Association of smoking status, insulin resistance, body mass index, and metabolic syndrome in workers: A 1-year follow-up study

Prevalence and Incidence of Metabolic Syndrome and Its Components Among Waterpipe Users

Objectives

To determine the associations between waterpipe use, duration, and intensity of use with prevalence and incidence of metabolic syndrome and its components (increased waist circumference, triglycerides, fasting glucose, blood pressure and decreased high-density lipoprotein cholesterol).

Methods

We conducted cross-sectional and prospective analyses using data from the Pars Cohort Study in southern Iran, encompassing 9,264 participants at the baseline, and 5,002 randomly selected in a repeated follow-up. We used multivariate logistic regression models adjusted for age, sex, education, wealth score, physical activity and cigarette pack-years to report odds ratios (OR) and 95% confidence intervals (CI).

Results

Among 9,264 participants, 3,119 (33.7%) had metabolic syndrome, and 3,482 (37.6%) had ever smoked waterpipe, with both more common in women than in men. In adjusted models, former waterpipe use was significantly associated with prevalence (OR = 1.43, 95% CI: 1.23-1.68) and incidence (OR = 1.57, 95% CI: 1.19-2.06) of the metabolic syndrome while current waterpipe use was not. Past use was associated with increased risk in all components of metabolic syndrome; current use was associated with increases in all except high blood glucose and hypertension. Past waterpipe users had higher waterpipe use intensity (before quitting) in comparison with current users (2.3 vs. 2.0 waterpipes per day, p < 0.01) and had started waterpipe smoking at a younger age (27.2 vs. 30.1 years, p < 0.01).

Conclusion

Waterpipe use was associated with metabolic syndrome and its components, especially among former users potentially due to higher intensity and earlier initiation of use.

Multi-omics Integration Identifies Genes Influencing Traits Associated with Cardiovascular Risks: The Long Life Family Study

The Long Life Family Study (LLFS) enrolled 4,953 participants in 539 pedigrees displaying exceptional longevity. To identify genetic mechanisms that affect cardiovascular risks in the LLFS population, we developed a multi-omics integration pipeline and applied it to 11 traits associated with cardiovascular risks. Using our pipeline, we aggregated gene-level statistics from rare-variant analysis, GWAS, and gene expression-trait association by Correlated Meta-Analysis (CMA). Across all traits, CMA identified 64 significant genes after Bonferroni correction (p ≤ 2.8×10-7), 29 of which replicated in the Framingham Heart Study (FHS) cohort. Notably, 20 of the 29 replicated genes do not have a previously known trait-associated variant in the GWAS Catalog within 50 kb. Thirteen modules in Protein-Protein Interaction (PPI) networks are significantly enriched in genes with low meta-analysis p-values for at least one trait, three of which are replicated in the FHS cohort. The functional annotation of genes in these modules showed a significant over-representation of trait-related biological processes including sterol transport, protein-lipid complex remodeling, and immune response regulation. Among major findings, our results suggest a role of triglyceride-associated and mast-cell functional genes FCER1A, MS4A2, GATA2, HDC, and HRH4 in atherosclerosis risks. Our findings also suggest that lower expression of ATG2A, a gene we found to be associated with BMI, may be both a cause and consequence of obesity. Finally, our results suggest that ENPP3 may play an intermediary role in triglyceride-induced inflammation. Our pipeline is freely available and implemented in the Nextflow workflow language, making it easily runnable on any compute platform (https://nf-co.re/omicsgenetraitassociation).

Cigarette smoking and PM2.5 might jointly exacerbate the risk of metabolic syndrome

Background

Cigarette smoking and particulate matter (PM) with aerodynamic diameter < 2.5 μm (PM2.5) are major preventable cardiovascular mortality and morbidity promoters. Their joint role in metabolic syndrome (MS) pathogenesis is unknown. We determined the risk of MS based on PM2.5 and cigarette smoking in Taiwanese adults.

Methods

The study included 126,366 Taiwanese between 30 and 70 years old with no personal history of cancer. The Taiwan Biobank (TWB) contained information on MS, cigarette smoking, and covariates, while the Environmental Protection Administration (EPA), Taiwan, contained the PM2.5 information. Individuals were categorized as current, former, and nonsmokers. PM2.5 levels were categorized into quartiles: PM2.5 ≤ Q1, Q1 < PM2.5 ≤ Q2, Q2 < PM2.5 ≤ Q3, and PM2.5 > Q3, corresponding to PM2.5 ≤ 27.137, 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3.

