3-year Incident Research Articles

Location Matters: The Role of the Neighborhood Environment for Incident Cardiometabolic Disease in Adults Aging With Physical Disability.

People aging with disability may be limited in their ability to engage in healthy behaviors to maintain cardiometabolic health. We investigated the role of health promoting features in the neighborhood environment for incident cardiometabolic disease in adults aging with physical disability in the United States. Retrospective cohort study. Optum's Clinformatics® Data Mart Database (2007-2018) of administrative health claims. ICD-9-CM codes were used to identify 15467 individuals with a diagnosis of Cerebral Palsy, Spina Bifida, Multiple Sclerosis, or Spinal Cord Injury. Cardiometabolic disease was identified using ICD-9-CM/ICD-10-CM codes over 3 years of follow-up. Measures of the neighborhood environment came from the National Neighborhood Data Archive and linked to individual residential ZIP codes over time. Covariates included age, sex, and comorbid health conditions. Cox regression models estimated hazard ratios (HR) for incident cardiometabolic disease. Using a 1-year lookback period, individuals with pre-existing cardiometabolic disease were excluded from the analysis. Net of individual risk factors, residing in neighborhoods with a greater density of broadband Internet connections (HR = .88, 95% CI: .81, .97), public transit stops (HR = .89, 95% CI: .83, .95), recreational establishments (HR = .89, 95% CI: .83, .96), and parks (HR = .88, 95% CI: .82, .94), was associated with reduced risk of 3-year incident cardiometabolic disease. Findings identify health-promoting resources that may mitigate health disparities in adults aging with disability.

Prediction of incident heart failure through deep learning-based analysis of 1-lead ECGs

Abstract Background/Introduction Identification of individuals at risk for heart failure (HF) can lead to early intervention. However, large scale screening for incident HF in the general population is insufficient, partly due to the limited capacities in health care systems and number of health care specialists. One-lead ECGs, e.g. from wearables capable of deriving this biomarker, are becoming more popular in the population. This holds the potential to identify individuals at risk who could benefit from a referral to a HF specialist. Purpose We examined the ability to predict three-year HF incidence from 1-lead ECGs using a deep learning (DL) model that was trained on data from the UK Biobank (UKB). Methods The UKB was established in 2006 and contains data from 500,000 participants from the British general population. N = 100,551 1-lead ECGs from 91,898 unique participants were used for this study. This includes 57,897 3-lead resting ECGs written during ergometry exams between 2006 and 2010 (Exam 1; median age 56.7 years, 46.2% men) and at the first follow-up from 2010-2013 (Exam 2; median age 61.3 years, 49% men) and 32,828 12-lead resting ECGs which were acquired between 2014 and 2020 (Exam 3; median age 63.5 years, 48.4% men). Lead I was extracted from the ECGs for all analyses. A 1D-Convolutional Neural Network was used for prediction of the 3-year risk of incident HF. A comparison with the CHARGE-AF score was performed using a nested 6-fold cross-validation scheme. The models were evaluated using the Area Under the Curve (AUC). Results In all three exams, the DL model was able to reliably detect 3-year incident HF (AUC; Exam 1: 0.738, Exam 2: 0.822, Exam 3: 0.738) while the CHARGE-AF score provided slightly better predictions at Exam 1 and Exam 3 (AUC 0.766, 0.748), but lower results in Exam 2 (AUC 0.736). Combining both models led to increased discriminatory properties across all exams (AUC; Exam 1: 0.812, Exam 2: 0.832, Exam 3: 0.788). Conclusion The derived DL model shows high discriminatory ability in the prediction of incident HF from 1-lead ECGs. The predictive ability can be further increased when combined with simple clinical variables from the CHARGE-AF score. This study represents another step towards the application of DL-based analysis of the ECG to advance health care.

