Early systemic sclerosis: marker autoantibodies and videocapillaroscopy patterns are each associated with distinct clinical, functional and cellular activation markers

Gabriele Valentini
Antonella Marcoccia
Giovanna Cuomo
Serena Vettori
Michele Iudici
Francesco Bondanini
Carlo Santoriello
Aldo Ciani
Domenico Cozzolino
Giovanni Maria De Matteis
Salvatore Cappabianca
Filiberto Vitelli
Alberto Spanò
Early systemic sclerosis: marker autoantibodies and videocapillaroscopy patterns are each associated with distinct clinical, functional and cellular activation markers
R E S E A R C H A R T I C L E Open Access
Introduction:Early systemic sclerosis (SSc) is characterized by Raynaud's phenomenon together with scleroderma marker autoantibodies and/or a scleroderma pattern at capillaroscopy and no other distinctive feature of SSc. Patients presenting with marker autoantibodies plus a capillaroscopic scleroderma pattern seem to evolve into definite SSc more frequently than patients with either feature. Whether early SSc patients with only marker autoantibodies or capillaroscopic positivity differ in any aspect at presentation is unclear. Methods: Seventy-one consecutive early SSc patients were investigated for preclinical cardiopulmonary alterations. Out of these, 44 patients and 25 controls affected by osteoarthritis or primary fibromyalgia syndrome were also investigated for serum markers of fibroblast (carboxyterminal propeptide of collagen I), endothelial (soluble E-selectin) and T-cell (soluble IL-2 receptor alpha) activation. Results: Thirty-two of the 71 patients (45.1%) had both a marker autoantibody and a capillaroscopic scleroderma pattern (subset 1), 16 patients (22.5%) had only a marker autoantibody (subset 2), and 23 patients (32.4%) had only a capillaroscopic scleroderma pattern (subset 3). Patients with marker autoantibodies (n = 48, 67.6%) had a higher prevalence of impaired diffusing lung capacity for carbon monoxide (P = 0.0217) and increased serum levels of carboxyterminal propeptide of collagen I (P = 0.0037), regardless of capillaroscopic alterations. Patients with a capillaroscopic scleroderma pattern (n = 55, 77.5%) had a higher prevalence of puffy fingers (P = 0.0001) and increased serum levels of soluble E-selectin (P = 0.0003) regardless of marker autoantibodies. Conclusion: These results suggest that the autoantibody and microvascular patterns in early SSc may each be related to different clinical-preclinical features and circulating activation markers at presentation. Longitudinal studies are warranted to investigate whether these subsets undergo a different disease course over time.

Introduction

Early systemic sclerosis (SSc) is a condition characterized by Raynaud's phenomenon (RP) associated with SSc marker autoantibodies (anti-Scl-70, anticentromere antibodies, anti-RNA polymerase III, anti-fibrillarin, anti-PmScl, and anti-Th/To) and/or nailfold videocapillaroscopy (NVC) findings typical of SSc (namely, megacapillaries and avascular areas -commonly referred to as an 'NVC scleroderma pattern'). By definition, patients with early SSc do not show any distinctive clinical manifestation of the disease (namely, sclerodactyly, digital ulcers/scars, two or more teleangectasias, clinically visible nailfold capillaries, cutaneous calcinosis, X-ray bibasilar lung fibrosis, X-ray esophageal dysmotility, electrocardiographic signs of myocardial fibrosis, or a serum creatinine increase suggestive of scleroderma renal crisis) except puffy fingers and/or arthritis [1][2][3][4].

Various attempts have been made to find a correct classification for these patients who do not meet the preliminary 1990 American College of Rheumatology (ACR) SSc criteria [5] in order to foster their inclusion in clinical trials. In fact, in 2001 LeRoy and Medsger proposed that RP patients with SSc marker autoantibodies or an NVC scleroderma pattern should be classified as being affected by limited SSc [1]. Seven years later, Koenig and colleagues validated the LeRoy and Medsger criteria in a large 20-year prospective study [2]. They found that, at the last follow-up, patients presenting with SSc marker autoantibodies and a scleroderma pattern at capillaroscopy (referred to as subset 1 in the present paper), with no other manifestation distinctive of the disease other than puffy fingers and/or arthritis, had developed definite SSc 60 times more frequently than patients presenting with only RP. Patients with either only SSc marker autoantibodies (subset 2) or a capillaroscopic scleroderma pattern (subset 3) had developed definite SSc five and eight times more frequently, respectively, than patients presenting with only RP. Koenig and colleagues therefore suggested that such cases be labeled collectively as early SSc.

Two years ago, we reported that 42% of thus defined early SSc patients admitted to our tertiary Rheumatology Unit had preclinical functional alterations of the esophagus, lung or heart [3]. Subsequently, we showed that a high percentage of early SSc patients develop definite SSc within 5 years of presentation and found that some circulating fibroblast, endothelial and T-cell activation markers could be used as predictors of disease evolution besides marker autoantibodies and NVC findings [4]. In their study, Koenig and colleagues did not systematically investigate visceral involvement and neither did they consider circulating activation markers [2]. In our previous papers we were unable to try any subsetting among our early SSc patients because of the low number of early SSc patients with only an NVC scleroderma pattern and negative for SSc marker autoantibodies admitted to our unit [3,4].

In the present study, we evaluated whether clinical, preclinical functional or cellular activation markers are related to distinct early SSc subsets at presentation by merging our early SSc cohort with that recruited at a secondary Angiology Unit, where a significant number of patients with early SSc were SSc marker antibodynegative and capillaroscopy-positive.

Materials and methods

Patients

Patients admitted for evaluation of RP from 1 November 2000 to 30 June 2012 to the outpatient clinic of the Rheumatology Unit of the Second University of Naples and from 1 January 2008 to 30 June 2012 to the outpatient clinic of the Angiology Unit of the Pertini Hospital in Rome who met the Koenig and colleagues criteria for early SSc (that is, RP with SSc marker autoantibodies and/or an NVC scleroderma pattern without any clinical manifestation of definite SSc) [2] were enrolled in the study after giving written informed consent.

The diagnosis of RP was confirmed if patients fulfilled LeRoy and Medsger's criteria [6]; that is, if a cold challenge induced bilateral, episodic biphasic or triphasic (pallor followed by dusky blueness and/or redness) color changes of fingers. According to standard clinical practice, and for the purpose of a correct disease classification, patients underwent a complete screening workplan.

Routine assessment

Each patient was investigated to identify any feature that precluded inclusion in the study. In detail, we looked for the following features: dysphagia, effort dyspnea, and findings consistent with previous scleroderma renal crisis at history; symmetrical skin sclerosis, digital ulcers/scars, two or more teleangectasias, clinically visible nailfold capillaries, cutaneous calcinosis, and recent-onset accelerated or malignant arterial hypertension at physical examination; bibasilar lung fibrosis at chest X-ray scan; esophageal dysmotility at barium esophageal X-ray scan; and blocks and/ or Q waves at electrocardiography. In addition, blood cell count, urinalysis, blood urea nitrogen, serum creatinine, alanine aminotransferase, aspartate aminotransferase, erythrosedimentation rate, serum protein electrophoresis with the evaluation of γ-globulin concentration, and serum C3 and C4 concentration were also evaluated.

Nailfold videocapillaroscopy assessment

NVC was carried out with an optical probe videocapillaroscope equipped with a ×200 magnification contact lens and connected to image analysis software (Videocap; DS MediGroup, Milan, Italy). The nailfold of the second, third, fourth and fifth fingers was examined bilaterally in each patient. Four consecutive fields extending over 1 mm in the middle of the nailfold were studied per finger. All images of patients from both centers were stored and reviewed by a physician (MI) experienced in NVC [3,4,7]. The degree of capillary enlargement (on a scale of 0 to 3) and capillary loss (graded A to D) were investigated. Megacapillaries (capillary enlargement ≥2) and/or avascular areas (capillary loss grade ≥C) were considered a scleroderma pattern [8,9]. Moreover, since NVC active and late patterns, which are characterized by a lower capillary density, have been found to be associated with more severe disease in SSc patients [10], we also subdivided patients according to the mean capillary number per millimeter; that is, >9/mm, 9 to 7/mm, 6 to 4/mm, and ≤3/mm.

Autoantibody profile assessment

An autoantibody screening and profiling of sera collected at the first visit was performed. Antinuclear antibodies and anticentromere antibodies were searched for by a conventional indirect immunofluorescence assay on HEp2 cells, using fluorescent human γ-globulins as detection antibodies and a serum dilution of 1:160 as the cutoff value (Astra srl, Pavone Canavese, Italy). Anti-double-stranded DNA antibodies were also searched for by indirect immunofluorescence on Crithidia Luciliae, using fluorescent human γ-globulins as detection antibodies and a serum dilution of 1:40 as the cutoff value (Astra srl). Anti-Scl-70, anti-PmScl, anti-SSA, anti-SSB, anti-Sm, anti-Jo1, and anti-U1RNP antibodies were identified by commercially available ELISA kits (Chematil srl, Angri, Italy), using 25 U/ml as the cutoff value. Anti-RNA polymerase III and anti-fibrillarin antibodies were identified by EliA Varelisa test (Phadia, Freiburg, Germany), using 150 U/ml as the cutoff value. Anti Th/To were identified by western blotting (reagents by Arnika srl, Milano, Italy). To avoid a differential verification bias, sera were blindly exchanged between the two centers and only confirmed results were considered. Each result was confirmed.

