558515
research-article2014
HPPXXX10.1177/1524839914558515Health Promotion PracticeRadler et al. / Improved Risk Factors in Overweight and Obese Worksite Participants
Improvements in Cardiometabolic Risk Factors Among Overweight and Obese Employees Participating in a University Worksite Wellness Program Diane Rigassio Radler, PhD1 Andrea Fleisch Marcus, PhD1 Rachel Griehs, MS1 Riva Touger-Decker, PhD1
Objective. To determine immediate changes in weight and cardiometabolic risk of participants in a university worksite wellness program (WWP). It was hypothesized that there would be significant improvements in weight and waist circumference after 12 weeks. Method. Employees volunteered for enrollment in a 12-week WWP that provided educational sessions in-person or online. At baseline and after 12 weeks, participants had one-on-one appointments with the study registered dietitian who measured clinical outcome markers (cardiometabolic risk factors) and provided individualized counseling. Results. Among 79 participants who returned for 12-week appointments, there were statistically significant improvements in weight (p < .0001), waist circumference (p < .0001), and other cardiometabolic risk factors from baseline to 12-weeks. Conclusions. Improvements in cardiometabolic risk factors may be observed in a relatively short period of time among those who enrolled in a WWP. Keywords: obesity; chronic disease; cardiovascular disease; health promotion; nutrition
Introduction >> Health and wellness concepts may vary by individuals but are rooted in values and shaped by physical,
Health Promotion Practice Month XXXX Vol. XX , No. (X) 1–9 DOI: 10.1177/1524839914558515 © 2014 Society for Public Health Education
social, and cultural environments (Berkman, Glass, Brissette, & Seeman, 2000). According to the World Health Organization (WHO; 1998), “Wellness is the optimal state of health . . .” encompassing physical and mental health in the community, family and work environments. Wellness should be part of everyday life; Healthy People 2020 aims to promote healthy behaviors to reduce preventable diseases and promote quality of life (U.S. Department of Health & Human Services, 2010b). Since 65% of the population in the United States is employed (U.S. Department of Commerce, U.S. Census Bureau, 2014) and may spend many hours a day at work, the workplace can be an ideal environment to support and promote health and wellness. Hence, worksite wellness programs (WWPs) can benefit the employee directly, while the employer gains a productive and healthy workforce (Pelletier, 2011). Worksite wellness refers to an infrastructure the employer cultivates in order to improve health behaviors and outcomes, which may target the employee or the work environment (Anderson et al., 2009; Centers for Disease Control and Prevention [CDC], 2013; Pearson et al., 2013). The need for such programs is underscored by the cardiometabolic risks posed by overweight and obesity 1
Rutgers University School of Health Related Professions, Newark, NJ, USA
Authors’ Note: Address correspondence to Diane Rigassio Radler, Rutgers University School of Health Related Professions, 65 Bergen Street, Room 157, Newark, NJ 07107, USA; e-mail: diane.
[email protected].
1
(Lloyd-Jones et al., 2010) and compounded by the fact that only one third of U.S. adults have a body mass index (BMI) that is healthy, while 64% are considered overweight (36%) or obese (28%). These statistics are similar for New Jersey, with 37% of adults overweight and 25% obese (CDC Behavioral Risk Factor Surveillance System, n.d.). By 2030, the prevalence of obesity in New Jersey is projected to be 48.6%, which could lead to an increased incidence of related chronic diseases and health care costs (Trust for America’s Health & Robert Wood Johnson Foundation, 2013). Conversely, if the prevalence of high BMI can be reduced by 5%, it may decrease obesity-related costs and spare numerous residents of the burden of obesityrelated diseases, such as type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD; Trust for America’s Health & Robert Wood Johnson Foundation, 2013). Lifestyle behaviors can affect disease risk; WWP can be cost-effective in preventing disease onset, progression, and severity (Carnethon et al., 2009; Eckel et al., 2014; Pelletier, 2011).
