Gender Disparity in Intra-Household Health Care Expenditure: - PDF document

Gender Disparity in Intra-Household Health Care Expenditure: Empirical Evidence from India Abstract “Excess female death” in India has sparked great attention in investigate gender discrimination in health care expenditure (HCE) for hospitalization in India. This study examines the intra- household gender disparity in HCE in treatment of illness and examines effect of demographic and socio-economic factors on gender disparity in HCE, using 25 th scheduled for two rounds (60 th and 71st) of the NSSO hospitalized cases. Descriptive statistics and bivariate analysis are used to describe the characteristics of sample study and to estimate average HCE. Oaxaca- Blinder decomposition used to understand the contribution of demographic and socio-economic factors results of gender gap in HCE. Results showed that there is a huge gender disparity in average HCE and disparity has been increased in 2014. Decomposition results suggest that about 84% gender difference in HCE is due to male-female difference in socio-economic, demographic and healthcare-related factors. Education level, type of disease, level of care and duration of stay in hospital are contributing towards widening the male-female gap in HCE. And 18% difference in male-female HCE is due to the effect of these factors. To reduce the gap between male-female OOP expenditure, we need to economically empower the women through improving education status and changes in gender attitude . 16

Introduction Gender disparity in health care and morbidly in India has been well documented in recent decades. The female advantage in life expectancy at birth is a recent phenomenon in India, unlike in many parts of the world (Canudas-Romo et al., 2015; Saikia et al. 2011). Also, the female advantage in overall life expectancy at birth masks the disadvantage spread across ages: In India, females are still subject to feticide and excess mortality (Bongaats, 2015; Sudha, 1999). Several research has shown that there is a significant variation in the health status of population and utilization of health care services (Batra et al., 2014; Baeten et. al., 2013; Joe et. al., 2008; Nikiema et. al., 2008; Purohit & Siddiqui, 1994). The literature on the social determinants of health showed how social and cultural factors affect health and longevity (Wilkinson & Marmot, 2003). One such factor is gender-based discrimination in health care utilization and lower health investment results of worsts health status of women and higher mortality compared to men. Recently, many researches has focused on gender discrimination and child health care, shows that parents are preferring to provide treatment for boys compared to girls when a household is facing tight resource constraints. For instance, Borooah (2004) shows that girls children were facing biased in getting proper nutritious and to be fully immunized results of excess female mortality (Rose, 1999) and decline sex ratios.. Anderson and Ray (2009, 2012) has shown that poor treatment and care at home of the female was leading causes of the risk of excess compared to males at each stage of lives. In a patriarchal society where female face discriminatory behavior in term of health care, nutrition intake, education and other opportunity, In India context are especially important to study the effect of gender on health. However, in India, the effect of gender on treatment seeking behavior within the household are relatively got less attention. While Pandey et al. (2002), find gender discrimination in the treatment of disease like diarrhea in rural West Bengal. Gosoniu et. al., (2008) showed that female suffering from tuberculosis did not get treatment at the appropriate time. There was a gender disparity in intra-household health care financing strategy among children (Behrman, 1988; Asfaw et. al., 2007, 2010). Asfaw (2007) showed that females have less probability to be hospitalized before their death. In India, very few study focused on gender disparity in Intra-household health care expenditure (HCE). This study 17

examines the gender disparity in average HCE and Intra-household HCE for inpatient care in India. Data source This study used 25 th scheduled for two rounds (60 th and 71st) of the National Sample Survey Organization (NSSO) data. The NSSO is a nationwide, large-scale population-based survey data and collected by MoSPI, Government of India (GOI). Since 1950, the NSSO has been collecting household-level data on socio-economic status of the study population, as well as health and morbidity status and health care consumption in India. The 60 th and 71 st round data were collected in 2004, and 2014 between January to Jnue adopted a two-stage stratified random design. In the 60 th round, the information was collected from 73868 households, and the sample size for male and female was 195,712 and 187,626. While in the 71st round, the information was collected from 65932 households and the sample sizes for male and female was 168,697 and 164,407. The information on health expenditure was collected separately for inpatients and outpatients. Details of ailments and hospitalization were collected in the reference period of last 365 days. HCE information collected at disaggregated level that includes total amount spent on medicines cost, doctor's fee, diagnostic tests charge, other medical expenses (blood, oxygen, attendant charges, personal medical appliances, physiotherapy, etc.), bed charges, transportation fee. For each individual of the households, the detail information about sex, age, morbidity status communicable and non-communicable disease, treatment status and hospitalization were recorded, and for each patient, the episode of ailments in last 356 days, treatment status, type of health care facility used, medical and non-medical HCE, sources of healthcare finance to overcome hospitalization cost and duration of hospitalization were collected using a questionnaire. This study used HCE of hospitalization (medical and nonmedical expense) for each hospitalized (inpatient care) person during the last 365 days before the survey. HCE used in this study is converted to constant prices by GDP deflator of 175 (2014) at base price index (2005=100). Methodology Measures 18

Outcome variable In the both round of the survey, data on HCE for hospitalization was collected separately for each episode of hospitalization. Along with medical expenditure, other expenditures recorded separately. Medical expenditure constituted by expenditure on medicine, bed charge for hospitalized treatment, charge for diagnostic test, doctor fee. The other expenditure includes all expenditures related to the treatment of an ailment incurred by the households, but expenditure regarding medical treatment is excluded. Other medical cost included all transport cost paid by the households connection with the treatment of patient, food and lodging expenditure of the escort(s) during last one year. The total expenditure constituted by sum of the medical expenditure and other expenditure. We have estimated gender disparity in average HCE (Inter- household) and Intra-household (with in household) HCE. Gender disparity in intra household HCE expenditure estimated only for 2014. The maternity cases are not included in this study since those are restricted to only one gender. To estimate per capita annual HCE, expenditure of all episodes for an individual has added in case of more than one episode of the same individual for the same disease. The explanation about the predictor variables is given in the detail. Predictor variables Age group: Age of the individuals has categorized into three groups: 0-14 years, 15-49 years and 50 and above 50 years. Education level: The educational status of an individual has coded into five categories: no education, up to the primary, up to secondary, up to higher secondary, Graduate and above. These groups had classified in such as way that they have a distinct effect on the health care spending. Religion: The religious categories have classified in Hindu-1, Muslim-2 and Others-3. Others religion constituted by Christianity, Sikhism, Jainism, Buddhism, Zoroastrianism, others. Social group: The social groups are recoded into three groups: Scheduled Caste (SC)/Schedule Tribe (ST), Other Backward Castes (OBCs) and General Castes. 19