A genomic approach identifies sRAGE as a putatively causal protein for asthma.

BACKGROUND: Asthma is a complex respiratory condition caused by environmental and genetic factors. Although lower concentrations of the anti-inflammatory protein soluble receptor for advanced glycation end products (sRAGE) have been associated with asthma in humans and mouse models, it is uncertain whether sRAGE plays a causal role in asthma. OBJECTIVE: We designed a 2-stage study of sRAGE in relation to asthma with association analysis in FHS participants as well as causal inference testing using Mendelian randomization (MR). METHODS: We measured plasma levels of sRAGE and performed cross-sectional analysis to examine the association between plasma sRAGE concentration and asthma status in 6546 FHS participants. We then used sRAGE protein advanced glycation end products (pQTLs) derived from a genome-wide association study of plasma sRAGE levels in ∼7000 FHS participants with UK Biobank asthma genome-wide association study in MR to consider sRAGE as a putatively causal protein for asthma. We also performed replication MR using an externally derived sRAGE pQTL from the INTERVAL study. Last, we conducted colocalization using cis-pQTL variants at the advanced glycosylation end-product specific receptor (AGER) locus with variants from the UK Biobank asthma genome-wide association study. RESULTS: Association analysis revealed that each 1 SD increment in sRAGE concentration was associated with a 14% lower odds of asthma in FHS participants (95% CI 0.76-0.96). MR identified sRAGE as putatively causal for and protective against asthma on the basis of self-reported (odds ratio [per 1 SE increment in inverse-rank-normalized sRAGE] = 0.97, 95% CI 0.95-0.99; P = .005) and doctor-diagnosed asthma (odds ratio = 0.97, 95% CI 0.95-0.99; P = .011). CONCLUSION: Through this genomic approach, we identified sRAGE as a putatively causal, biologically important, and protective protein in relation to asthma. Functional studies in cell/animal models are needed to confirm our findings.

Assessing the accuracy of race-and-ethnicity data in the Outcome and Assessment Information Set.

BACKGROUND: Limitations in the quality of race-and-ethnicity information in Medicare's data systems constrain efforts to assess disparities in care among older Americans. Using demographic information from standardized patient assessments may be an efficient way to enhance the accuracy and completeness of race-and-ethnicity information in Medicare's data systems, but it is critical to first establish the accuracy of these data as they may be prone to inaccurate observer-reported or third-party-based information. This study evaluates the accuracy of patient-level race-and-ethnicity information included in the Outcome and Assessment Information Set (OASIS) submitted by home health agencies. METHODS: We compared 2017-2022 OASIS-D race-and-ethnicity data to gold-standard self-reported information from the Medicare Consumer Assessment of Healthcare Providers and Systems® survey in a matched sample of 304,804 people with Medicare coverage. We also compared OASIS data to indirect estimates of race-and-ethnicity generated using the Medicare Bayesian Improved Surname and Geocoding (MBISG) 2.1.1 method and to existing Centers for Medicare & Medicaid Services (CMS) administrative records. RESULTS: Compared with existing CMS administrative data, OASIS data are far more accurate for Hispanic, Asian American and Native Hawaiian or other Pacific Islander, and White race-and-ethnicity; slightly less accurate for American Indian or Alaska Native race-and-ethnicity; and similarly accurate for Black race-and-ethnicity. However, MBISG 2.1.1 accuracy exceeds that of both OASIS and CMS administrative data for every racial-and-ethnic category. Patterns of inconsistent reporting of racial-and-ethnic information among people for whom there were multiple observations in the OASIS and Consumer Assessment of Healthcare Providers and Systems (CAHPS) datasets suggest that some of the inaccuracies in OASIS data may result from observation-based reporting that lessens correspondence with self-reported data. CONCLUSIONS: When health record data on race-and-ethnicity includes observer-reported information, it can be less accurate than both true self-report and a high-performing imputation approach. Efforts are needed to encourage collection of true self-reported data and explicit record-level data on the source of race-and-ethnicity information.

Association analysis between an epigenetic alcohol risk score and blood pressure.

Background: Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. Results: We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p = 0.002) and 0.50 (p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN. Conclusions: Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.

Association analysis between an epigenetic risk score and blood pressure.

