Ageing Trajectories Of Health: Longitudinal Opportunities And Synergies Research Articles

Association between dietary (poly)phenol intake and the ATHLOS Healthy Ageing Scale in the Polish arm of the HAPIEE study.

Inverse association between (poly)phenol intake and age-related disorders has been demonstrated; however, little is known whether they affect comprehensively assessed healthy aging. The aim of this study was to evaluate the associations between the intake of (poly)phenol (including selected classes and subclasses) and healthy aging scores related to biopsychosocial aspects of health and functioning. A cross-sectional study was performed using data on 9774 randomly selected citizens of Krakow (Poland) who were 45-69years of age. Dietary (poly)phenol intake was evaluated using a food frequency questionnaire and matching food consumption data with the Phenol-Explorer database. The healthy aging scores were estimated from the ATHLOS Healthy Ageing Scale (HAS) developed by the Ageing Trajectories of Health-Longitudinal Opportunities and Synergies (ATHLOS) consortium. Beta coefficients were calculated using multivariable linear regression models. In multivariable adjusted models, there were significant positive associations between the ATHLOS HAS score and intake of total (poly)phenols (b per increase of 100mg/day = 0.081; 95% CI, 0.050; 0.112) and among main classes of (poly)phenols with phenolic acids (b = 0.139; 95% CI, 0.098; 0.180). Intake of remaining classes of (poly)phenols (flavonoids, lignans, stilbenes, and others) was not related to the ATHLOS HAS score. Among individual classes studied, hydroxycinnamic acids, flavonols, flavones, and dihydrochalcones were associated with better healthy aging. The findings suggest the beneficial effect of total dietary (poly)phenol and some classes and subclasses of (poly)phenol intake in terms of healthy aging in Poland. These findings should be confirmed in other settings and with prospective data.

Association between dietary (poly)phenol intake and the ATHLOS Healthy Ageing Scale in the Polish arm of the HAPIEE study.

Inverse association between (poly)phenol intake and age-related disorders has been demonstrated; however, little is known whether they affect comprehensively assessed healthy aging. The aim of this study was to evaluate the associations between the intake of (poly)phenol (including selected classes and subclasses) and healthy aging scores related to biopsychosocial aspects of health and functioning. A cross-sectional study was performed using data on 9774 randomly selected citizens of Krakow (Poland) who were 45-69years of age. Dietary (poly)phenol intake was evaluated using a food frequency questionnaire and matching food consumption data with the Phenol-Explorer database. The healthy aging scores were estimated from the ATHLOS Healthy Ageing Scale (HAS) developed by the Ageing Trajectories of Health-Longitudinal Opportunities and Synergies (ATHLOS) consortium. Beta coefficients were calculated using multivariable linear regression models. In multivariable adjusted models, there were significant positive associations between the ATHLOS HAS score and intake of total (poly)phenols (b per increase of 100mg/day = 0.081; 95% CI, 0.050; 0.112) and among main classes of (poly)phenols with phenolic acids (b = 0.139; 95% CI, 0.098; 0.180). Intake of remaining classes of (poly)phenols (flavonoids, lignans, stilbenes, and others) was not related to the ATHLOS HAS score. Among individual classes studied, hydroxycinnamic acids, flavonols, flavones, and dihydrochalcones were associated with better healthy aging. The findings suggest the beneficial effect of total dietary (poly)phenol and some classes and subclasses of (poly)phenol intake in terms of healthy aging in Poland. These findings should be confirmed in other settings and with prospective data.

Are healthy ageing trajectories suitable to identify rehabilitation needs of the ageing population? An exploratory study using ATHLOS cohort data.

The 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. Data 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. Healthy 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. Our 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.

Are healthy ageing trajectories suitable to identify rehabilitation needs of the ageing population? An exploratory study using ATHLOS cohort data.

The 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. Data 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. Healthy 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. Our 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.

Using multiple imputation and intervention-based scenarios to project the mobility of older adults

BackgroundProjections of the development of mobility limitations of older adults are needed for evidence-based policy making. The aim of this study was to generate projections of mobility limitations among older people in the United States, England, and Finland.MethodsWe applied multiple imputation modelling with bootstrapping to generate projections of stair climbing and walking limitations until 2026. A physical activity intervention producing a beneficial effect on self-reported activities of daily living measures was identified in a comprehensive literature search and incorporated in the scenarios used in the projections. We utilised the harmonised longitudinal survey data from the Ageing Trajectories of Health – Longitudinal Opportunities and Synergies (ATHLOS) project (N = 24,982).ResultsBased on the scenarios from 2012 to 2026, the prevalence of walking limitations will decrease from 9.4 to 6.4%. A physical activity intervention would decrease the prevalence of stair climbing limitations compared with no intervention from 28.9 to 18.9% between 2012 and 2026.ConclusionsA physical activity intervention implemented on older population seems to have a positive effect on maintaining mobility in the future. Our method provides an interesting option for generating projections by incorporating intervention-based scenarios.

