ObjectiveThe association between Metabolic Syndrome (MetS), its components, and the risk of osteoarthritis (OA) has been a topic of conflicting evidence in different studies. The aim of this present study is to investigate the association between MetS, its components, and the risk of OA using data from the UK Biobank.MethodsA prospective cohort study was conducted in the UK Biobank to assess the risk of osteoarthritis (OA) related to MetS. MetS was defined according to the criteria set by the International Diabetes Federation (IDF). Additionally, lifestyle factors, medications, and the inflammatory marker C-reactive protein (CRP) were included in the model. Cox proportional hazards regression was used to calculate hazard ratios (HR) and 95% confidence intervals (CI). The cumulative risk of OA was analyzed using Kaplan-Meier curves and log-rank tests. To explore potential nonlinear associations between MetS components and OA risk, a restricted cubic splines (RCS) model was employed. In addition, the polygenic risk score (PRS) of OA was calculated to characterize individual genetic risk.ResultsA total of 45,581 cases of OA were identified among 370,311 participants, with a median follow-up time of 12.48 years. The study found that individuals with MetS had a 15% higher risk of developing OA (HR = 1.15, 95%CI:1.12-1.19). Additionally, central obesity was associated with a 58% increased risk of OA (HR = 1.58, 95%CI:1.5-1.66), while hyperglycemia was linked to a 13% higher risk (HR = 1.13, 95%CI:1.1-1.15). Dyslipidemia, specifically in triglycerides (HR = 1.07, 95%CI:1.05-1.09) and high-density lipoprotein (HR = 1.05, 95%CI:1.02-1.07), was also found to be slightly associated with OA risk. When stratified by PRS, those in the high PRS group had a significantly higher risk of OA compared to those with a low PRS, whereas no interaction was found between MetS and PRS on OA risks. Furthermore, the presence of MetS significantly increased the risk of OA by up to 35% in individuals with elevated CRP levels (HR = 1.35, 95% CI:1.3-1.4).ConclusionMetS and its components have been found to be associated with an increased risk of OA, particularly in individuals with elevated levels of CRP. These findings highlight the significance of managing MetS as a preventive and intervention measure for OA.

Background: Metabolic syndrome has been linked to an increased risk of colorectal cancer (CRC) incidence and mortality, but whether adopting a healthy lifestyle could attenuate the risk of CRC conferred by metabolic syndrome remains unclear. The aim of the study is to investigate the individual and joint effects of modifiable healthy lifestyle and metabolic health status on CRC incidence and mortality in the UK population. Methods: This prospective study included 328,236 individuals from the UK Biobank. An overall metabolic health status was assessed at baseline and categorized based on the presence or absence of metabolic syndrome. We estimated the association of the healthy lifestyle score (derived from 4 modifiable behaviors: smoking, alcohol consumption, diet, physical activity and categorized into "favorable," "intermediate", and "unfavorable") with CRC incidence and mortality, stratified by metabolic health status. Results: During a median follow-up of 12.5 years, 3,852 CRC incidences and 1,076 deaths from CRC were newly identified. The risk of incident CRC and its mortality increased with the number of abnormal metabolic factors and decreased with healthy lifestyle score (P trend = 0.000). MetS was associated with greater CRC incidence (HR = 1.24, 95% CI: 1.16 - 1.33) and mortality (HR = 1.24, 95% CI: 1.08 - 1.41) when compared with those without MetS. An unfavorable lifestyle was associated with an increased risk (HR = 1.25, 95% CI: 1.15 - 1.36) and mortality (HR = 1.36, 95% CI: 1.16 - 1.59) of CRC across all metabolic health status. Participants adopting an unfavorable lifestyle with MetS had a higher risk (HR = 1.56, 95% CI: 1.38 - 1.76) and mortality (HR = 1.75, 95% CI: 1.40 - 2.20) than those adopting a favorable healthy lifestyle without MetS. Conclusion: This study indicated that adherence to a healthy lifestyle could substantially reduce the burden of CRC regardless of the metabolic status. Behavioral lifestyle changes should be encouraged for CRC prevention even in participants with MetS.

RATIONALE: Several studies have reported that both short and long sleep durations are associated with the metabolic syndrome (MetS), but whether a dose-response relationship exists is unclear. OBJECTIVE: We performed a meta-analysis to study the magnitude of the association between the different durations of sleep and MetS. METHODS: We searched in the databases of PubMed, Web of Science and Ovid (All Journals@Ovid) from inception to October 4th, 2014 for cross-sectional studies where an association between MetS and sleep duration was analyzed. MEASUREMENTS AND MAIN RESULTS: 18 studies with 75,657 participants were included. Daily sleep duration of 7 to 8 hours was used as the reference group. The odds ratio (OR) of having MetS for short (<7 hours) sleep was 1.23 ([95% CI: 1.11 to 1.37], p < 0.001, I2 71%). The ORs for <5 hours, 5 to 6 hours, and 6 to 7 hours of sleep were: 1.51 ([95% CIs: 1.10 to 2.08], p = 0.01); 1.28 ([95% CIs: 1.11 to 1.48], p < 0.001); and 1.16 ([95% CI: 1.02 to 1.31], p = 0.02), respectively. The coefficient of sleep duration on log of ORs was -0.06 + 0.02 (p = 0.02). The OR for long sleep duration was 1.13 ([95% CI: 0.97 to 1.32], p = 0.10, I2 89%). CONCLUSIONS: A dose-response relationship exists between short sleep duration and MetS. Those who report a sleep duration of <5 hours have a 1.5 higher odds of having MetS. Our study does not support the notion that long sleep is associated with MetS

BACKGROUND: All 5 components of metabolic syndrome have been shown to improve with lifestyle and diet modification. New strategies for achieving adherence to meaningful lifestyle change are needed to optimize atherosclerotic cardiovascular risk reduction. We performed a systematic literature review, based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework (PRISMA), investigating optimal methods for achieving lifestyle change in metabolic syndrome. METHODS: We submitted standardized search terms to the PubMed Central, CINAHL, Web of Science, and Ovid databases. Within those results, we selected randomized controlled trials (RCTs) presenting unique methods of achieving lifestyle change in patients with one or more components of the metabolic syndrome. Data extraction using the population, intervention, comparator, outcome, and risk of bias framework (PICO) was used to compare the following endpoints: prevalence of metabolic syndrome, prevalence of individual metabolic syndrome components, mean number of metabolic syndrome components, and amount of weight loss achieved. RESULTS: Twenty-eight RCTs (6372 patients) were included. Eight RCTs demonstrated improvement in metabolic syndrome risk factors after 1 year. Team-based, interactive approaches with high-frequency contact with patients who are motivated made the largest and most lasting impact. Technology was found to be a useful tool in achieving lifestyle change, but ineffective when compared with personal contact. CONCLUSION: Patient motivation leading to improved lifestyle adherence is a key factor in achieving reduction in metabolic syndrome components. These elements can be enhanced via frequent encounters with the health care system. Use of technologies such as mobile and Internet-based communication can increase the effectiveness of lifestyle change in metabolic syndrome, but should not replace personal contact as the cornerstone of therapy. Our ability to derive quantitative conclusions is limited by inconsistent outcome measures across studies, low power and homogeneity of individual studies, largely motivated study populations, short follow-up periods, loss to follow-up, and lack of or incomplete blinding