Results

The prevalence of MS was significantly different according to PM2.5 exposure (p-value = 0.0280) and cigarette smoking (p-value < 0.0001). Higher PM2.5 levels were significantly associated with a higher risk of MS: odds ratio (OR); 95% confidence interval (CI) = 1.058; 1.014-1.104, 1.185; 1.134-1.238, and 1.149; 1.101-1.200 for 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. The risk of MS was significantly higher among former and current smokers with OR; 95% CI = 1.062; 1.008-1.118 and 1.531; 1.450-1.616, respectively, and a dose-dependent p-value < 0.0001. The interaction between both exposures regarding MS was significant (p-value = 0.0157). Stratification by cigarette smoking revealed a significant risk of MS due to PM2.5 exposure among nonsmokers: OR (95% CI) = 1.074 (1.022-1.128), 1.226 (1.166-1.290), and 1.187 (1.129-1.247) for 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. According to PM2.5 quartiles, current smokers had a higher risk of MS, regardless of PM2.5 levels (OR); 95% CI = 1.605; 1.444-1.785, 1.561; 1.409-1.728, 1.359; 1.211-1.524, and 1.585; 1.418-1.772 for PM2.5 ≤ 27.137, 27.137 < PM2.5 ≤ 32.589, 32.589 < PM2.5 ≤ 38.205, and PM2.5 > 38.205 μg/m3, respectively. After combining both exposures, the group, current smokers; PM2.5 > 38.205 μg/m3 had the highest odds (1.801; 95% CI =1.625-1.995).

Conclusion

PM2.5 and cigarette smoking were independently and jointly associated with a higher risk of MS. Stratified analyses revealed that cigarette smoking might have a much higher effect on MS than PM2.5. Nonetheless, exposure to both PM2.5 and cigarette smoking could compound the risk of MS.

Association Between Eating Speed and Metabolic Syndrome: A Systematic Review and Meta-Analysis

Objective: This review aimed to systematically summarize and meta-analyze the association between eating speed and metabolic syndrome (MetS). Methods: Following the Preferred Reporting Items for Systematic Reviews, and Meta Analyses (PRISMA) guidelines, four electronic databases (PubMed, Web of Science, MEDLINE, and EMBASE) were searched until March 2021 to identify eligible articles based on a series of inclusion and exclusion criteria. Heterogeneity was examined using I ² statistics. Using random-effects models, the pooled odds ratios (ORs), and 95% CIs were calculated to evaluate the association between eating speed with MetS and its components, including central obesity, blood pressure (BP), high-density lipoprotein cholesterol (HDL), triglyceride (TG), and fasting plasma glucose (FPG). Results: Of the 8,500 original hits generated by the systematic search, 29 eligible studies with moderate-to-high quality were included, involving 465,155 subjects. The meta-analysis revealed that eating faster was significantly associated with higher risks of MetS (OR = 1.54, 95% CI: 1.27-1.86), central obesity (OR = 1.54, 95% CI: 1.37-1.73), elevated BP (OR = 1.26, 95% CI: 1.13-1.40), low HDL (OR = 1.23, 95% CI: 1.15-1.31), elevated TG (OR = 1.29, 95% CI: 1.18-1.42), and elevated FPG (OR = 1.16, 95% CI: 1.06-1.27) compared to eating slowly. Conclusions: The results of the review indicated that eating speed was significantly associated with MetS and its components. Interventions related to decreasing eating speed may be beneficial for the management of MetS. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021242213, identifier: CRD42021242213.

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.

Association of obesity, visceral adiposity, and sarcopenia with an increased risk of metabolic syndrome: A retrospective study

Aims

Metabolic syndrome (MS) is a global health problem associated with an increased risk of diabetes mellitus (DM), cardiovascular disease (CVD), and cancer. Body composition parameters, including obesity, visceral adiposity, and sarcopenia contribute to the development of MS and CVD. Previous studies have investigated the association of individual body composition parameters with MS. Studies analyzing the association between multiple body composition parameters and MS have been rare. We aimed to investigate the association between MS and multiple body composition parameters, including obesity, visceral adiposity, and sarcopenia.