Background: Epigenome-wide association studies have revealed multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. Results: We generated an alcohol consumption epigenetic risk score (ERS) based on previously reported 144 alcohol-associated CpGs and examined the association of the ERS with systolic blood pressure (SBP), diastolic blood pressure (DBP), and hypertension (HTN) in 3,898 Framingham Heart Study (FHS) participants. We found an association of alcohol intake with the ERS in the meta-analysis with 0.09 units higher ERS per drink consumed per day (p < 0.0001). Cross-sectional analyses in FHS revealed that a one-unit increment of the ERS was associated with 1.93 mm Hg higher SBP (p = 4.64E-07), 0.68 mm Hg higher DBP (p = 0.006), and an odds ratio of 1.78 for HTN (p < 2E-16). Meta-analysis of the cross-sectional association of the ERS with BP traits in eight independent external cohorts (n = 11,544) showed similar relationships with blood pressure levels, i.e., a one-unit increase in ERS was associated with 0.74 (p = 0.002) and 0.50 (p = 0.0006) mm Hg higher SBP and DBP, but could not confirm the association with hypertension. Longitudinal analyses in FHS (n = 3,260) and five independent external cohorts (n = 4,021) showed that the baseline ERS was not associated with a change in blood pressure over time or with incident HTN. Conclusions: Our findings provide proof-of-concept that utilizing an ERS is a useful approach to capture the recent health consequences of lifestyle behaviors such as alcohol consumption.

Expression quantitative trait methylation analysis elucidates gene regulatory effects of DNA methylation: the Framingham Heart Study.

Expression quantitative trait methylation (eQTM) analysis identifies DNA CpG sites at which methylation is associated with gene expression. The present study describes an eQTM resource of CpG-transcript pairs derived from whole blood DNA methylation and RNA sequencing gene expression data in 2115 Framingham Heart Study participants. We identified 70,047 significant cis CpG-transcript pairs at p < 1E-7 where the top most significant eGenes (i.e., gene transcripts associated with a CpG) were enriched in biological pathways related to cell signaling, and for 1208 clinical traits (enrichment false discovery rate [FDR] ≤ 0.05). We also identified 246,667 significant trans CpG-transcript pairs at p < 1E-14 where the top most significant eGenes were enriched in biological pathways related to activation of the immune response, and for 1191 clinical traits (enrichment FDR ≤ 0.05). Independent and external replication of the top 1000 significant cis and trans CpG-transcript pairs was completed in the Women's Health Initiative and Jackson Heart Study cohorts. Using significant cis CpG-transcript pairs, we identified significant mediation of the association between CpG sites and cardiometabolic traits through gene expression and identified shared genetic regulation between CpGs and transcripts associated with cardiometabolic traits. In conclusion, we developed a robust and powerful resource of whole blood eQTM CpG-transcript pairs that can help inform future functional studies that seek to understand the molecular basis of disease.

Dietary and supplemental intake of vitamins C and E is associated with altered DNA methylation in an epigenome-wide association study meta-analysis.

BACKGROUND: Dietary intake of antioxidants such as vitamins C and E protect against oxidative stress, and may also be associated with altered DNA methylation patterns. METHODS: We meta-analysed epigenome-wide association study (EWAS) results from 11,866 participants across eight population-based cohorts to evaluate the association between self-reported dietary and supplemental intake of vitamins C and E with DNA methylation. EWAS were adjusted for age, sex, BMI, caloric intake, blood cell type proportion, smoking status, alcohol consumption, and technical covariates. Significant results of the meta-analysis were subsequently evaluated in gene set enrichment analysis (GSEA) and expression quantitative trait methylation (eQTM) analysis. RESULTS: In meta-analysis, methylation at 4,656 CpG sites was significantly associated with vitamin C intake at FDR ≤ 0.05. The most significant CpG sites associated with vitamin C (at FDR ≤ 0.01) were enriched for pathways associated with systems development and cell signalling in GSEA, and were associated with downstream expression of genes enriched in the immune response in eQTM analysis. Furthermore, methylation at 160 CpG sites was significantly associated with vitamin E intake at FDR ≤ 0.05, but GSEA and eQTM analysis of the top most significant CpG sites associated with vitamin E did not identify significant enrichment of any biological pathways investigated. CONCLUSIONS: We identified significant associations of many CpG sites with vitamin C and E intake, and our results suggest that vitamin C intake may be associated with systems development and the immune response.

