Doing well
Inequality in mortality decreased among the young while increasing for older adults, 1990–2010
Janet Currie & Hannes Schwandt
Science, 6 May 2016, Pages 708-712
Abstract:
Many recent studies point to increasing inequality in mortality in the U.S. over the past twenty years. These studies often use mortality rates in middle and old age. Here we study inequality in mortality for all age groups in 1990, 2000, and 2010. Our analysis is based on groups of counties ranked by their poverty levels. Consistent with previous studies, we find increasing inequality in mortality at older ages. For children and young adults below age 20, however, we find strong mortality improvements that are most pronounced in poorer counties, implying a strong decrease in mortality inequality. These younger cohorts will form the future adult U.S. population, so this research suggests that inequality in old age mortality is likely to decline in future.
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Elizabeth Bradley et al.
Health Affairs, May 2016, Pages 760-768
Abstract:
Although spending rates on health care and social services vary substantially across the states, little is known about the possible association between variation in state-level health outcomes and the allocation of state spending between health care and social services. To estimate that association, we used state-level repeated measures multivariable modeling for the period 2000–09, with region and time fixed effects adjusted for total spending and state demographic and economic characteristics and with one- and two-year lags. We found that states with a higher ratio of social to health spending (calculated as the sum of social service spending and public health spending divided by the sum of Medicare spending and Medicaid spending) had significantly better subsequent health outcomes for the following seven measures: adult obesity; asthma; mentally unhealthy days; days with activity limitations; and mortality rates for lung cancer, acute myocardial infarction, and type 2 diabetes. Our study suggests that broadening the debate beyond what should be spent on health care to include what should be invested in health — not only in health care but also in social services and public health — is warranted.
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Tsu-Yu Tsao et al.
American Journal of Public Health, June 2016, Pages 1036-1041
Objectives: To assess potential reductions in premature mortality that could have been achieved in 2008 to 2012 if the minimum wage had been $15 per hour in New York City.
Methods: Using the 2008 to 2012 American Community Survey, we performed simulations to assess how the proportion of low-income residents in each neighborhood might change with a hypothetical $15 minimum wage under alternative assumptions of labor market dynamics. We developed an ecological model of premature death to determine the differences between the levels of premature mortality as predicted by the actual proportions of low-income residents in 2008 to 2012 and the levels predicted by the proportions of low-income residents under a hypothetical $15 minimum wage.
Results: A $15 minimum wage could have averted 2800 to 5500 premature deaths between 2008 and 2012 in New York City, representing 4% to 8% of total premature deaths in that period. Most of these avertable deaths would be realized in lower-income communities, in which residents are predominantly people of color.
Conclusions: A higher minimum wage may have substantial positive effects on health and should be considered as an instrument to address health disparities.
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Martha McClintock et al.
Proceedings of the National Academy of Sciences, 31 May 2016, Pages E3071–E3080
Abstract:
The World Health Organization (WHO) defines health as a “state of complete physical, mental and social well-being and not merely the absence of disease or infirmity.” Despite general acceptance of this comprehensive definition, there has been little rigorous scientific attempt to use it to measure and assess population health. Instead, the dominant model of health is a disease-centered Medical Model (MM), which actively ignores many relevant domains. In contrast to the MM, we approach this issue through a Comprehensive Model (CM) of health consistent with the WHO definition, giving statistically equal consideration to multiple health domains, including medical, physical, psychological, functional, and sensory measures. We apply a data-driven latent class analysis (LCA) to model 54 specific health variables from the National Social Life, Health, and Aging Project (NSHAP), a nationally representative sample of US community-dwelling older adults. We first apply the LCA to the MM, identifying five health classes differentiated primarily by having diabetes and hypertension. The CM identifies a broader range of six health classes, including two “emergent” classes completely obscured by the MM. We find that specific medical diagnoses (cancer and hypertension) and health behaviors (smoking) are far less important than mental health (loneliness), sensory function (hearing), mobility, and bone fractures in defining vulnerable health classes. Although the MM places two-thirds of the US population into “robust health” classes, the CM reveals that one-half belong to less healthy classes, independently associated with higher mortality. This reconceptualization has important implications for medical care delivery, preventive health practices, and resource allocation.
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Total Economic Consequences of an Influenza Outbreak in the United States
Fynnwin Prager, Dan Wei & Adam Rose
Risk Analysis, forthcoming
Abstract:
Pandemic influenza represents a serious threat not only to the population of the United States, but also to its economy. In this study, we analyze the total economic consequences of potential influenza outbreaks in the United States for four cases based on the distinctions between disease severity and the presence/absence of vaccinations. The analysis is based on data and parameters on influenza obtained from the Centers for Disease Control and the general literature. A state-of-the-art economic impact modeling approach, computable general equilibrium, is applied to analyze a wide range of potential impacts stemming from the outbreaks. This study examines the economic impacts from changes in medical expenditures and workforce participation, and also takes into consideration different types of avoidance behavior and resilience actions not previously fully studied. Our results indicate that, in the absence of avoidance and resilience effects, a pandemic influenza outbreak could result in a loss in U.S. GDP of $25.4 billion, but that vaccination could reduce the losses to $19.9 billion. When behavioral and resilience factors are taken into account, a pandemic influenza outbreak could result in GDP losses of $45.3 billion without vaccination and $34.4 billion with vaccination. These results indicate the importance of including a broader set of causal factors to achieve more accurate estimates of the total economic impacts of not just pandemic influenza but biothreats in general. The results also highlight a number of actionable items that government policymakers and public health officials can use to help reduce potential economic losses from the outbreaks.
