Prognostic Factors and Models for Predicting Work Absence in Adults with Musculoskeletal Conditions Consulting a Healthcare Practitioner: A Systematic Review.

PURPOSE: It is difficult to predict which employees, in particular those with musculoskeletal pain, will return to work quickly without additional vocational advice and support, which employees will require this support and what levels of support are most appropriate. Consequently, there is no way of ensuring the right individuals are directed towards the right services to support their occupational health needs. The aim of this review will be to identify prognostic factors for duration of work absence in those already absent and examine the utility of prognostic models for work absence. METHODS: Eight databases were search using a combination of subject headings and key words focusing on work absence, musculoskeletal pain and prognosis. Two authors independently assessed the eligibility of studies, extracted data from all eligible studies and assessed risk of bias using the QUIPS or PROBAST tools, an adapted GRADE was used to assess the strength of the evidence. To make sense of the data prognostic variables were grouped according to categories from the Disability Prevention Framework and the SWiM framework was utilised to synthesise findings. RESULTS: A total of 23 studies were included in the review, including 13 prognostic models and a total of 110 individual prognostic factors. Overall, the evidence for all prognostic factors was weak, although there was some evidence that older age and better recovery expectations were protective of future absence and that previous absence was likely to predict future absences. There was weak evidence for any of the prognostic models in determining future sickness absence. CONCLUSION: Analysis was difficult due to the wide range of measures of both prognostic factors and outcome and the differing timescales for follow-up. Future research should ensure that consistent measures are employed and where possible these should be in-line with those suggested by Ravinskaya et al. (2023).

Chronic pain-mental health comorbidity and excess prevalence of health risk behaviours: a cross-sectional study.

BACKGROUND: Chronic musculoskeletal pain and anxiety/depression are significant public health problems. We hypothesised that adults with both conditions constitute a group at especially high risk of future cardiovascular health outcomes. AIM: To determine whether having comorbid chronic musculoskeletal pain and anxiety/depression is associated with the excess prevalence of selected known cardiovascular health risk behaviours. METHOD: A cross-sectional survey of adults aged 35+ years randomly sampled from 26 GP practice registers in West Midlands, England. Respondents were classified into four groups based on self-reported presence/absence of chronic musculoskeletal pain (pain present on most days for six months) and anxiety or depression (Hospital Anxiety and Depression Score 11+). Standardised binomial models were used to estimate standardised prevalence ratios and prevalence differences between the four groups in self-reported obesity, tobacco smoking, physical inactivity, and unhealthy alcohol consumption after controlling for age, sex, ethnicity, deprivation, employment status and educational attainment. The excess prevalence of each risk factor in the group with chronic musculoskeletal pain-anxiety/depression comorbidity was estimated. FINDINGS: Totally, 14 519 respondents were included, of whom 1329 (9%) reported comorbid chronic musculoskeletal pain-anxiety/depression, 3612 (25%) chronic musculoskeletal pain only, 964 (7%) anxiety or depression only, and 8614 (59%) neither. Those with comorbid chronic musculoskeletal pain-anxiety/depression had the highest crude prevalence of obesity (41%), smoking (16%) and physical inactivity (83%) but the lowest for unhealthy alcohol consumption (18%). After controlling for covariates, the standardised prevalence ratios and differences for the comorbid group compared with those with neither chronic musculoskeletal pain nor anxiety/depression were as follows: current smoking [1.86 (95% CI 1.58, 2.18); 6.8%], obesity [1.93 (1.76, 2.10); 18.9%], physical inactivity [1.21 (1.17, 1.24); 14.3%] and unhealthy alcohol consumption [0.81 (0.71, 0.92); -5.0%]. The standardised prevalences of smoking and obesity in the comorbid group exceeded those expected from simple additive interaction.

Demographic, health, physical activity, and workplace factors are associated with lower healthy working life expectancy and life expectancy at age 50.

