Education and non-communicable diseases in India: an exploration of gendered heterogeneous relationships.

BACKGROUND: While the association between education and non-communicable diseases (NCDs) is well established, it remains unclear whether this association varies by gender. The aim of this study was to examine two critical research questions: whether the association of education and NCDs is conditioned by gender and, if so, what are the factors contributing to this? METHODS: Data from the Longitudinal Aging Study in India Wave 1 (2017-2018) was used for the empirical analysis. The study employs bivariate, binary logistic regression and Oaxaca decomposition analyses. RESULTS: The results reveal that the net likelihood of having at least one chronic NCD increases with an increase in education level for men (<5 y of schooling: odds ratio [OR] 1.18 [95% confidence interval {CI} 1.09 to 1.28]; ≥10 y of schooling: OR 1.43 [95% CI 1.33 to 1.53]). However, for women, the result showed a contrasting pattern. The decomposition analysis revealed that the distinctive roles of marital status and working status in the diagnosis of morbidity for men and women are the key factors behind the gendered heterogeneous relationship of education and NCDs in India. CONCLUSIONS: The study found that it is important to acknowledge the potential impact of self-reporting bias in morbidity data while examining the relationship between education and NCDs.

Gender differences in premature mortality for cardiovascular disease in India, 2017-18.

BACKGROUND: The present study tries to provide a comprehensive estimate of gender differences in the years of life lost due to CVD across the major states of India during 2017-18. METHODS: The information on the CVD related data were collected from medical certification of causes of death (MCCD reports, 2018). Apart from this, information from census of India (2001, 2011), SRS (2018) were also used to estimate YLL. To understand the variation in YLL due to CVD at the state level, nine sets of covariates were chosen: share of elderly population, percentage of urban population, literacy rate, health expenditure, social sector expenditure, labour force participation, HDI Score and co-existence of other NCDs such as diabetes, & obesity. The absolute number of YLL and YLL rates were calculated. Further, Pearson's correlation had been calculated and to understand the effect of explanatory variables on YLL due to CVD, multiple linear regression analysis had been applied. RESULTS: Men have a higher burden of premature mortality in terms of Years of life lost (YLL) due to CVD than women in India, with pronounced differences at adult ages of 50-54 years and over. The age pattern of YLL rate suggests that the age group 85 + makes the highest contribution to the overall YLL rate due to CVD. YLL rate showed a J-shaped relationship with age, starting high at ages below 1 years, dropping to their lowest among children aged 1-4 years, and rising again to highest levels at 85 + years among both men and women. In all the states except Bihar men had higher estimated YLL due to CVD for all ages than women. Among men the YLL due to CVD was higher in Tamil Nadu followed by Madhya Pradesh and Chhattisgarh. On the other hand, the YLL due to CVD among men was lowest in Jharkhand followed by Assam. Similarly, among women the YLL due to CVD was highest in Tamil Nadu followed by Madhya Pradesh and Chhattisgarh. While, the YLL due to CVD among women was lowest in Jharkhand. Irrespective of gender, all factors except state health expenditure were positively linked with YLL due to CVD, i.e., as state health expenditure increases, the years of life lost (YLL) due to CVDs falls. Among all the covariates, the proportion of a state's elderly population emerges as the most significant predictor variable for YLL for CVDs (r = 0.42 for men and r = 0.50 for women). CONCLUSION: YLL due to cardiovascular disease varies among men and women across the states of India. The state-specific findings of gender differences in years of life lost due to CVD may be used to improve policies and programmes in India.

Socio-economic inequalities in burden of communicable and non-communicable diseases among older adults in India: Evidence from Longitudinal Ageing Study in India, 2017-18.

