Anne B Newman

University of Pittsburgh, Pittsburgh, Pennsylvania, United States

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Publications (700)4285.27 Total impact

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    ABSTRACT: Context: Subclinical hypothyroidism has been associated with increased risk of coronary heart disease (CHD), particularly with thyrotropin levels of 10.0 mIU/L or greater. The measurement of thyroid antibodies helps predict the progression to overt hypothyroidism, but it is unclear whether thyroid autoimmunity independently affects CHD risk. Objective: The objective of the study was to compare the CHD risk of subclinical hypothyroidism with and without thyroid peroxidase antibodies (TPOAbs). Data Sources and Study Selection: A MEDLINE and EMBASE search from 1950 to 2011 was conducted for prospective cohorts, reporting baseline thyroid function, antibodies, and CHD outcomes. Data Extraction: Individual data of 38 274 participants from six cohorts for CHD mortality, followed up for 460 333 person-years and 33 394 participants from four cohorts for CHD events. Data Synthesis: Among 38 274 adults (median age 55 y, 63% women), 1691 (4.4%) had subclinical hypothyroidism, of whom 775 (45.8%) had positive TPOAbs. During follow-up, 1436 participants died of CHD and 3285 had CHD events. Compared with euthyroid individuals, age- and gender-adjusted risks of CHD mortality in subclinical hypothyroidism were similar among individuals with and without TPOAbs [hazard ratio (HR) 1.15, 95% confidence interval (CI) 0.87-1.53 vs HR 1.26, CI 1.01-1.58, P for interaction 0.62], as were risks of CHD events (HR 1.16, CI 0.87-1.56 vs HR 1.26, CI 1.02-1.56, P for interaction = .65). Risks of CHD mortality and events increased with higher thyrotropin, but within each stratum, risks did not differ by TPOAb status. Conclusions: CHD risk associated with subclinical hypothyroidism did not differ by TPOAb status, suggesting that biomarkers of thyroid autoimmunity do not add independent prognostic information for CHD outcomes.
    Journal of Clinical Endocrinology &amp Metabolism 06/2014; · 6.31 Impact Factor
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    ABSTRACT: The plasma levels of high-density lipoprotein cholesterol (HDL) have an inverse relationship to the risks of atherosclerosis and cardiovascular disease (CVD), and have also been associated with longevity. We sought to identify novel loci for HDL that could potentially provide new insights into biological regulation of HDL metabolism in healthy-longevous subjects. We performed a genome-wide association (GWA) scan on HDL using a mixed model approach to account for family structure using kinship coefficients. A total of 4114 subjects of European descent (480 families) were genotyped at ~2.3 million SNPs and ~38 million SNPs were imputed using the 1000 Genome Cosmopolitan reference panel in MACH. We identified novel variants near-NLRP1 (17p13) associated with an increase of HDL levels at genome-wide significant level (p < 5.0E-08). Additionally, several CETP (16q21) and ZNF259-APOA5-A4-C3-A1 (11q23.3) variants associated with HDL were found, replicating those previously reported in the literature. A possible regulatory variant upstream of NLRP1 that is associated with HDL in these elderly Long Life Family Study (LLFS) subjects may also contribute to their longevity and health. Our NLRP1 intergenic SNPs show a potential regulatory function in Encyclopedia of DNA Elements (ENCODE); however, it is not clear whether they regulate NLRP1 or other more remote gene. NLRP1 plays an important role in the induction of apoptosis, and its inflammasome is critical for mediating innate immune responses. Nlrp1a (a mouse ortholog of human NLRP1) interacts with SREBP-1a (17p11) which has a fundamental role in lipid concentration and composition, and is involved in innate immune response in macrophages. The NLRP1 region is conserved in mammals, but also has evolved adaptively showing signals of positive selection in European populations that might confer an advantage. NLRP1 intergenic SNPs have also been associated with immunity/inflammasome disorders which highlights the biological importance of this chromosomal region.
    Frontiers in Genetics 06/2014; 5:159.
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    ABSTRACT: Background Unless effective preventive strategies are implemented, aging of the population will result in a significant worsening of the heart failure (HF) epidemic. Few data exist on whether baseline ECG abnormalities can refine risk prediction for HF. Methods We examined a prospective cohort of 2915 participants aged 70-79 years without preexisting HF, enrolled between April 1997-June 1998 in the Health Aging and Body Composition (Health ABC) study. Minnesota Code was used to define major and minor ECG abnormalities at baseline and at year 4 follow-up. Using Cox models, we assessed (1) the association between ECG abnormalities and incident HF and (2) the incremental value of adding ECG to the Health ABC HF Risk Score using the net reclassification index (NRI). Results At baseline, 380 participants (13.0%) had minor and 620 (21.3%) had major ECG abnormalities. During a median follow-up of 11.4 years, 485 (16.6%) participants developed incident HF. After adjusting for the Health ABC HF Risk Score variables, the hazard ratio (HR) was 1.27 (95% confidence interval [CI] 0.96-1.68) for minor and 1.99 (95% CI 1.61-2.44) for major ECG abnormalities. At year 4, 263 participants developed new and 549 had persistent abnormalities; both were associated with increased subsequent HF risk (HR = 1.94, 95% CI 1.38-2.72 for new and HR = 2.35, 95% CI 1.82-3.02 for persistent ECG abnormalities). Baseline ECG correctly reclassified 10.5% of patients with HF events, 0.8% of those without HF events and 1.4% of the overall population. The NRI across the Health ABC HF risk categories was 0.11 (95% CI 0.03-0.19). Conclusions Among older adults, baseline and new ECG abnormalities are independently associated with increased risk for HF. The contribution of ECG screening for targeted prevention of HF should be evaluated in clinical trials.
