Laws
Effects of the Affordable Care Act Medicaid Expansion on Subjective Well-Being in the US Adult Population, 2010–2016
Lindsay C. Kobayashi, PhD, Onur Altindag, PhD, Yulya Truskinovsky, PhD, and Lisa F. Berkman, PhD
Objectives. To determine whether the 2014 Affordable Care Act Medicaid expansion
affected well-being in the low-income and general adult US populations.
Methods. We obtained data from adults aged 18 to 64 years in the nationally rep-
resentative Gallup-Sharecare Well-Being Index from 2010 to 2016 (n = 1 674 953). We
used a difference-in-differences analysis to compare access to and difficulty affording
health care and subjective well-being outcomes (happiness, sadness, worry, stress, and
life satisfaction) before and after Medicaid expansion in states that did and did not
expand Medicaid.
Results. Access to health care increased, and difficulty affording health care declined
following the Medicaid expansion. Medicaid expansion was not associated with changes
to emotional states or life satisfaction over the study period in either the low-income
population who newly gained health insurance or in the general adult population as a
spillover effect of the policy change.
Conclusions. Although the public health benefits of the Medicaid expansion are in-
creasingly apparent, improved population well-being does not appear tobe among them.
Public Health Implications. Subjective well-being indicators may not be informative
enough to evaluate the public health impact of expanded health insurance. (Am J Public
Health. 2019;109:1236–1242. doi:10.2105/AJPH.2019.305164)
See also Galea and Vaughan, p. 1169.
Akey component of the US AffordableCare Act (ACA) was the expansion of Medicaid eligibility to nonelderly adults with incomes up to 138% of the federal poverty level.1 This policy resulted in 9.6 million people becoming newly eligible for Medicaid beginning in 2014.2 The rapidly growing literature documents a range of beneficial outcomes for the newly eligible population, including higher rates of insurance coverage, increased access to health care providers, improved quality of care, increased use of preventive health services, reduced likelihood of emergency department visits, and reduced financial difficulties.3–7 Public health spill- over effects with relevance to the general population also have been documented, including lower rates of crime, higher prescribing of opioid treatments, and reduced socioeconomic disparities in access to health care.8–11 Evidence of direct effects on health
outcomes is relatively scarce,5 whereas a growing body of evidence shows mixed re- sults for its effect on self-rated health.7,11–14
The effects of the ACA Medicaid expansion on population well-being in the United States are unknown.
Human well-being is gaining attention from researchers and policymakers as a metric of social welfare that goes beyond standard indicators for health policy evaluation.15–18
Broadly defined, subjective well-being is a
multidimensional concept that refers to people’s evaluative judgments about their quality of life, referred to as “life satisfaction,” and emotional or affective states such as happiness, anger, or sadness.17 Life satisfaction and emotional states are sensitive to external events, such as the 2008 financial crisis and local employment shocks19–21 and are strongly predictive of health outcomes, in- cluding risks of cardiovascular disease and all-cause mortality.22–26 As direct and im- mediate indicators of welfare, these well- being measures have been proposed as metrics to assess the human welfare implications of policy interventions.17,27 However, the ef- fects of health policies on the well-being of the US general population have rarely been investigated.
We hypothesized that the ACA Medicaid expansion would be associated with im- proved well-being in the policy-eligible low- income population through increasing access to health care, which in turn may reduce exposure to health and financial risks. With respect to effects on population well-being beyond the policy-eligible population, it is important to note that the ACA was politi- cally unpopular when the Medicaid expan- sion component went into effect in January 2014. At this time, 50% of persons in the United States had an unfavorable view of the ACA, compared with just 34% who reported a favorable opinion of the ACA.28 Hence, whereas the societal welfare benefits
ABOUT THE AUTHORS Lindsay C. Kobayashi is with the Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC. Onur Altindag is with the Department of Economics, Bentley University, Waltham, MA. Yulya Truskinovsky is with the De- partment of Economics, Wayne State University, Detroit, MI. Lisa F. Berkman is with the Department of Social and Behavioral Sciences and the Harvard Center for Population and Development Studies, Harvard T.H. Chan School of Public Health, Cambridge, MA.
Correspondence should be sent to Lisa F. Berkman, PhD, Harvard Center for Population and Development Studies, 9 Bow St., Cambridge, MA 02138 (e-mail: lberkman@hsph.harvard.edu). Reprints can be ordered at http://www.ajph.org by clicking the “Reprints” link.