Methods

A total of 13,620 subjects who underwent voluntary routine checkups at the Health Care Center of our institution between October 2014 and December 2019 were enrolled. Only data from the first examination of subjects who underwent repeated checkups were included. Clinical and laboratory data were collected. Skeletal muscle mass and visceral fat area (VFA) were measured using bioelectrical impedance analysis. Appendicular skeletal muscle mass (ASM) was divided by body weight (in kg) and expressed as a percentage (calculated as, ASM% = ASM × 100/Weight). Data were compared between the groups based on obesity, VFA, and ASM%. Logistic regression analysis was performed to determine the risk of MS in each group.

Results

Body mass index and VFA were significantly higher in subjects with MS than in those without MS. ASM% was significantly lower in subjects with MS than in those without MS. Subjects with obesity, visceral adiposity, or sarcopenia had a higher prevalence of MS than those without. As the number of metabolic components increased from 0 to 5, we identified a decreasing trend of ASM% and an increasing trend of VFA and BMI (P for trend < 0.001 for all). In the paired analyses, all the three body composition parameters showed additive effects in predicting MS. In the logistic regression analysis, the three parameters were associated with an increased risk of MS after adjustment for age, sex, hypertension, DM, dyslipidemia, smoking, alcohol intake, and C-reactive protein.

Conclusions

Obesity, visceral adiposity, and sarcopenia showed additive effects on MS prediction. Subjects with obesity, visceral adiposity, or sarcopenia were significantly associated with the increased risk of MS after adjustment for multiple confounders. Increasing skeletal muscle and reducing visceral fat may be strategies for the prevention or treatment of MS.

Association between self-reported eating speed and metabolic syndrome in a Beijing adult population: a cross-sectional study

Background

Research on the relationship between metabolic syndrome (MetS), its components and eating speed is limited in China. The present study aimed to clarify the association between MetS, its components and eating speed in a Beijing adult population.

Methods

This cross-sectional study included 7972 adults who were 18–65 years old and who received health check-ups at the Beijing Physical Examination Center in 2016. Logistic regression was conducted to explore the associations between MetS, its components and eating speed.

Results

The prevalence of MetS in this population was 24.65% (36.02% for males and 10.18% for females). Eating speed was significantly associated with a high risk for MetS, elevated blood pressure, and central obesity for both genders. Eating speed was associated with a high risk for elevated triglycerides and with a reduction in high-density lipoprotein in males, and eating speed was associated with a high risk for elevated fasting plasma glucose in females. Compared with slow eating speed, the multivariate-adjusted odds ratios of medium eating speed and fast eating speed for MetS were 1.65 (95% confidence interval 1.32–2.07) and 2.27 (95% confidence interval 1.80–2.86) for all subjects, 1.58 (95% confidence interval 1.21–2.07) and 2.21 (95% confidence interval 1.69–2.91) for males, and 1.75 (95% confidence interval 1.15–2.68) and 2.27 (95% confidence interval 1.46–3.53) for females, respectively.

Conclusions

Eating speed is positively associated with MetS and its components. Future recommendations aiming to prevent MetS and its components may focus on eating speed.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-5784-z) contains supplementary material, which is available to authorized users.

An association of smoking with serum urate and gout: A health paradox

BACKGROUND

The potential effect of cigarette smoking on levels of serum urate and risk of gout has been considered by a large number of studies, either as the primary variable of interest or as a covariate.

METHODS

Here we systematically review the published evidence relating to the relationship of smoking with serum urate, hyperuricaemia, and gout.

RESULTS

Many studies have reported that smoking reduces serum urate, however, the evidence has not been conclusive with other studies pointing to the opposite or no effect. It has also been suggested that smoking reduces the risk of gout, although there is some evidence to contradict this finding.

CONCLUSION

A consensus has yet to be reached as to the effect of smoking on serum urate levels and the risk of gout.