    American Heart Journal 06/2014; · 4.56 Impact Factor
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    ABSTRACT: Microvascular and macrovascular abnormalities are frequently found on noninvasive tests performed in older adults. Their prognostic implications on disability and life expectancy have not been collectively assessed.
    The Journals of Gerontology Series A Biological Sciences and Medical Sciences 05/2014; · 4.31 Impact Factor
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    ABSTRACT: Cerebral white matter hyperintensities (WMHs) are involved in the evolution of impaired mobility and executive functions. Executive functions and mobility are also associated. Thus, WMHs may impair mobility directly, by disrupting mobility-related circuits, or indirectly, by disrupting circuits responsible for executive functions. Understanding the mechanisms underlying impaired mobility in late life will increase our capacity to develop effective interventions.
    NeuroImage 05/2014; · 6.13 Impact Factor
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    ABSTRACT: Objectives To evaluate sleep–wake disturbances in sedentary community-dwelling elderly adults with functional limitations.DesignCross-sectional.SettingLifestyle Interventions and Independence in Elder (LIFE) Study.ParticipantsCommunity-dwelling persons (mean age 78.9) who spent fewer than 20 min/wk in the previous month engaged in regular physical activity and fewer than 125 min/wk of moderate physical activity, and had a Short Physical Performance Battery (SPPB) score of <10 (N = 1,635).MeasurementsMobility was evaluated according to 400-m walk time (slow gait speed defined as <0.8 m/s) and SPPB score (≤7 defined moderate to severe mobility impairment). Physical inactivity was defined according to sedentary time, as a percentage of accelerometry wear time with activity of <100 counts/min; participants in the top quartile of sedentary time were classified as having a high sedentary time. Sleep–wake disturbances were evaluated using the Insomnia Severity Index (ISI) (range 0–28; ≥8 defined insomnia), Epworth Sleepiness Scale (ESS) (range 0–24; ≥10 defined daytime drowsiness), Pittsburgh Sleep Quality Index (PSQI) (range 0–21; >5 defined poor sleep quality), and Berlin Questionnaire (high risk of sleep apnea).ResultsPrevalence rates were 43.5% for slow gait speed and 44.7% for moderate to severe mobility impairment, with 77.0% of accelerometry wear time spent as sedentary time. Prevalence rates were 33.0% for insomnia, 18.1% for daytime drowsiness, 47.8% for poor sleep quality, and 32.9% for high risk of sleep apnea. Participants with insomnia had a mean ISI score of 12.1, those with daytime drowsiness had a mean ESS score of 12.5, and those with poor sleep quality had a mean PSQI score of 9.2. In adjusted models, measures of mobility and physical inactivity were generally not associated with sleep–wake disturbances, using continuous or categorical variables.Conclusion In a large sample of sedentary community-dwelling elderly adults with functional limitations, sleep–wake disturbances were prevalent but only mildly severe and were generally not associated with mobility impairment or physical inactivity.
    Journal of the American Geriatrics Society 05/2014; · 4.22 Impact Factor
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    ABSTRACT: Step length variability (SLV) increases with age in those without overt neurologic disease, is higher in neurologic patients, is associated with falls, and predicts dementia. Whether higher SLV in older adults without neurologic disease indicates presence of neurologic abnormalities is unknown. Our objective was to identify whether SLV in older adults without overt disease is associated with findings from multimodal neuroimaging. A well-characterized cohort of 265 adults (79-90 years) was concurrently assessed by gait mat, magnetic resonance imaging with diffusion tensor, and neurological exam. Linear regression models adjusted for gait speed, demographic, health, and functional covariates assessed associations of MRI measures (grey matter volume, white matter hyperintensity volume, mean diffusivity, fractional anisotropy) with SLV. Regional distribution of associations was assessed by sparse partial least squares analyses. Higher SLV (mean: 8.4, SD: 3.3) was significantly associated with older age, slower gait speed, and poorer executive function and also with lower grey matter integrity measured by mean diffusivity (standardized beta = 0.16; p = 0.02). Associations between SLV and grey matter integrity were strongest for the hippocampus and anterior cingulate gyrus (both β = 0.18) as compared to other regions. Associations of SLV with other neuroimaging markers were not significant. Lower integrity of normal-appearing grey matter may underlie higher SLV in older adults. Our results highlighted the hippocampus and anterior cingulate gyrus, regions involved in memory and executive function. These findings support previous research indicating a role for cognitive function in motor control. Higher SLV may indicate focal neuropathology in those without diagnosed neurologic disease.
