Estimation and probabilistic projection of levels and trends in the sex ratio at birth in seven provinces of Nepal from 1980 to 2050: a Bayesian modeling approach

Abstract

Background The 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. Methods We 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. Results In 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. Conclusions Our 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.

Impact of maternal factors and environmental stress on sex ratio in Southern Poland

“…As per Polish regulations, this hospital is classi ed as a second-degree referral center, which means that high-risk pregnancies, including multiple pregnancies, are typically transferred to a higher-level referral center, such as Rzeszów, located approximately 56 km away [55]. This is particularly relevant for preterm births, as twin pregnancies are at a higher risk of premature delivery, as well as other complications during pregnancy [56, 57,58,59].…”

Suspected illegal abortion and unsafe abortion leading to uterine rupture and incomplete abortion: A case report

“…Hence, having a male child is preferred in these countries [ [6] , [7] , [8] , [9] ]. Also, sex-selective abortion is rising globally, particularly in South-East Asia [ 1 , [10] , [11] , [12] , [13] ]. This leads to a skewed birth rate and can be detrimental to the population control policy.…”

“…This leads to a skewed birth rate and can be detrimental to the population control policy. Furthermore, in countries that prohibit sex-selective abortion, couples can seek illegal options and abort the foetus [ 9 , 13 , 14 ]. The couples may take the help of service providers lacking the required skills, leading to unsafe abortion practices.…”

Bayesian Probabilistic Projection of Population Census in the Kingdom of Saudi Arabia

“…Alparslan et al [3] suggested new Bayesian inference paradigm differentially distributed private linear regression using technique of Markov Chain Monte Carlo (MCMC) to get regression coefficients for appropriate model prediction and they were able to provide numerical results. Chao et al [13] also made use of the Bayesian modelling approach to estimate and project the sex ratio at births' levels and trends in seven provinces of Nepal ranging from the year 1980 to 2050.…”