Socio-economic variations of breast cancer treatment and discontinuation: a study from a public tertiary cancer hospital in Mumbai, India.

BACKGROUND: The study examined the socio-economic variation of breast cancer treatment and treatment discontinuation due to deaths and financial crisis. METHODS: We used primary data of 500 patients with breast cancer sought treatment at India's one of the largest cancer hospital in Mumbai, between June 2019 and March 2022. This study is registered on the Clinical Trial Registry of India (CTRI/2019/07/020142). Kaplan-Meier method and Cox-hazard regression model were used to calculate the probability of treatment discontinuation. RESULTS: Of the 500 patients, three-fifths were under 50 years, with the median age being 46 years. More than half of the patients were from outside of the state and had travelled an average distance of 1,044 kms to get treatment. The majority of the patients were poor with an average household income of INR15,551. A total of 71 (14%) patients out of 500 had discontinued their treatment. About 5.2% of the patients died and 4.8% of them discontinued treatment due to financial crisis. Over one-fourth of all deaths were reported among stage IV patients (25%). Patients who did not have any health insurance, never attended school, cancer stage IV had a higher percentage of treatment discontinuation due to financial crisis. Hazard of discontinuation was lower for patients with secondary (HR:0.48; 95% CI: 0.27-0.84) and higher secondary education (HR: 0.42; 95% CI: 0.19-0.92), patients from rural area (HR: 0.79; 95% CI: 0.42-1.50), treated under general or non-chargeable category (HR: 0.60; 95% CI:0.22-1.60) while it was higher for the stage IV patients (HR: 3.61; 95% CI: 1.58-8.29). CONCLUSION: Integrating breast cancer screening in maternal and child health programme can reduce delay in diagnosis and premature mortality. Provisioning of free treatment for poor patients may reduce discontinuation of treatment.

Socio-economic and regional variation in breast and cervical cancer screening among Indian women of reproductive age: a study from National Family Health Survey, 2019-21.

BACKGROUND: In India, breast and cervical cancers account for two-fifths of all cancers and are predominantly prevalent among women in the reproductive age group. The Government of India recommended screening of breast and cervical cancer among women aged 30 years and over. This study examines the socio-economic and regional variations of breast and cervical screening among Indian women in the reproductive age. METHODS: A full sample of 707,119 women aged 15-49 and a sub-sample of 357,353 women aged 30-49 from National Family Health Survey-5 (2019-21) were used in the analysis. Self-reported ever screening for breast and cervical cancer for women aged 15-49 and women aged 30-49 were outcome variables. A set of socio-economic and risk factors associated with breast and cervical cancer screening were used as the predictors. Logistic regression was used to understand the significant correlates of cancer screening and, concentration index and concentration curve were used to assess the socio-economic inequality in breast and cervical cancer screening. RESULTS: The proportion of breast and cervical cancer screening among women aged 30-49 were 877 and 1965 per 100,000 women respectively. Cancer screening was lower among women who were poor, young, had lower educational attainment and resided in rural areas. The concentration index was 0.2 for ever screening of breast cancer and 0.15 for cervical cancer among women aged 30-49 years. The concertation curve for screening of both breast and cervical cancers was pro-rich. Women with higher educational attainment [OR:1.46, 95% CI: 1.31-1.62], aged 40-49 years [OR:1.35; 95% CI: 1.28-1.43], resided in the western [OR:1.62; 95% CI:1.4-1.87] or southern [OR:6.66; 95% CI:5.93-7.49] region had significantly higher odds of up taking either of the screening. The pattern of breast and cervical cancer screening among women aged 15-49 was similar to that of women 30-49. CONCLUSION: The overall proportion of cancer screening among women in 30-49 age group is low in India. Early screening and treatment can reduce the burden of these cancers. Creating awareness and providing knowledge on cancer could be a key strategy for reducing the burden of breast and cervical cancers among women in the reproductive age in India.

Multilevel population and socioeconomic variation in health insurance coverage in India.

