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Participant characteristics associated with greater reductions in waist circumference during a four-month, pedometer-based, workplace health program

  • Rosanne LA Freak-Poli1Email author,
  • Rory Wolfe1,
  • Helen Walls1,
  • Kathryn Backholer1 and
  • Anna Peeters1
BMC Public Health201111:824

DOI: 10.1186/1471-2458-11-824

Received: 16 February 2011

Accepted: 25 October 2011

Published: 25 October 2011

Abstract

Background

Workplace health programs have demonstrated improvements in a number of risk factors for chronic disease. However, there has been little investigation of participant characteristics that may be associated with change in risk factors during such programs. The aim of this paper is to identify participant characteristics associated with improved waist circumference (WC) following participation in a four-month, pedometer-based, physical activity, workplace health program.

Methods

762 adults employed in primarily sedentary occupations and voluntarily enrolled in a four-month workplace program aimed at increasing physical activity were recruited from ten Australian worksites in 2008. Seventy-nine percent returned at the end of the health program. Data included demographic, behavioural, anthropometric and biomedical measurements. WC change (before versus after) was assessed by multivariable linear and logistic regression analyses. Seven groupings of potential associated variables from baseline were sequentially added to build progressively larger regression models.

Results

Greater improvement in WC during the program was associated with having completed tertiary education, consuming two or less standard alcoholic beverages in one occasion in the twelve months prior to baseline, undertaking less baseline weekend sitting time and lower baseline total cholesterol. A greater WC at baseline was strongly associated with a greater improvement in WC. A sub-analysis in participants with a 'high-risk' baseline WC revealed that younger age, enrolling for reasons other than appearance, undertaking less weekend sitting time at baseline, eating two or more pieces of fruit per day at baseline, higher baseline physical functioning and lower baseline body mass index were associated with greater odds of moving to 'low risk' WC at the end of the program.

Conclusions

While employees with 'high-risk' WC at baseline experienced the greatest improvements in WC, the other variables associated with greater WC improvement were generally indicators of better baseline health. These results indicate that employees who started with better health, potentially due to lifestyle or recent behavioural changes, were more likely to respond positively to the program. Future health program initiators should think innovatively to encourage all enrolees along the health spectrum to achieve a successful outcome.

Keywords

waist circumference workplace association prevention risk-factor cardiovascular disease diabetes health promotion physical activity pedometer

Background

Workplace health programs have demonstrated improvements in the leading global risk factors for chronic disease [1, 2] which has led to their increasing role in chronic disease prevention [1, 2]. The majority of research has focused upon evaluating the program outcomes [1, 37] and program characteristics [25, 7, 8] which have increased the evidence-base for workplace health programs. However, there has been little evaluation of participant characteristics and process indicators that may be related to subsequent change in risk factors during such programs.

Identifying variables associated with a successful outcome in health promotion programs can help to determine the health program's reach and its effectiveness at enrolling a variety of participants, including employees with high health risks. The assessment of variables associated with the program can also be used to identify any inequities in the health program through identification of differences in outcome according to characteristics such as education status. Consequently, variables associated with program success can potentially be used to improve the reach and success of a health program, and this can be achieved by addressing any inequities in the targeting of enrolees or response to the program.

A number of workplace health program evaluations have demonstrated immediate improvements in physical activity, blood pressure and anthropometric measures [9]. As a direct intermediary between physical activity and disease [1013], waist circumference (WC) can be considered a useful marker of the success of such programs. Only one workplace health program evaluation which considered participant characteristics associated with successful outcomes has been identified [14]. To adequately evaluate variables associated with success in workplace health programs, a comprehensive evaluation needs to be undertaken in a large workplace health program with a range of potential association variables including demographic, behavioural, anthropometric, biomedical and process measures, that can be (where appropriate) assessed in accordance to clinically relevant guidelines. We recently performed an evaluation of a four-month, pedometer-based, workplace health program, with a range of measures at baseline. A pre-post analysis of this program found that WC decreased on average by 1.6 cm [9, 15].

The aim of this paper is to identify participant characteristics that are associated with greater improvements in waist circumference (WC) following participation in a four-month, pedometer-based, workplace health program.

Methods

Study population

Melbourne workplaces undertaking the 2008 Global Corporate Challenge® (GCC®) event were approached to be evaluation sites. Following receipt of the Workplace Consent, employees enrolled in the 2008 GCC® event were approached via email. In early 2008, 762 eligible participants were recruited from ten workplaces, providing a variety of sedentary occupations [9, 15]. Seventy-nine percent (n = 604) of participants returned directly after the health program for the four-month data collection [9]. Participants who returned for four-month data collection were less likely to report having diabetes and more likely to be older, participate in the GCC® due to health reasons, be a non-smoker and comply with the health program by undertaking 10,000 daily steps on average [9]. Eighty-eight percent (n = 671) of the total sample at baseline completed the WC measurement. Eighty percent (n = 539) of these participants returned to complete the WC measurement at four-months (89% of the total sample who returned at four-months) [9].

Description of the program

The GCC® is the provider of a pedometer-based workplace program that is established world-wide and occurs annually. The program involves wearing a visible step-count pedometer with a target of at least 10,000 steps per day for 125 days. Weekly encouragement emails are sent and a website is used for logging daily steps, accessing additional health information, communication amongst participants and comparing team progress. Participation requires an employer or employee financial contribution and is typically competitive.

