David G. Moriarty

Associations between recommended levels of physical activity and health-related quality of life. Findings from the 2001 Behavioral Risk Factor Surveillance System (BRFSS) survey.

BACKGROUND Although the benefits of regular physical activity on morbidity and mortality are established, relationships between recommended levels of physical activity and health-related quality of life (HRQOL) have not been described. The authors examined whether recommended levels of physical activity were associated with better HRQOL and perceived health status. METHODS Using data from 175,850 adults who participated in the 2001 Behavioral Risk Factor Surveillance System survey, the authors examined the independent relationship between recommended levels of moderate or vigorous physical activity and four measures of HRQOL developed by the U.S. Centers for Disease Control and Prevention. Multivariate logistic regression was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs) adjusted for age, race/ethnicity, sex, education, smoking status, and body mass index. RESULTS The proportion of adults reporting 14 or more unhealthy days (physical or mental) was significantly lower among those who attained recommended levels of physical activity than physically inactive adults for all age, racial/ethnic, and sex groups. After multivariate adjustment, the relative odds of 14 or more unhealthy days (physical or mental) in those with the recommended level of activity compared to physically inactive adults was 0.67 (95% CI: 0.60, 0.74) for adults aged 18-44 years, 0.40 (95% CI: 0.36, 0.45) for adults aged 45-64 years, and 0.41 (95% CI: 0.36, 0.46) for adults aged 65 years or older. The results persist even among adults with a chronic condition such as arthritis. CONCLUSIONS These results highlight the need for health programs to increase participation in regular physical activity.

Worsening Trends in Adult Health-Related Quality of Life and Self-Rated Health— United States, 1993-2001

Objectives. Health-related quality of life and self-rated health complement mortality and morbidity as measures used in tracking changes and disparities in population health. The objectives of this study were to determine whether and how health-related quality of life and self-rated health changed overall in U.S. adults and in specific sociodemographic and geographic groups from 1993 through 2001. Methods. The authors analyzed data from annual cross-sectional Behavioral Risk Factor Surveillance System surveys of 1.2 million adults from randomly selected households with telephones in the 50 states and the District of Columbia. Results. Mean physically and mentally unhealthy days and activity limitation days remained constant early in the study period but increased later on. Mean unhealthy days increased about 14% during the study period. The percentage with fair or poor self-rated health increased from 13.4% in 1993 to 15.5% in 2001. Health-related quality of life and self-rated health worsened in most demographic groups, especially adults 45–54 years old, high school graduates without further education, and those with annual household incomes less than

Physical activity and health related quality of life among people with arthritis

50,000. However, adults 65 years old or older and people identified as non-Hispanic Asian/Pacific Islander reported stable or improving health-related quality of life and self-rated health. In 18 of the states and the District of Columbia, mean unhealthy days increased, while only North Dakota reported a decrease. Conclusion. Population tracking of adult health-related quality of life and self-rated health identified worsening trends overall and for many groups, suggesting that the nations overall health goals as identified in the Healthy People planning process are not being met.

Associations between short- and long-term unemployment and frequent mental distress among a national sample of men and women.

Study objective: To assess the association between physical activity and health related quality of life (HRQOL) among persons with arthritis or chronic joint symptoms (CJS). Design: Cross sectional survey investigating the relation between physical activity level and HRQOL. HRQOL was estimated using the number of physically or mentally unhealthy days during the past 30 days. Physical activity was categorised as recommended, insufficient, or inactive according to federal activity recommendations. Persons with arthritis were defined as those with either self reported CJS or doctor diagnosed arthritis. Setting: Community dwelling, US adults residing in all 50 states and the District of Columbia. Participants: Respondents (n = 212 000) in the 2001 behavioral risk factor surveillance system (BRFSS), an annual population based, telephone survey. Main results: The 33% of BRFSS respondents with arthritis had a mean of 6.7 physically and 4.9 mentally unhealthy days during the past 30 days, compared with 1.8 and 2.7 among those without arthritis. Inactive men and women were 1.2–2.4 times more likely to report impaired HRQOL compared with those who met physical activity recommendations. Men and women who engage in insufficient physical activity also report variably reduced HRQOL. Conclusions: Among people with arthritis, recommended levels of physical activity were associated with fewer mean physically and mentally unhealthy days and a decreased probability of having severely impaired physical or mental HRQOL.