    Gait & posture 05/2014; · 2.58 Impact Factor
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    ABSTRACT: Physical activity (PA) may play a role in preserving kidney health. The purpose of this study was to determine if PA and sedentary behavior are associated with incident chronic kidney disease (CKD) and change in kidney function in older adults. The Health, Aging and Body Composition study is a prospective cohort of 3,075 well-functioning older adults. PA and television watching was measured by self-report and serum cystatin C was used to estimate glomerular filtration rate (eGFR). CKD was defined as an eGFR <60 ml/min/1.73m2. Rapid kidney function decline was defined as an annual loss in eGFR of >3ml/min/1.73m2. Discrete survival analysis was used to determine if baseline PA and television watching were related to 10-year cumulative incidence of CKD and rapid decline in kidney function. Individuals who reported watching television >3 hours/day had a higher risk of incident CKD (HR 1.34; 95% CI: 1.09, 1.65) and experiencing a rapid decline in kidney function (HR 1.26; 95% CI 1.05, 1.52) compared to individuals who watched television < 2 hours/day. PA was not related to either outcome. High levels of television watching are associated with declining kidney function; the mechanisms that underlie this association need further study.
    Journal of Physical Activity and Health 04/2014; · 1.95 Impact Factor
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    ABSTRACT: To examine the association between 6-min walk test (6 MWT) performance and all-cause mortality, coronary heart disease mortality, and incident coronary heart disease in older adults. We conducted a time-to-event analysis of 1,665 Cardiovascular Health Study participants without prevalent cardiovascular disease with a 6 MWT. During a mean follow-up of 8 years, there were 305 incident coronary heart disease events, and 504 deaths of which 100 were coronary heart disease-related deaths. The 6 MWT performance in the shortest two distance quintiles was associated with increased risk of all-cause mortality (290-338 m: hazard ratio [HR] = 1.7; 95% confidence interval [CI] = [1.2, 2.5]; <290 m: HR = 2.1; 95% CI = [1.4, 3.0]). The adjusted risk of coronary heart disease mortality incident events among those with a 6 MWT < 290 m was not significant. Performance on the 6 MWT is independently associated with all-cause mortality and is of prognostic utility in community-dwelling older adults.
    Journal of Aging and Health 04/2014; · 1.56 Impact Factor
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    ABSTRACT: Objectives. We examined a population-wide program, Pennsylvania's Healthy Steps for Older Adults (HSOA), designed to reduce the incidence of falls among older adults. Older adults completing HSOA are screened and educated regarding fall risk, and those identified as being at high risk are referred to primary care providers and home safety resources. Methods. From 2010 to 2011, older adults who completed HSOA at various senior center sites (n = 814) and a comparison group of older adults from the same sites who did not complete the program (n = 1019) were recruited and followed monthly. Although participants were not randomly allocated to study conditions, the 2 groups did not differ in fall risk at baseline or attrition. We used a telephone interactive voice response system to ascertain the number of falls that occurred each month. Results. In multivariate models, adjusted fall incidence rate ratios (IRRs) were lower in the HSOA group than in the comparison group for both total (IRR = 0.83; 95% confidence interval [CI] = 0.72, 0.96) and activity-adjusted (IRR = 0.81; 95% CI = 0.70, 0.93) months of follow-up. Conclusions. Use of existing aging services in primary prevention of falls is feasible, resulting in a 17% reduction in our sample in the rate of falls over the follow-up period. (Am J Public Health. Published online ahead of print March 13, 2014: e1-e8. doi:10.2105/AJPH.2013.301829).
    American Journal of Public Health 03/2014; · 3.93 Impact Factor
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    ABSTRACT: The contribution of heart failure (HF) unrelated to vascular disease to the overall HF burden in older adults is not well characterized. This was investigated in this study. We assessed HF incidence and outcomes in 2895 participants of the Health ABC Study (age 74 ± 3 years, 48.4% men, 41.4% black) in relation to vascular disease (coronary, peripheral, or cerebrovascular disease) either present at baseline or developed prior to HF. During 11.4 years follow-up, 493 participants developed HF; 134 (27.2%) in participants without any prior vascular disease and 177 (36.8%) without coronary disease. Both baseline [hazard ratio (HR) 2.4, 95% confidence interval (CI) 1.9-2.8] and incident vascular disease (HR 4.3, 95% CI 3.6-5.2) were associated with HF. During a median follow-up of 2.1 years after HF onset, 67.5% participants died. Annual mortality after HF development was 21.3% in those with compared with 24.6% in those without vascular disease (HR 1.11, 95% CI 0.87-1.43; P = 0.399). There were 658 all-cause (436.3/1000 person-years) and 523 HF-related (346.4/1000 person-years) hospitalizations after HF development. There was no significant difference in hospitalizations between those with and without vascular disease [rate ratio (RR) 1.04, 95% CI 0.86-1.24 for all-cause, and RR 0.84 95% CI 0.69-1.02 for HF hospitalization]. HF with preserved EF was more common in participants without vascular disease (67.0% vs. 55.0%, P = 0.040). A significant proportion of HF in older adults develops without prior vascular disease. Outcomes for these patients are poor compared with those with preceding vascular disease. These data suggest the need for more targeted HF prediction and prevention efforts.