Assessment of preclinical internal organ involvement

Patients from both centers underwent B-mode echocardiography and lung function study. Echocardiographic examination was performed as reported elsewhere [11]. The detection of diastolic abnormalities at B-mode echocardiography, indicated by an inverted ratio between early/ (atrial) late ventricular filling velocity (E/A ratio <1), in the absence of arterial hypertension, coronary artery disease and other symptoms/signs of cardiac disease, was regarded as early scleroderma heart involvement [12]. The detection of a diffusing lung capacity for carbon monoxide (DLCO) or a forced vital capacity <80% of the predicted values in the absence of a smoking habit and/or obstructive lung disease at lung function study was regarded as SSc lung involvement [13,14]. Moreover, after further informed consent, patients from the Rheumatology Unit with a reduced DLCO underwent high-resolution computed tomography of the chest [15].

Fibroblast, endothelial and T-cell activation markers

Early SSc patients for whom a baseline serum specimen was available and 25 controls, matched for sex and age and affected by osteoarthritis or primary fibromyalgia syndrome, were investigated at the Rheumatology Unit laboratory for the fibroblast, endothelial and T-cell activation markers carboxyterminal telopeptide of type I collagen (ICTP), soluble E-selectin (sE-selectin) and soluble IL-2 receptor alpha (sIL-2Rα), as described previously [4]. Briefly, sIL-2Rα and sE-selectin concentrations were measured by a multiplex suspension immunoassay (expressed as pg/ml), based on the use of spectrally encoded beads, each coupled with a capture antibody specific to the analyte of interest, as the solid support and a biotinylated detection antibody-streptavidine-phycoerythrin complex as the reporter system (all reagents were from Merk Millipore, Billerica, MA, USA) to be read by a double laser-based fluorimetric instrument (Luminex 200; Luminex Corporation, Austin, TX, USA). The ICTP concentrations were measured by a conventional competitive radioimmune assay (expressed as µg/l) (UniQ kits; Orion Diagnostica, Espoo, Finland). We did not measure the aminoterminal propeptide of type III collagen serum concentration because in our previous study it did not differ between early SSc and either undifferentiated connective tissue disease patients or controls at baseline [4].

Based on the autoantibody and capillaroscopic profiles, early SSc patients were divided into three subsets: subset 1, patients with both SSc marker autoantibody positivity and an NVC scleroderma pattern; subset 2, patients with only SSc marker autoantibody positivity; and subset 3, patients with only an NVC scleroderma pattern.

The study was reviewed and approved by the Azienda Ospedaliera Universitaria Seconda Università degli Studi di Napoli Ethics Committee and by the ASL RM/B Ethics Committee.

Statistical analysis

GraphPad Prism software version 6.0 (GraphPad Software Inc., San Diego, CA, USA) was used for statistical analysis. Continuous data were expressed as the mean ± standard deviation and the median with range, and were compared by the unpaired Student's t test or Mann-Whitney U test as appropriate when two groups were analyzed, and by one-way analysis of variance or Kruskal-Wallis test as appropriate when three or more groups were compared. Categorical data were analyzed by Fisher's exact test and the chi-square test when two or three groups, respectively, were considered.

Results

Forty-five patients were enrolled at the Rheumatology Unit of the Second University of Naples and 26 patients at the Angiology Unit of the Pertini Hospital in Rome. Table 1 presents the main epidemiologic, laboratory and capillaroscopic features of the patients enrolled by the Rheumatology and Angiology Units. There was no difference between the two series in terms of age, sex and time interval elapsed from the onset of RP. However, the prevalence of subset 1 patients was significantly higher (26/45 (57.8%) vs. 6/26 (23.1%), P = 0.0098) and the prevalence of subset 3 patients significantly lower (3/45 (6.7%) vs. 20/26 (76.9%), P = 0.0001) in the Rheumatology series. Subset 2 patients were recruited only by the Rheumatology Unit.

By definition, no patient presented any clinical feature of SSc other than puffy fingers or arthritis. The prevalence of puffy fingers was significantly higher in both subset 1 and subset 3 Angiology Unit patients than in the respective Rheumatology Unit patients (6/6 vs. 4/26, P = 0.004 for subset 1; 19/20 vs. 1/3, P = 0.04 for subset 3). The prevalence of arthritis did not differ statistically between the two centers (1/26 (3.85%) for Rheumatology Unit patients vs. 2/6 (33.3%) for Angiology Unit patients, P >0.05 for subset 1; 0/3 (0%) for Rheumatology Unit patients vs. 2/20 (10%) for Angiology Unit patients, P >0.05 for subset 3). Because of the low number of subset 3 patients recruited at the Rheumatology Unit and of subset 1 patients admitted to the Angiology Unit, in order to increase the power of the analysis we merged the two series. Figure 1 shows the prevalence of puffy fingers ( Figure 1A) and arthritis ( Figure 1B) in the three subsets. The prevalence of puffy fingers was significantly higher in subset 3 patients (20/23, 87%) from the pooled series than in subset 1 (10/32, 31.3%) and subset 2 (2/16, 12.5%) patients (P = 0.0001) ( Figure 1A). Thirty out of the 32 (93.75%) patients across the three subsets with puffy fingers had a positive NVC, and 25/39 (64.1%) patients without puffy fingers had a positive NVC (P = 0.0037) ( Figure 1C).

The prevalence of functional abnormalities did not differ between each subset of patients from the two centers. A forced vital capacity <80% of the predicted value and an inverted E/A ratio were found only in 2/32 (6.25%) and 1/32 (3.13%) subset 1 patients, respectively, and in no subset 2 and subset 3 patients. However, an impaired DLCO was more prevalent in subset 1 (11/32, 34.4%) and subset 2 (6/16, 37.5%) patients than in subset 3 (2/23, 8.7%) patients (P = 0.057) (Figure 2A). In addition, out of the 48 marker autoantibody-positive patients (that is, subset 1 + subset 2), DLCO <80% of the predicted value was detected in 17 (35.4%) versus 2/23 (8.7%) marker autoantibody-negative subset 3 patients (P = 0.0217) ( Figure 2B). Lastly, 6/14 (42.9%) patients with SSc marker autoantibodies other than anticentromere antibodies (three anti-Scl-70; three anti-RNA polymerase III) had a reduced DLCO as compared with 11/34 (34.4%) anticentromere antibody-positive patients. The difference did not reach statistical significance ( Figure 2C).

A ground glass opacity involving <5% of inferior lobes and an interlobular septal thickening were found in two patients and two different patients, respectively, by lung high-resolution computed tomography.    Figure 3 shows serum levels of the investigated activation markers in the three early SSc subsets and in controls. Two main findings emerged from this analysis. Firstly, serum concentrations of ICTP were significantly higher in patients with SSc marker autoantibodies (median = 4.025 µg/l in subset 1 + subset 2, range 1.883 to 10.53 µg/l) than in subset 3 patients (median = 2.51 µg/l, range 1.55 to 6.972 µg/l; P = 0.0108) ( Figure 3A). In detail, 4/15 (26.7%) subset 1 patients and 3/ 9 (33.3%) subset 2 patients had ICTP levels that exceeded the 95th percentile (5.05 µg/l) of the values measured in controls with respect to 2/17 (11.8%) subset 3 patients. Secondly, levels of sE-selectin were significantly higher in patients with an NVC scleroderma pattern (median = 1.031 pg/ml in subset 1 + subset 3, range 0.425 to 7.51 pg/ ml) than in subset 2 patients with only SSc marker autoantibodies (median = 0.67 pg/ml, range 0.486 to 1.203 pg/ml; P = 0.033) ( Figure 3B). In detail, sE-selectin levels exceeded the 95th percentile of the values recorded in controls (1.709 pg/ml), in 11/17 (64.7%) subset 3 patients, in 2/15 (13.3%) subset 1 patients and in 0/9 subset 2 patients (P = 0.0003). Noteworthy, we found that among all three subsets sE-selectin levels were significantly higher in patients with puffy fingers than in those without puffy fingers (2.013 pg/ml, range 0.55 to 7.51 vs. 0.725 pg/ml, range 0.425 to 1.203 pg/ml; P < 0.0001) ( Figure 3C). Finally, sIL-2Rα levels were lower in SSc marker autoantibody-negative   Figure 3D). sIL-2Rα levels were lower than the 5th percentile of control values (25.7 pg/ml) in 11/17 (64.7%) subset 3 patients but not in any subset 1 or subset 2 patient (P = 0.0001). The mean capillary number was >9/mm in 41 patients, 9 to 7/mm in 24 patients and 6 to 4/mm in six patients. No statistical difference was found among these three subgroups in the prevalence of each clinical, preclinical functional and laboratory abnormality investigated (data not shown). Finally, none of the investigated clinical (puffy fingers, arthritis), preclinical (DLCO/forced vital capacity reduction, E/A ratio inversion), or serological (SSc marker autoantibodies, ICTP, sE-selectin, sIL-2Rα) parameters was associated with the disease duration, as evaluated by RP onset.

