Latin American and the Caribbean countries exhibit high life expectancy and projections show that they will experience the fastest growth of older people in the following years. As people live longer, it is important to maximise the opportunity to age healthily. We aimed to examine the associations of lifestyle behaviours with healthy ageing in Cuba, Dominican Republic, Peru, Mexico and Puerto Rico, part of the 10/66 study. Residents 65 years old and over (n = 10,900) were interviewed between 2003 and 2010. In the baseline survey, we measured four healthy behaviours: Physical activity, non-smoking, moderate drinking and fruits or vegetables consumption. Healthy ageing was conceptualised within the functional ability framework over a median of 4 years follow-up. Logistic models were calculated per country and then pooled together with fixed-effects meta-analysis. People engaging in physical activity and consuming fruits or vegetables had increased odds of healthy ageing in the follow-up (OR: 2.59, 95% CI: 2.20⁻3.03; OR: 1.24, 95% CI: 1.06⁻1.44, respectively). Compared with participants engaging in none or one healthy behaviour, the ORs of participants engaging in two, three or four healthy behaviours increased in a linear way (OR: 1.60, 95% CI: 1.40⁻1.84; OR: 2.29, 95% CI: 1.94⁻2.69; OR: 2.46, 95% CI: 1.54⁻3.92, respectively). Our findings highlight the importance of awareness of a healthy lifestyle behaviour among older people. ; The authors would like to thank the ATHLOS (Ageing Trajectories of Health: Longitudinal Opportunities and Synergies) project, funded by the European Union's Horizon 2020 Research and Innovation Programme under grant agreement number 635316
Background: Our population is ageing and in 2050 more than one out of five people will be 60 years or older; 80% of whom will be living in a low-and-middle income country. Living longer does not entail living healthier; however, there is not a widely accepted measure of healthy ageing hampering policy and research. The World Health Organization defines healthy ageing as the process of developing and maintaining functional ability that will enable well-being in older age. We aimed to create a healthy ageing index (HAI) in a subset of six low-and-middle income countries, part of the 10/ 66 study, by using items of functional ability and intrinsic capacity. Methods: The study sample included residents 65-years old and over (n = 12,865) from catchment area sites in Cuba, Dominican Republic, Peru, Venezuela, Mexico and Puerto Rico. Items were collected by interviewing participants or key informants between 2003 and 2010. Two-stage factor analysis was employed and we compared one-factor, second-order and bifactor models. The psychometric properties of the index, including reliability, replicability, unidimensionality and concurrent convergent validity as well as measurement invariance per ethnic group and gender were further examined in the best fit model. Results: The bifactor model displayed superior model fit statistics supporting that a general factor underlies the various items but other subdomain factors are also needed. The HAI indicated excellent reliability (ω = 0.96, ωΗ = 0.84), replicability (H = 0.96), some support for unidimensionality (Explained Common Variance = 0.65) and some concurrent convergent validity with self-rated health. Scalar measurement invariance per ethnic group and gender was supported. Conclusions: A HAI with excellent psychometric properties was created by using items of functional ability and intrinsic capacity in a subset of six low-and-middle income countries. Further research is needed to explore sub-population differences and to validate this index to other cultural settings. ; This work is also supported by the ATHLOS (Ageing Trajectories of Health: Longitudinal Opportunities and Synergies) project, funded by the European Union's Horizon 2020 Research and Innovation Programme under grant agreement number 635316. A. M. P. was supported by the MRC MR/K021907/1
Background: 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. Methods: 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. Findings: 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. Interpretation: 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. Funding: European Union Horizon 2020 Research and Innovation Programme. ; The ATHLOS project was funded by the European Union Horizon 2020 Research and Innovation Programme (grant number 635316). This study was supported by the 5-year ATHLOS project
We investigated the relation between alcohol drinking and healthy ageing by meansof 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. ; This work was supported by the five-year Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) project. The ATHLOS project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 635316. The ATHLOS project researchers are grateful for data contribution and funding in the following studies: (A) The 10/66 study (10/66): The 10/66 study is supported by theWellcome Trust (GR066133/ GR080002), the European Research Council (340755), US Alzheimer's Association, WHO, FONDACIT (Venezuela) and the Puerto Rico State Government, and the Medical Research Council (MR/K021907/1 to A.M.P.). The authors gratefully acknowledge the work of the 10/66 Dementia Research Group who provided data for this paper; (B) The Australian Longitudinal Study of Ageing (ALSA): The ALSA study was supported by grants from the South Australian Health Commission, the Australian Rotary Health Research Fund, the US National Institute on Aging (Grant No. AG 08523–02), theO ce for the Ageing (SA), Elderly Citizens Homes (SA), the National Health and Medical Research Council (NH&MRC 22922), the Premiers Science Research Fund (SA) and the Australian Research Council (DP0879152; DP130100428). The authors gratefully acknowledge the work of the project team at the Flinders Centre for Ageing Studies, Flinders University who provided data for this paper; (C) The ATTICA study: The ATTICA study is supported by research grants from the Hellenic Cardiology Society (HCS2002) and the Hellenic Atherosclerosis Society (HAS2003). The authors gratefully acknowledge the work of the project team at the Harokopio University who provided data for this paper; (D) The