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1.  Association of Socioeconomic Position With Sensory Impairment Among US Working-Aged Adults 
American journal of public health  2015;105(6):1262-1268.
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.
doi:10.2105/AJPH.2014.302475
PMCID: PMC4431072  PMID: 25880957
2.  Changes in Disparity in County-Level Diagnosed Diabetes Prevalence and Incidence in the United States, between 2004 and 2012 
PLoS ONE  2016;11(8):e0159876.
Background
In recent decades, the United States experienced increasing prevalence and incidence of diabetes, accompanied by large disparities in county-level diabetes prevalence and incidence. However, whether these disparities are widening, narrowing, or staying the same has not been studied. We examined changes in disparity among U.S. counties in diagnosed diabetes prevalence and incidence between 2004 and 2012.
Methods
We used 2004 and 2012 county-level diabetes (type 1 and type 2) prevalence and incidence data, along with demographic, socio-economic, and risk factor data from various sources. To determine whether disparities widened or narrowed over the time period, we used a regression-based β-convergence approach, accounting for spatial autocorrelation. We calculated diabetes prevalence/incidence percentage point (ppt) changes between 2004 and 2012 and modeled these changes as a function of baseline diabetes prevalence/incidence in 2004. Covariates included county-level demographic and, socio-economic data, and known type 2 diabetes risk factors (obesity and leisure-time physical inactivity).
Results
For each county-level ppt increase in diabetes prevalence in 2004 there was an annual average increase of 0.02 ppt (p<0.001) in diabetes prevalence between 2004 and 2012, indicating a widening of disparities. However, after accounting for covariates, diabetes prevalence decreased by an annual average of 0.04 ppt (p<0.001). In contrast, changes in diabetes incidence decreased by an average of 0.04 ppt (unadjusted) and 0.09 ppt (adjusted) for each ppt increase in diabetes incidence in 2004, indicating a narrowing of county-level disparities.
Conclusions
County-level disparities in diagnosed diabetes prevalence in the United States widened between 2004 and 2012, while disparities in incidence narrowed. Accounting for demographic and, socio-economic characteristics and risk factors for type 2 diabetes narrowed the disparities, suggesting that these factors are strongly associated with changes in disparities. Public health interventions that target modifiable risk factors, such as obesity and physical inactivity, in high burden counties might further reduce disparities in incidence and, over time, in prevalence.
doi:10.1371/journal.pone.0159876
PMCID: PMC4972249  PMID: 27487006
3.  The Relationship Between County-Level Contextual Characteristics and Use of Diabetes Care Services 
Objectives
To examine the relationship between county-level measures of social determinants and use of preventive care among US adults with diagnosed diabetes. To inform future diabetes prevention strategies.
Methods
Data are from the Behavioral Risk Factor Surveillance System (BRFSS) 2004 and 2005 surveys, the National Diabetes Surveillance System, and the Area Resource File. Use of diabetes care services was defined by self-reported receipt of 7 preventive care services. Our study sample included 46 806 respondents with self-reported diagnosed diabetes. Multilevel models were run to assess the association between county-level characteristics and receipt of each of the 7 preventive diabetes care service after controlling for characteristics of individuals. Results were considered significant if P < .05.
Results
Controlling for individual-level characteristics, our analyses showed that 7 of the 8 county-level factors examined were significantly associated with use of 1 or more preventive diabetes care services. For example, people with diabetes living in a county with a high uninsurance rate were less likely to have an influenza vaccination, visit a doctor for diabetes care, have an A1c test, or a foot examination; people with diabetes living in a county with a high physician density were more likely to have an A1c test, foot examination, or an eye examination; and people with diabetes living in a county with more people with less than high-school education were less likely to have influenza vaccination, pneumococcal vaccination, or self-care education (all P < .05).
Conclusions
Many of the county-level factors examined in this study were found to be significantly associated with use of preventive diabetes care services. County policy makers may need to consider local circumstances to address the disparities in use of these services.
doi:10.1097/PHH.0b013e31829bfa60
PMCID: PMC4834855  PMID: 23963254
Andersen’s model; multilevel models; preventive diabetes care; social determinants
4.  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.
doi:10.1016/j.amepre.2014.10.004
PMCID: PMC4618492  PMID: 25601724
5.  Small area variation in diabetes prevalence in Puerto Rico 
Objective
To estimate the 2009 prevalence of diagnosed diabetes in Puerto Rico among adults ≥ 20 years of age in order to gain a better understanding of its geographic distribution so that policymakers can more efficiently target prevention and control programs.
