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Volume
6: No. 4, October 2009
ORIGINAL RESEARCH
Promoting Dietary Change Among State Health Employees in Arkansas Through a Worksite Wellness Program:
The Healthy Employee Lifestyle Program (HELP)
Amanda Philyaw Perez, MPH; Martha M. Phillips, PhD, MPH, MBA; Carol E. Cornell, PhD; Glen Mays, PhD, MPH; Becky Adams, MPH
Suggested citation for this article: Philyaw Perez A, Phillips MM, Cornell CE, Mays G, Adams B. Promoting dietary change among state health employees in Arkansas through a worksite wellness program: the Healthy Employee Lifestyle Program (HELP). Prev Chronic Dis 2009;6(4):A123.
http://www.cdc.gov/pcd/issues/2009/
oct/08_0136.htm. Accessed [date].
PEER REVIEWED
Abstract
Introduction
Maintaining a healthy and productive workforce is essential for employers in
public and private sectors. Poor nutrition and obesity contribute to chronic
diseases and influence health care costs and productivity. Research indicates
that eating a healthy diet is associated with lower body mass index and reduced
risk for developing chronic disease.
Methods
The Arkansas Department of Health implemented the Healthy Employee Lifestyle
Program to encourage wellness among state health employees. During the pilot
year, participants completed a health risk assessment at baseline and again
after 1 year that assessed diet and physical activity, other health risk
factors, and readiness to make behavioral changes. Participants were encouraged
to eat healthfully, participate in regular exercise, report health behaviors
using a Web-based reporting system, accumulate points for healthy behaviors, and
redeem points for incentives. Differences in participants’ (n = 214) reported
dietary behaviors between baseline and follow-up were assessed using χ2
analyses and tests of symmetry.
Results
Consumption of sweets/desserts, fats, protein, grains, processed meats, and
dairy did not differ significantly from baseline to follow-up. However, at
follow-up more participants reported eating 3 or more fruits and vegetables
per day than at baseline and being in the action and maintenance stages of
readiness to change for eating 5 or more fruits and vegetables per day and for
eating a diet low in fat.
Conclusion
Further study is needed to examine physical activity and other health risk
factors to determine whether the program merits a broader dissemination.
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Introduction
Among US adults, only one-third eat enough fruits and a little over
one-quarter eat enough vegetables per day to meet nutritional
recommendations set in the Healthy People 2010 national objectives (1),
and two-thirds are overweight or obese (2). Poor nutrition and obesity
contribute to chronic diseases that result in billions of dollars in medical costs
and lost work productivity per year (3-5). Forty-five percent of working-aged
Americans have chronic diseases, including hypertension, diabetes, heart
disease, stroke, and high cholesterol (6), that are affected by poor nutrition
(3) and obesity (7,8). Some research suggests that fruit and vegetable intake is
associated with having a lower body mass index (BMI) (9,10) and with reducing
the risk for developing chronic disease (10-12). Research suggests that merely
increasing the consumption of fruits and vegetables may help with weight
management, and increased consumption of high-fiber, energy-poor fruits and
vegetables often leads to a spontaneous reduction in fat intake (13). These
assumptions about the health and weight management benefits of fruit and
vegetable consumption need further investigation.
For decades, state-based programs have promoted public health messages about
healthful eating. In recent years, state governments have
recognized that their own state workers are as likely as the general public to
have poor health habits that are associated with deleterious health outcomes and
that directly influence state health care budgets (14). Studies on worksite
wellness programs have shown that fruit and vegetable consumption increases when
management and peers provide support, create environments that offer healthy
choices, and reward participants with incentives (15-17). Consequently, many
states have implemented worksite wellness initiatives to improve nutrition,
promote physical activity, and reduce obesity among state workers (14,17).