China Health and Retirement Longitudinal Study (CHARLS): The CHARLS study has received critical support from Peking University, the National Natural Science Foundation of China, the Behavioral and Social Research Division of the National Institute on Aging and the World Bank. The authors gratefully acknowledge the work of the project team at the Peking University who provided data for this paper; (E) Collaborative Research on Ageing (COURAGE) in Europe: The COURAGE study was supported by the European Community's Seventh Framework Programme (FP7/2007–2013) under grant agreement number 223071 (COURAGE in Europe). Data from Spain were also collected with support from the Instituto de Salud Carlos III-FIS research grants number PS09/00295, PS09/01845, PI12/01490, PI13/00059, PI16/00218 and PI16/01073; the Spanish Ministry of Science and Innovation ACI-Promociona (ACI2009–1010); the European Regional Development Fund (ERDF) 'AWay to Build Europe' grant numbers PI12/01490 and PI13/00059; and by the Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III. Data from Poland were collected with support from the Polish Ministry for Science and Higher Education grant for an international co-financed project (number 1277/7PR/UE/2009/7, 2009–2012) and Jagiellonian University Medical College grant for project COURAGE-POLFUS (K/ZDS/005241). The authors gratefully acknowledge the work of COURAGE researchers who provided data for this paper; (F) The Seniors-ENRICA: The Seniors-ENRICA cohort was funded by an unconditional grant from Sanofi-Aventis, the Ministry of Health of Spain, FIS grant 12/1166 (State Secretary for R+D and FEDER-FSE) and the Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III. The authors gratefully acknowledge the work of the project team at the Universidad Autónoma de Madrid who provided data for this paper; (G) The English Longitudinal Study of Ageing (ELSA): ELSA is supported by the U.S. National Institute of Aging, the National Centre for Social Research, the University College London (UCL) and the Institute for Fiscal Studies. The authors gratefully acknowledge the UK Data Service and UCL who provided data for this paper; (H) The Health, Alcohol and Psychosocial factors In Eastern Europe (HAPIEE) study: The HAPIEE study was supported by theWellcome Trust (grant numbers WT064947, WT081081), the US National Institute of Aging (grant number 1RO1AG23522) and the MacArthur Foundation Initiative on Social Upheaval and Health. The authors gratefully acknowledge the work of the project teams at University College London, the National Institute of Public Health in Prague, the Jagiellonian University Medical College in Krakow and the Kaunas University of Medicine who provided data for this paper; (I) The Health 2000/2011 study: The authors gratefully acknowledge the National Institute for Health and Welfare in Finland who provided data for this paper; (J) Health and Retirement Study (HRS): The HRS study is supported by the National Institute on Aging (grant number NIA U01AG009740) and the Social Security Administration, and is conducted by the University of Michigan. The authors gratefully acknowledge the University of Michigan who provided data for this paper; (K) The Japanese Study of Aging and Retirement (JSTAR): The JSTAR is conducted by the Research Institute of Economy, Trade and Industry (RIETI), the Hitotsubashi University, and the University of Tokyo. The authors gratefully acknowledge the RIETI who provided data for this paper; (L) The Korean Longitudinal Study of Ageing (KLOSA): The KLOSA study is funded by the Korea Employment Information Service (KEIS) and was supported by the Korea Labor Institute's KLOSA Team. The authors gratefully acknowledge the KEIS who provided data for this paper; (M) The Mexican Health and Aging Study (MHAS): The MHAS study is partly sponsored by the National Institutes of Health/National Institute on Aging (grant number NIH R01AG018016) and the INEGI in Mexico. The authors gratefully acknowledge the MHAS team who provided data for this paper retrieved from www.MHASweb.org: (N) The Study on Global Ageing and Adult Health (SAGE): The SAGE study is funded by the U.S. National Institute on Aging and has received financial support through Interagency Agreements (OGHA 04034785; YA1323-08-CN-0020; Y1-AG-1005–01) and Grants (R01-AG034479; IR21-AG034263-0182). The authors gratefully acknowledge theWorld Health Organizationwho provided data for this paper; (O) The Survey of Health, Ageing and Retirement in Europe (SHARE): The SHARE study is funded by the European Commission through FP5 (QLK6-CT-2001–00360), FP6 (SHARE-I3: RII-CT-2006–062193, COMPARE: CIT5-CT-2005–028857, SHARELIFE: CIT4-CT-2006–028812) and FP7 (SHARE-PREP: N 211909, SHARE-LEAP: N 227822, SHARE M4: N 261982). Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the U.S. National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553–01, IAG_BSR06-11, OGHA_04-064, HHSN271201300071C) and from various national funding sources is gratefully acknowledged (see www.share-project.org); (P) The Irish Longitudinal study on Ageing (TILDA): The authors gratefully acknowledge the Trinity College Dublin and the Irish Social Science Data Archive (www.ucd.ie/issda) who provided data for this paper; (Q) The Uppsala Birth Cohort Multigenerational Study (UBCOS): The UBCoS study has received funding from the Swedish Research Council for Health, Working Life and Welfare (FORTE; 2006–1518 and 2013–1084) and from the Swedish Research Council (VR; 2013–5104 and 2013–5474). The authors gratefully acknowledge the Centre for Health Equity Studies at the Stockholm University and Karolinska Institutet's team who provided data for this paper. Additionally, Stefanos Tyrovolas was supported by the Foundation for Education and European Culture, the Miguel Servet programme (reference CP18/00006), and the Fondos Europeos de Desarrollo Regional. Also, Alberto Raggi is supported by a grant from the Italian Ministry of Health (Ricerca Corrente, Fondazione Istituto Neurologico C. Besta, Linea 4—Outcome Research: dagli Indicatori alle Raccomandazioni Cliniche. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The authors had access to the data in the study and had final responsibility for the decision to submit for publication.