This article was accepted April 30, 2019. doi: 10.2105/AJPH.2019.305164
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introduced by the ACA Medicaid expansion could improve well-being in population members outside the policy-eligible pop- ulation, the unpopularity of the ACA could also have resulted in the Medicaid expansion having negative effects on well-being in the general population. We thus hypothesized that the net population spillover effect could be in either direction or possibly null if changes to this health policy did not affect well-being or had mixed effects on well- being among the unaffected segment of the general adult population.
Using individual-level data from more than 1.6 million US adults aged 18 to 64 years in the population-representative Gallup- Sharecare Well-Being Index from 2010 to 2016, we used a difference-in-differences analysis to compare pre- to post-ACA Medicaid expansion changes in subjective well-being indicators in (1) the policy-eligible low-income population who newly gained access to health insurance, and (2) the general adult population as a spillover effect of this policy change.
METHODS We conducted a secondary analysis of
data from the nationally representative US Gallup-Sharecare Well-Being Index, a daily telephone survey of at least 500 interviews each day with adults 18 years and older conducted by the Gallup Organization.29
As with the US Gallup Daily Poll, the survey uses a dual-frame stratified sampling design targeting landlines and cell phones and represents more than 90% of the adult US population.29 We restricted our sample to include individual-level data from adults aged 18 to 64 years and the years 2010 through 2016 (n = 1 674 953).
Ethical Approval The Gallup-Sharecare Well-Being Index
is conducted according to the Gallup Citi- zenship Guide and Code of Conduct. All pro- cedures were conducted in accordance with the ethical standards of the responsible com- mittee on human experimentation (in- stitutional and national) and with the Helsinki Declaration of 1975, as revised in 2000.
Identification of Policy-Eligible Population
The Medicaid expansion-eligible pop- ulation with household incomes up to 138% of the federal poverty level was identified according to reported household income bracket (< $720, $720–$5999, $6000– $11 999, $12 000–$23 999, $24 000–$35 999, $36 000–$47 999, $48 000–$59 999, ‡ $60 000), adjusted for household size as determined by reported marital status and number of children younger than 18 years in the household. Because household income was reported in brackets, we assigned in- dividuals the midpoint of their household income bracket that was reported in the study interview. Using this method, we estimated approximately 13% of the sample to be below 138% of the federal poverty rate, which is in line with national estimates.30 The analysis sample excludes observations between March and December of 2015 from the analysis because of missing information on income for this period.
Analytical Design To identify effects of the ACA Medicaid
expansion on well-being outcomes, we used a difference-in-differences analytical design to exploit plausibly exogeneous state-level variation in new eligibility for health insur- ance coverage resulting from the Medicaid expansion.31 This policy expanded Medicaid eligibility to cover individuals from house- holds with incomes up to 138% of the federal poverty level and was optional for states to participate in. Between January 1, 2014, and December 31, 2016, 32 states and the Dis- trict of Columbia participated in the ACA Medicaid expansion, whereas 18 states opted out. We categorized the 32 states that ex- panded Medicaid as implementing “full,” “substantial,” or “mild” expansion, follow- ing the definition from Simon et al. (see the box on page 1238).12
We excluded the 4 states defined as having mild expansion (Delaware, Massachusetts, New York, Vermont) and the District of Columbia after confirming that access to health insurance did not significantly change in these states compared with those that did not expand Medicaid. These mild expansion states had already implemented strong Med- icaid expansions separate from the ACA
policy before 2014. The substantial expansion states had, for the most part, implemented some degree of Medicaid expansion before 2014, but all participated in and substantially expanded their Medicaid programs as part of the ACA beginning in January 2014. The full expansion states fully expanded Medicaid coverage according to the ACA- mandated expansion beginning in January 2014.12
Outcomes We measured life satisfaction using Can-
tril’s Self-Anchoring Striving Scale, in which the respondent is asked to rate his or her life on a ladder scale in which 1 represents “the worst possible life for you” and 10 represents “the best possible life for you.”32 Two versions of the scale were administered in the study in- terview: 1 for current life satisfaction and 1 for the expectation of life satisfaction in 5 years.32
We rescaled the life satisfaction outcomes to be from 10 to 100 to aid with interpretability of the results. Emotional states were measured by asking respondents whether they had experienced happiness, sadness, worry, and stress on the day before the interview (yes vs no). We rescaled these dichotomous out- comes to be from 0 to 100, in which the rescaled outcomes indicate the average per- centage of the sample, out of 100%, who responded “yes” to experiencing the emo- tional state.