Discussion

To our knowledge, this is the first study to systematically explore clinical and preclinical organ involvement and circulating activation markers in early SSc patients subdivided into three subsets, depending on the presence of both marker autoantibodies and NVC scleroderma pattern or either of these features.

Firstly, we found that our early SSc patients, which were enrolled by two distinct clinical units, were similar in sex and age distribution and disease duration, but differed in terms of clinical features and serum levels of fibroblast, endothelial, and T-cell activation markers at presentation. Given the different target patients of the two units, it is not surprising that a higher prevalence of SSc marker autoantibody-positive patients was enrolled by the Rheumatology Unit whereas a higher prevalence of RP patients presenting with puffy fingers was enrolled by the Angiology Unit. These differences are in line with results reported in patients with definite SSc by Walker and colleagues, who analyzed data entered into the European League Against Rheumatism (EULAR) Scleroderma Trials and Research database and found that differences among patients from various centers depend mainly on the clinical attitude of the respective medical team [16]. Notwithstanding this possible center-related recruitment bias, in our study early SSc patients with marker autoantibodies had a higher prevalence of impaired DLCO and higher circulating levels of ICTP irrespective of an NVC scleroderma pattern (megacapillaries and/or avascular areas). Similarly, early SSc patients with an NVC scleroderma pattern had a higher prevalence of puffy fingers and higher circulating levels of E-selectin irrespective of circulating marker autoantibodies, the two features being closely related each other. These associations have never previously been searched for. Moreover, four out of the 14 Rheumatology Unit patients with DLCO <80% of the predicted value already presented mild alterations of lung anatomy as detected by high-resolution computed tomography.

In this context, it is noteworthy that an impaired DLCO is considered the first alteration in SSc interstitial ICTP μg/L sE-selectin pg/ml sIL-2R pg/ml sE-selectin pg/ml *p < 0.05 **p < 0.005 ***p < 0.0005 lung disease [14,17]. Increased ICTP levels have been reported in SSc patients [18] and suspected SSc patients (that is, patients not meeting the preliminary 1990 ACR criteria for SSc) [4]. Moreover, elevated ICTP levels have been found to correlate with modified Rodnan skin score and to be associated with a diffuse disease and a reduced pulmonary function [19]. Given these observations, it is conceivable that early SSc patients with SSc marker autoantibodies are at higher risk of developing fibrotic organ complications.

Puffy fingers and RP are considered the main clinical features of the undifferentiated connective tissue syndrome [20]. sE-selectin, which reflects endothelial activation, has been reported to be increased in patients with definite SSc [21]. Our study demonstrates that puffy fingers are detectable in early SSc patients, mainly in those with an NVC scleroderma pattern and increased sEselectin levels. Serum IL-2Rα levels, which reflect the activation of the adaptive immune response through T-cell recruitment, have been found to be strongly associated with mortality and inversely correlated to disease duration in SSc patients with diffuse disease [22]. Intriguingly, we found that sIL-2Rα levels were strikingly lower in early SSc patients who were marker autoantibodynegative. This result could indicate a lack of T-cell recruitment in the peripheral blood of autoantibodynegative early SSc patients.

Taken together, the results of our study seem to suggest that the major cellular pathways involved in the pathogenesis of SSc, as evaluated by serum concentration of relevant activation markers, differ among early patients at presentation, in relation to autoantibody and microvascular status. Nevertheless, the asynchronous appearance of autoantibody positivity and capillaroscopic alterations has been reported in two recent papers. First, Englert and colleagues described the case of one patient in whom anti-Scl-70 positivity, associated with fatigue, weight loss and puffy fingers, predated the appearance of RP and the development of capillaroscopic abnormalities [23]. Second, Moinzadeh and colleagues reported the late appearance of serum autoantibodies in three patients with an NVC scleroderma pattern at admission [24]. Whether SSc marker autoantibody positivity or the presence of an NVC scleroderma pattern really do identify the dominating activation of a given cellular pathway at the disease onset in early SSc patients can only be determined by investigating circulating and tissue markers of cell activation contemporaneously.

Our study has some limitations. First, it might be affected by a differential verification bias because the patients were examined by clinicians with different medical expertise. To reduce this possible bias, however, capillaroscopic images and sera were made anonymous and centralized to the Rheumatology Unit. Capillaroscopic images were blindly evaluated by one investigator experienced in NVC (MI); sera were blindly analyzed in duplicate by one investigator experienced in immunoassays (SV). Moreover, the clinical (puffy fingers) and preclinical (DLCO and E/A ratio) parameters used to assess both series of patients are well defined and routinely applied in clinical practice. Second, given the small number of patients, our conclusions may be susceptible to be changed by future studies on large number of patients, such as the ongoing Very Early Diagnosis of Systemic Sclerosis (VEDOSS) project [25,26]. In addition, one must underline that using the new ACR/ EULAR classification criteria presented at the ACR 2012 meeting [27,28], a number of our early SSc patients could already meet the criteria for SSc at presentation. Indeed, in a post-hoc analysis 10/71 (14.1%) patients met the new EULAR/ACR classification criteria for SSc and belonged to subset 1 (that is, patients with both SSc marker autoantibodies and capillaroscopic abnormalities). These patients met the new criteria because of the presence of puffy fingers along with SSc marker autoantibodies and the NVC scleroderma pattern. However, our major findings -that is, early SSc patients with SSc marker autoantibody have higher ICTP levels, regardless of the NVC pattern; and early SSc patients with an NVC scleroderma pattern have a higher prevalence of puffy fingers and higher circulating levels of E-selectin, regardless the autoantibody profile, the two features being closely related each other -did not differ significantly when we excluded these 10 patients from the analysis (see Additional files 1, 2, 3 and 4).

In conclusion, we found that early SSc patients show distinct clinical and preclinical features, and distinct circulating markers of cellular activation at presentation, according to their autoantibody and capillaroscopic status. Longitudinal large studies are required to verify whether the pathophysiological (cellular activation markers), functional (DLCO) and clinical (puffy fingers) differences in early SSc subsets that we detected in a small yet well characterized cohort really do translate into the development of different disease patterns over time.

Additional material

Additional file 1: Table S1 presenting epidemiologic, laboratory and capillaroscopic features in patients who did not meet EULAR/ACR classification criteria, and figure legends for Figures S1, S2, and S3.

Additional file 2: Figure S1 showing the prevalence of puffy fingers, arthritis and NVC scleroderma pattern in patients who did not meet EULAR/ACR classification criteria.

Additional file 3: Figure S2 showing the prevalence of DCLO impairment and autoantibody positivity in patients who did not meet EULAR/ACR classification criteria.

Additional file 4: Figure S3 showing serum levels of ICTP, sEselectin, sIL2Raa and sE-selectin in patients who did not meet EULAR/ACR classification criteria.

All data expressed as median (range) or number (percentage). ACA, anticentromere antibody; NVC, nailfold videocapillaroscopy; RP, Raynaud's phenomenon.

Figure 1
1Prevalence of puffy fingers, arthritis, and nailfold videocapillaroscopy scleroderma pattern in early systemic sclerosis patients. Prevalence of (A) puffy fingers and (B) arthritis in the 71 early systemic sclerosis (SSc) patients from both centers, divided into three subsets according to the SSc marker autoantibody status and the nailfold videocapillaroscopy (NVC) pattern: presence of both SSc marker autoantibodies and NVC scleroderma pattern (subset 1), presence of SSc marker autoantibodies only (subset 2), and presence of NVC scleroderma pattern only (subset 3). (C) Prevalence of NVC scleroderma pattern in all patients from both centers divided according to the presence/absence of puffy fingers. Chi-square test was applied for statistical analysis of data reported in (A) and (B); Fisher's exact test was applied for statistical analysis of data reported in (C).

Figure 2
2Prevalence of diffusing lung capacity for carbon monoxide impairment and systemic sclerosis marker autoantibody positivity. (A) Prevalence of diffusing lung capacity for carbon monoxide (DLCO) impairment (<80% of the predicted value) in the 71 early systemic sclerosis (SSc) patients from both centers, divided into three subsets according to the SSc marker autoantibody status and the nailfold videocapillaroscopy (NVC) pattern: presence of both SSc marker autoantibodies and NVC scleroderma pattern (subset 1), presence of SSc marker autoantibodies only (subset 2), and presence of NVC scleroderma pattern only (subset 3). (B) Prevalence of general SSc marker autoantibody positivity and (C) prevalence of either anticentromere antibody (ACA) or other SSc marker autoantibody positivity in all patients from both centers divided according to the presence/absence of DLCO impairment. Chi-square test was applied for statistical analysis of data reported in (A). Fisher's exact test was applied for statistical analyses of data reported in (B) and (C). Abs, autoantibodies.

