Skip to main content
. 2018 Aug 3;53(6):515–526. doi: 10.1093/abm/kay063

Table 3.

Multiple logistic regression model for metabolic syndrome using HR cluster as independent variable

OR (95% CI) p
HR Cluster (Cluster 2 vs. Cluster 1) 1.45 (1.02–2.07) .04
Sex (male vs. female) 1.35 (0.94–1.93) .10
Age (1 SD = 7.0 year increase in age) 1.04 (0.89–1.22) .64
Presence of CAD 0.98 (0.69–1.39) .91
BMI (1 SD = 5.3 kg/m2 increase in BMI) 3.46 (2.77–4.32) <.001
Exercise (hours/week) (1 SD=3.6 hour increase in exercise) 0.92 (0.79–1.06) .25
Household income
 $40,000–59,999 vs. ≤$39,999 0.80 (0.51–1.27) .35
 $60,000–99,999 vs. ≤$39,999 0.66 (0.42–1.03) .07
 ≥$100,000 vs. ≤$39,999 0.57 (0.34–0.93) .03
Years of school 0.95 (0.80–1.11) .50
Medication influencing MetS parameters 1.19 (0.72–1.94) .50
Other medications 1.61 (0.80–3.23) .18
Presence of comorbid medical conditions 1.50 (1.10–2.04) .01
Sex hormone therapy 0.63 (0.32–1.27) .20

OR = odds ratio, CI = confidence interval, SBP = systolic blood pressure, BMI = body mass index, CAD = coronary artery disease.