Although states may develop wellness initiatives for state workers, few
publish the findings regarding the implementation or evaluation of such
programs. Among those few, the North Carolina HeartSmart study showed
increased fruit and vegetable consumption among state employees after 1 year of
program participation (17). The public workforce size makes program
implementation difficult, but states such as North Carolina have initiated
approaches (eg, using the Internet) for delivering wellness interventions to
reach large numbers of employees (17). Computer or Web-based programs for
nutrition promotion make it easier to provide education, monitor dietary intake,
and track participant success in a cost-effective way (18). Such programs may
provide feasible, affordable solutions to improve employee health in both public
and private sectors and thereby reduce the effect of obesity and unhealthy
dietary habits on employee health and health care costs.
The Healthy Employee Lifestyle Program (HELP) uses Web-based technology and
site-specific program tailoring aimed at decreasing risk for chronic diseases
and reducing health care costs among state employees in Arkansas. The
Arkansas Department of Health (ADH) developed the HELP intervention and launched
a 1-year pilot study in February of 2005. We report the analysis of the
nutritional components of the 1-year pilot to assess the effectiveness of the
intervention in promoting dietary changes among participants, including shifts
in stages of readiness to change dietary practices.
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Methods
Overview of the Healthy Employee Lifestyle Program
The HELP intervention targeted 10,000 state health and human services
employees from 200 county-based offices and 2 central offices in Little Rock,
Arkansas. An ADH work team developed HELP in collaboration with the Centers for
Disease Control and Prevention (CDC), using resources provided in the Guide
to Community Preventive Services (Community Guide) and incorporating
findings from formative research with state employees to assess need and
interest in program participation.
The primary goals of HELP were to encourage behavior change in participants,
including 1) not smoking or participating in a smoking cessation program, 2)
eating 5 or more fruits and vegetables per day, 3) engaging in regular physical
activity, 4) achieving or maintaining a healthy BMI (<25.0 kg/m2) or
participating in a program to reduce BMI, and 5) seeking age-appropriate annual
health screenings. Secondary goals targeted behavior change using stages of
readiness from the Transtheoretical Model of Behavior Change (19).
All employees in the ADH and Department of Human Services
(DHS) were encouraged to participate in HELP and informed about the program via
e-mails, newsletters, posters, and other internal communications. Participants
enrolled in the program by creating an account through a Web-based system
available on the ADH and DHS intranet and by completing a
health risk assessment (HRA). The Trale HRA (20) evaluates
employee health status, BMI, dietary habits, participation in physical activity,
smoking status, stress level, alcohol consumption, and other health risk
factors. After completing the HRA, employees received an overall wellness
report, including scores that described the person’s current state of
health, risk factors for diseases and health conditions, and tips to improve
health. HELP participants were required to complete an HRA at baseline to be
able to enroll in the program and were encouraged to complete follow-up HRAs at
approximately 1-year intervals thereafter to assess progress toward personal
health goals. This study evaluated the first year of participation and 1
follow-up HRA. In this article, employees who signed up for participation but
only completed an initial HRA are referred to as enrollees. Employees who also
completed a follow-up HRA are referred to as participants.
Coordinators at the state, regional, and site levels implemented the program
by providing coordinator trainings, managing the HELP intervention Web-based
system, and distributing materials and information to other coordinators and
program participants. Program coordinators periodically transmitted educational
information regarding healthful eating, physical activity, state and agency
health events, lunch-and-learn sessions, and other health promotion activities.
Enrollees and participants reported their progress through the Web-based
system and earned points for self-reported fruit and vegetable consumption,
physical activity, smoking cessation, completion of age-appropriate health
screenings, weight management, and completion of HRAs. People could post
activity in these areas daily, weekly, or monthly. The online system maintained
for each enrollee a rolling tally of reward points earned by participants.
People could redeem earned points for rewards such as t-shirts, water
bottles, and up to 3 days of paid leave. We examined data from the pilot year of
the HELP intervention using a cross-sectional cohort design to compare HRA
responses to nutritional questions at baseline and approximately 1 year later.
