State‐Level Unemployment and the Utilization of Preventive Medical Services

Tefft, Nathan; Kageleiry, Andrew

doi:10.1111/1475-6773.12091

Cited by 34 publications

(45 citation statements)

References 28 publications

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“…[7][8][9]26 Further research should specifically identify the types of primary and specialty care services older veterans are reducing. It appears that higher local area unemployment imposed monetary constraints on these veterans through a reduction in enabling resources.…”

Section: Discussionmentioning

confidence: 99%

“…[7][8][9] Specifically, higher unemployment rates were associated with decreases in discretionary health services including preventative medical services and routine nonemergency medical care. [7][8][9] Specifically, higher unemployment rates were associated with decreases in discretionary health services including preventative medical services and routine nonemergency medical care.…”

mentioning

confidence: 99%

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Association Between Local Area Unemployment Rates and Use of Veterans Affairs Outpatient Health Services

et al. 2014

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Association Between Local Area Unemployment Rates and Use of Veterans Affairs Outpatient Health Services

et al. 2014

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“…The BRFSS collects data on personal health behaviors and individual characteristics and has frequently been used to study the relationship between unemployment and health (Ruhm and Black, 2002, Ruhm, 2005, Ruhm, 2003, Dee, 2001, Tefft and Kageleiry, 2014, Helliwell et al, 2011.…”

Section: Datamentioning

confidence: 99%

Unemployment Insurance and Physical Activity

Cylus¹

2017

Human Capital and Health Behavior

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Unemployment insurance (UI) reduces the opportunity cost of leisure, but it is unknown whether this additional leisure time is physically active. To obtain unbiased estimates of the effect of UI on physically active leisure participation, I exploit changes in UI program legislation across US states and time. Using nationally representative monthly data between 2003 and 2010 from the Behavioral Risk Factor Surveillance System (BRFSS) and the American Time Use Survey (ATUS), I find evidence that both state UI eligibility expansions and increases in maximum allowable state UI benefits coincide with greater probability of physical activity among the recently unemployed. Based on point estimates, state UI eligibility expansions increased the probability of physical activity participation by 8 to 10 percentage points among the unemployed with less than a high school education, while a 10 percent increase in the maximum allowable state UI benefit increased the probability of physical activity by 0.3 to 0.6 percentage points among the unemployed who have completed high school or some college.

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“…First, cigarette use has been linked to adverse life events, including unemployment (De Vogli & Santinello, 2005), loss of health insurance coverage, and financial stress (Siahpush, Borland, & Scollo, 2003), which, in turn, may be associated with lack of preventive health behaviors. Using data from a survey of the civilian, non-institutionalized population of adults (age 18 and older) in the United States between 1987 and 2010, Tefft and Kageleiry (2014) found that a 1% point increase in the state-level unemployment rate is associated with a 1.58 percent decrease in use of preventive health services. Women and economically disadvantaged populations are particularly vulnerable to macroeconomic fluctuations.…”

Section: Discussionmentioning

confidence: 99%

Lack of Preventive Health Behaviors in the Early Forties: The Role of Earlier Trajectories of Cigarette Smoking From Adolescence to Adulthood

Zhang

Brook

Leukefeld

et al. 2017

Substance Use & Misuse

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Introduction To study the degree to which individuals in different trajectories of cigarette smoking from adolescence to the early 40s are similar or different in terms of lack of preventive health behaviors (e.g., underuse of preventive health services, unhealthy eating habits) in early midlife. Methods Participants came from a community-based random sample of residents in two upstate New York counties (N=548). Data were collected from adolescence to early midlife (mean age = 43, SD = 2.8) at seven time points. Using growth mixture modeling, we statistically identified the number of smoking trajectories. Logistic regression analysis was used to study the relationship between the probabilities of participants’ smoking trajectory group membership and lack of preventive behaviors in early midlife. Results Five trajectory groups of cigarette smokers were identified. With controls, as compared to the nonsmoker trajectory group, higher probabilities of belonging to the heavy/continuous smoker trajectory group and the late starter trajectory groups were significantly associated with a higher likelihood of lack of preventive health behaviors (Adjusted Odds Ratio [A.O.R.] = 3.49; A.O.R. =4.02, respectively). In addition, as compared to the quitter/decreaser trajectory group, higher probabilities of belonging to the heavy/continuous smoker trajectory group and the late starter trajectory group were also significantly associated with a higher likelihood of lack of preventive health behaviors (A.O.R. = 3.51; A.O.R. = 4.04, respectively). Conclusions Intervention programs may consider focusing on heavy/continuous smokers and late starters in programs designed to promote adequate use of preventive health services and healthy general lifestyles in early midlife.

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State‐Level Unemployment and the Utilization of Preventive Medical Services

Cited by 34 publications

References 28 publications

Association Between Local Area Unemployment Rates and Use of Veterans Affairs Outpatient Health Services

Association Between Local Area Unemployment Rates and Use of Veterans Affairs Outpatient Health Services

Unemployment Insurance and Physical Activity

Lack of Preventive Health Behaviors in the Early Forties: The Role of Earlier Trajectories of Cigarette Smoking From Adolescence to Adulthood

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