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1.
Am J Prev Cardiol ; 18: 100646, 2024 Jun.
Article in English | MEDLINE | ID: mdl-38550633

ABSTRACT

Objective: Obesity is associated with a higher risk of cardiovascular disease. Understanding the associations between comprehensive health parameters and body mass index (BMI) may lead to targeted prevention efforts. Methods: Project Baseline Health Study (PBHS) participants were divided into six BMI categories: underweight (BMI <18.5 kg/m2), normal weight (BMI 18.5-24.9 kg/m2), overweight (BMI 25-29.9 kg/m2), class I obesity (30-34.9 kg/m2), class II obesity (35-39.9 kg/m2), and class III obesity (BMI ≥40 kg/m2). Demographic, cardiometabolic, mental health, and physical health parameters were compared across BMI categories, and multivariable logistic regression models were fit to evaluate associations. Results: A total of 2,493 PBHS participants were evaluated. The mean age was 50±17.2 years; 55 % were female, 12 % Hispanic, 16 % Black, and 10 % Asian. The average BMI was 28.4 kg/m2±6.9. The distribution of BMI by age group was comparable to the 2017-2018 National Health and Nutrition Examination Survey (NHANES) dataset. The obesity categories had higher proportions of participants with CAC scores >0, hypertension, diabetes, lower HDL-C, lower vitamin D, higher triglycerides, higher hsCRP, lower mean step counts, higher mean PHQ-9 scores, and higher mean GAD-7 scores. Conclusion: We identified associations of cardiometabolic and mental health characteristics with BMI, thereby providing a deeper understanding of cardiovascular health across BMI.

2.
Circ Genom Precis Med ; 16(3): 216-223, 2023 06.
Article in English | MEDLINE | ID: mdl-37039013

ABSTRACT

BACKGROUND: Epigenetic clocks estimate chronologic age using methylation levels at specific loci. We tested the hypothesis that accelerated epigenetic aging is associated with abnormal values in a range of clinical, imaging, and laboratory characteristics. METHODS: The Project Baseline Health Study recruited 2502 participants, including 1661 with epigenetic age estimates from the Horvath pan-tissue clock. We classified individuals with extreme values as having epigenetic age acceleration (EAA) or epigenetic age deceleration. A subset of participants with longitudinal methylation profiling was categorized as accelerated versus nonaccelerated. Using principal components analysis, we created phenoclusters using 122 phenotypic variables and compared individuals with EAA versus epigenetic age deceleration, and at one year of follow-up, using logistic regression models adjusted for sex (false discovery rate [Q] <0.10); in secondary exploratory analyses, we tested individual clinical variables. RESULTS: The EAA (n=188) and epigenetic age deceleration (n=195) groups were identified as having EAA estimates ≥5 years or ≤-5 years, respectively. In primary analyses, individuals with EAA had higher values for phenoclusters summarizing lung function and lipids, and lower values for a phenocluster representing physical function. In secondary analyses of individual variables, neutrophils, body mass index, and waist circumference were significantly higher in individuals with EAA (Q<0.10). No phenoclusters were significantly different between participants with accelerated (n=148) versus nonaccelerated (n=112) longitudinal aging. CONCLUSIONS: We report multiple cardiometabolic, hematologic, and physical function features characterizing individuals with EAA. These highlight factors that may mediate the adverse effects of aging and identify potential targets for study of mitigation of these effects. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03154346.


Subject(s)
Cardiovascular Diseases , Epigenesis, Genetic , Humans , Child, Preschool , DNA Methylation , Aging/genetics , Epigenomics
3.
PLoS One ; 16(7): e0254153, 2021.
Article in English | MEDLINE | ID: mdl-34324495

ABSTRACT

Newer data platforms offer increased opportunity to share multidimensional health data with research participants, but the preferences of participants for which data to receive and how is evolving. Our objective is to describe the preferences and expectations of participants for the return of individual research results within Project Baseline Health Study (PBHS). The PBHS is an ongoing, multicenter, longitudinal cohort study with data from four initial enrollment sites. PBHS participants are recruited from the general population along with groups enriched for heart disease and cancer disease risk. Cross-sectional data on return of results were collected in 2017-2018 from an (1) in-person enrollment survey (n = 1,890), (2) benchmark online survey (n = 1,059), and (3) participant interviews (n = 21). The main outcomes included (1) preferences for type of information to be added next to returned results, (2) participant plans for sharing returned results with a non-study clinician, and (3) choice to opt-out of receiving genetic results. Results were compared by sociodemographic characteristics. Enrollment and benchmark survey respondents were 57.1% and 53.5% female, and 60.0% and 66.2% white, respectively. Participants preferred the following data types be added to returned results in the future: genetics (29.9%), heart imaging, (16.4%), study watch (15.8%), and microbiome (13.3%). Older adults (OR 0.60, 95% CI: 0.41-0.87) were less likely to want their genetic results returned next. Forty percent of participants reported that they would not share all returned results with their non-study clinicians. Black (OR 0.64, 95% CI 0.43-0.95) and Asian (OR 0.47, 95% CI 0.30-0.73) participants were less likely, and older participants more likely (OR 1.45-1.61), to plan to share all results with their clinician than their counterparts. At enrollment, 5.8% of participants opted out of receiving their genetics results. The study showed that substantial heterogeneity existed in participant's preferences and expectations for return of results, and variations were related to sociodemographic characteristics.


Subject(s)
Information Dissemination , Patient Preference , Aged , Cross-Sectional Studies , Female , Humans , Longitudinal Studies , Male , Middle Aged
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