Deep learning based prediction of atrial fibrillation incidence from 1-lead ECGs: a model development and validation study

Abstract Introduction Wearables capable of deriving biomarkers such as 1-lead ECGs become largely available, therefore offering the potential to screen for prevalent and incident cardiovascular disease within the population. Screening for prevalent atrial fibrillation (AF) from such devices is already widely applied. It has remained unclear whether predicting incident AF using 1-lead ECGs is possible. The assessment of AF risk before clinical manifestation may permit early detection and thus slow or limit the onset and progression of the disease by taking appropriate measures. Purpose Utilizing data from the UK-Biobank (UKB), we examined the possibility to predict three-year AF incidence from single-lead ECGs using deep learning-based methods. Methods For this study 100,551 1-lead ECGs from 91,898 unique participants were utilized, including 57,897 4-lead resting ECGs during ergometry from 2006-2010 and 9,826 at the first follow-up (FU) from 2010-2013 and 32,828 12-lead resting ECGs during the FU imaging study from 2014-2020. The 12-lead and 4-lead ECGs share information from lead I, which was used for all further analyses. We employ a 1D-Convolutional Neural Network (CNN) to predict the 3-year risk of incident AF. The CNN is compared with the clinically used CHARGE-AF Score. External validation was performed in the SHIP-START cohort including its three FU examinations (n=2,579; nFU1=3,101; nFU2=2,613; nFU3=1,482) and a median FU time of 5-years to FU and SHIP-TREND (n=2,931) with one FU after 7-years. Results The CNN provided a good ability to predict of 3-year incident AF at all three UKB FUs (AUC: 0.729, 0.727, 0.705), while the CHARGE-AF Score provides better results at Exam1 (0.773), worse at Exam2 (0.692) and equal at Exam3 (0.717). A combination of the CHARGE-AF Score and the CNN improved the individual predictions at all three FUs (AUC: 0.811, 0.741, 0.753). The CNN provides an equally good ability to predict incident AF at all four FUs in SHIP-START (AUC: 0.659, 0.785 0.689, and 0.772) and in SHIP-TREND (0.780). Combined with the CHARGE-AF-Score score, the performance in SHIP-START increases to 0.757, 0.861, 0.765, and 0.812 and in SHIP-Trend to 0.826 respectively. Conclusion Using a CNN to predict incident AF from 1-lead ECGs, we provide further evidence for the added value of clinically applied deep learning-based methods. By combining the CNN predictions on ECG data with the well-established CHARGE-AF score, 3-year AF incidence can be predicted with high accuracy.

Sleep Complaints Among Adults With Major Depressive Episode Are Associated With Increased Risk of Incident Psychiatric Disorders

Objective: Sleep alterations have been suggested as a cause and consequence of psychiatric disorders. In this context, we evaluated the incidence of psychiatric disorders following sleep complaints in adults with major depressive episode (MDE).Methods: In a large, nationally representative 3-year prospective survey, the National Epidemiologic Survey on Alcohol and Related Conditions conducted in 2001-2002 (Wave 1) and 2004-2005 (Wave 2), we used structural equation modeling to examine shared and specific effects of trouble falling asleep, early morning awakening, and hypersomnia on incidence of common comorbid DSM-IV disorders among patients with MDE. The analyses adjusted for sociodemographic and clinical characteristics, including sedative or tranquilizer use.Results: Among participants with MDE at Wave 1, 3-year incidence rates were dysthymia = 2.9%, general anxiety disorder = 8.2%, panic disorder = 3.4%, social anxiety disorder = 4.0%, specific phobia = 3.0%, alcohol use disorder = 8.1%, nicotine dependence = 6.2%, cannabis use disorder = 2.7%, and other drug use disorder = 4.9%. Participants with 3-year incident psychiatric disorders commonly had trouble falling asleep (67.6% for cannabis use disorder to 76.4% for panic disorder), early morning awakening (43.3% for cannabis use disorder to 55.6% for dysthymia), and hypersomnia (51.3% for nicotine use disorder to 72.1% for social anxiety disorder). The effects of the incident general psychopathology factor, representing mechanisms related to incidence of all psychiatric disorders, were exerted almost exclusively through a factor representing shared effect across all sleep complaints. Sleep complaints were associated with increased risk of incident psychiatric disorders, independent of sociodemographic and clinical characteristics.Conclusions: These findings suggest that sleep complaints should be clinically assessed in all psychiatric disorders, as these prodromal symptoms might constitute transdiagnostic biomarkers and therapeutic targets for prevention.