    European Journal of Heart Failure 02/2014; · 6.58 Impact Factor
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    ABSTRACT: Obesity is a risk factor for disability, but risk of specific adipose depots is not completely understood. We investigated associations between mobility limitation, performance, and the following adipose measures: body mass index (BMI) and areas and densities of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and intermuscular adipose tissue (IMAT) in older adults. This was a prospective population-based study of men (n = 1459) and women (n = 1552) initially aged 70-79 y and free from mobility limitation. BMI was determined from measured height and weight. Adipose tissue area and density in Hounsfield units were measured in the thigh and abdomen by using computed tomography. Mobility limitation was defined as 2 consecutive reports of difficulty walking one-quarter mile or climbing 10 steps during semiannual assessments over 13 y. Poor performance was defined as a gait speed <1 m/s after 9 y of follow-up (n = 1542). In models adjusted for disability risk factors, BMI, and areas of VAT, abdominal SAT, and IMAT were positively associated with mobility limitation in men and women. In women, thigh SAT area was positively associated with mobility limitation risk, whereas VAT density was inversely associated. Associations were similar for poor performance. BMI and thigh IMAT area (independent of BMI) were particularly strong indicators of incident mobility limitation and poor performance. For example, in women, the HR (95% CI) and OR (95% CI) associated with an SD increment in BMI for mobility limitation and poor performance were 1.31 (1.21, 1.42) and 1.41 (1.13, 1.76), respectively. In men, the HR (95% CI) and OR (95% CI) associated with an SD increment in thigh IMAT for mobility limitation and poor performance were 1.37 (1.27, 1.47) and 1.54 (1.18, 2.02), respectively. Even into old age, higher BMI is associated with mobility limitation and poor performance. The amount of adipose tissue in abdominal and thigh depots may also convey risk beyond BMI.
    American Journal of Clinical Nutrition 02/2014; · 6.50 Impact Factor
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    ABSTRACT: Kidney damage is a common sequela of several chronic pathologic conditions. Whether biomarkers of kidney damage are prognostic for more severe outcomes is unknown. We measured three urinary biomarkers (kidney injury molecule-1 [KIM-1], IL-18, and albumin) in 3010 individuals enrolled in the Health, Aging and Body Composition (Health ABC) study and used Cox proportional hazards models to investigate the associations of urinary KIM-1/creatinine (cr), IL-18/cr, and albumin/cr (ACR) with all-cause mortality and cardiovascular disease (CVD). Multivariable models adjusted for demographics, traditional CVD risk factors, and eGFR. Mean age of participants was 74 years, 49% of participants were men, and 41% of participants were black. During the median 12.4 years of follow-up, 1450 deaths and 797 CVD outcomes occurred. Compared with the lowest quartile, successive quartiles had the following adjusted hazard ratios (HRs; 95% confidence intervals [95% CIs]) for mortality: KIM-1/cr: (1.21; 1.03 to 1.41), (1.13; 0.96 to 1.34), and (1.28; 1.08 to 1.52); IL-18/cr: (1.02; 0.88 to 1.19), (1.16; 0.99 to 1.35), and (1.06; 0.90 to 1.25); ACR: (1.08; 0.91 to 1.27), (1.24; 1.06 to 1.46), and (1.63; 1.39 to 1.91). In similar analyses, only ACR quartiles associated with CVD: (1.19; 0.95 to 1.48), (1.35; 1.08 to 1.67), and (1.54; 1.24 to 1.91). Urinary KIM-1 had a modest association with all-cause mortality but did not associate with CVD, and urinary IL-18 did not associate with either outcome. In contrast, albuminuria strongly associated with all-cause mortality and CVD. Future studies should evaluate reasons for these differences in the prognostic importance of individual kidney injury markers.
