Trajectories Of Healthy Ageing Research Articles

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.

Optimizing Older Adult Mental Health in Support of Healthy Ageing: A Pluralistic Framework to Inform Transformative Change across Community and Healthcare Domains.

This paper describes a pluralistic framework to inform transformative change across community and healthcare domains to optimize the mental health of older adults in support of healthy ageing. An extensive review and analysis of the literature informed the creation of a framework that contextualizes the priority areas of the WHO Decade of Health Ageing (ageism, age-friendly environments, long-term care, and integrated care) with respect to older adult mental health. The framework additionally identifies barriers, facilitators, and strategies for action at macro (social/system), meso (services/supports), and micro (older adults) levels of influence. This conceptual (analytical) framework is intended as a tool to inform planning and decision-making across policy, practice, education and training, research, and knowledge mobilization arenas. The framework described in this paper can be used by countries around the globe to build evidence, set priorities, and scale up promising practices (both nationally and sub-nationally) to optimize the mental health and healthy ageing trajectories of older adults as a population.

The combined effect of socioeconomic position and C-reactive protein for predicting incident cardiometabolic disease: Findings from a 14-year follow-up study of the English Longitudinal Study of Ageing (ELSA)

Cardiovascular disease and diabetes are leading causes of morbidity and mortality worldwide. Social inequalities in the distribution of these diseases across the population exist. The aim of the current study was to examine the additive effect of socioeconomic position and a known biological risk marker (C-reactive protein [CRP]) for future incident cardiometabolic disease. We used data from the English Longitudinal Study of Ageing (N = 5410). Tertiles of net financial wealth and CRP (>3 mg/L) were measured at wave 2 (2004/05) and disease incidence (coronary heart disease [CHD], stroke, diabetes/high blood glucose) was reported across the subsequent 14 years of follow-up (2006–2019). Individual diseases were modelled as well as cardiometabolic multimorbidity which was defined as 2 or more incident cardiometabolic disease diagnoses over follow-up. Participants were free from the disease of interest at baseline. Cox proportional hazard and logistic regression analyses were used controlling for sociodemographic, lifestyle and health-related covariates. After adjusting for all covariates, the combination of low wealth and elevated CRP was an independent predictor of incident diabetes/high blood glucose (Hazard Ratio (HR) = 2.14; 95% Confidence Interval (C.I.) = 1.49–3.07), CHD (HR = 2.48, 95% C.I. = 1.63–3.76), stroke (HR = 1.55; 95% C.I. = 1.18–2.04), relative to high wealth/low CRP. Low wealth and elevated CRP was also an independent predictor of incident cardiometabolic multimorbidity (Odds Ratio = 2.22, 95% C.I. = 1.16–4.28) in age and sex adjusted models. The presence of both low wealth and elevated CRP was implicated in the onset of CHD, stroke, diabetes/high blood glucose, and cardiometabolic multimorbidity up to 14 years later, reflecting the role of psychobiological processes in predicting disease burden. Our results reinforce calls for efforts to tackle structural inequalities to improve healthy ageing trajectories.

Ageing, functioning patterns and their environmental determinants in the spinal cord injury (SCI) population: A comparative analysis across eleven European countries implementing the International Spinal Cord Injury Community Survey.

As the European population with Spinal Cord Injury (SCI) is expected to become older, a better understanding of ageing with SCI using functioning, the health indicator used to model healthy ageing trajectories, is needed. We aimed to describe patterns of functioning in SCI by chronological age, age at injury and time since injury across eleven European countries using a common functioning metric, and to identify country-specific environmental determinants of functioning. Data from 6'635 participants of the International Spinal Cord Injury Community Survey was used. The hierarchical version of Generalized Partial Credit Model, casted in a Bayesian framework, was used to create a common functioning metric and overall scores. For each country, linear regression was used to investigate associations between functioning, chronological age, age at SCI or time since injury for persons with para- and tetraplegia. Multiple linear regression and the proportional marginal variance decomposition technique were used to identify environmental determinants. In countries with representative samples older chronological age was consistently associated with a decline in functioning for paraplegia but not for tetraplegia. Age at injury and functioning level were associated, but patterns differed across countries. An association between time since injury and functioning was not observed in most countries, neither for paraplegia nor for tetraplegia. Problems with the accessibility of homes of friends and relatives, access to public places and long-distance transportation were consistently key determinants of functioning. Functioning is a key health indicator and the fundament of ageing research. Enhancing methods traditionally used to develop metrics with Bayesian approach, we were able to create a common metric of functioning with cardinal properties and to estimate overall scores comparable across countries. Focusing on functioning, our study complements epidemiological evidence on SCI-specific mortality and morbidity in Europe and identify initial targets for evidence-informed policy-making.