Cardiovascular disease protein biomarkers are associated with kidney function: The Framingham Heart Study.

BACKGROUND: Biomarkers common to chronic kidney disease (CKD) and cardiovascular disease (CVD) may reflect early impairments underlying both diseases. METHODS: We evaluated associations of 71 CVD-related plasma proteins measured in 2,873 Framingham Heart Study (FHS) Offspring cohort participants with cross-sectional continuous eGFR and with longitudinal change in eGFR from baseline to follow-up (ΔeGFR). We also evaluated the associations of the 71 CVD proteins with the following dichotomous secondary outcomes: prevalent CKD stage ≥3 (cross-sectional), new-onset CKD stage ≥3 (longitudinal), and rapid decline in eGFR (longitudinal). Proteins significantly associated with eGFR and ΔeGFR were subsequently validated in 3,951 FHS Third Generation cohort participants and were tested using Mendelian randomization (MR) analysis to infer putatively causal relations between plasma protein biomarkers and kidney function. RESULTS: In cross-sectional analysis, 37 protein biomarkers were significantly associated with eGFR at FDR<0.05 in the FHS Offspring cohort and 20 of these validated in the FHS Third Generation cohort at p<0.05/37. In longitudinal analysis, 27 protein biomarkers were significantly associated with ΔeGFR at FDR<0.05 and 12 of these were validated in the FHS Third Generation cohort at p<0.05/27. Additionally, 35 protein biomarkers were significantly associated with prevalent CKD, five were significantly associated with new-onset CKD, and 17 were significantly associated with rapid decline in eGFR. MR suggested putatively causal relations of melanoma cell adhesion molecule (MCAM; -0.011±0.003 mL/min/1.73m2, p = 5.11E-5) and epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1; -0.006±0.002 mL/min/1.73m2, p = 0.0001) concentration with eGFR. DISCUSSION/CONCLUSIONS: Eight protein biomarkers were consistently associated with eGFR in cross-sectional and longitudinal analysis in both cohorts and may capture early kidney impairment; others were implicated in association and causal inference analyses. A subset of CVD protein biomarkers may contribute causally to the pathogenesis of kidney impairment and should be studied as targets for CKD treatment and early prevention.

Longitudinal change in blood DNA epigenetic signature after smoking cessation.

Cigarette smoking is associated with epigenetic changes that may be reversible following smoking cessation. Whole blood DNA methylation was evaluated in Framingham Heart Study Offspring (n = 169) and Third Generation (n = 30) cohort participants at two study visits 6 years apart and in Atherosclerosis Risk in Communities (ARIC) study (n = 222) participants at two study visits 20 years apart. Changes in DNA methylation (delta ß values) at 483,565 cytosine-phosphate-guanine (CpG) sites and differentially methylated regions (DMRs) were compared between participants who were current, former, or never smokers at both visits (current-current, former-former, never-never, respectively), versus those who quit in the interim (current-former). Interim quitters had more hypermethylation at four CpGs annotated to AHRR, one CpG annotated to F2RL3, and one intergenic CpG (cg21566642) compared with current-current smokers (FDR < 0.02 for all), and two significant DMRs were identified. While there were no significant differentially methylated CpGs in the comparison of interim quitters and former-former smokers, 106 DMRs overlapping with small nucleolar RNA were identified. As compared with all non-smokers, current-current smokers additionally had more hypermethylation at two CpG sites annotated to HIVEP3 and TMEM126A, respectively, and another intergenic CpG (cg14339116). Gene transcripts associated with smoking cessation were implicated in immune responses, cell homoeostasis, and apoptosis. Smoking cessation is associated with early reversion of blood DNA methylation changes at CpG sites annotated to AHRR and F2RL3 towards those of never smokers. Associated gene expression suggests a role of longitudinal smoking-related DNA methylation changes in immune response processes.

Whole Genome DNA and RNA Sequencing of Whole Blood Elucidates the Genetic Architecture of Gene Expression Underlying a Wide Range of Diseases.

