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