The global healthy ageing agenda: The impact of education, gender, childhood conditions and social engagement in rural South Africa

This paper examines factors associated with the likelihood of healthy ageing and the propensity to utilise health care resources for a rural community in South Africa and the associated policy implications. Our results suggest education exerts a positive influence, and its marginal impact is more prominent for females than males. Further, we show that better childhood health is associated with increased likelihood of ageing well. We also demonstrate an inverse relationship between health care utilisation and healthy ageing. The results presented here suggest that strategic policy investments across life courses in education and child-health fosters not only broader development goals but also enhances healthy ageing trajectories and improve the health and wellbeing of individuals across life stages. This study contributes to informing on the UN’s healthy ageing global strategic agenda in the context of a poor rural region.

Co-developing a health promotion programme for indigenous youths in Brazil: A concept mapping report.

Latin America and the Caribbean Region are home to about 42 million Indigenous people, with about 900,000 living in Brazil. The little routinely collected population-level data from Indigenous communities in the region available shows stark inequities in health and well-being. There are 305 Indigenous ethnic groups, speaking 274 languages, spread across the remote national territory, who have endured long-lasting inequities related to poverty, poor health, and limited access to health care. Malnutrition and mental health are key concerns for young people. Building on our Indigenous communities-academic partnerships over the last two decades, we collaborated with young people from the Terena Indigenous ethnic group, village leaders, teachers, parents, and local health practitioners from the Polo Base (community health centres) to obtain their perspectives on important and feasible actions for a youth health promotion programme. The report was conducted in the Tereré Village in Mato Grosso do Sul. Concept mapping, a participatory mixed method approach, was conducted in 7 workshops, 15 adults and 40 youths aged 9-17 years. Art-based concept mapping was used with 9 to 11 years old children (N = 20). Concept systems software was used to create concept maps, which were finalised during the workshops. Focused prompts related to factors that may influence the health and happiness of youths. The participatory method gave Terena youths a significant voice in shaping an agenda that can improve their health. Terena youths identified priority actions that clustered under 'Family', 'School', 'Education', 'Socio-economic circumstances', 'Respect' and 'Sport' in response to protecting happiness; and 'Nutrition pattern', 'Physical activity', 'Local environment', and 'Well-being' in response to having a healthy body. Through the participatory lens of concept mapping, youths articulated the interconnectedness of priority actions across these clusters such that behaviours (e.g. Nutrition pattern, drinking water, physical activity) and aspirations (being able to read, to have a good job) were recognised to be dependent on a wider ecology of factors (e.g. loss of eco-systems, parent-child relationships, student- teacher relationships, parental unemployment). In response to developing youth health, Terena adults suggested priority actions that clustered under 'Relationships', 'Health issues', 'Prevention at Polo Base', 'Access to health care', 'Communication with young people', 'Community life', 'Raising awareness' and 'School support'. Their priorities reflected the need for structural transformative actions (e.g. Polo Base and school staff working together) and for embedding actions to protect Indigenous culture (e.g. integrating their cultural knowledge into training programmes). Concept maps of Indigenous youths emphasised the need for a health promotion programme that engages with the structural and social determinants of health to protect their happiness and health, whilst those of adults emphasised the need to address specific health issues through preventative care via a school-Polo Base collaboration. Investment in a co-developed school-Polo-Base health promotion programme, with intersectoral engagement, has potential for making Indigenous health systems responsive to the inequalities of youth health, to yield dividends for healthy ageing trajectories as well as for the health of the next generation.

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

ObjectivesThe 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...

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.

