Time course of neck-shoulder pain among workers: A longitudinal latent class growth analysis

Hallman, David; Rasmussen, Charlotte Diana Nørregaard; Jørgensen, Marie Birk; Holtermann, Andreas

doi:10.5271/sjweh.3690

Cited by 15 publications

(17 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Stock et al studied students from seven different countries and confirmed the results of this study that women are more likely to develop musculoskeletal disorders in the neck [43]. The results of this study were approved for both students and the general population in longitudinal studyies [44][45][46]. In line with the results of this study, Dianat et al highlighted the difference between male and female students in the report of neck pain [47].…”

Section: Discussionsupporting

confidence: 83%

Musculoskeletal consequences in cyber-addicted students - Is it really a matter of health? A ROC curve analysis for prioritizing risk factors

Moghadam

Babamiri

Ghasemi

et al. 2019

Preprint

View full text Add to dashboard Cite

Background The high prevalence and also multiple consequences of addiction to various online content, including online games and social networks, have become a major challenge. The ability to predict musculoskeletal disorders from this addiction can help reveal in students' health status in the near future. The aim of this study was to determine the prevalence of this addiction and the ability to predict neck pain from this matter in students. Methods This study was carried out among 665 students. Data collection was performed through three questionnaires on problematic use of online games, social networking addiction, and Nordic musculoskeletal disorders. Data were compared with Chi-square and independent T-test, and the logistic regression model was then presented at a significant level of 0.05. Finally, the area under the receiver operating characteristic (ROC) curve and Discriminant analysis with SPSS and STATA software were conducted to clarify associations. Results The prevalence of Internet-related content addiction was 32.8%. The results showed that addiction to social networks and online games can increase the risk of neck disorder. Also 0.58 area under ROC curve depicted the ability to predict neck pain from this addiction. Conclusions In students with internet - related content addiction, neck disorder can be predicted. Given the high prevalence of internet addiction in students, it is essential to take immediate and appropriate interventions to avoid the associated adverse effects such as neck problems.

show abstract

Section: Discussionsupporting

confidence: 83%

Musculoskeletal consequences in cyber-addicted students - Is it really a matter of health? A ROC curve analysis for prioritizing risk factors

Moghadam

Babamiri

Ghasemi

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Based on model fit indices (BIC, entropy and BLRT) and distinction between classes obtained from consecutive LCGA models, a six-class solution was chosen 30. The growth pattern and prevalence (%) of the six identified trajectory classes of NSP were characterised as follows (see also online supplementary figure A): class 1, asymptomatic (11%); class 2, very low NSP (10%); class 3, low recovering NSP (18%); class 4, moderate fluctuating NSP (28%); class 5, strong fluctuating NSP (24%) and class 6, severe persistent NSP (9%).…”

Section: Resultsmentioning

confidence: 99%

“…Theoretical assumptions and empirical evidence were used to select possible confounders and effect modifiers which were accounted for in the statistical analyses. The following variables were measured at baseline as previously described30: age (years) and gender (male or female) based on civil registration number, body mass index (BMI) based on objectively measured height and weight, occupational sector (manufacturing, cleaning, transportation and administration/office work within the same workplaces) and seniority in the current job (years). Physical work load was measured by the question ‘How physically demanding do you normally consider your present work?’ using a 10-point (1–10) response scale modified from Borg,40 with higher values indicating higher physical demands.…”

Section: Methodsmentioning

confidence: 99%

“…Growth trajectories (latent classes) of the intensity in NSP were identified using LCGA in Latent Gold V.5.1 (Statistical Innovations Belmont, MA, USA). The LCGA procedure and the resulting trajectory classes of NSP are described in a previous study on the same population 30. In brief, the LCGA assigns individuals to latent classes based on maximum posterior probabilities.…”