Magnetic resonance imaging predictors (cartilage, osteophytes and meniscus) of prevalent and 3-year incident medial and lateral tibiofemoral knee joint tenderness and patellofemoral grind

ObjectiveTo identify magnetic resonance imaging (MRI) predictors (cartilage [C], osteophytes [O] and meniscus [M] scores) of prevalent and 3-year incident medial tibiofemoral (MTF) and lateral tibiofemoral (LTF) knee joint tenderness and patellofemoral (PF) grind. MethodsPopulation-based knee pain cohort aged 40–79 was assessed at baseline (N = 255), 3- and 7-year follow-up (N = 108 × 2 = 216). COM scores were measured at 6/8/6 subregions respectively. Age-sex-BMI adjusted logistic models predicted prevalence versus relevant COM predictors (medial, lateral or patellar / trochlear groove scores). Fully adjusted models also included all relevant COM predictors. Binary generalized estimating equations models predicting 3-year incidence were also adjusted for individual follow-up time between cycles.ResultsSignificant predictors of prevalent MTF tenderness: medial femoral cartilage (fully adjusted odds ratio [aOR] 1.84; 95% confidence interval [CI] 1.11, 3.05), female (aOR = 3.05; 1.67, 5.58), BMI (aOR = 1.53 per 5 units BMI; 1.10, 2.11). Predictors of prevalent LTF tenderness: female (aOR = 2.18; 1.22, 3.90). There were no predictors of prevalent PF grind in the fully adjusted model. However, medial patellar osteophytes was predictive in the age-sex-BMI adjusted model. There were no predictors of 3-year incident MTF tenderness. Predictors of 3-year incident LTF tenderness: female (aOR = 3.83; 1.25, 11.77). Predictors of 3-year incident PF grind: lateral patellar osteophytes (aOR = 4.82; 1.69, 13.77). In the age-sex-BMI adjusted model, patellar cartilage was also a predictor.ConclusionWe explored potential MRI predictors of prevalent and 3-year incident MTF/LTF knee joint tenderness and PF grind. These findings could guide preemptive strategies aimed at reducing these symptoms in the present and future (3-year incidence).

Triage performance and predictive value of the human gene methylation panel among women positive on self-collected HPV test: Results from a prospective cohort study.

Triaging of women positive for high-risk human papillomavirus (hrHPV) on self-collected samples requires a molecular reflex test to avoid recall for cytology or visual tests. We assessed triage performance and predictive value of human gene methylation panel (ZNF671/ASTN1/ITGA4/RXFP3/SOX17/DLX1) alone and with combination of HPV16/18 genotyping in a longitudinal screening study. Out of 9526 women at baseline, 1758 women positive for hrHPV on self-collected samples followed up yearly were included in the current analysis. Satisfactory risk stratification to detect cervical intraepithelial neoplasia grade 2 or worse (CIN2+) was demonstrated by the methylation panel with an odds ratio (OR) of 11.3 among methylation-positive women compared to methylation-negative counterparts. Triaging with methylation panel reduced colposcopy referral rate by 67.2% with sensitivity and specificity of 83.0% and 69.9% to detect CIN2+. The corresponding values for the combining methylation and HPV 16/18 were 96.6% and 58.3%. The cumulative 3-year incident CIN2+ risk was 6.8% (95% CI: 4.9%-8.6%) for hrHPV positive women, which was reduced to 4.5% (95% CI: 2.7%-6.3%) and 2.9% (95% CI: 1.2%-4.5%) for women negative on methylation triaging alone and negative on the combined strategy. The corresponding risk for women positive for both methylation and HPV 16/18 reached 33.7% (95% CI: 19.0%-45.8%). Our study demonstrated the satisfactory triage performance and predictive value of the methylation panel, especially in combination with HPV 16/18 genotyping. The substantially lower risk of CIN2+ among the triage negative women over the next 3 years suggests that the interval for repeat HPV test can be safely extended to at least 2 years.

Abstract 9091: Care Fragmentation and Health Outcomes Among African Americans: Jackson Heart Study