Determinants of Quality of Life Among People with Asthma: Findings from the Behavioral Risk Factor Surveillance System

Unemployment has been associated with poor psychologic well-being. Using data from the 2001 Behavioral Risk Factor Surveillance System, we examined relationships between unemployment and frequent mental distress (FMD), defined as 14 or more mentally unhealthy days during the previous 30 days, among 98,267 men and women aged 25–64 years. The age-standardized prevalence of FMD was 6.6% (standard error, 0.14) among employed adults, 14.0% (2.00) among adults unemployed >1 year, and 15.5% (1.18) among those unemployed <1 year. After adjustment, the relative odds of FMD were 2.09 (95% confidence interval [CI] = 1.75–2.50) for adults unemployed <1 year and 1.88 (95% CI = 1.31–2.71) for adults unemployed >1 year compared with employed adults. Similar patterns were observed across gender, race/ethnicity, education, income, and area unemployment groups. Unemployed persons are a population in need of public health intervention to reduce the burden of mental distress. Public health officials should work with government officials to incorporate the health consequences of unemployment into economic policymaking.

County-level social environment determinants of health-related quality of life among US adults: a multilevel analysis.

Asthma is a major contributor to impaired quality of life in the U.S. population. Little is known about population‐based determinants of quality of life among people with asthma, however. Using data from the 2000 Behavioral Risk Factor Surveillance System, we examined the associations between selected sociodemographic, behavioral, and other determinants and quality of life among 12,111 participants with current asthma. In multiple logistical regression models, three variables—employment status, smoking status, and physical activity—were significantly associated with all measures of impaired quality of life (poor or fair health, ≥ 14 physically unhealthy days, ≥ 14 mentally unhealthy days, ≥ 14 activity limitation days, or ≥ 14 physically or mentally unhealthy days). Education was significantly and inversely related to impaired quality of life for all measures except activity limitation days. Men were less likely than women to report having ≥ 14 physically unhealthy days, ≥ 14 mentally unhealthy days, or ≥ 14 physically or mentally unhealthy days. Compared with whites, Hispanics were more likely to report being in poor or fair health, and African Americans were less likely to report having ≥ 14 physically unhealthy days or ≥ 14 physically or mentally unhealthy days. In addition, participants with lower incomes were more likely to report impaired quality of life for three measures (general health status, ≥ 14 physically unhealthy days, and activity limitation days). The heaviest participants were more likely to be in poor or fair health or to report having more ≥ 14 physically unhealthy days, or ≥ 14 physically or mentally unhealthy days. Insurance coverage and the time since their last routine checkup were not significantly associated with any of the quality‐of‐life measures. These results show that three potentially modifiable factors (smoking status, physical activity, body mass index) are associated with quality of life among persons with asthma. Furthermore, among people with asthma, the elderly, women, poorly educated, and low‐income participants are especially likely to experience impaired quality of life.

Predicting the EuroQol Group’s EQ-5D Index from CDC’s “Healthy Days” in a US Sample

To show that an individual’s health-related quality of life (HRQOL) is not determined only by their personal-level characteristics, but also is socially determined by both physical and social environmental characteristics of their communities. This analysis examined the association of selected county-level indicators on respondents’ unhealthy days and assessed the utility of mean unhealthy days for US counties as community health indicators. Data came from the 1999–2001 Behavioral Risk Factor Surveillance System. We used multilevel models to calculate the proportion of between-county variation in HRQOL that was explained by county-level contextual variables and examine the causal heterogeneity of some personal-level factors modified by these contextual variables. Counties with worse socioeconomic indicators, high mortality rate, and low life expectancy were associated with higher numbers of unhealthy days. These indicators explained 13–22% variance of county-level physically unhealthy days and 4.5–9.5% variance of county-level mentally unhealthy days. The GINI index, suicide rate, percent uninsured, primary care facilities-to-population ratio, and most county-level demographic and housing indicators also had significant but smaller impact on respondents’ unhealthy days. Also, the counties with poorer socioeconomic scores had additional negative HRQOL impact on older persons. This study provides important new empirical information on whether various commonly-measured characteristics of the social environment, which are believed to be social determinants of health, are in fact associated with the perceived physical and mental health of its residents. Our findings provide additional support for the construct validity of county-level HRQOL as a community health indicator.

