High and Rising Mortality Rates Among Working-Age Adults (2021) / Chapter Skim
Currently Skimming:
6 A Framework for Developing Explanations of Working-Age Mortality Trends
6 A Framework for Developing Explanations of Working-Age Mortality Trends
Pages 187-218
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 187... ...
This chapter begins by describing the conceptual framework used by the committee to frame its broad discussion of the drivers of mortality trends. It then reviews the considerations used by the committee in developing potential explanations for the observed trends.
|
From page 188... ...
The most distal factors are referred to as "upstream" drivers, which generally fall within the category of "social, political, and cultural macro-level structure." Intermediate factors, those that are influenced by the macrostructural factors and represent the community-level contexts in which individuals live their daily lives, fall within the category of "mesolevel structure" in the figure. Upstream and intermediate factors are considered structural by virtue of their higher order or aggregate level of measurement and analysis (e.g., social and economic inequality, institutional or governmental policies, neighborhood, social networks)
|
From page 189... ...
While structural features of the environment are correlated with individual mortality risks, these structural features are often the result of individual characteristics and actions. For example, high-income individuals can afford to live in neighborhoods with green space for physical activity, healthy food choices, health care resources, and high-quality schools for children.
|
From page 190... ...
are governed by federal and state policies but also have autonomy to establish their own policies that influence community resources and mortality risks through spending on education; health care services; mental health and substance use programs; local health-related infrastructure, such as parks and sidewalks; and more. Together, these federal, state, and local policies are thought to drive subgroup and geographic differences in social and economic inequality, environmental conditions affecting health, and health care access (Hummer and Hamilton, 2019; Montez, Hayward, and Wolf, 2017)
|
From page 191... ...
owns the vast majority of America's wealth, economic opportunities become cemented into the social hierarchy, constraining intergenerational mobility for most. Social inequality further defines differential access to opportunities and resources that promote longevity and prevent premature mortality according to such attributes as gender, race and ethnicity, nativity, LGBTQ status, and educational attainment, and those disparities are exacerbated as this structurally based inequality widens (Hayward, Hummer, and Sasson, 2015; Phelan and Link, 2015; Phelan, Link, and Tehranifar, 2010)
|
From page 192... ...
The economic downturn during the 2008 Great Recession affected population subgroups differentially according to age, gender, race and ethnicity, and socioeconomic status, with short- and long-term implications for health. Technology Developments Another set of macro-level factors comprises technology developments, which can impact mortality trends in multiple ways.
|
From page 193... ...
On the other hand, low-income women who are single parents may be especially vulnerable to poor health and mortality risk, particularly in a period like the Great Recession or the COVID-19 pandemic, given the greater stresses of being in a low-socioeconomic structural position in the context of a weakened social safety net (e.g., limited unemployment benefits and dwindling food, housing, and health care benefits) (Montez et al., 2015)
|
From page 194... ...
Social network connections may also provide valued social capital resources, such as information about training or job opportunities, community health care access, and other local resources. To the extent that engagement in social networks reinforces common goals and interests and promotes positive and supportive social interaction, feelings of social cohesion and social integration are protective from mortality risks.
|
From page 195... ...
The physical characteristics of neighborhoods and communities that influence health and mortality risks include air and water quality; proximity to facilities that produce or store hazardous substances; exposures to lead paint, chemicals, mold, dust, or household pest infestation; access to nutritious foods; and safe and convenient places to exercise, such as sidewalks, running trails, and parks and recreation centers. Health Care Availability of and access to health care within the community in which people live or work is vital to health promotion; disease prevention; and the treatment of medical conditions, mental health, and injuries -- each of which can prevent premature death.
|
From page 196... ...
Extensive research has also focused on the role of behavior in mortality trends in general and in the recent rise in mortality among working-age adults in particular. Health behaviors, including tobacco use, alcohol and drug use, violence, exercise, and diet, have a direct relation to deaths from multiple causes, including drug poisoning, alcohol use, suicide, cancer, and cardiometabolic diseases.
|
From page 197... ...
as having latent, long-lasting effects on health and development that heighten the risk of premature mortality. Other factors operating in childhood, such as early adverse life experiences or low socioeconomic status, can affect mental and physical health later in adulthood (Felitti et al., 1998)
|
From page 198... ...
And increasing heavy alcohol use that causes increases in alcohol-related deaths could be responsive to changing social norms regarding access to and accessibility of alcohol over the past few decades. Although parsimony is desirable in developing potential explanations, it was important to keep in mind as the data were examined that in cases of multiple mortality trends in different subgroups, a range of correlated factors could be operating simultaneously.
|
From page 199... ...
. These types of relations characterize the complex systems that may give rise to observed mortality trends, so understanding their key features may be important to developing comprehensive explanations for those trends.
|
From page 200... ...
Differences Across Social Groups Any explanation of the drivers of the mortality trends described in this report must also consider the reasons why those drivers manifested differently by age, gender, race and ethnicity, socioeconomic status, and geographic region during the study period. As discussed in Chapters 2 and 3, U.S.
|
From page 201... ...
