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Socioeconomic inequalities in physical, psychological, and cognitive multimorbidity in middle-aged and older adults in 33 countries: a cross-sectional study.
Ni, Yujie; Zhou, Yaguan; Kivimäki, Mika; Cai, Ying; Carrillo-Larco, Rodrigo M; Xu, Xin; Dai, Xiaochen; Xu, Xiaolin.
Afiliação
  • Ni Y; School of Public Health, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, China.
  • Zhou Y; School of Public Health, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, China.
  • Kivimäki M; UCL Brain Sciences, University College London, London, UK.
  • Cai Y; Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China.
  • Carrillo-Larco RM; Emory Global Diabetes Research Center, Emory University, Atlanta, GA, USA; Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
  • Xu X; School of Public Health, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, China.
  • Dai X; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
  • Xu X; School of Public Health, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, China; School of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Au
Lancet Healthy Longev ; 4(11): e618-e628, 2023 11.
Article em En | MEDLINE | ID: mdl-37924843
ABSTRACT

BACKGROUND:

Many physical, psychological, and cognitive disorders are highly clustered among populations with low socioeconomic status. However, the extent to which socioeconomic status is associated with different combinations of these disorders is unclear, particularly outside high-income countries. We aimed to evaluate these associations in 33 countries including high-income countries, upper-middle-income countries, and one lower-middle-income country.

METHODS:

This cross-sectional multi-region study pooled individual-level data from seven studies on ageing between 2017 and 2020. Education and total household wealth were used to measure socioeconomic status. Physical disorder was defined as having one or more of the self-reported chronic conditions. Psychological and cognitive disorders were measured by study-specific instruments. The outcome included eight categories no disorders, physical disorder, psychological disorder, cognitive disorder, and their four combinations. Multivariable-adjusted logistic regression models were used to estimate odds ratios (ORs) and 95% CIs for the associations of socioeconomic status with these outcomes separately for high-income countries, upper-middle-income countries, and the lower-middle-income country.

FINDINGS:

Among 167 376 individuals aged 45 years and older, the prevalence of multimorbidity was 24·5% in high-income countries, 33·9% in upper-middle-income countries, and 8·1% in the lower-middle-income country (India). Lower levels of education, household wealth, and a combined socioeconomic status score were strongly associated with physical, psychological, and cognitive multimorbidity in high-income countries and upper-middle-income countries, with ORs (low vs high socioeconomic status) for physical-psychological-cognitive multimorbidity of 12·36 (95% CI 10·29-14·85; p<0·0001) in high-income countries and of 23·84 (18·85-30·14; p<0·0001) in upper-middle-income countries. The associations in the lower-middle-income country were mixed. Participants with both a low level of education and low household wealth had the highest odds of multimorbidity (eg, OR for physical-psychological-cognitive multimorbidity 21·21 [15·95-28·19; p<0·0001] in high-income countries, 37·07 [25·66-53·56; p<0·0001] in upper-middle-income countries, and 54·96 [7·66-394·38; p<0·0001] in the lower-middle-income country).

INTERPRETATION:

In study populations from high-income countries, upper-middle-income countries, and the lower-middle-income country, the odds of multimorbidity, which included physical, psychological, and cognitive disorders, were more than ten times greater in individuals with low socioeconomic status. Equity-oriented policies and programmes that reduce social inequalities in multimorbidity are urgently needed to achieve Sustainable Development Goals.

FUNDING:

Zhejiang University, Fundamental Research Funds for the Central Universities, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Wellcome Trust, Medical Research Council, National Institute on Aging, and Academy of Finland. TRANSLATION For the Chinese translation of the abstract see Supplementary Materials section.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Envelhecimento / Multimorbidade Limite: Aged / Humans / Middle aged Idioma: En Revista: Lancet Healthy Longev Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Envelhecimento / Multimorbidade Limite: Aged / Humans / Middle aged Idioma: En Revista: Lancet Healthy Longev Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China