Data collection

Table 1

Guideline recommendation summary table [15]

Guideline recommendation

Not meeting recommended guideline

BEHAVIOURAL

 

Physical activitya [2931]

<150mins moderate intensity activity per week

Fruit Intake [29, 31, 32]

<2 serves per day

Vegetable Intake [29, 31, 32]

<4 serves per day

Tobacco

≥1 tobacco cigarette(s) per day

ANTHROPOMETRIC

 

Blood pressure [31, 33]

 

Systolic

≥ 140 mmHg

Diastolic

≥ 90 mmHg

Body Mass Index (BMI) [31, 3436]

≥25 kg/m2

BIOMEDIAL

 

Fasting Glucose [31, 3436]

≥ 7.0 mmol/L

Cholesterol (total) [37]

≥ 5.5 mmol/L

Triglycerides [38]

≥1.5 mmol/L

RISK MODELS

 

Diabetes type 2 5-year risk (assessed by The Australian Type 2 Diabetes Risk Assessment Tool - AUSDRISK) [31, 39, 40]

intermediate 1/100-1/20; high ≥1/20

Cardiovascular disease (CVD) 10-year risk (assessed by the Absolute cardiovascular disease risk assessment tool) [31, 4143]

intermediate 1/100-1/5; high ≥1/5

aPhysical activity was preferably accrued over at least five sessions per week, with vigorous activity given double weighting

Data were collected directly prior to the GCC® 2008 event (baseline) and immediately after completion of the GCC® 2008 event (four-month follow-up). In brief, trained staff visited employees' workplaces for scheduled morning appointments to collect fasting anthropometric and biomedical measurements. Before measurements, participants were asked to remove outer garments, belts and workplace ID tags from around their waists. To record WC, participants were asked to point out their lower rib margin and the top of the hip (iliac crest) and the measurement was taken midway. Waist was recorded using a Figure Finder Tape Measure (Novel Products Inc 2005 code PE024) and a mirror to ensure that the tape was horizontal. An Internet-based self-report questionnaire was completed by participants at their own convenience. The questionnaire incorporated demographic information [1618], motivation and support for participation, a health history [16] and behavioural measures [16, 18, 19]. Meeting alcohol guidelines was defined as consuming two or fewer standard drinks on one occasion in the last twelve months [20]. Other national measurement guidelines for risk assessment are summarised in Table 1, including diabetes type 2 and cardiovascular disease predicted risk scores [9, 15].

Step information

Step information was obtained by the GCC® through participation in the program. Participants were asked to enter their step-counts, as indicated on the pedometer, daily into the website diary. Bicycle ride length was also recorded on a daily basis and incorporated into the step-count by the GCC® (6.4 km = 10,000 steps).

Further methodological details of the GCC® Evaluation Study have been described elsewhere [9, 15].

Outcome

WC has been shown to be a better predictor of metabolic risk than body mass index, due to the independent association between an increased WC with health [1013] and mortality [10, 2125]. Reduction in WC can be achieved through lifestyle changes and is an achievable goal for workplace health program initiatives. Recently it was identified that completion of this four-month, pedometer-based, workplace health program was associated with improvements in WC of 1.6 cm on average [9]. WC change for each participant was calculated by subtracting their baseline measurement from their four-month follow-up measurement.

Variable selection

All measured variables at baseline, i.e. participant characteristics present prior to commencing the program, were considered potential "predictors" of WC change in the sense that the characteristics pre-dated the program-related changes. The only exception was the process variable, indicating compliance with the program, as measured by step count. Where possible these variables were considered as having a linear continuous-scale relationship with WC change rather than using categorisations that may be arbitrary. Several variables were assessed in accordance to clinically relevant guidelines as summarised in Table 1[9, 15].

Analysis

All analyses were performed using Stata version 11 (Stata Corporation, TX). Robust standard errors, clustered by workplace, were used in all statistical analyses, including the calculation of confidence intervals. A p-value <0.05 was used to determine statistical significance.

Variables related to WC change were assessed by univariable and multivariable linear regression analyses with WC change as the outcome variable. This analysis was repeated in participants with high-risk WC, as defined in Table 1, at baseline that had also completed four-month data collection. Also in participants with high-risk WC at baseline, univariable and multivariable logistic regression analyses were fitted to high/low risk WC at follow-up.

To distinguish associated variables having an indirect influence on WC from participants exerting a more direct influence, two multiple regression approaches were taken. Potential association variables were formed into 10 separate and non-overlapping groups as follows.

1 Age (continuous), sex

2 Socio economic status by SEIFA, tertiary education, occupation and marital status

3 Prior GCC® Event participation and reasons for participation

4 Health behaviours

5 Psychosocial measures

6 Anthropometric measures

7 Biomedical measures

8 Predicted risk scores

9 Workplace characteristics

10 Step-data

In the first approach, the first two groups (baseline demographics) were used for adjustment in separate models containing one of the remaining 8 groups of variables (Multivariable Approach 1 in Tables 2, 3 and 4). In the second approach, these groups of variables were entered sequentially into the regression model, adjusting for the previous group as confounders (Multivariable Approach 2 in Tables 2, 3 and 4). Baseline WC was not included in the models in either approach due to its potential for introducing bias [26]. Consequently, as the diabetes type-2 predicted risk score included WC in the calculation, it was also excluded from the models. Instead, as described above, additional analyses were performed in a subset of participants identified as having high-risk baseline WC.

Glucose and triglyceride variables followed skewed distributions and were log-transformed before inclusion in regression models. Pregnant participants (n = 13) were excluded from analyses. Each analysis used participants with complete data on the relevant variable/s.

Ethics

The study, project number CF08/0271-2008000125, was approved by Monash University Human Research Ethics through the standing committee on ethics in research-involving humans.

Results

Distribution of waist circumference change

https://static-content.springer.com/image/art%3A10.1186%2F1471-2458-11-824/MediaObjects/12889_2011_Article_3709_Fig1_HTML.jpg
Figure 1

Distribution of waist circumference change associated with participation in a four-month workplace health program.

The change in waist circumference (WC) followed an approximately normal distribution with an average reduction of 1.6 cm (±5.9SD), Figure 1a. Males and females were similar in their mean WC reduction (-1.3 ± 5.5SD for males compared to -1.8 ± 6.2SD for females, p = 0.4), Figure 1b.