Covariates We adjusted all models for age, race/
ethnicity, education, gender, marital status, and the presence of children in the household to account for any residual confounding by these factors. We additionally adjusted for time-invariant indicators for state of residence (state fixed effects) as well as calendar day of the interview (time fixed effects). The state fixed effects account for any unmeasured differences between states, such as average differences in the outcomes. The time fixed effects account for any unmeasured common secular trends or events across states that could potentially confound the associations between Medicaid expansion and the outcomes under study, such as holidays, political events, or stock market volatility.
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Statistical Analysis Our difference-in-differences analysis of
the ACA Medicaid expansion consisted of 3 steps. First, we assessed whether adults living in states that expanded Medicaid reported changes in their rates of health insurance coverage, access to a personal doctor, and difficulty affording health care following the expansion relative to those in nonexpansion states. Second, we assessed whether adults living in states that expanded Medicaid had changes in their subjective well-being fol- lowing the expansion relative to those in nonexpansion states. Third, we visually compared differential pre- and post-Medicaid expansion time trends in the outcomes be- tween expansion and nonexpansion states to confirm that the outcomes followed parallel trends over time before Medicaid expansion in both groups. We conducted these 3 steps first among the policy-eligible low-income population and then among the general adult population.
For the first 2 steps, we used ordinary least squares regressions to model the associations between living in a state that expanded Medicaid and each of the access to health care and subjective well-being outcomes under study, adjusted for age, gender, race/ethnic- ity, education, marital status, the presence of children in the household, and the state and time fixed effects. We clustered the SEs at the state level in all models to account for spatial
correlations in outcomes across individuals living in the same states. We did not include the Gallup sampling weights in our models, as we had no reason to believe that the prob- ability of survey response was related to both subjective well-being and living in a state that had expanded Medicaid at a specific point in time over our study period. Our results were relatively unaffected by using the sampling weights in a sensitivity analysis.
The difference-in-differences research design relies on the assumption of parallel trends, meaning that, after accounting for covariates, all outcomes followed the same trends in expansion and nonexpansion states before the Medicaid expansion index date. This assumption allows interpretation of the post-Medicaid expansion outcome trends in the nonexpansion states to represent the counterfactual outcomes in the states that expanded Medicaid, had they not expanded it. We tested this assumption directly in the third step of our analysis by using a dynamic difference-in-differences analysis, which captures the differences in outcome trends between expansion and nonexpansion states over the full study period on a monthly basis. Specifically, we visually inspected monthly differences in covariate-adjusted outcomes between expansion and nonexpansion states. If the parallel trends assumption holds, these differences should be statistically indistinguish- able from zero before Medicaid expansion.
For a more technical explanation of our analytical approach, please refer to the sup- plementary statistical analysis in Appendix A (available as a supplement to the online version of this article at http://www.ajph. org). We conducted the statistical analyses using Stata/SE version 15.1 (College Station, TX) and R version 3.6 (R Core Team, Vienna, Austria).
Heterogeneity of Policy Effects We examined heterogeneity in the effects
of the ACA Medicaid expansion on well- being outcomes by applying our main model to the following subgroups in the policy- eligible population: gender, race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic), education (less than college, college graduate), marital status (married, not married), and having any children younger than 18 years in the household (yes, no).
Sensitivity Analyses We estimated the results separately for
states that fully and substantially expanded Medicaid to assess whether the results differed between these 2 groups.
