Dataset Information

Development of a common scale for measuring healthy ageing across the world: results from the ATHLOS consortium.

ABSTRACT:

Background

Research efforts to measure the concept of healthy ageing have been diverse and limited to specific populations. This diversity limits the potential to compare healthy ageing across countries and/or populations. In this study, we developed a novel measurement scale of healthy ageing using worldwide cohorts.

Methods

In the Ageing Trajectories of Health-Longitudinal Opportunities and Synergies (ATHLOS) project, data from 16 international cohorts were harmonized. Using ATHLOS data, an item response theory (IRT) model was used to develop a scale with 41 items related to health and functioning. Measurement heterogeneity due to intra-dataset specificities was detected, applying differential item functioning via a logistic regression framework. The model accounted for specificities in model parameters by introducing cohort-specific parameters that rescaled scores to the main scale, using an equating procedure. Final scores were estimated for all individuals and converted to T-scores with a mean of 50 and a standard deviation of 10.

Results

A common scale was created for 343 915 individuals above 18 years of age from 16 studies. The scale showed solid evidence of concurrent validity regarding various sociodemographic, life and health factors, and convergent validity with healthy life expectancy (r = 0.81) and gross domestic product (r = 0.58). Survival curves showed that the scale could also be predictive of mortality.

Conclusions

The ATHLOS scale, due to its reliability and global representativeness, has the potential to contribute to worldwide research on healthy ageing.

SUBMITTER: Sanchez-Niubo A

PROVIDER: S-EPMC8271194 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Publications

Development of a common scale for measuring healthy ageing across the world: results from the ATHLOS consortium.

Sanchez-Niubo Albert A Forero Carlos G CG Wu Yu-Tzu YT Giné-Vázquez Iago I Prina Matthew M De La Fuente Javier J Daskalopoulou Christina C Critselis Elena E De La Torre-Luque Alejandro A Panagiotakos Demosthenes D Arndt Holger H Ayuso-Mateos José Luis JL Bayes-Marin Ivet I Bickenbach Jerome J Bobak Martin M Caballero Francisco Félix FF Chatterji Somnath S Egea-Cortés Laia L García-Esquinas Esther E Leonardi Matilde M Koskinen Seppo S Koupil Ilona I Mellor-Marsá Blanca B Olaya Beatriz B Pająk Andrzej A Prince Martin M Raggi Alberto A Rodríguez-Artalejo Fernando F Sanderson Warren W Scherbov Sergei S Tamosiunas Abdonas A Tobias-Adamczyk Beata B Tyrovolas Stefanos S Haro Josep Maria JM

International journal of epidemiology 20210701 3

<h4>Background</h4>Research efforts to measure the concept of healthy ageing have been diverse and limited to specific populations. This diversity limits the potential to compare healthy ageing across countries and/or populations. In this study, we developed a novel measurement scale of healthy ageing using worldwide cohorts.<h4>Methods</h4>In the Ageing Trajectories of Health-Longitudinal Opportunities and Synergies (ATHLOS) project, data from 16 international cohorts were harmonized. Using ATH ...[more]

PMID: 33274372

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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.

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Dataset Information

Development of a common scale for measuring healthy ageing across the world: results from the ATHLOS consortium.

Background

Methods

Results

Conclusions

Publications

Development of a common scale for measuring healthy ageing across the world: results from the ATHLOS consortium.

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