Figure 3
3Serum levels of fibroblast, endothelial, and T-cell activation markers. Serum levels of (A) fibroblast (carboxyterminal telopeptide of type I collagen (ICTP)), (B) endothelial (soluble E-selectin (sE-selectin)), and (D) T-cell (soluble IL-2 receptor alpha (sIL2Rαa)) activation markers in 25 controls affected by ostheoarthritis or fibromyalgia, and 44 early systemic sclerosis (SSc) patients, divided into three subsets according to the SSc marker autoantibody status and the nailfold videocapillaroscopy (NVC) pattern: presence of both SSc marker autoantibodies and NVC scleroderma pattern (subset 1), presence of SSc marker autoantibodies only (subset 2), and presence of NVC scleroderma pattern only (subset 3). (C) Serum levels of sE-selectin in all patients from both centers divided according to the presence/absence of puffy fingers. Kruskal-Wallis test and Mann-Whitney U test were applied for statistical analysis of data reported in (A), (B), and (D). Mann-Whitney U test was applied for statistical analysis of data reported in (C).

Table 1
1Epidemiologic, laboratory and capillaroscopic features of the two early systemic sclerosis seriesFeature
Rheumatology Unit (n = 45)
Angiology Unit (n = 26)
P value

Sex (female/male ratio)
43/2
22/4
NS

Age (years)
41 (17-73)
37.5 (16-71)
NS

RP duration (years)
3 (0.5-24)
3 (1-20)
NS

Subset 1: antibody-positive, NVC-positive
26 (57.8)
6 (2.2)
0.0098

Anti-Scl-70 antibody-positive
5 (19.2)
0

ACA-positive
19 (73.1)
3 (50)
Anti-RNA polymerase III antibody-positive
2 (7.7)
3 (50)

Megacapillaries only
21 (80.8)
3 (50)

Avascular areas ± megacapillaries
5 (19.2)
3 (50)

9%) patients from the Rheumatology Unit and for 22/26 (84.6%) patients from the Angiology Unit. The clinical, serological and NVC features of the 22 Rheumatology Unit patients reflected the characteristics of the whole series of the center (data not shown).Valentini et al. Arthritis Research & Therapy 2013, 15:R63
http://arthritis-research.com/content/15/3/R63
Sera collected at admission were available for 22/45
(48.

Valentini et al. Arthritis Research & Therapy 2013, 15:R63 http://arthritis-research.com/content/15/3/R63
AcknowledgementsThe study was supported by the Italian Foundation for Arthritis Research.Competing interestsThe authors declare that they have no competing interests.Authors' contributions GV conceived, designed and coordinated the study, and drafted and critically revised the manuscript. AM acquired clinical data, performed nailfold videocapillaroscopy and participated in the design of the study. GC acquired clinical data, performed the statistical analysis, and participated in the design of the study and in drafting the manuscript. SV performed all immunoassays, the statistical analysis, and the post-hoc analysis, and drafted and critically revised the manuscript. MI performed nailfold videocapillaroscopy and participated in the acquisition of data. FB performed autoantibody testing and routine biochemical analysis. CS and AC performed and analyzed lung function tests. DC and GMDM performed and analyzed B-mode echocardiography. SC and FV performed and analyzed chest X-ray scans. AS participated in the design of the study and critically revised the manuscript. All authors read and approved the final manuscript.Submit your next manuscript to BioMed Central and take full advantage of:
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Early systemic sclerosis: marker autoantibodies and videocapillaroscopy patterns are each associated with distinct clinical, functional and cellular activation markers. Valentini, Arthritis Research & Therapy. 1563Cite this article asCite this article as: Valentini et al.: Early systemic sclerosis: marker autoantibodies and videocapillaroscopy patterns are each associated with distinct clinical, functional and cellular activation markers. Arthritis Research & Therapy 2013 15:R63.


Office-Based Physical Activity and Nutrition

Krysten Blackford
PhDJonine Jancey
PhD, MSc;; Peter Howat
Melissa Ledger
PhD, MMathAndy H Lee
Office-Based Physical Activity and Nutrition
10.5888/pcd10.130029Volume 10 -September 12, 2013 OR I GI N A L R ES E A R CH Suggested citation for this article: Blackford K, Jancey J, Howat P, Ledger M, Lee AH. Office-Based Physical Activity and Nutrition Intervention: Barriers, Enablers, and Preferred Strategies for Workplace Obesity Prevention, Perth, Western Australia, 2012. Prev Chronic Dis 2013;10:130029. DOI: http://dx.doi.org/10.5888/pcd10.130029 . PEER REVIEWEDIntervention: BarriersEnablersand Preferred Strategies for Workplace Obesity PreventionPerthWestern Australia2012
IntroductionWorkplace health promotion programs to prevent overweight and obesity in office-based employees should be evidence-based and comprehensive and should consider behavioral, social, organizational, and environmental factors. The objective of this study was to identify barriers to and enablers of physical activity and nutrition as well as intervention strategies for health promotion in office-based workplaces in the Perth, Western Australia, metropolitan area in 2012.MethodsWe conducted an online survey of 111 employees from 55 organizations. The online survey investigated demographics, individual and workplace characteristics, barriers and enablers, intervention-strategy preferences, and physical activity and nutrition behaviors. We used χ and Mann-Whitney U statistics to test for differences between age and sex groups for barriers and enablers, intervention-strategy preferences, and physical activity and nutrition behaviors. Stepwise multiple regression analysis determined factors that affect physical activity and nutrition behaviors.ResultsWe identified several factors that affected physical activity and nutrition behaviors, including the most common barriers ("too tired" and "access to unhealthy food") and enablers ("enjoy physical activity" and "nutrition knowledge"). Intervention-strategy preferences demonstrated employee support for health promotion in the workplace.ConclusionThe findings provide useful insights into employees' preferences for interventions; they can be used to develop comprehensive programs for evidence-based workplace health promotion that consider environmental and policy influences as well as the individual. 2

Introduction

Poor nutrition and physical inactivity among employees affect the workplace; overweight and obesity are among the most common health issues affecting productivity (1). Physical inactivity has increased in workplaces because job roles have changed from manual labor to predominantly inactive tasks (2). Because of the common use of desktop computers, 45% of employed adults in Australia work in sedentary roles (3). Similarly, a rise in levels of automation and in the number of labor-saving devices has resulted in more people working in sedentary roles in the United States (4). The combination of sedentary behavior and easy access to energy-dense, nutrient-poor foods compounds the risk of overweight and obesity (4).

The workplace has a direct influence on employee health (5). For this reason, it is a critical setting for health promotion (2). Effective workplace health programs should incorporate behavioral, environmental, and policy approaches (6). It is therefore essential to have favorable physical and social environments as well as a supportive organizational culture to encourage positive behavior change (7).

Participation rates for workplace health programs vary among studies, demographic groups, and types of programs (8). Further investigation into barriers and enablers of program engagement among employees is needed, including examination of the characteristics of nonparticipating but eligible employees (9). Few studies describe effective workplace programs to prevent or manage overweight and obesity and reduce the burden of chronic disease. Evidencebased information for guiding the development of workplace health promotion programs is particularly lacking in Western Australia, the state with the highest prevalence (63%) of overweight/obesity in Australia (10).

The Social Cognitive Theory (11) provides the foundation for this study, addressing both underlying determinants of health behavior and methods of promoting change. This theory explores the importance of social norms and environmental influences on health behavior and how to modify these influences to achieve positive health outcomes (11). Exploring how employees perceive physical and nutrition and how they interact with their physical and social environment will identify barriers and enablers and strategies for workplace health promotion programs. The objective of this study was to identify barriers and enablers of physical activity and nutrition as well as intervention strategies (individual, environmental, policy) for health promotion in office-based workplaces in the Perth metropolitan area.

Methods

We conducted an online survey among office-based employees in June 2012. For study inclusion, employees had to be aged 18 to 45 years, located in the Perth metropolitan area, and working in an office that had at least 20 staff members. The study received Curtin University Human Research Ethics approval (no. PH-71-2012).

In preparation for the survey, we conducted formative research in 2 steps. In March 2012, we conducted 4 focus groups with 37 employees. We recruited office-based workers, who represented a random sample of the target population, through a computer-assisted telephone interview system. The focus group discussion guide explored physical activity and nutrition behaviors, barriers and enablers to physical activity and healthy eating, and preferred intervention strategies for workplace health promotion. In April 2012, we conducted 15-minute semistructured telephone interviews of 10 managers from 8 organizations. The interviews explored managerial support for workplace health promotion. To participate, managers had to manage a team of at least 10 office-based staff in the Perth metropolitan area. We used professional networks and office-based worksites listed in the Perth telephone directory to recruit participants.

We again used professional networks and office-based worksites listed in the Perth telephone directory to recruit participants for the online survey of office-based workers. We approached 410 employees; 137 employees representing 55 organizations agreed to participate. A link to the survey was sent to participants by e-mail after informal agreement to participate was established. After providing informed consent, participants completed the survey, which took approximately 10 to 15 minutes. Participants who had not commenced the survey within a week received a reminder email.

