Worksite health screening programs for predicting the development of Metabolic Syndrome in middle-aged employees: a five-year follow-up study

Can biomarkers be used to improve diagnosis and prediction of metabolic syndrome in childhood cancer survivors? A systematic review

Childhood cancer survivors (CCS) are at increased risk to develop metabolic syndrome (MetS), diabetes, and cardiovascular disease. Common criteria underestimate adiposity and possibly underdiagnose MetS, particularly after abdominal radiotherapy. A systematic literature review and meta-analysis on the diagnostic and predictive value of nine newer MetS related biomarkers (adiponectin, leptin, uric acid, hsCRP, TNF-alpha, IL-1, IL-6, apolipoprotein B (apoB), and lipoprotein(a) [lp(a)]) in survivors and adult non-cancer survivors was performed by searching PubMed and Embase. Evidence was summarized with GRADE after risk of bias evaluation (QUADAS-2/QUIPS). Eligible studies on promising biomarkers were pooled. We identified 175 general population and five CCS studies. In the general population, valuable predictive biomarkers are uric acid, adiponectin, hsCRP and apoB (high level of evidence), and leptin (moderate level of evidence). Valuable diagnostic biomarkers are hsCRP, adiponectin, uric acid, and leptin (low, low, moderate, and high level of evidence, respectively). Meta-analysis showed OR for hyperuricemia of 2.94 (age-/sex-adjusted), OR per unit uric acid increase of 1.086 (unadjusted), and AUC for hsCRP of 0.71 (unadjusted). Uric acid, adiponectin, hsCRP, leptin, and apoB can be alternative biomarkers in the screening setting for MetS in survivors, to enhance early identification of those at high risk of subsequent complications.

The association of serum uric acid with metabolic syndrome and its components-From a single-clinical centre in China

BACKGROUND AND OBJECTIVES

Increasing evidence suggests that uric acid (UA) levels may play a role in the MetS. The purpose of this study was the association of serum uric acid with metabolic syndrome and its components from a single-clinical centre in China.

SUBJECTS AND METHODS

We retrospectively analysed the physical examination information of patients at the Health Checkup Centre of the Beijing Friendship Hospital, Capital Medical University in 2018. MetS was defined as ≥3 of the risk factors according to the revised Harmonised criteria. Statistical analyses were performed using the SPSS statistical software package, version 22.0 (IBM Corporation, Armonk, NY, USA).

RESULTS

A total of 36 663 subjects were retrospectively analysed. The incidence of MetS was 23.6% amongst the study participants and 38.9% in subjects with HUA. The incidence of HUA was 33.3% in the MetS group. Higher SUA levels were correlated with an increased risk of having full MetS, hypertriglyceridemia and low HDL-C after adjustment (all P < .001 for the trend). Only in males higher SUA levels correlated with an increased risk of being overweight. Individuals with the highest quartile of SUA had no significant association with having HP in males, and a significant association between SUA levels and hypertension was only seen in the highest quartile of females. Males with the highest quartile of SUA (Q4) and females with the higher quartiles of SUA (Q3 and Q4) had no significant association with having hyperglycemia.

CONCLUSION

The incidence of HUA was increased in the MetS group consisting of Chinese patient subjects living in Beijing. SUA is strongly associated with full MetS as well as hypertriglyceridemia and low HDL-C. The relationship between HUA and an overweight BMI, HP and hyperglycemia varied by gender.

Effect of shift work on the development of metabolic syndrome after 3 years in Japanese male workers

A 3-year follow-up study of an occupational cohort was conducted to clarify the effect of the type of shift work on the risk of development of metabolic syndrome (MetS). The subjects were 1,677 Japanese male employees aged 36 to 57. Age, each component of MetS, serum uric acid, serum insulin, lifestyle factors, and occupational position were used for the analyses. The odds ratios (95% confidence intervals) of 2-shift work (n = 686) and 3-shift work (n = 99) against daytime work (n = 868) for the development of MetS, as defined by the National Cholesterol Education Program, were 1.43 (1.05, 1.95) and 0.72 (0.37, 1.41), respectively. When Japanese criteria were adopted for defining MetS, the corresponding odds ratios (95% confidence intervals) were 1.88 (1.29, 2.74) and 0.87 (0.39, 1.97), respectively. The results of the analyses suggested that 2-shift work was a risk factor for the development of metabolic syndrome.

Identification of cardiovascular risk components in urban Chinese with metabolic syndrome and application to coronary heart disease prediction: a longitudinal study

Background

Metabolic syndrome (MetS) is proposed as a predictor for cardiovascular disease (CVD). It involves the mechanisms of insulin resistance, obesity, inflammation process of atherosclerosis, and their complex relationship in the metabolic network. Therefore, more cardiovascular risk-related biomarkers within this network should be considered as components of MetS in order to improve the prediction of CVD.

Methods

Factor analysis was performed in 5311 (4574 males and 737 females) Han Chinese subjects with MetS to extract CVD-related factors with specific clinical significance from 16 biomarkers tested in routine health check-up. Logistic regression model, based on an extreme case-control design with 445 coronary heart disease (CHD) patients and 890 controls, was performed to evaluate the extracted factors used to identify CHD. Then, Cox model, based on a cohort design with 1923 subjects followed up for 5 years, was conducted to validate their predictive effects. Finally, a synthetic predictor (SP) was created by weighting each factor with their risks for CHD to develop a risk matrix to predicting CHD.

Results

Eight factors were obtained from both males and females with a similar pattern. The AUC to classify CHD under the extreme case-control suggested that SP might serve as a useful tool in identifying CHD with 0.994 (95%CI 0.984-0.998) for males and 0.998 (95%CI 0.982-1.000) for females respectively. In the cohort study, the AUC to predict CHD was 0.871 (95%CI 0.851-0.889) for males and 0.899 (95%CI 0.873-0.921) for females, highlighting that SP was a powerful predictor for CHD. The SP-based 5-year CHD risk matrix provided as convenient tool for CHD risk appraisal.

Conclusions

Eight factors were extracted from sixteen biomarkers in subjects with MetS and the SP adds to new insights into studies of prediction of CHD risk using data from routine health check-up.

A longitudinal cohort based association study between uric acid level and metabolic syndrome in Chinese Han urban male population

BACKGROUND

It has been recently demonstrated that serum uric acid (UA) is associated with metabolic syndrome (MetS) or its related clinical indications based on cross-sectional or prospective cohort studies. Nonetheless, due to the fact that UA level constantly fluctuates from time to time even for the person, using a single measure of UA level at baseline of those studies may not be sufficient for estimating the UA-Mets association.

METHODS

To further estimate this time-dependent association, we fitted a generalized estimating equation (GEE) regression model with data from a large-scale 6-year longitudinal study, which included 2222 participants aged > =25 years with an average of 3.5 repeated measures of UA per person in the Health Management Center of Shandong Provincial Hospital, Shandong, China.

RESULTS

After adjusting for other potential confounding factors (i.e., total cholesterol, low-density lipoprotein), it was verified that time-dependent UA level was an independent risk factor for MetS (OR = 1.6920, p < 0.0001). It was found that UA level was positively associated with obesity, hypertension, and dyslipidemia, but was inversely associated with hyperglycemia.

CONCLUSIONS

Serum UA level may serve as an important risk factor of MetS. Additionally, our study suggested that UA level be an independent risk factor to obesity, hypertension and dyslipidemia, but a protective factor to hyperglycemia. These findings are concordant with results from other studies on Asian populations, and jointly provide a basis to further develop a risk assessment model for predicting MetS using UA levels and other factors in China.