Table 1:
Tests of Preventability in Fundamental Cause Theory 2010–2020 – Type of Test, Key Results and Author’s Conclusion.
| Author/Year | Descriptions | Results | Author Quote |
|---|---|---|---|
| Disease Preventability | |||
| Bränström et al (2016) | Morbidity data (2001 to 2011) from a representative population–based study in Sweden. Studied individuals identified as heterosexual homosexual, or bisexual. | There were no sexual orientation differences in morbidity from low-preventable diseases. By contrast, gay or bisexual men and lesbian or bisexual women had a greater risk of high-preventable morbidity than heterosexual men and women. | “Our findings support fundamental cause theory and suggest that unequal distribution of health-protective resources, including knowledge, prestige, power, and supportive social connections, might explain sexual orientation health disparities (p. 1109).” |
| Delavar et al (2020) | Retrospective cohort study using US Surveillance, Epidemiology, and End Results data. Children and adolescents diagnosed with a first primary malignant cancer were followed up. Race/ethnic differences in in survival for cancers for which death is more versus less preventable. | Compared with non-Hispanic white children and adolescents, a significantly higher risk of death was observed for high- than low-amenability cancers for non-Hispanic black patients. | “We found racial/ethnic disparities in childhood and adolescent cancer survival for non-Hispanic black, non-Hispanic American Indian/Alaskan Native, non-Hispanic Asian or Pacific Islander, and Hispanic (any race) patients. These disparities were larger overall for more survivable cancer types, which are generally more amenable to medical intervention (p. 435).” |
| Ericsson et al (2019) | Study conducted to investigate socioeconomic differences in mortality by comparing preventable with non-preventable causes of death in participants from the Swedish Twin Registry. | SES gradients by education and occupation were observed and were not explained by family or genetic factors that the twin study allowed the authors to assess. In cohort analysis results the hazard ratio associated with having an occupation of low versus high standing was higher for high-preventability causes of death versus for low-preventability causes. | “There was a social gradient in both preventable mortality and non-preventable mortality, but with an indication of a moderately stronger effect in preventable causes of death (p. 1701).” |
| Kiadaliri and Englund (2020) | Studied over 92,000 people with osteoarthritis (OA) in Sweden following them for an average of 6.5 years for high preventability versus low preventability causes of death. | There were educational gradients for both more avoidable and less avoidable causes of death. The magnitude of relative educational inequality was greater for more avoidable than less avoidable Causes. |
“The Results suggest that educational attainment is a fundamental cause of inequality in OA.” (p. S448) |
| Mackenbach et al (2015) | Harmonized mortality data by educational level on 19 national and regional populations from 16 European countries to assess relative risk of mortality among men and women aged 30–79 for 24 causes of death classified into four groups: amenable to behavior change, amenable to medical intervention, amenable to injury prevention, and non-preventable. | Lower education is associated with elevated risk for regardless of preventability, but the relative risks are generally higher for diseases that are more versus less preventable. The median relative risk for low education for preventable causes is 2.15 for men and 1.90 for women whereas for low preventability causes they are 1.53 for men and 1.43 for women. Across countries/regions low education relative risks for men and women separately were higher for diseases preventable by behavior change than for low preventability diseases in all country wide comparisons (24/24), and 30/35 possible comparisons when regional studies conducted in Spain and Italy were included. | “Our results provide some further support for the theory of “fundamental causes”. However, the absence of larger inequalities for preventable causes in Southern Europe and for injury mortality among women indicates that further empirical and theoretical analysis is necessary to understand when and why the additional resources that a higher socioeconomic status provides, do and do not protect against prevailing health risks.” (p. 60) |
| Mackenbach et al (2017) | Harmonized mortality data by educational level for 22 causes of death and 20 In European populations 1980–2010). Educational differences in rate of decline among four categories: amenable to behavior change, amenable to medical intervention, amenable to injury prevention, and low preventability. | Mortality declines more rapidly over time for more highly educated than less highly educated people. The largest differences in mortality decline between low and high educated people are for causes amenable to behavior change. Mortality increases by 0.80 per cent per year among the low educated but declines by 0.93 per cent per annum among the high educated. Differences between low and high educated are also observed for conditions amenable to injury prevention and are smallest for low preventability conditions. | “While our results provide support for the fundamental causes theory, our results suggest that other mechanisms than the theory implies also play a role.” (p. 1117) |
