Abstract
Population ageing is commonly cited as one of the main drivers of increasing pressures on health care systems, as more people with chronic morbidities live to older ages. This chapter digs deeper into this presumed relationship by estimating the successive health impacts of: total population change, population ageing, changing ethnic mix of the population and trends in the age-specific incidence of disease. The decomposition of a set of health projections is developed using a micro-simulation model. These projections are based on the population of England aged 50 and over, classified by local authority of residence. The model projects forward, for the 20 years beyond 2011, the prevalence of cardiovascular disease, diabetes and respiratory illness. For diabetes the finding is that population increase alone contributes to a 24 % increase in prevalence by 2031, while the changes in gender, ethnicity and age composition together contribute another 24 %. Taking account of all potential contributions, the overall diabetes prevalence count increases by 57 %. For cardio-vascular disease (CVD), population increase contributes a 23 % increase; demographic composition processes a further 30 %; while decreases in CVD prevalence rates reduce prevalence by 60 %, resulting in an overall decrease of 35 % in those with CVD by 2031. For respiratory illness, population increase contributes 23 %; demographic composition changes 13 %; while a decrease in prevalence rates of 29 % means that the burden of the disease reduces by a modest 1 %. These results underline the potential for successful health intervention (as in CVD), the urgent need for prevention (as in diabetes) and the incentive to continue to care about health to very old ages (as in respiratory illness). These headline results refer to England as a whole but we also show how they vary across local authorities by area type, pointing to models of good practice in morbidity control.
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References
Bongaarts, J., & Bulatao, R. A. (1999). Completing the demographic transition. Population and Development Review, 25(3), 515–529.
Brailsford, S. C., Harper, P. R., Patel, B., & Pitt, M. (2009). An analysis of the academic literature on simulation and modelling in health care. Journal of Simulation, 3, 130–140.
Clark, S. D. (2015). Modelling the impacts of demographic ageing on the demand for health care services. PhD dissertation, School of Geography, University of Leeds. http://etheses.whiterose.ac.uk/11676/
Harland, K. (2013). Microsimulation model user guide: Flexible modelling framework. National Centre for Research Methods Working Paper 06/13. http://eprints.ncrm.ac.uk/3177/2/microsimulation_model.pdf
He, W., Goodkind, D., & Kowal, P. (2016). An ageing world. International Population Reports. United States Census Bureau. http://www.census.gov/content/dam/Census/library/publications/2016/demo/p95-16-1.pdf
Health and Social Care Information Centre. (2005a). Health survey for England 2004: The health of minority Ethnic Groups – Headline tables. http://www.ic.nhs.uk/webfiles/publications/hlthsvyeng2004ethnic/HealthSurveyForEngland161205_PDF%20.pdf
Health and Social Care Information Centre. (2005b). The health of minority Ethnic Groups, Vol. 1, K Sproston & J. Mindell. http://www.ic.nhs.uk/pubs/hse04ethnic
House of Lords. (2013). Ready for ageing? House of Lords Select Committee Report. http://www.parliament.uk/business/committees/committees-a-z/lords-select/public-services-committee/report-ready-for-ageing/
Institute of Public Care. (2011). Poppi user guide. Projecting Older People Population Information. http://www.poppi.org.uk/POPPI%20User%20Guide.pdf
Law, M. R., Wald, N. J., & Rudnicka, A. R. (2003). Quantifying effect of statins on low density lipoprotein cholesterol, ischaemic heart disease, and stroke: Systematic review and meta-analysis. British Medical Journal, 326, 1423–1429.
Marmot, M. (2015). The health gap: The challenge of unequal world. London: Bloomsbury.
Mason, T., Sutton, M., Whittaker, W., & Birch, S. (2015). Exploring the limitations of age-based models for health care planning. Social Science and Medicine, 132, 11–19.