The online survey (Appendix) collected information on participant demographic characteristics (sex, country of birth, home postcode, education, employment status, average number of hours worked per day, occupation, and year of birth) workplace characteristics (eg, industry type, number of employees, office location/postcode, and health-related activities offered), physical activity and nutrition barriers and enablers, physical activity and nutrition behaviors, preferred intervention strategies (activities, materials and resources, policies and environmental conditions) for workplace health promotion, and preferred methods of communication. Previous research (1,2), other scientific literature, and a validated instrument (12) helped the formulation of the questions. Extensive pilot testing preceded final implementation. Participants were placed in a drawing to win several $50 gift certificates.

We analyzed the quantitative data from the online survey by using SPSS version 20.0 (International Business Machines Corp, Armonk, New York). Participants were asked to answer questions on preferred intervention strategies by using a 5-point Likert scale. To facilitate analysis, answers to questions on intervention materials and resources were recoded into 3 groups: not preferred (strongly not preferred or not preferred), neutral (neutral), and preferred (preferred or strongly preferred). Answers to questions on physical activity and nutrition activities were recoded into the following: unlikely (very unlikely or unlikely), neutral (neutral), and likely (likely or very likely). Similarly, answers to questions on policy and environmental strategies were recoded into the following: disagree (strongly disagree or disagree), neutral (neutral), and agree (agree or strongly agree).

We quantified the number of participants in each category and used χ and Mann-Whitney U statistics to test for differences between age and sex groups for barriers and enablers, intervention-strategy preferences, and physical activity and nutrition behaviors. We divided the participants into 2 age groups: younger (18-31 y) and older (32-45 y). 2 Stepwise multiple regression analysis accounted for collinearity and determined factors affecting physical activity and nutrition behavior. The first step was to identify associations between independent variables (barriers and enablers, demographics, and individual and workplace characteristics) and dependent variables (total daily sitting time [hours per day], total daily walking time [minutes per day], total physical activity [minutes per day], and total fruit and vegetable consumption [grams per day]). Independent variables associated (P < .05) with the dependent variables were entered into the regression model.

Results

Of 137 people who agreed to participate in the online survey, 111 (81.0%) completed it. The mean age of the respondents was 32.5 years; most were women (Table 1). Most respondents had a bachelor's degree or higher, and most were employed full time. Two-thirds were Australian-born. Approximately 15% of respondents were insufficiently active (<30 min/d) and approximately half of respondents did not meet the recommended servings of fruits and vegetables per day. Most respondents worked in noncommercial industries (eg, education and training, government, health and medical, not-for-profit). Small-or medium-sized organizations (20-99 employees) employed more than half of the participants; the remainder worked in large organizations (≥100 employees).

Barriers and enablers

The most common physical activity barriers were "too tired" (54.1%) and "work commitments/long hours" (53.2%). The older group was more likely than the younger group to cite family commitments as a barrier (53.8% vs 22.0%; P = .001). The most common physical activity enablers were "enjoy physical activity" (54.1%) and "health benefits" (54.1%). More men than women cited "being able to cycle/walk to shops/work" (54.2% vs 28.7%; P = .02), "shower and change rooms at work" (62.5% vs 25.3%; P = .001), and "work recreation teams" (25.0% vs 5.7%; P = .01).

The most common nutrition barriers were "unhealthy food available in office" (30.6%) and "lack of healthy options near office" (28.8%). The younger age group was more likely than the older group to cite the barriers "unhealthy food vending machines" (18.6% vs 3.8%; P = .02) and "healthy food more expensive than unhealthy food" (32.2% vs 15.4%; P = .04). The most common nutrition enablers included "food prepared at home" (84.7%) and "nutrition knowledge" (55.9%). We found no significant associations by age or sex.

Behavior predictors

Total daily sitting time For total daily sitting time, we found significant group differences according to 1 activity offered by the workplace (fitness assessments), 1 barrier ("work commitments/long hours"), and 1 enabler ("work recreation teams"). The regression model (Table 2) confirmed the association of these independent variables with total daily sitting time.

Total daily walking time For total walking time, we found significant group differences according to 1 activity offered by the workplace (corporate gym membership) and 3 enablers ("colleagues to exercise with," "lunch-time activities," and "work recreation teams"). The regression model suggested that "lunch-time activities" is a significant predictor of total walking time.

Total daily physical activity time For total daily physical activity time, we found significant group differences according to 1 demographic characteristic (sex), 2 activities offered by the workplace (health screening/assessments and a cycle-or walk-to-work promotion), 3 barriers ("too tired," "family commitments," and "lack of motivation/interest"); and 4 enablers ("enjoy physical activity," "showers and change rooms at work," "health benefits," and "work recreation teams"). The regression model showed that sex, "work recreation teams" (an enabler), "work commitments/long hours" (a barrier), and "average number of hours worked per day" were significant predictors of total physical activity time.

Total fruit and vegetable consumption

For fruit and vegetable consumption, we found significant group differences according to 1 demographic characteristic (employment status); 1 barrier ("lack of healthy food options near office"); and 2 enablers ("food prepared at home" and "nutrition knowledge"). The regression model suggested that "nutrition knowledge" and "food prepared at home" (enablers) and "no healthy food options near office" (a barrier) are significant predictors of total fruit and vegetable consumption.

Preferred intervention strategies

Physical activity

The most preferred activities were stretching program at desk (73.9%) and group classes (eg, yoga) (73.0%). More of the younger age group than the older age were likely to participate in a corporate gym membership (61.0% vs 40.8%, P = .01) and the Global Corporate Challenge (59.3% vs 36.2%, P = .05). A greater percentage of women than men stated they would be likely to participate in a walking group at lunch time (57.6% vs 26.1%, P = .02) and group classes (64.6% vs 26.1%, P = .004).

The preferred materials and resources were a stretching chart (72.1%) and a calendar (containing tips, information on topics such as goal setting) (70.2%). The younger age group had a greater preference for pedometers (70.2% vs 42.0%, P = .01), whereas women had a greater preference for pedometers (64.3% vs 30.4%, P = .01) and a calendar (58.3% vs 22.7%, P = 0.01).

The preferred policy/environmental supports were flexible work hours (94.6%) and shower and change facilities (90.1%). A greater percentage of women (36.9%) than men (14.3%) agreed that motivational posters reminding them to take the stairs would support them to be more active in the workplace (P = .04).

Nutrition

The preferred nutrition activities were personalized dietary programs (76.6%) and cooking demonstrations (73.0%). A greater percentage of the younger age group than the older age group were likely to participate in a weight-loss challenge with colleagues (58.6% vs 30.6%, P = .01). A greater percentage of women than men were likely to participate in cooking demonstrations (66.7% vs 33.3%, P = .006) and weight-loss challenges with colleagues (50.0% vs 28.6%, P = .003).

The preferred nutrition materials and resources were healthy recipes (83.8%) and a nutrition newsletter (79.3%). Women had a greater preference than men for a newsletter (70.9% vs 43.5%, P = .02), a healthy eating manual (70.2% vs 41.7%, P = .03), healthy recipes (77.6% vs 41.7%, P = .002), and a dietary guideline chart (54.1% vs 30.4%, P = .03).

The preferred policy/environmental supports were having a well-equipped kitchen at work (91.0%) and a free box of fruit provided in the kitchen (87.4%). A greater percentage of women (47.6%) than men (13.6%) agreed that motivational posters in the kitchen would support them to eat a healthful diet at work (P = .02).

Preferred contact methods

The most preferred program delivery methods were e-mail (89.2%) and web-based/Internet (58.6%). The least preferred were telephone (1.8%) and mail (12.6%). A greater percentage of respondents from the younger age group preferred mail as a program delivery method (18.6% vs 5.8%, P = .04). The most preferred format was electronic (59.5%), and the least preferred was hard copy (5.4%).

Discussion

This study identified several factors affecting physical activity and nutrition behaviors, including the most common barriers and enablers. Many barriers highlighted the limited amount of time available to employees outside of working hours and the need to ensure healthy and supportive environments in the workplace. Intervention-strategy preferences demonstrated employee support for health promotion in the workplace.

The reported barriers to physical activity and nutrition were quite different from each other -"too tired" and "work commitments/long hours" were the physical activity barriers most often cited. The most common barriers to eating a healthful diet were "unhealthy food available in office" and "lack of healthy options near office." Studies on physical activity and nutrition have reported similar findings: "not enough time" and "work schedule" were identified as the most common physical activity barriers (13), and "lack of knowledge," "lack of time," and "presence of tempting and limited healthy food options" were the most common nutrition barriers cited (14). These findings highlight the challenge of long working hours and the responsibility of organizations to provide physical activity and nutrition programs to support employee health. Because disparities exist in the level of physical activity among population subgroups (15), it is useful to identify enablers and predictors of physical activity behavior to better inform the development of workplace health interventions (16). Two barriers were significant predictors of physical activity in this study: employees who reported work commitments/long hours as a barrier reported 55 more minutes of total daily sitting time than those who did not cite this barrier, and employees who reported family commitments as a barrier participated in 19.9 fewer minutes of total daily physical activity than those who did not cite this barrier.

