Abstract
This chapter summarises the global and regional prevalence, disability (Years Lived with Disability (YLDs)) and overall burden (Disability Adjusted Life Years (DALYs)) and costs for the common musculoskeletal disorders including low back and neck pain, hip and knee osteoarthritis, rheumatoid arthritis, gout, and a remaining combined group of other MSK conditions. The contribution of the role of pain in disability burden is introduced. Trends over time and predictions of increasing MSK disability with demographic changes are addressed and the particular challenges facing the developing world are highlighted.
Over the past century, global health priorities in health have been largely focussed on communicable diseases. With the world’s population growth, increased average age and decreased death rates , people are now living longer and becoming increasingly susceptible to non-communicable diseases, including musculoskeletal (MSK) disorders. In the recent Global Burden of Disease (GBD) 2010 Study, the burden disability of all MSK disorders was estimated in 187 countries and 21 regions of the world for the years 1990 and 2010. In the burden estimates, there were five major defined conditions and all other MSK disorders (the rest) captured in a group titled ‘other MSK disorders’. The defined conditions were (1) osteoarthritis (OA), (2) rheumatoid arthritis (RA), (3) gout, (4) low back pain (LBP) and (5) neck pain (NP). Throughout the world, the prevalence and burden from MSK conditions were exceptionally high . Globally, all MSK disorders combined accounted for 21.3% of the total years lived with disability (YLDs), second to mental and behavioural problems (23.2%) . When taking into account both death and disability, all MSK disorders combined accounted for 6.7% of the total global disability-adjusted life years (DALYs), which was the fourth greatest burden on the health of the world’s population (third greatest in developed countries) . Out of the 291 conditions studied, LBP ranked first (highest) for disability (YLDs) and sixth for the overall burden (DALYs). For NP, the condition ranked fourth highest for YLDs and 21st for DALYs. ‘Other MSK disorders’ ranked sixth highest for YLDs and 23rd for DALYs. OA, RA and gout were also significant contributors to the global disability burden.
Osteoporosis represented by low bone mineral density (BMD) was included in the GBD 2010 Study for the first time as one of the 67 risk factors studied. Population-attributable fractions (PAFs) were determined for low BMD as a risk factor for fractures. Additionally, PAFs were also determined for occupation as a risk factor for LBP, and elevated body mass index as a risk factor for LBP and OA.
In this chapter, aspects related to the burden of disability due to MSK disorders are described, including the prevalence, disability and role of pain related to disability, costs associated with MSK disorders and predictions of increasing MSK disability with demographic changes and socio-economic impact.
Prevalence of musculoskeletal disorders
The prevalence and incidence of a series of MSK disorders reported in population-based epidemiological studies were systematically reviewed and published . In the GBD 2010 Study, extensive systematic reviews of the prevalence of each of the MSK disorders (knee and hip OA, RA, LPB, NP, gout and other MSK disorders) were conducted from the years 1980 to 2009 . Searches were carried out in MEDLINE, EMBASE, CINAHL, CAB abstracts, WHOLIS and SIGLE databases, with no age, gender or language restrictions. The data were required to be population based and were excluded if they were not representative of the general population. For some conditions, prevalence data from a number of data sets, including world health surveys and national health surveys, were also included. Some variability observed in the data were the case definition used, age groupings and the reported prevalence periods. In addition, there were some missing data for specific age groups, regions and years of interest.
To deal with these challenges and to estimate the prevalence rates for each of the world regions, a Bayesian meta-regression tool, DisMod-MR , was utilised. The tool was developed by the GBD core team, at the Institute for Health Metrics and Evaluation (IHME), University of Washington, Seattle, WA, USA. It was used to pool heterogeneous data presented in different age groups, to adjust data for methodological differences, to check data for internal consistency and to predict values for countries and regions with little or no data. DisMod-MR produced a full set of age/sex/region/year-specific estimates for prevalence. Using the available data from the systematic reviews and population-based data sets, age-standardised prevalence estimates were modelled for the years 1990 and 2010. The prevalence estimates for the MSK disorders within each of the 21 world regions are shown below.