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Understanding the Improvement in Disability Free Life Expectancy In the U.S. Elderly Population
Michael Chernew et al.
NBER Working Paper, June 2016
Abstract:
Understanding how healthy lifespans are changing is essential for public policy. This paper explores changes in healthy lifespan in the U.S. over time and considers reasons for the changes. We reach three fundamental conclusions. First, we show that healthy life increased measurably in the US between 1992 and 2008. Years of healthy life expectancy at age 65 increased by 1.8 years over that time period, while disabled life expectancy fell by 0.5 years. Second, we identify the medical conditions that contribute the most to changes in healthy life expectancy. The largest improvements in healthy life expectancy come from reduced incidence and improved functioning for those with cardiovascular disease and vision problems. Together, these conditions account for 63 percent of the improvement in disability-free life expectancy. Third and more speculatively, we explore the role of medical treatments in the improvements for these two conditions. We estimate that improved medical care is likely responsible for a significant part of the cardiovascular and vision-related extension of healthy life.
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Save Time, Save Lives: The Impact of 9-1-1 on Lethality and Homicides
Thomas Stratmann & David Chandler Thomas
George Mason University Working Paper, April 2016
Abstract:
Several theories have been offered to explain the recent declines in the lethality and homicide rates in the United States. We hypothesize that technological innovations, which improved information transmission and shortened the response time between an aggravated assault incident and treatment, reduced the cost of saving lives and caused much of the decline in lethality and homicide rates in recent decades. Using difference-in-differences and regression-discontinuity designs, we show that improvements in emergency services (9-1-1) caused significant decreases in lethality and homicide rates. Various placebo and falsification tests support these findings.
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Theresa Senn, Jennifer Walsh & Michael Carey
Archives of Sexual Behavior, July 2016, Pages 1069-1082
Abstract:
Prior research shows that violence is associated with sexual risk behavior, but little is known about the relation between community violence (i.e., violence that is witnessed or experienced in one’s neighborhood) and sexual risk behavior. To better understand contextual influences on HIV risk behavior, we asked 508 adult patients attending a publicly funded STI clinic in the U.S. (54 % male, M age = 27.93, 68 % African American) who were participating in a larger trial to complete a survey assessing exposure to community violence, sexual risk behavior, and potential mediators of the community violence–sexual risk behavior relation (i.e., mental health, substance use, and experiencing intimate partner violence). A separate sample of participants from the same trial completed measures of sexual behavior norms, which were aggregated to create measures of census tract sexual behavior norms. Data analyses controlling for socioeconomic status revealed that higher levels of community violence were associated with more sexual partners for men and with more episodes of unprotected sex with non-steady partners for women. For both men and women, substance use and mental health mediated the community violence–sexual risk behavior relation; in addition, for men only, experiencing intimate partner violence also mediated this relation. These results confirm that, for individuals living in communities with high levels of violence, sexual risk reduction interventions need to address intimate partner violence, substance use, and mental health to be optimally effective.
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Erica Spatz et al.
JAMA Cardiology, forthcoming
Design, Setting, and Participants: In this observational study, county-level risk-standardized (age, sex, and race) hospitalization and 1-year mortality rates for AMI from January 1, 1999, to December 31, 2013, were measured for Medicare beneficiaries 65 years or older. Data analysis was performed from June 2 through December 1, 2015. Counties were stratified by median income percentile using 1999 US Census Bureau data adjusted for inflation: low- (<25th), average- (25th-75th), or high- (>75th) income groups.
Results: In the 15-year study period, AMI risk-standardized hospitalization and mortality rates decreased significantly for all 3 county income groups. Mean hospitalization rates were significantly higher among low-income counties compared with high-income counties in 1999 (1353 vs 1123 per 100 000 person-years, respectively) and in 2013 (853 vs 648 per 100 000 person-years, respectively). One-year mortality rates after hospitalization for AMI were similar across county income groups, decreasing from 1999 (31.5%, 31.4%, and 31.1%, for high-, average-, and low-income counties, respectively) to 2013 (26.2%, 26.1%, and 25.4%, respectively). Income was associated with county-level, risk-standardized AMI hospitalization rates but not mortality rates. Increasing 1 interquartile range of median county consumer price index–adjusted income ($12 000) was associated with a decline in 46 and 37 hospitalizations per 100 000 person-years for 1999 and 2013, respectively; interaction between income and time was 0.56. The rate of decline in AMI hospitalizations was similar for all county income groups; however, low-income counties lagged behind high-income counties by 4.3 (95% CI, 3.1-5.9) years. There were no significant differences in trends across geographic regions.