Section: Methodsmentioning

confidence: 99%

“…Latent class growth analysis (LCGA) is a common statistical approach for identifying homogeneous sub-populations (latent classes) based on individual growth parameters (ie, intercept, slope and residual variance) in repeated measures data 29. We have previously used LCGA to distinguish trajectory classes of NSP among the current population of workers based on frequent repeated measurements of NSP over 1 year 30. We identified six distinct trajectories of NSP ranging from ‘asymptomatic’ (prevalence 11%) to ‘severe persistent NSP’ (9%).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Are trajectories of neck–shoulder pain associated with sick leave and work ability in workers? A 1-year prospective study

et al. 2019

Self Cite

View full text Add to dashboard Cite

ObjectivesThe study aimed to determine the extent to which latent trajectories of neck–shoulder pain (NSP) are associated with self-reported sick leave and work ability based on frequent repeated measures over 1 year in an occupational population.MethodsThis longitudinal study included 748 Danish workers (blue-collar, n=620; white collar, n=128). A questionnaire was administered to collect data on personal and occupational factors at baseline. Text messages were used for repeated measurements of NSP intensity (scale 0–10) over 1 year (14 waves in total). Simultaneously, self-reported sick leave (days/month) due to pain was assessed at 4-week intervals, while work ability (scale 0–10) was assessed using a single item (work ability index) at 12-week intervals over the year. Trajectories of NSP, distinguished by latent class growth analysis, were used as predictors of sick leave and work ability in generalised estimation equations with multiple adjustments.ResultsSick leave increased and work ability decreased across all NSP trajectory classes (low, moderate, strong fluctuating and severe persistent pain intensity). In the adjusted model, the estimated number of days on sick leave was 1.5 days/month for severe persistent NSP compared with 0.1 days/month for low NSP (relative risk=13.8, 95% CI 6.7 to 28.5). Similarly, work ability decreased markedly for severe persistent NSP (OR=12.9, 95% CI 8.5 to 19.7; median 7.1) compared with low NSP (median 9.5).ConclusionSevere persistent NSP was associated with sick leave and poor work ability over 1 year among workers. Preventive strategies aiming at reducing severe persistent NSP among working populations are needed.

show abstract

Sick leave due to musculoskeletal pain: determinants of distinct trajectories over 1 year

Hallman

Holtermann

Björklund

et al. 2019

Int Arch Occup Environ Health

Self Cite

View full text Add to dashboard Cite

PurposeThis study aimed to identify sub-groups of workers with different trajectories of sick leave due to musculoskeletal pain over 1 year, and to investigate the extent to which the identified trajectories are associated with personal, occupational, lifestyle, and pain-related factors at baseline.MethodsData on 981 blue- and white-collar workers were analyzed in the DPHACTO cohort (2012–2014). The number of days on sick leave due to pain was reported using text messages at 4-week intervals across 1 year. Latent class growth analysis was used to distinguish sub-groups with different trajectories of sick leave. A web-based questionnaire at baseline was used to assess personal, occupational (physical and psychosocial), lifestyle, and pain-related factors. Multinomial regression models were constructed to determine associations between baseline factors and trajectories of sick leave (referencing no sick leave), with adjustment for potential confounders.ResultsFour distinct sub-groups were identified, with trajectories of sick leave due to pain ranging from no sick leave (prevalence 76%; average 0.5 days/year) to some days and increasing sick leave due to pain over 1 year (2%; 89 days/year). The increasing trajectory of sick leave was associated with higher perceived physical exertion, more time in manual work, less social community and influence at work, less leisure-time physical activity, smoking, and more severe symptoms (e.g., multisite pain, low back pain intensity, and pain interference).ConclusionsWe identified four distinct trajectories of sick leave due to musculoskeletal pain. The sub-group with increasing sick leave due to pain was associated with several modifiable physical and psychosocial factors at work and outside work, which may have implications for prevention.Electronic supplementary materialThe online version of this article (10.1007/s00420-019-01447-y) contains supplementary material, which is available to authorized users.

show abstract

Time course of neck-shoulder pain among workers: A longitudinal latent class growth analysis

Cited by 15 publications

References 30 publications

Musculoskeletal consequences in cyber-addicted students - Is it really a matter of health? A ROC curve analysis for prioritizing risk factors

Musculoskeletal consequences in cyber-addicted students - Is it really a matter of health? A ROC curve analysis for prioritizing risk factors

Are trajectories of neck–shoulder pain associated with sick leave and work ability in workers? A 1-year prospective study

Sick leave due to musculoskeletal pain: determinants of distinct trajectories over 1 year

Contact Info

Product

Resources

About