    Journal of the American Society of Nephrology 02/2014; · 9.47 Impact Factor
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    ABSTRACT: Current approaches to falls prevention mostly rely on secondary and tertiary prevention and target individuals at high risk of falls. An alternative is primary prevention, in which all seniors are screened, referred as appropriate, and educated regarding falls risk. Little information is available on research designs that allow investigation of this approach in the setting of aging services delivery, where randomization may not be possible. Healthy Steps for Older Adults, a statewide program of the Pennsylvania (PA) Department of Aging, involves a combination of education about falls and screening for balance problems, with referral to personal physicians and home safety assessments. We developed a non-randomized statewide trial, Falls Free PA, to assess its effectiveness in reducing falls incidence over 12 months. We recruited 814 seniors who completed the program (503 first-time participants, 311 people repeating the program) and 1,020 who did not participate in the program, from the same sites. We assessed the quality of this non-randomized design by examining recruitment, follow-up across study groups, and comparability at baseline. Of older adults approached in senior centers, 90.5 % (n = 2,219) signed informed consent, and 1,834 (82.4 %) completed baseline assessments and were eligible for follow-up. Attrition in the three groups over 12 months was low and non-differential (<10 % for withdrawal and <2 % for other loss to follow-up). Median follow-up, which involved standardized monthly assessment of falls, was 10 months in all study groups. At baseline, the groups did not differ in measures of health or falls risk factors. Comparable status at baseline, recruitment from common sites, and similar experience with retention suggest that the non-randomized design will be effective for assessment of this approach to primary prevention of falls.
    Prevention Science 02/2014; · 2.63 Impact Factor
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    ABSTRACT: Although the beneficial effects of physical activity (PA) on memory and executive function are well established in older adults, little is known about the relationship between PA and brain microstructure and the contributions of physical functional limitations and chronic diseases. This study examined whether higher PA would be longitudinally associated with greater microstructural integrity in memory- and executive function-related networks and whether these associations would be independent of physical function and chronic diseases. Diffusion tensor imaging was obtained in 2006-2008 in 276 participants (mean age = 83.0 years, 58.7% female, 41.3% black) with PA (sedentary, lifestyle active, and exercise active) measured in 1997-1998. Gait speed, cognition, depressive symptoms, cardiovascular and pulmonary diseases, hypertension, stroke, and diabetes were measured at both time points. Mean diffusivity and fractional anisotropy were computed from normal-appearing gray and white matter in frontoparietal and subcortical networks. Moderating effects of physical function and chronic diseases were tested using hierarchical regression models. Compared with the sedentary, the exercise active group had lower mean diffusivity in the medial temporal lobe and the cingulate cortex (β, p values: -.405, .023 and -.497, .006, respectively), independent of age, sex, and race. Associations remained independent of other variables, although they were attenuated after adjustment for diabetes. Associations between PA and other neuroimaging markers were not significant. Being exercise active predicts greater memory-related microstructural integrity in older adults. Future studies in older adults with diabetes are warranted to examine the neuroprotective effect of PA in these networks.
    The Journals of Gerontology Series A Biological Sciences and Medical Sciences 01/2014; · 4.31 Impact Factor
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    ABSTRACT: When data are sparse and/or predictors multicollinear, current implementation of sparse partial least squares (SPLS) does not give estimates for non-selected predictors nor provide a measure of inference. In response, an approach termed "all-possible" SPLS is proposed, which fits a SPLS model for all tuning parameter values across a set grid. Noted is the percentage of time a given predictor is chosen, as well as the average non-zero parameter estimate. Using a "large" number of multicollinear predictors, simulation confirmed variables not associated with the outcome were least likely to be chosen as sparsity increased across the grid of tuning parameters, while the opposite was true for those strongly associated. Lastly, variables with a weak association were chosen more often than those with no association, but less often than those with a strong relationship to the outcome. Similarly, predictors most strongly related to the outcome had the largest average parameter estimate magnitude, followed by those with a weak relationship, followed by those with no relationship. Across two independent studies regarding the relationship between volumetric MRI measures and a cognitive test score, this method confirmed a priori hypotheses about which brain regions would be selected most often and have the largest average parameter estimates. In conclusion, the percentage of time a predictor is chosen is a useful measure for ordering the strength of the relationship between the independent and dependent variables, serving as a form of inference. The average parameter estimates give further insight regarding the direction and strength of association. As a result, all-possible SPLS gives more information than the dichotomous output of traditional SPLS, making it useful when undertaking data exploration and hypothesis generation for a large number of potential predictors.
    Frontiers in Neuroinformatics 01/2014; 8:18.
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    ABSTRACT: To examine whether observed differences in dementia rates between black and white older people living in the community could be explained by measures of socioeconomic status (income, financial adequacy, education, and literacy) and health related factors. Prospective cohort study. General community from two clinic sites in the United States (Pittsburgh, Pennsylvania and Memphis, Tennessee). 2457 older people (mean age 73.6 years; 1019 (41.5%) black; 1233 (50.2%) women), dementia-free at baseline, in the Health, Aging, and Body Composition study. Dementia was determined over 12 years (ending January 2011) by prescribed dementia drugs, hospital records, and decline in global cognitive scores. The influence of socioeconomic status and health related factors on dementia rates was examined in a series of Cox proportional hazard models in which these variables were added sequentially in covariate blocks. Over follow-up, 449 (18.3%) participants developed dementia. Black participants were more likely than white participants to develop dementia (211 (20.7%) v 238 (16.6%), P<0.001; unadjusted hazard ratio 1.44, 95% confidence interval 1.20 to 1.74). The hazard ratio lessened somewhat after adjustment for demographics, apolipoprotein E e4, comorbidities, and lifestyle factors (1.37, 1.12 to 1.67) but was greatly reduced and no longer statistically significant when socioeconomic status was added (1.09, 0.87 to 1.37). These findings suggest that differences in the burden of risk factors, especially socioeconomic status, may contribute to the higher rates of dementia seen among black compared with white older people. Strategies aimed at reducing these disparities may favorably affect the incidence of dementia.
