Effects of physical exercise in older adults with reduced physical capacity: meta-analysis of resistance exercise and multimodal exercise

Older adults with reduced physical capacity are at greater risk of progression to care dependency. Progressive resistance strength exercise and multimodal exercise have been studied to restore reduced physical capacity. To summarize the best evidence of the two exercise regimes, this meta-analysis study appraised randomized-controlled trials from published systematic reviews. Medline, Embase, and the Cochrane Database of Systematic Review and Cochrane Central Register of Controlled Clinical Trials were searched for relevant systematic reviews. Two reviewers independently screened the relevant systematic reviews to identify eligible trials, assessed trial methodological quality, and extracted data. RevMan 5.3 software was used to analyze data on muscle strength, physical functioning, activities of daily living, and falls. Twenty-three eligible trials were identified from 22 systematic reviews. The mean age of the trial participants was 75 years or older. Almost all multimodal exercise trials included muscle strengthening exercise and balance exercise. Progressive resistance exercise is effective in improving muscle strength of the lower extremity and static standing balance. Multimodal exercise is effective in improving muscle strength of the lower extremity, dynamic standing balance, gait speed, and chair stand. In addition, multimodal exercise is effective in reducing falls. Neither type of exercise was effective in improving activities of daily living. For older adults with reduced physical capacity, multimodal exercise appears to have a broad effect on improving muscle strength, balance, and physical functioning of the lower extremity, and reducing falls relative to progressive resistance exercise alone

Role of vitamin D supplementation in the management of musculoskeletal diseases: update from an European Society of Clinical and Economical Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) working group.

Vitamin D is a key component for optimal growth and for calcium-phosphate homeostasis. Skin photosynthesis is the main source of vitamin D. Limited sun exposure and insufficient dietary vitamin D supply justify vitamin D supplementation in certain age groups. In older adults, recommended doses for vitamin D supplementation vary between 200 and 2000 IU/day, to achieve a goal of circulating 25-hydroxyvitamin D (calcifediol) of at least 50 nmol/L. The target level depends on the population being supplemented, the assessed system, and the outcome. Several recent large randomized trials with oral vitamin D regimens varying between 2000 and 100,000 IU/month and mostly conducted in vitamin D-replete and healthy individuals have failed to detect any efficacy of these approaches for the prevention of fracture and falls. Considering the well-recognized major musculoskeletal disorders associated with severe vitamin D deficiency and taking into account a possible biphasic effects of vitamin D on fracture and fall risks, an European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) working group convened, carefully reviewed, and analyzed the meta-analyses of randomized controlled trials on the effects of vitamin D on fracture risk, falls or osteoarthritis, and came to the conclusion that 1000 IU daily should be recommended in patients at increased risk of vitamin D deficiency. The group also addressed the identification of patients possibly benefitting from a vitamin D loading dose to achieve early 25-hydroxyvitamin D therapeutic level or from calcifediol administration

Redesigning care for older people to preserve physical and mental capacity: WHO guidelines on community-level interventions in integrated care.

Islene Araujo de Carvalho and coauthors discuss the WHO guidelines on integrated care for older people

A call for standardised age-disaggregated health data.

The 2030 Sustainable Development Goals agenda calls for health data to be disaggregated by age. However, age groupings used to record and report health data vary greatly, hindering the harmonisation, comparability, and usefulness of these data, within and across countries. This variability has become especially evident during the COVID-19 pandemic, when there was an urgent need for rapid cross-country analyses of epidemiological patterns by age to direct public health action, but such analyses were limited by the lack of standard age categories. In this Personal View, we propose a recommended set of age groupings to address this issue. These groupings are informed by age-specific patterns of morbidity, mortality, and health risks, and by opportunities for prevention and disease intervention. We recommend age groupings of 5 years for all health data, except for those younger than 5 years, during which time there are rapid biological and physiological changes that justify a finer disaggregation. Although the focus of this Personal View is on the standardisation of the analysis and display of age groups, we also outline the challenges faced in collecting data on exact age, especially for health facilities and surveillance data. The proposed age disaggregation should facilitate targeted, age-specific policies and actions for health care and disease management