| Masters et al (2015) | 19 waves (1986–2004) of the National Health Interview Survey are linked to official death records up at the National Death Index (NDI). The resulting file provides annual individual-level cause-specific mortality status for over 900,000 Black and White, males and females in the United States through December 31st, 2006. | Cohort-based reductions in mortality are larger for more preventable causes of death and, consistent with FTC, the greatest reductions in these deaths occurred among the more highly educated populations. But there were inconsistencies in this general conclusion when results are broken down by race and gender. | “Overall, findings are consistent with nearly all features of fundamental cause theory. Results show, first, larger education gradients in mortality risk for causes of death that are under greater human control than for less preventable causes of death, and, second, that these gradients grew more rapidly across successive cohorts than gradients for less preventable causes. Results also show that relative sizes and cohort-based changes in the education gradients vary substantially by race/ethnicity and gender” (p. 19) |
| Rydland et al (2020) | More versus less preventable morbidities were identified in the 2014 European Social Survey of 12,073 men and 13,488 women aged 25 to 69 from 20 countries. | In both men and women, the proportion of educational gaps were larger for the high-preventable than the low-preventable conditions in most countries. In the pooled conditions and countries analysis, no associations were significant among the low-preventable conditions. For the high-preventable conditions there were significant but modest educational gaps in both men and women. | “In a first explorative comparative European analysis we found support for the FCT hypothesis. Thus, the FCT can be used on morbidity data classified as low- versus high-preventable. We recommend extending this framework with institutional theories to explain within- and between-country health inequalities (from prepublication)” |
| Tehranifar et al (2016) | 51 cancer sites were classified into least amenable, partly amenable, and mostly amenable cancers. Cox regression models, on 516,939 cancer cases diagnosed between 1995–1999 examined whether racial disparities in mortality rates varied according to the amenability associated with a cancer site. | Blacks and Hispanics diagnosed with partly and mostly amenable cancers had higher mortality rates relative to whites with cancers of the same amenability levels; further, these differences decreased in magnitude or reversed in direction with increasing age. In contrast, the racial differences in mortality were smaller and remained fairly constant across age groups for least amenable cancers. | “Cancer survival disadvantage for racial minorities is larger in younger age groups for cancers that are more amenable to medical interventions (p. 553).” |
| Vanthomme et al (2017) | Data were from a record linkage study between the Belgian censuses of 1991 and 2001 and register data on mortality. The study population comprised all Belgian men aged 50–79 years during follow-up. | Despite an overall downward trend in cancer mortality, educational differences are observed for the majority of cancer sites in the 2000s. Generally, inequalities are largest for mortality from preventable cancers. | “Educational differences in site-specific cancer mortality persist in the 2000s in Belgium, mainly for the more preventable cancer sites” (p.480). |
| Zapata Moya et al (2015) | Data from three waves of the Spanish National Health Survey (collected between 2003 and 2010), and European Health Survey in Spain examined education gradients in more (depression, diabetes and myocardial infarction) versus less (malignant tumors) preventable diseases. | Education gradients in more-preventable illness are observed, while this is far less the case in our less-preventable disease group. | “However, as expected (Hypothesis 1) based on the Fundamental Cause Theory, educational gradients are only observed for the relatively more-preventable ill-nesses (depression, diabetes, and myocardial infarction), and not for the less preventable (malignant tumors) (p. 148).” |
| Preventability Shifts | |||
| (Clouston et al 2014b) | Age, race, sex, specific mortality rates for suicide among U.S. residents 25 years or over (1968–2009) were derived from death certificate and population data from the National Center for Health Statistics. Change in associations between county-level SES and suicide (prevention knowledge developed) mortality are compared. | Suicide mortality rates are initially similar in higher SES counties but shift upon the distribution of antidepressant medications (SSRIs) in lower SES counties are at greater risk and by 2009 the difference in mortality between counties with SES one SD above compared to one SD below grew substantially following the distribution of SSRI medications. | “We found support for the theory that SES based disparities in suicide arose with the widespread dispersal of SSRIs, which were concentrated in areas of higher SES. (p. 7)” |
| Rubin et al (2014) | Age, race, sex, specific mortality rates for lung and pancreatic cancer for people 45 years or over (1968–2009) were derived from death certificate and population data from the National Center for Health Statistics. Change in associations between county-level SES and lung (prevention knowledge developed) and pancreatic cancer (little prevention knowledge developed) mortality are compared. | Lung cancer mortality rates are initially higher in higher SES counties but by 1980 persons in lower SES counties are at greater risk and by 2009 the difference in mortality between counties with SES one SD above compared to one SD below average was 33 people per 100,000. In contrast, for pancreatic cancer where changes in preventability did not occur, people from higher SES counties were slightly more likely die of this cause with the association remaining relatively stable over the period of observation. | “These data support the fundamental cause hypothesis: social conditions influencing access to resources more greatly impact mortality when preventative knowledge exists (p. 54)” |