Variability in responses observed in human white adipose tissue models

Obesity is a risk factor for a myriad of diseases including diabetes, cardiovascular dysfunction, cirrhosis, and cancer, and there is a need for new systems to study how excess adipose tissue relates to the onset of disease processes. This study provides proof-of-concept patient-specific tissue models of human white adipose tissue to accommodate the variability in human samples. Our 3D tissue engineering approach established lipolytic responses and changes in insulin-stimulated glucose uptake from small volumes of human lipoaspirate, making this methodology useful for patient specific sample source assessments of treatment strategies, drug responses, disease mechanisms, and other responses that vary between patients. Mature unilocular cells were maintained ex vivo in silk porous scaffolds for up to a month of culture and imaged non-invasively with coherent anti-Stokes Raman scattering. Interestingly, differences in responsiveness between tissues were observed in terms of magnitude of lipolysis, ability to suppress lipolysis, differences in glucose uptake, and lipid droplet size. Body mass index was not a factor in determining tissue responsiveness; rather, it is speculated that other unknown variables in the backgrounds of different patients (ethnicity, athleticism, disease history, lifestyle choices, etc.) likely had a more significant effect on the observed differences. This study reinforces the need to account for the variability in backgrounds and genetics within the human population to determine adipose tissue responsiveness. In the future, this tissue system could be used to inform individualized care strategies-enhancing therapeutic precision, improving patient outcomes, and reducing clinical costs.

Outcomes of The BODY Project: A Program to Halt Obesity and Its Medical Consequences in High School Students

Adolescent obesity continues to be a major public health issue with a third of American adolescents being overweight or obese. Excess weight is associated with cardiovascular risk factors and pre-diabetes. High school students identified as carrying excess weight [body mass index (BMI) ≥25 kg/m(2), or BMI percentile ≥85 %] were invited to participate in The BODY Project, an intervention that included a medical evaluation and a personalized medical report of the results of that evaluation sent to the parent/guardian at home. The medical evaluation and report was repeated 12 months later. The reports also contained advice on how the individual student could modify their lifestyle to improve the specific medical parameters showing abnormalities. Outcomes were change in BMI, blood pressure, high-density lipoprotein (HDL), low-density lipoprotein (LDL), fasting glucose, and fasting insulin. Students participating in The BODY Project intervention demonstrated modest, yet significant, reductions in BMI (p < 0.001) 1 year later, and also had significant improvements in systolic blood pressure (p < 0.001) and cholesterol profile (HDL p = 0.002; LDL p < 0.001) at follow-up. The BODY Project, by means of a minimal educational program anchored on the principle of teachable moments around the students' increased perception of their own risk for disease from the medical abnormalities uncovered, demonstrates evidence of potential effectiveness in addressing adolescent obesity.

The association between quitting smoking and weight gain: a systematic review and meta-analysis of prospective cohort studies

This systematic review and meta-analysis aimed to quantify weight gain after smoking cessation and the difference in weight gain between quitters and continuing smokers. Five electronic databases were searched before January 2015. Population-based prospective cohort studies were included if they recorded the weight change of adult smokers from baseline (before smoking cessation) to follow-up (at least 3 months after cessation). Thirty-five cohort studies were identified, including 63,403 quitters and 388,432 continuing smokers. The mean weight gain was 4.10 kg (95% confidence interval [CI]: 2.69, 5.51) and body mass index (BMI) gain was 1.14 kg m(-2) (95% CI: 0.50, 1.79) among quitters. Compared with continuing smoking, quitting smoking was significantly associated with absolute weight (adjusted mean difference [MD]: 2.61 kg; 95% CI: 1.61, 3.60) and BMI gain (adjusted MD: 0.63 kg m(-2) ; 95% CI: 0.46, 0.80). Subgroup analyses using geographic region found that the difference in weight gain was considerably greater in studies from North America than from Asia. Follow-up length was identified as a source of heterogeneity, such that studies with longer follow-up showed greater difference in weight gain. Effective strategies are needed to encourage smokers to quit irrespective of potential weight gain and to help quitters avoid excess weight gain.

A study of gender-wise risk association between fatty liver and metabolic syndrome components (Asia-Pacific criteria) in a South Indian urban cohort

BACKGROUND

Metabolic syndrome (MS) is associated with fatty liver (FL) disease. Gender differences in this association are not known.

AIM

The aim of the present study was to determine gender-wise association between FL and MS components (using Asia-Pacific guidelines 2007) in an urban south Indian cohort with normal liver function tests (LFT).

METHODS

Records of consecutive attendees of a Master Health Check up program were reviewed for age, gender, body mass index (BMI), blood pressure, fasting blood sugar (FBS), high-density lipoproteins, triglyceride (TG) levels, presence of FL by ultrasound. The cohort was grouped gender-wise as FL and nonfatty liver (NFL). Foreign nationals; those with alcohol intake >20 g/day; and those with diabetes, hypertension, hypertriglyceridemia, chronic liver disease, or abnormal LFT were excluded.

