Dataset Information

Predictors of metabolic syndrome in community-dwelling older adults.

ABSTRACT:

Objectives

The metabolic syndrome has been associated with a variety of individual variables, including demographics, lifestyle, clinical measures and physical performance. We aimed to identify independent predictors of the prevalence and incidence of metabolic syndrome in a large cohort of older adults.

Methods

The Longitudinal Aging Study Amsterdam is a prospective cohort including community-dwelling adults aged 55-85 years. Metabolic syndrome was defined according to criteria of the National Cholesterol Education Program Adult Treatment Panel III. The incidence of metabolic syndrome was calculated over a period of three years. Stepwise backward logistic regression analyses were used to identify predictors, including variables for demographics, lifestyle, clinical measures and physical performance, both in a cross-sectional cohort (n = 1292) and a longitudinal sub-cohort (n = 218).

Results

Prevalence and incidence of metabolic syndrome were 37% (n = 479) and 30% (n = 66), respectively. Cross-sectionally, heart disease (OR: 1.91, 95% CI: 1.37-2.65), peripheral artery disease (OR: 2.13, 95% CI: 1.32-3.42), diabetes (OR: 4.74, 95% CI: 2.65-8.48), cerebrovascular accident (OR: 1.92, 95% CI: 1.09-3.37), and a higher Body Mass Index (OR: 1.32, 95% CI: 1.26-1.38) were significant independent predictors of metabolic syndrome. Longitudinally, Body Mass Index (OR: 1.16, 95% CI: 1.05-1.27) was an independent predictor of metabolic syndrome.

Conclusion

Four age related diseases and a higher Body Mass Index were the only predictors of metabolic syndrome in the cross-sectional cohort, despite the large variety of variables included in the multivariable analysis. In the longitudinal sub-cohort, a higher Body Mass Index was predictive of developing metabolic syndrome.

SUBMITTER: Van Ancum JM

PROVIDER: S-EPMC6209297 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predictors of metabolic syndrome in community-dwelling older adults.

Van Ancum Jeanine M JM Jonkman Nini H NH van Schoor Natasja M NM Tressel Emily E Meskers Carel G M CGM Pijnappels Mirjam M Maier Andrea B AB

PloS one 20181031 10

<h4>Objectives</h4>The metabolic syndrome has been associated with a variety of individual variables, including demographics, lifestyle, clinical measures and physical performance. We aimed to identify independent predictors of the prevalence and incidence of metabolic syndrome in a large cohort of older adults.<h4>Methods</h4>The Longitudinal Aging Study Amsterdam is a prospective cohort including community-dwelling adults aged 55-85 years. Metabolic syndrome was defined according to criteria o ...[more]

PMID: 30379967

Similar Datasets

Project description:BackgroundMetabolic Syndrome (MetS) is a cluster of risk factors for diabetes and cardiovascular diseases with pathophysiology strongly linked to aging. A range of circulatory metabolic biomarkers such as inflammatory adipokines have been associated with MetS; however, the diagnostic power of these markers as MetS risk correlates in elderly has yet to be elucidated. This cross-sectional study investigated the diagnostic power of circulatory metabolic biomarkers as MetS risk correlates in older adults.MethodsHundred community dwelling older adults (mean age: 68.7 years) were recruited in a study, where their blood pressure, body composition and Pulse Wave Velocity (PWV) were measured; and their fasting capillary and venous blood were collected. The components of the MetS; and the serum concentrations of Interleukin-6 (IL-6), Tumor Necrosis Factor-α (TNF-α), Plasminogen Activator Inhibitor-I (PAI-I), Leptin, Adiponectin, Resistin, Cystatin-C, C-Reactive Protein (CRP), insulin and ferritin were measured within the laboratory, and the HOMA1-IR and Atherogenic Index of Plasma (AIP) were calculated.ResultsApart from other markers which were related with some cardiometabolic (CM) risk, after Bonferroni correction insulin had significant association with all components of Mets and AIP. These associations also remained significant in multivariate regression. The multivariate odds ratio (OR with 95% confidence interval (CI)) showed a statistically significant association between IL-6 (OR: 1.32 (1.06-1.64)), TNF-α (OR: 1.37 (1.02-1.84)), Resistin (OR: 1.27 (1.04-1.54)) and CRP (OR: 1.29 (1.09-1.54)) with MetS risk; however, these associations were not found when the model was adjusted for age, dietary intake and adiposity. In unadjusted models, insulin was consistently statistically associated with at least two CM risk factors (OR: 1.33 (1.16-1.53)) and MetS risk (OR: 1.24 (1.12-1.37)) and in adjusted models it was found to be associated with at least two CM risk factors and MetS risk (OR: 1.87 (1.24-2.83) and OR: 1.25 (1.09-1.43)) respectively. Area under curve (AUC) for receiver operating characteristics (ROC) demonstrated a good discriminatory diagnostics power of insulin with AUC: 0.775 (0.683-0.866) and 0.785 by cross validation and bootstrapping samples for at least two CM risk factors and AUC: 0.773 (0.653-0.893) and 0.783 by cross validation and bootstrapping samples for MetS risk. This was superior to all other AUC reported from the ROC analysis of other biomarkers. Area under precision-recall curve for insulin was also superior to all other markers (0.839 and 0.586 for at least two CM risk factors and MetS, respectively).ConclusionFasting serum insulin concentration was statistically linked with MetS and its risk, and this link is stronger than all other biomarkers. Our ROC analysis confirmed the discriminatory diagnostic power of insulin as CM and MetS risk correlate in older adults.

