RESUMO
OBJECTIVE: Ongoing research has evidenced the importance of muscle measurement in predicting adverse outcomes. Measurement of other muscles is promising in current research. This study aimed to determine the correlation between temporal muscle thickness (TMT) and appendicular lean soft tissue (ALSTI) in older adults. DESIGN: Cross-sectional study. SETTINGS AND PARTICIPANTS: Single cohort gathered in Gothenburg, Sweden, consisting of individuals born in 1944 (n = 1203). METHODS: We studied 657 magnetic resonance images to measure TMT. Comparisons of TMT with dual-energy X-ray absorptiometry ALSTI (kg/m2) as a reference standard were performed. Finally, TMT associations with cognition evaluated using the Mini-Mental State Examination (MMSE), gait speed, and handgrip strength were explored with linear regressions. RESULTS: The correlation between TMT and ALSTI was weak yet significant (r = 0.277, P < .001). TMT exhibited significant associations with MMSE (estimate = 0.168, P = .002), gait speed (estimate = 1.795, P < .001), and ALSTI (estimate = 0.508, P < .001). These associations varied when analyzed by sex. In women, TMT was significantly associated with gait speed (estimate = 1.857, P = .005) and MMSE (estimate = 0.223, P = .003). In men, TMT scores were significantly correlated with ALSTI scores (estimate = 0.571, P < .001). CONCLUSION AND IMPLICATIONS: Repurposing head images can be an accessible alternative to detect muscle mass and ultimately detect sarcopenia. These studies have the potential to trigger interventions or further evaluation to improve the muscle and overall health of individuals. However, additional research is warranted before translating these findings into clinical practice.
Assuntos
Força da Mão , Sarcopenia , Masculino , Humanos , Feminino , Idoso de 80 Anos ou mais , Idoso , Força da Mão/fisiologia , Músculo Temporal , Estudos Transversais , Sarcopenia/diagnóstico por imagem , Cognição/fisiologia , Força Muscular/fisiologiaRESUMO
Over recent decades, epidemiology has made significant contributions to our understanding of dementia, translating scientific discoveries into population health. Here, we propose reframing dementia epidemiology as "population neuroscience," blending techniques and models from contemporary neuroscience with those of epidemiology and biostatistics. On the basis of emerging evidence and newer paradigms and methods, population neuroscience will minimize the bias typical of traditional clinical research, identify the relatively homogenous subgroups that comprise the general population, and investigate broader and denser phenotypes of dementia and cognitive impairment. Long-term follow-up of sufficiently large study cohorts will allow the identification of cohort effects and critical windows of exposure. Molecular epidemiology and omics will allow us to unravel the key distinctions within and among subgroups and better understand individuals' risk profiles. Interventional epidemiology will allow us to identify the different subgroups that respond to different treatment/prevention strategies. These strategies will inform precision medicine. In addition, insights into interactions between disease biology, personal and environmental factors, and social determinants of health will allow us to measure and track disease in communities and improve population health. By placing neuroscience within a real-world context, population neuroscience can fulfill its potential to serve both precision medicine and population health.