Baylor University Medical Center Proceedings April 2014, Volume 27, Number 2 | Page 23

Table 1. Demographic characteristics of the 853 hospital employees in the cohort Category Variable Female Male All Gender Employee gender 788 (92%) 65 (8%) 853 Ethnicity American Indian∗ 4 (100%) 0 4 Table 2. Regression analysis of the metabolic syndrome from 2009 to 2012, stratified by weight, gender, and ethnicity in 853 employees of a pediatric hospital Variable Standard Wald ChiParameter∗ DF estimate error square Significance <.0001 Intercept 1 –1.031 0.15 45.85 68 Square root of time† 1 –0.15 0.079 3.7 1 (2%) 53 Obesity 0 1 1.46 0.083 309.4 <.0001 108 (93%) 8 (7%) 116 Overweight 1 1 0.43 0.085 24.5 <.0001 15 (94%) 1 (6%) 16 0.33 0.085 15.4 <.0001 Asian 18 (90%) 2 (10%) 20 African American (Black) 67 (98%) 1 (2%) Hispanic other 52 (98%) Hispanic White Multiple Pacific Islander∗ 1 (100%) 0.06 Gender 0 1 1 Asian 0 1 1.29 0.30 18.4 <.0001 52 (9%) 575 Black 1 1 –0.77 0.178 18.7 <.0001 2 1 0.19 0.179 1.0 0 Caucasian (White) 18–30 166 (98%) 3 (2%) 169 Hispanic other 30–40 253 (91%) 26 (9%) 279 Hispanic white 3 1 0.28 0.14 3.9 0.05 40–50 206 (91%) 24 (9%) 230 1 –0.71 0.35 4.2 0.04 159 (94%) 10 (6%) 169 Multiple ethnicities 4 50–65 Age group 523 (91%) 65+ ∗Excluded 4 (67%) 2 (33%) 6 from the study due to small size. than 90% of participants were women, and 575 of 853 (67%) were Caucasian. At baseline, the mean age was 39 years for the women and 42 years for the men. Because of the small sample in the ethnic groups of American Indian and Pacific Islander, these individuals were excluded from the analysis. We found that more obese individuals migrated to the overweight category than overweight individuals migrated towards the obese category. The normal weight rate kept stable over the 4 years. The logistic regression model validated a decline of MS over time (P = 0.02), showing that the program was effective in reducing MS over time in the entire cohort (Table 2). There was an increased risk of MS in both the obese and overweight categories (P < 0.0001) compared with the normal weight group. MS risk increased in men using women as a reference (P < 0.0001), as well as in Asians (P < 0.0001), Blacks (P < 0.0001), Hispanic Whites (P = 0.0495), and multiple races (P = 0.04). The data were also analyzed to determine odds ratios (OR). There was an overall decrease in the odds of MS in this cohort from 2009 to 2012 (OR = 0.84, P = 0.02). The odds of having MS were the highest in the obese category (OR = 20.37, P < 0.0001), followed by the overweight category (OR = 7.42, P < 0.0001). Men were almost twice as likely to have MS (OR = 2.02, P < 0.0001) as women. If all other factors were controlled, several ethnicities had an increased odds of having MS, including Hispanic other (OR = 2.02, P = 0.0001), Hispanic White (OR = 1.87, P < 0.0001), and Asians, who had the highest risk for MS (OR = 4.46, P < 0.0001). In contrast, African Americans had a decreased odds of having MS (OR = 0.69, P = 0.03). Age groups older than the 18–30 year reference group had increased odds of having MS, including the April 2014 0.3 ∗Weight = 0 for obese and 1 for overweight vs normal; gender = 0 for males vs females; G = 0, 1, 2, 3, 4 for Asian, Black, Hispanic other, Hispanic White, and Multiple vs White. †Square root of time = year 2009 to 2012. 40–50 year group (OR = 1.66, P = 0.0015) and the 50–65 year group (OR = 2.22, P = 0.0001). The results using the longitudinal GEE logistic model on the right side of Table 3 confirm a significant decline of MS over the 4 years of the study (P = 0.004). The same significant association between MS and the obese and overweight groups was found (P < 0.0001), as well as the increased MS in men (P = 0.0008) when compared to women. Furthermore, a significant association between MS and most ethnicities (P < 0.0001) except for the African American and American Indian categories (P = 0.23 and 0.4, respectively) was found. This model also showed that all subjects older than 30 years had a significantly increased risk for MS, including the 40–50 year group (P < 0.0086) and 50–65 year group (P < 0.0001), when compared to baseline. DISCUSSION There are not many cohort studies that follow MS over time. Even fewer longitudinal studies have been conducted that focus on MS and ethnicity factors. Due to limited data, we could not evaluate the effect of smoking status on the model. However, smoking status has been found to have a significant effect on MS in other studies (2). Having a high risk of MS in older age is consistent with Sun’s finding in 2012 (3). Our finding on the different risks in ethnicities and possible protective factors in African Americans in one model of the longitudinal study is new in the research of MS. It suggests that African Americans can have better health if obesity and other factors are better controlled. More research is needed to evaluate what these protective factors are, since it was not corroborated A cohort analysis of the cardiovascular risk factors in the employees of a pediatric hospital from 2009 to 2012 97