Measuring health disparities: a comparison of absolute and relative disparities.

Monitoring national trends in disparities in different diseases could provide measures to evaluate the impact of intervention programs designed to reduce health disparities. In the US, most of the reports that track health disparities provided either relative or absolute disparities or both. However, these two measures of disparities are not only different in scale and magnitude but also the temporal changes in the magnitudes of these measures can occur in opposite directions. The trends for absolute disparity and relative disparity could move in opposite directions when the prevalence of disease in the two populations being compared either increase or decline simultaneously. If the absolute disparity increases but relative disparity declines for consecutive time periods, the absolute disparity increases but relative disparity declines for the combined time periods even with a larger increase in absolute disparity during the combined time periods. Based on random increases or decreases in prevalence of disease for two population groups, there is a higher chance the trends of these two measures could move in opposite directions when the prevalence of disease for the more advantaged group is very small relative to the prevalence of disease for the more disadvantaged group. When prevalence of disease increase or decrease simultaneously for two populations, the increase or decrease in absolute disparity has to be sufficiently large enough to warrant a corresponding increase or decrease in relative disparity. When absolute disparity declines but relative disparity increases, there is some progress in reducing disparities, but the reduction in absolute disparity is not large enough to also reduce relative disparity. When evaluating interventions to reduce health disparities using these two measures, it is important to consider both absolute and relative disparities and consider all the scenarios discussed in this paper to assess the progress towards reducing or eliminating health disparities.

Association of Socioeconomic Position With Sensory Impairment Among US Working-Aged Adults.

OBJECTIVES: We examined the relationship between socioeconomic position (SEP) and sensory impairment. METHODS: We used data from the 2007 to 2010 National Health Interview Surveys (n = 69 845 adults). Multivariable logistic regressions estimated odds ratios (ORs) for associations of educational attainment, occupational class, and poverty-income ratio with impaired vision or hearing. RESULTS: Nearly 20% of respondents reported sensory impairment. Each SEP indicator was negatively associated with sensory impairment. Adjusted odds of vision impairment were significantly higher for farm workers (OR = 1.41; 95% confidence interval [CI] = 1.01, 2.02), people with some college (OR = 1.29; 95% CI = 1.16, 1.44) or less than a high school diploma (OR = 1.36; 95% CI = 1.19, 1.55), and people from poor (OR = 1.35; 95% CI = 1.20, 1.52), low-income (OR = 1.28; 95% CI = 1.14, 1.43), or middle-income (OR = 1.19; 95% CI = 1.07, 1.31) families than for the highest-SEP group. Odds of hearing impairment were significantly higher for people with some college or less education than for those with a college degree or more; for service groups, farmers, and blue-collar workers than for white-collar workers; and for people in poor families. CONCLUSIONS: More research is needed to understand the SEP-sensory impairment association.

Secular changes in prediabetes indicators among older-adult Americans, 1999-2010.

BACKGROUND: Sex-specific prediabetes estimates are not available for older-adult Americans. PURPOSE: To estimate prediabetes prevalence, using nationally representative data, in civilian, non-institutionalized, older U.S. adults. METHODS: Data from 7,995 participants aged ≥50 years from the 1999-2010 National Health and Nutrition Examination Surveys were analyzed in 2013. Prediabetes was defined as hemoglobin A1c=5.7%-6.4% (39-47 mmol/mol [HbA1c5.7]), fasting plasma glucose of 100-125 mg/dL (impaired fasting glucose [IFG]), or both. Crude and age-adjusted prevalences for prediabetes, HbA1c5.7, and IFG by sex and three age groups were calculated, with additional adjustment for sex, age, race/ethnicity, poverty status, education, living alone, and BMI. RESULTS: From 1999 to 2005 and 2006 to 2010, prediabetes increased for adults aged 50-64 years (38.5% [95% CI=35.3, 41.8] to 45.9% [42.3, 49.5], p=0.003) and 65-74 years (41.3% [37.2, 45.5] to 47.9% [44.5, 51.3]; p=0.016), but not significantly for adults aged ≥75 years (45.1% [95% CI=41.1, 49.1] to 48.9% [95% CI=45.2, 52.6]; p>0.05). Prediabetes increased significantly for women in the two youngest age groups, and HbA1c5.7 for both sexes (except men aged ≥75 years), but IFG remained stable for both sexes. Men had higher prevalences than women for prediabetes and IFG among adults aged 50-64 years, and for IFG among adults aged ≥75 years. Across demographic subgroups, adjusted prevalence gains for both sexes were similar and most pronounced for HbA1c5.7, virtually absent for IFG, but greater for women than men for prediabetes. CONCLUSIONS: Given the large, growing prediabetes prevalence and its anticipated burden, older adults, especially women, are likely intervention targets.

Measuring access to eye care: a public health perspective.

PURPOSE: To examine the different dimensions of access to eye care from a public health perspective. METHODS: We substantively review the theoretical and empirical literature on access to eye care and summarize the major considerations in measuring access to eye care using a modified behavioral framework. RESULTS: We found that progress has been made, but some gaps still remain in measuring access to eye care. Most studies have focused on individual characteristics and use of eye care services. Only a very few studies have touched on contextual characteristics, such as demographic make-up of the area in which the patient lives, and their impact on the use of eye care services. Few studies have explored the linkage between the use of eye care services and outcomes or between the use of such services and patient satisfaction. CONCLUSIONS: To address a variety of demands from patients, providers, and policy makers, it is necessary to account for potential access and realized access measures. We need to adopt new methods in assessing the relationship between contextual characteristics and use of eye care services. Moreover, we need to better understand patients' satisfaction and their relationship with utilization and health outcomes.