OBJECTIVES: This study explores population-level variation in different types of health insurance coverage in India. We aimed to estimate the extent to which contextual factors at community, district, and state levels may contribute to place-based inequalities in coverage after accounting for household-level socioeconomic factors. METHODS: We used data from the 2015-2016 National Family Health Survey in India, which provides the most recent and comprehensive information available on reports of different types of household health insurance coverage. We used multilevel regression models to estimate the relative contribution of different population levels to variation in coverage by national, state, and private health insurance schemes. RESULTS: Among 601,509 households in India, 29% reported having coverage in 2015-2016. Variation in each type of coverage existed between population levels before and after adjusting for differences in the distribution of household socioeconomic and demographic factors. For example, the state level accounted for 36% of variation in national scheme coverage and 41% of variation in state scheme coverage after adjusting for household characteristics. In contrast, the community level was the largest contextual source of variation in private insurance coverage (accounting for 24%). Each type of coverage was associated with higher socioeconomic status and urban location. CONCLUSIONS: Contextual factors at community, district, and state levels contribute to variation in household health insurance coverage even after accounting for socioeconomic and demographic factors. Opportunities exist to reduce disparities in coverage by focusing on drivers of place-based differences at multiple population levels. Future research should assess whether new insurance schemes exacerbate or reduce place-based disparities in coverage.

Geographic Variation in Household and Catastrophic Health Spending in India: Assessing the Relative Importance of Villages, Districts, and States, 2011-2012.

Policy Points: Per-capita household health spending was higher in economically developed states and was associated with ability to pay, but catastrophic health spending (CHS) was equally high in both poorer and more developed states in India. Based on multilevel modeling, we found that the largest geographic variation in health spending and CHS was at the state and village levels, reflecting wide inequality in the accessibility to and cost of health care at these levels. Contextual factors at macro and micro political units are important to reduce health spending and CHS in India. CONTEXT: In India, health care is a local good, and households are the major source of financing it. Earlier studies have examined diverse determinants of health care spending, but no attempt has been made to understand the geographical variation in household and catastrophic health spending. We used multilevel modeling to assess the relative importance of villages, districts, and states to health spending in India. METHODS: We used data on the health expenditures of 101,576 households collected in the consumption expenditure schedule (68th round) carried out by the National Sample Survey in 2011-2012. We examined 4 dependent variables: per-capita health spending (PHS), per-capita institutional health spending (PIHS), per-capita noninstitutional health spending (PNHS), and catastrophic health spending (CHS). CHS was defined as household health spending exceeding 40% of its capacity to pay. We used multilevel linear regression and logistic models to decompose the variation in each outcome by state, region, district, village, and household levels. FINDINGS: The average PHS was 1,331 Indian rupees (INR), which varied by state-level economic development. About one-fourth of Indian households incurred CHS, which was equally high in both the economically developed and poorer states. After controlling for household level factors, 77.1% of the total variation in PHS was attributable to households, 10.1% to states, 9.5% to villages, 2.6% to districts, and 0.7% to regions. The pattern in variance partitioning was similar for PNHS. The largest interstate variation was found for CHS (15.9%), while the opposite was true for PIHS (3.2%). CONCLUSIONS: We observed substantial variations in household health spending at the state and village levels compared with India's districts and regions. The large variation in CHS attributable to states indicates interstate inequality in the accessibility to and cost of health care. Our findings suggest that contextual factors at the macro and micro political units are important to reduce India's household health spending and CHS.

Contributing factors for reduction in maternal mortality ratio in India.

