Human Studies

Epidemiological literature on the relationship between physical activity and chronic pain is scarce and inconsistent. Hence, our aim was to assess the relationship applying comprehensive methodology, including self-reported and accelerometer measures of physical activity and different severity levels of chronic pain. We used data from the Tromsø Study (2015-2016). All residents in the municipality, aged 40 years and older were invited to participate (n=32,591, 51% women). A total of 21,083 (53% women) reported on questionnaires. Additionally, 6,778 participants (54% women) were invited to wear accelerometers (6,125 with complete measurements). Our exposure measures were self-reported leisure time physical activity, exercise frequency, duration and intensity and two accelerometer-measures (steps per day and minutes of moderate to vigorous physical activity per day). Outcome measurements were chronic pain and moderate-to-severe chronic pain. We used Poisson regression to estimate chronic pain prevalence and prevalence ratios for each physical activity measure, with adjustments for sex, age, education level, smoking history, and occupational physical activity. Our main analyses showed an inverse dose-response relationships between all physical activity measures and both severity measures of chronic pain, except that the dose-response relationship with exercise duration was only found for moderate-to-severe pain. All findings were stronger for the moderate-to-severe pain outcomes than for chronic pain. Robustness analyses gave similar results as the main analyses. We conclude that an inverse dose-response association between physical activity and chronic pain is consistent across measures. To summarize, higher levels of physical activity is associated with less chronic pain and moderate-to-severe chronic pain.

Quantitative sensory testing (QST) assesses the functional integrity of small and large nerve fibre afferents and central somatosensory pathways; QST was assumed to provide insight into the mechanisms of neuropathy. We analysed QST profiles and phenotypes in diabetes mellitus patients to study whether these could differentiate patients with and without pain and neuropathy.

It is well recognized that underrepresented and minoritized groups do not have the same career opportunities. However, there are limited data on the range and specifics of potential barriers that withhold people in headache medicine and science from reaching their full potential. Moreover, people from different geographical regions often perceive different challenges. We aimed to identify world-wide perceived career barriers and possibilities for promoting equality amongst professionals in the headache fields.

To verify the use of pain drawing to assess multisite pain in with primary dysmenorrhea (PD) and to assess its divergent validity, test-retest reliability, intra- and inter-rater reliability and measurement errors.

Chronic back pain (CBP) is heterogenous and identifying sub-groups could improve clinical decision making. Machine learning can build upon prior sub-grouping approaches by using a data-driven approach to overcome clinician subjectivity, however, only binary classification of pain versus no-pain has been attempted to date. In our cross-sectional study, age- and sex-matched participants with CBP (n = 4156) and pain-free controls (n = 14,927) from the UkBioBank were included. We included variables of body mass index, depression, loneliness/social isolation, grip strength, brain grey matter volumes and functional connectivity. We used fuzzy c-means clustering to derive CBP sub-groups and Support Vector Machine (SVM), Naïve Bayes, k-Nearest Neighbour (kNN) and Random Forest classifiers to determine classification accuracy. We showed that two variables (loneliness/social isolation and depression) and five clusters were optimal for creating sub-groups of CBP individuals. Classification accuracy was greater than 95% for when CBP sub-groups were assessed only, while misclassification in CBP sub-groups increased to 35-53% across classifiers when pain-free controls were added. We showed that individuals with CBP could sub-grouped and accurately classified. Future research should optimise variables by including specific spinal, psychosocial and nervous system measures associated with CBP to create more robust sub-groups that are discernible from pain-free controls.

The development of reproducible and sensitive outcome measures has been challenging in hereditary transthyretin (ATTRv) amyloidosis. Recently, quantification of intramuscular fat by magnetic resonance imaging (MRI) has proven as a sensitive marker in patients with other genetic neuropathies. The aim of this study was to investigate the role of muscle quantitative MRI (qMRI) as an outcome measure in ATTRv.