Methods
A Bayesian multilevel model was fitted to the combined 2008–2010 Behavioral Risk Factor Surveillance System and 2009 United States Census data to estimate diabetes prevalence for each of the 78 municipios (counties) in Puerto Rico.
Results
The mean unadjusted estimate for all counties was 14.3% (range by county, 9.9%–18.0%). The average width of the confidence intervals was 6.2%. Adjusted and unadjusted estimates differed little.
Conclusions
These 78 county estimates are higher on average and showed less variability (i.e., had a smaller range) than the previously published estimates of the 2008 diabetes prevalence for all United States counties (mean, 9.9%; range, 3.0%–18.2%).
PMCID: PMC4537060  PMID: 23939364
Diabetes mellitus; prevalence; public policy; Puerto Rico
6.  Socioeconomic Status and Mortality 
Diabetes Care  2012;36(1):49-55.
OBJECTIVE
Although several studies have examined the association between socioeconomic status (SES) and mortality in the general population, few have investigated this relationship among people with diabetes. This study sought to determine how risk of mortality associated with measures of SES among adults with diagnosed diabetes is mitigated by association with demographics, comorbidities, diabetes treatment, psychological distress, or health care access and utilization.
RESEARCH DESIGN AND METHODS
The study included 6,177 adults aged 25 years or older with diagnosed diabetes who participated in the National Health Interview Surveys (1997–2003) linked to mortality data (follow-up through 2006). SES was measured by education attained, financial wealth (either stocks/dividends or home ownership), and income-to-poverty ratio.
RESULTS
In unadjusted analysis, risk of death was significantly greater for people with lower levels of education and income-to-poverty ratio than for those at the highest levels. After adjusting for demographics, comorbidities, diabetes treatment and duration, health care access, and psychological distress variables, the association with greater risk of death remained significant only for people with the lowest level of education (relative hazard 1.52 [95% CI 1.04–2.23]). After multivariate adjustment, the risk of death was significantly greater for people without certain measures of financial wealth (e.g., stocks, home ownership) (1.56 [1.07–2.27]) than for those with them.
CONCLUSIONS
The findings suggest that after adjustments for demographics, health care access, and psychological distress, the level of education attained and financial wealth remain strong predictors of mortality risk among adults with diabetes.
doi:10.2337/dc11-1864
PMCID: PMC3526248  PMID: 22933434
7.  Access to Health Care and Control of ABCs of Diabetes 
Diabetes Care  2012;35(7):1566-1571.
OBJECTIVE
To examine the relationship between access to health care and diabetes control.
RESEARCH DESIGN AND METHODS
Using data from the National Health and Nutrition Examination Survey, 1999–2008, we identified 1,221 U.S. adults (age 18–64 years) with self-reported diabetes. Access was measured by current health insurance coverage, number of times health care was received over the past year, and routine place to go for health care. Diabetes control measures included the proportion of people with A1C >9%, blood pressure ≥140/90 mmHg, and non-HDL cholesterol ≥130 mg/dL.
RESULTS
An estimated 16.0% of known diabetic adults were uninsured. Diabetes control profiles were worse among uninsured than among insured persons (A1C >9% [34.1 vs. 16.5%, P = 0.002], blood pressure ≥140/90 mmHg [31.8 vs. 22.8%, P < 0.05], and non-HDL cholesterol ≥130 mg/dL [67.1 vs. 65.4%, P = 0.7]). Compared with insured persons, uninsured persons were more likely to have A1C >9% (multivariate-adjusted odds ratio 2.4 [95% CI 1.2–4.7]). Compared with those who reported four or more health care visits in the past year, those who reported no health care visits were more likely to have A1C >9% (5.5 [1.2–26.3]) and blood pressure ≥140/90 mmHg (1.9 [1.1–3.4]).
CONCLUSIONS
In people with diabetes, lack of health care coverage is associated with poor glycemic control. In addition, low use of health care service is associated with poor glucose and blood pressure control.
doi:10.2337/dc12-0081
PMCID: PMC3379598  PMID: 22522664
8.  Household Income and Cardiovascular Disease Risks in U.S. Children and Young Adults 
Diabetes Care  2011;34(9):1998-2004.
