted a Bayesian hierarchical time series model to estimate and project the provincial SRB, with a focus on modelling the potential SRB imbalance.ResultsIn 2016, the highest SRB is estimated in Province 5 (Lumbini Pradesh) at 1.102, corresponding to 110.2 male births per 100 female births, with a 95% credible interval (1.044, 1.127) and the lowest SRB is in Province 2 at 1.053 (1.035, 1.109). The SRB imbalance probabilities in all provinces are generally low and vary from 16% in Province 2 to 81% in Province 5 (Lumbini Pradesh). SRB imbalances are estimated to have begun at the earliest in 2001 in Province 5 (Lumbini Pradesh) with a 95% credible interval (1992, 2022) and the latest in 2017 (1998, 2040) in Province 2. We project SRB in all provinces to begin converging back to the national baseline in the mid-2030s. By 2050, the SRBs in all provinces are projected to be around the SRB baseline level.ConclusionsOur findings imply that the majority of provinces in Nepal have low risks of SRB imbalance for the period 1980-2016. However, we identify a few provinces with higher probabilities of having SRB inflation. The projected SRB is an important illustration of potential future prenatal sex discrimination and shows the need to monitor SRB in provinces with higher possibilities of SRB imbalance.

Project description:BackgroundAcute respiratory infections (ARI) are the most common illnesses affecting people of all ages worldwide. Viruses contribute to 30-70% of acute respiratory infections. Identification of these respiratory viruses is not given high priority except influenza; however, the knowledge about prevalence of non-influenza viruses, their seasonal pattern and genetic evolution have significant epidemiological value.MethodsAs a part of National Influenza-like illness surveillance programme, respiratory specimens were collected children and adults with symptoms of ILI or ARI, between January 2012 and March 2015 (including SARI cases). Real-time PCR was done to identify 13 respiratory viruses. Sequencing was done for representative isolates of each virus using ABI 3730 Genetic Analyzer.ResultsDuring the study period between January 2012 and March 2015, a total of 648 patients with symptoms of ARI were included in this study. The mean age of the patients was 20.2 years (SD = 19.13, median = 18); 292 (45.1%) were children (≤13 years) and 356 (54.9%) were adults. Respiratory viruses were identified in 44% (287/648) of all patients. Influenza accounted for the maximum number of cases- 179/648 (27.6%). Among the non-influenza viruses, RSV predominated with 34 cases (5.2%), followed by HMPV 24 (3.7%) and PIV-3 20 (3%). Four patients died due to INF A/H1N1 (2012-2, 2015-2) as a result of acute respiratory distress syndrome (ARDS) (CFR 3.7%). Among the non-influenza viruses, no particular seasonality pattern was observed over the different months of the study period.ConclusionAntibiotic usage in treating acute respiratory infections empirically is not justified as nearly half of ARI are due to viruses; nearly 28% of them were due to influenza viruses. Among the non-influenza viruses, RSV predominated, followed by HMPV. This study is based on an active influenza surveillance initiated after 2009 pandemic influenza outbreak, in the Union territory of Puducherry which has contributed significantly to the knowledge of the burden of influenza and non-influenza viruses among children and adults. Such surveillance network has paved the way for better diagnosis and timely therapeutic interventions.

Dataset Information

Probabilistic projection of the sex ratio at birth and missing female births by State and Union Territory in India.

Publications

Probabilistic projection of the sex ratio at birth and missing female births by State and Union Territory in India.

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