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

Table 3. The impact of a wellness program over time on the metabolic syndrome parameters in 853 employees of a pediatric hospital, stratified by weight, gender, and ethnicity 95% confidence Parameter Estimate GEE standard error Parameter error Estimates Z Pr> |Z| Intercept –3.16 0.19 –3.53 –2.7929 Square root of time* –0.17 0.063 –0.29 –0.044 –2.65 0.008 –16.8 <.0001 Obese 0 2.78 0.21 2.37 3.19 13.17 <.0001 Overweight 1 1.93 0.20 1.54 2.31 9.84 <.0001 Normal weight 2 0 0 0 0 Male 0 0.71 0.23 0.26 1.16 3.11 0.002 Female 1 0 0 0 0 Asian 0 1.29 0.44 0.42 2.14 2.92 0.003 Black 1 –0.39 0.26 –0.90 0.12 –1.49 0.13 Hispanic other 2 0.54 0.27 0.004 1.08 1.98 0.05 2.74 0.006 Hispanic white 3 0.58 0.21 0.17 0.99 Multiple ethnicity 4 –0.34 0.69 –1.70 1.01 White 5 <30 y 0 –0.52 0.24 –0.99 30–40 y 1 –0.34 0.15 –0.63 >40 y 2 0.00 0.00 0.00 0.00 0 0 0 –0.5 0.62 0.05 –2.17 0.03 –0.05 –2.26 0.03 0 *Square root of time = year 2009 to 2012. GEE indicates generalized estimated equation. by the second model, to assess if these are true factors, whether genetic, nutritional, or environmental. The study showed an overall decline of MS over time in the obese and overweight categories during the 4 years of the study, which indicates movement away from increased cardiovascular risk. Certainly, the diﬀerences in MS in diﬀerent ethnicities warrant more research to assess whether there are genetic, cultural, or environmental factors that are worth studying for future interventional strategies. Night shift employees—those who do not work in daytime hours—comprise 20% of the US workforce and are more predisposed to have MS (3). Hospitals depend on shift workers. Factors associated with rapid progression toward getting MS for middle-aged workers include persistent daynight rotating shift work, shift duration, education, length of employment, age, diﬀerences in diet, body mass index, total cholesterol, triglycerides, job strain, sedentary activity, dietary style, and smoking (4–12, 15, 16). Educational level may be a confounding factor in MS as it impacts shift work. Animal studies indicate that shifts in usual mealtimes which impact the diurnal rhythms of carbohydrate and lipid metabolism pose critical implications for MS risk in shift workers (12). Socioeconomic factors such as income have unknown eﬀects on shift work and MS. Criteria for MS are used in many wellness programs to generate information about cardiovascular health for employees. Yet the longitudinal success of wellness programs is rarely 98 followed over time despite substantial monetary investments by employers. Measuring grouped criteria outcomes and providing feedback such as provided by this study to employees is vital to initiating change within an employee base (13–15). 1. Ha M, Park J. Shiftwork and metabolic risk factors of cardiovascular disease. J Occup Health 2005;47(2):89–95. 2. Mohebbi I, Shateri K, Seyedmohammadzad M. The relationship between working schedule patterns and the markers of the metabolic syndrome: comparison of shift workers with day workers. Int J Occup Med Environ Health 2012;25(4):383–391. 3. Yoon YS, Lee ES, Park C, Lee S, Oh SW. The new deﬁnition of metabolic syndrome by the International Diabetes Federation is less likely to identify metabolically abnormal but non-obese individuals than the deﬁnition by the revised National Cholesterol Education Program: the Korea NHANES study. Int J Obes (Lond) 2007;31(3):528–534. 4. Lin YC, Hsiao TJ, Chen PC. Persistent rotating shift-work exposure accelerates development of metabolic syndrome among middle-aged female employees: a ﬁve-year follow-up. Chronobiol Int 2009;26(4):740– 755. 5. Copertaro A, Bracci M, Barbaresi M, Santarelli L. Role of waist circumference in the diagnosis of metabolic syndrome and assessment of cardiovascular risk in shift workers [article in Italian]. Med Lav 2008;99(6):444–453. 6. Pietroiusti A, Neri A, Somma G, Coppeta L, Iavicoli I, Bergamaschi A, Magrini A. Incidence of metabolic syndrome among night-shift healthcare workers. Occup Environ Med 2010;67(1):54–57. 7. Jermendy G, Nádas J, Hegyi I, Vasas I, Hidvégi T. Assessment of cardiometabolic risk among shift workers in Hungary. Health Qual Life Outcomes 2012;10:18. Baylor University Medical Center Proceedings Volume 27, Number 2

Baylor University Medical Center Proceedings April 2014, Volume 27, Number 2 | Seite 24