    BMJ (online) 12/2013; 347:f7051. · 16.38 Impact Factor
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    ABSTRACT: -Tumor necrosis factor (TNF) levels are associated with risk for heart failure (HF). The soluble TNF type-1 (sTNF-R1) and type-2 (sTNF-R2) receptors are elevated in patients with manifest HF, but whether they are associated with risk for incident HF is unclear. -Using Cox proportional hazard models, we examined the association between baseline levels of sTNF-R1 and sTNF-R2 with incident HF risk among 1285 participants of the Health, Aging, and Body Composition Study (age 74.0±2.9 years; 51.4% women; 41.1% black). At baseline, median (interquartile range) of TNF, sTNF-R1, and sTNF-R2 levels were 3.14 (2.42-4.06) pg/ml, 1.46 (1.25-1.76) ng/ml, and 3.43 (2.95-4.02) ng/ml, respectively. During a median follow-up of 11.4 (6.9, 11.7) years, 233 (18.1%) participants developed HF. In models controlling for other HF risk factors, TNF (hazard ratio [HR], 1.28; 95% confidence interval [CI], 1.02-1.61 per log2 increase), and sTNF-R1 (HR, 1.68; 95%CI, 1.15-2.46 per log2 increase), but not sTNF-R2 (HR, 1.15; 95%CI, 0.80-1.63 per log2 increase), were associated with a higher risk for HF. These associations were consistent across whites and blacks (TNF, sTNF-R1, sTNF-R2, interaction P=0.531, 0.091 and 0.795, respectively), and in both genders (TNF, sTNF-R1, sTNF-R2, interaction P=0.491, 0.672 and 0.999, respectively). TNF-R1 was associated with a higher risk for HF with preserved versus reduced ejection fraction (HR, 1.81; 95%CI, 1.03, 3.18; P=0.038 for preserved vs. HR, 0.90; 95%CI, 0.56, 1.44; P=0.667 for reduced ejection fraction, interaction P=0.05). -In older adults, elevated levels of sTNF-R1 are associated with an increased risk for incident HF. However, addition of TNF-R1 to the previously validated Health ABC HF risk model did not demonstrate material improvement in net discrimination or reclassification.
    Circulation Heart Failure 12/2013; · 6.68 Impact Factor
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    ABSTRACT: Obesity is associated with increased risk of many types of cancer. Less is known regarding associations between adipose depots and cancer risk. We aimed to explore relationships between adipose depots, risk of cancer, and obesity-related cancer (per NCI definition) in participants initially aged 70-79 years without prevalent cancer (1179 men, 1340 women), and followed for incident cancer for 13 years. Measures included body mass index (BMI), total adipose tissue from dual-energy X-ray absorptiometry, and computed tomography measures of visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue, thigh intermuscular adipose tissue, and thigh muscle attenuation (Hounsfield unit, HU), where low HU indicates fatty infiltration. Hazard ratios (HR) and 95% confidence intervals (CIs) were estimated by Cox proportional hazards models adjusted for demographics, lifestyle variables, and medical conditions. During follow-up, 617 participants developed cancer of which 224 were obesity-related cancers. Total adipose tissue and VAT were positively associated with cancer risk among women (HR 1.14, 95% CI 1.01-1.30 per SD increase; HR 1.15, 95% CI 1.02-1.30 per SD increase). There were no associations with cancer risk among men. Total adipose tissue was positively associated with obesity-related cancer risk among women (HR 1.23, 95% CI 1.03-1.46 per SD increase). VAT was positively associated with obesity-related cancer risk among men (HR 1.30, 95% CI 1.06-1.60 per SD increase) and remained associated even with adjustment for BMI (HR 1.40, 95% CI 1.08-1.82 per SD increase). These findings provide insight into relationships between specific adipose depots and cancer risk and suggest differential relationships among men and women.