OBJECTIVE
To assess the cardiovascular risk profile of youths across socioeconomic groups in the U.S.
RESEARCH DESIGN AND METHODS
Analysis of 1999–2008 National Health and Nutrition Examination Surveys (NHANES) including 16,085 nonpregnant 6- to 24-year-olds to estimate race/ethnicity-adjusted prevalence of obesity, central obesity, sedentary behaviors, tobacco exposure, elevated systolic blood pressure, glycated hemoglobin, non-HDL cholesterol (non–HDL-C), and high-sensitivity C-reactive protein according to age-group, sex, and poverty-income ratio (PIR) tertiles.
RESULTS
Among boys aged 6–11 years, 19.9% in the lowest PIR tertile were obese and 30.0% were centrally obese compared with 13.2 and 21.6%, respectively, in the highest-income tertile households (Pobesity < 0.05 and Pcentral obesity < 0.01). Boys aged 12–17 years in lowest-income households were more likely than their wealthiest family peers to be obese (20.6 vs. 15.6%, P < 0.05), sedentary (14.8 vs. 9.3%, P < 0.05), and exposed to tobacco (19.0 vs. 6.5%, P < 0.01). Compared with girls aged 12–17 years in highest-income households, lowest-income household girls had higher prevalence of obesity (17.9 vs. 13.1%, P < 0.05), central obesity (41.5 vs. 29.2%, P < 0.01), sedentary behaviors (20.4 vs. 9.4%, P < 0.01), and tobacco exposure (14.1 vs. 5.9%, P < 0.01). Apart from higher prevalence of elevated non–HDL-C among low-income women aged 18–24 years (23.4 vs. 15.8%, P < 0.05), no other cardiovascular disease risk factor prevalence differences were observed between lowest- and highest-income background young adults.
CONCLUSIONS
Independent of race/ethnicity, 6- to 17-year-olds from low-income families have higher prevalence of obesity, central obesity, sedentary behavior, and tobacco exposure. Multifaceted cardiovascular health promotion policies are needed to reduce health disparities between income groups.
doi:10.2337/dc11-0792
PMCID: PMC3161277  PMID: 21868776
9.  Evaluation of risk equations for prediction of short-term coronary heart disease events in patients with long-standing type 2 diabetes: the Translating Research into Action for Diabetes (TRIAD) study 
Background
To evaluate the U.K. Prospective Diabetes Study (UKPDS) and Framingham risk equations for predicting short-term risk of coronary heart disease (CHD) events among adults with long-standing type 2 diabetes, including those with and without preexisting CHD.
Methods
Prospective cohort of U.S. managed care enrollees aged ≥ 18 years and mean diabetes duration of more than 10 years, participating in the Translating Research into Action for Diabetes (TRIAD) study, was followed for the first occurrence of CHD events from 2000 to 2003. The UKPDS and Framingham risk equations were evaluated for discriminating power and calibration.
Results
A total of 8303 TRIAD participants, were identified to evaluate the UKPDS (n = 5914, 120 events), Framingham-initial (n = 5914, 218 events) and Framingham-secondary (n = 2389, 374 events) risk equations, according to their prior CHD history. All of these equations exhibited low discriminating power with Harrell’s c-index <0.65. All except the Framingham-initial equation for women and the Framingham-secondary equation for men had low levels of calibration. After adjsusting for the average values of predictors and event rates in the TRIAD population, the calibration of these equations greatly improved.
Conclusions
The UKPDS and Framingham risk equations may be inappropriate for predicting the short-term risk of CHD events in patients with long-standing type 2 diabetes, partly due to changes in medications used by patients with diabetes and other improvements in clinical care since the Frmaingham and UKPDS studies were conducted. Refinement of these equations to reflect contemporary CHD profiles, diagnostics and therapies are needed to provide reliable risk estimates to inform effective treatment.
doi:10.1186/1472-6823-12-12
PMCID: PMC3433369  PMID: 22776317
10.  Competing Demands for Time and Self-Care Behaviors, Processes of Care, and Intermediate Outcomes Among People With Diabetes 
Diabetes Care  2011;34(5):1180-1182.
OBJECTIVE
To determine whether competing demands for time affect diabetes self-care behaviors, processes of care, and intermediate outcomes.
