Physical Activity Participation Decreases the Risk of Depression in Older Adults: The ATHLOS Population-Based Cohort Study

BACKGROUND

To which extent physical activity is associated with depression independent of older adults' physical and cognitive functioning is largely unknown. This cohort study using harmonised data by the EU Ageing Trajectories of Health: Longitudinal Opportunities and Synergies consortium, including over 20 countries, to evaluate the longitudinal association of physical activity (light-to-moderate or vigorous intensity) with depression in older adults (aged ≥ 50 years).

RESULTS

We evaluated 56,818 participants (light-to-moderate models; 52.7% females, age 50-102 years) and 62,656 participants (vigorous models; 52.7% females, age 50-105 years). Compared to never, light-to-moderate or vigorous physical activity was associated with a lower incidence rate ratio (IRR) of depression (light-to-moderate model: once/week: 0.632, 95% CI 0.602-0.663; twice or more/week: 0.488, 95% CI 0.468-0.510; vigorous model: once/week: 0.652, 95% CI 0.623-0.683; twice or more/week: 0.591, 95% CI 0.566-0.616). Physical activity remained associated with depression after adjustment for the healthy ageing scale, which is a scale that incorporated 41 items of physical and cognitive functioning (light-to-moderate model: once/week: 0.787, 95% CI 0.752-0.824; twice or more/week: 0.711, 95% CI 0.682-0.742; vigorous model: once/week: 0.828, 95% CI 0.792-0.866; twice or more/week: 0.820, 95% CI 0.786-0.856).

CONCLUSIONS

Physical activity, of any intensity and weekly frequency, was a strong protective factor against depression, independent of physical and mental functioning. Health policies could stimulate the incorporation of lower physical activity intensity to protect against depression, which might be more feasible at the population level.

The associations of physical incapacity and wealth with remaining in paid employment after age 60 in five middle-income and high-income countries

Previous studies on health and socioeconomic determinants of later-life labour force participation have mainly come from high-income European countries and the United States of America (USA). Findings vary between studies due to different measures of socioeconomic status and labour force outcomes. This study investigated longitudinal associations of physical incapacity and wealth with remaining in paid employment after age 60 in middle- and high-income countries. Using harmonised cohort data in the USA, England, Japan, Mexico and China (N=32,132), multilevel logistic regression was applied for main associations. The age-related probabilities of remaining in paid employment by physical incapacity and wealth were estimated using marginal effects. This study found that physical incapacity predicted lower odds of remaining in paid employment in each country. Wealth was associated with higher odds of remaining in paid employment in the USA, England, and Japan, but not in Mexico. Probabilities of remaining in paid employment were high in Mexico but low in China. The absolute difference in the probability of remaining in paid employment between the richest and the poorest groups was greater in the USA than that in any other country. In the USA, England and Japan, the inverse association between physical incapacity and remaining in paid employment could be partially compensated by wealth only when physical incapacity was not severe. National policies, including considering older adults' changing capacities for job placement and prioritising the provision of supportive services for socioeconomically disadvantaged older adults, developing pathways for informal workers to access social security and pension coverage, and encouraging employers to hire socioeconomically disadvantaged older workers and enhancing their employability, could be facilitated. Future studies, such as exploring health and socioeconomic determinants of remaining in part-time and full-time paid employment separately in more countries, and the moderating effects of relevant policies on these associations, are needed.

ATHLOS Healthy Aging Scale score as the predictor of all-cause mortality in Poland and Czechia

Background

The ATHLOS consortium (Aging Trajectories of Health–Longitudinal Opportunities and Synergies) used data from several aging cohorts to develop a novel scale measuring healthy aging comprehensively and globally (ATHLOS Healthy Aging Scale). In the present study, we assessed the predictive performance of the ATHLOS Healthy Aging Scale for all-cause mortality in middle-aged and older adults.

Methods

Data from the Polish and Czech HAPIEE (Health Alcohol and Psychosocial factors In Eastern Europe) prospective cohorts were used. There were 10,728 Poles and 8,857 Czechs recruited. The ATHLOS Healthy Aging Scale score was calculated for all participants using data from the baseline examination carried out from 2002 to 2005. The follow-up for all-cause mortality was completed over 14 years. The associations between quintiles of the ATHLOS Healthy Aging Scale and all-cause mortality were estimated using Cox proportional hazards models.