STATISTICS

Chi-square, gender-wise univariate and logistic regression analyses of each MS component for FL, relative risk (RR), and 95 % confidence interval (CI) for significant factors (p < 0.05 and RR or log odds >1.5) were calculated.

RESULTS

Of the 1,075 (63 % males) cases included, 45.8 % had FL. Gender (log odds 1.6 compared to women) and BMI ≥25 kg/m(2) (RR 1.6 % to 95 % CI 1.3 to 1.9; log odds 2.2) were the only factors associated with FL in men. In women, age ≥40 years (log odds 2.3), fasting blood sugar (FBS) ≥100 mg/dL (RR 1.8-1.4 to 2.3; log odds 1.9), and TG ≥150 mg/dL (RR 1.7-1.3 to 2.1; log odds 1.7) were independently associated with FL.

CONCLUSION

There was a gender-wise difference in MS components associated with hepatic steatosis and normal LFT in a south Indian urban cohort.

Relationship between smoking and metabolic syndrome in men with diabetes mellitus

INTRODUCTION

Metabolic syndrome is a potent risk factor for cardiovascular disease and is often complicated in patients with diabetes. The aim of this study was to determine whether and how smoking is related to metabolic syndrome in patients with diabetes.

METHODS

Subjects were men with diabetes (n=2675) who had been diagnosed as a result of health examinations at their workplaces. They were divided into nonsmokers, light smokers (≤ 20 cigarettes per day) and heavy smokers (>20 cigarettes per day). The relationships of smoking with metabolic syndrome and its components, including obesity, high blood pressure, and dyslipidemia [high triglycerides and/or low high-density lipoprotein cholesterol (HDL-C)] in nondrinkers, light drinkers (<22 grams of ethanol per day), and heavy drinkers (≥ 22 grams of ethanol per day) were investigated by logistic regression analysis with adjustment for age, regular exercise, and drug therapy for diabetes.

RESULTS

In nondrinkers with diabetes, the odds ratio (OR) versus nonsmokers for metabolic syndrome was significantly higher in heavy smokers (2.47 [95% confidence interval (CI) 1.43-4.25]) but not different in light smokers [1.03 (95% CI 0.71-1.49)] when compared with the reference level of 1.00. In the light and heavy drinker groups, the ORs versus nonsmokers for metabolic syndrome were not significantly different from the reference level in the smoker groups, except for a significantly lower OR of light smokers in the heavy drinker group [0.69 (95% CI 0.53-0.90)]. In nondrinkers, the ORs of heavy smokers versus nonsmokers for large waist circumference [1.64 (95% CI 1.01-2.68)], high triglycerides [1.78 (95% CI 1.12-2.81)], and low HDL-C [3.20 (95% CI 1.99-5.14]), but not the OR for high blood pressure [1.02 (95% CI 0.60-1.72)], were significantly higher than the reference level.

CONCLUSION

In nondrinkers with diabetes, there is a positive association between heavy smoking and metabolic syndrome, which is mainly due to higher risks of central obesity and dyslipidemia, such as hypertriglyceridemia and low HDL cholesterolemia, in heavy smokers than in nonsmokers.

Prevalence rate of Metabolic Syndrome in a group of light and heavy smokers

BACKGROUND

Smoking is an important cause of morbidity and mortality worldwide. It is widely accepted as a major risk factor for metabolic and cardiovascular disease. Smoking reduces insulin sensitivity or induces insulin resistance and enhances cardiovascular risk factors such as elevated plasma triglycerides, decreases high-density lipoprotein cholesterol and causes hyperglycemia. Several studies show that smoking is associated with metabolic abnormalities and increases the risk of Metabolic Syndrome. The aim of this study was to estimate the prevalence of the metabolic syndrome in a group of light and heavy smokers, wishing to give up smoking.

METHODS

In this cross-sectional study all the enrolled subjects voluntary joined the smoking cessation program held by the Respiratory Pathophysiology Unit of San Matteo Hospital, Pavia, Northern Italy.All the subjects enrolled were former smokers from at least 10 years and had no cancer or psychiatric disorders, nor history of diabetes or CVD or coronary artery disease and were not on any medication.

