Rural-urban variations in psychological distress: findings from the Behavioral Risk Factor Surveillance System, 2007

Objectives:  

To describe rural and urban differences in the prevalence and correlates of psychological distress in the United States.     

Serious psychological distress and its associations with body mass index: findings from the 2007 Behavioral Risk Factor Surveillance System

Objectives:  

To examine the associations of body mass index (BMI) with serious psychological distress (SPD) after taking into consideration the obesity-related comorbidities (ORCs), lifestyle factors, or emotional support.     

Relationships between serious psychological distress and the use of health services in the United States: findings from the Behavioral Risk Factor Surveillance System

Objective:  

To determine rates of access to and use of health services among adults with Serious Psychological Distress (SPD).     

Association between diagnosed diabetes and serious psychological distress among U.S. adults: the Behavioral Risk Factor Surveillance System, 2007

Objectives:  

To estimate the prevalence of serious psychological distress (SPD) according to diabetes status and to assess the association of diabetes-related risks and conditions with SPD among U.S. adults.     

Trends in cigarette smoking among US adults with diabetes: findings from the Behavioral Risk Factor Surveillance System

BACKGROUND: Smoking substantially increases morbidity and mortality rates in people with diabetes. Previous studies have shown that the prevalence of smoking among people with diabetes is similar to that among people without diabetes. We sought to examine temporal trends in the prevalence of smoking among people with diabetes since 1990. METHODS: We analyzed data from the Behavioral Risk Factor Surveillance System for 1990-2001. RESULTS: The age-adjusted prevalence of smoking among adults with diabetes was 23.6% (men, 25.4%; women, 22.2%) in 1990 and 23.2% (men, 24.8%; women, 21.9%) in 2001. In comparison, the prevalence among participants without diabetes was 24.2% (men, 25.7%; women, 22.8%) in 1990 and 23.2% (men, 24.8%; women, 21.5%) in 2001. Thus, the prevalence of cigarette smoking was similar and remained stable from 1990 through 2001. Among participants with diabetes, significant decreases in the prevalence of smoking occurred among African Americans and those aged >/=65 years. CONCLUSIONS: New efforts and commitments to promote smoking cessation among people with diabetes are needed.     

Modifiable characteristics of a healthy lifestyle and chronic health conditions in older adults with or without serious psychological distress, 2007 Behavioral Risk Factor Surveillance System

Objective:  

The associations between serious psychological distress (SPD), chronic health conditions, healthy behaviors, healthy weight, and use of preventive services were examined among adults 65 years old and older using the 2007 Behavioral Risk Factor Surveillance System (BRFSS).     

Smoking status and health-related quality of life: as findings from the 2001 Behavioral Risk Factor Surveillance System data

PURPOSE: To examine the relationship between smoking status and health-related quality of life (HRQOL). DESIGN: Our study used a cross-sectional analysis with self-reported data from the 2001 Behavioral Risk Factor Surveillance System (BRFSS). SETTING: United States. SUBJECTS: Subjects were a representative sample of noninstitutionalized adults aged 18 years and older. After excluding respondents who reported being pregnant and for whom smoking status could not be determined, we included 209,031 respondents. MEASURES: Multiple logistic regressions were performed to examine the associations of smoking status with the four HRQOL items, controlling for demographic and health-related characteristics. RESULTS: Current smokers had a higher likelihood of reporting poor general health status compared with nonsmokers and ex-smokers. Compared with nonsmokers, current smokers had a higher likelihood of reporting > or = 14 days of poor physical health (odds ratio [OR] = 1.64, 95% confidence interval [CI] = 1.51-1.77), poor mental health (OR = 1.99, 95% Cl = 1.84-2.16), and activity limitations (OR = 1.80, 95% Cl = 1.63-2.00). Similarly, compared with ex-smokers, current smokers had a higher likelihood of reporting > or = 14 days of poor physical health (OR = 1.30, 95% CI = 1.19-1.42), poor mental health (OR = 1.65, 95% CI = 1.50-1.81), and activity limitations (OR = 1.48, 95% CI = 1.32-1.65). Age, income, and presence of comorbidities also significantly explained variation in HRQOL. CONCLUSIONS: Our study reaffirms the significant association between smoking and HRQOL in a large nationally representative sample. Poor health associated with smoking persists as a major public health problem, and effective preventive and smoking cessation efforts should be undertaken.     