Project description:Reablement is a rehabilitation intervention for community-dwelling older adults, which has recently been implemented in several countries. Its purpose is to improve functional ability in daily occupations (everyday activities) perceived as important by the older person. Performance and satisfaction with performance in everyday life are the major outcomes of reablement. However, the evidence base concerning which factors predict better outcomes and who receives the greatest benefit in reablement is lacking.The objective of this study was to determine the potential factors that predict occupational performance and satisfaction with that performance at 10 weeks follow-up.The sample in this study was derived from a nationwide clinical controlled trial evaluating the effects of reablement in Norway and consisted of 712 participants living in 34 municipalities. Multiple linear regression was used to investigate possible predictors of occupational performance (COPM-P) and satisfaction with that performance (COPM-S) at 10 weeks follow-up based on the Canadian Occupational Performance Measure (COPM).The results indicate that the factors that significantly predicted better COPM-P and COPM-S outcomes at 10 weeks follow-up were higher baseline scores of COPM-P and COPM-S respectively, female sex, having a fracture as the major health condition and high motivation for rehabilitation. Conversely, the factors that significantly predicted poorer COPM-P and COPM-S outcomes were having a neurological disease other than stroke, having dizziness/balance problems as the major health condition and having pain/discomfort. In addition, having anxiety/depression was a predictor of poorer COPM-P outcomes. The two regression models explained 38.3% and 38.8% of the total variance of the dependent variables of occupational performance and satisfaction with that performance, respectively.The results indicate that diagnosis, functional level, sex and motivation are significant predictors of outcomes following reablement.

Project description:BackgroundWith the advancing age of the population, and increasing demands on healthcare services, community participation has become an important consideration for healthy ageing. Low levels of community participation have been linked to increased mortality and social isolation. The extent to which community participation has been measured objectively in older adults remains scarce. This study aims to describe where and how older adults participate in the community and determine the feasibility of measurement methods for community participation.MethodsThis observational cross-sectional study obtained data from 46 community dwelling older adults. A combination of Global Positioning Systems (GPS), accelerometry, and self-reported diaries were used over a 7-day monitoring period. Feasibility of methods were determined by calculating the loss of GPS data, questionnaires, and comparison of self-reported locations with GPS co-ordinates. Relationships between community participation, physical activity, social interactions, health related quality of life, sleep quality and loneliness were explored.ResultsOlder adults took a median (IQR) of 15 (9.25-18.75) trips out of home over the 7-day monitoring period, most frequently visiting commercial and recreational locations. In-home activities were mainly sedentary in nature, with out of home activities dependent on location type. Self-reported and GPS measures of trips out of home and the locations visited were significantly correlated (self-report 15.7 (5.6) GPS 14.4 (5.8) (r = 0.94)). Significant correlations between both the number of trips taken from home, with social interactions (r = 0.62) and the minutes of moderate to vigorous physical activity (MVPA) (r = 0.43) were observed. Daily MVPA was higher in participants who visited local walk/greenspaces (r = 0.48).ConclusionParticipants performed more activities with social interactions out of home and visited commercial locations most frequently. The combination of GPS, accelerometry and self-report methods provided a detailed picture of community participation for older adults. Further research is required with older adults of varying health status to generalise the relationships between community participation, location and physical activity.Trial registrationEthical approval was gained from the Flinders University Social and Behavioural Research Ethics Committee (protocol no. 8176).

Dataset Information

Predictors of metabolic syndrome in community-dwelling older adults.

Objectives

Methods

Results

Conclusion

Publications

Predictors of metabolic syndrome in community-dwelling older adults.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets