Relative Contributions of Socioeconomic, Local Environmental, Psychosocial, Lifestyle/Behavioral, Biophysiological, and Ancestral Factors to Racial/Ethnic Disparities in Type 2 Diabetes.

OBJECTIVE: Racial/ethnic minorities in the U.S. have a higher prevalence of type 2 diabetes mellitus (T2DM) than white adults. While many independent risk factors for T2DM have been identified, these determinants are often viewed in isolation without considering the joint contributions of competing risk factors. The objective of this study was to assess the relative contributions of six domains of influence to racial/ethnic disparities in T2DM. RESEARCH DESIGN AND METHODS: Cross-sectional analyses were conducted using the Boston Area Community Health III Survey (2010-2012), the third wave of a population-based sample of men and women from three racial/ethnic groups (black, Hispanic, white) living in Boston, Massachusetts (N = 2,764). Prevalent diabetes was defined by self-report of T2DM, fasting glucose >125 mg/dL, or HbA1c ≥6.5%. Structural equation models were constructed to evaluate the direct effects of each conceptual domain of influence on T2DM prevalence, as well as their indirect effects on the race/ethnicity-T2DM relationship. All direct and indirect pathways were included. RESULTS: The final model indicated that 38.9% and 21.8% of the total effect of black race and Hispanic ethnicity, respectively, on T2DM prevalence was mediated by the socioeconomic, environmental, psychosocial, and lifestyle/behavioral risk scores. The largest mediating influence was the socioeconomic risk score, which explained 21.8% and 26.2% of the total effect of black race and Hispanic ethnicity, respectively. CONCLUSIONS: Our study found that socioeconomic factors had the greatest impact on explaining the excess prevalence of T2DM among racial/ethnic minorities.

Do Behavioral Risk Factors for Prediabetes and Insulin Resistance Differ across the Socioeconomic Gradient? Results from a Community-Based Epidemiologic Survey.

To examine whether behavioral risk factors associated with diabetes (diet, BMI, waist circumference, physical activity, and sleep duration) are also related to both prediabetes and insulin resistance (IR), we used data from Boston Area Community Health (BACH) Survey (2010-2012, n = 3155). Logistic and linear regression models were used to test the association of lifestyle factors with prediabetes status, insulin resistance, and prediabetes or insulin resistance. All regression models were stratified by education and income levels (to examine whether risk factors had differential effects across socioeconomic factors) and adjusted for age, gender, race/ethnicity, family history of diabetes, and smoking status. We found that large waist circumference was consistently associated with higher levels of insulin resistance (IR) and increased odds of prediabetes. While the association between large waist circumference and IR was consistent across all levels of SES (P < 0.001), the association between large waist circumference and prediabetes was only statistically significant in the highest socioeconomic strata with odds ratios of 1.68 (95% CI 1.07-2.62) and 1.88 (95% CI 1.22-2.92) for postgraduate degree and income strata, respectively. There was no association between diet, physical activity, sleep duration, and the presence of multiple risk factors and prediabetes or IR within SES strata.

Racial ethnic differences in type 2 diabetes treatment patterns and glycaemic control in the Boston Area Community Health Survey.