Multiple healthy behaviors and optimal self-rated health: Findings from the 2007 Behavioral Risk Factor Surveillance System Survey

ObjectiveThe aim of this study was to examine the association between the number of healthy behaviors (i.e., not currently smoking, not currently drinking excessively, physically active, and consuming fruits and vegetables five or more times per day) and optimal self-rated health (SRH) among U.S. adults or adults with cardiovascular diseases (CVDs) or diabetes.MethodsWe estimated the age-standardized prevalence of optimal SRH among a total of 430,912 adults who participated in the 2007 Behavioral Risk Factor Surveillance System (BRFSS). Prevalence ratios were produced with multivariate Cox regression models using number of healthy behaviors as a predictor; status of optimal SRH was used as an outcome variable while controlling for sociodemographic and health risk factors.ResultsThe age-standardized prevalence of reporting optimal SRH was 83.5%, 55.6%, and 56.3% among adults overall, and adults with CVDs or diabetes, respectively. Also in the aforementioned order, adults who reported having four healthy behaviors had 33%, 85%, and 87% increased likelihoods of reporting optimal SRH, when compared to their counterparts who reported none of these behaviors.ConclusionThe findings of this study indicate that number of healthy behaviors is associated with optimal SRH among adults, especially adults with CVDs or diabetes. These findings reinforce the support for identifying and implementing clinical and population-based intervention strategies that effectively promote multiple healthier lifestyle behaviors among adults.     

Self-reported body mass index and health-related quality of life: findings from the Behavioral Risk Factor Surveillance System

OBJECTIVE: To examine the relationship between self-reported body mass index (BMI) and health-related quality of life in the general adult population in the United STATES: RESEARCH METHODS AND PROCEDURES: Using data from 109,076 respondents in the 1996 Behavioral Risk Factor Surveillance System, we examined how self-reported BMI is associated with five health-related quality of life measures developed by the Centers for Disease Control and Prevention for population health surveillance. RESULTS: After adjusting for age, gender, race or ethnicity, educational attainment, employment status, smoking status, and physical activity status, participants with a self-reported BMI of <18.5 kg/m(2) and participants with a self-reported BMI of > or =30 kg/m(2) reported impaired quality of life. Compared with persons with a self-reported BMI of 18.5 to <25 kg/m(2), odds ratios (ORs) of poor or fair self-rated health increased among persons with self-reported BMIs of <18.5 (1.57, 95% confidence interval [CI]: 1.31 to 1.89), 25 to <30 kg/m(2) (1.12, 95% CI: 1.04 to 1.20), 30 to <35 kg/m(2) (1.65, 95% CI: 1.50 to 1.81), 35 to <40 kg/m(2) (2.58, 95% CI: 2.21 to 3.00), and > or =40 kg/m(2) (3.23, 95% CI: 2.63 to 3.95); ORs for reporting > or =14 days of poor physical health during the previous 30 days were 1.44 (95% CI: 1.21 to 1.72), 1.04 (95% CI: 0.96 to 1.14), 1.32 (95% CI: 1.19 to 1.47), 1.80 (95% CI: 1.52 to 2.13), and 2.37 (95% CI: 1.90 to 2.94), respectively; ORs for having > or =14 days of poor mental health during the previous 30 days were 1.18 (95% CI: 0.97 to 1.42), 1.02 (95% CI: 0.95 to 1.11), 1.22 (95% CI: 1.10 to 1.36), 1.68 (95% CI: 1.42 to 1.98), and 1.66 (95% CI: 1.32 to 2.09), respectively. DISCUSSION: In the largest study to date, low and increased self-reported BMI significantly impaired health-related quality of life. Particularly, deviations from normal BMI affected physical functioning more strongly than mental functioning.     