Predictors of waist circumference improvement

Table 2

Linear regression analyses assessing potential baseline and step-data predictors of waist circumference change

Group

Predictor Variable

n

Crude WC change

Univariate

Multivariable Approach 1a

Multivariable Approach 2b

    

WC change (cm)

P-value

WC change (cm)

P-value

WC change (cm)

P-value

 

DEMOGRAPHICS

        

1

Age (year)

539

-

-0.02

0.5

-0.02

0.5

-0.02

0.5

 

Sex

        
 

   Female

305

-1.78

reference

reference

reference

 

   Male

234

-1.33

0.45

0.4

0.48

0.4

0.48

0.4

2

Socio Economic Status (by SEIFA %)

      
 

   Most Advantaged

189

-1.46

reference

reference

reference

 

   Advantaged

224

-1.50

-0.04

0.9

-0.16

0.7

-0.16

0.7

 

   Disadvantaged

92

-1.83

-0.37

0.8

-0.49

0.6

-0.49

0.6

 

   Most Disadvantaged

33

-2.68

-1.21

0.5

-1.07

0.4

-1.07

0.4

 

Tertiary Education

        
 

   Not completed

115

-0.04

reference

reference

reference

 

   Completed

423

-2.04

-2.00

0.046

-2.13

0.016

-2.13

0.016

 

Occupation

        
 

   Professional

221

-1.61

reference

reference

reference

 

   Associate professional

97

-2.41

-0.80

0.09

-1.05

0.09

-1.05

0.09

 

   Manager

96

-1.71

-0.10

0.9

0.07

0.9

0.07

0.9

 

   Clerical or Service

76

-1.10

0.51

0.7

0.15

0.9

0.15

0.9

 

Marital Status

        
 

   Married/de facto

366

-1.38

reference

reference

reference

 

   Widowed/separated/divorced

46

-3.21

-1.84

0.07

-1.62

0.2

-1.62

0.2

 

   Never married

120

-1.85

-0.47

0.7

-0.46

0.6

-0.46

0.6

 

BASELINE MEASURES

        

3

   Prior GCC® Participationc

532

-1.62

0.08

0.9

0.09

0.8

0.09

0.8

 

Reasons for Participation c

        
 

Health

531

-1.94

-0.93

0.09

-0.71

0.3

-0.71

0.3

 

To look my best

531

-1.82

-0.45

0.1

-0.27

0.3

-0.27

0.3

 

Fitness

531

-1.75

-0.36

0.2

-0.09

0.7

-0.09

0.7

 

Colleagues

531

-1.72

-0.20

0.6

-0.24

0.7

-0.24

0.7

 

Friends or family

531

-2.14

-0.52

0.6

-0.92

0.4

-0.92

0.4

 

Behavioural Measures

        

4

Fruit Intake

        
 

   Not meeting guidelines

364

-1.21

reference

    
 

   Meeting guidelines

168

-2.58

-1.37

0.06

-1.04

0.09

-1.01

0.1

 

Vegetable Intake

        
 

   Not meeting guidelines

455

-1.49

reference

    
 

   Meeting guidelines

77

-2.56

-1.08

0.06

-0.38

0.6

-0.51

0.5

 

Takeaway Dinner

        
 

   Once or less per month

246

-1.68

reference

    
 

   About once a week

214

-1.63

0.05

0.9

-0.70

0.2

-0.62

0.3

 

   More than once a week

72

-1.56

0.12

0.9

-0.67

0.6

-0.61

0.6

 

Alcohol

        
 

   Not meeting guidelines

307

-1.42

reference

    
 

   Meeting guidelines

225

-1.95

-0.54

0.2

-0.58

0.035

-0.65

0.016

 

Tobacco

        
 

   Smoker

50

-1.00

reference

    
 

   Non-smoker

482

-1.71

-0.71

0.4

0.13

0.9

0.32

0.7

 

Physical Activity

        
 

   Not meeting guidelines

322

-1.49

reference

    
 

   Meeting guidelines

209

-1.87

-0.38

0.5

0.00

1.0

-0.10

0.9

 

Sitting Time (per hour per day)

        
 

   Weekday

530

-

0.19

0.015

0.09

0.048

0.10

0.06

 

   Weekend

529

-

0.12

0.026

0.28

0.018

0.28

0.025

 

Psychosocial Measures

        

5

   Physical Functioning (SF12)

523

-

-0.06

0.09

-0.05

0.08

-0.05

0.2

 

   Mental Functioning (SF12)

523

-

0.00

0.9

-0.02

0.6

-0.01

0.5

 

Anthropometric Measures d

      

6

Blood Pressure (mmHg)

        
 

   Systolic

517

-

-0.01

0.5

0.00

1.0

0.00

0.9

 

   Diastolic

517

-

0.03

0.2

-0.03

0.6

-0.03

0.5

 

   Not meeting guidelines

90

-1.72

reference

    
 

   Meeting guidelines

427

-1.51

0.20

0.6

    
 

Heart rate (Mean, SD)

517

-

-0.03

0.3

-0.02

0.5

-0.04

0.2

 

Weight (Mean, SD)e

537

-

-0.02

0.4

    
 

Body Mass Index

        
 

   Body Mass Index

222

-

-0.07

0.08

-0.08

0.08

-0.08

0.08

 

   Not meeting guidelines

315

-1.68

reference

    
 

   Meeting guidelines

222

-1.51

0.17

0.8

    
 

Waist circumferencef

        
 

   Waist circumference

539

-

-0.12

0.001

    
 

   Not meeting guidelines

288

-2.86

reference

    
 

   Meeting guidelines

251

-0.12

2.74

0.001

    
 

Biomedical Measures (fasting) d

      

7

Total Cholesterol

        
 

   Total Cholesterol

535

-

0.20

0.4

0.49

0.034

0.38

0.029

 

   Not meeting guidelines

150

-1.66

reference

    
 

   Meeting guidelines

385

-1.63

0.03

1.0

    
 

Glucose

        
 

   Glucose

535

-

0.12

0.3

0.06

0.2

0.02

0.09

 

   Not meeting guidelines

20

0.05

reference

    
 

   Meeting guidelines

535

1.49

4.23

0.3

    
 

Triglycerides

        
 

   Triglycerides

535

-

0.83

0.7

0.49

0.1

0.99

1.0

 

   Not meeting guidelines

109

0.10

reference

    
 

   Meeting guidelines

426

2.43

2.33

0.1

    
 

Predicted risk scores d

        

8

   Cardiovascular disease risk (next 10 years)

        
 

   CVD risk (continuous)

504

-

-0.03

0.6

-0.08

0.2

-0.11

0.4

 

   Low-risk

452

-1.61

reference

    
 

   Intermediate-risk

45

-1.76

-0.14

0.9

    
 

   High-risk

7

-2.91

-1.30

0.056

    
 

   Diabetes risk (next 5 years)f

        
 

   Diabetes risk (continuous)

529

-

-0.09

0.09

    
 