    Applied Physiology Nutrition and Metabolism 12/2013; · 2.01 Impact Factor
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    ABSTRACT: Background: To promote healthy aging, the University of Pittsburgh Prevention Research Center (PRC) developed the 10 KeysTM to Healthy Aging, a bundled health promotion program. The PRC partnered with the Arthritis Foundation (AF) to combine the 10 KeysTM with the AF Exercise Program (AFEP). The program was designed for older adults with arthritis or joint pain because they are at higher risk for other chronic conditions. Methods: A cluster randomized trial was implemented to compare the combined 10 Keys TM and AFEP program compared to AFEP alone, and to build sustainability of the program in the community. The collaboration involved combining content, training instructors, and recruiting host sites, instructors, and participants. Sites were matched on key characteristics for stratified randomization. Results: To date, 18 sites have been randomized to the integrated program (7 programs) or AFEP alone (11) with a goal of 40. Sessions have been held twice weekly for 10 weeks with 467 program participants. Of these, 122 consented to a detailed assessment of preventive health behaviors at baseline and follow-up. Research participants were on average 72.4 ( 9.2) years; 84.4% were women, and 98% Caucasian. Feedback was positive with 92% rating the program as excellent or very good. 50% of the sites continued to offer the program after the initial ten weeks. Conclusions: This program delivers bundled health promotion targeting multiple co-morbid conditions to at-risk older adults in the community. Program continuation suggests that it will be sustainable. Impact on preventive health behaviors remains to be tested.
    141st APHA Annual Meeting and Exposition 2013; 11/2013

Publication Stats

39k Citations
4,285.27 Total Impact Points

Institutions

  • 1991–2015
    • University of Pittsburgh
      • • Department of Epidemiology
      • • Department of Medicine
      • • UPMC - Comprehensive Lung Center
      • • School of Medicine
      • • Department of Psychiatry
      Pittsburgh, Pennsylvania, United States
  • 2014
    • Columbia University
      New York City, New York, United States
  • 2007–2014
    • Pennsylvania Department of Health
      Harrisburg, Pennsylvania, United States
    • University of Colorado
      • Division of Renal Diseases and Hypertension
      Denver, CO, United States
  • 2013
    • Oregon State University
      • School of Biological and Population Health Sciences
      Corvallis, OR, United States
    • Bristol-Myers Squibb
      New York, New York, United States
    • University of Pennsylvania
      Philadelphia, Pennsylvania, United States
    • King's College London
      • Institute of Psychiatry
      London, ENG, United Kingdom
    • Yale-New Haven Hospital
      • Department of Laboratory Medicine
      New Haven, Connecticut, United States
    • Northwestern University
      • Feinberg School of Medicine
      Evanston, Illinois, United States
    • University of Cambridge
      • Department of Public Health and Primary Care
      Cambridge, England, United Kingdom
    • Uppsala University
      Uppsala, Uppsala, Sweden
    • University of Connecticut
      • UConn Center on Aging
      Storrs, Connecticut, United States
  • 2011–2013
    • California Pacific Medical Center Research Institute
      • Research Institute
      San Francisco, California, United States
    • Medizinische Universität Innsbruck
      • Sektion für Genetische Epidemiologie
      Innsbruck, Tyrol, Austria
    • California State University, Sacramento
      Sacramento, California, United States
    • Autonomous University of Barcelona
      Cerdanyola del Vallès, Catalonia, Spain
    • Kaiser Permanente
      Oakland, California, United States
    • National University (California)
      San Diego, California, United States
    • State University of New York Downstate Medical Center
      • Department of Epidemiology and Biostatistics (EPID, BIOS)
      Brooklyn, NY, United States
    • Duke University Medical Center
      • Center for the Study of Aging and Human Development
      Durham, NC, United States
    • United States Department of Agriculture
      Washington, Washington, D.C., United States
    • Johns Hopkins Bloomberg School of Public Health
      • Department of Health Policy and Management
      Baltimore, MD, United States
  • 2006–2013
    • Emory University
      • • Division of Cardiology
      • • School of Medicine
      • • Division of Endocrinology
      Atlanta, Georgia, United States
    • The University of Tennessee Health Science Center
      • • Department of Medicine
      • • Department of Preventive Medicine
      Memphis, Tennessee, United States
    • St. Francis Hospital
      Roslyn, New York, United States
    • University of San Francisco
      San Francisco, California, United States
  • 2004–2013
    • University of California, San Francisco
      • • Division of Hospital Medicine
      • • Department of Psychiatry
      • • Veterans Affairs Medical Center
      • • Department of Epidemiology and Biostatistics
      • • Division of General Internal Medicine
      San Francisco, CA, United States
    • University of Minnesota Twin Cities
      • School of Public Health
      Minneapolis, MN, United States
    • National Institutes of Health
      • Laboratory of Epidemiology, Demography, and Biometry (LEDB)
      Bethesda, MD, United States
    • Case Western Reserve University