Introduction: African American (AA) adults experience high comorbidity burden, yet the association between care fragmentation and outcomes among AA is unknown. We aimed to characterize care fragmentation among AA Medicare beneficiaries in the Jackson Heart Study (JHS) and associated outcomes. Methods: We identified 2 cohorts of JHS participants enrolled in Medicare: 1) established cardiovascular disease (CVD), including coronary artery disease, stroke, and heart failure, and 2) complex medical needs, defined as a Charlson Comorbidity Index ≥ 3. Care fragmentation was defined as 1 - Bice-Boxerman index, which was estimated from all ambulatory visits in Medicare claims during 1 year before (pre-baseline) and 1 year after baseline exam. Cox proportional hazard was used to assess associations between pre-baseline exam care fragmentation and cumulative incident all-cause hospitalizations and mortality over 3 years. Results: Among eligible JHS participants, 148 had CVD and 94 had complex medical needs. Pre-baseline care fragmentation was ≥ 0.5 among 78% of Cohort 1 and 84% of Cohort 2. Age, sex, insurance status, and income were similar across care fragmentation quartiles in each cohort. Depression symptom scores were higher in the highest care fragmentation quartile compared to the lowest quartile in Cohort 1 (19.5 vs. 11.0; p=0.006), but not in Cohort 2 (16.0 vs. 16.0; p=0.05). Burden of care fragmentation was similar 1 year before and after baseline exam in each cohort ( Figure ). Pre-baseline care fragmentation was not associated with 3-year incident all-cause hospitalization and mortality in each cohort, even after adjustment for age, sex, Charlson score, and depressive symptoms. Conclusions: Care fragmentation was prevalent among AA Medicare beneficiaries with CVD or complex medical needs during 1 year before and after enrollment into JHS. There were no associations between care fragmentation and outcomes in either cohort, though the sample size was limited.

Abstract 13530: Epi+Gen CHD: A More Sensitive and Cost-Effective Tool to Assess Risk and Monitor Treatment Response for Coronary Heart Disease

Coronary heart disease (CHD) is preventable, but current lipid-based risk assessment tools such as The Framingham Risk Score (FRS) and ASCVD Pooled Cohort Equation (PCE) have limitations. Using DNA-based genetic and epigenetic biomarkers, we have developed a more sensitive and cost-effective incident CHD risk assessment tool, Epi+Gen CHD, that can provide actionable insights and monitor treatment response. This test can be administered remotely via telemedicine using at-home sampling, or in a clinical setting. Epi+Gen CHD was developed and validated using machine learning techniques and datasets from the Framingham Heart Study (FHS) and Intermountain Healthcare (IM). It incorporates five SNPs and three methylation markers for predicting 3-year incident CHD. It was more sensitive than FRS and PCE and had high generalizability across cohorts with sensitivity/specificity of 79/75% in the FHS test set and 75/72% in the IM set. In contrast, the sensitivity/specificity was 15/93% in FHS and 31/89% in IM for FRS, and sensitivity/specificity was 41/74% in FHS and 69/55% in IM for the PCE. To assess cost effectiveness, we conducted cost-utility analyses of Epi+Gen CHD. As compared to the PCE, we found that the use of Epi+Gen CHD was associated with both better survival and highly competitive negative incremental cost-effective ratios (cost savings) ranging from -$42,000 to -$-8,000 per quality-adjusted life year with and without accounting for a secondary test. Finally, to understand if the epigenetic biomarkers in Epi+Gen CHD could be leveraged to monitor treatment response, we performed a proof-of-concept study that assessed the three Epi+Gen CHD methylation sites in 39 subjects before and after 3 months of biochemically verified smoking cessation, then analyzed the relationship between change in methylation at each of the sites to the change in smoking intensity (cg05575921 methylation). We showed that in those who quit smoking, methylation change at one Epi+Gen CHD site (cg00300879) was significantly associated with change in smoking intensity (p < 0.04). We conclude that Epi+Gen CHD can identify patients at risk for CHD, save more lives, reduce more healthcare spending and guide prevention interventions better than current methods.

External validation of integrated genetic-epigenetic biomarkers for predicting incident coronary heart disease.

Aim: The Framingham Risk Score (FRS) and atherosclerotic cardiovascular disease (ASCVD) Pooled Cohort Equation (PCE) for predicting risk for incident coronary heart disease (CHD) work poorly. To improve risk stratification for CHD, we developed a novel integrated genetic-epigenetic tool. Materials & methods: Using machine learning techniques and datasets from the Framingham Heart Study (FHS) and Intermountain Healthcare (IM), we developed and validated an integrated genetic-epigenetic model for predicting 3-year incident CHD. Results: Our approach was more sensitive than FRS and PCE and had high generalizability across cohorts. It performed with sensitivity/specificity of 79/75% in the FHS test set and 75/72% in the IM set. The sensitivity/specificity was 15/93% in FHS and 31/89% in IM for FRS, and sensitivity/specificity was 41/74% in FHS and 69/55% in IM for PCE. Conclusion: The use of our tool in a clinical setting could better identify patients at high risk for a heart attack.