   Low-risk

202

-1.26

reference

    
 

   Intermediate-risk

276

-1.55

-0.28

0.6

    
 

   High-risk

51

-3.45

-2.19

0.004

    
 

WORKPLACE CHARACTERISTICS g

      

9

   Public ownership (vs. private)

539

-2.00

-0.67

0.4

-0.57

0.2

-0.37

0.5

 

   Outer city location (vs. inner city)

539

-2.22

-0.37

0.7

0.16

0.8

0.06

1.0

 

PROCESS MEASURES

        
 

Step data d

        

10

   Step average per day (per 10,000 steps)

538

-

-0.20

0.7

-0.25

0.8

0.12

0.9

 

   <10,000 steps average (per day)

179

-1.48

reference

     
 

   Meeting ≥10,000 steps average (per day)

359

-1.65

-0.17

0.7

    

a Associated risk-factor subgroups adjusted only for baseline demographic confounders

b Associated risk-factor subgroups adjusted for all potential predictors within the analysis step and above

c The reference group for this binary variable is 'no'. The reference group data is not shown.

d Continuous variables chosen over categorical variables

e Excluded due to the inclusion of body mass index (BMI)

f Excluded from model as baseline WC was not considered as a predictor.

g The reference group for this binary variable is shown in brackets. The reference group data is not shown.

Between baseline and four-months, variables associated with WC improvement identified through univariable analyses included having completed tertiary education and less weekend or weekday sitting time at baseline, Table 2. Participants who were not meeting guidelines for WC at baseline (as defined in Table 1) responded positively to the program and had a 2.9 cm larger reduction in WC than participants who were meeting guidelines for WC at baseline. For every extra centimetre of WC at baseline, a 0.12 cm loss in WC at four-months was observed. Similarly, participants with high baseline diabetes type-2 risk had a 2.2 cm larger reduction in WC than participants with low baseline diabetes type-2 risk.

Multivariable approaches 1 and 2 produced similar results, Table 2. Between baseline and four-months, participants who had completed tertiary education at baseline had a 2.1 cm larger reduction in WC than participants who had not completed tertiary education at baseline. On average, participants who reported at baseline that they did not consume more than two alcoholic standard drinks in one occasion in the past twelve months reduced their WC by 0.7 cm more than participants who did not meet alcohol recommended guidelines. For every hour less per day of baseline weekend sitting time, a 0.3 cm greater loss in WC at four-months was observed. For every millimole per litre less of total cholesterol at baseline, a 0.4 cm greater loss in WC at four-months was observed.

High-risk versus low-risk baseline waist circumference

Table 3

Comparison of baseline characteristics between high-risk and low-risk waist circumference at baselinea

 

Low-risk WC

(Mean ± SD or Percentage)

High-risk WC

(Mean ± SD or Percentage)

P-value

n

251

288

-

WORKPLACE CHARACTERISTICS b

Public ownership (vs. private)

32.7

43.1

<0.001

Inner city location (vs. outer city)

70.9

67.7

0.4

DEMOGRAPHICS

   

Age (year)

38 ± 10

43 ± 10

<0.001

Male

52.2

35.8

<0.001

Socio Economic Status (by SEIFA)

   

Most Advantaged

37.5

33.1

0.3

Advantaged

40.6

42.5

 

Disadvantaged

15.9

18.1

 

Most Disadvantaged

6.0

6.3

 

Completion of tertiary education

81.6

76.0

0.2

Occupation

   

Professional

50.7

40.2

0.022

Associate professional

19.2

20.3

 

Manager

17.9

21.1

 

Clerical or Service

12.2

18.4

 

Marital Status

   

Married or de facto

67.5

69.9

0.6

Widowed, separated or divorced

8.1

9.1

 

Never married

24.4

21.0

 

BASELINE MEASURES

   

Prior GCC® Participationc

21.54

24.83

0.06

Motivation for Participation c

Health

56.7

76.6

<0.001

To look my best

43.3

72.7

<0.001

Fitness

60.8

73.1

0.038

Colleagues

58.4

55.6

0.4

Friends or family

2.5

2.5

1.0

Behavioural Measures

   

Self reported hypertension

10.3

24.6

0.001

Self reported diabetes

2.1

8.4

0.001

Fruit Intake (meeting guidelines)

28.5

34.3

0.5

Vegetable Intake (meeting guidelines)

14.2

14.7

0.9

Takeaway Dinner

   

Once or less per month

46.3

46.2

0.9

About once a week

39.4

40.9

 

More than once a week

14.2

12.9

 

Alcohol (meeting guidelines)

39.8

44.4

0.1

Non tobacco smoker

92.7

88.8

0.2

Physical Activity (meeting guidelines)

41.2

37.8

0.018

Sitting Time (hrs per day)

   

Weekday

8.3 ± 3.6

8.2 ± 3.6

0.8

Weekend

5.7 ± 3.1

4.0 ± 2.6

0.001

Physical Measures

   

Systolic Blood Pressure (mmHg)

116.1 ± 14.0

120.9 ± 15.0

0.010

Diastolic Blood Pressure (mmHg)

77.2 ± 10.0

81.8 ± 10.1

0.001

Blood Pressure (meeting guidelines)

86.1

79.5

0.036

Heart rate (beats per minute)

67.3 ± 10.2

69.5 ± 9.3

0.007

Weight (kg)

68.7 ± 11.1

84.1 ± 15.4

<0.001

Body Mass Index (kg/m2)

23.6 ± 2.4

29.2 ± 4.5

<0.001

Body Mass Index (meeting guidelines)

69.1

17.4

<0.001

Waist circumference (cm)

79.4 ± 8.1

95.2 ± 10.2

<0.001

Waist circumference (meeting guidelines)

100.0

0.0

<0.001

Biomedical Measures (fasting)

   

Total Cholesterol (mmol/L)

4.8 ± 0.9

5.0 ± 1.0

0.1

Total Cholesterol (meeting guidelines)

75.6

68.8

0.025

Glucose (mmol/L)

4.9 ± 0.7

5.2 ± 1.1

0.004

Glucose (meeting guidelines)

99.2

93.7

0.025

Triglycerides (mmol/L)

1.0 ± 0.5

1.3 ± 1.0

0.003

Triglycerides (meeting guidelines)

