Literature DB >> 33572441

Definitions and Prevalence of Multimorbidity in Large Database Studies: A Scoping Review.

Ying Pin Chua1, Ying Xie2, Poay Sian Sabrina Lee2, Eng Sing Lee1,2.   

Abstract

BACKGROUND: Multimorbidity presents a key challenge to healthcare systems globally. However, heterogeneity in the definition of multimorbidity and design of epidemiological studies results in difficulty in comparing multimorbidity studies. This scoping review aimed to describe multimorbidity prevalence in studies using large datasets and report the differences in multimorbidity definition and study design.
METHODS: We conducted a systematic search of MEDLINE, EMBASE, and CINAHL databases to identify large epidemiological studies on multimorbidity. We used the Preferred Reporting Items for Systematic Reviews and Meta-analysis Extension for Scoping Reviews (PRISMA-ScR) protocol for reporting the results.
RESULTS: Twenty articles were identified. We found two key definitions of multimorbidity: at least two (MM2+) or at least three (MM3+) chronic conditions. The prevalence of multimorbidity MM2+ ranged from 15.3% to 93.1%, and 11.8% to 89.7% in MM3+. The number of chronic conditions used by the articles ranged from 15 to 147, which were organized into 21 body system categories. There were seventeen cross-sectional studies and three retrospective cohort studies, and four diagnosis coding systems were used.
CONCLUSIONS: We found a wide range in reported prevalence, definition, and conduct of multimorbidity studies. Obtaining consensus in these areas will facilitate better understanding of the magnitude and epidemiology of multimorbidity.

Entities:  

Keywords:  definition; large database; multimorbidity; prevalence

Year:  2021        PMID: 33572441      PMCID: PMC7916224          DOI: 10.3390/ijerph18041673

Source DB:  PubMed          Journal:  Int J Environ Res Public Health        ISSN: 1660-4601            Impact factor:   3.390


  45 in total

1.  Cross sectional survey of multicentre clinical databases in the United Kingdom.

Authors:  Nick Black; Marian Barker; Mary Payne
Journal:  BMJ       Date:  2004-06-19

Review 2.  Sample size estimation in epidemiologic studies.

Authors:  Karimollah Hajian-Tilaki
Journal:  Caspian J Intern Med       Date:  2011

3.  Measuring diagnoses: ICD code accuracy.

Authors:  Kimberly J O'Malley; Karon F Cook; Matt D Price; Kimberly Raiford Wildes; John F Hurdle; Carol M Ashton
Journal:  Health Serv Res       Date:  2005-10       Impact factor: 3.402

4.  Collaborative care for patients with depression and chronic illnesses.

Authors:  Wayne J Katon; Elizabeth H B Lin; Michael Von Korff; Paul Ciechanowski; Evette J Ludman; Bessie Young; Do Peterson; Carolyn M Rutter; Mary McGregor; David McCulloch
Journal:  N Engl J Med       Date:  2010-12-30       Impact factor: 91.245

5.  Patterns of multimorbidity in elderly veterans.

Authors:  Michael A Steinman; Sei J Lee; W John Boscardin; Yinghui Miao; Kathy Z Fung; Kelly L Moore; Janice B Schwartz
Journal:  J Am Geriatr Soc       Date:  2012-10-04       Impact factor: 5.562

6.  Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.

Authors:  Karen Barnett; Stewart W Mercer; Michael Norbury; Graham Watt; Sally Wyke; Bruce Guthrie
Journal:  Lancet       Date:  2012-05-10       Impact factor: 79.321

7.  Development of a research tool to document self-reported chronic conditions in primary care.

Authors:  Martin Fortin; José Almirall; Kathryn Nicholson
Journal:  J Comorb       Date:  2017-11-09

8.  Multimorbidity, healthcare utilization and socioeconomic status: A register-based study in Denmark.

Authors:  Anne Frølich; Nermin Ghith; Michaela Schiøtz; Ramune Jacobsen; Anders Stockmarr
Journal:  PLoS One       Date:  2019-08-01       Impact factor: 3.240

9.  Impact of multimorbidity: acute morbidity, area of residency and use of health services across the life span in a region of south Europe.

Authors:  Quintí Foguet-Boreu; Concepció Violan; Albert Roso-Llorach; Teresa Rodriguez-Blanco; Mariona Pons-Vigués; Miguel A Muñoz-Pérez; Enriqueta Pujol-Ribera; Jose M Valderas
Journal:  BMC Fam Pract       Date:  2014-03-26       Impact factor: 2.497

10.  The influence of socioeconomic deprivation on multimorbidity at different ages: a cross-sectional study.

Authors:  Gary McLean; Jane Gunn; Sally Wyke; Bruce Guthrie; Graham C M Watt; David N Blane; Stewart W Mercer
Journal:  Br J Gen Pract       Date:  2014-07       Impact factor: 5.386

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  5 in total

1.  Age, sex, residence, and region-specific differences in prevalence and patterns of multimorbidity among older Chinese: evidence from Chinese Longitudinal Healthy Longevity Survey.

Authors:  Siyue Han; Guangju Mo; Tianjing Gao; Qing Sun; Huaqing Liu; Min Zhang
Journal:  BMC Public Health       Date:  2022-06-04       Impact factor: 4.135

Review 2.  Multimorbidity matters in low and middle-income countries.

Authors:  Ana Basto-Abreu; Tonatiuh Barrientos-Gutierrez; Alisha N Wade; Daniela Oliveira de Melo; Ana S Semeão de Souza; Bruno P Nunes; Arokiasamy Perianayagam; Maoyi Tian; Lijing L Yan; Arpita Ghosh; J Jaime Miranda
Journal:  J Multimorb Comorb       Date:  2022-06-16

3.  Age- and Sex-Specific Differences in Multimorbidity Patterns and Temporal Trends on Assessing Hospital Discharge Records in Southwest China: Network-Based Study.

Authors:  Liya Wang; Hang Qiu; Li Luo; Li Zhou
Journal:  J Med Internet Res       Date:  2022-02-25       Impact factor: 7.076

4.  Inequality of opportunity in a land of equal opportunities: The impact of parents' health and wealth on their offspring's quality of life in Norway.

Authors:  Espen Berthung; Nils Gutacker; Birgit Abelsen; Jan Abel Olsen
Journal:  BMC Public Health       Date:  2022-09-06       Impact factor: 4.135

5.  Multimorbidity in the elderly in China based on the China Health and Retirement Longitudinal Study.

Authors:  Xiaorong Guo; Benhua Zhao; Tianmu Chen; Bin Hao; Tao Yang; Huimin Xu
Journal:  PLoS One       Date:  2021-08-05       Impact factor: 3.240

  5 in total

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