Immunosenescence profiles are not associated with muscle strength, physical performance and sarcopenia risk in very old adults: The Newcastle 85+ Study

Decline in immune system function (immunosenescence) has been implicated in several age-related disorders. However, little is known about whether alteration in T-cell senescence, a process underlying immunological ageing, is related to muscle health in very old adults (aged ≥85 years). Utilising data from the Newcastle 85+ Study, we aimed to (a) derive and characterise immunosenescence profiles by clustering 13 baseline immunosenescence-related biomarkers of lymphocyte compartments in 657 participants; (b) explore the association between the profiles and 5-year change in muscle strength (grip strength) and physical performance (Timed Up-and-Go test), and (c) determine whether immunosenescence profiles predict 3-year incident sarcopenia. Two distinct clusters were identified; Cluster 1 (‘Senescent-like phenotype’, n = 421), and Cluster 2 (‘Less senescent-like phenotype’, n = 236) in individuals with complete biomarker data. Although Cluster 1 was characterised by T-cell senescence (e.g., higher frequency of CD4 and CD8 senescence-like effector memory cells), and elements of the immune risk profile (lower CD4/CD8 ratio, CMV+), it was not associated with change in muscle function over time, or with prevalent or incident sarcopenia. Future studies will determine whether more in-depth characterisation or change in T-cell phenotypes predict the decline in muscle health in late adulthood.

Abstract P416: An Externally Validated and Highly Sensitive Artificial Intelligence-driven Integrated Genetic-epigenetic DNA Test for Incident Coronary Heart Disease Prediction

Despite being largely preventable, every year, coronary heart disease (CHD) affects millions of Americans. Currently, primary prevention of CHD starts with an understanding of several risk factors (e.g. age, gender, diabetes) that are aggregated to derive an incident CHD risk score using risk calculators such as the Framingham Risk Score (FRS) and ASCVD Pooled Cohort Equation (PCE). Unfortunately, this approach involves multiple tests and its lack in sensitivity could result in ineffective treatment recommendations to patients for the prevention of CHD. As an alternative, we have developed and independently validated a single, simpler, AI-driven, digital PCR (dPCR)-based integrated genetic-epigenetic DNA test that can more sensitively estimate the 3-year incident CHD risk for both men and women. Our technology accounts for the inherited and acquired (lifestyle/environment) risks for CHD through three genetic (SNP) and three epigenetic (DNA methylation) biomarkers, respectively, and can be performed on DNA from blood or saliva. The incident CHD risk prediction model was developed using genome-wide DNA methylation and genotype data from the Framingham Heart Study (FHS) Offspring cohort (n=1172 in training set, n=512 in test set) and was validated in an Intermountain Healthcare (IM) cohort (n=80 in validation set, n=79 in test set). The final prediction model is an ensemble of SVM, Random Forest and Logistic Regression models, and its performance in the FHS and IM test sets is summarized in Table 1. The FRS and PCE risk calculators were implemented on all FHS and IM cohort data. A clinically implementable version of this tool as part of its translation into a Laboratory Developed Test incorporates standard Taqman assays for genotyping and custom dPCR assays for DNA methylation quantification. The strong correlation between our dPCR assay values and the Illumina array values are shown in Figure 1, indicating successful dPCR assay translation. We are also extending this tool to include more ethnically diverse cohorts.

Depressive symptoms are associated with incident frailty in a Chinese population: the Rugao Longevity and Aging Study.

This study aimed at investigating whether depression symptoms are associated with prevalent and incident physical frailty in Chinese older population. We analyzed data of 1168 older Chinese adults aged 70 and above in the aging arm of the Rugao Longevity and Aging Study (RuLAS). Depressive symptoms (Geriatric Depression Scale ≥ 6) were assessed by the Geriatric Depression Scale. Frailty was defined using Fried phenotype criteria at baseline and 3-year survey. At baseline, 8.9% of the participants had depression symptoms. The prevalence of pre-frailty and frailty were 34.5% and 5.9%, respectively. The percentages of depressive symptoms increase from robust (5.3%) to pre-frail (11.2%), and then to frail (31.9%) groups. After adjustments of multiple covariates, depressive symptoms were associated with both prevalent pre-frailty (OR = 1.75, 95% CI 1.08-2.84) and prevalent frailty (OR = 5.64, 95% CI 2.85-11.14) at baseline. At 3-year survey, 9.3% participants reported the development of frailty. After multiple adjustments, depressive symptoms were associated with a 2.79-fold (95% CI 1.09-7.10) increased risk of 3-year incident frailty. Depressive symptoms are associated with prevalent and incident frailty in Chinese older population. Together with the observations of the European populations, depressive symptoms may be a candidate risk factor of frailty.