To create a scientific resource of expression quantitative trail loci (eQTL), we conducted a genome-wide association study (GWAS) using genotypes obtained from whole genome sequencing (WGS) of DNA and gene expression levels from RNA sequencing (RNA-seq) of whole blood in 2622 participants in Framingham Heart Study. We identified 6,778,286 cis -eQTL variant-gene transcript (eGene) pairs at p <5×10 -8 (2,855,111 unique cis -eQTL variants and 15,982 unique eGenes) and 1,469,754 trans -eQTL variant-eGene pairs at p <1e-12 (526,056 unique trans -eQTL variants and 7,233 unique eGenes). In addition, 442,379 cis -eQTL variants were associated with expression of 1518 long non-protein coding RNAs (lncRNAs). Gene Ontology (GO) analyses revealed that the top GO terms for cis- eGenes are enriched for immune functions (FDR <0.05). The cis -eQTL variants are enriched for SNPs reported to be associated with 815 traits in prior GWAS, including cardiovascular disease risk factors. As proof of concept, we used this eQTL resource in conjunction with genetic variants from public GWAS databases in causal inference testing (e.g., COVID-19 severity). After Bonferroni correction, Mendelian randomization analyses identified putative causal associations of 60 eGenes with systolic blood pressure, 13 genes with coronary artery disease, and seven genes with COVID-19 severity. This study created a comprehensive eQTL resource via BioData Catalyst that will be made available to the scientific community. This will advance understanding of the genetic architecture of gene expression underlying a wide range of diseases.

Whole Genome DNA and RNA Sequencing of Whole Blood Elucidates the Genetic Architecture of Gene Expression Underlying a Wide Range of Diseases.

To create a scientific resource of expression quantitative trail loci (eQTL), we conducted a genome-wide association study (GWAS) using genotypes obtained from whole genome sequencing (WGS) of DNA and gene expression levels from RNA sequencing (RNA-seq) of whole blood in 2622 participants in Framingham Heart Study. We identified 6,778,286 cis -eQTL variant-gene transcript (eGene) pairs at p < 5x10 - 8 (2,855,111 unique cis -eQTL variants and 15,982 unique eGenes) and 1,469,754 trans -eQTL variant-eGene pairs at p < 1e-12 (526,056 unique trans -eQTL variants and 7,233 unique eGenes). In addition, 442,379 cis -eQTL variants were associated with expression of 1518 long non-protein coding RNAs (lncRNAs). Gene Ontology (GO) analyses revealed that the top GO terms for cis- eGenes are enriched for immune functions (FDR < 0.05). The cis -eQTL variants are enriched for SNPs reported to be associated with 815 traits in prior GWAS, including cardiovascular disease risk factors. As proof of concept, we used this eQTL resource in conjunction with genetic variants from public GWAS databases in causal inference testing (e.g., COVID-19 severity). After Bonferroni correction, Mendelian randomization analyses identified putative causal associations of 60 eGenes with systolic blood pressure, 13 genes with coronary artery disease, and seven genes with COVID-19 severity. This study created a comprehensive eQTL resource via BioData Catalyst that will be made available to the scientific community. This will advance understanding of the genetic architecture of gene expression underlying a wide range of diseases.

Elucidating the genetic architecture of DNA methylation to identify promising molecular mechanisms of disease.

DNA methylation commonly occurs at cytosine-phosphate-guanine sites (CpGs) that can serve as biomarkers for many diseases. We analyzed whole genome sequencing data to identify DNA methylation quantitative trait loci (mQTLs) in 4126 Framingham Heart Study participants. Our mQTL mapping identified 94,362,817 cis-mQTLvariant-CpG pairs (for 210,156 unique autosomal CpGs) at P < 1e-7 and 33,572,145 trans-mQTL variant-CpG pairs (for 213,606 unique autosomal CpGs) at P < 1e-14. Using cis-mQTL variants for 1258 CpGs associated with seven cardiovascular disease (CVD) risk factors, we found 104 unique CpGs that colocalized with at least one CVD trait. For example, cg11554650 (PPP1R18) colocalized with type 2 diabetes, and was driven by a single nucleotide polymorphism (rs2516396). We performed Mendelian randomization (MR) analysis and demonstrated 58 putatively causal relations of CVD risk factor-associated CpGs to one or more risk factors (e.g., cg05337441 [APOB] with LDL; MR P = 1.2e-99, and 17 causal associations with coronary artery disease (e.g. cg08129017 [SREBF1] with coronary artery disease; MR P = 5e-13). We also showed that three CpGs, e.g., cg14893161 (PM20D1), are putatively causally associated with COVID-19 severity. To assist in future analyses of the role of DNA methylation in disease pathogenesis, we have posted a comprehensive summary data set in the National Heart, Lung, and Blood Institute's BioData Catalyst.