In contrast, employees participating in work recreation teams engaged in 25.1 more minutes of total daily physical activity. Similarly, those participating in lunch-time activities walked for 14.9 more minutes more per day than those who did not participate, and employees reporting "health benefits" as an enabler engaged in 11.6 more minutes of daily physical activity than those who did not report this enabler. These findings suggest that more emphasis should be placed on educating employees about the health benefits of physical activity.

Employees who indicated a lack of healthy food options near the office as a nutrition barrier reported consuming a smaller amount of fruit and vegetables per day (103.9 g) than those who did not report the barrier, whereas those who prepared food at home and had nutrition knowledge consumed more fruit (118.0 g) and vegetables (87.3 g) than those who did not prepare food at home or have nutrition knowledge. These findings indicate that employees working in a location that lacks healthy food options can be encouraged to prepare food at home and increase self-efficacy through nutrition education.

Participation in workplace health programs can vary among demographic groups and the types of programs offered (8). It is therefore important to identify preferences for individual, organizational, and policy intervention methods to enhance engagement and participation.

Preferences for physical activity strategies for the individual included stretching programs that can be performed at a desk, group classes, and the provision of pedometers, stretching charts, and calendars. The encouragement of light resistance training through stretching programs can provide multiple health benefits for employees who are normally sedentary and untrained (17). Group classes provide a socially supportive environment and an effective way to encourage physical activity (3).

More than half of respondents indicated a preference for pedometers. The use of pedometers can increase daily step counts and encourage physical activity during work hours (13); most staff members are usually willing to participate in activities using pedometers (18).

Step counts can be increased by using pedometers in conjunction with diaries and self -monitoring methods such as a calendar (13).

The ability of environmental and policy strategies to increase physical activity in the workplace is well recognized (19). We found that among the most preferred workplace policies were flexible work hours. Breaks and flexible hours have a positive effect on employee physical activity and health (20).

Preferences for nutrition strategies for the individual were personalized dietary programs and cooking demonstrations, and the most preferred nutrition material/resource was healthy recipes. Such activities and resources are useful for improving knowledge, skills, and self-efficacy, which are significant mediators of increased fruit and vegetable intake (21).

Among the most preferred environmental and policy strategies were provision of fruit boxes and healthful food. A systematic review showed that environmental modifications affect the dietary intake of office-based employees (2). Strategies to improve dietary behaviors included ensuring availability of healthy food options, a finding consistent with other studies (22).

The most preferred method for information delivery was e-mail, followed by Internet-based delivery. Similarly, the most preferred format for program materials was electronic. The preference for electronic and Internet-based programs may be linked to the decreased stigma associated with enrolling in an Internet-based obesity program to address body weight (23). Electronic media have the advantage of having the capacity to reach large numbers of people at low cost (24).

Our study has several limitations. The survey recruitment process may have attracted more motivated individuals to the study (25). Also, most respondents were women; however, most employees at office-based worksites in Western Australia are women (10). Finally, the sample size (n = 111) may limit the generalizability of the study; nevertheless, such a sample size is deemed adequate for the purpose of formative research.

These findings can be generalized to most office-based worksites because we included numerous office sizes and industry types. Barriers and enablers provide information on factors to be overcome or encouraged through health promotion programs. Preferences for intervention strategies indicate strategies that are most and least likely to engage employees. In addition, our methods and survey instrument can serve as models for formative evaluation to assist development of office-based obesity prevention in other regions.

Findings from this study increase current understanding of the barriers, enablers, and preferred intervention strategies for programs to prevent obesity in office-based employees. Workplace health programs should be designed and implemented to ensure optimal reach and to provide benefits to employees and their organizations (26). Our findings can be used to develop comprehensive evidence-based workplace health promotion programs that consider the individual as well as environmental and policy influences (16).

Table 1 .
121. Quintiliani L, Poulsen S, Sorensen G. Healthy eating strategies in the workplace. Int J Workplace Health Manag 2010;3(3):182-96. CrossRef 22. Engbers LH, van Poppel M, Chin A Paw M, van Mechelen W. Worksite health promotion programs with environmental changes: a systematic review. Am J Prev Med 2005;29(1):61-70. CrossRef PubMed 23. Pressler A, Knebel U, Esch S, Kölbl D, Esefeld K, Scherr J, et al. An internet-delivered exercise intervention for workplace health promotion in overweight sedentary employees: a randomized trial. Prev Med 2010;51(3-4):234-9. CrossRef PubMed 24. Cavill J-L, Jancey J, Howat P. Review and recommendations for online physical activity and nutrition programmes targeted at over 40s. Glob Health Promot 2012;19(2):44-53. CrossRef 25. Soler RE, Leeks K, Razi S, Hopkins D, Griffith M, Aten A, et al. A systematic review of selected interventions for worksite health promotion: the assessment of health risks with feedback. Am J Prev Med 2010;38(2 Suppl):S237-62. CrossRef PubMed 26. Machen R, Cuddihy T, Reaburn P, Higgins H. Development of a workplace wellness promotion pilot framework: a case study of the Blue Care Staff Wellness Program. ACHPER Healthy Lifestyles Journal 2010;1(2):13-20. Demographic and Behavioral Characteristics of Office-Based Workers Who Participated in Online Survey (N = 111), Perth, Western Australia, 2012 Total physical activity time, mean (SD), minutes/day 58.1 (33.7)Abbreviations: TAFE, technical and further education; SD, standard deviation. Values are numbers (percentages) unless otherwise indicated.Tables

Characteristic

Table 2 .
2Stepwise Regression Results for Physical Activity and Nutrition Behaviors for Office-Based Workers (N = 111), Perth, Western Australia, 2012 Walking time (minutes/day) Total physical activity time (minutes/day) Total fruit and vegetable consumption (grams/day) Appendix. Text of Online Survey Questions and Response Options Section 1: Information About You 1. Sex: male, female. 2. Country of birth: Australia, other. 3. Home postcode: [fill-in-the-blank]. 4. Highest level of education: left school before year 10; year 10 or equivalent; year 12 or equivalent; trade, diploma or TAFE [technical or further education], bachelor degree or higher. 5. Employment status: full time, part time, casual/contract/temp.Variable

Page 11 of 11Preventing Chronic Disease | Office-Based Physical Activity and Nutrition Intervention...
AcknowledgmentsAn Australian Health Promotion Association/Healthway Graduate Scholarship and the Centre for Behavioural Research in Cancer Control supported this work. Cancer Council Western Australia provides funding support to the Centre for Behavioural Research in Cancer Control.Section 8: NutritionThe next section will ask you about your nutrition during a typical work day.1. How many serves of fruit do you eat in a typical work day? [Line drawing of an apple, 2 apricots, and 1 cup of chopped fruit answers question, "What is a serve of fruit?" Additional text says, "One serve equals 1 medium piece (an apple, banana, orange or pear); 2 small pieces (apricots, plums, or kiwi fruit); 1 cup diced pieces or canned fruit; ½ cup 100% juice; 1½ tablespoons dried sultanas or 4 dried apricots."] Indicate the number of serves consumed per day on average: 0, 1, 2, 3, 4, 5, 6, 7+. The RIS file format is a text file containing bibliographic citations. These files are best suited for import into bibliographic management applications such as EndNote , Reference Manager , andProCite . A free trial download is available at each application's web site.
Effects of worksite health promotion interventions on employee diets: a systematic review. Ni Mhurchu, C Aston, L Jebb, S , BMC Public Health. 1062CrossRef PubMedNi Mhurchu C, Aston L, Jebb S. Effects of worksite health promotion interventions on employee diets: a systematic review. BMC Public Health 2010;10:62. CrossRef PubMed

Monitoring and evaluation of worksite health promotion programs -current state of knowledge and implications for practice. Geneva (CH): World Health Organization. L Engbers, Engbers L. Monitoring and evaluation of worksite health promotion programs -current state of knowledge and implications for practice. Geneva (CH): World Health Organization; 2008.

Employee engagement with a corporate physical activity program: the global corporate challenge. P Scherrer, L Sheridan, R Sibson, M Ryan, N Henley, J Int Bus Stud. 181Scherrer P, Sheridan L, Sibson R, Ryan M, Henley N. Employee engagement with a corporate physical activity program: the global corporate challenge. J Int Bus Stud 2010;18(1):125-39.

Task Force on Community Preventive Services. A recommendation to improve employee weight status through worksite health promotion programs targeting nutrition, physical activity, or both. Am J Prev Med. 374CrossRef PubMedTask Force on Community Preventive Services. A recommendation to improve employee weight status through worksite health promotion programs targeting nutrition, physical activity, or both. Am J Prev Med 2009;37 (4):358-9. CrossRef PubMed

Geneva (CH): World Health Organization. Workplace health promotionWorkplace health promotion. Geneva (CH): World Health Organization; 2012. http://www.who.int/occupational_health/topics/workplace/en/.