OBJECTIVES: Numerous studies continue to report poorer glycaemic control, and a higher incidence of diabetes-related complications among African-Americans and Hispanic-Americans as compared with non-Hispanic Caucasians with type 2 diabetes. We examined racial/ethnic differences in receipt of hypoglycaemic medications and glycaemic control in a highly insured Massachusetts community sample of individuals with type 2 diabetes. SETTING: Community-based sample from Boston, Massachusetts, USA. PARTICIPANTS: 682 patients with physician-diagnosed diabetes from the third wave of the Boston Area Community Health Survey (2010-2012). The study included approximately equal proportions of African-Americans, Hispanics and Caucasians. METHODS: We examined racial/ethnic disparities in diabetes treatment by comparing proportions of individuals on mutually exclusive diabetes treatment regimens across racial/ethnic subgroups. Using multivariable linear and logistic regression, we also examined associations between race/ethnicity and glycaemic control in the overall population, and within treatment regimens, adjusting for age, gender, income, education, health insurance, health literacy, disease duration, diet and physical activity. RESULTS: Among those treated (82%), the most commonly prescribed antidiabetic regimens were biguanides only (31%), insulin only (23%), and biguanides and insulin (16%). No overall racial/ethnic differences in treatment or glycaemic control (per cent difference for African-Americans: 6.18, 95% CI -1.00 to 13.88; for Hispanic-Americans: 1.01, 95% CI -10.42 to 12.75) were observed. Within regimens, we did not observe poorer glycaemic control for African-Americans prescribed biguanides only, insulin only or biguanides combined with insulin/sulfonylureas. However, African-Americans prescribed miscellaneous regimens had higher risk of poorer glycaemic control (per cent difference=23.37, 95% CI 7.25 to 43.33). There were no associations between glycaemic levels and Hispanic ethnicity overall, or within treatment regimens. CONCLUSIONS: Findings suggest a lack of racial/ethnic disparities in diabetes treatment patterns and glycaemic control in this highly insured Massachusetts study population. Future studies are needed to understand impacts of increasing insurance coverage on racial/ethnic disparities in treatment patterns and related outcomes.

Biogeographic ancestry is associated with higher total body adiposity among African-American females: the Boston Area Community Health Survey.

OBJECTIVES: The prevalence of obesity is disproportionately higher among African-Americans and Hispanics as compared to whites. We investigated the role of biogeographic ancestry (BGA) on adiposity and changes in adiposity in the Boston Area Community Health Survey. METHODS: We evaluated associations between BGA, assessed via Ancestry Informative Markers, and adiposity (body mass index (BMI), percent body fat (PBF), and waist-to-hip ratio (WHR)) and changes in adiposity over 7 years for BMI and WHR and 2.5 years for PBF, per 10% greater proportion of BGA using multivariable linear regression. We also examined effect-modification by demographic and socio-behavioral variables. RESULTS: We observed positive associations between West-African ancestry and cross-sectional BMI (percent difference=0.62%; 95% CI: 0.04%, 1.20%), and PBF (ß=0.35; 95% CI: 0.11, 0.58). We also observed significant effect-modification of the association between West-African ancestry and BMI by gender (p-interaction: <0.002) with a substantially greater association in women. We observed no main associations between Native-American ancestry and adiposity but observed significant effect-modification of the association with BMI by diet (p-interaction: <0.003) with inverse associations among participants with higher Healthy Eating Scores. No associations were observed between BGA and changes in adiposity over time. CONCLUSION: Findings support that West-African ancestry may contribute to high prevalence of total body adiposity among African-Americans, particularly African-American women.

The role of neighborhood characteristics in racial/ethnic disparities in type 2 diabetes: results from the Boston Area Community Health (BACH) Survey.

Racial/ethnic disparities in the prevalence of type 2 diabetes mellitus (T2DM) are well documented and until recently, research has focused almost exclusively on individual-based determinants as potential contributors to these disparities (health behaviors, biological/genetic factors, and individual-level socio-demographics). Research on the role of neighborhood characteristics in relation to racial/ethnic disparities in T2DM is very limited. Therefore, the aim of this research is to identify and estimate the contribution of specific aspects of neighborhoods that may be associated with racial/ethnic disparities in T2DM. Data from the Boston Area Community Health III Survey (N = 2764) was used in this study, which is a community-based random-sample survey of adults in Boston, Massachusetts from three racial/ethnic groups (Black, Hispanic, and White). We applied two-level random intercepts logistic regression to assess the associations between race/ethnicity, neighborhood characteristics (census tract socioeconomic status, racial composition, property and violent crime, open space, geographic proximity to grocery stores, convenience stores, and fast food, and neighborhood disorder) and prevalent T2DM (fasting glucose > 125 mg/dL, HbA1c ≥ 6.5%, or self-report of a T2DM diagnosis). Black and Hispanic participants had 2.89 times and 1.48 times the odds of T2DM as White participants, respectively. Multilevel models indicated a significant between-neighborhood variance estimate of 0.943, providing evidence of neighborhood variation. Individual demographics (race/ethnicity, age and gender) explained 22.3% of the neighborhood variability in T2DM. The addition of neighborhood-level variables to the model had very little effect on the magnitude of the racial/ethnic disparities and on the between-neighborhood variability. For example, census tract poverty explained less than 1% and 6% of the excess odds of T2DM among Blacks and Hispanics and only 1.8% of the neighborhood variance in T2DM. While the findings of this study overall suggest that neighborhood factors are not a major contributor to racial/ethnic disparities in T2DM, further research is needed including data from other geographic locations.