      • Department of Pediatrics (University Hospitals Case Medical Center)
      Cleveland, OH, United States
    • University of Florence
      • Dipartimento di Medicina Sperimentale e Clinica
      Florence, Tuscany, Italy
    • University of Wisconsin, Madison
      • Department of Nutritional Sciences
      Madison, MS, United States
  • 2001–2013
    • National Institute on Aging
      • • Laboratory of Epidemiology, Demography and Biometry (LEDB)
      • • Clinical Research Branch (CRB)
      Baltimore, Maryland, United States
  • 2012
    • Inselspital, Universitätsspital Bern
      • Department of General Internal Medicine
      Bern, BE, Switzerland
    • University of Toulouse
      Tolosa de Llenguadoc, Midi-Pyrénées, France
    • Syracuse University
      • Department of Exercise Science
      Syracuse, New York, United States
    • Saint Luke's Hospital (NY, USA)
      New York City, New York, United States
  • 2009–2012
    • Boston University
      • Pulmonary Center
      Boston, Massachusetts, United States
    • Hospital of the University of Pennsylvania
      • Department of Medicine
      Philadelphia, Pennsylvania, United States
    • Instituto Nacional de Cardiología
      Ciudad de México, The Federal District, Mexico
    • CHA University
      • Department of Internal Medicine
      Seoul, Seoul, South Korea
    • University of South Carolina
      Columbia, South Carolina, United States
    • University of California, Berkeley
      • Division of Epidemiology
      Berkeley, CA, United States
    • University of Georgia
      • Department of Foods and Nutrition
      Athens, GA, United States
  • 2008–2012
    • Albert Einstein College of Medicine
      • Department of Epidemiology & Population Health
      New York City, NY, United States
    • University of Lausanne
      • Faculté de biologie et de médecine (FBM)
      Lausanne, VD, Switzerland
    • Pennington Biomedical Research Center
      Baton Rouge, Louisiana, United States
    • Pittsburg State University
      Kansas, United States
    • University of Exeter
      • Peninsula College of Medicine and Dentistry
      Exeter, ENG, United Kingdom
  • 2005–2012
    • University of Vermont
      • • Department of Pathology
      • • Department of Medicine
      Burlington, VT, United States
    • University of Washington Seattle
      • • Department of Biostatistics
      • • Division of Nephrology
      Seattle, WA, United States
    • University of Missouri
      • Department of Health Sciences
      Columbia, MO, United States
    • Fletcher Allen Health Care
      Burlington, Vermont, United States
    • University of Queensland 
      • School of Human Movement Studies
      Brisbane, Queensland, Australia
  • 2010–2011
    • Weill Cornell Medical College
      • Division of Hospital Medicine
      New York City, New York, United States
    • Yale University
      • Department of Internal Medicine
      New Haven, CT, United States
    • The University of Memphis
      Memphis, Tennessee, United States
    • Ben-Gurion University of the Negev
      Be'er Sheva`, Southern District, Israel
  • 2005–2011
    • Wake Forest University
      • Department of Health and Exercise Science
      Winston-Salem, NC, United States
    • Tufts Medical Center
      • • Division of Nephrology
      • • Department of Medicine
      Boston, Massachusetts, United States
    • University of Florida
      • Department of Aging and Geriatric Research
      Gainesville, FL, United States
  • 2004–2011
    • Beth Israel Deaconess Medical Center
      • • Division of Gerontology
      • • Department of Medicine
      • • Division of General Medicine and Primary Care
      Boston, MA, United States
  • 2003–2011
    • Wake Forest School of Medicine
      • • Department of Internal Medicine
      • • Sticht Center on Aging
      • • Section on Gerontology and Geriatric Medicine
      Winston-Salem, NC, United States
    • University of Leuven
      Louvain, Flanders, Belgium
  • 2005–2010
    • University of Maryland, Baltimore
      • • Department of Medicine
      • • Division of Nephrology
      Baltimore, MD, United States
  • 2002–2009
    • VU University Medical Center
      • Department of Psychiatry
      Amsterdam, North Holland, Netherlands
    • Johns Hopkins Medicine
      Baltimore, Maryland, United States
  • 2006–2008
    • Vanderbilt University
      • • Department of Neurology
      • • Department of Medicine
      Nashville, MI, United States
  • 2005–2007
    • U.S. Department of Veterans Affairs
      Washington, Washington, D.C., United States
  • 2004–2007
    • San Francisco VA Medical Center
      San Francisco, California, United States
  • 2005–2006
    • Maastricht University
      Maestricht, Limburg, Netherlands
  • 2003–2005
    • The University of Arizona
      • Department of Medicine
      Tucson, AZ, United States
  • 2001–2005
    • University of Tennessee
      • • Department of Periodontology
      • • Department of Preventive Medicine
      Knoxville, TN, United States
  • 2000–2005
    • VU University Amsterdam
      • • IHS-Institute of Health Sciences
      • • Faculty of Medicine/VU University Medical Center
      Amsterdamo, North Holland, Netherlands
    • Georgetown University
      • Division of Cardiology
      Washington, D. C., DC, United States
  • 1991–2005
    • Johns Hopkins University
      • Department of Medicine
      Baltimore, Maryland, United States
  • 1993
    • Childrens Hospital of Pittsburgh
      Pittsburgh, Pennsylvania, United States