Cost-effectiveness of a long-term Internet-delivered worksite health promotion programme on physical activity and nutrition: a cluster randomized controlled trial. S J Robroek, S Polinder, F Bredt, A Burdorf, Health Educ Res. 273PubMedRobroek SJ, Polinder S, Bredt F, Burdorf A. Cost-effectiveness of a long-term Internet-delivered worksite health promotion programme on physical activity and nutrition: a cluster randomized controlled trial. Health Educ Res 2012;27(3):399-410. PubMed

Taking the stairs instead: the impact of workplace design standards on health promotion strategies. S Mcgann, J Jancey, M Tye, Australas Med J. 68McGann S, Jancey J, Tye M. Taking the stairs instead: the impact of workplace design standards on health promotion strategies. Australas Med J 2013;6(8)23-28.

Healthcare workers' participation in a healthy-lifestyle-promotion project in Western Sweden. I H Jonsdottir, M Borjesson, G Ahlborg, BMC Public Health. 111CrossRef PubMedJonsdottir IH, Borjesson M, Ahlborg G. Healthcare workers' participation in a healthy-lifestyle-promotion project in Western Sweden. BMC Public Health 2011;11(1):448-56. CrossRef PubMed

Worksite-based weight loss programs: a systematic review of recent literature. M A Benedict, D Arterburn, Am J Health Promot. 226CrossRef PubMedBenedict MA, Arterburn D. Worksite-based weight loss programs: a systematic review of recent literature. Am J Health Promot 2008;22(6):408-16. CrossRef PubMed

. No.: 4102.0Australian Bureau of Statistics. Australian social trends. ReportCanberra: Australian Bureau of StatisticsAustralian Bureau of Statistics. Australian social trends, Dec 2011. Report No.: 4102.0. Canberra: Australian Bureau of Statistics; 2011.

Health behavior and health education: theory, research, and practice. K Glanz, B K Rimer, K Viswanath, San Francisco (CAJossey-BassGlanz K, Rimer BK, Viswanath K. Health behavior and health education: theory, research, and practice. 4th edition. San Francisco (CA): Jossey-Bass; 2008.

Physical activity and nutrition program for seniors (PANS): protocol of a randomized controlled trial. L Burke, J Jancey, P Howat, A Lee, D Kerr, T Shilton, BMC Public Health. 10CrossRef PubMedBurke L, Jancey J, Howat P, Lee A, Kerr D, Shilton T, et al. Physical activity and nutrition program for seniors (PANS): protocol of a randomized controlled trial. BMC Public Health 2010;10:751-7. CrossRef PubMed

Workplace physical activity interventions: a systematic review. L Dugdill, A Brettle, C Hulme, S Mccluskey, A Long, Int J Workplace Health Manag. 11CrossRefDugdill L, Brettle A, Hulme C, McCluskey S, Long A. Workplace physical activity interventions: a systematic review. Int J Workplace Health Manag 2008;1(1):20-40. CrossRef

A qualitative examination of the role of small, rural worksites in obesity prevention. C Escoffery, M Kegler, I Alcantara, M Wilson, K Glanz, Prev Chronic Dis. 8475Escoffery C, Kegler M, Alcantara I, Wilson M, Glanz K. A qualitative examination of the role of small, rural worksites in obesity prevention. Prev Chronic Dis 2011;8(4):A75.

Barriers to physical activity in an on-site corporate fitness centre. H M Schwetschenau, W O'brien, C Cunningham, S Jex, J Occup Health Psychol. 134CrossRef PubMedSchwetschenau HM, O'Brien W, Cunningham C, Jex S. Barriers to physical activity in an on-site corporate fitness centre. J Occup Health Psychol 2008;13(4):371-80. CrossRef PubMed

Correlates of physical activity: why are some people physically active and others not?. A E Bauman, R Reis, J Sallis, J Wells, R Loos, B Martin, Lancet. 3809838CrossRef PubMedBauman AE, Reis R, Sallis J, Wells J, Loos R, Martin B. Correlates of physical activity: why are some people physically active and others not? Lancet 2012;380(9838):258-71. CrossRef PubMed

Health and fitness benefits of a resistance training intervention performed in the workplace. P M Zavanela, B Crewther, L Lodo, A Florindo, E Miyabara, M Aoki, J Strength Cond Res. 263Zavanela PM, Crewther B, Lodo L, Florindo A, Miyabara E, Aoki M. Health and fitness benefits of a resistance training intervention performed in the workplace. J Strength Cond Res 2012;26(3):811-7. PubMed

Promoting physical activity in the workplace: using pedometers to increase daily activity levels. L Thomas, M Williams, Health Promot J Austr. 172PubMedThomas L, Williams M. Promoting physical activity in the workplace: using pedometers to increase daily activity levels. Health Promot J Austr 2006;17(2):97-102. PubMed

Effect of innovative building design on physical activity. G Nicoll, C Zimring, J Public Health Policy. 30CrossRef PubMedNicoll G, Zimring C. Effect of innovative building design on physical activity. J Public Health Policy 2009;30:S111 -23. CrossRef PubMed

Booster breaks: an easy-to-implement workplace policy designed to improve employee health, increase productivity, and lower health care costs. W Taylor, J Workplace Behav Health. 26CrossRefTaylor W. Booster breaks: an easy-to-implement workplace policy designed to improve employee health, increase productivity, and lower health care costs. J Workplace Behav Health 2011;26:70-84. CrossRef

Hours worked per day (average): 1 or less. 102, 3, 4, 5, 6, 7, 8, 9Hours worked per day (average): 1 or less, 2, 3, 4, 5, 6, 7, 8, 9, 10+.

Year of birth. fill-in-the-blankYear of birth [fill-in-the-blank].

Section 2: Information About Your Workplace 1. Industry: building and construction, education and training, entertainment, financial services, tourism and hospitality, government, health and medical, mining and energy, not-for-profit, retail and sales, transport, other. fill-in-the-blankSection 2: Information About Your Workplace 1. Industry: building and construction, education and training, entertainment, financial services, tourism and hospitality, government, health and medical, mining and energy, not-for-profit, retail and sales, transport, other [fill-in-the-blank].

Approximately how many staff work in your office/workplace? Only include the number of people located in your office building, and not the total number for your whole organisation if located across a number of different sites. fill-in-the-blankApproximately how many staff work in your office/workplace? Only include the number of people located in your office building, and not the total number for your whole organisation if located across a number of different sites: [fill-in-the-blank].

Office location/postcode. fill-in-the-blankOffice location/postcode: [fill-in-the-blank].

What health related activities does your workplace currently offer? Please select all that apply: allocated stretching/relaxing times; flexible work hours; corporate sports teams; physical activity sessions; health screening/assessments; fitness assessments; sports days/activities; corporate gym membership; cycle or walk to work promotion; sponsored events, eg, fun runs; group classes, eg, yoga; personalised diet programs; healthy cooking demonstrations; fruit and vegetable boxes. nutrition awareness/education; none; unsure; other [fill-inthe blankWhat health related activities does your workplace currently offer? Please select all that apply: allocated stretching/relaxing times; flexible work hours; corporate sports teams; physical activity sessions; health screening/assessments; fitness assessments; sports days/activities; corporate gym membership; cycle or walk to work promotion; sponsored events, eg, fun runs; group classes, eg, yoga; personalised diet programs; healthy cooking demonstrations; fruit and vegetable boxes; nutrition awareness/education; none; unsure; other [fill-in- the blank].

Which of the following currently limit you being able to undertake regular physical activity during a typical work day (choose all that apply)? None; too tired; work commitments/long hours; family commitments; weather; lack of motivation/interest; financial cost; health reasons; unsure of the benefits of physical activity; lack of access to facilities/activities; time to commute to and from work. Section 3: Barriers and Enablers 1. no workplace support; getting hot and sweaty; other [fillin-the-blankSection 3: Barriers and Enablers 1. Which of the following currently limit you being able to undertake regular physical activity during a typical work day (choose all that apply)? None; too tired; work commitments/long hours; family commitments; weather; lack of motivation/interest; financial cost; health reasons; unsure of the benefits of physical activity; lack of access to facilities/activities; time to commute to and from work; no workplace support; getting hot and sweaty; other [fill- in-the-blank].

Which of the following currently enable or encourage you to undertake regular physical activity during a typical work day (choose all that apply)? None; being able to cycle/walk to shops/work; enjoy physical activity; flexible work hours; colleagues to exercise with; challenges/competitions; weather; showers and change rooms at work; workplace support. health benefits; lunch-time activities; corporate gym membership; work recreation teams; other [fill-in-the-blank2. Which of the following currently enable or encourage you to undertake regular physical activity during a typical work day (choose all that apply)? None; being able to cycle/walk to shops/work; enjoy physical activity; flexible work hours; colleagues to exercise with; challenges/competitions; weather; showers and change rooms at work; workplace support; health benefits; lunch-time activities; corporate gym membership; work recreation teams; other [fill-in-the-blank].