Personal emergency preparedness for people with disabilities from the 2006-2007 Behavioral Risk Factor Surveillance System

BackgroundPeople with disabilities may be disproportionately at risk of injury or death in emergency situations due to physical, cognitive, and socioeconomic factors. These factors individually or in combination have the potential to affect response to emergencies before, during, or after the incident. This study examines general emergency preparedness of persons with disabilities compared to those without disabilities.MethodsThe 2006-2007 Behavioral Risk Factor Surveillance System of 6 states included 188,288 self-reported respondents with disabilities who were surveyed regarding their general emergency preparedness. Chi square analysis examined the relationship of general preparedness variables with disability status. Logistic regression analysis examined how various demographic variables affected the likelihood of being unprepared for an emergency.ResultsPersons with disabilities were significantly more likely to state that they were not prepared at all for an emergency. They were also less likely to have a 3-day supply of water, a working battery-operated radio, and a working flashlight and to evacuate an emergency situation. Persons with a disability are 1.22 times more likely to be unprepared for an emergency. For those with a disability, being female, nonwhite, with less education, less income, and uncoupled and living in an urban area increase the likelihood of being unprepared for an emergency.ConclusionIncreased effort must be made to empower persons with disabilities to become involved in their own emergency preparedness. Efforts are being made by several government and nongovernmental organizations to assist in this effort though most have not addressed specific needs of vulnerable populations within the disability community. Strategies for emergency preparedness must be considerate of these high risk populations. Finally, mechanisms must be developed to connect persons within the disability community to the information necessary on emergency preparedness through methods such as telehealth.     

Associations between minimum wage policy and access to health care: evidence from the Behavioral Risk Factor Surveillance System, 1996-2007

Objectives. We examined whether minimum wage policy is associated with access to medical care among low-skilled workers in the United States.Methods. We used multilevel logistic regression to analyze a data set consisting of individual-level indicators of uninsurance and unmet medical need from the Behavioral Risk Factor Surveillance System and state-level ecological controls from the US Census, Bureau of Labor Statistics, and several other sources in all 50 states and the District of Columbia between 1996 and 2007.Results. Higher state-level minimum wage rates were associated with significantly reduced odds of reporting unmet medical need after control for the ecological covariates, substate region fixed effects, and individual demographic and health characteristics (odds ratio = 0.853; 95% confidence interval = 0.750, 0.971). Minimum wage rates were not significantly associated with being uninsured.Conclusions. Higher minimum wages may be associated with a reduced likelihood of experiencing unmet medical need among low-skilled workers, and do not appear to be associated with uninsurance. These findings appear to refute the suggestion that minimum wage laws have detrimental effects on access to health care, as opponents of the policies have suggested.Minimum wage laws have long been advanced as policy mechanisms to improve the economic conditions of the working poor. Recently, questions have been raised about the true net benefit of such policies for low-skilled workers. Although income gains arising from minimum wage increases are clearly beneficial, these policies may also have secondary effects that could negatively affect low-skilled workers.The adverse effect most commonly considered is a potential contraction of employment in the low-wage sector as firms employ fewer workers or limit hours to offset the added payroll. Of particular interest in the realm of public health, however, is the possibility that minimum wage laws may substantially reduce access to health care. Research has yet to clarify this relationship.Competing hypotheses have been advanced that describe both positive and negative effects of minimum wage increases on health care access. Proponents of higher minimum wage laws suggest that the direct income-increasing effect of such interventions may be improvements in access to care, as workers are better able to afford out-of-pocket health care expenses such as insurance premiums, deductibles, and copayments. With greater disposable income available following wage hikes, affected workers would then be less likely to experience cost-related barriers to accessing medical care. These hypotheses, building on recent empirical literature documenting associations between higher income and better access to health care,^1–5 propose that increases in workers'' hourly wage will bolster their health care access.Alternatively, opponents of the policies warn that higher minimum wages will lead to unintended effects that will directly and indirectly weaken access to care for the working poor. Some economists have argued that employers may offset increases in the minimum wage directly by cutting health insurance benefits or by offering less generous benefit plans.^6–8 Minimum wage opponents have also argued that increases in the minimum wage depress employment, which could result in a net worsening in access to health care and in the economic conditions of vulnerable populations through a reduction in low-wage employment opportunities.After remaining at $5.15 since 1997, the federal minimum wage increased to $5.85 in July 2007 as part of a 3-step increase to the current $7.25 rate. During the 10 years between increases, the real value of the minimum wage had eroded to equal its lowest point in the preceding 50 years, whether defined in real terms or as a proportion of average wages.⁹ In many areas of the United States, even this newly increased minimum wage was not enough to keep workers and their dependents out of poverty, as the $12 168 earned by a full-time minimum wage earner in 2007 represented only 70% of the federal poverty limit of $17 170 for a family of three.¹⁰In response to the diminishing real value of the federal standard between 1997 and 2007, many states and municipalities enacted policies mandating higher minimum wages for workers in their jurisdictions. At the time of the 2007 federal wage hike, 31 states and the District of Columbia had passed laws setting higher wage standards, none of which was surpassed by the federal increase.⁹At this intersection of poverty and health care access, the minimum wage may be a policy tool with potential implications for health outcomes, but little empirical evidence currently exists to clearly determine whether access to care for low-skilled workers will be helped or harmed by changes to minimum wage policy. Although the employment effects of minimum wage laws have been extensively researched, the exact nature of the relationship between the policies and employment opportunities is hotly debated among economists. Whereas some researchers have found that minimum wage hikes lead to a rise in unemployment,^11–15 others have found that they enhance employment.^16–20Far less empirical attention has been paid to other effects of minimum wages, such as the potential effect on access to health care. Simon and Kaestner²¹ used data from the 1979–2000 Current Population Survey (CPS) to investigate the association between the minimum wage and workers'' receipt of fringe benefits such as health insurance and pensions. They found that increased minimum wages were associated with an increased probability of receiving health insurance and pensions, but concluded that the absence of a consistent differential effect between low- and high-skilled workers suggested “that the minimum wage had no causal effect on low-wage workers'' fringe benefit receipt.”^21(p52)Simon and Kaestner''s study appears to be the only one published to directly examine the association between minimum wages and provision of employer-sponsored health insurance, and to our knowledge none has examined other measures of health care access. We sought to extend this line of empirical research into the effects of the minimum wage and fill the gap in the literature by building on prior works in several important ways.First, we employed more recent data that capitalize on the proliferation of state-level minimum wage laws between 2000 and 2007 to capture greater variance in minimum wage rates throughout the United States. Second, whereas earlier work focused on receipt of health insurance as a fringe benefit, we focused our analysis more directly on access to care by examining both a broader measure of health insurance coverage and an additional direct measure of access: reporting cost-related barriers to receiving needed medical care. Finally, we included more comprehensive sets of individual and state-level covariates in addition to state and regional fixed effects and time trends.Using 12 years of data from the Behavioral Risk Factor Surveillance System (BRFSS)²² and several additional sources, we examined associations between state-level minimum wage policies and respondent-level indicators of access to health care. Given the competing hypotheses about the potential effects of minimum wage policy, this analysis provides unique empirical evidence on an important policy whose theoretical effects have been hotly contested.     

