CALIFORNIA COMPENSATION CASES
Vol. 88, No. 5 May 2023
A Report of En Banc and Significant Panel Decisions of the WCAB and Selected Court Opinions of Related Interest, With a Digest of WCAB Decisions...
By Hon. Susan V. Hamilton, Former Assistant Secretary and Deputy Commissioner, California Workers’ Compensation Appeals Board
In 2022 there were 7,490 wildfires in California. They burned 362,455 acres...
By Christopher Mahon
Should temporary workers be treated separately under workers’ compensation law due to additional employment and income risks they may incur after workplace injuries? A new study...
Here's a noteworthy panel decision where a family member conveyed essential information to the AME on behalf of the injured employee. The Lexis headnote is below.
CA - NOTEWORTHY PANEL DECISIONS...
Oakland, CA – Part II of a California Workers’ Compensation Institute (CWCI) research series on low- volume/high-cost drugs used to treat California injured workers identifies three Dermatological drugs...
Money Can’t Buy Happiness, But It May Help You Live Longer
The panoply of interrelated research on longevity appears to be coalescing around a consensus that socioeconomic status (“SES”) is an important indicator of life expectancy. Data suggests that those on the lowest rungs of the socioeconomic ladder tend to have a correspondingly lower life expectancy than those on the upper rungs. And the gap between the two has apparently been on the rise over the past 30 years. This trend, coupled with its societal implications and resultant policy decisions, has made the urgency of finding out what is driving these statistics more acute.
A group of researchers, Arijit Nandi, Maria Glymour and S.V. Subramanian, set out to test the effect of health behaviors such as smoking, alcohol consumption and physical inactivity on socioeconomic differences in mortality. Published in the March 2014 edition of Epidemiology, their study Association Among Socioeconomic Status, Health Behaviors and All-Cause Mortality in the United States found that such less-than-optimal health behavior is more prevalent in disadvantaged socioeconomic groups. It concluded that “[t]he distribution of health-damaging behaviors may explain a substantial portion of excess mortality associated with low SES in the United States, suggesting the importance of social inequalities in unhealthy behaviors.”
The study acknowledges several variable factors could potentially influence the life expectancy of individuals within a discrete socioeconomic group. In addition to health behaviors, these include: (1) different exposure to stress; (2) different access to material resources; and (3) different medical care quality. A recent New York Times article, Income Gap, Meet the Longevity Gap, published March 15, 2014, confirms this assessment. In comparing the longevity statistics between two counties of located less than 400 miles apart, the article noted that “[t]he link between income and longevity has been clearly established. Poor people are likelier to smoke. They have less access to the health care system. They tend to weigh more. And their bodies suffer the debilitating effects of more intense and more constant stress.”
Study Methodology and Results
A sample of 8037 participants in a Health and Retirement study, born between 1931 and 1941, were followed for “all-cause mortality” from 1998 through 2008. Each participant was assigned to one of four SES groups based on such markers as individual education, occupation, labor force status, household income and household wealth. Every two years, the participants’ smoking, alcohol use and physical activity was assessed.
In the first year of follow-up, 20% of respondents reported smoking, 32% reported alcohol consumption and 52% reported physical inactivity. The study found definite patterns between SES and these health behaviors – the more socially disadvantaged the participant was, the greater the risk of engaging in unhealthy behavior. In other words, the most disadvantaged were found to have smoked more, drank more and exercised less.
The study made efforts to account for such confounding factors as age, sex, race and early-life SES. Additional “sensitivity analyses” were undertaken to test the reliability of the results including separately testing the effect of educational status (a common indicator of adult SES) and body mass index (as a substitute for diet) on mortality. These “sensitivity analyses” aligned with the study results.
Between 1998 and 2008, 10% of the study participants died. Smoking was found to double the risk of mortality and physical inactivity tripled it. Alcohol consumption was “U-shaped”, with a lower risk of mortality among those reporting 1-2 drinks and 3-4 drinks per sitting, relative to none. The study found longevity increased along with socioeconomic status. In short, the study found that those in the most disadvantaged group had a nearly three times greater risk of reduced longevity compared to the least disadvantaged, with health behaviors accounting for about two-thirds of this increased risk.
As acknowledged by Nandi et al, the research on this issue is far from settled. For example, they noted that one French study concluded that although longevity decreased as SES decreased, health behaviors accounted for less than a quarter of this association. This discrepancy is attributed to a perceived disparity in health behavior evident among various socioeconomic groups in the U.S. that is not evident in France.
Another factor impacting results is the various methodologies used in different studies. This is particularly true in studies where socioeconomic status is a variable, as there are so many factors at play. For example access to quality healthcare, education and social resources plays a role, as does the impact of recurrent stress on an individual’s body.
As the Commentary to the study Commentary: Socioeconomic Status, Health Behavior, and Mortality: Old Question Plus Modern Methods Equals New Insights? noted “[t]he fact that a large number of sensitivity analyses were needed to overcome limitations inherent in the data emphasizes the need for better data.” Accordingly, the Commentary favors a nuanced rather than an absolute view of the study, noting that while gaps in data may be “trivial for epidemiologists who, regrettably, are becoming used to reporting confounded estimates from observational studies, [but] it is not trivial for policy makers who might take the findings at face value.”
Moreover, the Commentary notes it is “widely accepted” by social epidemiologists that factors influencing an individual’s behavior choices are not always fully within an individual’s control. For example, smoking could be viewed as a coping mechanism for stress. Arguably, therefore, either the stress should be ameliorated, or an alternate coping mechanism should be introduced. In other words, in order to address social disparities in health, it may be necessary to take a holistic view of addressing the social disparities themselves.
The study itself concludes:
“[p]atient level interventions have the potential to produce changes in health behaviors, although structural barriers to sustained behavior change suggest the need for complementary social approaches.”
A Final Word
So the takeaway is this: health behavior matters. According to this study, it accounts for about two-thirds of the disparity in longevity between the highest and lowest socioeconomic groups. But the solution is seemingly not as simple as telling people to smoke less and move around more. Lifestyle choices and access to resources play an important role.
Given the trend suggesting an increasing association between socioeconomic status and longevity, we can expect to see many more of these studies in the future. What impact this combined body of research may have on policy decisions in such arenas as healthcare, employment, disability and retirement benefits remains to be seen.
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