85.6

74.4

<0.001

Predicted risk scores

   

Cardiovascular disease risk (next 10 years)

   

CVD risk

2.9 ± 4.2

5.5 ± 5.2

0.001

High-risk

0.00

2.62

0.002

Intermediate-risk

5.06

12.36

 

Diabetes risk (next 5 years)

   

Diabetes risk

5.5 ± 3.3

9.3 ± 5.1

<0.001

High-risk

2.5

15.8

<0.001

Intermediate-risk

42.2

60.7

 

PROCESS MEASURES

   

Step data

   

Steps average (per day)

11815 ± 3661

11491 ± 3690

0.5

Meeting 10,000 steps average (per day)

67.6

66.0

0.8

FOUR-MONTH MEASURES

   

Waist circumference (cm)

79.3 ± 8.8

92.3 ± 11.32

<0.001

Waist circumference (meeting guidelines)

91.2

22.9

<0.001

aIn participants who attended both baseline and four-month follow-up data collections.

b The reference group for this binary variable is shown in brackets. The reference group data is not shown.

c The reference group for this binary variable is 'no'. The reference group data is not shown

To investigate whether variables associated with WC change alter for participants most at risk, further analyses were undertaken in this sub-group. Fifty-three percent (n = 288) of participants were categorised as having a high-risk WC at baseline. Participants who had a high-risk WC at baseline were more likely to be older; be female; have a managerial, clerical or service occupation; work for a publically owned company; participate in the program due to health, fitness or appearance reasons; and have poorer health indicators when compared to baseline low-risk WC participants who returned at four-months, Table 3.

Predictors of continuous waist circumference improvement in participants with high-risk waist circumference at baseline

Table 4

Linear regression assessing baselinea variables associated with waist circumference change in participants not meeting WC guidelines

Group

Predictor Variable

n

Crude WC change

Univariate

Multivariable Approach 1a

Multivariable Approach 2b

    

WC change (cm)

P-value

WC change (cm)

P-value

WC change (cm)

P-value

 

DEMOGRAPHICS

        

1

Age (year)

288

-

0.03

0.4

0.03

0.4

0.03

0.4

 

Sex

        
 

   Female

185

-2.94

reference

reference

reference

 

   Male

103

-2.73

0.21

0.6

0.16

0.7

0.16

0.7

2

Socio Economic Status (by SEIFA %)

       
 

   Most Advantaged

95

-2.84

reference

reference

reference

 

   Advantaged

122

-2.61

0.23

0.8

0.32

0.6

0.32

0.6

 

   Disadvantaged

52

-2.82

0.02

1.0

0.31

0.9

0.31

0.9

 

   Most Disadvantaged

18

-5.78

-2.94

0.1

-2.11

0.3

-2.11

0.3

 

Tertiary Education

        
 

   Not completed

69

-1.08

reference

reference

reference

 

   Completed

219

-3.43

-2.35

0.018

-2.35

0.017

-2.35

0.017

 

Occupation

        
 

   Professional

105

-2.34

reference

reference

reference

 

   Associate professional

53

-4.13

-1.79

0.06

-1.89

0.1

-1.89

0.1

 

   Manager

55

-3.52

-1.18

0.08

-1.00

0.2

-1.00

0.2

 

   Clerical or Service

48

-2.84

-0.50

0.7

-1.06

0.4

-1.06

0.4

 

Marital Status

        
 

   Married/de facto

200

-2.45

reference

reference

reference

 

   Widowed/separated/divorced

26

-4.82

-2.37

0.2

-2.42

0.2

-2.42

0.2

 

   Never married

60

-3.48

-1.02

0.3

-0.36

0.6

-0.36

0.6

 

BASELINE MEASURES

        

3

   Prior GCC® Participationc

286

-2.86

0.08

0.8

-0.04

0.9

-0.04

0.9

 

Reasons for Participation c

        
 

Health

286

-2.82

0.27

0.8

0.14

0.9

0.14

0.9

 

To look my best

286

-2.80

0.32

0.5

0.32

0.6

0.32

0.6

 

Fitness

286

-2.75

0.49

0.4

0.07

0.9

0.07

0.9

 

Colleagues

286

-3.24

-0.81

0.053

-0.72

0.3

-0.72

0.3

 

Friends or family

286

-4.01

-1.15

0.2

-1.10

0.3

-1.10

0.3

 

Behavioural Measures

        

4

Fruit Intake

        
 

   Not meeting guidelines

188

-2.42

reference

    
 

   Meeting guidelines

98

-3.77

-1.34

0.027

-0.96

0.3

-0.96

0.3

 

Vegetable Intake

        
 

   Not meeting guidelines

244

-2.77

reference

    
 

   Meeting guidelines

42

-3.52

-0.75

0.4

0.40

0.8

0.32

0.8

 

Takeaway Dinner

        
 

   Once or less per month

132

-0.55

reference

    
 

   About once a week

117

-1.34

-0.79

0.2

-0.63

0.2

-0.52

0.2

 

   More than once a week

37

-3.11

-2.55

0.7

-0.85

0.7

-0.73

0.7

 

Alcohol

        
 

   Not meeting guidelines

159

-2.95

reference

    
 

   Meeting guidelines

127

-2.80

0.15

0.8

-0.28

0.6

-0.28

0.6

 

Tobacco

        
 

   Smoker

32

-1.30

reference

    
 

   Non-smoker

254

-3.03

-1.73

0.2

0.38

0.7

0.49

0.6

 

Physical Activity

        
 

   Not meeting guidelines

178

-2.45

reference

    
 

   Meeting guidelines

108

-3.60

-1.15

0.2

-0.92

0.3

-0.94

0.3

 

Sitting Time (per hour per day)

        
 

   Weekday

286

-

0.15

0.2

0.11

0.4

0.12

0.4

 

   Weekend

282

-

0.26

0.2

0.23

0.3

0.23

0.3

 

Psychosocial Measures

        

5

Physical Functioning (SF12)

282

-

-0.11

0.049

-0.09

0.02

-0.07

0.2

 

Mental Functioning (SF12)

282

-

0.00

1.0

-0.03

0.3

-0.02

0.5

 

Anthropometric Measures d

      