The association between health insurance coverage and diabetes care; data from the 2000 Behavioral Risk Factor Surveillance System

OBJECTIVE: To describe the association between type of health insurance coverage and the quality of care provided to individuals with diabetes in the United States. DATA SOURCE: The 2000 Behavioral Risk Factor Surveillance System. STUDY DESIGN: Our study cohort included individuals who reported a diagnosis of diabetes (n=11,647). We performed bivariate and multivariate logistic regression analyses by age greater or less than 65 years to examine the association of health insurance coverage with diabetes-specific quality of care measures, controlling for the effects of race/ethnicity, annual income, gender, education, and insulin use. PRINCIPAL FINDINGS: Most individuals with diabetes are covered by private insurance (39 percent) or Medicare (44 percent). Among persons under the age of 65 years, 11 percent were uninsured. The uninsured were more likely to be African American or Hispanic and report low incomes. The uninsured were less likely to report annual dilated eye exams, foot examinations, or hemoglobin A1c (HbA1c) tests and less likely to perform daily blood glucose monitoring than those with private health insurance. We found few differences in quality indicators between Medicare, Medicaid, or the Department of Veterans Affairs (VA) as compared with private insurance coverage. Persons who received care through the VA were more likely to report taking a diabetes education class and HbA1c testing than those covered by private insurance. CONCLUSIONS: Uninsured adults with diabetes are predominantly minority and low income and receive fewer preventive services than individuals with health insurance. Among the insured, different types of health insurance coverage appear to provide similar levels of care, except for higher rates of diabetes education and HbA1c testing at the VA.     

