Dataset Information

Predictors of pain in general ageing populations: results from a multi-country analysis based on ATHLOS harmonized database.

ABSTRACT: BACKGROUND:Pain is a common symptom, often associated with neurological and musculoskeletal conditions, and experienced especially by females and by older people, and with increasing trends in general populations. Different risk factors for pain have been identified, but generally from studies with limited samples and a limited number of candidate predictors. The aim of this study is to evaluate the predictors of pain from a large set of variables and respondents. METHODS:We used part of the harmonized dataset of ATHLOS project, selecting studies and waves with a longitudinal course, and in which pain was absent at baseline and with no missing at follow-up. Predictors were selected based on missing distribution and univariable association with pain, and were selected from the following domains: Socio-demographic and economic characteristics, Lifestyle and health behaviours, Health status and functional limitations, Diseases, Physical measures, Cognition, personality and other psychological measures, and Social environment. Hierarchical logistic regression models were then applied to identify significant predictors. RESULTS:A total of 13,545 subjects were included of whom 5348 (39.5%) developed pain between baseline and the average 5.2?years' follow-up. Baseline risk factors for pain were female gender (OR 1.34), engaging in vigorous exercise (OR 2.51), being obese (OR 1.36) and suffering from the loss of a close person (OR 1.88) whereas follow-up risk factors were low energy levels/fatigue (1.93), difficulties with walking (1.69), self-rated health referred as poor (OR 2.20) or average to moderate (OR 1.57) and presence of sleep problems (1.80). CONCLUSIONS:Our results showed that 39.5% of respondents developed pain over a five-year follow-up period, that there are proximal and distal risk factors for pain, and that part of them are directly modifiable. Actions aimed at improving sleep, reducing weight among obese people and treating fatigue would positively impact on pain onset, and avoiding vigorous exercise should be advised to people aged 60 or over, in particular if female or obese.

SUBMITTER: Raggi A

PROVIDER: S-EPMC7201730 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Predictors of pain in general ageing populations: results from a multi-country analysis based on ATHLOS harmonized database.

Raggi Alberto A Leonardi Matilde M Mellor-Marsá Blanca B Moneta Maria V MV Sanchez-Niubo Albert A Tyrovolas Stefanos S Giné-Vázquez Iago I Haro Josep M JM Chatterji Somnath S Bobak Martin M Ayuso-Mateos Jose L JL Arndt Holger H Hossin Muhammad Z MZ Bickenbach Jerome J Koskinen Seppo S Tobiasz-Adamczyk Beata B Panagiotakos Demosthenes D Corso Barbara B

The journal of headache and pain 20200506 1

<h4>Background</h4>Pain is a common symptom, often associated with neurological and musculoskeletal conditions, and experienced especially by females and by older people, and with increasing trends in general populations. Different risk factors for pain have been identified, but generally from studies with limited samples and a limited number of candidate predictors. The aim of this study is to evaluate the predictors of pain from a large set of variables and respondents.<h4>Methods</h4>We used ...[more]

PMID: 32375641

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Project description:BackgroundThe ageing process is highly heterogeneous leading to diverse ageing trajectories. Such trajectories have been modelled to study trends and determinants of ageing and could potentially be used to inform the planning of rehabilitation services at population level. The objective of this paper was to explore whether healthy ageing trajectories are suitable to identify targets for rehabilitation interventions for the ageing population.MethodsData from the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) harmonized cohort and the English Longitudinal Study of Ageing (ELSA), which is included in ATHLOS, were used. Growth mixture models were implemented to replicate healthy ageing trajectories modelled elsewhere as 'high stable', 'low stable', and 'rapid decline'. Regularized partial correlation networks were used to estimate expected-influence and bridge expected-influence centrality measures.ResultsHealthy ageing trajectories modelled with ATHLOS (N = 131116) and ELSA (N = 14904) were consistent with previous work. At the first individual wave, prevalence of problems of respondents in the 'high stable' and 'rapid decline' trajectories were comparable; at the last individual wave, prevalence remained similar for the 'high stable' but increased substantially in all domains for the 'rapid decline' trajectory. Expected-influence centrality measures provided different results than prevalence estimates. For instance, in the first individual wave mobility and carrying, moving, and handling objects had highest impact on overall functioning for the 'rapid decline' and 'high stable' trajectories, while the most prevalent functioning problems concerned cognition, pain, as well as energy and drive functions.ConclusionsOur study stressed the relevance of healthy ageing trajectories for identifying functioning domains and categories that need to be targeted by rehabilitation services in a heterogeneous ageing population. The use of such trajectories at country level has the potential to make a meaningful contribution to the planning and delivery of rehabilitation interventions through health systems and to informed policy making.