RESULTS

The subjects smoke 32.3 ± 16.5 mean Pack Years. The prevalence of the metabolic syndrome is 52.1%: 57.3% and 44.9% for males and females respectively. Analysing the smoking habit influence on the IDF criteria for the metabolic syndrome diagnosis we found that all the variables show an increasing trend from light to heavy smokers, except for HDL cholesterol. A statistical significant correlation among Pack Years and waist circumference (R = 0.48, p < 0.0001), Systolic Blood Pressure (R = 0.18, p < 0.05), fasting plasma glucose (R = 0.19, p < 0.005) and HDL cholesterol (R = -0.26, p = 0.0005) has been observed.

CONCLUSIONS

Currently smoking subjects are at high risk of developing the metabolic syndrome.Therapeutic lifestyle changes, including smoking cessation are a desirable Public health goal and should successfully be implemented in clinical practice at any age.

Active smoking and risk of metabolic syndrome: a meta-analysis of prospective studies

Background

Epidemiological evidence suggests that smoking has been associated with emergence of metabolic syndrome. However, data on this issue are inconsistent and controversial. We therefore conducted a meta-analysis to examine the association between smoking and metabolic syndrome.

Methodology and Principal Findings

We searched the Medline, Embase and the Cochrane Library database up to March 2012 to identify prospective cohort studies related to smoking and metabolic syndrome. Reference lists of retrieved articles were also reviewed. Summary effect estimates were derived using a random-effects model and stratified by gender, smoking dose, follow-up duration and geographical area. Primary analysis of 13 studies involving 56,691 participants and 8,688 cases detected a significant positive association between active smoking and risk of metabolic syndrome (pooled relative risk [RR] 1.26, 95% CI: 1.10–1.44). Estimates of effects were substantially consistent in the stratified analyses. In the dose-response analysis, risk of metabolic syndrome was stronger for active male smokers (pooled RR 1.34, 95% CI: 1.20–1.50) than it was for former male smokers (pooled RR 1.19, 95% CI: 1.00–1.42), and greater for heavy smokers (pooled RR 1.42, 95% CI: 1.27–1.59) compared with light smokers (pooled RR 1.10, 95% CI: 0.90–1.35). No evidence of statistical publication bias was found (Egger' s test P = 0.227, Begg' s test P = 0.113).

Conclusions

Active smoking is associated with development of metabolic syndrome. Smoking cessation appears to reduce the risk of metabolic syndrome.

[Incidence of metabolic syndrome and associated lifestyle factors in a worksite male population]

OBJECTIVES

The prevention of metabolic syndrome (MetS) is one of the main targets of health promotion activities in the workplace. The present study aimed to clarify the incidence of MetS and associated lifestyle factors in a worksite male population.

METHODS

The study subjects consisted of 948 working men (mean age: 44 yr old) who did not meet the Japanese criteria for MetS during the annual health examination at a precision instrument development plant in Kanagawa, Japan, 2005. New-onset MetS was followed using the health examination data from 2006 to 2009. The incidence of MetS according to the combination of the presence of abdominal obesity and the number of other components of MetS (elevated blood pressure, dyslipidemia, and elevated fasting glucose) at baseline were calculated. The incidence of MetS was also compared among the groups with regard to differences in lifestyles (dietary habits, smoking status, sleep duration, exercise habits, and alcohol intake). A Cox proportional hazard model was used to identify independent factors contributing to an increased risk of MetS.

RESULTS

New-onset MetS was observed in 76 subjects during a mean follow-up period of 3.7 yr. The incidence of MetS was 2.2/100 person-years and the 4-year incidence of MetS according to Kaplan-Meier analysis was 8.5%. The highest 4-year incidence of MetS was found in the group without abdominal obesity but with two or more components of MetS (37.9%) and the second highest incidence was found in the group with abdominal obesity and one other component of MetS (24.6%). The presence of abdominal obesity and each increase in the number of other components of MetS had an increased age-adjusted hazard ratio for an increased risk of MetS (5.23 and 4.79, respectively, both p<0.001). Similarly, sleep duration 5 h or less, current smoking, and ethanol intake 300 g/wk or more had an increased age-adjusted hazard ratio for an increased risk of MetS.

CONCLUSIONS

The present study showed a high incidence of MetS in not only the group with abdominal obesity, but also the group without abdominal obesity but with two or more components of MetS. Sleep deprivation, current smoking, and excess alcohol intake were found to be factors contributing to an increased risk of MetS among several lifestyle factors examined. The usefulness of health promotion activities that preferentially target subjects who have such medical conditions and/or lifestyles are therefore expected to reduce the incidence of MetS in the workplace, from a high-risk strategy viewpoint.