The contribution of biogeographical ancestry and socioeconomic status to racial/ethnic disparities in type 2 diabetes mellitus: results from the Boston Area Community Health Survey.

PURPOSE: Racial/ethnic disparities in the incidence of type 2 diabetes mellitus (T2DM) are well documented, and many researchers have proposed that biogeographical ancestry (BGA) may play a role in these disparities. However, studies examining the role of BGA on T2DM have produced mixed results to date. Therefore, the objective of this research was to quantify the contribution of BGA to racial/ethnic disparities in T2DM incidence controlling for the mediating influences of socioeconomic factors. METHODS: We analyzed data from the Boston Area Community Health Survey, a prospective cohort with approximately equal numbers of black, Hispanic, and white participants. We used 63 ancestry-informative markers to calculate the percentages of participants with West African and Native American ancestry. We used logistic regression with G-computation to analyze the contribution of BGA and socioeconomic factors to racial/ethnic disparities in T2DM incidence. RESULTS: We found that socioeconomic factors accounted for 44.7% of the total effect of T2DM attributed to black race and 54.9% of the effect attributed to Hispanic ethnicity. We found that BGA had almost no direct association with T2DM and was almost entirely mediated by self-identified race/ethnicity and socioeconomic factors. CONCLUSIONS: It is likely that nongenetic factors, specifically socioeconomic factors, account for much of the reported racial/ethnic disparities in T2DM incidence.

Cohort profile: the Boston Area Community Health (BACH) survey.

The Boston Area Community Health (BACH) Survey is a community-based, random sample, epidemiologic cohort of n = 5502 Boston (MA) residents. The baseline BACH Survey (2002-05) was designed to explore the mechanisms conferring increased health risks on minority populations with a particular focus on urologic signs/symptoms and type 2 diabetes. To this end, the cohort was designed to include adequate numbers of US racial/ethnic minorities (Black, Hispanic, White), both men and women, across a broad age of distribution. Follow-up surveys were conducted ∼5 (BACH II, 2008) and 7 (BACH III, 2010) years later, which allows for both within- and between-person comparisons over time. The BACH Survey's measures were designed to cover the following seven broad categories: socio-demographics, health care access/utilization, lifestyles, psychosocial factors, health status, physical measures and biochemical parameters. The breadth of measures has allowed BACH researchers to identify disparities and quantify contributions to social disparities in a number of health conditions including urologic conditions (e.g. nocturia, lower urinary tract symptoms, prostatitis), type 2 diabetes, obesity, bone mineral content and density, and physical function. BACH I data are available through the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repositories (www.niddkrepository.org). Further inquiries can be made through the New England Research Institutes Inc. website (www.neriscience.com/epidemiology).

Racial and socioeconomic disparities in sleep and chronic disease: results of a longitudinal investigation.