Prevalence, Awareness, Treatment, and Control of Hypertension and Its Associated Risk Factors: Results from Baseline Survey of SWADES Family Cohort Study

Introduction. Hypertension is one of the most important modifiable risk factors for cardiovascular diseases. The objective of this study is to estimate the prevalence, awareness, treatment, and control of hypertension and its associated risk factors in Ernakulam district, Kerala. Methods. In this prospective family-based cohort study, 573 families were included with a total of 997 participants aged 30 years and above. Baseline interviews were conducted in participant’s homes using a combination of self-structured and standardized questionnaire. Blood pressure and plasma glucose were assessed for each participant. Results. The prevalence of hypertension was 43%. It was slightly higher in women than men (43.7% vs. 41.4%). The mean systolic blood pressure in the hypertensive population was 141.9 mmHg and mean diastolic blood pressure was 85.3 mmHg. In total, 78% (86.2% in women, 62.9% in men) of the participants were aware of their hypertension. Among those aware, 60.4% (63.5% in women, 52.6% in men) of the participants were on treatment, and hypertension was controlled in 75.1% (77.5% women, 68% in men) of the participants on treatment. The prevalence of hypertension was higher among persons with comorbidities (diabetes 64.5%, transient ischemic attack 54.7%, and heart disease 64.4%). Prevalence was lower among persons who did regular vigorous intensity exercise versus those who did moderate intensity exercise (32% vs. 45.7%) and among nonsmokers versus smokers (42.2% vs. 46.6%). Conclusion. The prevalence of hypertension in Kerala is high. Although awareness is quite high, there is a need to improve the number of persons with hypertension taking treatment

Investigating the broad domains of intrinsic capacity, functional ability and environment: An exploratory graph analysis approach for improving analytical methodologies for measuring healthy aging

The current paper compared the empirical structure of 280 variables from the 2016 wave of the Health and Retirement Study (N = 16,327) estimated using exploratory graph analysis with a theoretical structure based on 20 broad domains of intrinsic capacity, functional ability and environment, identified in the International Classification of Functioning, Disability and Health compendium. The results showed that a structure with 21 first-order factors had the best fit to the data (i.e., lowest total entropy fit value) for both the training and validation sample. A second-order exploratory graph analysis was applied on the interfactor correlation matrix and identified five second-order factors. The five-factor structure presented a better fit than the theoretical three-factor structure (approximately) representing intrinsic capacity, functional ability and environment. A close inspection of the network structure generated by analyzing the rotated network loadings of the 21 first-order factors revealed an interplay between cognition, mobility, need for help with daily activities, walking capacity, physical capacity, liver functioning, positive affect and perceived mastery, low perceived control, and depression/negative mood. Combined, our results can help guide future research by providing a framework for estimating the structure of multi-domain aging research as well as generating questions that can be addressed in future research

Investigating the performance of Exploratory Graph Analysis and traditional techniques to identify the number of latent factors: A simulation and tutorial

R scripts used in the paper. Abstract: Exploratory graph analysis (EGA) is a new technique that was recently proposed within the framework of network psychometrics to estimate the number of factors underlying multivariate data. Unlike other methods, EGA produces a visual guide--–network plot–--that not only indicates the number of dimensions to retain, but also which items cluster together and their level of association. Although previous studies have found EGA to be superior to traditional methods, they are limited in the conditions considered. These issues are here addressed through an extensive simulation study that incorporates a wide range of plausible structures that may be found in practice, including continuous and dichotomous data, unidimensional and multidimensional structures. Additionally, two new EGA techiniques are presented, one that extends EGA to also deal with unidimensional structures, and the other based on the triangulated maximally filtered graph approach (EGAtmfg). Both EGA techniques are compared with five widely used and/or recommended factor analytic techniques. Overall, EGA and EGAtmfg are found to perform as well as the most accurate traditional method, parallel analysis, and to produce the best large-sample properties of all the methods evaluated. To increase use and transparency, we present a straightforward R tutorial on how to use and interpret EGA, and apply it to the scores from a well-known psychological instrument: the Marlowe-Crowne Social Desirability Scale