6

Blood Pressure (mmHg)

        
 

   Systolic

273

-

0.02

0.4

0.00

1.0

0.00

0.9

 

   Diastolic

273

-

0.02

0.6

-0.01

0.8

-0.02

0.6

 

   Not meeting guidelines

56

-2.21

reference

    
 

   Meeting guidelines

217

-3.03

-0.82

0.3

    
 

Heart rate (Mean, SD)

288

-

-0.02

0.6

-0.02

0.7

-0.02

0.7

 

Weight (Mean, SD)e

288

-

0.02

0.5

    
 

Body Mass Index

        
 

   Body Mass Index

288

-

0.13

0.2

0.12

0.3

0.08

0.5

 

   Not meeting guidelines

238

-2.49

reference

    
 

   Meeting guidelines

50

-4.63

-2.14

0.1

    
 

Waist circumferencef

        
 

   Waist circumference

288

-

-0.05

0.2

    
 

   Not meeting guidelines

288

n/a

    
 

   Meeting guidelines

0

       
 

Biomedical Measures (fasting) d

      

7

Total Cholesterol

        
 

   Total Cholesterol

285

-

0.47

0.2

0.79

0.051

0.86

0.014

 

   Not meeting guidelines

89

-2.71

reference

    
 

   Meeting guidelines

196

-2.94

-0.23

0.7

    
 

Glucose

        
 

   Glucose

285

-

2.29

0.8

0.22

0.6

0.03

0.3

 

   Not meeting guidelines

18

0.06

reference

    
 

   Meeting guidelines

267

1.07

1.02

1.0

    
 

Triglycerides

        
 

   Triglycerides

285

-

1.31

0.6

0.47

0.2

0.45

0.2

 

   Not meeting guidelines

73

0.03

reference

    
 

   Meeting guidelines

212

1.96

1.93

0.4

    
 

Predicted risk scores d

        

8

Cardiovascular disease risk (next 10 years)

      
 

   CVD risk (continuous)

267

-

0.09

0.2

0.03

0.7

0.02

0.9

 

   Low-risk

227

-2.89

reference

    
 

   Intermediate-risk

33

-2.79

0.09

0.9

    
 

   High-risk

7

-2.91

-0.03

1.0

    
 

Diabetes risk (next 5 years)f

      
 

   Diabetes risk (continuous)

285

-

0.06

0.3

    
 

   Low-risk

67

-3.79

reference

    
 

   Intermediate-risk

173

-2.34

1.45

0.033

    
 

   High-risk

45

-3.55

0.24

0.6

    
 

WORKPLACE CHARACTERISTICS g

      

9

Public ownership (vs. private)

288

-2.66

0.36

0.6

0.09

0.9

0.06

0.9

 

Outer city location (vs. inner city)

288

-3.08

-0.68

0.4

-0.96

0.3

-1.34

0.2

 

PROCESS MEASURES

        
 

Step data d

       

10

Step average per day (per 10,000 steps)

288

-

-1.04

0.08

-1.40

0.07

-0.55

0.6

 

   <10,000 steps average (per day)

190

-2.13

reference

    
 

   Meeting ≥10,000 steps average (per day)

190

-3.24

-1.11

0.049

    

a Associated risk-factor subgroups adjusted only for baseline demographic confounders

b Associated risk-factor subgroups adjusted for all potential predictors within the analysis Group and above

c The reference group for this binary variable is 'no'. The reference group data is not shown.

d Continuous variables chosen over categorical variables

e Excluded due to the inclusion of body mass index (BMI)

f Excluded from model as baseline WC was not considered as a predictor.

g The reference group for this binary variable is shown in brackets. The reference group data is not shown.

Note: For participants not meeting WC guidelines at baseline

Within the baseline high-risk WC group, variables associated with WC improvement identified through univariable analyses included having completed tertiary education, eating two or more serves of fruit per day, having greater physical functioning at baseline and meeting the goal of at least 10,000 steps per day on average during the health program, Table 4. Within the high WC risk baseline group, a weak association between baseline WC and improved WC was observed, however it was not statistically significant nor was it of the same magnitude of the observed association in all participants. An additional analysis within the high-risk WC group comparing the BMI in the obese group to the BMI in the normal group in regards to WC change indicated weak evidence of a relationship (2.8 cm greater loss in the normal weight group, p = 0.06). Participants with moderate baseline diabetes type-2 risk had a 1.4 cm larger reduction in WC when compared to participants with low baseline diabetes type-2 risk, however no relationship with high diabetes type-2 risk was identified.

In participants who had a high-risk WC at baseline, participants who had completed tertiary education at baseline had a 2.4 cm larger reduction in WC when compared to participants who had not completed tertiary education at baseline. For every millimole per litre less of total cholesterol at baseline, a 0.9 cm greater loss in WC at four-months was observed.

Predictors of improving waist circumference to meet low-risk guidelines at four-months

Table 5

Assessment of variables associated with improving waist circumference to meet recommended guidelines at follow-up

Group

Predictor Variable

n

% meeting WC guidelines at four-months

Univariate

Multivariable Approach 1a

Multivariable Approach 2b

    

OR

P-value

OR

P-value

OR

P-value

 

DEMOGRAPHICS

        

1

Age (year)

288

-

0.97

0.08

0.97

0.039

0.97

0.039

 

Sex

        
 

   Female

185

21.08

reference

reference

reference

 

   Male

103

26.21

1.33

0.4

1.43

0.3

1.43

0.3

2

Socio Economic Status (by SEIFA %)

       
 

   Most Advantaged

95

21.05

reference

reference

reference

 

   Advantaged

122

22.13

1.07

0.9

1.03

0.9

1.03

0.9

 

   Disadvantaged

52

26.92

1.38

0.6

1.39

0.5

1.39

0.5

 

   Most Disadvantaged

18

27.78

1.44

0.4

1.63

0.2

1.63

0.2

 

Tertiary Education

        
 

   Not completed

69

20.29

reference

reference

reference

 

   Completed

219

23.74

1.22

0.3

1.07

0.8

1.07

0.8

 

Occupation

        
 

   Professional

105

22.86

reference

reference

reference

 

   Associate professional

53

22.64

0.99

1.0

0.96

0.9

0.96

0.9

 

