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Given the aging global population, identifying heart failure (HF) phenotypes has become crucial, as distinct disease characteristics can influence treatment and prognosis in older adults. This study aimed to analyze the association between clustering of cardiovascular risk factors and HF in older adults. A cross-sectional epidemiological study was conducted with 1322 older adults (55% women, mean age 70.4) seen in primary health care. Diagnosis of HF was performed by a cardiologist based on diagnostic tests and medical history. Cardiovascular risk factors included hypertension, diabetes, hypercholesterolemia, and smoking. Using logistic regression, potential associations were tested. Individual risk factor analysis showed that older adults with hypertension, diabetes, or hypercholesterolemia had up to 7.6 times higher odds to have HF. The cluster where older adults had only one risk factor instead of none increased the odds of HF by 53.0%. Additionally, the odds of older patients having HF ranged from 3.59 times for the two-risk factor cluster to 20.61 times for the simultaneous presence of all four factors. The analysis of clusters substantially increasing HF risk in older adults revealed the importance of individualizing subgroups with distinct HF pathophysiologies. The clinical significance of these clusters can be beneficial in guiding a more personalized therapeutic approach.

Objective: This study aimed to assess the mediation effects of lean mass and fat mass on the relationship between body mass index (BMI) and handgrip strength (HGS) in adolescents., Method: The sample included 118 adolescents (60 girls) aged 10-14 years. Body composition, determined from lean mass (LM) and fat mass (FM), was measured by dual-energy x-ray absorptiometry. HGS was measured using a digital dynamometer. Moderate-to-vigorous physical activity and sexual maturation, treated as covariates, were evaluated by accelerometry and pubic hair development, respectively. Spearman correlation and simple mediation analysis were used for statistical analysis., Results: A positive relationship was observed between BMI and HGS (rho = .364, p < .001), BMI and LM (rho = .466, p < .001), LM and HGS (rho = .784, p < .001), BMI and FM (rho = .907, p < .001), and FM and HGS (rho = .291, p = .001). LM was the only significant mediator of the relationship between BMI and HGS., Conclusion: Only LM mediated the association between BMI and HGS, almost entirely explaining the relationship. The findings reinforce the need to include LM measurements in routine strength testing. Furthermore, strategies focused on LM development may be promising in preventing low muscle strength in adolescents., (© 2023 Wiley Periodicals LLC.)

Introduction: We assessed whether midlife sensory and motor functions added to prediction models using the Cardiovascular Risk Factors, Aging, and Incidence of Dementia Score (CAIDE) and Framingham Risk Score (FRS) improve risk predictions of 10-year changes in biomarkers of neurodegeneration and Alzheimer's disease., Methods: Longitudinal data of N  = 1529 (mean age 49years) Beaver Dam Offspring Study participants from baseline, 5-year, and 10-year follow-up were included. We tested whether including baseline sensory (hearing, vision, olfactory) impairment and motor function measures improves CAIDE or FRS risk predictions of 10-year incidence of biomarker positivity of serum-based neurofilament light chain (NfL) and amyloid beta (Aβ) 42 /Aβ 40 using logistic regression., Results: Adding sensory and motor measures to CAIDE-only and FRS-only models significantly improved NfL and Aβ 42 /Aβ 40 positivity predictions in adults above the age of 55., Discussion: Including midlife sensory and motor function improved long-term biomarker positivity predictions. Non-invasive sensory and motor assessments could contribute to cost-effective screening tools that identify individuals at risk for neurodegeneration early to target interventions and preventions., Highlights: Sensory and motor measures improve risk prediction models of neurodegenerative biomarkersSensory and motor measures improve risk prediction models of AD biomarkersPrediction improvements were strongest in late midlife (adults >55 years of age)Sensory and motor assessments may help identify high-risk individuals early., Competing Interests: The authors have no conflicts of interest to report. Author disclosures are available in the supporting information [Link], [Link]., (© 2024 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: We aimed to assess whether midlife sensory and motor functions improve risk prediction of 10-year cognitive decline and impairment when added to risk prediction models using the Cardiovascular Risk Factors, Aging, and Incidence of Dementia Score (CAIDE) and Framingham Risk Score (FRS)., Methods: Longitudinal data of N  = 1529 (mean age 49 years; 54% women) Beaver Dam Offspring Study (BOSS) participants from baseline, 5 and 10-year follow-up were included. We tested whether including baseline sensory (hearing, vision, olfactory) impairment and motor function improves CAIDE or FRS risk predictions of 10-year cognitive decline or cognitive impairment incidence using logistic regressions., Results: Adding sensory and motor measures to CAIDE-only and FRS-only models significantly improved areas under the curve for cognitive decline and impairment models., Discussion: Including midlife sensory and motor function improved risk predictions of long-term cognitive decline and impairment in middle-aged to older adults. Sensory and motor assessments could contribute to cost-effective and non-invasive screening tools that identify high-risk individuals earlier to target intervention and prevention strategies., Highlights: Sensory and motor measures improve risk prediction models of cognitive decline.Sensory and motor measures improve risk prediction models of cognitive impairment.Prediction improvements were strongest in midlife (adults < 55 years of age).Sensory and motor changes may help identify high-risk individuals early., Competing Interests: The authors have no conflict of interest to report. Author disclosures are available in the supporting information., (© 2024 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

This study's aim was to identify risk factors associated with sensorineural and neurocognitive function (brain aging) in older adults. In N  = 1,478 Epidemiology of Hearing Loss Study participants (aged 64-100 years, 59% women), we conducted sensorineural and cognitive tests, which were combined into a summary measure using Principal Component Analysis (PCA). Participants with a PCA score <-1 standard deviation (SD) were considered to have brain aging. Incident brain aging was defined as PCA score <-1 SD at 5-year follow-up among participants who had a PCA score ≥-1 SD at baseline. Logistic regression and Poisson models were used to estimate associations between baseline risk factors of lifestyle, vascular and metabolic health, and inflammation and prevalent or incident brain aging, respectively. In an age-sex adjusted multivariable model, not consuming alcohol (odds ratio(OR) = 1.77, 95% confidence Interval (CI) = 1.18,2.66), higher interleukin-6 levels (OR = 1.30, 95% CI = 1.03,1.64), and depressive symptoms (OR = 2.44, 95% CI = 1.63,3.67) were associated with a higher odds of having brain aging, while higher education had protective effects (OR = 0.55, 95% CI = 0.33,0.94). A history of stroke, arterial stiffness, and obesity were associated with an increased risk of developing brain aging during the five years of follow-up. Lifestyle, vascular, metabolic and inflammatory factors were associated with brain aging in older adults, which adds to the evidence of shared pathways for sensorineural and neurocognitive declines in aging. Targeting these shared central processing etiological factors with interventions may lead to retention of better neurological function, benefiting multiple systems, i.e., hearing, smell, and cognition, ultimately helping older adults retain independence and higher quality of life longer., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Merten, Fischer, Pinto, Chappell and Schubert.)