Effects of dietary patterns and low protein intake on sarcopenia risk in the very old: The Newcastle 85+ study

SummaryBackgroundSarcopenia, a progressive age-related loss of skeletal muscle mass and strength, leads to disability, falls, and hospitalisation. Individual variation in sarcopenia onset may be partly explained by lifestyle factors such as physical activity and diet. Healthy dietary patterns (DPs) have been linked to better physical functioning in older adults, but their role in sarcopenia in the very old (aged ≥85) is unknown.AimsTo investigate the association between DPs and the risk of sarcopenia over 3 years, and to determine whether protein intake influences this relationship in community-dwelling older adults from the Newcastle 85 + Study.MethodsThe analytic sample consisted of 757 participants (61.2% women) who had dietary assessment at baseline. After two-step clustering with 30 food groups to derive DPs, we used logistic regression to determine the risk of prevalent and incident sarcopenia across DPs in all participants, and in those with low (<1 g/kg adjusted body weight/day [g/kg aBW/d]) and good protein intake (≥1 g/kg aBW/d).ResultsWe identified three DPs (DP1: ‘Low Red Meat’, DP2: ‘Traditional British’ and DP3: ‘Low Butter’) that varied by unsaturated fat spreads/oils, butter, red meat, gravy and potato consumption. Compared with participants in DP3, those in DP2 had an increased risk of prevalent (OR = 2.42, 95% CI: 1.15–5.09, p = 0.02) but not 3-year incident sarcopenia (OR = 1.67, 0.59–4.67, p = 0.33) adjusted for socio-demographic, anthropometry, health and lifestyle factors. Furthermore, DP2 was associated with an increased risk of prevalent sarcopenia at baseline (OR = 2.14, 1.01–4.53, p = 0.05) and 3-year follow-up (OR = 5.45, 1.81–16.39, p = 0.003) after adjustment for key covariates in participants with good protein intake.ConclusionA DP high in foods characteristic of a traditional British diet (butter, red meat, gravy and potato) was associated with an increased risk of sarcopenia even when overall protein intake was good. The results need to be replicated in other cohorts of the very old to understand the role of DPs in sarcopenia onset and management.

Effect of Cardiac Surgery-Associated Acute Kidney Injury on Long-Term Outcomes of Chinese Patients: A Historical Cohort Study

Background/Aims: To evaluate the long-term outcomes of Chinese patients with cardiac surgery-associated acute kidney injury (CSA-AKI). Methods: Patients who underwent cardiac surgery with a median 3-year follow-up were enrolled. The long-term survival rate and the incidence of chronic kidney disease (CKD) were recorded, and related risk factors were analyzed. Results: Of all 1,363 patients, 457 (33.5%) developed CSA-AKI. The AKI patients had a lower 3-year survival rate (88.8 vs. 97.2%, respectively, p < 0.001) and a higher incidence of CKD stages 3-5 (9.9 vs. 2.3%, respectively, p < 0.001) than the non-AKI patients. Cox regression analysis showed that AKI, atrial fibrillation, chronic cardiac insufficiency, longer surgical duration, respiratory failure after surgery, and longer mechanical ventilation time were associated with long-term mortality, while AKI, older age, and lower baseline kidney function were associated with incident CKD stages 3-5. Conclusion: CSA-AKI increased the risk of 3-year mortality and incident CKD stages 3-5.

Herpesvirus Infections and Risk of Frailty and Mortality in Older Women: Women's Health and Aging Studies.

To examine the relationship between herpesvirus infections and mortality and incident frailty risks in community-dwelling older women. Nested prospective cohort study. Women's Health and Aging Studies I and II. Community-dwelling older women aged 70 to 79 (n = 633). Baseline serum antibody (immunoglobulin G) levels against four herpesviruses (herpes simplex virus types 1 (HSV-1) and 2 (HSV-2), varicella-zoster virus (VZV), 7 Epstein-Barr virus (EBV)), 3-year incident frailty rates, and 5-year mortality. Women seropositive for HSV-1 and HSV-2, but not VZV and EBV, had higher risk of 3-year incident frailty (HSV-1: hazard ratio (HR) = 1.90, 95% confidence interval (CI) = 0.96-3.74; HSV-2: HR = 2.10, 95% CI = 1.05-4.37) and 5-year mortality (HR = 1.73, 95% CI = 0.93-3.20; HR = 1.80, 95% CI = 0.94-3.44, respectively) than seronegative women. Incremental increases in serum HSV-1 and HSV-2 antibody levels were associated with incrementally higher risks of incident frailty and mortality. After adjustment for potential confounders, only higher serum HSV-2 antibody level was independently predictive of higher risk of mortality in older women (for each unit increase in antibody index, HR = 1.47, 95% CI = 1.05-2.07). HSV-1 and HSV-2 antibody levels are not independently associated with risk of incident frailty in older women. Only HSV-2 antibody level is independently predictive of 5-year mortality risk, with each incremental increase in the antibody level adding further risk.

