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Mar 2, 20217 min read

Changing the Way We Fight Chronic Illness - LifeCourse Model

Updated: Mar 3, 2021

Multi-Level Model of Health: The Life Course Framework


Multi-level models of health describe the various influences on health and the complex interaction between them. The figure below (Galea 2015) represents these influences in an upstream/downstream arrangement. The life course framework emphasizes the temporal, cumulative effects of experiences on health outcomes and disease patterns across an individual’s lifetime, or across generations – the biological, behavioral, and psychosocial processes that exist across the lifespan (WHO 2000). This model best describes where the root cause of health problems can be found and where sustainable improvement can (and should) be taken. Notice that the top three “upstream” influences (thus modifiable influences with the most reach) are our neighborhoods/communities, institutions, and socioeconomic policies.



This framework is explained by HelpAge International’s (n.d.) video below. The “Leave No One Behind” initiative states that we are born and live through varied events, we make choices, and face the consequences of policies and government systems, discrimination, and other influences that accumulate over time. Consistent with the figure above, the initiative proposes policy development that looks forward at impacts in our older age and looks back and responds to older people's diverse past experiences (HelpAge International n.d.).





Chronic Illness and Frailty


The most common and costly health issue facing Canadians is chronic disease – Diabetes, Coronary Heart Disease (CHD), Chronic Obstructive Pulmonary Disease (COPD), cognitive and physical decline, and generalized frailty – they are also among the most preventable, non-communicable diseases and are characterized as having multiple risk factors, long latency, prolonged affliction, and are associated with impairments/functional disability (PHAC 2020). The symptoms of chronic illness accumulate and contribute to increasing frailty. This results in: frequent hospitalizations, loss of independence, home care, long-term institutionalization, unpaid family caregiving, and more. A common goal among acute care hospitals to address chronic illness burden is admission reduction. Unplanned hospital (re)admission has negative impacts on the lives of patients, compromises the efficiency of hospitals/care providers and growing rates of chronic, complex conditions are bringing discharged patients back into acute care at higher rates (AE Tonix n.d.). Connecting patients with resources to manage their chronic illness is certainly prudent, but alone it fails to explore and address the root cause of chronic illness, frailty and the health system use we are seeing amongst subgroups. As the life course framework tells us, individual modifiable risk factors for chronic illness and use of the health system goes beyond managing symptoms. If we look upstream, the influences on chronic illness, frailty, and health system use are the community the individual lives in, institutions (resources) available, and socioeconomic status. This blog will focus on these three influences on chronic illness and frailty progression.


Neighborhood/Community


Neighborhood contextual influences on health are difficult to effectively study due to the inability to control the confounding variable of socioeconomic status (SES) and economic segregation as they occur naturally: rich people rarely live in poor neighborhoods and vice versa (Kawachi, Subramanian 2018). Despite methodological challenges, there is considerable evidence that social integration and support are beneficial to health: social and instrumental supports influence adherence to medical treatment, help-seeking behavior, and utilization of health services (Von Dem Knesebeck 2015). Chaix (2009) conducted a literature review that focused on the influence of neighborhood identities and social interactions on psycho-cognitive antecedents of behaviors and health outcomes and found that, while controlling for SES, socially-deprived area residents report an increased risk for CHD. This means that social interactions may contribute to the SES disparities we see in CHD occurrence and risk. Broader societal factors like capitalism, racism, and patriarchy are where health disparities take root and can grow (Lincoln 2018). The influence of neighborhood environment on health spans the life course: lower-income children have longer life expectancies if they live in highly educated, high income communities with high levels of government expenditures telling us that a child’s neighborhood is more important for the child’s economic future than is the economic status of the child’s family (Orentlicher 2018). Older individuals that may have adequate SES (i.e., income through government benefits or family support) but live in neighborhoods with violence and crime and/or have smaller sizes of close networks, are more reluctant to leave their homes and thus engage in less physical, cognitively-stimulating activity leading to cognitive decline through depressive symptoms and lethargy (Settels, Leist 2021). Investing in the overall community environment is a protective strategy that can safeguard against the causes of poor health and chronic illness, moreover it benefits all individuals in the neighborhood.


Institutions


Institutions can support communities and offset the effects of inequality unfortunately, disadvantaged communities tend to also face declines in institutions/informal social networks that have been shown to improve healthy behaviors (Settels, Leist 2021). Underlying social factors described above not only influence health directly but also impact access and utilization of social programs, including health care. Providing medical care is necessary, but interestingly, the availability of a health system tends to vary inversely with the need for it in the population served (Von Dem Knesebeck 2015). A natural experiment took place in Oregon when a lottery system granted Medicaid benefits to applicants. The lottery winners received more health care than their uninsured counterparts, at less financial burden, yet still suffered the same rate of hypertension, high cholesterol, and diabetes (Orentlicher 2018). If hospital admission can be used as an indicator for health system utilization, effective programs to reduce (re)admissions (such as INSPIRE) show that patient education and community/home care are halfway successful (Ae Tonix n.d.). This shows us that to decrease hospitalization, policy implemented farther upstream, targeting root causes of exacerbation is effective but the health system only has so much reach. It can only treat the symptoms of chronic illness once it has developed and progressed. If we look further upstream, at non-health system institutions, it is widely known that education and income are lower in older individuals placing them at risk of chronic health issues/frailty and health system utilization yet the availability of libraries in a community can delay cognitive decline (Lee, Chon, Kim, Ki, Yun 2020) (Settels, Leist 2021). Societal institutions can compensate for individual and community level health risks – providing institutional supports (education, unions, extended health insurance, pharmacare, mental health care, recreation, etc.) to the right populations at the right time in the life course would have significant downstream effects on chronic illness and age-related health burdens.


