AUGUST 2008 HOT TOPIC

Neighborhood Economic Conditions Influence the Consumption of Fruits and Vegetables

Health disparities across racial and ethnic groups in the United States are large and persistent. Obesity rates, one major area of concern, are increasing faster among black and Hispanic populations than among whites. Diet, particularly the intake of fruits and vegetables, figures prominently in obesity, and disparities in the consumption of fresh produce across different ethnic groups contribute to health disparities. Yet research has shed little light on the causes of disparities in the consumption of fruits and vegetables across the United States. Because blacks and Mexican Americans tend to live in more disadvantaged neighborhoods, it is likely that neighborhood economic conditions contribute to these disparities. A study based on national data, led by RAND researcher Tamara Dubowitz, examined the impact of neighborhood economic conditions on produce consumption. The study found that across the United States, residents of more affluent neighborhoods consumed significantly more servings of fruits and vegetables per week than did residents in less affluent neighborhoods. Neighborhood economic conditions also accounted for some of the disparities in fruit and vegetable intake across racial/ethnic groups. Whites and Mexican Americans living in economically similar neighborhoods consumed approximately the same number of servings of fruits and vegetables per week. Blacks still consumed fewer servings of fruits and vegetables per week than did whites in economically similar neighborhoods, but the difference was smaller than before neighborhood differences were taken into account. The results suggest that special efforts by community groups, businesses, or government to increase the availability of fresh produce and other healthy foods in disadvantaged neighborhoods may help local residents improve their diets. The results also underscore the importance of understanding the complex picture of culture and other competing influences on diet, especially when considering how differing racial/ethnic groups may experience their neighborhood environment.

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Life Expectancy Is Better Than Age as a Predictor of Health Care Spending

Increasing longevity, coupled with declining fertility rates, will substantially increase the number of people over age 80 in the United States in the coming decades. Given the link between age and health care costs, some researchers have predicted that these trends will produce sharp increases in health care costs, particularly for Medicare. To prepare for this eventuality, Medicare needs an accurate forecast of future costs. Yet it remains unresolved how best to estimate these costs: Does an individual’s current age best predict future health care costs, or is life expectancy (that is, remaining years of life) a better predictor? Using Medicare data, researchers Baoping Shang and Dana Goldman investigated this issue. Their analysis reached three conclusions: (1) life expectancy is a better predictor of health care expenditures than age, (2) neither age nor life expectancy has strong predictive power if health status is included in the model, and (3) spending projections based on life expectancy are lower than projections based on age. The gap between estimates increases as life expectancy increases (life expectancy at birth in the United States is projected to increase from 77.5 in 2008 to 79.7 in 2040 and to 82.0 in 2080). For example, in 2040, age-based projections of total spending are 9 percent higher than projections based on life expectancy; in 2080, age-based estimates are 22 percent higher. There are two alternative explanations for the direction of medical costs for the elderly. If people are living longer because several factors—such as medical technology, high-quality health care, healthy individual behaviors, and decreased environmental hazards—are improving health, then future Medicare beneficiaries will be healthier than current beneficiaries and projections based on age will overestimate future health care expenditures. If technology is keeping people alive longer—but in poor health—then projections based on life expectancy will underestimate future health care expenditures. The study found evidence to support the first of these explanations.

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IOM Quality Improvement Framework Is Useful for Behavioral Health Care

Mental health and substance use disorders are the leading cause of death and disability among women and among men ages 15–44, and they are the second leading cause of death and disability among all men, according to the Institute of Medicine (IOM). More than 33 million Americans are treated annually for these behavioral health illnesses and, like individuals with physical illness, this population is at risk of receiving poor care because of the nation’s broken health care system. When the IOM’s quality improvement framework was first introduced in 2001 to fix shortcomings in the U.S. health care system, the behavioral health community was concerned that the framework might not work for mental health and substance use disorders. But an examination shows that the IOM framework responds to the unique challenges of treating individuals with behavioral health issues and is currently incorporated into numerous nationwide projects targeting care for these conditions. For example, researchers from the RAND–University of Pittsburgh Health Institute, a collaboration between RAND Health and the University of Pittsburgh Schools of the Health Sciences, are participating in three quality improvement projects that are implementing IOM recommendations for behavioral health: (1) a study to increase the use of effective models for treating depression in primary care settings; (2) an evidence-based evaluation of mental health care services provided to veterans with schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, or substance use disorder; and (3) a community-based quality improvement initiative to bridge the physical and mental health care systems to enhance service delivery for women with maternal depression.

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