RESULTS The characteristics of the sample were
consistent with the US general adult pop- ulation (Table 1). We observed increases in the rates of health insurance coverage, in- creases in the likelihood of having a doctor, and decreases in the likelihood of reporting difficulty affording medical care in states that fully or substantially expanded Medicaid (Table 2). In the policy-eligible population, mean insurance coverage over the period before the expansion was 64.1%, and fol- lowing the expansion it increased by 7.5 percentage points (95% confidence interval [CI] = 5.3, 9.8; Table 2). Of the policy- eligible population, 66% had access to a personal doctor during the period before Medicaid expansion; following the expansion the proportion reporting having access to a personal doctor increased by 3.5 percentage points (95% CI = 1.5, 5.5; Table 2). Of the policy-eligible population, 38% had difficulty affording medical care during the period
CLASSIFICATION OF US STATES BY AFFORDABLE CARE ACT MEDICAID EXPANSION: 2010–2016
Full expansion
AK, AZ, AR, CO, IL, IA, IN, KY, LA, MD, MI, MT, NH, NV, NJ, NM, ND, OH, OR, PA, RI, WA, WV
Substantial expansion
CA, CT, HI, MN, WI
Mild expansion
DE, DC, MA, NY, VT
Nonexpansion
AL, FL, GA, ID, KS, ME, MS, MO, NE, NC, OK, SC, SD, TN, TX, UT, VA, WY
Note. All expansion states in the box expanded Medicaid eligibility in January 2014 except MI in April 2014, NH in August 2014, PA in January 2015, IN in February 2015, AK in September 2015, MT in January 2016, and LA in July 2016. We retrieved dates of expansion from Kaiser Family Foundation28 and classification of changes in Medicaid from Simon et al.12 WI did not expand Medicaid, but childless adults up to 100% of the federal poverty level (as defined according to 2016 thresholds determined by the US Census Bureau) were eligible. ID, UT, ME, NE, and VA approved Medicaid expansion but did not implement it during the study period.28
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before the expansion; following the expan- sion the proportion reporting difficulty affording medical care decreased by 3.7 percentage points (95% CI = –6.2, –1.2; Table 2). In the general adult population, we saw average effects in the same direction but of smaller magnitude (Table 2).
In both the policy-eligible and the general adult populations, we observed no mean- ingful changes in mean reported life
satisfaction in the expansion states versus nonexpansion states following Medicaid ex- pansion (Table 2). However, we observed a precisely estimated effect of an extremely small magnitude on expected life satisfaction in 5 years in the general population (–0.25 points of 100; 95% CI = –0.47, –0.03). However, this effect was not observed in the policy-eligible population. We observed no meaningful changes in mean reported
measures of happiness, sadness, stress, or worry in the Medicaid expansion states versus nonexpansion states in either the policy-eligible population or the general population (Table 2).
The results of the dynamic difference-in- differences analysis are shown in Figure 1. We observed no differential pre-Medicaid ex- pansion trends in access to health care, life satisfaction, or emotional states in expansion versus nonexpansion states, consistent with the parallel trends assumption of the differ- ence-in-differences analytic design. After Medicaid expansion, we observed statistically significant differential increases in reported access to a doctor and having health insurance and decreases in difficulty affording health care sustained over time in expansion states versus nonexpansion states (Figure 1). We did not observe any differential changes in the well-being outcomes after expansion. For ease of presentation, Figure 1 reports the results of the dynamic difference-in-differ- ences models only for the policy-eligible population; the results for the general adult population were similar and are shown in Appendix A, Figure A.
Heterogeneity of Policy Effects In the policy-eligible population, we
observed no heterogeneity in the association between Medicaid expansion and subjective well-being across population subgroups defined by gender, level of educational attainment, marital status, or number of children in the household (Appendix A, Tables A–F). We observed reduced life satisfaction and increased stress and worry in non-Hispanic Whites and, conversely, improved life satisfaction and reduced worry in non-Hispanic Blacks associated with the ACA Medicaid expansion, but these effects were of very small magnitude (Appendix A, Tables A–F). However, because of the num- ber of simultaneous hypotheses we tested in this heterogeneity analysis, we interpret these statistically significant associations with caution.
Sensitivity Analyses When the analyses were restricted to full
and substantial Medicaid expansion states separately, the results were similar to the main analysis (Appendix A, Tables G and H).