Results

A total of 9,922 Polish and 8,518 Czech participants contributed ATHLOS Healthy Aging Scale and mortality data with 1,828 and 1,700 deaths, respectively. After controlling for age, the ATHLOS Healthy Aging Scale score was strongly associated with mortality in a graded fashion for both genders and countries (hazard ratios for lowest vs. highest quintile were 2.98 and 1.96 for Czech and Polish women and 2.83 and 2.66 for Czech and Polish men, respectively). The associations were only modestly attenuated by controlling for education, economic activity, and smoking, and there was further modest attenuation after additional adjustment for self-rated health.

Conclusion

The novel ATHLOS Healthy Aging Scale is a good predictor of all-cause mortality in Central European urban populations, suggesting that this comprehensive measure is a useful tool for the assessment of the future health trajectories of older persons.

Determinants of verbal fluency trajectories among older adults from the English Longitudinal Study of Aging

BACKGROUND

Prevalence of dementia and cognitive impairment increase creating the need for identifying modifiable risk factors to reduce their burden. The aim of this study was to identify latent groups following similar trajectories in cognitive performance assessed with the verbal fluency test, as well as their determinants.

METHODS

Data from English Longitudinal Study of Aging (ELSA) were studied. Latent groups of similar course through a 6-year period in the outcome variable (verbal fluency) were investigated, along with their determinants, using Group Based Trajectory Modeling (GBTM).

RESULTS

Four latent groups of verbal fluency trajectories were revealed. Education was the strongest predictor for a favorable trajectory, while cardiovascular disease and depression symptoms were associated with lower within each trajectory.

CONCLUSION

Cardiovascular diseases and depressive symptoms are associated with a worse course of verbal fluency through aging, implying that they might serve as targets for interventions to prevent cognitive decline in the aging population. Contrarily, higher level of education is associated with a more favorable course through aging.

A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the ATHLOS project

The ATHLOS cohort is composed of several harmonized datasets of international groups related to health and aging. As a result, the Healthy Aging index has been constructed based on a selection of variables from 16 individual studies. In this paper, we consider additional variables found in ATHLOS and investigate their utilization for predicting the Healthy Aging index. For this purpose, motivated by the volume and diversity of the dataset, we focus our attention upon data clustering, where unsupervised learning is utilized to enhance prediction power. Thus we show the predictive utility of exploiting hidden data structures. In addition, we demonstrate that imposed computation bottlenecks can be surpassed when using appropriate hierarchical clustering, within a clustering for ensemble classification scheme, while retaining prediction benefits. We propose a complete methodology that is evaluated against baseline methods and the original concept. The results are very encouraging suggesting further developments in this direction along with applications in tasks with similar characteristics. A straightforward open source implementation for the R project is also provided (https://github.com/Petros-Barmpas/HCEP).

Supplementary Information

The online version contains supplementary material available at 10.1007/s13755-022-00171-1.

Healthy aging and late-life depression in Europe: Does migration matter?

Background

There is limited research examining the impact of risk and protective factors on late-life depression using large population-based datasets, particularly those examining differences among older migrants and non-migrants in Europe countries. Thus, the first aim was to analyze differences between migrants and non-migrants regarding socioeconomic status, depression, multimorbidity, healthy aging, and lifestyle behaviors. The second aim was to examine the impact of healthy aging on late-life depression in older migrants compared to their counterparts without a history of international migration in extensive and harmonized data from different population-based cohort studies.

Materials and methods

We analyzed cross-sectional, predominantly nationally representative, community-based data from European participants in the Aging Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) cohort. The descriptive analyses included sociodemographic variables, somatic comorbidities, multimorbidity, healthy aging, and lifestyle behaviors according to migration status. The effects of these variables on late-life depression were examined in a multivariate logistic regression model, including migration status and years since migration as predictors.