   Manager

55

23.64

1.04

0.9

1.04

0.9

1.04

0.9

 

   Clerical or Service

48

27.08

1.25

0.4

1.51

0.2

1.51

0.2

 

Marital Status

        
 

   Married/de facto

200

23

reference

reference

reference

 

   Widowed/separated/divorced

26

23.08

1.00

1.0

1.34

0.7

1.34

0.7

 

   Never married

60

23.33

1.02

1.0

0.71

0.4

0.71

0.4

 

BASELINE MEASURES

        

3

   Prior GCC® Participationc

286

22.54

0.96

0.9

0.88

0.6

1.13

0.6

 

Reasons for Participation c

        
 

Health

286

21.92

0.76

0.4

1.22

0.6

1.22

0.6

 

To look my best

286

19.23

0.48

<0.001

0.38

0.004

0.38

0.004

 

Fitness

286

20.57

0.61

0.2

0.93

0.9

0.93

0.9

 

Colleagues

286

23.9

1.11

0.7

0.89

0.7

0.89

0.7

 

Friends or family

286

14.29

0.55

0.6

0.69

0.8

0.69

0.8

 

Behavioural Measures

        

4

Fruit Intake

        
 

   Not meeting guidelines

188

19.15

reference

    
 

   Meeting guidelines

98

30.61

1.86

0.028

2.42

<0.001

3.05

0.001

 

Vegetable Intake

        
 

   Not meeting guidelines

244

23.36

reference

    
 

   Meeting guidelines

42

21.43

0.89

0.8

0.62

0.4

0.61

0.4

 

Takeaway Dinner

        
 

   Once or less per month

132

20.45

reference

    
 

   About once a week

117

24.79

1.28

0.4

1.35

0.4

1.31

0.5

 

   More than once a week

37

27.03

1.44

0.3

1.44

0.6

1.49

0.5

 

Alcohol

        
 

   Not meeting guidelines

159

24.53

reference

    
 

   Meeting guidelines

127

21.26

0.83

0.6

0.71

0.3

0.64

0.2

 

Tobacco

        
 

   Smoker

32

21.88

reference

    
 

   Non-smoker

254

23.23

1.08

0.8

0.71

0.5

0.61

0.4

 

Physical Activity

        
 

   Not meeting guidelines

178

20.79

reference

    
 

   Meeting guidelines

108

26.85

1.40

0.002

1.42

0.1

1.48

0.2

 

Sitting Time (hrs per day)

        
 

   Weekday

286

-

0.94

0.1

0.99

0.9

1.00

0.9

 

   Weekend

286

-

0.80

0.025

0.78

0.053

0.75

0.023

 

Psychosocial Measures

        

5

Physical Functioning (SF12)

282

-

1.07

<0.001

1.08

<0.001

1.06

0.004

 

Mental Functioning (SF12)

282

-

1.00

0.6

1.03

0.022

1.03

0.2

 

Physical Measures d

      

6

Blood Pressure (mmHg)

        
 

   Systolic

273

-

0.97

<0.001

0.99

0.8

1.01

0.7

 

   Diastolic

273

-

0.95

<0.001

0.96

0.4

0.93

0.2

 

   Not meeting guidelines

56

7.14

reference

    
 

   Meeting guidelines

217

26.73

4.74

<0.001

    
 

Heart rate (Mean, SD)

273

-

0.99

0.8

0.99

0.8

1.00

0.9

 

Weight (Mean, SD)e

288

-

0.94

<0.001

    
 

Body Mass Index

        
 

   Body Mass Index

288

-

0.64

<0.001

0.55

<0.001

0.51

<0.001

 

   Not meeting guidelines

238

15.13

reference

    
 

   Meeting guidelines

50

60

8.42

<0.001

    
 

Waist circumferencef

        
 

   Waist circumference

288

-

0.91

<0.001

    
 

Biomedical Measures (fasting) d

      

7

Total Cholesterol

        
 

   Total Cholesterol

285

-

0.60

0.001

0.66

0.018

0.63

0.1

 

   Not meeting guidelines

89

14.61

reference

    
 

Meeting guidelines

196

26.53

2.11

0.040

    
 

Glucose

        
 

   Glucose

285

-

1.40

0.5

2.60

1.0

3.00

1.0

 

   Not meeting guidelines

18

22.22

reference

    
 

   Meeting guidelines

267

22.85

1.04

1.0

    
 

Triglycerides

        
 

   Triglycerides

285

-

1.48

0.001

1.54

0.012

3.12

0.7

 

   Not meeting guidelines

73

16.44

reference

    
 

   Meeting guidelines

212

25

1.69

0.1

    
 

Predicted risk scores d

       

8

Cardiovascular disease risk (next 10 years)

      
 

   CVD risk (continuous)

267

-

0.93

0.1

0.89

0.1

1.26

0.2

 

   Low-risk

227

23.35

reference

    
 

   Intermediate-risk

33

12.12

0.45

0.2

    
 

   High-risk

7

42.86

2.46

0.4

    
 

Diabetes risk (next 5 years)f

      
 

   Diabetes risk (continuous)

285

-

0.88

0.031

    
 

   Low-risk

67

40.3

reference

    
 

   Intermediate-risk

173

19.08

0.35

<0.001

    
 

   High-risk

45

11.11

0.19

0.013

    
 

WORKPLACE CHARACTERISTICS g

      

9

Public ownership (vs. private)

288

21.77

0.89

0.6

1.30

0.4

1.31

0.6

 

Outer city location (vs. inner city)

288

22.58

0.97

0.9

1.12

0.8

1.21

0.8

 

PROCESS MEASURES

        
 

Step data d

        

10

Step average per day

288

-

1.00

0.2

1.00

0.2

1.00

0.3

 

   <10,000 steps average (per day)

98

19.39

reference

    
 

   Meeting ≥10,000 steps average (per day)

190

24.74

1.37

0.4

    

a Associated risk-factor subgroups adjusted only for baseline demographic confounders

b Associated risk-factor subgroups adjusted for all potential predictors within the analysis Group and above

c The reference group for this binary variable is 'no'. The reference group data is not shown.

d Continuous variables chosen over categorical variables

e Excluded due to the inclusion of body mass index (BMI)

f Excluded from model as baseline WC was not considered as a predictor.

g The reference group for this binary variable is shown in brackets. The reference group data is not shown.