RESEARCH DESIGN AND METHODS
We used survey and medical record data from 5,478 participants in Translating Research Into Action for Diabetes (TRIAD) and hierarchical regression models to examine the cross-sectional associations between competing demands for time and diabetes outcomes, including self-management, processes of care, and intermediate health outcomes.
RESULTS
Fifty-two percent of participants reported no competing demands, 7% reported caregiving responsibilities only, 36% reported employment responsibilities only, and 6% reported both caregiving and employment responsibilities. For both women and men, employment responsibilities (with or without caregiving responsibilities) were associated with lower rates of diabetes self-care behaviors, worse processes of care, and, in men, worse HbA1c.
CONCLUSIONS
Accommodations for competing demands for time may promote self-management and improve the processes and outcomes of care for employed adults with diabetes.
doi:10.2337/dc10-2038
PMCID: PMC3114509  PMID: 21464464
11.  Association Between Iron Deficiency and A1C Levels Among Adults Without Diabetes in the National Health and Nutrition Examination Survey, 1999–2006 
Diabetes Care  2010;33(4):780-785.
OBJECTIVE
Iron deficiency has been reported to elevate A1C levels apart from glycemia. We examined the influence of iron deficiency on A1C distribution among adults without diabetes.
RESEARCH DESIGN AND METHODS
Participants included adults without self-reported diabetes or chronic kidney disease in the National Health and Nutrition Examination Survey 1999–2006 who were aged ≥18 years of age and had complete blood counts, iron studies, and A1C levels. Iron deficiency was defined as at least two abnormalities including free erythrocyte protoporphyrin >70 μg/dl erythrocytes, transferrin saturation <16%, or serum ferritin ≤15 μg/l. Anemia was defined as hemoglobin <13.5 g/dl in men and <12.0 g/dl in women.
RESULTS
Among women (n = 6,666), 13.7% had iron deficiency and 4.0% had iron deficiency anemia. Whereas 316 women with iron deficiency had A1C ≥5.5%, only 32 women with iron deficiency had A1C ≥6.5%. Among men (n = 3,869), only 13 had iron deficiency and A1C ≥5.5%, and only 1 had iron deficiency and A1C ≥6.5%. Among women, iron deficiency was associated with a greater odds of A1C ≥5.5% (odds ratio 1.39 [95% CI 1.11–1.73]) after adjustment for age, race/ethnicity, and waist circumference but not with a greater odds of A1C ≥6.5% (0.79 [0.33–1.85]).
CONCLUSIONS
Iron deficiency is common among women and is associated with shifts in A1C distribution from <5.5 to ≥5.5%. Further research is needed to examine whether iron deficiency is associated with shifts at higher A1C levels.
doi:10.2337/dc09-0836
PMCID: PMC2845027  PMID: 20067959
12.  Does frank diabetes in first-degree relatives of a pregnant woman affect the likelihood of her developing gestational diabetes mellitus or non-gestational diabetes? 
Objective
To examine the associations between patterns of family histories of diabetes and a history of gestational diabetes (hGDM).
Study Design
Parous women participating in the Third National Health and Nutrition Examination Survey (n=4566) were classified as having hGDM only, diagnosed diabetes, or neither. Family history of diabetes was categorized as: maternal-only, paternal-only, biparental, and sibling-only. The covariate-adjusted prevalence and odds of having hGDM were estimated.
Results
Compared to women without a family history of diabetes, women with a maternal history of diabetes (odds ratio 3.0, 95% CI 1.2-7.3), paternal history of diabetes (odds ratio 3.3, 95% CI 1.1-10.2), or a sibling history of diabetes (odds ratio 7.1, 95% CI 1.6-30.9) had greater odds of hGDM, after adjustment for age and race/ethnicity.
Conclusions
Women with a sibling history of diabetes were more likely to have hGDM than women with other family history patterns.
doi:10.1016/j.ajog.2009.06.069
PMCID: PMC2789883  PMID: 19691951
gestational diabetes; family history; sibling
13.  Cardiovascular Disease Risk Profiles in Women with Histories of Gestational Diabetes but Without Current Diabetes 
Obstetrics and gynecology  2008;112(4):875-883.
