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Updated: May 3, 2026

The MODS method for diagnosis of tuberculosis and multidrug resistant tuberculosis
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Multimorbidity patterns: a systematic review.

Alexandra Prados-Torres1, Amaia Calderón-Larrañaga1, Jorge Hancco-Saavedra2

  • 1EpiChron Research Group on Chronic Diseases, Aragón Health Sciences Institute (IACS), IIS Aragón, Miguel Servet University Hospital, Pl +2, Paseo Isabel la Católica 1-3, 50009, Zaragoza, Spain; Department of Microbiology, Preventive Medicine and Public Health, University of Zaragoza, Facultad de Medicina, C/ Domingo Miral s/n, 50009, Zaragoza, Spain; Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Carlos III Health Institute, Madrid, Spain; Teaching Unit of Preventive Medicine and Public Health, Aragón Health Sciences Institute (IACS), IIS Aragón, Edificio CIBA, Avda. San Juan Bosco 13, 50009, Zaragoza, Spain.

Journal of Clinical Epidemiology
|January 30, 2014
PubMed
Summary

This review identified common disease patterns in associative multimorbidity, finding links between cardiovascular/metabolic diseases, mental health issues, and musculoskeletal disorders. Further research is needed to understand these nonrandom disease associations.

Keywords:
Associative multimorbidityChronic diseaseElectronic medical recordsPatient-centered carePractice guidelinesPrimary health care

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Area of Science:

  • Epidemiology
  • Medical Informatics
  • Public Health

Background:

  • Associative multimorbidity, the nonrandom co-occurrence of diseases, presents a complex challenge in healthcare.
  • Understanding disease patterns is crucial for effective disease management and prevention strategies.

Purpose of the Study:

  • To systematically review studies on associative multimorbidity patterns.
  • To identify methodological features and commonalities in observed disease associations.

Main Methods:

  • Comprehensive literature search of MEDLINE and EMBASE databases up to June 2012.
  • Inclusion of studies identified through bibliographies.
  • Analysis of methodological heterogeneity and identified disease patterns.

Main Results:

  • 14 articles were reviewed, exhibiting methodological heterogeneity.
  • 97 distinct disease patterns were identified, with 63 involving three or more diseases.
  • Three consistent pattern groups emerged: cardiovascular/metabolic diseases, mental health disorders, and musculoskeletal disorders.

Conclusions:

  • Despite methodological variations, significant similarities in disease patterns were observed.
  • The identified patterns suggest non-chance associations between diseases.
  • Future research should focus on quantifying these associations and elucidating underlying causal mechanisms.