| Saldana-Ruiz et al (2013) | Data from the National Center for Health Statistics were used to calculate age-, gender-, and race-specific colorectal cancer mortality rates for counties in the continental United States (1968 to 2005). Change in associations between county level SES and colon cancer morality before and after screening improvements are examined. | Prior to 1980, people living in counties of higher socioeconomic status (SES) were at greater risk than people living in lower SES counties. Beginning in 1980, this gradient began to narrow and then reversed as people living in higher SES counties experienced greater reductions in colorectal cancer mortality than those in lower SES counties. | “Our findings support the fundamental cause hypothesis: once knowledge about prevention and treatment of colorectal cancer became available, social and economic resources became increasingly important in influencing mortality rates” (p. 99). |
| Wang et al (2012) | Mortality data (1968 to 2008) from the National Center for Health Statistics are used to calculate age-, gender-, and race-specific colorectal cancer mortality rates for counties in the United States. Changes in associations between county level SES and colon cancer mortality and a State-level of diffusion of innovations score and colon cancer mortality were examined before and after screening improvements were developed. | Beginning in the 1980s, the impact of county SES on colorectal cancer mortality developed into an inverse association (high SES lower mortality) and grew over time. States with a propensity for faster diffusion experienced faster reductions in mortality over this period. Finally, the tendency for rapid diffusion had a moderating impact on the influence of SES: the influence of SES was attenuated in states with a higher propensity for faster diffusion | “By examining geographical and contextual factors, we confirm the importance of fundamental cause theory in determining how social disparities in colorectal cancer arise (p. 613).” |
| Zapata-Moya et al (2019) | 50 to 69-year-old participants in the Onco-barometer survey (2010) of the non-institutionalized Spanish adult population in 2010. Assessed socioeconomic differences in access and use of health screens according to the stage their stage in the diffusion cycle. | SES was associated with use of cancer screening tests (PSA tests, Pap smears and mammograms), but not for preventive practices at early diffusion stage, like fecal occult blood tests, and for cardiovascular diseases (blood-pressure checks and cholesterol readings) that are in a late stage of diffusion. SES inequalities varied according to diffusion stage being smaller in the early stage of diffusion, growing in the intermediate stages and declining in the late stages of the diffusion process. | “Taken together, FCT and DOI theory can provide an integrated framework with which to study health inequalities in the adoption of preventive practices from a temporal and comparative perspective (p. 191).” |
| Manipulated Preventability | |||
| Bann et al (2016) | 70–89-year-old participants of a multicenter lifestyle intervention study using individuals randomized to a structured physical activity program. Assessed the incidence of mobility disability among higher and lower SES participants. | The benefits from the intervention seeking to reduce incidence of mobility disability via increased physical activity were concentrated among participants with some postgraduate education. Trends were evident in associations with income alone but were not statistically significant. | “the benefits of a physical activity intervention in preventing mobility disability did not significantly differ by socioeconomic group, yet effect sizes of intervention benefits were largest among those with higher education or income.” (p. 931) |
| Grytten et al (2020) | Studied the staggered implementation of a school reform that increased the length of compulsory education from seven to nine years in Norway. Follow-up for high versus low preventability until maximum age 64. | The estimated effect was of the policy change as it was rolled out over time in Norway and not educational attainment per se. The regression coefficient for being exposed versus unexposed to the reform led to a reduction for preventable deaths. For causes of death that could not be prevented, the estimate was small and not statistically significant. | “Our results supported the fundamental cause theory. This is because education had a stronger effect on mortality for causes of death that are preventable than for causes of death that are not preventable. More education had no effect on the probability of dying of diseases that were amenable to medical intervention only (online prepublication).” |
| Yang et al (2014) | Patients at 31 Belarusian maternity wards and their affiliates were randomized to receive breastfeeding promotion interventions | The promotion of breastfeeding resulted in graded inequalities in the intervention group by maternal education that were not evident in the control group. | “Our study intervention, which was designed to promote prolonged and exclusive breastfeeding, slightly widened socioeconomic inequalities in discontinuation of exclusive breastfeeding by 3 months and of any breastfeeding by 12 months.” (pg. 1291) |
| Zapata Moya and Navarro Yanez (2017) | Quasi-experimental design examining differences in standardized mortality rates between neighborhoods that were participating in urban regeneration processes versus those without ongoing regeneration projects. | Areas where urban regeneration projects were active experienced increases in SES inequalities in more preventable, but not less preventable, causes of death | “Area-based initiatives improve the opportunity structure by providing different types of flexible resources to residence, which may mediate the well-documented inverse relationship between SES and mortality risk.” (pg. 245) |
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Disease Preventability examines the association between SES and mortality across multiple disease outcomes that vary in the preventability of death; Preventability Shift examines particular diseases over time before and after changes in our capacity to address mortality from that particular disease occurred; Manipulated Preventability examines inequalities emerging during controlled trials in which exposure to an intervention is randomized.