Quantifying the population burden of musculoskeletal disorders, including impact on sickness absence: analysis of national Scottish data

Abstract Objectives Musculoskeletal disorders (MSDs) account for the greatest burden of years lived with disability globally. To prevent disability, good-quality services need to be commissioned, appropriate for local need. We analysed data collected systematically from a new musculoskeletal service serving 70% of the population of Scotland to evaluate: age- and sex-specific occurrence; anatomical distribution; and impact and effect on work ability. Methods A new centralized telephone-based triage for people with musculoskeletal disorders was set up in Scotland in 2015. Available to most of the population aged >16 years (>3 million people), data were collected systematically into a database detailing: anatomical site, nature of onset, duration, impact/risk (modified STarT score), deprivation level and, for those in employment, sickness absence. Results Data were available from 219 314 new callers, 2015–18. Calls were more frequently from women (60%), increased with age until the eighth decade, and 66% reported symptoms that had been present for >6 weeks. Callers were more likely to be living in more deprived areas in each age band between 20 and 64 years and tended to have higher-impact symptoms. The majority (53%) of callers were in employment, and 19% of these were off sick because of their symptoms. Sickness absence was more common among those with highest impact/risk scores from deprived areas with more acute symptoms. Discussion Large-scale systematic data collection for MSDs emphasizes the size and impact of the burden among adults aged >16 years. A socio-economic gradient is evident in terms of prevalence and impact of MSDs, particularly for sickness absence.

[1]  J. Protheroe,et al.  Refinement and validation of a tool for stratifying patients with musculoskeletal pain , 2021, European journal of pain.

[2]  F. Blyth,et al.  Health systems strengthening to arrest the global disability burden: empirical development of prioritised components for a global strategy for improving musculoskeletal health , 2021, BMJ Global Health.

[3]  C. Sinopidis,et al.  Cross-cultural validation of the start back screening tool in a Greek low back pain sample. , 2021, Musculoskeletal science & practice.

[4]  T. Vos,et al.  Global estimates of the need for rehabilitation based on the Global Burden of Disease study 2019: a systematic analysis for the Global Burden of Disease Study 2019 , 2020, The Lancet.

[5]  T. Pincus,et al.  STarT back tool retained its predicting abilities in patients with acute and sub-acute low back pain after a transcultural adaptation and validation to Hebrew. , 2020, Musculoskeletal science & practice.

[6]  S. Linton,et al.  Association of STarT Back Tool and the short form of the Örebro Musculoskeletal Pain Screening Questionnaire with multidimensional risk factors , 2020, Scientific Reports.

[7]  T. Lehtimäki,et al.  Exposure to heavy physical work from early to later adulthood and primary healthcare visits due to musculoskeletal diseases in midlife: a register linked study , 2019, BMJ Open.

[8]  Blair H Smith,et al.  Chronic pain: a review of its epidemiology and associated factors in population-based studies. , 2019, British journal of anaesthesia.

[9]  K. Bhaskaran,et al.  Identification of mental health and quality of life outcomes in primary care databases in the UK: a systematic review , 2019, BMJ Open.

[10]  A. Kiadaliri,et al.  Educational inequalities in mortality associated with rheumatoid arthritis and other musculoskeletal disorders in Sweden , 2019, BMC Musculoskeletal Disorders.

[11]  Carmen Huckel Schneider,et al.  The Global Burden of Musculoskeletal Pain-Where to From Here? , 2019, American journal of public health.

[12]  Andrew J. Knighton Is a Patient's Current Address of Record a Reasonable Measure of Neighborhood Deprivation Exposure? A Case for the Use of Point in Time Measures of Residence in Clinical Care , 2018, Health equity.

[13]  M. Fliesser,et al.  Education, job position, income or multidimensional indices? Associations between different socioeconomic status indicators and chronic low back pain in a German sample: a longitudinal field study , 2018, BMJ Open.

[14]  R. K. Celeste,et al.  Do socioeconomic inequalities in pain, psychological distress and oral health increase or decrease over the life course? Evidence from Sweden over 43 years of follow-up , 2017, Journal of Epidemiology & Community Health.

[15]  Joanne L. Jordan,et al.  Effective treatment options for musculoskeletal pain in primary care: A systematic overview of current evidence , 2017, PloS one.

[16]  M. Brucker Social Determinants of Health. , 2017, Nursing for women's health.

[17]  G. Rey,et al.  eAppendix for : “ Survival analysis with multiple causes of death : Extending the competing risks model ” , 2016 .

[18]  Liliya Leopold Cumulative Advantage in an Egalitarian Country? Socioeconomic Health Disparities over the Life Course in Sweden , 2016, Journal of health and social behavior.

[19]  M. Englund,et al.  Influences on the decision to use an osteoarthritis diagnosis in primary care: a cohort study with linked survey and electronic health record data , 2016, Osteoarthritis and cartilage.

[20]  Carol Doyle,et al.  Effect of Stratified Care for Low Back Pain in Family Practice (IMPaCT Back): A Prospective Population-Based Sequential Comparison , 2014, The Annals of Family Medicine.

[21]  Olalekan Uthman,et al.  Absence from work and return to work in people with back pain: a systematic review and meta-analysis , 2013, Occupational and Environmental Medicine.

[22]  R. Hoffmann Illness, not age, is the leveler of social mortality differences in old age. , 2011, The journals of gerontology. Series B, Psychological sciences and social sciences.

[23]  K. Ferraro,et al.  Aging and cumulative inequality: how does inequality get under the skin? , 2009, The Gerontologist.

[24]  Carel T J Hulshof,et al.  Working for a healthier tomorrow , 2008, Occupational and Environmental Medicine.

[25]  D. A. van der Windt,et al.  Content and outcome of usual primary care for back pain: a systematic review. , 2008, The British journal of general practice : the journal of the Royal College of General Practitioners.

[26]  Gordon Waddell,et al.  IS WORK GOOD FOR YOUR HEALTH , 2008 .

[27]  Ricky Mullis,et al.  A primary care back pain screening tool: identifying patient subgroups for initial treatment. , 2008, Arthritis and rheumatism.

[28]  C. Jinks,et al.  Primary care treatment of knee pain--a survey in older adults. , 2007, Rheumatology.

[29]  M. Ward Education level and mortality in systemic lupus erythematosus (SLE): evidence of underascertainment of deaths due to SLE in ethnic minorities with low education levels. , 2004, Arthritis and rheumatism.

[30]  T. Koepsell,et al.  Formal education and back pain: a review , 2001, Journal of epidemiology and community health.

[31]  A. Kposowa Unemployment and suicide: a cohort analysis of social factors predicting suicide in the US National Longitudinal Mortality Study , 2001, Psychological Medicine.

[32]  B. Floderus,et al.  Mortality among women and men relative to unemployment, part time work, overtime work, and extra work: a study based on data from the Swedish twin registry , 2001, Occupational and environmental medicine.

[33]  V. Mason The prevalence of back pain in Great Britain : a report on OPCS Omnibus Survey data , 1994 .

[34]  David R. Jones,et al.  UNEMPLOYMENT AND MORTALITY IN THE OPCS LONGITUDINAL STUDY , 1984, The Lancet.

[35]  T. Gross,et al.  For Personal Use. Only Reproduce with Permission from Elsevier Ltd Public Health Inequalities in Health between and within Countries: Poverty and Inequality Social Determinants of Health Inequalities , 2022 .