Maternal mortality ratio (MMR) estimates have been studied over time for understanding its variation across the country. However, it is never sufficient without accounting for presence of variability across in terms of space, time, maternal and system level factors. The study endeavours to estimate and quantify the effect of exposures encompassing all maternal health indicators and system level indicators along with space-time effects influencing MMR in India. Using the most recent level of possible -factors of MMR, maternal health indicators from the National Family Health Survey (NFHS: 2019-21) and system level indicators from government reports a heatmap compared the relative performance of all 19 SRS states. Facet plots with a regression line was utilised for studying patterns of MMR for different states in one frame. Using Bayesian Spatio-temporal random effects, evidence for different MMR patterns and quantification of spatial risks among individual states was produced using estimates of MMR from SRS reports (2014-2020). India has witnessed a decline in MMR, and for the majority of the states, this drop is linear. Few states exhibit cyclical trend such as increasing trends for Haryana and West Bengal which was evident from the two analytical models i.e., facet plots and Bayesian spatio- temporal model. Period of major transition in MMR levels which was common to all states is identified as 2009-2013. Bihar and Assam have estimated posterior probabilities for spatial risk that are relatively greater than other SRS states and are classified as hot spots. More than the individual level factors, health system factors account for a greater reduction in MMR. For more robust findings district level reliable estimates are required. As evident from our study the two most strong health system influencers for reducing MMR in India are Institutional delivery and Skilled birth attendance.

Health-Related Quality of Life (HRQoL) Using EQ-5D-5L: Value Set Derived for Indian Breast Cancer Cohort.

OBJECTIVE: The purpose of this study was to report quality of life of newly diagnosed breast cancer patients from India in a large cohort using the EQ-5D-5L instrument. METHODS: The study used longitudinal data of 500 breast cancer and 200 non-cancer subjects registered at our centre, during June 2019 and March 2022. The EQ-5D-5L and EQ-VAS instruments were used to measure and compare utility scores among cancer and non-cancer subjects. Descriptive statistics were analyzed and Tobit regression model were used to confirm the predictors of the utility score. RESULTS: The cancer subjects had a mean EQ-ED-5L utility score of 0.8703 (SD=0.121), 0.8745 (SD=0.094) and 0.8902 (SD=0.107) at the time of baseline, completion and follow up surveys respectively.  EQ-5D-5L values had significantly worsened after diagnosis of cancer as compared to the non-cancer cohort (0.87 vs. 0.93, p value 0.000). EQ-5D-5L utility scores as per stage for the cancer cohort were 0.88, 0.86 and 0.83 respectively for stage I-II, III and IV. Similarly, the EQ-VAS scores for stage I-II, III and IV were 74.9, 72.6 and 73.2 respectively. Multivariate analysis confirmed strong association of age, religion and income with the utility-values. CONCLUSION: This is the first longitudinal study reporting the utility scores derived from a large cohort of breast cancer patients demonstrating lower utility scores compared to non-cancer cohort. The utility scores also improve post treatment completion for cancer patients and decrease with higher stage at diagnosis. This information will be useful for future health economic research in India pertaining to breast cancer.

Unintended effects of Janani Suraksha Yojana on maternal care in India.

BACKGROUND: The Janani Suraksha Yojana (JSY) is the largest ever conditional cash transfer programme worldwide. It primarily aimed to reduce the maternal and child mortality by increasing the facility based delivery in India. Besides, the JSY has resulted in reduction of out-of-pocket expenditure for delivery care and increased antenatal care. Though studies have examined the direct outcome of JSY, limited studies have attempted to understand the unintended effects (indirect) of the programme. The aim of this study is to examine the effect of JSY on contraceptive use, initiation of breast feeding and postnatal check-up in India. DATA & METHODS: Data from the National Family Health Survey 4, 2015-16 was used in the analyses. A total of 148,746 institutional births in five years preceding the survey were analysed and the analyses were carried out for Low Performing States (LPS) and High Performing States (HPS). Descriptive statistics and the propensity score matching were used to understand the unintended effects of JSY. RESULTS: In India, the use of contraception, early initiation of breastfeeding and postnatal check up was consistently higher among JSY beneficiaries compared to non-JSY beneficiaries. Among JSY beneficiaries, about 45% of the mothers breastfed their child within one hour compared to 42% of the JSY non-beneficiaries. The pattern was almost similar for postnatal check-up. The variations in contraceptive use, breastfeeding practice and postnatal check-up among JSY beneficiaries were higher in LPS states compared to HPS. For instance, in LPS, among JSY beneficiaries, about 58% mothers breastfed their child within one hour of delivery compared to 46% in HPS. Controlling for socio-economic covariates, the JSY beneficiaries in LPS were 12% more likely to use contraception, 8% were more likely to initiate the breast feeding within one hour of child delivery and 6% were more likely to get their postnatal check-up than their counterparts in HPS. DISCUSSION: The unintended effects of JSY were strong and significant in the low performing states. The coverage of JSY should be further extended and the programme needs to be continued.