Agreement between self-reports and medical records was only fair in a cross-sectional study of performance of annual eye examinations among adults with diabetes in managed care.

BACKGROUND: Despite consensus about the importance of measuring quality of diabetes care and the widespread use of self-reports and medical records to assess quality, little is known about the degree of agreement between these data sources. OBJECTIVES: To evaluate agreement between self-reported and medical record data on annual eye examinations and to identify factors associated with agreement. RESEARCH DESIGN AND SUBJECTS: Data from interviews and medical records were available for 8409 adults with diabetes who participated in the baseline round of the Translating Research Into Action for Diabetes (TRIAD) Study. MEASURES: Agreement between self-reports and medical records was evaluated as concordance and Cohen's kappa coefficient. RESULTS: Self-reports indicated a higher performance of annual dilated eye examinations than did medical records (75.9% vs. 38.8%). Concordance between the data sources was 57.9%. Agreement was only fair (kappa coefficient = 0.25; 95% confidence interval, 0.23-0.26). Nearly two-thirds (64.6%) of discordance was due to lack of evidence in the medical record to support self-reported performance of the procedure. After adjustment, agreement was most strongly related to health plan (chi = 977.9, df = 9; P < 0.0001), and remained significantly better for 3 of the 10 health plans (P < 0.00001) and for persons younger than 45 years of age (P = 0.00002). CONCLUSIONS: The low level of agreement between self-report and medical records suggests that many providers of diabetes care do not have easily available accurate information on the eye examination status of their patients.

Fruit, vegetable and fat intake in a population-based sample of African Americans.

BACKGROUND: African Americans experience high rates of obesity and other chronic diseases, which may be related, in part, to diet. However, little is known about dietary patterns in this population, particularly from population-based data sources. METHODS: A cross-sectional analysis was conducted of 2,172 African-American adults in Project DIRECT (Diabetes Interventions Reaching and Educating Communities Together). A baseline assessment was conducted using a multistaged population-based probability sample from Raleigh and Greensboro, NC. Daily fruit, vegetable and fat intake was evaluated using a modified version of the Block questionnaire, and then stratified results were analyzed by sociodemographic, health and behavior characteristics. STATA Survey commands were used to account for the complex survey design. RESULTS: Overall, a very small number of participants met national recommendations for > or = 2 servings of fruit (8%) and > or = 3 servings of vegetables (16%) per day. Many participants reported eating high-fat foods; the average daily fat intake was 86 g, and the average daily intake from saturated fat was 24 g. People with more education and higher incomes had a higher average daily fruit intake (all p < 0.05). CONCLUSIONS: The data suggest that participants' fruit, vegetable and fat intake deviated greatly from national guidelines; older people, women, participants with higher socioeconomic status and those who were physically active consumed healthier foods. These data may be useful in developing dietary and weight loss interventions for African Americans.

Health behaviors and quality of care among Latinos with diabetes in managed care.

OBJECTIVES: We evaluated whether ethnicity and language are associated with diabetes care for Latinos in managed care. METHODS: Using data from 4685 individuals in the Translating Research Into Action for Diabetes (TRIAD) Study, a multicenter study of diabetes care in managed care, we constructed multivariate regression models to compare health behaviors, processes of care, and intermediate outcomes for Whites and English- and Spanish-speaking Latinos. RESULTS: Latinos had lower rates of self-monitoring of blood glucose and worse glycemic control than did Whites, higher rates of foot self-care and dilated-eye examinations, and comparable rates of other processes and intermediate outcomes of care. CONCLUSIONS: Although self-management and quality of care are comparable for Latinos and Whites with diabetes, important ethnic disparities persist in the managed care settings studied.

Racial/ethnic differences in the healthcare experience (coverage, utilization, and satisfaction) of US adults with diabetes.

OBJECTIVE: To examine racial/ethnic differences in healthcare coverage, utilization, and satisfaction, among US adults with diabetes. DESIGN AND SETTING: We conducted a cross-sectional analysis among 9443 adults with diabetes who participated in the 1999 Behavioral Risk Factor Surveillance System (BRFSS), a telephone survey of the civilian non-institutionalized US population aged > or = 18 yrs. MAIN OUTCOME MEASURES: We compared healthcare coverage, utilization, and satisfaction across 4 race/ethnicity categories: non-Hispanic Whites (NHW), non-Hispanic Blacks (NHB), Hispanics (HSP), and others, and examined whether these factors were associated with self-rated health status. RESULTS: By self-report, more NHB (14.8%), HSP (20.7%), and members of other races (21.8%) were uninsured, compared to NHW (6.4%). Similarly, cost was a barrier to visiting a doctor for 23.9% of HSP, 19.5% of NHB, and 13.4% of members of other races; however, only 8.2% of non-Hispanic Whites reported cost as a barrier. More NHW (90.1%) and NHB (90.7) reported having had a check-up in the past year, compared to HSP (84.5%) or others (84.1%). All 3 variables exhibited significant differences by race or ethnicity (all P<.01). After adjustment for age, sex, income, education, and insulin use, the association with race/ethnicity persisted for health insurance coverage (P<.001), and for cost as a barrier (P<.003). Reporting cost as a barrier to visiting a doctor (P=.013), and rating one's overall health care as fair or poor (P=.001), were associated with poorer health status. CONCLUSIONS: These results suggest that ethnic minorities with diabetes report less healthcare coverage and more cost-related barriers to utilization, compared to non-Hispanic Whites. Persons with fair/poor health status were more likely to report cost barriers and poor satisfaction. Future research should focus on the reasons for such differences and on interventions to improve health care for minority populations.