TABLE 2—Effects of the Affordable Care Act (ACA) Medicaid Expansion on Access to Health Care and Well-Being: Gallup-Sharecare Well-Being Index, United States, 2010–2016
Policy-Eligible Adult Population General Adult Population
Outcome Effect (95% CI)
Preexpansion Mean
Effect (95% CI)
Preexpansion Mean
Access to health care
Health insurance 7.51 (5.24, 9.77) 64.08 2.25 (0.88, 3.63) 85.15
Access to personal doctor 3.48 (1.48, 5.48) 65.91 1.18 (0.42, 1.95) 80.82
Difficulty affording health
care
–3.71 (–6.20, –1.22) 37.87 –1.03 (–2.01, –0.06) 17.16
Well-being (on 0–100 scale)
Current life satisfaction 0.21 (–0.59, 1.01) 61.41 0.18 (–0.13, 0.48) 69.03
Expected life satisfaction in 5 y 0.08 (–0.82, 0.98) 75.15 –0.25 (–0.47, –0.03) 78.30
Worry –0.06 (–1.70, 1.58) 46.60 0.05 (–0.39, 0.49) 33.44
Sadness –0.09 (–1.92, 1.74) 30.29 0.10 (–0.25, 0.46) 17.28
Stress –0.11 (–1.57, 1.36) 52.94 0.17 (–0.30, 0.64) 43.73
Happiness –0.76 (–1.91, 0.39) 80.85 0.00 (–0.33, 0.34) 88.11
Note. CI=confidence interval. This table shows the difference-in-differences estimates of the effect of the ACA Medicaid expansion on access to health care and subjective well-being. The sample excludes mild expansionstates,asshownintheboxonpage1238. Allregressionscontrolforage,race/ethnicity,education, gender, marital status, having any children in the household, and state and interview day fixed effects. The policy-eligible population is defined as reporting a family income below 138% of the federal poverty level (as defined according to 2016 thresholds determined by the US Census Bureau). The general adult population includes the policy-eligible adult population. All outcome means are rescaled to be out of100 and calculated only for expansion states for the period 2010–2013, before the ACA Medicaid expansion took place. The minimum regression sample sizes for the policy-eligible and full general adult populations are 144939 and 1056794, respectively. Estimated with ordinary least squares and SEs are clustered at the state level.
TABLE 1—Characteristics of the Study Population: Gallup-Sharecare Well-Being Index, United States, 2010–2016
Policy-Eligible Adult Population General Adult Population
Characteristic Mean (SD) or % No. Mean (SD) or % No.
Age, y 41.1 (13.7) 165 144 44.9 (13.5) 1 186 733
Non-Hispanic White 55.7 161 221 74.8 1 148 122
Non-Hispanic Black 15.6 161 221 9.6 1 148 122
Hispanic 23.9 161 221 10.9 1 148 122
Married 48.4 164 805 60.6 1 176 407
College 16.6 163 491 44.2 1 173 981
Any children 54.6 164 927 38.7 1 184 418
Note. The general adult population includes the policy-eligible adult population.
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DISCUSSION Using the ACA Medicaid expansion in
2014 as a natural experiment in a difference- in-differences analysis of nationally repre- sentative data from 2010 to 2016, we ob- served that living in a state that expanded Medicaid was not associated with changes to subjective well-being either in the policy- eligible population or in the general adult population. We observed a very small decline in expected life satisfaction in 5 years’ time in the general adult population, which may have been a chance finding. The findings were consistent across a range of population
subgroups and according to the degree of state-level Medicaid expansion.
Our results are consistent with previous studies that have documented health in- surance coverage and health care access benefits of the ACA Medicaid expansion, which are outcomes that are seemingly rel- evant to well-being.3–7 We were also in- terested in whether the Medicaid expansion had a net spillover effect on general pop- ulation well-being, as the ACA is a well- publicized expansion of the US social safety net that elicits strong responses across the political spectrum. However, in this
nationally representative study of more than 1.6 million US adults from 2010 to 2016, we found no evidence of changes to well-being in either the policy-eligible low-income population or the general adult population following the ACA Medicaid expansion.