Objective
To compare the cardiovascular disease risk factor profiles of parous women with a history of gestational diabetes who had not developed diabetes, parous women with diagnosed diabetes, and parous women with neither condition.
Methods
We conducted cross-sectional analyses of 4,631 parous women who were not currently pregnant in the Third National Health and Nutrition Examination Survey (1988-1994). Women were classified by self-report as having a history of gestational diabetes who were not currently diabetic (n=85), diagnosed diabetics (n=218), or as having neither condition (n=4,328). We compared these groups with respect to cholesterol subtypes, blood pressure, uric acid, microalbuminuria, insulin, and glucose, and clustering of risk factors, before and after adjustment for demographic and behavioral factors and central obesity.
Results
In unadjusted comparisons, women who had a history of gestational diabetes who were not currently diabetics had a more favorable or similar risk factor profile compared to unaffected women, with two exceptions: greater levels of mean fasting glucose (94.0 mg/dl vs. 106.8 mg/dl, p<0.001) and mean fasting insulin (10.2 IU/l vs. 14.0 IU/l, p<0.001). These patterns were attenuated after adjustment for demographic factors and waist circumference, but remained significant for fasting glucose and the ratio of urine microalbumin/creatinine. Parous women with diagnosed diabetes had significantly worse cardiovascular disease risk profiles than unaffected women before and after adjustment.
Conclusions
Women who had a history of gestational diabetes who were not currently diabetics have a similar cardiovascular disease risk profile to unaffected women, with the exception of insulin and glucose levels.
doi:10.1097/AOG.0b013e31818638b5
PMCID: PMC2610423  PMID: 18827131
14.  The Missed Patient With Diabetes 
Diabetes Care  2008;31(9):1748-1753.
OBJECTIVE—This study examined the association between access to health care and three classifications of diabetes status: diagnosed, undiagnosed, and no diabetes.
RESEARCH DESIGN AND METHODS—Using data from the 1999–2004 National Health and Nutrition Examination Survey, we identified 110 “missed patients” (fasting plasma glucose >125 mg/dl but without diagnoses of diabetes), 704 patients with diagnosed diabetes, and 4,782 people without diabetes among adults aged 18–64 years. The population percentage undetected among adults with diabetes and the odds ratio of being undetected among adults who reported not having diabetes were compared between groups based on their access to health care.
RESULTS—Among those with diabetes, the percentages having undetected diabetes were 42.2% (95% CI 36.7–47.7) among the uninsured, 25.9% (22.9–28.9) among the insured, 49.3% (43.0–55.6) for those uninsured >1 year, 38.7% (29.2–48.2) for those uninsured ≤1 year, and 24.5% (21.7–27.3) for those continuously insured over the past year. Type of insurance, number of times receiving health care in the past year, and routine patterns of health care utilization were also associated with undetected diabetes. Multivariate adjustment indicated that having undetected diabetes was associated with being uninsured (odds ratio 1.7 [95% CI 1.0–2.9]) and with being uninsured >1 year (2.6 [1.4–5.0]).
CONCLUSIONS—Limited access to health care, especially being uninsured and going without insurance for a long period, was significantly associated with being a “missed patient” with diabetes. Efforts to increase detection of diabetes may need to address issues of access to care.
doi:10.2337/dc08-0572
PMCID: PMC2518339  PMID: 18753665
15.  Inflammation Among Women With a History of Gestational Diabetes Mellitus and Diagnosed Diabetes in the Third National Health and Nutrition Examination Survey  
Diabetes Care  2008;31(7):1386-1388.
OBJECTIVE—We compared inflammatory markers among women with a history of gestational diabetes mellitus (hGDM), women with diagnosed diabetes, and unaffected women in a population-based sample.
RESEARCH DESIGN AND METHODS—We conducted cross-sectional analyses of 6,346 nonpregnant women in the Third National Health and Nutrition Examination Survey (1988–1994). Women were classified as having hGDM (n = 87), diagnosed diabetes (n = 244), or neither condition (n = 6,015). Inflammatory markers included ferritin, leukocyte count, and C-reactive protein levels.
RESULTS—After adjustment, women with diagnosed diabetes had the most marked differences in inflammatory markers compared with unaffected women. Differences between unaffected women and women with hGDM were minimal.