Alcohol Use and Frailty in Community-Dwelling Older Persons Aged 65 to 70 Years.

Alcohol use has beneficial as well as adverse consequences on health, but few studies examined its role in the development of age-related frailty. To describe the cross-sectional and longitudinal association between alcohol intake and frailty in older persons. The Lausanne cohort 65+ population-based study, launched in 2004. Community. One thousand five hundred sixty-four persons aged 65-70 years. Annual data collection included demographics, health and functional status, extended by a physical examination every 3 years. Alcohol use (AUDIT-C), and Fried's frailty criteria were measured at baseline and 3-year follow-up. Participants were categorized into robust (0 frailty criterion) and vulnerable (1+ criteria). Few participants (13.0%) reported no alcohol consumption over the past year, 57.8% were light-to-moderate drinkers, while 29.3% drank above recommended thresholds (18.7% "at risk" and 10.5% "heavy" drinkers). At baseline, vulnerability was most frequent in non-drinkers (43.0%), least frequent in light-to-moderate drinkers (26.2%), and amounted to 31.9% in "heavy" drinkers showing a reverse J-curve pattern. In multivariate analysis, compared to light-to-moderate drinkers, non-drinkers had twice higher odds of prevalent (adjOR: 2.24; 95%CI:1.39-3.59; p=.001), as well as 3-year incident vulnerability (adjOR: 2.00; 95%CI:1.02-3.91; p=.043). No significant association was observed among "at risk" and "heavy" drinkers. Non-drinkers had two-times higher odds of prevalent and 3-year incident vulnerability, even after adjusting for their baseline poorer health status. Although residual confounding is still possible, these results likely reflect a healthy survival effect among drinkers while those who experienced health- or alcohol-related problems stopped drinking earlier.

Disease-specific perception of fracture risk and incident fracture rates: GLOW cohort study

Accurate patient risk perception of adverse health events promotes greater autonomy over, and motivation towards, health-related lifestyles. We compared self-perceived fracture risk and 3-year incident fracture rates in postmenopausal women with a range of morbidities in the Global Longitudinal study of Osteoporosis in Women (GLOW). GLOW is an international cohort study involving 723 physician practices across ten countries (Europe, North America, Australasia); 60,393 women aged ≥55 years completed baseline questionnaires detailing medical history and self-perceived fracture risk. Annual follow-up determined self-reported incident fractures. In total 2,945/43,832 (6.8%) sustained an incident fracture over 3 years. All morbidities were associated with increased fracture rates, particularly Parkinson's disease (hazard ratio [HR]; 95% confidence interval [CI], 3.89; 2.78-5.44), multiple sclerosis (2.70; 1.90-3.83), cerebrovascular events (2.02; 1.67-2.46), and rheumatoid arthritis (2.15; 1.53-3.04) (all p < 0.001). Most individuals perceived their fracture risk as similar to (46%) or lower than (36%) women of the same age. While increased self-perceived fracture risk was strongly associated with incident fracture rates, only 29% experiencing a fracture perceived their risk as increased. Under-appreciation of fracture risk occurred for all morbidities, including neurological disease, where women with low self-perceived fracture risk had a fracture HR 2.39 (CI 1.74-3.29) compared with women without morbidities. Postmenopausal women with morbidities tend to under-appreciate their risk, including in the context of neurological diseases, where fracture rates were highest in this cohort. This has important implications for health education, particularly among women with Parkinson's disease, multiple sclerosis, or cerebrovascular disease.

