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Research ArticleOriginal Research

Predicting Incident Multimorbidity

Luke T. A. Mounce, John L. Campbell, William E. Henley, Maria C. Tejerina Arreal, Ian Porter and Jose M. Valderas
The Annals of Family Medicine July 2018, 16 (4) 322-329; DOI: https://doi.org/10.1370/afm.2271
Luke T. A. Mounce
1University of Exeter Medical School, St Luke’s Campus, Exeter, Devon, United Kingdom
PhD
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John L. Campbell
1University of Exeter Medical School, St Luke’s Campus, Exeter, Devon, United Kingdom
MD
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William E. Henley
1University of Exeter Medical School, St Luke’s Campus, Exeter, Devon, United Kingdom
PhD
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Maria C. Tejerina Arreal
2Faculty of Psychology, University of Murcia, Murcia, Spain
PhD, MPH, LCP
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Ian Porter
1University of Exeter Medical School, St Luke’s Campus, Exeter, Devon, United Kingdom
PhD
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Jose M. Valderas
1University of Exeter Medical School, St Luke’s Campus, Exeter, Devon, United Kingdom
BMBS, PhD, MPH
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  • For correspondence: J.M.Valderas@exeter.ac.uk
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Abstract

PURPOSE Multimorbidity is associated with adverse outcomes, yet research on the determinants of its incidence is lacking. We investigated which sociodemographic, health, and individual lifestyle (eg, physical activity, smoking behavior, body mass index) characteristics predict new cases of multimorbidity.

METHODS We used data from 4,564 participants aged 50 years and older in the English Longitudinal Study of Aging that included a 10-year follow-up period. Discrete time-to-event (complementary log-log) models were constructed for exploring the associations of baseline characteristics with outcomes between 2002-2003 and 2012-2013 separately for participants with no initial conditions (n = 1,377) developing multimorbidity, any increase in conditions within 10 years regardless of initial conditions, and the impact of individual conditions on incident multimorbidity.

RESULTS The risks of developing multimorbidity were positively associated with age, and they were greater for the least wealthy, for participants who were obese, and for those who reported the lowest levels of physical activity or an external locus of control (believing that life events are outside of one’s control) for all groups regardless of baseline conditions (all linear trends <.05). No significant associations were observed for sex, educational attainment, or social detachment. For participants with any increase in conditions (n = 4,564), a history of smoking was the only additional predictor. For participants with a single baseline condition (n = 1,534), chronic obstructive pulmonary disease (COPD), asthma, and arrhythmia showed the strongest associations with subsequent multimorbidity.

CONCLUSIONS Our findings support the development and implementation of a strategy targeting the prevention of multimorbidity for susceptible groups. This approach should incorporate behavior change addressing lifestyle factors and target health-related locus of control.

Key words
  • multimorbidity
  • epidemiology
  • incidence
  • determinants
  • patient characteristics
  • older people
  • Received for publication November 20, 2017.
  • Revision received April 3, 2018.
  • Accepted for publication April 19, 2018.
  • © 2018 Annals of Family Medicine, Inc.
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The Annals of Family Medicine: 16 (4)
The Annals of Family Medicine: 16 (4)
Vol. 16, Issue 4
July/August 2018
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Predicting Incident Multimorbidity
Luke T. A. Mounce, John L. Campbell, William E. Henley, Maria C. Tejerina Arreal, Ian Porter, Jose M. Valderas
The Annals of Family Medicine Jul 2018, 16 (4) 322-329; DOI: 10.1370/afm.2271

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Predicting Incident Multimorbidity
Luke T. A. Mounce, John L. Campbell, William E. Henley, Maria C. Tejerina Arreal, Ian Porter, Jose M. Valderas
The Annals of Family Medicine Jul 2018, 16 (4) 322-329; DOI: 10.1370/afm.2271
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