Association of trajectory of body mass index with knee pain risk in Japanese middle-aged women in a prospective cohort study: the Japan Nurses' Health Study

Phenotypes of osteoarthritis-related knee pain and their transition over time: data from the osteoarthritis initiative

BACKGROUND

Identification of knee osteoarthritis (OA) pain phenotypes, their transition patterns, and risk factors for worse phenotypes, may guide prognosis and targeted treatment; however, few studies have described them. We aimed to investigate different pain phenotypes, their transition patterns, and potential risk factors for worse pain phenotypes.

METHODS

Utilizing data from the Osteoarthritis Initiative (OAI), pain severity was assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale. We identified the activity-related pain phenotypes and estimated the transition probabilities of pain phenotypes from baseline to the 24-month using latent transition analysis. We examined the risk factors at baseline with the 24-month pain phenotypes and the transition of pain phenotypes.

RESULTS

In 4796 participants, we identified four distinct knee pain phenotypes at both baseline and 24-month follow-up: no pain, mild pain during activity (Mild P-A), mild pain during both rest and activity (Mild P-R-A), and moderate pain during both rest and activity (Mod P-R-A). 82.9% knees with no pain at baseline stayed the same at 24-month follow-up, 17.1% progressed to worse pain phenotypes. Among "Mild P-A" at baseline, 32.0% converted to no-pain, 12.8% progressed to "Mild P-R-A", and 53.2% remained. Approximately 46.1% of "Mild P-R-A" and 54.5% of "Mod P-R-A" at baseline experienced remission by 24-month. Female, non-whites, participants with higher depression score, higher body mass index (BMI), higher Kellgren and Lawrence (KL) grade, and knee injury history were more likely to be in the worse pain phenotypes, while participants aged 65 years or older and with higher education were less likely to be in worse pain phenotypes at 24-month follow-up visit. Risk factors for greater transition probability to worse pain phenotypes at 24-month included being female, non-whites, participants with higher depression score, higher BMI, and higher KL grade.

CONCLUSIONS

We identified four distinct knee pain phenotypes. While the pain phenotypes remained stable in the majority of knees over 24 months period, substantial proportion of knees switched to different pain phenotypes. Several socio-demographics as well as radiographic lesions at baseline are associated with worse pain phenotypes at 24-month follow-up visit and transition of pain phenotypes.

Evidence on risk factors for knee osteoarthritis in middle-older aged: a systematic review and meta analysis

PURPOSE

This review was made to identify the risk factors for knee osteoarthritis (KOA) in middle-older aged (≥ 40 years), and to provide the newest evidence for the prevention of KOA.

METHOD

Cohort study and case-control study of the risk factors of KOA was included from Pubmed, Web of Science, Ovid Technologies, China National Knowledge Infrastructure (CNKI), Chinese Science and Technology Periodical Database (VIP), Wanfang Database, SinoMed from their inceptions to July 2023. Two authors independently screened the literature and extracted data. Assessment of quality was implemented according to Agency for Healthcare Research and Quality (AHRQ) and Newcastle-Ottawa Quality Assessment Scale. Meta-analysis was performed using RevMan 5.3 software.

RESULTS

3597 papers were identified from the seven databases and 29 papers containing 60,354 participants were included in this review. Meta-analysis was performed for 14 risk factors, and 7 of these were statistical significance (P < 0.05). The risk factors which were analyzed in this review included trauma history in knee (1.37 [95% CI 1.03-1.82], P = 0.030), body mass index (BMI) ≥ 24 kg/m2 (1.30 [95% CI 1.09-1.56], P = 0.004), gender (female) (1.04 [95% CI 1.00-1.09], P = 0.030), age ≥ 40 (1.02 [95% CI 1.01-1.03], P = 0.007), more exercise (0.75 [95% CI 0.62-0.91], P = 0.003), a high school education background (0.49 [95% CI 0.30-0.79], P = 0.003) and an university education background (0.22 [95% CI 0.06-0.86], P = 0.030).

CONCLUSION

The risk factors analyzed in this review included trauma history in knee, overweight or obesity, gender (female), age ≥ 40 and the protective factors included more exercise and a high school or an university education background.

Specific body mass index trajectories were related to musculoskeletal pain and mortality: 19-year follow-up cohort

OBJECTIVE

We aimed to study 19-year body mass index (BMI) patterns and their (1) bidirectional relationship with musculoskeletal pain and (2) mortality risk.

STUDY DESIGN AND SETTING

We used data from the Chingford study and group-based trajectory modelling to define 19-year BMI patterns. We investigated whether baseline back, hand, hip, and knee pain (as single- and multi-site) predicted 19-year BMI trajectory, and whether 19-year BMI patterns predicted pain in year 20. We explored BMI trajectories and mortality risk over 25 years (life expectancy).

RESULTS

We included 938 women (mean age: year-1=54, year-20=72) and found seven distinct 19-year BMI trajectories: two normal-weighted (reference), slightly overweight, lower and upper overweight-to-obese, lower and upper obese. BMI patterns capturing the increase overweight-to-obese (BMI 27-34 overtime) were bidirectionally related to knee and multi-site pain. The lower obese pattern (BMI 33-38) was unidirectionally associated with lower limb pain. Women with BMI above 40 had an increased all-cause and cardiovascular mortality risk.

CONCLUSION

For most postmenopausal women, the overweight WHO category was a transition. Two patterns capturing increase overweight-to-obese were mutually related to musculoskeletal pain, i.e., knee and multi-site pain contributed to becoming obese, and trajectories of becoming obese increased the odds of experiencing pain later.

Group‐based trajectory modeling of body mass index and body size over the life course: A scoping review

Background

Group‐based trajectory modeling has been applied to identify distinct trajectories of growth across the life course. Objectives of this study were to describe the methodological approaches for group‐based modeling of growth across the life course and to summarize outcomes across studies.

Methods

A scoping review with a systematic search of Medline, EMBASE, CINAL, and Web of Science was conducted. Studies that used a group‐based procedure to identify trajectories on any statistical software were included. Data were extracted on trajectory methodology, measures of growth, and association with outcomes.

Results

A total of 59 studies were included, and most were published from 2013 to 2020. Body mass index was the most common measure of growth (n = 43). The median number of identified trajectories was 4 (range: 2–9). PROC TRAJ in SAS was used by 33 studies, other procedures used include TRAJ in STATA, lcmm in R, and Mplus. Most studies evaluated associations between growth trajectories and chronic disease outcomes (n = 22).

Conclusions

Group‐based trajectory modeling of growth in adults is emerging in epidemiologic research, with four distinct trajectories observed somewhat consistently from all studies. Understanding life course growth trajectories may provide further insight for population health interventions.