Background Cost-of-living crises are damaging to population mental health and require a public health response. It is important to assess whether public health interventions are effective. We aimed to identify population-level methods and measures and the appropriateness of the measures for vulnerable populations. Methods A rapid evidence review was undertaken. Nineteen databases, including grey literature, were searched for evidence published between 1970 and April 2023. Results Seven reviews, nine primary studies and two reports from grey literature were identified. Methods consisted of analyses of existing data from national or regional cohort studies, household panel surveys, repeated cross-sectional surveys, routine medical data, or data on suicide death rates. Twelve brief validated mental health measurement tools, embedded in population-level surveys, were identified. Two quasi-experimental studies used data from a UK household panel survey to examine the impact of the introduction of specific welfare policies on mental health. Studies identified socio-economic vulnerabilities, but it was not possible to determine whether data were effectively captured from people from minority ethnic groups. Conclusion Population-level surveys can be used in quasi-experimental studies to measure the effects of a public health initiative with specific roll out dates to tackle cost-of-living impacts. It is unclear as to whether the identified methods and tools are suitable for use with people from minority ethnic groups.

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: Multiple studies and meta-analyses have reported the diagnostic value of C-reactive protein (CRP) in several diseases. However, the precision, and influence of potential bias regarding the diagnostic values of existing evidence may have implications for clinical practice. Methods: We performed an umbrella review of diagnostic test accuracy studies of CRP for diseases by searching PubMed, Embase, China National Knowledge Infrastructure, and WanFang databases up to March 7, 2021. Five independent reviewers evaluated eligibility, extracted data, and assessed methodological quality. We descriptively analyzed the diagnostic accuracy of CRP for multiple diseases, heterogeneity between studies, and publication bias. Results: Seventy-four meta-analyses were included, with 13 diseases classified according to the International Classification of Diseases-11 (ICD-11). The methodological quality of the included meta-analyses was mostly low, with only 16 meta-analyses rated as moderate or high, including seven diseases classified by ICD-11. CRP had a relatively greater diagnostic accuracy for two of these diseases. For postoperative infectious complications after bariatric surgery, sensitivity and specificity were 0.81 (0.34-1) and 0.91 (0.73-1), respectively. For anastomotic leakage after colorectal surgery, sensitivity and specificity were 0.95 (0.75-0.99) and 0.95 (0.75-0.99), respectively. Conclusions: The diagnostic accuracy of CRP for multiple diseases has been extensively studied; however, most studies have low methodological quality. Evidence indicates that CRP has a relatively greater diagnostic accuracy for inflammation and infection diseases, especially for postoperative infectious complications after bariatric surgery and anastomotic leakage after colorectal surgery.