Consideration of vulnerability and precipitating factors may also help explain differences in mortality trends across social and geographic groups. For example, structural factors related to social inequality and disadvantage may consistently make low-educated, low-income, and racial/ethnic minority groups vulnerable to adverse health impacts through stress/mental disorders or other mechanisms.
|
From page 202... ...
Researchers studying mortality trends often distinguish between period-based and cohort-based explanations of the trends. Period-based influences affect mortality change simultaneously for all age groups in a population in the same time period.
|
From page 203... ...
. A preferred descriptive approach for detecting cohort-based variation in mortality trends entails plotting age-specific mortality rates across time periods to observe the degree to which the period-based trends in mortality rates are parallel (Kupper et al., 1985)
|
From page 204... ...
In subsequent chapters, these ideas are applied in discussing potential explanations for recent mortality trends and in identifying research gaps in understanding the prominent mortality trends highlighted in Part I of this report. ANNEX 6-1 Period- and Cohort-Based Examination of Trends in U.S.
|
From page 205... ...
, the age-specific mortality rates differ considerably by birth cohort, and the age patterns increase across cohorts. For example, the M40 rates in DGP1 are observed to be 35 deaths per 100,000 population for birth cohort 1956, 70 for birth cohort 1966, and 97 for birth cohort 1976.
|
From page 206... ...
206 HIGH AND RISING MORTALITY RATES AMONG WORKING-AGE ADULTS 1936 120 1946 1956 100 1966 1976 1986 80 Observed Mx 60 40 20 0 20 25 30 35 40 45 50 55 60 65 Age ANNEX FIGURE 6-1 DGP1 Mx by birth cohort. 1936 120 1946 1956 100 1966 1976 1986 Observed Mx 80 60 40 20 0 20 25 30 35 40 45 50 55 60 65 Age ANNEX FIGURE 6-2 DGP2 Mx by birth cohort.
|
From page 207... ...
, but the differences in DGP3 are larger across cohorts because of both the cohort and period effects on mortality trends. Thus, this descriptive approach of contrasting different cohorts' age-specific death rates does not help detect cohort-based variation in mortality trends.
|
From page 208... ...
208 HIGH AND RISING MORTALITY RATES AMONG WORKING-AGE ADULTS 120 100 80 Observed Mx 20 60 25 30 35 40 40 45 50 20 55 60 65 0 1990 1995 2000 2005 2010 2015 Period ANNEX FIGURE 6-4 DGP1 Mx by period. 80 70 60 Observed Mx 50 40 20 25 30 30 35 40 20 45 50 10 55 60 65 0 1990 1995 2000 2005 2010 2015 Period ANNEX FIGURE 6-5 DGP2 Mx by period.
|
From page 209... ...
Because of the disparate mortality trends between these age groups, their Mx levels were comparable in 2015. And because the age groups experienced strikingly different trends across time periods, the "nonparallelism" in the plots suggests strong cohort-based variation in their mortality rates.
|
From page 210... ...
These varying patterns in the mortality trends among working-age Americans are worth considering when evaluating possible explanations for the recent mortality trends in the United States. Any explanation for rising mortality among U.S.
|
From page 211... ...
Blue lines indicate drug-related Mx for ages 25–54, and orange lines indicate Mx for ages 55–64. These ages are differentiated to highlight important racebased differences in drug-related mortality trends among U.S.
|
From page 212... ...
NOTE: Blue lines indicate Mx for age groups 25–29, and 50–54, and orange lines indicate Mx for age groups 55–59 and 60–64. SOURCE: Data from https://www.cdc.gov/nchs/nvss/nvss-restricted-data.htm.
|
From page 213... ...
A FRAMEWORK FOR DEVELOPING EXPLANATIONS 213 80 Black Men 70 60 50 40 30 20 10 0 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 80 White Men 70 55-59 60-64 60 25-54 Avg 50 40 30 20 10 0 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 ANNEX FIGURE 6-8 Drug-related mortality rates for U.S. Black and White men ages 55–59 and 60–64 versus 25–54 average, 1990–2017.
|
From page 214... ...
Annex Figure 6-10 plots Mx from alcohol-related deaths across time periods to illustrate important racial/ethnic- and gender-based differences in the mortality trends. Across the 1990s and 2000s, death rates from alcohol use declined substantially among the U.S.
|
From page 215... ...
NOTE: Lines indicate the ratio between Mx in each year and Mx in 1990. SOURCE: Data from https://www.cdc.gov/nchs/nvss/nvss-restricted-data.htm.
|
From page 216... ...
216 HIGH AND RISING MORTALITY RATES AMONG WORKING-AGE ADULTS 50 Black Women 40 30 20 10 0 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 50 White Women 40 40 45 50 55 30 60 20 10 0 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017
|
From page 217... ...
A FRAMEWORK FOR DEVELOPING EXPLANATIONS 217 140 Black Men 120 100 80 60 40 20 0 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 140 40 White Men 45 120 50 100 55 60 80 60 40 20 0 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 ANNEX FIGURE 6-10 Alcohol-related mortality rate by 5-year age group, 40–44 to 60–64, between 1990 and 2017, U.S. Black and White women and men.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.