Whole genome DNA and RNA sequencing of whole blood elucidates the genetic architecture of gene expression underlying a wide range of diseases.

To create a scientific resource of expression quantitative trail loci (eQTL), we conducted a genome-wide association study (GWAS) using genotypes obtained from whole genome sequencing (WGS) of DNA and gene expression levels from RNA sequencing (RNA-seq) of whole blood in 2622 participants in Framingham Heart Study. We identified 6,778,286 cis-eQTL variant-gene transcript (eGene) pairs at p < 5 × 10-8 (2,855,111 unique cis-eQTL variants and 15,982 unique eGenes) and 1,469,754 trans-eQTL variant-eGene pairs at p < 1e-12 (526,056 unique trans-eQTL variants and 7233 unique eGenes). In addition, 442,379 cis-eQTL variants were associated with expression of 1518 long non-protein coding RNAs (lncRNAs). Gene Ontology (GO) analyses revealed that the top GO terms for cis-eGenes are enriched for immune functions (FDR < 0.05). The cis-eQTL variants are enriched for SNPs reported to be associated with 815 traits in prior GWAS, including cardiovascular disease risk factors. As proof of concept, we used this eQTL resource in conjunction with genetic variants from public GWAS databases in causal inference testing (e.g., COVID-19 severity). After Bonferroni correction, Mendelian randomization analyses identified putative causal associations of 60 eGenes with systolic blood pressure, 13 genes with coronary artery disease, and seven genes with COVID-19 severity. This study created a comprehensive eQTL resource via BioData Catalyst that will be made available to the scientific community. This will advance understanding of the genetic architecture of gene expression underlying a wide range of diseases.

Opioid medication use and blood DNA methylation: epigenome-wide association meta-analysis.

Aim: To identify differential methylation related to prescribed opioid use. Methods: This study examined whether blood DNA methylation, measured using Illumina arrays, differs by recent opioid medication use in four population-based cohorts. We meta-analyzed results (282 users; 10,560 nonusers) using inverse-variance weighting. Results: Differential methylation (false discovery rate <0.05) was observed at six CpGs annotated to the following genes: KIAA0226, CPLX2, TDRP, RNF38, TTC23 and GPR179. Integrative epigenomic analyses linked implicated loci to regulatory elements in blood and/or brain. Additionally, 74 CpGs were differentially methylated in males or females. Methylation at significant CpGs correlated with gene expression in blood and/or brain. Conclusion: This study identified DNA methylation related to opioid medication use in general populations. The results could inform the development of blood methylation biomarkers of opioid use.

Fracture risk assessment (FRAX) without BMD and risk of major osteoporotic fractures in adults with type 1 diabetes.

OBJECTIVE: To evaluate the association between Fracture Risk Assessment Tool (FRAX) without bone mineral density (BMD) and risk for major osteoporotic fractures (MOF) in type 1 diabetes. METHODS: Subjects with type 1 diabetes and without diabetes from the 'Coronary Artery Calcification in Type 1 Diabetes' study were included. Risk for MOF was calculated using FRAX-based clinical risk factors and without BMD at visit 3 (2006-2008). Incident fractures were defined as fractures that occurred between visit 3 and visit 4 (2013-2017). Survival models were used to study the predictability of new MOF by diabetes status. RESULTS: 346 type 1 diabetes (mean age 43.3 ± 9, BMI 26.4 ± 5, diabetes duration 29.4 ± 8.6 years, A1c 7.8 ± 1.1) and 411 controls (mean age 46.9 ± 9 years, BMI 26.3 ± 5 kg/m2, A1c 5.5 ± 0.4) were analyzed in this study. In unadjusted survival analysis, the FRAX score without BMD was significantly associated with MOF (HR 1.08, 95% CI: 1.04-1.13, p < 0.0001), and remained significantly associated after adjustment for age and sex (HR 1.09, 95% CI: 1.04-1.15, p = 0.0007) and type 1 diabetes (HR 1.08, 95% CI: 1.04-1.12, p = 0.0002). In the fully adjusted model (adjusted for age, sex and type 1 diabetes), the FRAX score without BMD was the only variable significantly associated with risk of MOF (HR 1.08, 95% CI: 1.02-1.14, p = 0.006). CONCLUSION: Clinical use of FRAX without BMD is useful tool in identifying adults with type 1 diabetes at higher risk for MOF risk and may help clinicians to guide therapeutic decision-making in this high fracture risk population.