CONCLUSIONS—Women with diagnosed diabetes have less favorable inflammation profiles than unaffected women and greater ferritin levels than women with hGDM. After adjustment, women with hGDM who have not developed diagnosed diabetes have inflammation profiles similar to those of unaffected women.
doi:10.2337/dc07-2362
PMCID: PMC2453639  PMID: 18375415
16.  Correlates of Bone Mineral Density among Postmenopausal Women of African Caribbean Ancestry: Tobago Women’s Health Study 
Bone  2008;43(1):156-161.
Population dynamics predict a drastic growth in the number of older minority women, and resultant increases in the number of fractures. Low bone mineral density (BMD) is an important risk factor for fracture. Many studies have identified the lifestyle and health related factors that correlate with BMD in Whites. Few studies have focused on non-Whites. The objective of the current analyses is to examine the lifestyle, anthropometric and health related factors that are correlated with BMD in a population based cohort of Caribbean women of West African ancestry. We enrolled 340 postmenopausal women residing on the Caribbean Island of Tobago. Participants completed a questionnaire and had anthropometric measures taken. Hip BMD was measured by DXA. We estimated volumetric BMD by calculating bone mineral apparent density (BMAD). BMD was 10% and 20% higher across all age groups in Tobagonian women compared to US non-Hispanic Black and White women, respectively. In multiple linear regression models, 35–36% of the variability in femoral neck and total hip BMD respectively was predicted. Each 16 kilogram (one standard deviation (SD)) increase in weight was associated with 7% higher BMD; and weight explained over 10% of the variability of BMD. Each eight year (1 SD) increase in age was associated with 6% lower BMD. Current use of both thiazide diuretics and oral hypoglycemic medication were associated with 4–5% higher BMD. For femoral neck BMAD, 26% of the variability was explained by a multiple linear regression model. Current statin use was associated with 5% higher BMAD and a history of breast feeding or coronary heart disease were associated with 1–1.5% of higher BMAD. In conclusion, African Caribbean women have the highest BMD on a population level reported to date for women. This may reflect low European admixture. Correlates of BMD among Caribbean women of West African ancestry were similar to those reported for U.S. Black and White women.
doi:10.1016/j.bone.2008.03.005
PMCID: PMC2519239  PMID: 18448413
Osteoporosis; epidemiology; African ancestry continental group; bone densitometry; women
17.  Educational disparities in health behaviors among patients with diabetes: the Translating Research Into Action for Diabetes (TRIAD) Study 
BMC Public Health  2007;7:308.
Background
Our understanding of social disparities in diabetes-related health behaviors is incomplete. The purpose of this study was to determine if having less education is associated with poorer diabetes-related health behaviors.
Methods
This observational study was based on a cohort of 8,763 survey respondents drawn from ~180,000 patients with diabetes receiving care from 68 provider groups in ten managed care health plans across the United States. Self-reported survey data included individual educational attainment ("education") and five diabetes self-care behaviors among individuals for whom the behavior would clearly be indicated: foot exams (among those with symptoms of peripheral neuropathy or a history of foot ulcers); self-monitoring of blood glucose (SMBG; among insulin users only); smoking; exercise; and certain diabetes-related health seeking behaviors (use of diabetes health education, website, or support group in last 12 months). Predicted probabilities were modeled at each level of self-reported educational attainment using hierarchical logistic regression models with random effects for clustering within health plans.
Results
Patients with less education had significantly lower predicted probabilities of being a non-smoker and engaging in regular exercise and health-seeking behaviors, while SMBG and foot self-examination did not vary by education. Extensive adjustment for patient factors revealed no discernable confounding effect on the estimates or their significance, and most education-behavior relationships were similar across sex, race and other patient characteristics. The relationship between education and smoking varied significantly across age, with a strong inverse relationship in those aged 25–44, modest for those ages 45–64, but non-evident for those over 65. Intensity of disease management by the health plan and provider communication did not alter the examined education-behavior relationships. Other measures of socioeconomic position yielded similar findings.
Conclusion
The relationship between educational attainment and health behaviors was modest in strength for most behaviors. Over the life course, the cumulative effect of reduced practice of multiple self-care behaviors among less educated patients may play an important part in shaping the social health gradient.
doi:10.1186/1471-2458-7-308
PMCID: PMC2238766  PMID: 17967177
19.  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.
PMCID: PMC2568677  PMID: 15622690

Results 1-20 (20)