Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 May 24;13(11):3089.
doi: 10.3390/jcm13113089.

Musculoskeletal Diseases as the Most Prevalent Component of Multimorbidity: A Population-Based Study

Nina Rajovic  1 , Slavisa Zagorac  2   3 , Andja Cirkovic  1 , Bojana Matejic  4 , Danilo Jeremic  3   5 , Radica Tasic  6 , Jelena Cumic  3   7 , Srdjan Masic  8 , Jovana Grupkovic  2 , Vekoslav Mitrovic  9 , Natasa Milic  1   10 , Boris Gluscevic  3   5
Affiliations

Musculoskeletal Diseases as the Most Prevalent Component of Multimorbidity: A Population-Based Study

Nina Rajovic et al. J Clin Med. .

Abstract

Background/Objectives: Due to their high frequency, common risk factors, and similar pathogenic mechanisms, musculoskeletal disorders (MSDs) are more likely to occur with other chronic illnesses, making them a "component disorder" of multimorbidity. Our objective was to assess the prevalence of multimorbidity and to identify the most common clusters of diagnosis within multimorbidity states, with the primary hypothesis that the most common clusters of multimorbidity are MSDs. Methods: The current study employed data from a population-based 2019 European Health Interview Survey (EHIS). Multimorbidity was defined as a ≥2 diagnosis from the list of 17 chronic non-communicable diseases, and to define clusters, the statistical method of hierarchical cluster analysis (HCA) was performed. Results: Out of 13,178 respondents, multimorbidity was present among 4398 (33.4%). The HCA method yielded six multimorbidity clusters representing the most common diagnoses. The primary multimorbidity cluster, which was prevalent among both genders, age groups, incomes per capita, and statistical regions, consisted of three diagnoses: (1) lower spine deformity or other chronic back problem (back pain), (2) cervical deformity or other chronic problem with the cervical spine, and (3) osteoarthritis. Conclusions: Given the influence of musculoskeletal disorders on multimorbidity, it is imperative to implement appropriate measures to assist patients in relieving the physical discomfort and pain they endure. Public health information, programs, and campaigns should be utilized to promote a healthy lifestyle. Policymakers should prioritize the prevention of MSDs by encouraging increased physical activity and a healthy diet, as well as focusing on improving functional abilities.

Keywords: cervical deformity; hierarchical cluster analysis; low back deformity; multimorbidity; musculoskeletal disorders; osteoarthritis.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
(a) Multimorbidity distribution categorized by age groups; (b) multimorbidity distribution based on monthly income per capita; (c) multimorbidity distribution in four statistical regions of Serbia.
Figure 1
Figure 1
(a) Multimorbidity distribution categorized by age groups; (b) multimorbidity distribution based on monthly income per capita; (c) multimorbidity distribution in four statistical regions of Serbia.
Figure 2
Figure 2
Dendrogram of most common clusters of multimorbidity obtained by HCA method.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Barnett K., Mercer S.W., Norbury M., Watt G., Wyke S., Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: A cross-sectional study. Lancet. 2012;380:37–43. doi: 10.1016/S0140-6736(12)60240-2. - DOI - PubMed
    1. The Academy of Medical Sciences. Multimorbidity: A Priority for Global Health Research. Academy of Medical Sciences. 2018. [(accessed on 15 April 2024)]. Available online: https://acmedsci.ac.uk/filedownload/82222577.
    1. Hien H., Berthé A., Drabo M.K., Meda N., Konaté B., Tou F., Badini-Kinda F., Macq J. Prevalence and patterns of multimorbidity among the elderly in Burkina Faso: Cross-sectional study. Trop. Med. Int. Health. 2014;19:1328–1333. doi: 10.1111/tmi.12377. - DOI - PubMed
    1. Pati S., Swain S., Hussain M.A., Kadam S., Salisbury C. Prevalence, correlates, and outcomes of multimorbidity among patients attending primary care in Odisha, India. Ann. Fam. Med. 2015;13:446–450. doi: 10.1370/afm.1843. - DOI - PMC - PubMed
    1. Vadrevu L., Kumar V., Kanjilal B. Rising challenge of multiple morbidities among the rural poor in India—A case of the Sundarbans in West Bengal. Int. J. Med. Sci. Public Health. 2016;5:343. doi: 10.5455/ijmsph.2016.25082015129. - DOI

LinkOut - more resources