Background/Literature Review >> WWPs can select clinical markers to monitor as outcome measures such as BMI, waist circumference, blood pressure (BP), and serum glucose and lipid values (Consensus Statement of the Health Enhancement Research Organization, American College of Occupational and Environmental Medicine, & Care Continuum Alliance, 2013) all of which are considered cardiometabolic risk factors (Carnethon et al., 2009; Eckel et al., 2013). Since a 7% weight loss can reduce insulin resistance and CVD risk, percentage weight change may be a marker of overall risk reduction. Waist circumference, a measure of abdominal obesity, is a marker of risk for T2DM and metabolic syndrome (Klein et al., 2004). The primary aims of cardiometabolic screening are to identify disease risk and recommend actions to improve health. For the purposes of this article, cardiometabolic screening will be used to refer to all of these markers. Worksites can use these data to describe their employee population’s health status or use a matrix such as the Framingham risk percentage to describe a 10-year CVD risk; they may also monitor changes in employee health in WWP that aim to promote a healthy weight and reduce disease risk (Lin, O’Connor, Whitlock, & Beil, 2010). In the United States, 29.1% of adults have hypertension, but only 82.8% of them reported awareness of nonnormal BP (Crim et al., 2012; Nwankwo, Yoon, Burt, & Gu, 2013). Although a single measurement of high BP is not diagnostic of hypertension, this minimally
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invasive measurement can detect surveillance hypertension (Crim et al., 2012). Similarly, fingerstick screenings of serum lipids and glucose offer immediate results that may help detect risk factors for CVD and T2DM (Consensus Statement of the Health Enhancement Research Organization et al., 2013). Lifestyle modification is a primary recommendation to lower BP and lipid levels prior to the introduction of medications (Stone et al., 2014). WWPs have expanded in number, scope, content, and method(s) of delivery over the past decade (Aneni et al., 2014) from traditional in-person modes to Internet-based or combination modalities. Internetbased programs have been studied with variable outcomes (Aneni et al., 2014; Verweij, Coffeng, van Mechelen, & Proper, 2011). The length of such programs ranged from a few weeks to 3, 6, and 12 months, with some of longer durations. Touger-Decker, Denmark, Bruno, O’Sullivan-Maillet, and Lasser (2010) studied the impact of an Internet-based versus in-person WWP in a nonrandomized clinical trial. All participants had in-person individual appointments with the study registered dietitian (RD) at baseline, 3 months, and 6 months. All participants experienced significant improvements in weight, waist circumference, percentage body fat, and Framingham risk percentage independent of group assignment 3 and 6 months after baseline. That study’s outcomes (Touger-Decker et al., 2010), along with the American Heart Association (AHA) policy statement (Carnethon et al., 2009), provided the basis and evidence to support the outcome measures and methods for the current study protocol.
Method >>
Aim and Objective The primary aim of this study was to determine changes in cardiometabolic risk factors after the immediate intervention phase among participants in a longitudinal WWP study who returned for their 12-week appointment. It was hypothesized that among the participants who returned for 12-week appointments, there will be a statistically significant improvement in weight and waist circumference compared with baseline measurements. Study Design, Setting, and Population This study used a pre–postintervention design in which participants served as their own controls. Participants were enrolled in four cohorts throughout the year (January, March, May, and July 2013) as a means to manage the timing of appointments, education
sessions, and follow-ups with the one RD clinician. The four cohorts enrolled in the WWP reported herein were participants from two of the University’s campuses, one urban and one suburban. The university’s institutional review board approved this study. Eligible participants were employees who were overweight or obese based on BMI ≥25 or waist circumference reflective of abdominal obesity (men ≥40 inches [102 cm]; women ≥35 inches [88 cm]). Women who were pregnant, breastfeeding, or within 3 months postpartum were excluded. There was no cost to the participants and no monetary incentive to participate. Intervention Description Email information blasts were sent to announce the commencement of the WWP; prospective participants attended a recruitment session at which time the study protocol was explained and they were screened for eligibility. All participants were scheduled for individual appointments with the RD at baseline and after the 12-week intervention phase for measurement and calculation of cardiometabolic risk factors including height, weight, percentage body fat, waist circumference, 2-hour postprandial glucose, total cholesterol, HDL (high-density lipoprotein) cholesterol, and BP; completion of health histories; the International Physical Activity Questionnaire (IPAQ; The IPAQ Group; https://sites.google.com/site/theipaq/home) and the CDC’s health-related quality of life tool (CDC, 