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      Family transfers and long-term care: An analysis of the WHO Study on global AGEing and adult health (SAGE)

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          Abstract

          Background

          Populations globally are ageing, resulting in increased need for long-term care. Where social welfare systems are insufficient, these costs may fall to other family members. We set out to estimate the association between long-term care needs and family transfers in selected low- and middle- income countries.

          Methods

          We used data from the World Health Organization’s Study on global AGEing and adult health (SAGE). Using regression, we analysed the relationship between long-term care needs in older households and i) odds of receiving net positive transfers from family outside the household and ii) the amount of transfer received, controlling for relevant socio-demographic characteristics.

          Results

          The proportion of household members requiring long-term care was significantly associated with receiving net positive transfers in China (OR: 1.76; p = 0.023), Ghana (OR: 2.79; p = 0.073), Russia (OR: 3.50; p < 0.001). There was a statistically significant association with amount of transfer received only in Mexico (B: 541.62; p = 0.010).

          Conclusion

          In selected LMICs, receiving family transfers is common among older households, and associated with requiring long-term care. Further research is needed to better understand drivers of observed associations and identify ways in which financial protection of older adults’ long-term care needs can be improved.

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          Most cited references32

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          Multimorbidity in older adults.

          M Salive (2013)
          Multimorbidity, the coexistence of 2 or more chronic conditions, has become prevalent among older adults as mortality rates have declined and the population has aged. We examined population-based administrative claims data indicating specific health service delivery to nearly 31 million Medicare fee-for-service beneficiaries for 15 prevalent chronic conditions. A total of 67% had multimorbidity, which increased with age, from 50% for persons under age 65 years to 62% for those aged 65-74 years and 81.5% for those aged ≥85 years. A systematic review identified 16 other prevalence studies conducted in community samples that included older adults, with median prevalence of 63% and a mode of 67%. Prevalence differences between studies are probably due to methodological biases; no studies were comparable. Key methodological issues arise from elements of the case definition, including type and number of chronic conditions included, ascertainment methods, and source population. Standardized methods for measuring multimorbidity are needed to enable public health surveillance and prevention. Multimorbidity is associated with elevated risk of death, disability, poor functional status, poor quality of life, and adverse drug events. Additional research is needed to develop an understanding of causal pathways and to further develop and test potential clinical and population interventions targeting multimorbidity. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2013.
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            Coping with health-care costs: implications for the measurement of catastrophic expenditures and poverty.

            Owen O'Donnell, J Krishnakumar, Eddy van Roon … (2008)
            In the absence of formal health insurance, we argue that the strategies households adopt to finance health care have important implications for the measurement and interpretation of how health payments impact on consumption and poverty. Given data on source of finance, we propose to (a) approximate the relative impact of health payments on current consumption with a 'coping'-adjusted health expenditure ratio, (b) uncover poverty that is 'hidden' because total household expenditure is inflated by financial coping strategies and (c) identify poverty that is 'transient' because necessary consumption is temporarily sacrificed to pay for health care. Measures that ignore coping strategies not only overstate the risk to current consumption and exaggerate the scale of catastrophic payments but also overlook the long-run burden of health payments. Nationally representative data from India reveal that coping strategies finance as much as three-quarters of the cost of inpatient care. Payments for inpatient care exceed 10% of total household expenditure for around 30% of hospitalized households but less than 4% sacrifice more than 10% of current consumption to accommodate this spending.Ignoring health payments leads to underestimate poverty by 7-8% points among hospitalized households; 80% of this adjustment is hidden poverty due to coping.
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              Economic impacts of health shocks on households in low and middle income countries: a review of the literature

              Khurshid Alam, Ajay Mahal (2014)
              Poor health is a source of impoverishment among households in low -and middle- income countries (LMICs) and a subject of voluminous literature in recent years. This paper reviews recent empirical literature on measuring the economic impacts of health shocks on households. Key inclusion criteria were studies that explored household level economic outcomes (burden of out-of-pocket (OOP) health spending, labour supply responses and non-medical consumption) of health shocks and sought to correct for the likely endogeneity of health shocks, in addition to studies that measured catastrophic and impoverishment effects of ill health. The review only considered literature in the English language and excluded studies published before 2000 since these have been included in previous reviews. We identified 105 relevant articles, reports, and books. Our review confirmed the major conclusion of earlier reviews based on the pre-2000 literature - that households in LMICs bear a high but variable burden of OOP health expenditure. Households use a range of sources such as income, savings, borrowing, using loans or mortgages, and selling assets and livestock to meet OOP health spending. Health shocks also cause significant reductions in labour supply among households in LMICs, and households (particularly low-income ones) are unable to fully smooth income losses from moderate and severe health shocks. Available evidence rejects the hypothesis of full consumption insurance in the face of major health shocks. Our review suggests additional research on measuring and harmonizing indicators of health shocks and economic outcomes, measuring economic implications of non-communicable diseases for households and analyses based on longitudinal data. Policymakers need to include non-health system interventions, including access to credit and disability insurance in addition to support formal insurance programs to ameliorate the economic impacts of health shocks.
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                Author and article information

                Contributors
                Adrianna Murphy
                Journal
                Journal ID (nlm-ta): J Econ Ageing
                Journal ID (iso-abbrev): J Econ Ageing
                Title: Journal of the Economics of Ageing
                Publisher: Elsevier B.V
                ISSN (Print): 2212-828X
                ISSN (Electronic): 2212-8298
                Publication date PMC-release: 1 November 2018
                Publication date (Print): November 2018
                Volume: 12
                Pages: 195-201
                Affiliations
                [a ]London School of Hygiene and Tropical Medicine, UK
                [b ]World Health Organization, United States
                [c ]University of Newcastle, Australia
                [d ]University of Bologna, Italy
                [e ]European Observatory on Health Systems and Policies, UK
                Author notes
                [* ]Corresponding author. adrianna.murphy@ 123456lshtm.ac.uk
                Article
                Publisher ID: S2212-828X(16)30067-6
                DOI: 10.1016/j.jeoa.2017.08.003
                PMC ID: 6282503
                SO-VID: 4f0ba4d4-d575-46b1-8493-bc3e82499eac
                Copyright © © 2017 The Authors
                License:

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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