Mental Health of Protective Services Workers: Results From the National Epidemiologic Survey on Alcohol and Related Conditions

To determine the prevalence of mental disorders in a nationally representative sample of protective services workers (PSWs), compare it to that of adults in other occupations, and determine if an association exists between trauma exposure and 3-year incident psychiatric disorders in PSWs. Data from the longitudinal US National Epidemiologic Survey on Alcohol and Related Conditions waves 1 (fielded 2001-2002) and 2 (fielded 2004-2005) were used to compare the prevalence of mental disorders at baseline in a representative sample of PSWs to that of adults in other occupations. Among PSWs, we also explored the association between recent exposure to potentially traumatic events and the development of mood, anxiety, and alcohol-use disorders over a 3-year follow-up period. At baseline, PSWs had a lifetime prevalence of mental and alcohol-use disorders similar to that of adults in other occupations. However, PSWs experienced a greater variety of potentially traumatic events between baseline and follow-up. Exposure to a greater number of different trauma types was associated with increased odds of incident mood (adjusted odds ratio [AOR] = 1.87, 95% CI = 1.09-3.22, P = .024), and alcohol-use disorders (AOR = 1.84, 95% CI = 1.16-2.91, P = .011). These associations were particularly strong among early career PSWs who joined the profession between waves 1 and 2 (AOR = 2.30, 95% CI = 1.26-4.19, P = .008, for mood disorders; AOR = 2.44, 95% CI = 1.30-4.58, P = .007, for alcohol-use disorders). While PSWs do not appear to have a higher prevalence of mental health problems than workers in other occupations, they are more likely to experience multiple types of potentially traumatic events. PSWs who are exposed to multiple types of potentially traumatic events are at increased risk of developing new mental disorders, particularly in the early stages of their careers. Developing curricula in coping skills and providing timely interventions for early career PSWs may help reduce future psychiatric morbidity in these workers.

The association between cystatin C and incident type 2 diabetes is related to central adiposity

Cystatin C has recently been shown to be associated with incident type 2 diabetes. This study aims to validate this association and to study the impact of baseline adiposity. We investigated the 3-year diabetes incidence in 2849 participants from the French Data of an Epidemiological Study on the Insulin Resistance syndrome study, without overt kidney disease. Odds ratios (ORs) associated with cystatin C were adjusted for classical diabetes risk factors and interactions between cystatin C and these risk factors were studied. Baseline serum cystatin C was significantly associated with incident diabetes on univariate analysis (OR/1 SD of log cystatin C: 1.74; 95% confidence interval [CI] 1.33-2.28; P=0.0001) and after adjustment for age and gender (OR 1.55; 95% CI 1.15-2.10; P=0.0039). This association was independent of serum creatinine-derived measures of baseline renal function and independent of fasting plasma glucose and HbA1c. When body mass index (BMI), waist circumference or baseline insulin resistance index were used as covariates, there was an interaction with cystatin C level. Cystatin C was associated only with incident diabetes for people with BMI, waist circumference or insulin resistance index≥median value with OR (95% CIs), respectively: 1.35 (0.98-1.84, P=0.0625); 1.39 (1.01-1.91, P=0.0441) and 1.41 (1.02-1.94, P=0.0398). Cystatin C was associated with 3-year incident diabetes but only in people with central adiposity or insulin resistance. This should be considered in further studies assessing the clinical relevance of its prognostic value.

Predicting 3-Year Incident Mobility Disability in Middle-Aged and Older Adults Using Physical Performance Tests

ObjectiveTo identify a standard physical performance test, which can predict 3-year incident mobility disability independent of demographics. DesignLongitudinal cohort study. SettingPopulation-based middle-aged and older adult cohort assessment performed at a local geriatric clinical center. ParticipantsCommunity-living middle-aged and older persons (age, 50–85y) without baseline mobility disability (N=622). InterventionsNot applicable. Main Outcome MeasuresMobility disability was ascertained at baseline and at 3-year follow-up using an established self-report method: self-reported inability to walk a quarter mile without resting or inability to walk up a flight of stairs unsupported. Physical performance tests included self-selected usual gait speed, time required to complete 5 times sit-to-stand (5TSTS), and 400-m brisk walking. Demographic variables age, sex, height, and weight were recorded. ResultsOverall, 13.5% participants reported 3-year incident mobility disability. Usual gait speed <1.2m/s, requiring >13.6 seconds to complete 5TSTS, and completing 400m at <1.19m/s walking speed were highly predictive of future mobility disability independent of demographics. ConclusionsInability to complete 5TSTS in <13.7 seconds can be a clinically convenient guideline for monitoring and for further assessment of middle-aged and older persons, in order to prevent or delay future mobility disability.