Results

Data of 122,571 individuals aged ≥ 50 years were analyzed, of which 11,799 (9.60%) were migrants. The descriptive analyses indicated that compared to non-migrants, migrants showed a higher prevalence of diabetes (25.6%), hypertension (38.0%), coronary artery disease (49.4%), stroke (4.9%), and depression (31.1%). Healthy aging was also better in non-migrants (51.7; SD = 9.7) than in migrants (39.6; SD = 18.2). The results of the logistic regression showed that migration status [OR = 1.231 (CIs: 0.914-1.547)] and increased number of years since migration in the host country [OR = 0.003 (CIs: 0.001-0.005)] were associated with greater levels of depressive symptoms. Concerning health variables, multimorbidity was associated with higher levels of depressive symptoms [OR = 0.244 (CIs: 0.211-0.278)], whereas better healthy aging was associated with fewer depressive symptoms [OR = -0.100 (CIs: -0.102 to -0.098)]. The interaction between migration and healthy aging status was also significant [OR. = -0.019 (CIs: -0.025 to -0.014)].

Conclusion

Migrants reported higher risks for worse health outcomes compared to non-migrants. Significantly, worse healthy aging was associated with a greater risk of depressive symptoms in migrants than in non-migrants. Shedding light on migration and aging processes is essential for promoting a cross-cultural understanding of late-life depression in Europe.

ATHLOS Healthy Ageing Scale score as the predictor of mortality in Poland and the Czech Republic

Background

A novel tool to measure healthy ageing was developed by the ATHLOS consortium (Ageing Trajectories of Health-Longitudinal Opportunities and Synergies). ATHLOS Healthy Ageing Scale, constructed using harmonized data from 16 independent ageing cohorts, was designed to contribute to worldwide research on healthy ageing. The aim of the analysis was to assess the relation between ATHLOS Healthy Ageing Scale and all-cause mortality in Central European populations.

Methods

Participants of the Polish and Czech HAPIEE cohorts (baseline age 45-69 years) were followed for 14 years. ATHLOS Healthy Ageing Scale was based on over 40 health indicators related to intrinsic capacity and functional ability. Cox proportional hazards models were used to determine the relationship between the ATHLOS Healthy Ageing Scale scores and all-cause mortality.

Results

As many as 9,922 Polish and 8,518 Czech participants had non-missing data on the ATHLOS Healthy Ageing Scale score and mortality (1828 and 1700 deaths, respectively). After adjustment for age, dose-response associations with mortality in both genders and countries were found (HR for lowest vs. highest quintile of the ATHLOS Healthy Ageing Scale: 2.98 and 1.96 in Czech and Polish women and 2.83 and 2.66 in Czech and Polish men, respectively). Only modest attenuation was observed when additionally adjusted for education, economic activity, smoking and self-rated health.

Conclusions

The ATHLOS Healthy Ageing Scale was found to be a good predictor of all-cause mortality in urban populations of Poland and Czechia. This composite indicator seems to be an important contributor to a better assessment of healthy ageing.

Key messages

Challenges of data sharing in European Covid-19 projects: A learning opportunity for advancing pandemic preparedness and response

The COVID-19 pandemic saw a massive investment into collaborative research projects with a focus on producing data to support public health decisions. We relay our direct experience of four projects funded under the Horizon2020 programme, namely ReCoDID, ORCHESTRA, unCoVer and SYNCHROS. The projects provide insight into the complexities of sharing patient level data from observational cohorts. We focus on compliance with the General Data Protection Regulation (GDPR) and ethics approvals when sharing data across national borders. We discuss procedures for data mapping; submission of new international codes to standards organisation; federated approach; and centralised data curation. Finally, we put forward recommendations for the development of guidelines for the application of GDPR in case of major public health threats; mandatory standards for data collection in funding frameworks; training and capacity building for data owners; cataloguing of international use of metadata standards; and dedicated funding for identified critical areas.

Estimating the Prevalence of Recreational Opioid Use in Spain Using a Multiplier Method

Acknowledgement of the prevalence of recreational opioid use (PROU) is key to the planning and evaluation of care services. However, in Spain, the prevalence of PROU in recent years is unknown. The objective of this study was to estimate the PROU between 2005 and 2019 in the general populations of six Spanish cities. A benchmark-multiplier methodology was used to estimate the PROU population size. The benchmark used was overdose deaths from recreational opioid use in Spain’s six most populated cities. The multiplier was the overdose death rate in a cohort of heroin users. Linear regression was used to estimate the trend of the PROU estimate over the set period of years. In 2005, the PROU was 4.78 (95%CI 3.16–7.91) per 1000 people. The estimated trend decreased, with the two lowest values being 2.35 per 1000 in 2015 and 2.29 in 2018. In 2019 the PROU was 2.60 per 1000 (95%CI 1.72–4.31), 45% lower than in 2005. While the decline in the PROU continues, its deceleration over the last four years calls for increased vigilance, especially in light of the opioid crisis in North America that has occurred over the last few years.