To the extent that people care about equity and the health care access of others in their state, we expected that subjective well-being, as captured by life satisfaction and emotional state, would improve in the gen- eral population. Positive community-level public health effects associated with the ACA Medicaid expansion—including reductions
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FIGURE 1—Month-to-Month Differences (Percentage Points) in Access to Health Care and Well-Being Between Medicaid Expansion States and Nonexpansion States in the Policy-Eligible Low-Income Population, by (a) Health Insurance, (b) Access to a Personal Doctor, (c) Financial Difficulty Affording Health Care, (d) Current Life Satisfaction, (e) Expected Life Satisfaction in 5 Years, (f) Happiness, (g) Worry, (h) Sadness, and (i) Stress: United States, 2010–2016
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in crime, increased prescribing of opioid treatments, and reduced socioeconomic in- equalities in access to health care—suggest the potential for positive effects of the policy beyond its direct effects on individual health insurance coverage.8–10
Although no other studies that we are aware of have investigated the effects of the ACA Medicaid expansion on dimensions of subjective well-being, evaluation of the 2008 Oregon Health Insurance Experiment found that reported happiness increased among those newly eligible for Medicaid after the first year,33 although the effect dissipated after 2 years.34 This finding contrasts with ours, which showed no changes in happiness in the US population following the ACA Medicaid expansion. However, our results are mostly consistent with those from other studies evaluating self-rated health following the expansion. Self-rated health captures aspects of subjective well-being in addition to being a robust indicator of physical health. Using data from the National Health Interview Surveys, the Gallup Well-Being Index, and the Be- havioral Risk Factors Surveillance System, other studies also using a difference-in-dif- ferences design have found no effect7,11,13 or a very small positive effect12 of the expansion on self-rated health. The exception was 1 study that used survey data from Kentucky (full expansion), Arkansas (expansion of private insurance through the federal marketplace), and Texas (no expansion) and found a 5–percentage point increase in excellent self-rated health associated with expanded health insurance coverage in the former 2 states.14
These null results suggest that gaining access to health insurance has at most a negligible effect on life satisfaction and no impact on emotional states. The indicators of life satisfaction and emotional states that we used in this study are recommended by the Organisation for Economic Co-operation and Development for measuring subjective well-being in survey research.35 These in- dicators have shown sensitivity to external financial shocks, namely the 2008 financial crisis, whereby Deaton used data from the Gallup Well-Being Index to show that emotional states and life satisfaction worsened in the US population following the finan- cial crisis.19
Newly gaining health insurance is pre- sumably a less extreme and less instantaneous financial shock, to which life satisfaction and emotional states simply may not respond. We were unable to capture other dimensions of subjective well-being, including purpose in life, sense of belonging, locus of control, and other emotional states that are not assessed by Gallup. Additional research using robust, causal designs should investigate the effects of the ACA Medicaid expansion as well as other health policies on a diverse range of human well-being indicators. Future research should also replicate our results as more time passes since the ACA Medicaid expansion, assuming that it stays in place, as it may take time for individuals to become accustomed to the new range of health services available to them and to understand the broader societal implica- tions of an expanded social safety net.
A limitation of this study is that we were not able to directly identify the individuals who were eligible to gain health insurance coverage through Medicaid expansion be- cause Gallup collected household income information in categorical brackets. We identified household income by assigning respondents the midpoint of their reported household income bracket; this approach likely resulted in a degree of nondifferential misclassification of the policy-eligible pop- ulation, which could bias our results, most likely toward the null. A main strength of this study is its extremely large and population- representative sample of US adults, with unique repeated cross-sectional data over a long follow-up that included comprehensive subjective well-being and other measures that are not available in any other nationally representative survey of the US population. We took advantage of exogeneous state-level Medicaid expansion as a natural experiment to assess the effects of Medicaid expansion on health care access and well-being in the adult US population.
As seemingly direct indicators of well- being, emotional state and life satisfaction measures appear useful for empirically assessing the human welfare implications of health policy interventions.19–21,27 However, this study puts into question whether these subjective well-being measures can be useful in drawing evaluative conclusions about health policies in the United States, as the ACA Medicaid expansion has generated
many outcomes that policy analysts and re- searchers would consider to be beneficial to public health. These include higher rates of health insurance coverage, greater use of preventive health services, reduced use of emergency medical services, reduced finan- cial difficulties, lower crime rates, and a narrowing of the socioeconomic gap in access to health care.3–10,14
This study contributes to this growing body of literature, demonstrating that al- though the ACA Medicaid expansion had meaningful effects on health insurance cov- erage and care access, its effects were not reflected in the emotional states or life satis- faction of the US adult population over the follow-up period that we examined. These results contribute to current discourse on the utility of subjective well-being measures for the evaluation of health policy and should be corroborated in the future as more time passes since the implementation of Medicaid expansion.
CONTRIBUTORS All authors conceptualized the study and its statistical design and analysis and contributed to article writing and editing, interpretation of results, and critical revision of the article for intellectual content.
ACKNOWLEDGMENTS This research was conducted while L. C. K. and O. A. were David E. Bell fellows and Y. T. was an Alfred P. Sloan Fellow on Aging and Work at the Harvard Center for Population and Development Studies.
We thank Gallup, for making their data available to us.
CONFLICTS OF INTEREST L. F. B. has received financial support as a consulting senior scientist with Gallup.
HUMAN PARTICIPANT PROTECTION As this was a secondary analysis of de-identified data, in- stitutional review board approval was not required.
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