Importance

Coronary artery calcium (CAC), measured by computed tomography (CT), has strong predictive value for incident cardiovascular disease (CVD) events. The standard CAC score is the Agatston, which is weighted upward for greater calcium density. However, some data suggest increased plaque calcium density may be protective for CVD.

Objective

To determine the independent associations of CAC volume and CAC density with incident CVD events.

Design, setting, and participants

Multicenter, prospective observational MESA study (Multi-Ethnic Study of Atherosclerosis), conducted at 6 US field centers of 3398 men and women from 4 race/ethnicity groups; non-Hispanic white, African American, Hispanic, and Chinese. Participants were aged 45-84 years, free of known CVD at baseline, had CAC greater than 0 on their baseline CT, and were followed up through October 2010.

Main outcomes and measures

Incident coronary heart disease (CHD) and all CVD events

Results

During a median of 7.6 years of follow-up, there were 175 CHD events and an additional 90 other CVD events for a total of 265 CVD events. With both lnCAC volume and CAC density scores in the same multivariable model, the lnCAC volume score showed an independent association with incident CHD, with a hazard ratio (HR) of 1.81 (95% CI, 1.47-2.23) per standard deviation (SD = 1.6) increase, absolute risk increase 6.1 per 1000 person-years, and for CVD an HR of 1.68 (95% CI, 1.42-1.98) per SD increase, absolute risk increase 7.9 per 1000 person-years. Conversely, the CAC density score showed an independent inverse association, with an HR of 0.73 (95% CI, 0.58-0.91) per SD (SD = 0.7) increase for CHD, absolute risk decrease 5.5 per 1000 person-years, and an HR of 0.71 (95% CI, 0.60-0.85) per SD increase for CVD, absolute risk decrease 8.2 per 1000 person years. Area under the receiver operating characteristic curve analyses showed significantly improved risk prediction with the addition of the density score to a model containing the volume score for both CHD and CVD. In the intermediate CVD risk group, the area under the curve for CVD increased from 0.53 (95% CI, 0.48-0.59) to 0.59 (95% CI, 0.54-0.64), P = .02.

Conclusions and relevance

CAC volume was positively and independently associated with CHD and CVD risk. At any level of CAC volume, CAC density was inversely and significantly associated with CHD and CVD risk. The role of CAC density should be considered when evaluating current CAC scoring systems.

Objective

South Asians have a higher prevalence of type 2 diabetes compared with other race/ethnic groups. Body composition is associated with the risk for type 2 diabetes. Differences in body composition between South Asians and other race/ethnic groups are one hypothesized mechanism to explain the disproportionate prevalence of type 2 diabetes in this population.

Research design and methods

This study used data from the Mediators of Atherosclerosis in South Asians Living in America (MASALA) and the Multi-Ethnic Study of Atherosclerosis (MESA) cohorts to determine whether body composition mediated the elevated prevalence of impaired fasting glucose and type 2 diabetes in South Asians. Participants (n = 2,615) with complete body composition data were included. Ordinal logistic regression models were calculated to determine the odds for glycemic impairment in South Asians compared with the MESA cohort.

Results

In multivariate models, South Asians had a significantly higher prevalence of glycemic impairment and type 2 diabetes compared with all four race/ethnic groups included in the MESA (P < 0.001 for all). In unadjusted and multivariate adjusted models, South Asians had higher odds for impaired fasting glucose and type 2 diabetes compared with all other race/ethnic groups (P < 0.001 for all). The addition of body composition measures did not significantly mitigate this relationship.

Conclusions

We did not identify strong evidence that accounting for body composition explains differences in the risk for type 2 diabetes. Future prospective studies of the MESA and MASALA cohorts are needed to understand how adipose tissue impacts the risk for type 2 diabetes and how to best assess this risk.