Associations between essential metals exposure and metabolic syndrome (MetS): Exploring the mediating role of systemic inflammation in a general Chinese population

In recent years, several major organizations have endorsed the concept of the metabolic syndrome and developed working definitions for it. How well these definitions predict the risk for adverse events in people with the metabolic syndrome is only now being learned. The purpose of this study was to summarize the estimates of relative risk for all-cause mortality, cardiovascular disease, and diabetes reported from prospective studies in samples from the general population using definitions of the metabolic syndrome developed by the National Cholesterol Education Program (NCEP) and World Health Organization (WHO). The author reviewed prospective studies from July 1998 through August 2004. For studies that used the exact NCEP definition of the metabolic syndrome, random-effects estimates of combined relative risk were 1.27 (95% CI 0.90-1.78) for all-cause mortality, 1.65 (1.38-1.99) for cardiovascular disease, and 2.99 (1.96-4.57) for diabetes. For studies that used the most exact WHO definition of the metabolic syndrome, the fixed-effects estimates of relative risk were 1.37 (1.09-1.74) for all-cause mortality and 1.93 (1.39-2.67) for cardiovascular disease; the fixed-effects estimate was 2.60 (1.55-4.38) for coronary heart disease. These estimates suggest that the population-attributable fraction for the metabolic syndrome, as it is currently conceived, is approximately 6-7% for all-cause mortality, 12-17% for cardiovascular disease, and 30-52% for diabetes. Further research is needed to establish the use of the metabolic syndrome in predicting risk for death, cardiovascular disease, and diabetes in various population subgroups.

Taking into account a continuous exposure in regression models by using categorization, when non-linear dose-response associations are expected, have been widely criticized. As one alternative, restricted cubic spline (RCS) functions are powerful tools (i) to characterize a dose-response association between a continuous exposure and an outcome, (ii) to visually and/or statistically check the assumption of linearity of the association, and (iii) to minimize residual confounding when adjusting for a continuous exposure. Because their implementation with SAS® software is limited, we developed and present here an SAS macro that (i) creates an RCS function of continuous exposures, (ii) displays graphs showing the dose-response association with 95 per cent confidence interval between one main continuous exposure and an outcome when performing linear, logistic, or Cox models, as well as linear and logistic-generalized estimating equations, and (iii) provides statistical tests for overall and non-linear associations. We illustrate the SAS macro using the third National Health and Nutrition Examination Survey data to investigate adjusted dose-response associations (with different models) between calcium intake and bone mineral density (linear regression), folate intake and hyperhomocysteinemia (logistic regression), and serum high-density lipoprotein cholesterol and cardiovascular mortality (Cox model). 2010 John Wiley & Sons, Ltd.

Mortality resulting from coronary heart disease (CHD), cardiovascular disease (CVD), and all causes in persons with diabetes and pre-existing CVD is high; however, these risks compared with those with metabolic syndrome (MetS) are unclear. We examined the impact of MetS on CHD, CVD, and overall mortality among US adults. In a prospective cohort study, 6255 subjects 30 to 75 years of age (54% female) (representative of 64 million adults in the United States) from the Second National Health and Nutrition Examination Survey were followed for a mean+/-SD of 13.3+/-3.8 years. MetS was defined by modified National Cholesterol Education Program criteria. From sample-weighted multivariable Cox proportional-hazards regression, compared with those with neither MetS nor prior CVD, age-, gender-, and risk factor-adjusted hazard ratios (HRs) for CHD mortality were 2.02 (95% CI, 1.42 to 2.89) for those with MetS and 4.19 (95% CI, 3.04 to 5.79) for those with pre-existing CVD. For CVD mortality, HRs were 1.82 (95% CI, 1.40 to 2.37) and 3.14 (95% CI, 2.49 to 3.96), respectively; for overall mortality, HRs were 1.40 (95% CI, 1.19 to 1.66) and 1.87 (95% CI, 1.60 to 2.17), respectively. In persons with MetS but without diabetes, risks of CHD and CVD mortality remained elevated. Diabetes predicted all mortality end points. Those with even 1 to 2 MetS risk factors were at increased risk for mortality from CHD and CVD. Moreover, MetS more strongly predicts CHD, CVD, and total mortality than its individual components. CHD, CVD, and total mortality are significantly higher in US adults with than in those without MetS.