2000); and individualized diet and lifestyle counseling. Appointments with the RD were scheduled around participants’ workplace commitments; they received telephone and e-mail reminders before appointments. At each one-on-one appointment, the RD completed two 24-hour diet recalls and provided individualized diet and physical activity counseling to help participants achieve their weight goal and improve diet quality consistent with the AHA/American College of Cardiology, the Physical Activity and Dietary Guidelines for Americans, and the Dietary Approaches to Stop Hypertension (Appel et al., 2006; Eckel et al., 2013; U.S. Department of Health & Human Services, 2008, 2010a). Energy needs for weight loss were based on a range 20– to 25–kcal/kg current body weight. Following the baseline appointment and counseling, participants had access to 12 weeks of educational materials on the University’s distance learning platform (MOODLE) and through on-site live sessions conducted by the RD; the content was the same in the live and online sessions. Weekly education included topics on the nutrition facts food label, regular physical activity, healthy food shopping, and eating out. Participants had continued
access to the RD for questions via e-mail, phone, and a private blog. One-on-one follow-up appointments were planned 12 weeks after baseline; however, given this WWP was offered at the workplace, scheduling had to accommodate participants’ work demands and time off. Hence, this article reports on participants who completed their 12-week appointments within 10 to 14 weeks after the baseline appointment. Participant Characteristics and Outcome Measurements Demographic characteristics and past medical history were self-reported by participants at the baseline appointment. All measurements were taken by the study RD; participants were asked to remove their shoes and outdoor clothing and to empty their pockets. Height was measured to the nearest 0.5 inch using a portable stadiometer (Charder Electronic Co., Ltd., Taichung City, Taiwan); body weight, body composition, and BMI were measured using a bioelectrical impedance analyzer (Tanita BC-418, Tanita Worldwide, Arlington Heights, IL); and waist circumference was measured to the nearest 0.5 cm using a cloth tape against a light shirt at the midpoint between the highest point on the iliac crest and the lowest point of the costal margin in the mid-axillary line (National Heart Lung and Blood Institute, 2001). After the participant was sitting for at least 10 minutes, BP was measured using the automated Omron BP710 monitor (Omron Healthcare Inc, Bannockburn, IL) with a wide-range cuff so that it fits both standard and large arms (9-17 inches in circumference); the BP measurement was repeated before the conclusion of the appointment, and the mean of the two readings was recorded. Hypertension was defined in two ways: as having been told that they had hypertension by a physician previously (Nwankwo et al., 2013) and as surveillance hypertension (Crim et al., 2012), which refers to hypertension in individuals who are currently using antihypertensive medications, or have an average systolic BP (SBP) of 140 mmHg or above, or a diastolic BP (DBP) of 90 mmHg or above based on up to three measures on one occasion. A Cholestech LDX Analyzer (Hayward, CA) was used to measure blood glucose, total cholesterol, and HDL cholesterol in a 35-microliter drop of blood obtained by fingerstick; participants were advised to fast for at least 2 hours prior to their appointments in order to improve the accuracy of the measurements. The CDC health-related quality of life questionnaire is validated for use in free-living adult populations and includes four core measures
Radler et al. / IMPROVED RISK FACTORS IN OVERWEIGHT AND OBESE WORKSITE PARTICIPANTS 3
identifying self-rated health (CDC, 2000). The IPAQ short form is a self-administered tool to assess physical activity in adults. The Framingham 10-year CVD risk percentage was calculated in SPSS Version 21.0 according to the sex-specific multivariable risk factor algorithm developed by D’Agostino et al. (2008). Power Estimation and Statistical Analysis A sample size calculation was conducted to insure the study sample was sufficient to detect differences in clinical measurements between the baseline and 12-week appointments. For a difference of 3 pounds between weight at baseline and 12-week using a matched pair t test, 53 subjects were required to obtain power of 0.95 with an a priori alpha of .05. This study was adequately powered with 79 subjects. IBM SPSS Version 21 (Armonk, NY) was used for data analyses. Descriptive statistics were calculated for the sample at baseline. Comparisons of cardiometabolic factors at the baseline and 12-week appointments were conducted using matched pair t tests. Differences between completers and noncompleters at baseline were assessed using chi-square tests and independent samples t tests. Pearson product moment correlations were used to determine the relationships between weight change and other cardiometabolic factors. McNemar’s test was used to assess change in surveillance hypertension status from baseline to 12 weeks. Bivariate changes in cardiometabolic factors were analyzed for the total sample of completers as well as separately for those who lost weight or had no weight gain.
