Background The role of diet quality in the accumulation of multiple chronic conditions is mostly unknown. This study examined diet quality in association with the number of chronic conditions and the rate of multimorbidity development among community-dwelling older adults.
Methods We used data from 2 784 adults aged ≥65 years from the Seniors-ENRICA 2 cohort. Diet quality was assessed at baseline (2015–17) with the Alternate Healthy Eating Index-2010 (AHEI-2010) and the Mediterranean Diet Adherence Screener (MEDAS). Information on medical diagnoses was obtained from electronic clinical records up to 2021.
Results Higher adherence to the AHEI-2010 was associated with a lower number of total chronic conditions (β [95% CI] quartile 4 vs 1: −0.57 [−0.86 to 0.27], p trend < .001] and cardiometabolic conditions (−0.30 [−0.44 to −0.17], p trend < .001) at baseline, while higher adherence to the MEDAS was associated with a lower number of total chronic conditions (−0.30 [−0.58 to −0.02], p trend = .01) and neuropsychiatric and neurodegenerative conditions (−0.09 [−0.17 to −0.01], p trend = .01). After a median follow-up of 5.2 years (range: 0.1–6.1 years) higher adherence to the AHEI-2010 was associated with a lower increase in chronic conditions (β [95% confidence interval] quartile 4 vs 1: −0.16 [−0.30 to −0.01], p trend = .04) and with lower rate of chronic disease accumulation.
Conclusions Higher diet quality, as measured by the AHEI-2010, was associated with a lower number of chronic health conditions and a lower rate of multimorbidity development over time.
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.