Conclusions and Relevance: Hospitalization and mortality rates of AMI declined among counties of all income levels, although hospitalization rates among low-income counties lag behind those of the higher income groups. These findings lend support for a more targeted, community-based approach to AMI prevention.
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Corby Martin et al.
JAMA Internal Medicine, June 2016, Pages 743-752
Importance: Calorie restriction (CR) increases longevity in many species and reduces risk factors for chronic diseases. In humans, CR may improve health span, yet concerns remain about potential negative effects of CR.
Objective: To test the effect of CR on mood, quality of life (QOL), sleep, and sexual function in healthy nonobese adults.
Design, Setting, and Participants: A multisite randomized clinical trial (Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy Phase 2 [CALERIE 2]) was conducted at 3 academic research institutions. Adult men and women (N = 220) with body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 22.0 to 28.0 were randomized to 2 years of 25% CR or an ad libitum (AL) control group in a 2:1 ratio favoring CR. Data were collected at baseline, 12 months, and 24 months and examined using intent-to-treat analysis. The study was conducted from January 22, 2007, to March 6, 2012. Data analysis was performed from July 18, 2012, to October 27, 2015.
Main Outcomes and Measures: Self-report questionnaires were administered to measure mood (Beck Depression Inventory-II [BDI-II], score range 0-63, higher scores indicating worse mood, and Profile of Mood States [POMS], with a total mood disturbance score range of −32 to 200 and higher scores indicating higher levels of the constructs measured), QOL (Rand 36-Item Short Form, score range 0-100, higher scores reflecting better QOL, and Perceived Stress Scale, score range 0-40, higher scores indicating higher levels of stress), sleep (Pittsburgh Sleep Quality Index [PSQI], total score range 0-21, higher scores reflecting worse sleep quality), and sexual function (Derogatis Interview for Sexual Function–Self–report, total score range 24-188, higher scores indicating better sexual functioning).
Results: In all, 218 participants (152 women [69.7%]; mean [SD] age, 37.9 (7.2) years; mean [SD] BMI, 25.1 [1.6]) were included in the analyses. The CR and AL groups lost a mean (SE) of 7.6 (0.3) kg and 0.4 (0.5) kg, respectively, at month 24 (P < .001). Compared with the AL group, the CR group had significantly improved mood (BDI-II: between-group difference [BGD], −0.76; 95% CI, −1.41 to −0.11; effect size [ES], −0.35), reduced tension (POMS: BGD, −0.79; 95% CI, −1.38 to −0.19; ES, −0.39), and improved general health (BGD, 6.45; 95% CI, 3.93 to 8.98; ES, 0.75) and sexual drive and relationship (BGD, 1.06; 95% CI, 0.11 to 2.01; ES, 0.35) at month 24 as well as improved sleep duration at month 12 (BGD, −0.26; 95% CI, −0.49 to −0.02; ES, −0.32) (all P < .05). Greater percent weight loss in the CR group at month 24 was associated with increased vigor (Spearman correlation coefficient, ρ = −0.30) and less mood disturbance (ρ = 0.27) measured with the POMS, improved general health (ρ = −0.27) measured with the SF-36, and better sleep quality per the PSQI total score (ρ = 0.28) (all P < .01).
Conclusions and Relevance: In nonobese adults, CR had some positive effects and no negative effects on health-related QOL.
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Elizabeth Davenport et al.
Journal of Neurotrauma, forthcoming
Abstract:
The purpose of this study is to determine if the effects of cumulative head impacts during a season of high school football produce changes in diffusional kurtosis imaging (DKI) metrics in the absence of clinically diagnosed concussion. Subjects were recruited from a high school football team and were outfitted with the Head Impact Telemetry System (HITs) during all practices and games. Biomechanical head impact exposure metrics were calculated including: total impacts, summed acceleration, and Risk Weighted cumulative Exposure (RWE). Twenty-four players completed pre- and post-season MRI, including DKI; players who experienced clinical concussion were excluded. Fourteen subjects completed pre- and post-season Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT). DKI-derived metrics included mean kurtosis (MK), axial kurtosis (K axial), and radial kurtosis (K radial), and white matter modeling (WMM) parameters included axonal water fraction (AWF), tortuosity of the extra-axonal space, extra-axonal diffusivity (De axial and radial), and intra-axonal diffusivity. These metrics were used to determine the total number of abnormal voxels, defined as 2 standard deviations above or below the group mean. Linear regression analysis revealed a statistically significant relationship between RWEcp and MK. Secondary analysis of other DKI-derived and WMM metrics demonstrated statistically significant linear relationships with RWEcp after covariate adjustment. These results were compared with the results of DTI-derived metrics from the same imaging sessions in this exact same cohort. Several of the DKI-derived scalars (Da, MK, K axial, and K radial) explained more variance when compared to RWEcp, suggesting that DKI may be more sensitive to subconcussive head impacts. No significant relationships between DKI-derived metrics and ImPACT measures were found. It is important to note, the pathological implications of these metrics are not well understood. In summary, we demonstrate a single season of high school football can produce DKI measurable changes in the absence of clinically diagnosed concussion.