| Region | OA Hip | OA Knee | RA | LBP | NP | Gout | Other MSK | |
|---|---|---|---|---|---|---|---|---|
| Global | Total (%) | 0.9 | 3.8 | 0.24 | 9.4 | 4.9 | 0.08 | 8.36 |
| 95% UI | 0.7–1.0 | 3.6–4.1 | 0.23–0.25 | 9.0–9.8 | 4.6–5.3 | 0.07–0.08 | 8.1–8.6 | |
| Central Asia | Total (%) | 1.0 | 4.1 | 0.29 | 8.4 | 5.0 | 0.04 | 8.87 |
| 95% UI | 0.7–1.5 | 3.5–4.8 | 0.23–0.36 | 7.4–9.6 | 4.4–5.6 | 0.03–0.05 | 7.8–10.1 | |
| East Asia | Total (%) | 0.3 | 4.0 | 0.16 | 6.7 | 5.9 | 0.06 | 7.19 |
| 95% UI | 0.2–0.3 | 3.2–4.8 | 0.15–0.18 | 5.5–8.0 | 4.7–7.3 | 0.05–0.06 | 6.8–7.6 | |
| High-income Asia Pacific | Total (%) | 1.4 | 6.0 | 0.40 | 9.0 | 5.7 | 0.08 | 11.26 |
| 95% UI | 0.7–2.6 | 5.0–7.1 | 0.35–0.46 | 7.2–11.1 | 4.8–6.7 | 0.06–0.1 | 9.1–14.1 | |
| South Asia | Total (%) | 0.9 | 2.5 | 0.17 | 10.2 | 3.3 | 0.02 | 6.94 |
| 95% UI | 0.5–1.8 | 2.1–2.9 | 0.16–0.19 | 9.0–11.5 | 2.8–4.0 | 0.01–0.02 | 6.5–7.4 | |
| Southeast Asia | Total (%) | 0.7 | 3.0 | 0.16 | 7.8 | 3.8 | 0.06 | 6.92 |
| 95% UI | 0.5–1.0 | 2.6–3.6 | 0.15–0.18 | 7.1–8.7 | 3.4–4.3 | 0.05–0.07 | 6.1–7.9 | |
| Australasia | Total (%) | 0.8 | 3.5 | 0.46 | 12.2 | 5.7 | 0.39 | 10.40 |
| 95% UI | 0.7–1.0 | 2.7–4.4 | 0.30–0.70 | 10.5–13.9 | 4.5–7.1 | 0.35–0.43 | 9.7–11.1 | |
| Caribbean | Total (%) | 1.0 | 4.1 | 0.27 | 6.5 | 4.9 | 0.03 | 7.86 |
| 95% UI | 0.6–1.5 | 3.4–4.9 | 0.23–0.32 | 5.6–7.4 | 4.3–5.5 | 0.02–0.04 | 7.0–8.8 | |
| Central Europe | Total (%) | 1.0 | 4.1 | 0.28 | 11.4 | 5.0 | 0.05 | 8.89 |
| 95% UI | 0.7–1.5 | 3.5–4.7 | 0.23–0.35 | 10.0–13.1 | 4.4–5.6 | 0.03–0.07 | 7.8–10.1 | |
| Eastern Europe | Total (%) | 1.0 | 3.8 | 0.28 | 11.2 | 5.0 | 0.05 | 8.94 |
| 95% UI | 0.6–1.9 | 2.9–4.9 | 0.19–0.39 | 9.8–12.8 | 4.2–6.0 | 0.03–0.08 | 7.2–11.0 | |
| Western Europe | Total (%) | 1.0 | 3.6 | 0.44 | 15.0 | 6.3 | 0.20 | 10.05 |
| 95% UI | 0.9–1.3 | 3.2–4.0 | 0.39–0.51 | 14.1–16.0 | 5.8–6.8 | 0.18–0.24 | 9.0–11.1 | |
| Andean Latin America | Total (%) | 1.0 | 4.1 | 0.28 | 7.4 | 4.9 | 0.04 | 8.78 |
| 95% UI | 0.6–1.8 | 3.3–5.2 | 0.19–0.38 | 5.9–9.0 | 4.1–5.8 | 0.03–0.07 | 7.3–10.5 | |
| Central Latin America | Total (%) | 1.0 | 4.1 | 0.28 | 6.6 | 4.5 | 0.03 | 9.07 |
| 95% UI | 0.6–1.6 | 3.4–5.1 | 0.24–0.33 | 5.8–7.4 | 3.9–5.2 | 0.02–0.04 | 8.3–10.0 | |
