Patriarchy, Fertility and Excess Female Child Mortality in India.

Research investigating association between patriarchy and demographic behavior is limited in India. The only study on this subject utilized 1981 Indian Census data to examine associations between patriarchy and fertility. We examined the association of patriarchy, measured using India Patriarchy Index (IPI), with total fertility rate (TFR) and excess female child mortality in India.

Menstrual disorder and its treatment seeking among adolescent girls in India: evidence from nationwide survey.

Background: Adolescents make up 18 % of India's total population, with 116 million being girls. Most research has focused on menstrual health and hygiene practices, with limited studies on menstrual pain/disorder (MPD) among adolescent girls using micro-level data from specific regions of India.

Objectives: This study aims to investigate the prevalence of menstrual pain/distress, its treatment-seeking behavior, and its associated predictors among adolescent girls.

Trends in child marriage, sexual violence, early sexual intercourse and the challenges for policy interventions to meet the sustainable development goals.

Introduction: Child marriage remains a prevalent issue in low- and middle-income countries (LMIC) despite global declines. Girls are disproportionately affected, facing health risks, limited education, and restricted decision-making power. We aim to provide insights for child marriage prevalence across LMIC from 1990 to 2020, with a focus on sexual violence and early sexual intercourse for public health policy interventions.

Burden of Anaemia, Hypertension and Diabetes among pregnant women in India.

Non-communicable Diseases such as anaemia, hypertension and diabetes and their treatment may upsurge the risk of childbirth-related complications for both women and their babies. The present study is an attempt to assess the level and determinants of Anaemia, Hypertension and Diabetes among pregnant women using the fourth round of National Family Health Survey-4 (2015-16) data. Bivariate and logistic regression techniques have been used for data analysis.