Note: For participants not meeting WC guidelines at baseline

Between baseline and four-months, 22.9% of participants who had high-risk WC at baseline improved their WC enough to meet low-risk guidelines at four-months, Table 5. Through univariable analysis, new baseline variables associated with reducing WC to meet low-risk guidelines at four-months, included not participating in the program for appearance reasons, meeting fruit intake guidelines, meeting physical activity guidelines, less weekend sitting time, higher physical functioning, lower systolic and diastolic blood pressure, meeting guidelines for blood pressure, lower baseline weight, lower BMI, meeting BMI guidelines, smaller WC, lower total cholesterol, meeting total cholesterol guidelines, more elevated triglycerides and higher diabetes risk, Table 5.

Although all participants in this sub-analysis had high-risk WC at baseline, a few were meeting guidelines for body composition when assessed by BMI. Within the high-risk WC group at baseline, participants who were meeting guidelines for BMI at baseline responded positively to the program and had 8.4 increased odds of improving their WC to meeting guidelines at four-months than participants not meeting baseline BMI guidelines, p < 0.001. Participants with low baseline diabetes type-2 risk had 5.4 increased odds of improving their WC to meeting guidelines at four-months than participants who were at high baseline diabetes risk, p = 0.013.

Within the high-risk baseline WC group, for every year increase in age at baseline, it was 3% less likely that the participant would improve their WC to meet low-risk guidelines at four-months. Employees participating in the program for reasons other than appearance had 2.6 increased odds of improving their WC to meet guidelines than employees participating for other reasons. Participants eating two or more pieces of fruit per day at baseline were 3.1 times more likely to improve their WC to meet guidelines than participants eating less than two pieces per day. For every hour decrease of weekend sitting time at baseline, it was 33% more likely that the participant would improve their WC to meet guidelines at four-months. For every BMI unit decrease at baseline, it was twice as likely that the participant would improve their WC to meet guidelines at four-months.

Discussion

In this study analysing variables associated with waist circumference (WC) change following participation in a four-month, pedometer-based, workplace health program, employees with a high-risk WC at baseline experienced the greatest improvements in WC. Strong predictors of improved WC during the program for all employees and employees with high-risk baseline WC were having completed tertiary education, undertaking less baseline weekend sitting time and having lower total cholesterol at baseline. An additional predictor of improvement in WC for all employees was not consuming more than two standard alcoholic beverages in one occasion during the twelve months prior to baseline. Unique baseline predictors were identified for improving WC to meet guidelines at four-months and these included participating for reasons other than appearance, eating at least two serves of fruit per day, higher physical functioning and lower BMI.

Our finding that employees with a high-risk WC at baseline experienced the greatest improvements in WC confirms findings from a similar workplace health program evaluation [14]. However, the relationship between baseline WC and WC change seems to be contradictory to the relationships observed with the other predictors, which mainly indicated better health. The finding that employees with larger WC at baseline improved the most during the program may be because they had the greatest opportunity to improve. In addition, some unique variables associated with improved WC that indicated better health were restricted to the high-risk baseline WC group.

The finding that employees with better health benefited the most from the program may indicate that healthier employees may find it easier to make the small changes required for a visible outcome. Whilst others, who need to make a greater change, may need additional support or motivation that may not be available through a workplace health program alone. However, a horse-racing effect [26] may be also present and as we did not assess behavioural change status, employees who are defined as 'healthier' at baseline may actually have recently made positive changes and be on a pathway to reducing their health risks. Hence, the workplace health program could be supporting employees to continue making the healthier behavioural changes. An alternate theory is that the markers of better health may be indicators of better socio-economic status. However, when several socio-economic confounders were included in the model, only adequate fruit intake in the high-risk baseline WC sub-analysis became non-significant.

Regardless of the reasoning for the healthier employees responding better to the program, the result highlights a possible need for these programs to respond to the enrolees and encourage change based on their individual baseline characteristics. Program initiators may need to think innovatively about how to further promote change in employees with multiple baseline risk factors.

The strengths of this evaluation included the range and quality of measurements, the large sample size and the variety of sedentary occupations within the sample [15]. The main limitation is the lack of assessment and evaluation of program and workplace characteristics. We recommend that future health programs not only evaluate a wide range of participant predictors (behavioural, anthropological and biological), but also the program and workplace characteristics as predictors. Another limitation is that the potential selection bias associated with workplace recruitment, individual recruitment and participant retention [9, 15]. Workplaces electing evaluation may have been more motivated as they conscripted to the GCC®2008 early, study participants may have been more motivated and/or have better baseline health and returning study participants had healthier baseline measures [9, 15, 27, 28]. A healthier, more motivated cohort would be more likely to comply with the health program (overestimating the health benefits) but a greater proportion of a healthier cohort would already be meeting health guidelines at baseline (underestimating the general health benefits of participation due to ceiling effects) [9]. However, selection bias is unlikely to substantially affect the interrelationships between predictors and WC change. A potential limitation is not having an explicit measure of the potential regression to the mean effect for waist circumference. However, as waist circumference decreased over time in both the low and high baseline risk groups there was no evidence of the regression to the mean effect in this sample.

Conclusions

While employees with high-risk WC at baseline experienced the greatest improvements in WC, the other predictors of WC improvement were generally indicators of better health at baseline. These results indicate that employees who started with better health, potentially due to lifestyle or recent behavioural changes, were more likely to respond positively to the program. The results from this paper can be used to inform employees during recruitment for workplace physical activity programs that there are benefits for participants who are in the healthier spectrum, as well as employees who have a higher WC risk. However, we suggest that these programs may need to promote additional support and motivation for participants who are at greatest health risk. We encourage future health program initiators to think innovatively about how to encourage all enrolees along the health spectrum to achieve clinically relevant improvement.

Declarations

Authors’ Affiliations

(1)
1Department of Epidemiology & Preventive Medicine, Faculty of Medicine, Nursing & Health Sciences, School of Public Health and Preventive Medicine, Monash University, The Alfred Centre, Alfred Hospital

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© Freak-Poli et al; licensee BioMed Central Ltd. 2011

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