| Southern Latin America | Total (%) | 1.4 | 4.2 | 0.36 | 8.0 | 5.6 | 0.28 | 10.42 |
| 95% UI | 0.7–2.6 | 3.2–5.3 | 0.26–0.51 | 6.1–10.0 | 4.7–6.8 | 0.15–0.49 | 8.5–12.7 | |
| Tropical Latin America | Total (%) | 1.0 | 4.2 | 0.26 | 11.1 | 4.9 | 0.04 | 8.31 |
| 95% UI | 0.4–2.0 | 3.0–6.0 | 0.25–0.28 | 9.4–13.2 | 3.9–6.3 | 0.02–0.09 | 7.8–8.8 | |
| North Africa and Middle East | Total (%) | 0.6 | 5.7 | 0.16 | 14.8 | 4.3 | 0.03 | 7.41 |
| 95% UI | 0.4–0.7 | 5.1–6.4 | 0.14–0.19 | 13.8–15.9 | 3.9–4.7 | 0.02–0.03 | 6.7–8.2 | |
| High-income North America | Total (%) | 1.9 | 4.1 | 0.44 | 7.7 | 6.5 | 0.24 | 14.21 |
| 95% UI | 1.8–2.2 | 3.4–4.9 | 0.41–0.48 | 6.5–9.0 | 5.6–7.5 | 0.22–0.28 | 13.4–15.1 | |
| Oceania | Total (%) | 0.7 | 5.8 | 0.17 | 8.1 | 4.6 | 0.12 | 8.80 |
| 95% UI | 0.4–1.2 | 4.5–7.3 | 0.12–0.26 | 6.1–10.3 | 3.8–5.6 | 0.06–0.21 | 7.1–10.7 | |
| Central sub-Saharan Africa | Total (%) | 1.0 | 4.1 | 0.21 | 8.2 | 5.1 | 0.04 | 8.78 |
| 95% UI | 0.6–1.7 | 3.2–5.3 | 0.15–0.31 | 6.3–10.6 | 4.2–6.2 | 0.02–0.06 | 7.2–10.6 | |
| East sub-Saharan Africa | Total (%) | 1.0 | 4.1 | 0.20 | 8.6 | 5.1 | 0.03 | 8.74 |
| 95% UI | 0.7–1.3 | 3.6–4.7 | 0.17–0.25 | 7.9–9.5 | 4.6–5.7 | 0.02–0.05 | 7.7–9.8 | |
| Southern sub-Saharan Africa | Total (%) | 0.7 | 4.2 | 0.21 | 7.4 | 5.8 | 0.03 | 8.88 |
| 95% UI | 0.6–0.8 | 3.2–5.6 | 0.19–0.23 | 6.5–8.4 | 4.9–6.9 | 0.01–0.05 | 7.0–11.1 | |
| West sub-Saharan Africa | Total (%) | 0.9 | 4.1 | 0.19 | 10.6 | 5.1 | 0.02 | 8.82 |
| 95% UI | 0.6–1.5 | 3.4–5.1 | 0.18–0.22 | 9.6–11.7 | 4.5–5.8 | 0.02–0.02 | 7.5–10.3 | |
Related posts:
A time for action: Opportunities for preventing the growing burden and disability from musculoskeletal conditions in low- and middle-income countries
Determinants of MSK health and disability – Social determinants of inequities in MSK health
Determinants of MSK health and disability: Lifestyle determinants of symptomatic osteoarthritis
Corrigendum to “Granulomatous inflammation: the overlap of immune deficiency and inflammation” [Best Pract Res Clin Rheumatol 28 (2014) 191–212]
‘Erratum to “Osteoporosis and fragility fractures: Vertebral fractures” [Best Practice & Research Clinical Rheumatology 27 (2013) 743–55]’
A public health approach to musculoskeletal health
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