OBJECTIVES: Sleep problems appear to differentially affect racial minorities and people of lower socioeconomic status (SES). These population subgroups also have higher rates of many debilitating diseases such as obesity, type 2 diabetes mellitus (T2DM), hypertension, coronary heart disease, stroke, and mortality. Considering the presence of social disparities in sleep and chronic disease, this research aims to assess the role of sleep disparities in the incidence of obesity, T2DM, hypertension, and/or cardiovascular disease (CVD). DESIGN: The Boston Area Community Health (BACH) Survey is a population-based random-sample cohort of 5502 participants aged 30-79. Sleep restriction (< or = 5 hours/night) and restless sleep were assessed at baseline. Health status was ascertained at baseline and approximately 5 years later among 1610 men and 2535 women who completed follow-up. SETTING: Participants completed an in-person, home visit, interview at baseline (2002-2005) and follow-up (2006-2010). PARTICIPANTS: Boston, Massachusetts residents (2301 men, 3201 women) aged 30-79 years from three racial groups (1767 Black, 1876 Hispanic, 1859 White) participated in the BACH Survey. RESULTS: There were significant differences in the prevalence of sleep-related problems at baseline by both race and SES as well as significant disparities in the incidence of T2DM, high blood pressure and cardiovascular disease at follow-up. Restless sleep was associated with an increased risk of obesity, T2DM, and CVD. However, we found that sleep does not mediate social disparities in health outcomes. CONCLUSIONS: Results from the BACH Survey confirm large social disparities in health outcomes as well as large social disparities in short sleep duration and restless sleep. However, sleep did not appear to mediate the relationship between race, SES, and health disparities.

Report on endograft management of traumatic thoracic aortic transections at 30 days and 1 year from a multidisciplinary subcommittee of the Society for Vascular Surgery Outcomes Committee.

OBJECTIVES: The Society for Vascular Surgery Outcomes Committee, including ad hoc members from Society of Thoracic Surgeons, American Association of Thoracic Surgery, and Society for Interventional Radiology, collected outcomes of patients with traumatic thoracic aortic transections treated with endovascular grafts. Results through 1 year of follow-up are reported. METHODS: Data from five physician-sponsored investigational device exemption clinical trials from 2000 to 2008 were entered using standardized forms and definitions. Adverse events were reported early (≤30 days) and late (>30 days) by body system. Major adverse events included one or more of the following: death, stroke, myocardial infarction, renal failure, respiratory failure, paralysis, or bowel ischemia. RESULTS: There were 60 symptomatic patients (68.3% men; mean age, 46 years) with traumatic aortic transections, of which 97% were due to a motor vehicle accident and 3% were related to other blunt trauma. The average total injury severity score was 39, most with involvement of the chest and abdomen. The average surgical time was 125 minutes. The mean hospital length of stay was 17 days. Associated procedures for the management of nonaortic injuries occurred in 51.7%. All-cause mortality was 9.1% at 30 days and 14.4% at 1 year. One or more major adverse events occurred in 23.3% of the patients, major adverse events occurred early in 20.0% and late in 3.6%. Death accounted for 41.7% of the early and all of the late major adverse events. Early adverse events included 16.7% pulmonary, 13.3% neurologic, and 11.7% vascular complications. Late adverse events included one patient (1.8%) with pulmonary failure and one patient (1.8%) who died of an unknown cause. CONCLUSIONS: One-year results of endograft placement for the management of patients with traumatic aortic injury are acceptable. Most cases treated were due to motor vehicle accident and associated with multiple coexisting injuries. Approximately three-quarters of the deaths occurred ≤30 days, indicating the acute severity of the condition. Although the relatively low rates of adverse and major adverse events are consistent with what is anticipated in an otherwise healthy population, future device and procedural developments may facilitate improved outcomes in the future.

Report on the results of thoracic endovascular aortic repair for acute, complicated, type B aortic dissection at 30 days and 1 year from a multidisciplinary subcommittee of the Society for Vascular Surgery Outcomes Committee.