McCulloch, A. (2011). Health service funding. http://www.significancemagazine.org/details/webexclusive/1385441/Health-Service-funding.html
McCulloch, A. (2012a). Standardising death. http://www.significancemagazine.org/details/webexclusive/1501135/Standardising-Death.html
McCulloch, A. (2012b). Population ageing and mortality. http://www.significancemagazine.org/details/webexclusive/1664457/Population-ageing-and-mortality.html
Mooney, C. Z. (1997). Monte Carlo simulation. Quantitative applications in the social sciences. Sage University Paper, Number 07–116.
National Center for Health Statistics. (2016). Health, United States, 2015, with special feature on racial and ethnic health disparities. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, NCHS, Hyattsville MD. http://www.cdc.gov/nchs/data/hus/hus15.pdf
Office for National Statistics. (2003). National statistics 2001 area classification. Office for National Statistics. http://www.ons.gov.uk/ons/guide-method/geography/products/area-classifications/ns-area-classifications/index/index.html
Office for National Statistics. (2010). Final recommended questions for the 2011 census in England and Wales on Health. Office for National Statistics. http://www.ons.gov.uk/ons/guide-method/census/2011/the-2011-census/2011-census-questionnaire-content/question-and-content-recommendations/final-recommended-questions-2011---health.pdf.
Office for National Statistics. (2013). National population projections, 2012-based extra variants report. Office for National Statistics. http://www.ons.gov.uk/ons/dcp171776_338113.pdf
Office for National Statistics. (2014a). Health expectancies at birth and at age 65 in the United Kingdom, 2009–2011. Office for National Statistics. http://www.ons.gov.uk/ons/rel/disability-and-health-measurement/health-expectancies-at-birth-and-age-65-in-the-united-kingdom/2009-11/index.html
Office for National Statistics. (2014b). Methodology: 2012-based sub national population projection. Office for National Statistics. http://www.ons.gov.uk/ons/rel/snpp/sub-national-population-projections/2012-based-projections/rpt-snpp-2012-based-methodology-report.html
Office for National Statistics. (2014c). Microdata. Office for National Statistics. http://www.ons.gov.uk/ons/guide-method/census/2011/census-data/2011-census-prospectus/release-plans-for-2011-census-statistics/subsequent-releases-of-specialist-products/microdata/index.html
Office for National Statistics. (2015). Methodology note for the 2011 area classification for local authorities. Office for National Statistics. http://www.ons.gov.uk/ons/guide-method/geography/products/area-classifications/ns-area-classifications/ns-2011-area-classifications/methodology-and-variables/methodology.pdf
Public Health England. (2016). Recent trends in life expectancy at older ages: Update to 2014. https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/499252/Recent_trends_in_life_expectancy_at_older_ages_2014_update.pdf
Rees, P., & Clark, S. (2014). The projection of Ethnic Group populations aged 18 and over for Westminster parliamentary constituencies in Great Britain for election years 2015, 2020, 2025, 2030 and 2035. London: A Report to the Policy Exchange.
Rees, P., Zuo, C., Wohland, P., Jagger, C., Norman, P., Boden, P., & Jasinska, M. (2013a). The implications of ageing and migration for the future population, health, labour force and households of Northern England. Applied Spatial Analysis and Policy, 6(2), 93–122.
Rees, P., Wohland, P., & Norman, P. (2013b). The demographic drivers of future ethnic group populations for UK local Areas 2001–2051. The Geographical Journal, 179(1), 44–60.
Sanderson, W. C., & Scherbov, S. (2010). Remeasuring aging. Science, 329, 1287–1288.
Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis. Oxford: Oxford University Press.
University of Leeds. (2016). ETHPOP database. http://www.ethpop.org/
Van Imhoff, E., & Post, W. (1998). Microsimulation methods for population projection. Population-E, 10(1), 97–136.
Zweifel, P., Felder, S., & Meiers, M. (1999). Ageing of population and health care expenditure: A red herring? Health Economics, 8, 485–496.
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Clark, S.D., Rees, P.H. (2017). The Drivers of Health Trends: A Decomposition of Projected Health for Local Areas in England. In: Swanson, D. (eds) The Frontiers of Applied Demography. Applied Demography Series, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-319-43329-5_2
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