Modelling Determinants of Deaths Attributable to External Causes Among Adults in India

Sil, Apyayee; Sil, Arpan; Dhillon, Preeti

doi:10.1177/00302228211009736

Cited by 2 publications

(1 citation statement)

References 37 publications

(56 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The number of children desired by women is a discrete random variable ranging from 1 to 10, which is used in a Poisson regression model (Wang & Famoye, 1997). The coefficients were exponentiated to yield the incident rate ratio (IRR) to ease the interpretation of the results (Sil & Dhillon, 2023).…”

Section: Methodsmentioning

confidence: 99%

Study on Marriage Pairings and Women’s Fertility Intentions in China

Tian,

He,

Wang

2023

Journal of Family Issues

View full text Add to dashboard Cite

The effect of marriage pairings on fertility intentions is specific and has attracted increasing scholarly attention in recent years. Using data from the China Family Panel Studies (CFPS), this study explored the impact of couples’ educational pairings, age pairings, and income pairings on women’s desired number of children and their preference for sons. The results showed that marital-educational pairing had a greater effect on women’s fertility intentions than age and income pairing. The effect of marital pairing on women’s fertility intentions is also influenced by women’s age and urban–rural differences. The study helps to understand the changes in women’s fertility intentions and the factors influencing them after the fertility policy transition in China and inspires scholars to pay more attention to the interaction process between couples in the study of fertility intentions.

show abstract

Section: Methodsmentioning

confidence: 99%

Study on Marriage Pairings and Women’s Fertility Intentions in China

Tian,

He,

Wang

2023

Journal of Family Issues

View full text Add to dashboard Cite

show abstract

Factors affecting External causes of deaths among adults (15–59 years) in South Indian states: A study using Bayesian model on National Family Health Survey-4 (2015–16) data

Sil

Dhillon

et al. 2021

Clinical Epidemiology and Global Health

Self Cite

View full text Add to dashboard Cite

The study aimed at finding risk factors associated with adult mortality (15-59 years) due to external causes (accidents, suicide, poisoning, homicide, and violence) of the South Indian states by using the fourth round of National Family Health Survey data. Despite having a higher literacy rate and comparatively being better developed than other Indian states, the number of external causes of deaths in the South Indian states is alarming. The study used Bayesian Logistic Regression method for analysis. Three Chain of Markov Chain and Monte Carlo (MCMC) model was used. The sex of the deceased was found to be an important factor in all 5 states (Tamil Nadu, Karnataka, Kerala, Tamil Nadu, Telangana and Andhra Pradesh). Place of residence was an important factor for all states except Karnataka. The prevalence of external adult deaths was high among femaleheaded households irrespective of all the south Indian states. The family members in Karnataka and Andhra Pradesh, wealth index in Telangana, drinking habit in Kerala, car access in Kerala and Tamil Nadu and massmedia access in Tamil Nadu were found significant factors (the model converged for the factors) that affecting external causes of deaths. Some holistic efforts should be undertaken by the Government for adult deaths by spreading awareness among adult, setting up specialized teams for policy-making and timely measures to curtail the underlying causes of such unnatural deaths and to ameliorate the overall situation.

show abstract

Modelling Determinants of Deaths Attributable to External Causes Among Adults in India

Cited by 2 publications

References 37 publications

Study on Marriage Pairings and Women’s Fertility Intentions in China

Study on Marriage Pairings and Women’s Fertility Intentions in China

Factors affecting External causes of deaths among adults (15–59 years) in South Indian states: A study using Bayesian model on National Family Health Survey-4 (2015–16) data

Contact Info

Product

Resources

About