State smoking prevalence estimates: a comparison of the Behavioral Risk Factor Surveillance System and current population surveys.

OBJECTIVES: This study examined whether there are systematic differences between the Behavioral Risk Factor Surveillance System (BRFSS) and the Current Population Survey (CPS) for state cigarette smoking prevalence estimates. METHODS: BRFSS telephone survey estimates were compared with estimates from the US Census CPS tobacco-use supplements (the CPS sample frame includes persons in households without telephones). Weighted overall and sex- and race-specific BRFSS and CPS state estimates of adults smoking were analyzed for 1985, 1989, and 1992/1993. RESULTS: Overall estimates of smoking prevalence from the BRFSS were slightly lower than estimates from CPS (median difference: -2.0 percentage points in 1985, -0.7 in 1989, and -1.9 in 1992/1993; P < .05 for all comparisons), but there was variation among states. Differences between BRFSS and CPS estimates were larger among men than among women and larger among Blacks than among Hispanics or Whites; for most states, these differences were not significant. CONCLUSIONS: The BRFSS generally provides state estimates of smoking prevalence similar to those obtained from CPS, and these are appropriate for ongoing state surveillance of smoking prevalence.     

An economic analysis of adult obesity: results from the Behavioral Risk Factor Surveillance System

This paper examines the factors that may be responsible for the 50% increase in the number of obese adults in the US since the late 1970s. We employ the 1984-1999 Behavioral Risk Factor Surveillance System, augmented with state level measures pertaining to the per capita number of fast-food and full-service restaurants, the prices of a meal in each type of restaurant, food consumed at home, cigarettes, and alcohol, and clean indoor air laws. Our main results are that these variables have the expected effects on obesity and explain a substantial amount of its trend.     

Disability,Gender and Intimate Partner Violence: Relationships from the Behavioral Risk Factor Surveillance System

Research on women with disabilities has found that the most common perpetrators of violence were current or former intimate partners (Young et al. Arch. Phys. Med. Rehabil. 78, S34–S38, 1997; Riddington, Beating the “odds”: Violence and Women with Disabilities (Position Paper 2). 1989). This article examines intimate partner sexual and physical abuse experienced by women with disabilities compared to women without disabilities and men with and without disabilities through chi square analysis and regression analysis using data from the 2005 Behavioral Risk Factor Surveillance System (BRFSS). Results show that women with disabilities experienced almost twice the rate of all forms of abuse compared to the other populations. Variables increasing the likelihood of abuse include being female, disabled, not employed, uncoupled and younger age. Implications for future research, screening and intervention for rehabilitation professionals are discussed.     

Health Disparities by Sexual Orientation: Results and Implications from the Behavioral Risk Factor Surveillance System

Until recently, population-based data for monitoring sexual minority health have been limited, making it difficult to document and address disparities by sexual orientation. The primary objective of this study was to examine differences by sexual orientation in an array of health outcomes and health risk factors using one of the nation’s largest health surveys. Data for this study came from 8290 adults who identified as lesbian, gay, or bisexual (LGB) and 300,256 adults who identified as heterosexual in the 2014–2015 Behavioral Risk Factor Surveillance System (BRFSS). Logistic regression models were used to compare physical and mental health outcomes, health condition diagnoses, and health risk factors by sexual orientation, controlling for demographic and socioeconomic status. Controlling for sociodemographic characteristics, gay and bisexual men reported higher odds of frequent mental distress [odds ratio (OR) 1.71, P?=?0.001; OR 2.33, P?<?0.001] and depression (OR 2.91, P?<?0.001; OR 2.41, P?<?0.001), compared with heterosexual men. Lesbian and bisexual women had higher odds of frequent mental distress (OR 1.53, P?<?0.001; OR 2.08, P?<?0.001) and depression (OR 1.93, P?<?0.01; OR 3.15, P?<?0.001), compared to heterosexual women. Sexual minorities also faced higher odds of poor physical health, activity limitations, chronic conditions, obesity, smoking, and binge drinking, although these risks differed by sexual orientation and gender. This study adds to the mounting evidence of health disparities by sexual orientation. Community health practitioners and policymakers should continue to collect data on sexual orientation in order to identify and address root causes of sexual orientation-based disparities, particularly at the community-level.