Project description:BackgroundThe rapid growth of the size of the older population is having a substantial effect on health and social care services in many societies across the world. Maintaining health and functioning in older age is a key public health issue but few studies have examined factors associated with inequalities in trajectories of health and functioning across countries. The aim of this study was to investigate trajectories of healthy ageing in older men and women (aged ≥45 years) and the effect of education and wealth on these trajectories.MethodsThis population-based study is based on eight longitudinal cohorts from Australia, the USA, Japan, South Korea, Mexico, and Europe harmonised by the EU Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) consortium. We selected these studies from the repository of 17 ageing studies in the ATHLOS consortium because they reported at least three waves of collected data. We used multilevel modelling to investigate the effect of education and wealth on trajectories of healthy ageing scores, which incorporated 41 items of physical and cognitive functioning with a range between 0 (poor) and 100 (good), after adjustment for age, sex, and cohort study.FindingsWe used data from 141 214 participants, with a mean age of 62·9 years (SD 10·1) and an age range of 45-106 years, of whom 76 484 (54·2%) were women. The earliest year of baseline data was 1992 and the most recent last follow-up year was 2015. Education and wealth affected baseline scores of healthy ageing but had little effect on the rate of decrease in healthy ageing score thereafter. Compared with those with primary education or less, participants with tertiary education had higher baseline scores (adjusted difference in score of 10·54 points, 95% CI 10·31-10·77). The adjusted difference in healthy ageing score between lowest and highest quintiles of wealth was 8·98 points (95% CI 8·74-9·22). Among the eight cohorts, the strongest inequality gradient for both education and wealth was found in the Health Retirement Study from the USA.InterpretationThe apparent difference in baseline healthy ageing scores between those with high versus low education levels and wealth suggests that cumulative disadvantage due to low education and wealth might have largely deteriorated health conditions in early life stages, leading to persistent differences throughout older age, but no further increase in ageing disparity after age 70 years. Future research should adopt a lifecourse approach to investigate mechanisms of health inequalities across education and wealth in different societies.FundingEuropean Union Horizon 2020 Research and Innovation Programme.

Project description:ObjectivesIn this study we aimed to 1) describe healthy ageing trajectory patterns, 2) examine the association between multimorbidity and patterns of healthy ageing trajectories, and 3) evaluate how different groups of diseases might affect the projection of healthy ageing trajectories over time.Setting and participantsOur study was based on 130880 individuals from the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) harmonised dataset, as well as 9171 individuals from Waves 2-7 of the English Longitudinal Study of Ageing (ELSA).MethodsUsing a healthy ageing index score, which comprised 41 items, covering various domains of health and ageing, as outcome, we employed the growth mixture model approach to identify the latent classes of individuals with different healthy ageing trajectories. A multinomial logistic regression was conducted to assess if and how multimorbidity status and multimorbidity patterns were associated with changes in healthy ageing, controlled for sociodemographic and lifestyle risk factors.ResultsThree similar patterns of healthy ageing trajectories were identified in the ATHLOS and ELSA datasets: 1) a 'high stable' group (76% in ATHLOS, 61% in ELSA), 2) a 'low stable' group (22% in ATHLOS, 36% in ELSA) and 3) a 'rapid decline' group (2% in ATHLOS, 3% in ELSA). Those with multimorbidity were 1.7 times (OR = 1.7, 95% CI: 1.4-2.1) more likely to be in the 'rapid decline' group and 11.7 times (OR = 11.7 95% CI: 10.9-12.6) more likely to be in the 'low stable' group, compared with people without multimorbidity. The cardiorespiratory/arthritis/cataracts group was associated with both the 'rapid decline' and the 'low stable' groups (OR = 2.1, 95% CI: 1.2-3.8 and OR = 9.8, 95% CI: 7.5-12.7 respectively).ConclusionHealthy ageing is heterogeneous. While multimorbidity was associated with higher odds of having poorer healthy ageing trajectories, the extent to which healthy ageing trajectories were projected to decline depended on the specific patterns of multimorbidity.

Dataset Information

Predictors of pain in general ageing populations: results from a multi-country analysis based on ATHLOS harmonized database.

Publications

Predictors of pain in general ageing populations: results from a multi-country analysis based on ATHLOS harmonized database.

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