Study design and participants
A pre-post design with no control group was used because no control group was
available for comparison and HRAs were not completed by employees who did not
participate in the program. To ensure anonymity, as promised by the program
contractors (Trale, Inc, Daleville, Indiana), participant identifiers were not assigned or included
in the HRA database. Therefore, HRAs could not be matched to people across time
with absolute certainty. Analysis files for the comparison of baseline and
follow-up HRAs were created by identifying those dates of birth with more than 1
HRA in the file and with at least 1 HRA completed between February 2005 and
March 2006. HRAs were then matched by birth date, age, sex, and height to
identify HRAs that were likely completed by the same people. HRAs
completed within 8 months of or more than 16 months after the index HRA were
excluded from the analysis sets. These strategies generated 2 files (1 for
baseline HRAs and 1 for follow-up HRAs), each of which included 214
observations. The University of Arkansas for Medical Sciences institutional
review board reviewed and approved this study.
Study measures
The HRA assessed intake frequency of fat, sweets/desserts, fruits,
vegetables, protein, grains, dairy, processed meats, and fried foods by using
categorical response options (never, 1-4 times/wk, 5-7 times/wk, 2 times/d, ≥3
times/d) for each category. Stage of readiness to change (ie, precontemplation,
contemplation, preparation, action, maintenance) (19) was assessed for eating a
low-fat diet, taking daily steps to achieve or maintain a healthy weight, and
eating 5 or more fruits and vegetables daily. Response options for these 3
questions were categorical: “not doing this and have no plans to start” (precontemplation),
“plans to do this within the next 6 months” (contemplation), “plans to do this
within the next 30 days” (preparation), “started doing this within the last 6
months” (action), and “have been doing this for at least 6 months or more”
(maintenance). Because of the small sample size, the stages of
readiness to change were collapsed into 3 categorical variables of precontemplation/contemplation, preparation, and action/maintenance.
Statistical analysis
Data were analyzed using SAS version 9.1 (SAS Institute, Inc, Cary,
North Carolina). Univariate analyses were completed to describe program
enrollees at baseline. A pre-post analysis of HRA responses for the matched
sample was completed using the Bowker test of symmetry and the McNemar χ2
test. The null hypothesis was no difference in distribution of responses in the
baseline and follow-up groups (α = .05).
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Results
Of the 10,000 ADH and DHS employees, 10% (n = 1,017) enrolled in HELP during the first year, February 2005 to March 2006. Most enrollees and participants were female and white (Table 1). Mean BMI of enrollees and participants was 30 kg/m2, and approximately 75% of HELP enrollees and participants were either overweight or obese.
At follow-up, more participants ate 3 or more servings of vegetables per day
than they did at baseline (26.2% vs 13.6%, P = .03)
(Table 2). The data showed an overall trend of increased fruit consumption between baseline and follow-up. There was a shift in consumption of 3 or more fruits per day from 10.8% at baseline to 17.3% at follow-up (P = .08). Participants’ consumption of the more healthful food groups of
proteins, grains, and dairy did not increase significantly between baseline and follow-up. No significant differences toward decreased consumption of sweets/desserts, fats, fried foods, and processed meats were observed.
Participants progressed between baseline and follow-up in stages of readiness to change for eating 5 or more fruits and vegetables per day (P = .002) and for eating a low-fat diet (P = .04) (Table 3). For eating 5 or more fruits and vegetables per day, 42% of participants were in the preparation stage and 41% were in the action or maintenance stages. At follow-up, the percentage of participants in the preparation stage fell to 27% while the percentage in the action
or maintenance stage increased to 59% (P = .002). Similarly, for eating a diet low in fat, 29% of participants were in the preparation stage and 49% were in the action or maintenance stage at baseline; at follow-up, the percentage of participants in the preparation stage fell to 21% and the percentage in the action or maintenance stage increased to 59% (P = .04).
