The role of age inequalities in cause of death in the slow pace of epidemiological transition in India.

In developed countries, low disparity in lifespan contributed by the reduction in the burden of noncommunicable diseases (NCDs) is the key to advances in epidemiological transition. Contrarily, India passing through a phase of the dual burden of CDs and NCDs shows a heavy burden of NCDs responsible for the high disparity in lifespan. The Gini coefficient was decomposed for examining the contribution of 22 causes of death and their repercussions for inequality in age at death for 30 years between 1990-1994 and 2015-2019, using Global Burden of Disease data. The outcomes of the study reveal that India's epidemiological transition has been just modest on account of high inequality in mortality by NCDs emplaced in the middle through old age despite a consistent mortality decline at infant through old age for communicable diseases (CDs). The structural changes in causes of death structure is shaped by CDs rather than NCDs, but overall bolstered by the adult mortality decline, especially in women. However, the process is restrained by the small contribution of the middle age group and a benign contribution of old mortality decline owing to the low threshold age. India needs to target health interventions in seeking significant mortality decline in the middle age group of 50-69 years that is warranted for epidemiological transition apace as evident in the developed nations.

Multimorbidity matters in low and middle-income countries.

Multimorbidity is a complex challenge affecting individuals, families, caregivers, and health systems worldwide. The burden of multimorbidity is remarkable in low- and middle-income countries (LMICs) given the many existing challenges in these settings. Investigating multimorbidity in LMICs poses many challenges including the different conditions studied, and the restriction of data sources to relatively few countries, limiting comparability and representativeness. This has led to a paucity of evidence on multimorbidity prevalence and trends, disease clusters, and health outcomes, particularly longitudinal outcomes. In this paper, based on our experience of investigating multimorbidity in LMICs contexts, we discuss how the structure of the health system does not favor addressing multimorbidity, and how this is amplified by social and economic disparities and, more recently, by the COVID-19 pandemic. We argue that generating epidemiologic data around multimorbidity with similar methods and definition is essential to improve comparability, guide clinical decision-making and inform policies, research priorities, and local responses. We call for action on policy to refinance and prioritize primary care and integrated care as the center of multimorbidity.

Design and Methodology of the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia (LASI-DAD).

BACKGROUND/OBJECTIVES: To provide high-quality data on older adults in India that will enable an in-depth study of late-life cognition and dementia in India and cross-country analysis of risk factors for cognitive aging and dementia. DESIGN: The Longitudinal Aging Study in India (LASI) is a nationally representative survey of health, economic, and social well-being of the Indian population aged 45 and older. Its large sample of more than 70,000 older adults represents not only the country as a whole but also each state. LASI-Diagnostic Assessment of Dementia (DAD) is an in-depth study of late-life cognition and dementia, drawing a subsample of over 3,000 LASI respondents aged 60 and older. SETTING: Participants were interviewed at home or in a participating hospital according to their preferences. PARTICIPANTS: Adults aged 60 and older (N = 3,224), along with 3,191 informants. MEASUREMENTS: Respondents underwent a battery of cognitive tests, and informants were interviewed about their cognitive and health conditions. A common set of cognitive tests was selected to enable international comparisons, and additional cognitive tests suitable for illiterate and innumerate populations were also selected. Rich data on risk factors of dementia were collected through health examination, venous blood assays, and genotyping. RESULTS: The response rate was 82.9%, varying across sex, education, and urbanicity. Data are available to other researchers. CONCLUSION: LASI-DAD provides an opportunity to study late-life cognition and dementia and their risk factors in the older population in India and to gain further insights through cross-country analysis by pooling data from its international sister studies. J Am Geriatr Soc 68:S5-S10, 2020.

Pathways of economic inequalities in maternal and child health in urban India: a decomposition analysis.

BACKGROUND/OBJECTIVE: Children and women comprise vulnerable populations in terms of health and are gravely affected by the impact of economic inequalities through multi-dimensional channels. Urban areas are believed to have better socioeconomic and maternal and child health indicators than rural areas. This perception leads to the implementation of health policies ignorant of intra-urban health inequalities. Therefore, the objective of this study is to explain the pathways of economic inequalities in maternal and child health indicators among the urban population of India. METHODS: Using data from the third wave of the National Family Health Survey (NFHS, 2005-06), this study calculated relative contribution of socioeconomic factors to inequalities in key maternal and child health indicators such as antenatal check-ups (ANCs), institutional deliveries, proportion of children with complete immunization, proportion of underweight children, and Infant Mortality Rate (IMR). Along with regular CI estimates, this study applied widely used regression-based Inequality Decomposition model proposed by Wagstaff and colleagues. RESULTS: The CI estimates show considerable economic inequalities in women with less than 3 ANCs (CI = -0.3501), institutional delivery (CI = -0.3214), children without fully immunization (CI = -0.18340), underweight children (CI = -0.19420), and infant deaths (CI = -0.15596). Results of the decomposition model reveal that illiteracy among women and her partner, poor economic status, and mass media exposure are the critical factors contributing to economic inequalities in maternal and child health indicators. The residuals in all the decomposition models are very less; this implies that the above mentioned factors explained maximum inequalities in maternal and child health of urban population in India. CONCLUSION: Findings suggest that illiteracy among women and her partner, poor economic status, and mass media exposure are the critical pathways through which economic factors operate on inequalities in maternal and child health outcomes in urban India.