Which of the following currently limit your ability to consume a healthy diet during a typical work day (choose all that apply)? None; family commitments; lack of equipped kitchen at work; work commitments/long hours; lack of healthy food options near office; unhealthy food vending machines; unhealthy food available in office (fundraisers, morning teas, etc); healthy food more expensive than unhealthy food; my lack of cooking skills; my lack of nutrition knowledge. other [fill-in-the-blankWhich of the following currently limit your ability to consume a healthy diet during a typical work day (choose all that apply)? None; family commitments; lack of equipped kitchen at work; work commitments/long hours; lack of healthy food options near office; unhealthy food vending machines; unhealthy food available in office (fundraisers, morning teas, etc); healthy food more expensive than unhealthy food; my lack of cooking skills; my lack of nutrition knowledge; other [fill-in-the-blank].

Which of the following currently enable or encourage you to consume a healthy diet during a typical work day (choose all that apply)? None; healthy food supplied at office; access to healthy food outlets; food prepared at home; healthy food vending machines; kitchen facilities at work; colleagues eat healthy food; cooking skills. nutrition knowledge; other [fill-in-the-blank4. Which of the following currently enable or encourage you to consume a healthy diet during a typical work day (choose all that apply)? None; healthy food supplied at office; access to healthy food outlets; food prepared at home; healthy food vending machines; kitchen facilities at work; colleagues eat healthy food; cooking skills; nutrition knowledge; other [fill-in-the-blank].

Section 4: Preferred Physical Activity Strategies. Section 4: Preferred Physical Activity Strategies

Indicate how likely you would be to participate in the following physical activities if offered in your workplace [scale of 1 (very unlikely) to 5 (very likely)]: jogging/running group at lunch time; walking group at lunch time; team sports at lunch time; Global Corporate Challenge (eg, pedometer challenge). corporate gym membershipIndicate how likely you would be to participate in the following physical activities if offered in your workplace [scale of 1 (very unlikely) to 5 (very likely)]: jogging/running group at lunch time; walking group at lunch time; team sports at lunch time; Global Corporate Challenge (eg, pedometer challenge); corporate gym membership;

sponsored events, eg, fun runs; group classes, eg, yoga, Pilates; stretching program at desk; 2 options for other. fill-in-the-blanksponsored events, eg, fun runs; group classes, eg, yoga, Pilates; stretching program at desk; 2 options for other [fill-in-the-blank].

We are now going to ask you about your preference for materials and resources to support/encourage your participation in workplace physical activity. We are now going to ask you about your preference for materials and resources to support/encourage your participation in workplace physical activity.

pedometer; newsletter (physical activity tips, health benefits, exercises, etc); stretching chart; calendar (events, physical activity tips, goal setting, etc); physical activity booklet (stretches, exercises, tips, goal setting, etc); health alerts via text message; health alerts via email; web-based physical activity information/materials; 2 options for other. Indicate which of the following physical activity materials and resources you would prefer in your workplace (if free). 1not preferred) to 5 (preferred). fill-in-the-blankIndicate which of the following physical activity materials and resources you would prefer in your workplace (if free) [scale of 1 (not preferred) to 5 (preferred)]: pedometer; newsletter (physical activity tips, health benefits, exercises, etc); stretching chart; calendar (events, physical activity tips, goal setting, etc); physical activity booklet (stretches, exercises, tips, goal setting, etc); health alerts via text message; health alerts via email; web-based physical activity information/materials; 2 options for other [fill-in-the-blank].

We are now going to ask you about policy and environmental strategies to support/encourage your participation in workplace physical activity. We are now going to ask you about policy and environmental strategies to support/encourage your participation in workplace physical activity.

The following do/would support me to be physically active in the workplace: flexible work hours. Indicate whether you agree or disagree with the following statementsIndicate whether you agree or disagree with the following statements [scale of 1 (strongly disagree) to 5 (strongly agree)]. The following do/would support me to be physically active in the workplace: flexible work hours;

extended lunch breaks; incentives (eg, small prizes and gifts); 10 min breaks every 2 hours; shower and change facilities; facilities such as bicycle racks; motivational posters reminding me to take the stairs instead of the lift; easy access to stairs; 2 options for other. fill-in-the-blankextended lunch breaks; incentives (eg, small prizes and gifts); 10 min breaks every 2 hours; shower and change facilities; facilities such as bicycle racks; motivational posters reminding me to take the stairs instead of the lift; easy access to stairs; 2 options for other [fill-in-the-blank].

Section 5: Preferred Nutrition Strategies. Section 5: Preferred Nutrition Strategies

Indicate how likely you would be to participate in the following nutrition activities if offered in your workplace [scale of 1 (very unlikely) to 5 (very likely): nutrition education sessions; veggie garden competitions; cooking demonstrations; personalised dietary program; weight loss challenge with colleagues; 2 options for other. fill-inthe-blankIndicate how likely you would be to participate in the following nutrition activities if offered in your workplace [scale of 1 (very unlikely) to 5 (very likely): nutrition education sessions; veggie garden competitions; cooking demonstrations; personalised dietary program; weight loss challenge with colleagues; 2 options for other [fill-in- the-blank].

We are now going to ask you about your preference for materials & resources to support/encourage healthy eating in the workplace. We are now going to ask you about your preference for materials & resources to support/encourage healthy eating in the workplace.

Indicate which of the following nutrition materials you would prefer to receive in the workplace: newsletter containing recipes, tips, etc; healthy eating manual containing recipes, nutrition information, health tips, etc; healthy recipes; dietary guideline chart outlining food groups and how much to eat; nutrition alerts via text message; nutrition alerts via e-mail; web-based nutrition information; 2 options for other. fill-in-the-blankIndicate which of the following nutrition materials you would prefer to receive in the workplace: newsletter containing recipes, tips, etc; healthy eating manual containing recipes, nutrition information, health tips, etc; healthy recipes; dietary guideline chart outlining food groups and how much to eat; nutrition alerts via text message; nutrition alerts via e-mail; web-based nutrition information; 2 options for other [fill-in-the-blank].

We are now going to ask you about policy and environmental strategies to support/encourage your healthy eating in the workplace. We are now going to ask you about policy and environmental strategies to support/encourage your healthy eating in the workplace.

The following do/would support me to eat a healthy diet in the workplace: free cooking sessions; free nutrition education sessions; healthy food catering policy (healthy options at meetings, morning teas, etc); fruit boxes; healthy eating posters in kitchen/meals areas; healthy options in vending machines; well-equipped kitchen at work (eg, microwave, toaster, fridge, etc); 2 options for other. Indicate whether you agree or disagree with the following statements. scale of 1 (strongly disagree. strongly agree. fill-in-the-blankIndicate whether you agree or disagree with the following statements [scale of 1 (strongly disagree) to 5 (strongly agree). The following do/would support me to eat a healthy diet in the workplace: free cooking sessions; free nutrition education sessions; healthy food catering policy (healthy options at meetings, morning teas, etc); fruit boxes; healthy eating posters in kitchen/meals areas; healthy options in vending machines; well-equipped kitchen at work (eg, microwave, toaster, fridge, etc); 2 options for other [fill-in-the-blank].

Section 6: Preferred Contact Methods 1. If you were to participate in a workplace health promotion program, how would you like the program information to be delivered? (Tick all that apply): SMS; e-mail; phone; mail; web-based/Internet; online forums/discussions; health seminars. none; other [fill-in-the-blankSection 6: Preferred Contact Methods 1. If you were to participate in a workplace health promotion program, how would you like the program information to be delivered? (Tick all that apply): SMS; e-mail; phone; mail; web-based/Internet; online forums/discussions; health seminars; none; other [fill-in-the-blank].

Preferred format of program materials (e.g. newsletters, manuals etc): hard copy, electronic; both. Preferred format of program materials (e.g. newsletters, manuals etc): hard copy, electronic; both.

How often would you like to participate/receive updates? I would not participate; weekly; fortnightly; monthly; other. fill-in-the-blankHow often would you like to participate/receive updates? I would not participate; weekly; fortnightly; monthly; other [fill-in-the-blank].

Section 7: Physical Activity The next section will ask you about your physical activity during a typical work day. Section 7: Physical Activity The next section will ask you about your physical activity during a typical work day.

During a typical work day, how many hours do you spend sitting?1 hour. 2 hours; 3 hours; 4 hours; 5 hours; 6 hours; 7 hours; 8 hours; 9 hours; 10 hours; 11 hours; 12 hours; 13+ hoursDuring a typical work day, how many hours do you spend sitting?1 hour; 2 hours; 3 hours; 4 hours; 5 hours; 6 hours; 7 hours; 8 hours; 9 hours; 10 hours; 11 hours; 12 hours; 13+ hours.

During a typical work day, how many minutes do you spend walking for transport? (Examples include walking to/from work, walking to shops etc. fill-in-the blankDuring a typical work day, how many minutes do you spend walking for transport? (Examples include walking to/from work, walking to shops etc): [fill-in-the blank].

During a typical work day, how many minutes do you spend walking for recreation? (Examples include brisk walking during lunch or before/after work. fill-in-the blankDuring a typical work day, how many minutes do you spend walking for recreation? (Examples include brisk walking during lunch or before/after work): [fill-in-the blank].