Methodological challenges in harmonisation of the variables used as indicators of social capital in epidemiological studies of ageing – results of the ATHLOS project

AbstractThe present article aims to highlight methodological aspects related to understanding and conceptualising social capital for the purposes of population research as well as describing the key challenges in the harmonisation process of indicators of social capital. The study was conducted in the frame of the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) project. After a review of social capital theories developed in social science and a subsequent review of the documentation of 18 international cohorts, decision trees of the harmonisation of social variables were developed. The known-group validity was verified. The results focused on generalised trust, civic engagement and social participation are presented. The summary of the availability of any indicators of these concepts is classified in seven domains (generalised trust, political participation, religious participation, senior-specific participation, participation in sport groups, participation in volunteer/charity group activities, any participation) across surveys. The results of the analysis for known-group validity support the construct validity of the harmonised variables.

Determinants of Processing Speed Trajectories among Middle Aged or Older Adults, and Their Association with Chronic Illnesses: The English Longitudinal Study of Aging

The aim of this study was to identify latent groups of similar trajectories in processing speed through aging, as well as factors that are associated with these trajectories. In the context of the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) project, data from the English Longitudinal Study of Aging (ELSA) (n = 12099) were analyzed. Latent groups of similar trajectories in the processing scores as well as their predictors and covariates were investigated, using group-based trajectory models (GBTM). The coefficient estimates for potential group predictors correspond to parameters of multinomial logit functions that are integrated in the model. Potential predictors included sex, level of education, marital status, level of household wealth, level of physical activity, and history of smoking, while time-varying covariates included incidence of cardiovascular disease (CVD), diabetes mellitus, depressive symptoms, and sleep disturbances. Four trajectories were identified and named after their baseline scores and shapes: High (4.4%), Middle/Stable (31.5%), Low/Stable (44.5%), and Low Decline (19.6%). Female sex, higher levels of education, mild level of physical activity, having been married, and higher level of wealth were associated with a higher probability of belonging to any of the higher groups compared to the Low/Decline that was set as reference, while presence of CVD, diabetes mellitus, and depressive symptoms were associated with lower processing speed scores within most trajectories. All the aforementioned factors might be valid targets for interventions to reduce the burden of age-related cognitive impairment.

Trajectories of healthy ageing among older adults with multimorbidity: A growth mixture model using harmonised data from eight ATHLOS cohorts.

In 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. Our 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). Using 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. Three 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). Healthy 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.

Sex differences in mortality: results from a population-based study of 12 longitudinal cohorts

BACKGROUND:Women generally have longer life expectancy than men but have higher levels of disability and morbidity. Few studies have identified factors that explain higher mortality in men. The aim of this study was to identify potential factors contributing to sex differences in mortality at older age and to investigate variation across countries.METHODS:This study included participants age ≥ 50 yr from 28 countries in 12 cohort studies of the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) consortium. Using a 2-step individual participant data meta-analysis framework, we applied Cox proportional hazards modelling to investigate the association between sex and mortality across different countries. We included socioeconomic (education, wealth), lifestyle (smoking, alcohol consumption), social (marital status, living alone) and health factors (cardiovascular disease, diabetes, mental disorders) as covariates or interaction terms with sex to test whether these factors contributed to the mortality gap between men and women.RESULTS:The study included 179 044 individuals. Men had 60% higher mortality risk than women after adjustment for age (pooled hazard ratio [HR] 1.6; 95% confidence interval 1.5–1.7), yet the effect sizes varied across countries (I2 = 71.5%, HR range 1.1–2.4). Only smoking and cardiovascular diseases substantially attenuated the effect size (by about 22%).INTERPRETATION:Lifestyle and health factors may partially account for excess mortality in men compared with women, but residual variation remains unaccounted for. Variation in the effect sizes across countries may indicate contextual factors contributing to gender inequality in specific settings.

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

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

Metabolic dysregulation in older adults with depression and loneliness: The ATHLOS study

This study aimed to examine how loneliness contributes to metabolic dysregulation among older adults with depression and determine the relative contribution of loneliness to the development of chronic diseases in late adulthood. Harmonised data from the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) project were used. Concretely, the sample comprised 6195 participants (53.95% women; M = 61.30 years, SD = 7.11) from three European cohorts. Three groups were considered: control group (CG); depressive symptom episode group (DEP); and a group with depression and loneliness (DEP + LONE). A metabolic score was estimated using anthropometric and blood indicators, by means of multi-indicator multi-causes (MIMIC) modelling and after controlling for sociodemographic and health-related covariates. Group-comparison was based on measurement-invariance procedures. Multimorbidity development was predicted at follow-up considering the study group and relevant covariates. All the analyses were sex-specific. As a result, measurement invariance revealed the influence of group (ΔCFI = −0.017 for male participants and ΔCFI = −0.009 for female ones) on metabolic scores in both sexes. Metabolic scores were significantly lower (i.e., they had more metabolic risk) in DEP + LONE women in comparison to women from the other groups. DEP men showed the lowest metabolic scores but those from the DEP + LONE group showed meaningfully lower scores than CG men (d = 1.35). In terms of multimorbidity prediction, DEP + LONE group membership significantly predicted the outcome in both sexes; DEP group membership significantly predicted multimorbidity at follow-up in women. In summary, these results highlight the relevant contribution of loneliness in depression-related metabolic dysregulation in the short- (concurrent metabolic risk) and long-term (chronic condition development). Moreover, sex-specific mechanisms seem to be involved in metabolic alterations of depressed people showing loneliness feelings. This study calls for action to reduce the impact of loneliness in old age and to promote healthy ageing.