Socioeconomic Policy: Poverty Reduction


The furthest upstream determinant of health – SES policy permeates each health influence across the lifespan. Lincoln (2018) describes aging as a process that reflects our life chances from birth onward: barriers, opportunities, wages, workplace benefits, households, labor force participation, race, gender all converge and accumulate leading to poverty and inequality later in life. Those living in low SES areas have poorer nutritional intake and engage in more unhealthy behaviours (smoking) (CIHI 2008). The graph below (left) taken from Disano et al. (2010) beside the graphic (below right) taken from the Canadian Institute of Health Information (CIHI 2019) captures an unchanging pattern in COPD burden in terms of preventable and overall hospitalizations, and how the health gap according to SES is widening over time.






Each facet of chronic illness and age-related frailty can be traced back to SES. When effective institutions and social supports are lacking, acute care hospitals become overwhelmed with vulnerable individuals. It is short-sighted to look at the cost of chronic illness on hospital budgets as we continue to see that attempts to reduce hospital readmissions are largely unsuccessful (Gershon et al. 2019). Widespread income security improves individual and community health as demonstrated in the examples provided by Orentlicher (2018), describing poverty as the real public health crisis:


  • A study of 24 OECD countries showed that increasing the minimum wage is associated with decreased mortality rates and smoking behaviors

  • A 4-year minimum income experiment in rural Manitoba demonstrated benefit to the collective community (despite only one third receiving payments), hospitalizations decreased, and health status significantly improved

  • Poor elderly persons in Mexico experienced improvements in health measures comparable to their counterparts 5-10 years younger when given a $67 pension. As we saw in Analyn’s story, a pension can significantly alleviate old-age poverty (HelpAge International n.d.).


Contrary to the life course model, the following PSA (CFN n.d.) describes frailty and individual influences that improve outcomes:



After examining chronic illness/frailty under the life course model of health, it is undeniable that individual behavioral modification and (re)admission reduction is inadequate public health policy. It ignores the social influences on individual choices and behaviors. Social conditions like race, ethnicity, gender, SES, and neighborhood enrichment all interact and effect an individual’s ability to participate in the work force, achieve income security, engage in healthy behaviors, and plan for old age (Lincoln, 2018). Providing income assistance, building institutions and programs conducive to social engagement, and establishing community infrastructure would significantly improve the burden of chronic illness and frailty in Canada (Lee et al. 2020).





AE Tonix. (n.d.). Provinces with Lower Hospital Readmissions: What Can They Teach Us? Retrieved February 18, 2021, from https://aetonix.com/chronic-disease-management/provinces-with-lower-hospital-readmissions-what-can-they-teach-us/



Chaix, B. (2009). Geographic life environments and coronary heart disease: A literature review, theoretical contributions, methodological updates, and a research agenda. In Annual Review of Public Health (Vol. 30, pp. 81–105). Annu Rev Public Health. https://doi.org/10.1146/annurev.publhealth.031308.10015



(CIHI) Canadian Institute for Health Information. (2019). Hospitalization rates for COPD across Canadian cities | CIHI. https://www.cihi.ca/en/hospitalization-rates-for-copd-across-canadian-cities



Galea, S. (2015). The Determination of Health Across the Life Course and Across Levels of Influence | SPH. Boston University School of Public Health. https://www.bu.edu/sph/news/articles/2015/the-determination-of-health-across-the-life-course-and-across-levels-of-influence-2/


Gershon, A. S., Thiruchelvam, D., Aaron, S., Stanbrook, M., Vozoris, N., Tan, W. C., Cho, E., & To, T. (2019). Socioeconomic status (SES) and 30-day hospital readmissions for chronic obstructive pulmonary (COPD) disease: A population-based cohort study. PLOS ONE, 14(5), e0216741. https://doi.org/10.1371/journal.pone.0216741


Help Age International. (n.d.). Lifecourse approach to ageing | What we do | HelpAge International. Retrieved February 18, 2021, from https://www.helpage.org/what-we-do/life-course-approach-to-ageing/#.YC21qo2dPRg.twitter


Kawachi, I., & Subramanian, S. V. (2018). Social epidemiology for the 21st century. Social Science and Medicine, 196, 240–245. https://doi.org/10.1016/j.socscimed.2017.10.034


Lee, Y., Chon, D., Kim, J., Ki, S., & Yun, J. (2020). The Predictive Value of Social Frailty on Adverse Outcomes in Older Adults Living in the Community. Journal of the American Medical Directors Association, 21(10), 1464-1469.e2. https://doi.org/10.1016/j.jamda.2020.03.010



Orentlicher, D. (2018). Healthcare, health, and income. Journal of Law, Medicine and Ethics, 46(3), 567–572. https://doi.org/10.1177/1073110518804198



Settels, J., & Leist, A. K. (2021). Changes in neighborhood-level socioeconomic disadvantage and older Americans’ cognitive functioning. Health and Place, 68, 102510. https://doi.org/10.1016/j.healthplace.2021.102510


Von Dem Knesebeck, O. (2015). Concepts of social epidemiology in health services research. BMC Health Services Research, 15(1). https://doi.org/10.1186/s12913-015-1020-z






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