Although retirement ages are rising in the United Kingdom and other countries, the average number of years people in England can expect to spend both healthy and work from age 50 (Healthy Working Life Expectancy; HWLE) is less than the number of years to the State Pension age. This study aimed to estimate HWLE with the presence and absence of selected health, socio-demographic, physical activity, and workplace factors relevant to stakeholders focusing on improving work participation. Data from 11,540 adults in the English Longitudinal Study of Ageing were analysed using a continuous time 3-state multi-state model. Age-adjusted hazard rate ratios (aHRR) were estimated for transitions between health and work states associated with individual and combinations of health, socio-demographic, and workplace factors. HWLE from age 50 was 3.3 years fewer on average for people with pain interference (6.54 years with 95% confidence interval [6.07, 7.01]) compared to those without (9.79 [9.50, 10.08]). Osteoarthritis and mental health problems were associated with 2.2 and 2.9 fewer healthy working years respectively (HWLE for people without osteoarthritis: 9.50 years [9.22, 9.79]; HWLE with osteoarthritis: 7.29 years [6.20, 8.39]; HWLE without mental health problems: 9.76 years [9.48, 10.05]; HWLE with mental health problems: 6.87 years [1.58, 12.15]). Obesity and physical inactivity were associated with 0.9 and 2.0 fewer healthy working years respectively (HWLE without obesity: 9.31 years [9.01, 9.62]; HWLE with obesity: 8.44 years [8.02, 8.86]; HWLE without physical inactivity: 9.62 years [9.32, 9.91]; HWLE with physical inactivity: 7.67 years [7.23, 8.12]). Workers without autonomy at work or with inadequate support at work were expected to lose 1.8 and 1.7 years respectively in work with good health from age 50 (HWLE for workers with autonomy: 9.50 years [9.20, 9.79]; HWLE for workers lacking autonomy: 7.67 years [7.22, 8.12]; HWLE for workers with support: 9.52 years [9.22, 9.82]; HWLE for workers with inadequate support: 7.86 years [7.22, 8.12]). This study identified demographic, health, physical activity, and workplace factors associated with lower HWLE and life expectancy at age 50. Identifying the extent of the impact on healthy working life highlights these factors as targets and the potential to mitigate against premature work exit is encouraging to policy-makers seeking to extend working life as well as people with musculoskeletal and mental health conditions and their employers. The HWLE gaps suggest that interventions are needed to promote the health, wellbeing and work outcomes of subpopulations with long-term health conditions.

The clinical characteristics, managements, and outcomes of acute myocardial infarction in osteoarthritis patients; a cross-sectional analysis of 6.5 million patients.

OBJECTIVES: The prevalence of osteoarthritis (OA) and cardiovascular disease are increasing and both conditions share similar risk factors. We investigated the association between OA and receipt of invasive managements and clinical outcomes in patients with acute myocardial infarction (AMI). METHODS: Using the National Inpatient Sample, adjusted binary logistic regression determined the association between OA and each outcome variable. RESULTS: Of 6,561,940 AMI hospitalizations, 6.3% had OA. OA patients were older and more likely to be female. OA was associated with a decreased odds of coronary angiography (adjusted odds ratio 0.91; 95% confidence interval 0.90, 0.92), PCI (0.87; 0.87, 0.88), and coronary artery bypass grafting (0.98; 0.97, 1.00). OA was associated with a decreased odds of adverse outcomes (in-hospital mortality: 0.68; 0.67, 0.69; major acute cardiovascular and cerebrovascular events: 0.71; 0.70, 0.72; all-cause bleeding: 0.76; 0.74, 0.77; and stroke/TIA: 0.84; 0.82, 0.87). CONCLUSIONS: This study of a representative sample of the US population highlights that OA patients are less likely to be offered invasive interventions following AMI. OA was also associated with better outcomes post-AMI, possibly attributed to a misclassification bias where unwell patients with OA were less likely to receive an OA code because codes for serious illness took precedence.