Results >>
Participant Demographic Characteristics The sample (N = 79) included those participants who attended both a baseline and 12-week appointment (completers), between January and October 2013. Of the 147 who had baseline appointments, 79 completed 12-week appointments (10-14 weeks) representing a 54% retention rate. When differences between completers and noncompleters were assessed, there were significantly more (p = .037) noncompleters from the urban cohorts (n = 46) than from the suburban cohorts (n = 22). However, there was no significant difference in mean baseline BMI between completers and noncompleters. The participants had a mean age of 49.9 years (95% confidence interval [CI; 47.5, 52.3]); they were mostly female (87.3%, n = 69) and held staff positions (94.9%, n = 75; Table 1).
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Table 1 Demographic Characteristics of the Study Sample (N = 79) Characteristic
n (%)
Gender Female 69 (87.3) Male 10 (12.7) Race/ethnicity White (non-Hispanic) 32 (40.5) Black (non-Hispanic) 27 (34.2) Hispanic 9 (11.4) Asian 5 (6.3) Other 6 (7.6) Campus Newark 40 (50.6) Piscataway 39 (49.4) Position at university Staff 75 (94.9) Faculty 4 (5.1) Self-reported medical history at baseline appointment Cardiovascular disease 0 (0) Prediabetes 3 (3.8) Diabetes 7 (8.9) Dyslipidemia 14 (17.7)
Changes in Cardiometabolic Risk, Framingham Risk Percentage, BMI, and Hypertension Status Data regarding cardiometabolic risk factors and Framingham 10-year CVD risk percentage at baseline and 12-week appointments with change proportions and statistics are described in Table 2. Paired samples t test were used to detect statistically significant changes in weight, BMI, waist circumference, percentage body fat, BP (both SBP and DBP), and glucose from baseline to 12 weeks. The change in the Framingham 10-year CVD risk percentage was not statistically significant; however, its downward trend is a positive finding. The mean percentage change in body weight was a decrease of 1.72% (SE = 0.37; range = −12.61% to +4.77%). Two thirds (n = 54, 68.4%) of participants lost weight (Table 3). The strong positive correlation between weight change and waist circumference change for the total sample (r = .571, p < .001) and for those who lost weight (r = .587, p < .001) indicates that with greater weight loss, waist circumference decreased concurrently. Correlations between changes in weight and
Table 2 Clinical Biometric Screening Markers at the Baseline and 12-weeka Follow-Up Appointment 12-Week Follow-Upa
Baseline Characteristic
N
M
SE
N
M
SE
pb
Change
Weight (lb) BMI Waist circumference (cm) Body fat (%) Blood pressure Systolic (mmHg) Diastolic (mmHg) Total cholesterol (mg/dL) HDL (mg/dL) Glucose (mg/dL) Framingham 10-year CVD Risk (%)
79 79 77 78
200.68 34.75 103.40 41.51
4.78 0.69 1.68 0.73
79 79 77 78
197.04 33.90 100.98 40.90
4.63 0.70 1.70 0.78