Type 1 Diabetes Accelerates Progression of Coronary Artery Calcium Over the Menopausal Transition: The CACTI Study.

OBJECTIVE: Type 1 diabetes is associated with a higher risk of cardiovascular disease (CVD) in women. Although menopause increases risk of CVD, it is uncertain how menopause affects risk of CVD in women with type 1 diabetes. We examined whether risk of CVD changes differentially in women with and those without type 1 diabetes over the transition through menopause. RESEARCH DESIGN AND METHODS: Premenopausal women with type 1 diabetes (n = 311) and premenopausal women without diabetes (n = 325) enrolled in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study and attended up to four study visits over 18 years. Coronary artery calcium (CAC) volume was measured from computed tomography scans obtained at each visit. Longitudinal repeated-measures modeling estimated the effect of diabetes on CAC volume over time and the effect of menopause on the diabetes-CAC relationship. RESULTS: CAC volume was higher at baseline and increased more over time in women with type 1 diabetes than in women without diabetes. A significant diabetes-by-menopause interaction was found (P < 0.0001): postmenopausal women with type 1 diabetes had significantly higher CAC volumes than premenopausal women (5.14 ± 0.30 vs. 2.91 ± 0.18 mm3), while there was no difference in women without diabetes (1.78 ± 0.26 vs. 1.78 ± 0.17 mm3). This interaction remained significant after adjusting for CVD risk factors. CONCLUSIONS: Type 1 diabetes was associated with higher CAC volume and accelerated progression of CAC over time. Menopause increased CAC progression more in women with diabetes than in women without diabetes independent of age and other CVD risk factors known to worsen with menopause.

Lower objectively measured physical activity is linked with perceived risk of hypoglycemia in type 1 diabetes.

AIMS: Compare physical activity (PA) levels in adults with and without type 1 diabetes and identify diabetes-specific barriers to PA. METHODS: Forty-four individuals with type 1 diabetes and 77 non-diabetic controls in the Coronary Artery Calcification in Type 1 Diabetes study wore an accelerometer for 2 weeks. Moderate-to-vigorous physical activity (MVPA) was compared by diabetes status using multiple linear regression. The Barriers to Physical Activity in Type 1 Diabetes questionnaire measured diabetes-specific barriers to PA, and the Clarke hypoglycemia awareness questionnaire measured hypoglycemia frequency. RESULTS: Individuals with type 1 diabetes engaged in less MVPA, fewer bouts of MVPA, and spent less time in MVPA bouts per week than individuals without diabetes (all p < 0.05), despite no difference in self-reported PA (p > 0.05). The most common diabetes-specific barrier to PA was risk of hypoglycemia. Individuals with diabetes reporting barriers spent less time in MVPA bouts per week than those not reporting barriers (p = 0.047). CONCLUSIONS: Individuals with type 1 diabetes engage in less MVPA than those without diabetes despite similar self-reported levels, with the main barrier being perceived risk of hypoglycemia. Adults with type 1 diabetes require guidance to meet current PA guidelines and reduce cardiovascular risk.

Declining Admission Rates And Thirty-Day Readmission Rates Positively Associated Even Though Patients Grew Sicker Over Time.

Programs from the Centers for Medicare and Medicaid Services simultaneously promote strategies to lower hospital admissions and readmissions. However, there is concern that hospitals in communities that successfully reduce admissions may be penalized, as patients that are ultimately hospitalized may be sicker and at higher risk of readmission. We therefore examined the relationship between changes from 2010 to 2013 in admission rates and thirty-day readmission rates for elderly Medicare beneficiaries. We found that communities with the greatest decline in admission rates also had the greatest decline in thirty-day readmission rates, even though hospitalized patients did grow sicker as admission rates declined. The relationship between changing admission and readmission rates persisted in models that measured observed readmission rates, risk-standardized readmission rates, and the combined rate of readmission and death. Our findings suggest that communities can reduce admission rates and readmission rates in parallel, and that federal policy incentivizing reductions in both outcomes does not create contradictory incentives.