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

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.

Risk of all-cause mortality associated with chronic obstructive pulmonary disease and the role of healthy ageing trajectories: a population-based study of middle-aged and older adults

OBJECTIVES

The aims were to study the risk of all-cause mortality associated with chronic obstructive pulmonary disease (COPD) and healthy ageing trajectories (HAT) in three birth cohorts and to determine the moderating role of HAT in the association between COPD and all-cause mortality.

DESIGN

Prospective cohort study.

SETTING

Data from waves 1 to 5 of The Survey of Health, Ageing and Retirement in Europe.

PARTICIPANTS

The total sample was 28 857 community-dwelling individuals aged 50+ years.

MAIN OUTCOME

All-cause mortality associated with COPD and HAT adjusting for covariates. We performed Aalen additive hazards models to explore these associations. Interactions between COPD and HAT were also explored. Analyses were conducted separately in three birth cohorts (>1945, 1936-1945 and ≤1935). Latent class growth analysis was used to classify participants into HAT.

RESULTS

Three parallel HAT were found in the three birth cohorts ('low', 'medium' and 'high' healthy ageing). Participants with COPD had an increased mortality risk, but this effect was no longer significant after adjusting for covariates. The 'low' HAT was associated with increased mortality risk in the three subsamples, although this effect was lower after adjustment. The interaction between COPD and HAT was significant only in the ≤1935 birth cohort, indicating that those with COPD and a 'low' trajectory had a greater risk of mortality.

CONCLUSIONS

The healthy ageing scale may be a suitable tool to identify patients at higher risk to mitigate disease burden and improve patients' quality of life.

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.

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.

Functioning profiles in a nationally representative cohort of Spanish older adults: A latent class study

Ageing well involves individuals continuing participating in personal, social and civic affairs even in older age. From this standpoint, limitations in individual's functioning (beyond the mere absence of disease) may drastically impact on how well people becoming older. This study aimed to identify functional status profiles in a nationally representative sample of older adults, using latent class analysis methods. Moreover, it intended to study the how identified classes would be related to health-related outcomes later in life, as a way to provide some evidence on predictive validity. Data from a nationally representative sample of Spanish older adults (N = 2,118; 56.18% women; M = 71.50 years, SD = 7.76), were used. Profiles were identified according to a large set of functioning indicators from multiple domains using latent class analysis. Outcomes were studied over a 3-year follow-up, considering both the individual (quality of life, well-being and mortality) and institutional level (health service utilisation). As a result, seven profiles were identified: normative profile (showed by most participants), limited cognitive functioning class, limited global functioning class, limited mental and mobility functioning class, poor self-reported health class, limited sensory functioning class and limited objective functioning class. All the profiles with limitations across domains showed poor outcomes. Multidimensional limitations were related to the worst outcomes, especially when psychosomatic complaints and high feelings of loneliness were reported. To sum up, latent class analysis constitutes a suitable alternative to study population heterogeneity, providing relevant evidence to help making decision in public and community health.

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

OBJECTIVES

Our 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. Additionally, we explored the associations with several covariates.

DESIGN

The total sample was 72 140 people aged 50+ years from three population-based studies (English Longitudinal Study of Ageing, Survey of Health, Ageing and Retirement in Europe Study and Study on Global Ageing and Adult Health) included in the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) project and representing eight regions with LMICs and HICs. Variables were previously harmonised using an ex-post strategy. Eight NCDs were used in latent class analysis. Multinomial models were made to calculate associations with covariates. All the analyses were stratified by age (50-64 and 65+ years old).