Geographic Patterns of Frequent Mental Distress U.S. Adults, 1993-2001 and 2003-2006

Background. Obtaining reliable preference-based scores from the widely used Healthy Days measures would enable calculation of quality-adjusted life years (QALYs) and cost-utility analyses in many US community populations and over time. Previous studies translating the Healthy Days to the EQ-5D, a preference-based measure, relied on an indirect method because of a lack of population-based survey data that asked both sets of questions of the same respondents. Method. Data from the 2005–2006 National Health Measurement Study (NHMS; n = 3844 adults 35 years old or older) were used to develop regression-based models to estimate EQ-5D index scores from self-reported age, self-rated general health, and numbers of unhealthy days. Results. The models explained up to 52% of the variance in the EQ-5D. Estimated EQ-5D scores matched well to the observed EQ-5D scores in mean scores overall and by age, gender, race/ethnicity, income, education, body mass index, smoking, and disease categories. The average absolute differences were 0.005 to 0.006 on a health utility scale. After estimating mean EQ-5D index scores overall and for various subgroups in a large representative US sample of Healthy Days respondents, the authors found that these mean scores also closely matched the corresponding mean scores of EQ-5D respondents obtained from another large US representative sample with an average absolute difference of 0.013 points. Conclusions. This study yielded a mapping algorithm to estimate EQ-5D index scores from the Healthy Days measures for populations of adults 35 years old and older. Such analysis confirms it is feasible to estimate mean EQ-5D index scores with acceptable validity for use in calculating QALYs and cost-utility analyses based on the overall model fit and relatively small differences between the observed and the estimated mean scores.

A Conceptual Framework For Identifying Unmet Health Care Needs of Community Dwelling Elderly

BACKGROUND Mental illnesses and other mental health problems often lead to prolonged, disabling, and costly mental distress. Yet little is known about the geographic distribution of such mental distress in the U.S. METHODS Since 1993, the CDC has tracked self-perceived mental distress through the Behavioral Risk Factor Surveillance System (BRFSS). In 2007 and 2008, analysis was performed on BRFSS data reported by 2.4 million adults from 1993-2001 and 2003-2006 to map and describe the prevalence of frequent mental distress (FMD)-defined as having >or=14 mentally unhealthy days during the previous 30 days-for all states and for counties with at least 30 respondents. RESULTS The adult prevalence of FMD for the combined periods was 9.4% overall, ranging from 6.6% in Hawaii to 14.4% in Kentucky. From 1993-2001 to 2003-2006, the mean prevalence of FMD increased by at least 1 percentage point in 27 states and by more than 4 percentage points in Mississippi, Oklahoma, and West Virginia. Most states showed internal geographic variations in FMD prevalence. The Appalachian and the Mississippi Valley regions had high and increasing FMD prevalence, and the upper Midwest had low and decreasing FMD prevalence. CONCLUSIONS Geographic areas were identified with consistently high and consistently low FMD prevalence, as well as areas in which FMD prevalence changed substantially. Further evaluation of the causes and implications of these patterns is warranted. Surveillance of mental distress may be useful in identifying unmet mental health needs and disparities and in guiding health-related policies and interventions.

Relationships Between Engaging in Recommended Levels of Physical Activity and Health-Related Quality of Life Among Hypertensive Adults

Assessing the unmet health care needs that affect the quality of life of older persons is an important task facing both aging services agencies and health departments. This article reviews various strategies for assessing unmet health care needs and a presents comprehensive framework for assessing such needs. Needs for health services are categorized by their function, such as basic maintenance, supportive, rehabilitative, treatment, promotive, and preventive needs. Factors contributing to unmet needs are categorized by the types of barriers to using existing services. These barriers include recognition or awareness of need, knowledge about services, and availability, accessibility, affordability, and acceptability of services. Means of data collection for different types of unmet health care needs are presented. Recommendations for using the proposed framework are made to both health departments and aging services agencies.