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Discussion
Our findings from the 1-year pilot of the HELP program suggest that a Web-based worksite wellness incentive program may improve nutritional health behaviors of public-sector employees. The HELP program encourages behavior change through 3 main approaches: 1) providing an overall wellness report with tips for improving health, 2) rewarding health behaviors with points redeemable for incentives, and 3) providing education and peer support. These pilot results are promising, given the small sample of 214 participants. A larger sample would have been helpful in detecting more modest changes in behavior.
Fruit and vegetable consumption was the only dietary behavior rewarded by the
HELP intervention. Other desirable behaviors (eg, decreasing consumption of fats or sweets) were not directly rewarded
by the program. This reward system may have contributed to the lack of significant change in other dietary behaviors. Further investigation is necessary to determine how best to achieve change in the broader range of dietary behaviors.
Our findings are consistent with other wellness interventions that reported increased fruit and vegetable consumption and decreased fat consumption among program participants (16,17). For example, both the Seattle and Treatwell 5-A-Day worksite wellness studies reported increased fruit and vegetable consumption among participants (21,22).
Similarly, the Worksite Internet Nutrition program reported decreased fat consumption and increased fruit and vegetable consumption among participants by using
applied nutritional behavior change principles through an e-mailed intervention (23).
The changes observed among HELP participants may not be solely due to program participation. During the period of pilot implementation, Arkansas
reformed state policies and organizational structures responsible for health programs in Arkansas, and media outlets heralded the state’s multiple efforts to improve health by promoting nutrition and physical activity. Longer-term longitudinal studies are needed to determine the HELP program’s effectiveness.
A limitation of this study was the inability to match precisely the baseline and follow-up HRAs for participants. Although the cross-sectional samples were matched closely, the interpretation of findings of change over time would have been strengthened by a true longitudinal sample. This study is limited further by the nature of the data, which were self-reported. The influence of this limitation may be mitigated somewhat by the failure of the program to reward change over time; therefore,
there was little or no incentive for participants to skew their responses on the follow-up HRA in any single direction. Having 1 year between baseline and follow-up HRAs may have minimized the self-report bias because participants were not likely to remember previous responses. Further, to the extent that people in the matched samples were different from people for whom no match was possible, our ability to generalize these findings to program participants overall is limited. People who
remained in the program and were motivated to complete a follow-up HRA could have been systematically different from those who failed to do so, further limiting the generalizability of these findings.
People with a high BMI tend to use health services more often, which lowers their work productivity because of absence and contributes to higher insurance premiums for employers (4,5,24,25). Most (75%) HELP enrollees reported BMIs in the overweight or obese ranges, suggesting that HELP was able to reach and recruit the desired, higher-risk employees. Our data do not include information on health care use or days missed from work, both of which would be indicators of program
effectiveness.
The HELP pilot program produced positive outcomes in a brief period. Results suggest that the HELP intervention can be a feasible, affordable, easily implemented health behavior intervention that shows some promise for improving dietary behaviors of working adults. Findings suggest that, in time, risk, morbidity, and mortality may decrease if participants continue to increase healthy behaviors and decrease less healthy behaviors (5). Increased fruit and vegetable consumption is an
easily communicated health message that shows promise for decreasing risk for chronic disease (17,21,22). Further analysis of the HELP data for physical activity and other health risk factors will be examined to determine whether the program merits a broader dissemination.
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Acknowledgments
This project was funded by CDC application no. U58/CCU622813 through the ADH.
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Author Information
Corresponding Author: Amanda Philyaw Perez, MPH, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, 4301 W Markham St, No. 863, Little Rock, AR 72205. Telephone: 501-686-6802. E-mail:
PhilyawAmandaG@uams.edu.
Author Affiliations: Martha M. Phillips, Carol E. Cornell, Glen Mays, University of Arkansas for Medical Sciences, Little Rock, Arkansas; Becky Adams, Arkansas Department of Health, Little Rock, Arkansas.
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