RESULTS

Three clusters were identified: 'cardio-metabolic' (8.93% in participants aged 50-64 years and 27.22% in those aged 65+ years), 'respiratory-mental-articular' (3.91% and 5.27%) and 'healthy' (87.16% and 67.51%). In the younger group, Russia presented the highest prevalence of the 'cardio-metabolic' group (18.8%) and England the 'respiratory-mental-articular' (5.1%). In the older group, Russia had the highest proportion of both classes (48.3% and 9%). Both the younger and older African participants presented the highest proportion of the 'healthy' class. Older age, being woman, widowed and with low levels of education and income were related to an increased risk of multimorbidity. Physical activity was a protective factor in both age groups and smoking a risk factor for the 'respiratory-mental-articular'.

CONCLUSION

Multimorbidity is common worldwide, especially in HICs and Russia. Health policies in each country addressing coordination and support are needed to face the complexity of a pattern of growing multimorbidity.

Pain rates in general population for the period 1991-2015 and 10-years prediction: results from a multi-continent age-period-cohort analysis

Background

Pain is a common symptom, often associated with neurological and musculoskeletal conditions, and experienced especially by females and by older people. The aims of this study are to evaluate the temporal variations of pain rates among general populations for the period 1991–2015 and to project 10-year pain rates.

Methods

We used the harmonized dataset of ATHLOS project, which included 660,028 valid observations in the period 1990–2015 and we applied Bayesian age–period–cohort modeling to perform projections up to 2025. The harmonized Pain variable covers the content “self-reported pain experienced at the time of the interview”, with a dichotomous (yes or no) modality.

Results

Pain rates were higher among females, older subjects, in recent periods, and among observations referred to cohorts of subjects born between the 20s and the 60s. The 10-year projections indicate a noteworthy increase in pain rates in both genders and particularly among subjects aged 66 or over, for whom a 10–20% increase in pain rate is foreseen; among females only, a 10–15% increase in pain rates is foreseen for those aged 36–50.

Conclusions

Projected increase in pain rates will require specific interventions by health and welfare systems, as pain is responsible for limited quality of subjective well-being, reduced employment rates and hampered work performance. Worksite and lifestyle interventions will therefore be needed to limit the impact of projected higher pain rates.

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

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.

Trajectories of Immediate and Delayed Verbal Memory in the Spanish General Population of Middle-aged and Older Adults

(1) Cognitive decline differs among individuals and cognition function domains. We sought to identify distinct groups of immediate and delayed verbal memory in two age subsamples (50–64, 65+ years), and to analyze associated factors. (2) Latent class mixed models were used to identify verbal memory trajectories in a sample of Spanish community-dwelling individuals over 8 years’ follow up. Chi-square and Kruskal–Wallis tests were used to assess differences among trajectories. (3) Different trajectories were identified. In the case of immediate verbal memory, these were: very low/decline (6.3%), low/stable (38.2%), medium/slow decline (43.4%), and high/slow decline (12.2%) in the middle-aged group, and low/decline (20.4%), medium/slow decline (60.4%), and high/slow decline (19.2%) in the older subsample. In delayed verbal memory, more distinct patterns were found: very low/decline (12.4%), low/stable (51.4%), medium/accelerated decline (24.7%), and high/slow increase (11.4%) in the younger group, and low/slow decline (34.4%), medium/decline (52.7%), and high/slow decline (12.9%) in the older group. (4) Overall, low initial performance and decline were associated with older age, lower education, and higher diabetes/stroke prevalence. Differences found suggests heterogeneity in cognitive ageing. The high prevalence of cardiovascular diseases in those with worse cognition suggests that early interventions to prevent those conditions should be targeted in midlife to delay cognitive decline.

Self-reported and activPALTM-monitored physical activity and sedentary behaviour in college students: Not all sitting behaviours are linked to perceived stress and anxiety