Out-of-pocket expenditure and correlates of caesarean births in public and private health centres in India.

Increasing caesarean births is a global trend and of recent origin in India. Besides its utility and disutility, increasing caesarean births exert higher economic burden on households and the nation. Using 148,746 births from the National Family Health Survey, 2015-16, this paper examines the correlates and provides comparable estimates of out of pocket expenditure (OOPE) on caesarean births in public and private health centres in India. The monthly state specific rural-urban consumer price index and the OOPE on births over seven years are used to derive comparable OOPE estimate at 2016 prices. A composite variable combining type of birth and place of delivery is computed and classified as private and caesarean, public and caesarean, private and non-caesarean, public and non-caesarean. Descriptive statistics, logistic and tobit regression model were used to understand the differentials and determinants of OOPE on caesarean births. Caesarean births were significantly higher among mothers belonging to higher socioeconomic status, first order births, mothers with high BMI, pregnancy complications, repeat caesarean and in private health centres confirming that both maternal demand and institutional factors are leading to the increasing in caesarean rates in India. The mean OOPE of caesarean births in public health centres of poorer states was higher than that in the richer states of India (US$107 in low performing states compared to US$88 in high performing states) while such differentials across private health centres are small. The marginal effect of a caesarean birth in private health centres in low performing states was US$296 dollar higher than that of non-caesarean births. Improving the public health centres for conducting caesarean births, developing standard guideline for clinical practices in conducting caesarean births and creating awareness on comprehensive pregnancy care can reduce the caesarean rates and OOPE on caesarean birth in India.

Variation in Chronic Diseases Across Households, Communities, Districts, and States in India.

INTRODUCTION: Globally, chronic noncommunicable diseases are the leading cause of death and accounted for 6 million deaths in India in 2016. However, the extent to which variation in chronic disease can be attributed to different population levels in India is unknown, as is whether variation in individual-level factors explains outcome variation at different population levels. METHODS: Cross-sectional data from the District Level Household and Facility Survey 2012-2013 conducted across 21 states, 275 districts, 14,235 villages, 378,487 households, and 1,098,940 individuals aged ≥18 years in India were analyzed in 2018‒2019. Multilevel logistic models were used to partition variation in outcomes and attribute it to individual, household, village, district and state population levels. Outcomes included experiencing respiratory, cardiovascular, musculoskeletal, or eye symptoms; reporting a positive diagnosis by a doctor for chronic heart disease, hypertension, diabetes, or vision problems; and objectively assessed real-time measures of hypertension and diabetes. RESULTS: For reported diagnosis of hypertension or diabetes, a much larger percentage of variation in these outcomes was attributed to differences among households as compared to differences among units within other population levels. However, for objectively measured hypertension and diabetes, variation in these outcomes was important at the village level, followed by variation at the household level. Wealth status was positively associated with respiratory and cardiovascular symptoms, as well as all reported diagnoses and real-time measurements except for vision problems. Inclusion of individual-level sociodemographic variables explained 0%-30% of variation attributed to the household level for most chronic disease symptoms and diagnoses, but almost none at the higher levels. CONCLUSIONS: These findings imply that household- and village-level factors explain substantial variation in the prevalence of chronic disease symptoms and reported diagnoses in India.