The effect of opioids on the cognitive function of older adults: results from the Personality and Total Health through life study.

chronic pain, a common complaint among older adults, affects physical and mental well-being. While opioid use for pain management has increased over the years, pain management in older adults remains challenging, due to potential severe adverse effects of opioids in this population. we examined the association between opioid use, and changes in cognitive function of older adults. prospective study. community dwelling older adults. study population consisted of 2,222 individuals aged 65-69years at baseline from the Personality and Total Health Through Life Study in Australia. medication data were obtained from the Pharmaceutical Benefits Scheme. Cognitive measures were obtained from neuropsychological battery assessment. Opioid exposure was quantified as Total Morphine Equivalent Dose (MED). The association between change in cognitive function between Wave 2 and Wave 3, and cumulative opioid use was assessed through generalized linear models. cumulative opioid exposure exceeding total MED of 2,940 was significantly associated with poorer performance in the Mini Mental State Examination (MMSE). Compared with those not on opioids, individuals exposed to opioids resulting in cumulative total MED of greater than 2,940 had significantly lower scores in the MMSE (Model 1: β = -0.34, Model 2: β = -0.35 and Model 3: β = -0.39, P < 0.01). Performance in other cognitive assessments was not associated with opioid use. prolonged opioid use in older adults can affect cognitive function, further encouraging the need for alternative pain management strategies in this population. Pain management options should not adversely affect healthy ageing trajectories and cognitive health.

The impact of physical activity on healthy ageing trajectories: evidence from eight cohort studies

BackgroundResearch has suggested the positive impact of physical activity on health and wellbeing in older age, yet few studies have investigated the associations between physical activity and heterogeneous trajectories of healthy ageing. We aimed to identify how physical activity can influence healthy ageing trajectories using a harmonised dataset of eight ageing cohorts across the world.MethodsBased on a harmonised dataset of eight ageing cohorts in Australia, USA, Mexico, Japan, South Korea, and Europe, comprising 130,521 older adults (Mage = 62.81, SDage = 10.06) followed-up up to 10 years (Mfollow-up = 5.47, SDfollow-up = 3.22), we employed growth mixture modelling to identify latent classes of people with different trajectories of healthy ageing scores, which incorporated 41 items of health and functioning. Multinomial logistic regression modelling was used to investigate the associations between physical activity and different types of trajectories adjusting for sociodemographic characteristics and other lifestyle behaviours.ResultsThree latent classes of healthy ageing trajectories were identified: two with stable trajectories with high (71.4%) or low (25.2%) starting points and one with a high starting point but a fast decline over time (3.4%). Engagement in any level of physical activity was associated with decreased odds of being in the low stable (OR: 0.18; 95% CI: 0.17, 0.19) and fast decline trajectories groups (OR: 0.44; 95% CI: 0.39, 0.50) compared to the high stable trajectory group. These results were replicated with alternative physical activity operationalisations, as well as in sensitivity analyses using reduced samples.ConclusionsOur findings suggest a positive impact of physical activity on healthy ageing, attenuating declines in health and functioning. Physical activity promotion should be a key focus of healthy ageing policies to prevent disability and fast deterioration in health.

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.

Educational differences in trajectories and determinants of healthy ageing in midlife and older Americans

ObjectivesTo advance knowledge of the influence of educational level on trajectories and determinants of healthy ageing in midlife and older Americans. Study designData are from the Health and Retirement Study, a nationally representative, longitudinal survey of Americans age 51 and over. We used generalized estimating equations to examine trajectories and determinants of healthy ageing by level of education among 17,591 adults followed over a 14-year period. Educational level was categorized as less than a high school diploma, high school diploma, some college education, and a college or higher degree. Potential determinants included demographic factors, early-life characteristics (childhood health and childhood poverty), health-related factors (health behaviours, physical and mental health conditions), and psychosocial characteristics (perceived neighbourhood safety, volunteerism, and work status). Main outcome measuresInformed by earlier work, we defined healthy ageing as freedom from cognitive impairment, freedom from disability, and high physical functioning. ResultsThe log odds of healthy ageing declined over time in all educational groups. Importantly, the decline was smaller in adults with a college or higher degree than in those without a high school diploma. Age, gender, wealth, health behaviours, productive engagement, depressive symptoms, and the presence of chronic conditions predicted healthy ageing across the educational spectrum; however, the impact of several factors (age, gender, race/ethnicity, childhood poverty, and volunteerism) varied by educational level. ConclusionsEducation shapes trajectories of healthy ageing in the United States. Similarities and differences in determinants of healthy ageing are evident across levels of education. Findings highlight broad-based and education-specific targets for intervention.