Developing countries like India grapple with significant challenges due to the double burden of communicable and non-communicable disease in older adults. Examining the distribution of the burden of different communicable and non-communicable diseases among older adults can present proper evidence to policymakers to deal with health inequality. The present study aimed to determine socioeconomic inequality in the burden of communicable and noncommunicable diseases among older adults in India. This study used Longitudinal Ageing study in India (LASI), Wave 1, conducted during 2017-2018. Descriptive statistics along with bivariate analysis was used in the present study to reveal the initial results. Binary logistic regression analysis was used to estimate the association between the outcome variables (communicable and non-communicable disease) and the chosen set of separate explanatory variables. For measurement of socioeconomic inequality, concentration curve and concentration index along with state wise poor-rich ratio was calculated. Additionally, Wagstaff's decomposition of the concentration index approach was used to reveal the contribution of each explanatory variable to the measured health inequality (Communicable and non- communicable disease). The study finds the prevalence of communicable and non-communicable disease among older adults were 24.9% and 45.5% respectively. The prevalence of communicable disease was concentrated among the poor whereas the prevalence of NCDs was concentrated among the rich older adults, but the degree of inequality is greater in case of NCD. The CI for NCD is 0.094 whereas the CI for communicable disease is -0.043. Economic status, rural residence are common factors contributing inequality in both diseases; whereas BMI and living environment (house type, drinking water source and toilet facilities) have unique contribution in explaining inequality in NCD and communicable diseases respectively. This study significantly contributes in identifying the dichotomous concentration of disease prevalence and contributing socio- economic factors in the inequalities.

Prevalence, socio-demographic determinants, and self-reported reasons for hysterectomy and choice of hospitalization in India.

BACKGROUND: There is limited evidence of hysterectomy in India because of a lack of data in large-scale, nationally representative health surveys. In 2015-16, the fourth National Family Health Survey (NFHS-4)-a cross-sectional survey-collected for the first-time direct information on hysterectomy and self-reported reasons for undergoing the procedure among women in the reproductive age group. The current study evaluates the prevalence, determinants, and choice of hospitalization (Public vs. Private) for conducting hysterectomy in India among women aged 15-49 years in 29 states and seven union territories (UTs) based on the new large-scale population-based nationally representative dataset (NFHS 5). METHODS: Cross-tabulations and percentage distributions were utilized to analyse the prevalence of hysterectomy and the choice of hospitalization (public vs. private) across different socioeconomic backgrounds and reasons for undergoing hysterectomy. A multivariate binary logistic regression model was also used to find statistically significant determinants of hysterectomy. RESULTS: In India as a whole, 3.3% of women aged 15-49 years had undergone a hysterectomy. The percentage of women who had undergone the procedure was found to vary considerably across the states and the UTs. The southern region stands out for the considerably higher prevalence of hysterectomy; particularly in the states of Andhra Pradesh (8.7%) and Telangana (8.2%), the prevalence was very high followed by Bihar (6%) and Gujrat (4%). On the other hand, the North-eastern region had the lowest prevalence of hysterectomy (1.2%). A noticeable fact that emerged was that the majority of the hysterectomies were performed in the private sector (69.6%) in India. But the scenario was quite different in north-eastern region as in this region more hysterectomies were performed in public health facilities (73%) rather than private health facilities (26.7%). Age, place of residence, religion, caste, level of education, geographic region, wealth quintiles, parity, age at first cohabitation of women were found to be the socio-demographic determinants statistically associated with hysterectomy in India. The likelihood of hysterectomy was higher among women living in rural areas (AOR: 1.3, CI: 1.23-1.35), in the richest wealth quintile (AOR 2.6; CI 2.37-2.76) and in the southern region (AOR 1.6; CI 1.47-1.66). The reasons frequently reported for hysterectomy were excessive menstrual bleeding/pain, followed by fibroids/cysts. CONCLUSION: This study has attempted to analyse hysterectomy prevalence and its socio-economic determinants using the latest fifth round of NFHS data of all the states and covering 21 states and union territories of India, which gives wider coverage of hysterectomy and more recent with accurate data. More research is needed therefore to unravel the complex dynamics of hysterectomy in India (and elsewhere) which could be used to help women make more informed choices and in turn advance their reproductive health and rights.