This study examined relationships between physical activity (PA) and sedentary behaviour (SB) with state-trait anxiety and stress. State-Trait anxiety (State-Trait Anxiety Inventory), psychological stress (Perceived Stress Scale), SB across domains during weekdays and weekends (Last 7-day Sedentary Behaviour Questionnaire) and PA intensities (International Physical Activity Questionnaire) were assessed by self-report in 360 undergraduates (44% females, mean age 20.9 ± 2.93 years). A subsample (n = 121; 53.7% females; mean age 20.8 ± 2.6 years) wore an activPAL^TM to determine total SB, light, and moderate-to-vigorous intensity PA (MVPA). Self-reported MVPA was significantly associated with lower trait anxiety and perceived stress, whereas light PA was only associated with lower perceived stress. Weekend total self-reported SB was related to higher trait anxiety and perceived stress levels, while total SB during the week was not. Of all SB domains, only leisure SB (screen and non-screen based) was associated with higher trait anxiety and perceived stress. PA attenuated the negative relationships between excessive sitting time and trait anxiety but not perceived stress. No associations were found for monitor-based measures of PA and SB. No associations were found between PA or SB variables with state anxiety. Further research is needed to assess causal and reciprocal relationships between PA, SB and mental health in college students.

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

AIMS

To study the temporal dynamics of depression symptom episodes in old-age and the related influence of risk factors.

METHODS

Data from 41 362 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.

RESULTS

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).

CONCLUSIONS

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.

CREATION OF A COMMON METRIC OF HEALTH STATUS IN THE HARMONIZED DATASET OF THE ATHLOS PROJECT

Although life longevity has increased across the world, evidence suggests some heterogeneity of the ageing process across individuals. To investigate different ageing patterns, the ATHLOS project harmonised data from 411,000 individuals across 17 existing cohort studies. The harmonised dataset provides comparable information on functioning measures, cognition, mental health, sociodemographic and lifestyle behaviours. To measure the process of healthy ageing across time and cohorts, we employed a Bayesian Multilevel Item Response Theory(IRT) and created a common metric of health status by using items of functioning. The IRT measurement model includes parameters describing the difficulty and discriminatory power of each item. We adopted the Bayesian Multilevel framework as it allows item parameters to vary among studies and the simultaneous estimation of all parameters under a Markov Chain Monte Carlo(MCMC) method. Finally, we assessed the predictive validity of the metric against mortality by performing a Receiver Operating Characteristic(ROC) curve analysis.

Sociodemographic Indicators of Health Status Using a Machine Learning Approach and Data from the English Longitudinal Study of Aging (ELSA)

BACKGROUND Studies on the effects of sociodemographic factors on health in aging now include the use of statistical models and machine learning. The aim of this study was to evaluate the determinants of health in aging using machine learning methods and to compare the accuracy with traditional methods. MATERIAL AND METHODS The health status of 6,209 adults, age <65 years (n=1,585), 65-79 years (n=3,267), and >80 years (n=1,357) were measured using an established health metric (0-100) that incorporated physical function and activities of daily living (ADL). Data from the English Longitudinal Study of Ageing (ELSA) included socio-economic and sociodemographic characteristics and history of falls. Health-trend and personal-fitted variables were generated as predictors of health metrics using three machine learning methods, random forest (RF), deep learning (DL) and the linear model (LM), with calculation of the percentage increase in mean square error (%IncMSE) as a measure of the importance of a given predictive variable, when the variable was removed from the model. RESULTS Health-trend, physical activity, and personal-fitted variables were the main predictors of health, with the%incMSE of 85.76%, 63.40%, and 46.71%, respectively. Age, employment status, alcohol consumption, and household income had the%incMSE of 20.40%, 20.10%, 16.94%, and 13.61%, respectively. Performance of the RF method was similar to the traditional LM (p=0.7), but RF significantly outperformed DL (p=0.006). CONCLUSIONS Machine learning methods can be used to evaluate multidimensional longitudinal health data and may provide accurate results with fewer requirements when compared with traditional statistical modeling.

Long-term trajectories of depressive symptoms in old age: Relationships with sociodemographic and health-related factors

BACKGROUND

This study aimed at depicting the course of depression symptoms over the old age, with a special interest in a) uncovering its relationships with sociodemographic and health-related factors; b) analysing its predictive role on healthy-ageing outcomes later in life.

METHODS

The sample comprised 8317 older adults (46.02% men) from the English Longitudinal Study of Ageing. Robust structural equation modelling was used to identify symptom trajectories and their relationships with time-varying factors. Trajectory class and covariates were used to predict outcomes (quality of life, satisfaction with life, and daily living functioning) in a 2-year follow-up.

