Association of Lumbar MRI Findings with Current and Future Back Pain in a Population-Based Cohort Study

ObjectivesThe aim was to investigate differences in the prescription of antidepressants during the transition to disability pension (DP) comparing DP due to back pain with DP due to other musculoskeletal and DP due to other somatic diagnoses.DesignA population-based cohort study with follow-up 3 years before and after the event. Estimated prevalence and adjusted ORs with 95% CIs for antidepressant prescription were computed for the 7-year window (ie, t-3 to t+3) around the DP by generalised estimating equations for repeated measures.Setting and participantsThis Swedish population-based nationwide study with registry data included individuals aged 18–64 years, with DP due to back pain (n=2011), DP due to other musculoskeletal (n=3548) or DP due to other somatic diagnoses (n=11 809).Primary outcome measuresPrescription of antidepressants.ResultsBefore DP, the prevalence of prescription of antidepressants was stable in DP due to back pain, but increased for the other DP groups. Similarly, the likelihood of prescription increased only marginally before DP due to back pain (ORs from 0.86 at t-3 to 1.10 at t-1), but clearly in DP due to musculoskeletal (from 0.42 to 1.15) and somatic diagnoses (from 0.29 to 0.98). Both prevalence measures and risks remained at the elevated levels after DP.ConclusionsPathways to DP due to musculoskeletal and somatic diagnoses seem to be partly driven by adverse mental health, which remains at a higher level after DP. The increasing prescription of antidepressants prior to DP suggests that special attention should be paid to mental health for prevention of DP. The period after DP needs attention to avoid deterioration of mental health.

Download Full-text

Increased risk of strokes in patients with chronic low back pain (CLBP): A nationwide population-based cohort study

Clinical Neurology and Neurosurgery ◽

10.1016/j.clineuro.2020.105725 ◽

2020 ◽

Vol 192 ◽

pp. 105725

Author(s):

Hao-Chin Wang ◽

Yuan-Chih Su ◽

Hsiang-Ning Luk ◽

Jen-Hung Wang ◽

Chung-Y Hsu ◽

...

Keyword(s):

Cohort Study ◽

Low Back Pain ◽

Back Pain ◽

Chronic Low Back Pain ◽

Population Based ◽

Low Back ◽

Increased Risk

Download Full-text

Examining the effects of low back pain and mental health symptoms on healthcare utilisation and costs: a protocol for a population-based cohort study

BMJ Open ◽

10.1136/bmjopen-2019-031749 ◽

2019 ◽

Vol 9 (9) ◽

pp. e031749 ◽

Cited By ~ 1

Author(s):

Jessica J Wong ◽

Pierre Côté ◽

Andrea C Tricco ◽

Laura C Rosella

Keyword(s):

Mental Health ◽

Cohort Study ◽

Low Back Pain ◽

Back Pain ◽

Healthcare Utilisation ◽

Population Based ◽

Community Dwelling ◽

Low Back ◽

Mental Health Symptoms ◽

Health Symptoms

IntroductionLow back pain (LBP) is a leading cause of disability associated with high healthcare utilisation and costs. Mental health symptoms are negative prognostic factors for LBP recovery; however, no population-based studies have assessed the joint effects of LBP and mental health symptoms on healthcare utilisation. This proposed study will characterise the health system burden of LBP and help identify priority groups to inform resource allocation and public health strategies. Among community-dwelling adult respondents of five cycles of the Canadian Community Health Survey (CCHS) in Ontario, we aim to assess the effect of self-reported LBP on healthcare utilisation and costs and assess whether this effect differs between those with and without self-reported mental health symptoms.Methods and analysisWe designed a dynamic population-based cohort study using linkages of survey and administrative data housed at ICES. The Ontario sample of CCHS (2003–2004, 2005–2006, 2007/2008, 2009/2010, 2011/2012; total of ~1 30 000 eligible respondents) will be used to define the cohort of adults with self-reported LBP with and without mental health symptoms. Healthcare utilisation and costs will be assessed by linking health administrative databases. Follow-up ranges from 6 to 15 years (until 31 March 2018). Sociodemographic (eg, age, sex, education) and health behaviour (eg, comorbidities, physical activity) factors will be considered as potential confounders. Poisson and linear (log-transformed) regression models will be used to assess the association between LBP and healthcare utilisation and costs. We will assess effect modification with mental health symptoms on the additive and multiplicative scales and conduct sensitivity analyses to assess the impact of misclassification and residual confounding.Ethics and disseminationThis study is approved by the University of Toronto Research Ethics Board. We will disseminate findings using a multifaceted knowledge translation strategy, including scientific conference presentations, publications in peer-reviewed journals and workshops with key knowledge users.

Download Full-text