Comparing socio-economic inequalities in healthy ageing in the United States of America, England, China and Japan: evidence from four longitudinal studies of ageing

AbstractHealthy ageing has become a popular topic worldwide. So far, a consensus measure of healthy ageing has not been reached; and no studies have compared the magnitude of socio-economic inequality in healthy ageing outside Europe. This study aims to create a universal measure of healthy ageing and compare socio-economic inequalities in healthy ageing in the United States of America (USA), England, China and Japan. We included 10,305 American, 6,590 English, 5,930 Chinese and 1,935 Japanese participants for longitudinal analysis. A harmonised healthy ageing index (HAI) was developed to measure healthy ageing multi-dimensionally. Educational, income and wealth rank scores were derived accounting for the entire socio-economic distribution and the sample size of each category of socio-economic indicator. Associations between socio-economic rank scores and HAIs were assessed using multi-level modelling to calculate the Slope Indices of Inequality. Healthy ageing trajectories were predicted based on the full-adjusted age-cohort models. We found that education was a universally influential socio-economic predictor of healthy ageing. Moving from the highest to the lowest educational groups was associated with a 6.7 (5.2–8.2), 8.2 (6.0–10.4), 13.9 (11.4–16.3) and 6.1 per cent (3.9–8.2%) decrease in average HAI at 60 years in the USA, England, China and Japan, respectively. After 60 years, the educational inequality in healthy ageing kept increasing in the USA and China. The educational inequality in healthy ageing in China was also greater than any other socio-economic inequality in the four countries. Wealth was more influential in predicting healthy ageing inequality among American, English and Japanese participants, while income was more influential among Chinese participants. The socio-economic inequality in healthy ageing in Japan was relatively small. Chinese and American participants had worse healthy ageing profiles than Japanese and English participants.

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.

Healthy ageing trajectories and lifestyle behaviour: the Mexican Health and Aging Study

Projections show that the number of people above 60 years old will triple by 2050 in Mexico. Nevertheless, ageing is characterised by great variability in the health status. In this study, we aimed to identify trajectories of health and their associations with lifestyle factors in a national representative cohort study of older Mexicans. We used secondary data of 14,143 adults from the Mexican Health and Aging Study (MHAS). A metric of health, based on the conceptual framework of functional ability, was mapped onto four waves (2001, 2003, 2012, 2015) and created by applying Bayesian multilevel Item Response Theory (IRT). Conditional Growth Mixture Modelling (GMM) was used to identify latent classes of individuals with similar trajectories and examine the impact of physical activity, smoking and alcohol on those. Conditional on sociodemographic and lifestyle behaviour four latent classes were suggested: high-stable, moderate-stable, low-stable and decliners. Participants who did not engage in physical activity, were current or previous smokers and did not consume alcohol at baseline were more likely to be in the trajectory with the highest deterioration (i.e. decliners). This study confirms ageing heterogeneity and the positive influence of a healthy lifestyle. These results provide the ground for new policies.

Early-life socioeconomic circumstances explain health differences in old age, but not their evolution over time

BackgroundEarly-life socioeconomic circumstances (SEC) are associated with health in old age. However, epidemiological evidences on the influence of these early-life risk factors on trajectories of healthy ageing are inconsistent, preventing...

Towards a multidimensional healthy ageing phenotype.

There is great interest in developing tools to measure healthy ageing and to identify early stages of health impairment, which may guide the implementation of interventions to prevent or delay the development of disease, disability, and mortality. Here, we review the most recent developments directed to operationalize, and test, definitions of healthy ageing. There is lack of consensus about how to define healthy ageing and, unsurprisingly, diversity in the instruments for its measurement. However, progress is being made in describing and in devising tools to capture the healthy ageing phenotype. Attempts to measure healthy ageing have relied primarily on cross-sectional data collected in older people. More recent studies have assessed the healthy ageing phenotype using markers of multiple functional domains and have used longitudinal data to model the dynamics and trajectories of healthy ageing. Given the complexity of the ageing process, no single measure is able to predict the ageing trajectory. Current attempts to operationalize the healthy ageing phenotype have relied on markers and data from earlier cohort studies and are limited by the tools used to collect data in those studies. Such data are often unsuitable to detect early subtle declines in function and/or are inappropriate for use in younger old adults. Future studies employing more objective and novel markers of healthy ageing are likely to offer opportunities to define and operationalize the healthy ageing phenotype.