RESULTS

Three trajectory classes (so-called, normative, subclinical, chronic symptom trajectories) were identified for both sexes. Rising hearing difficulties and history of psychiatric problems were consistently associated with the chronic symptom trajectory. Lower education level, history of psychiatric problems, and increasing visual difficulties were connected with the subclinical trajectories. Finally, participants with either a subclinical or a chronic symptom trajectory showed worse outcomes than the remaining participants in the follow-up.

CONCLUSION

This study highlighted the presence of varying courses of depression symptoms (each showing some distinctive features from other another) over the old age, pointing to some relevant implications for clinical assessment and treatment prescription.

Machine learning methodologies versus cardiovascular risk scores, in predicting disease risk

Background

The use of Cardiovascular Disease (CVD) risk estimation scores in primary prevention has long been established. However, their performance still remains a matter of concern. The aim of this study was to explore the potential of using ML methodologies on CVD prediction, especially compared to established risk tool, the HellenicSCORE.

Methods

Data from the ATTICA prospective study (n = 2020 adults), enrolled during 2001–02 and followed-up in 2011–12 were used. Three different machine-learning classifiers (k-NN, random forest, and decision tree) were trained and evaluated against 10-year CVD incidence, in comparison with the HellenicSCORE tool (a calibration of the ESC SCORE). Training datasets, consisting from 16 variables to only 5 variables, were chosen, with or without bootstrapping, in an attempt to achieve the best overall performance for the machine learning classifiers.

Results

Depending on the classifier and the training dataset the outcome varied in efficiency but was comparable between the two methodological approaches. In particular, the HellenicSCORE showed accuracy 85%, specificity 20%, sensitivity 97%, positive predictive value 87%, and negative predictive value 58%, whereas for the machine learning methodologies, accuracy ranged from 65 to 84%, specificity from 46 to 56%, sensitivity from 67 to 89%, positive predictive value from 89 to 91%, and negative predictive value from 24 to 45%; random forest gave the best results, while the k-NN gave the poorest results.

Conclusions

The alternative approach of machine learning classification produced results comparable to that of risk prediction scores and, thus, it can be used as a method of CVD prediction, taking into consideration the advantages that machine learning methodologies may offer.

Depression and metabolic syndrome in the older population: A review of evidence

BACKGROUND

Metabolic syndrome (MetS) has been shown to be associated with depression in older adults but the results are mixed. We summarized and evaluated the association between depression and MetS in people aged 60 years or over.

METHODS

Relevant published studies from January 1997 to July 2017 were identified by searching two electronic databases: PubMed/Medline and EMBASE. Observational studies were considered.

RESULTS

Twelve studies were included in the systematic review. Depression seemed to be related with MetS in the majority of the studies (10/12 = 83.3%). As far as the longitudinal studies are concerned, the onset of depression was related to MetS in 2 out of 3 studies (66.6%), while a relation between chronicity of depression and MetS was reported (1 study). Regarding cross-sectional studies, 7 out of 9 (77.7%) concluded that there was a positive association between depression and MetS. Mixed evidence was found among studies concerning the association between depression and the individual components of MetS. Four out of ten studies (40%) reported that depression was significantly associated with the waist circumference, a component of MetS.

LIMITATIONS

There was a high degree of heterogeneity between studies regarding their design. Only studies written in English, from peer-reviewed journals were included.

CONCLUSIONS

Depression seemed to be significantly associated with MetS in people aged 60 years or over. Among the components of MetS, abdominal obesity seemed to be associated more strongly and consistently with depression. The direction of the causality and mechanisms underlying the relationship are still largely unknown.

Application of latent growth modeling to identify different working life trajectories: the case of the Spanish WORKss cohort

Objective The aim of this study was to describe the application of latent class growth analysis (LCGA) to identify different working life trajectories (WLT) using employed working time by year as a repeated measure. Methods Trajectories are estimated using LCGA, which considers all individuals within a trajectory to be homogeneous. The methodology was applied to a subsample of the Spanish WORKing life Social Security (WORKss) cohort, limited to persons born 1956-1965 (N=247 475). The number of days worked per year is used as a repeated measure across 32 time points (1981-2013). Results According to the model-fit results and further guided by expert knowledge, a four WTL model was selected as the optimal approach: WLT1 or "high labor force participation" (N=99 591; 40.2%); WLT2 or "decreased labor force participation" (N= 22 846; 9.2%); WLT3 or "increased labor force participation" (N=59 213; 23.9%); and WLT4 or "low labor force participation" (N=65 827; 26.6%). WLT1 consisted mainly of men with more years of work experience (>19 years) while WLT4 was mainly composed by women with <9 years. The other two trajectories had opposite trends and no sex differences. The occupational category variable had little influence in the trajectories. Conclusions Longitudinal data that are regularly collected by administrative systems can benefit from LCGA approaches to identify different trajectory patterns that may be associated with an outcome of interest. In occupational epidemiology, this study represents a step forward by using this modeling approach to identify different WLT.