OBJECTIVE: This study analyzed 1-year outcome after thoracic endovascular aortic repair (TEVAR) in patients with complicated type B aortic dissection (cTBAoD) who had rupture or malperfusion and symptom onset ≤14 days (acute), 15 to 30 days (subacute), and 31 to 90 days (chronic) until required intervention. The main focus of this report is primarily on the acute cohort. METHODS: Clinical data were systematically collected from five physician-sponsored investigational device exemption (IDE) clinical trials between 2000 and 2008 using standardized definitions and forms. Adverse events were reported early (≤30 days) and late (>30 days) by body system. Major adverse events included death, stroke, myocardial infarction, renal failure, respiratory failure, paralysis, and bowel ischemia. RESULTS: There were 99 cTBAoD patients: 85 were acute, 11 were subacute, and 3 were chronic. Among the acute patients, 31.8% had rupture and 71.8% had malperfusion, including 55.7% lower extremity, 36.1% renal, 19.7% visceral, 8.2% other, and 3.3% spinal cord (patients may have more than one source). Rupture and malperfusion were both reported for three acute patients. Additional findings for the acute cohort included pain (76.5%), hypertension (43.5%), and bleeding (8.2%); comorbidities included hypertension (83.5%), current/past smoking history (69.8%), and diabetes (12.9%). The main focus of this analysis was the acute cohort (n = 85). Age averaged 59 years (72.9% male). Early adverse events included pulmonary (36.5%), vascular (28.2%), renal (25.9%), and neurologic (23.5%). Early major adverse events occurred in 37.6% of patients, including death (10.6%), stroke (9.4%), renal failure (9.4%), and paralysis (9.4%); late adverse events included vascular (15.8%), cardiac (10.5%), gastrointestinal (6.6%), and hemorrhage (5.3%). The point-estimate mortality rate was 10.8 (95% confidence interval [CI], 4.1-17.5) at 30 days and 29.4 (95% CI, 18.4-40.4) at 1 year, when 34 patients remained at risk. CONCLUSIONS: Emergency TEVAR for patients with cTBAoD (malperfusion or rupture) provided acceptable mortality and morbidity results out to 1 year. Manufacturers can use this 30-day mortality point-estimate of 10.8 (95% CI, 4.1-17.5) for the acute cohort to establish a performance goal for use in single-arm commercial IDE trials if the Food and Drug Administration and other regulatory bodies concur.

Diagnosis and management of depression in 3 countries: results from a clinical vignette factorial experiment.

OBJECTIVE: International differences in disease prevalence rates are often reported and thought to reflect different lifestyles, genetics, or cultural differences in care-seeking behavior. However, they may also be produced by differences among health care systems. We sought to investigate variation in the diagnosis and management of a "patient" with exactly the same symptoms indicative of depression in 3 different health care systems (Germany, the United Kingdom, and the United States). METHOD: A factorial experiment was conducted between 2001 and 2006 in which 384 randomly selected primary care physicians viewed a video vignette of a patient presenting with symptoms suggestive of depression. Under the supervision of experienced clinicians, professional actors were trained to realistically portray patients who presented with 7 symptoms of depression: sleep disturbance, decreased interest, guilt, diminished energy, impaired concentration, poor appetite, and psychomotor agitation or retardation. RESULTS: Most physicians listed depression as one of their diagnoses (89.6%), but German physicians were more likely to diagnose depression in women, while British and American physicians were more likely to diagnose depression in men (P = .0251). American physicians were almost twice as likely to prescribe an antidepressant as British physicians (P = .0241). German physicians were significantly more likely to refer the patient to a mental health professional than British or American physicians (P < .0001). German physicians wanted to see the patient in follow-up sooner than British or American physicians (P < .0001). CONCLUSIONS: Primary care physicians in different countries diagnose the exact same symptoms of depression differently depending on the patient's gender. There are also significant differences between countries in the management of a patient with symptoms suggestive of depression. International differences in prevalence rates for depression, and perhaps other diseases, may in part result from differences among health care systems in different countries.