Ageing trajectories of health—longitudinal opportunities and synergies (ATHLOS) Healthy Ageing Scale in adults from 16 international cohorts representing 38 countries worldwide

BackgroundUniform international measurement tools for assessing healthy ageing are currently lacking.ObjectivesThe study assessed the novel comprehensive global Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) Healthy Ageing Scale, using...

Multimorbidity patterns in low-middle and high income regions: a multiregion latent class analysis using ATHLOS harmonised cohorts

ObjectivesOur aim was to determine clusters of non-communicable diseases (NCDs) in a very large, population-based sample of middle-aged and older adults from low- and middle-income (LMICs) and high-income (HICs) regions....

Education and wealth inequalities in healthy ageing in eight harmonised cohorts in the ATHLOS consortium: a population-based study

The 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. This 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. We 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. The 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. European Union Horizon 2020 Research and Innovation Programme.

Alcohol Drinking and Health in Ageing: A Global Scale Analysis of Older Individual Data through the Harmonised Dataset of ATHLOS.

We investigated the relation between alcohol drinking and healthy ageing by means of a validated health status metric, using individual data from the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) project. For the purposes of this study, the ATHLOS harmonised dataset, which includes information from individuals aged 65+ in 38 countries, was analysed (n = 135,440). Alcohol drinking was reflected by means of three harmonised variables: alcohol drinking frequency, current and past alcohol drinker. A set of 41 self-reported health items and measured tests were used to generate a specific health metric. In the harmonised dataset, the prevalence of current drinking was 47.5% while of past drinking was 26.5%. In the pooled sample, current alcohol drinking was positively associated with better health status among older adults ((b-coef (95% CI): 1.32(0.45 to 2.19)) and past alcohol drinking was inversely related (b-coef (95% CI): −0.83 (−1.51 to −0.16)) with health status. Often alcohol consumption appeared to be beneficial only for females in all super-regions except Africa, both age group categories (65–80 years old and 80+), both age group categories, as well as among all the financial status categories (all p < 0.05). Regional analysis pictured diverse patterns in the association for current and past alcohol drinkers. Our results report the need for specific alcohol intake recommendations among older adults that will help them maintain a better health status throughout the ageing process.

HEALTH TRAJECTORIES OVER TIME IN THE ATHLOS PROJECT: FINDINGS FROM MULTIPLE COHORTS

The ATHLOS (Ageing Trajectories of Health: Longitudinal Opportunities and Synergies) project is a consortium of 15 partners across Europe who are working together to understand patterns of healthy ageing trajectories, and to seek the factors that determine those patterns, in a harmonised dataset of 17 international cohort studies of ageing. During this symposium we will be presenting some of the work that has recently been carried out within this project. The symposium will consist of four talks: the first talk will introduce the project, and describe the preliminary work that took place within the first few years of the project, and the challenges faced by the consortium. The second talk will focus on the harmonisation process and on the development of the health metric, an indicator used to measure healthy ageing in this project. The third talk will focus on inequalities in healthy ageing, specifically investigating the impact of education and wealth across cohorts. Finally, in the last talk we will describe the role of lifestyle behaviours (specifically physical activity, smoking and alcohol consumption) and their impact on healthy ageing trajectories.

Stability of clinically relevant depression symptoms in old-age across 11 cohorts: a multi-state study.

To study the temporal dynamics of depression symptom episodes in old-age and the related influence of risk factors. Data from 41362 old adults (54.61% women; mean age=75.30, SD=6.20) from the Ageing Trajectories of Health - Longitudinal Opportunities and Synergies (ATHLOS) project were used. Depressive symptoms were followed over an 18-year period. A multi-state model, comprising three statuses (no depression, new clinically relevant episode of symptoms and episode persistence), was fitted. Multinomial regression was used to study the role of risk factors in status transition. Almost 85% of participants showed no depression, but prevalence became lower over time (B=-0.25, P<0.001). New episode point prevalence was over 5.30% with a significant probability of moving to persistence status (transition probability=0.27). Episode persistence became evident in 9.86% of episode status transitions, with increasing rate over time (B=0.54, P<0.01). Loneliness was proven to be the strongest predictor of episode emergence (OR=17.76) and persistence (OR=5.93). The course of depression tends to become chronic and unremitting in old-age. This study may help to plan interventions to tackle symptom escalation and risk factor influence.

Cohort Profile: The Ageing Trajectories of Health - Longitudinal Opportunities and Synergies (ATHLOS) project.

Cohort Profile : The Ageing Trajectories of Health - Longitudinal Opportunities and Synergies (ATHLOS) project