Cohort profile: the Spanish WORKing life Social Security (WORKss) cohort study

PURPOSE

The global economy is changing the labour market and social protection systems in Europe. The effect of both changes on health needs to be monitored in view of an ageing population and the resulting increase in prevalence of chronic health conditions. The Spanish WORKing life Social Security (WORKss) cohort study provides unique longitudinal data to study the impact of labour trajectories and employment conditions on health, in terms of sickness absence, permanent disability and death.

PARTICIPANTS

The WORKss cohort originated from the Continuous Working Life Sample (CWLS) generated by the General Directorate for the Organization of the Social Security in Spain. The CWLS contains a 4% representative sample of all individuals in contact with the Social Security system. The WORKss cohort exclusively includes individuals with a labour trajectory from 1981 or later. In 2004, the cohort was initiated with 1,022 ,79 Social Security members: 840,770 (82.2%) contributors and 182,009 (17.8%) beneficiaries aged 16 and older.

FINDINGS TO DATE

The WORKss cohort includes demographic characteristics, chronological data about employment history, retirement, permanent disability and death. These data make possible the measurement of incidence of permanent disability, the number of potential years of working life lost, and the number of contracts and inactive periods with the Social Security system. The WORKss cohort was linked to temporary sickness absence registries to study medical diagnoses that lead to permanent disability and consequently to an earlier exit from the labour market in unhealthy conditions.

FUTURE PLANS

Thanks to its administrative source, the WORKss cohort study will continue follow-up in the coming years, keeping the representativeness of the Spanish population affiliated to the Social Security system. The linkage between the WORKss cohort and temporary sickness absence registries is envisioned to continue. Future plans include the linkage of the cohort with mortality registries.

MMPs/TIMPs and inflammatory signalling de-regulation in human incisional hernia tissues

Background: Incisional hernia is a common and important complication of laparotomies. Epidemiological studies allude to an underlying biological cause, at least in a subset of population. Interest has mainly focused on abnormal collagen metabolism. However, the role played by other determinants of extracellular matrix (ECM) composition is unknown. To date, there are few laboratory studies investigating the importance of biological factors contributing to incisional hernia development. We performed a descriptive tissue-based analysis to elucidate the possible relevance of matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) in association with local cytokine induction in human incisional hernia tissues. The expression profiles of MMPs, TIMPs and pro-inflammatory cytokine signalling were investigated in aponeurosis and skeletal muscle specimens taken intraoperatively from incisional hernia (n= 10) and control (n= 10) patients. Semiquantitative RT-PCR, zymography and immunoblotting analyses were done. Incisional hernia samples displayed alterations in the microstructure and loss of ECM, as assessed by histological analyses. Moreover, incisional hernia tissues showed increased MMP/TIMP ratios and de-regulated inflammatory signalling (tumor necrosis factor [TNFA] and interleukin [IL]-6 tended to increase, whereas aponeurosis TNFA receptors decreased). The changes were tissue-specific and were detectable at the mRNA and/or protein level. Statistical analyses showed several associations between individual MMPs, TIMPs, interstitial collagens and inflammatory markers. The increment of MMPs in the absence of a counterbalance by TIMPs, together with an ongoing de-regulated inflammatory signalling, may contribute in inducing a functional defect of the ECM network by post-translational mechanisms, which may trigger abdominal wall tissue loss and eventual rupture. The notable TIMP3 protein down-regulation in incisional hernia fascia may be of pathophysiological significance. We conclude that this study may help to pinpoint novel hypotheses of pathogenesis that can lead to a better understanding of the disease and ultimately to improvement in current therapeutic approaches.