title: Workplace Health Promotion: Assessing the Cardiopulmonary Risks of the Construction Workforce in Hong Kong.
abstract: OBJECTIVE
  Health needs of different employee subgroups within an industry can differ. We report the results of a workplace cardiopulmonary risk assessment targeting workers and support staff in the construction industry.
  
  
  METHODS
  A free worksite-based cardiopulmonary risk assessment for 1,903 workers on infrastructural contracts across Hong Kong was initiated in May 2014. Cardiopulmonary risk screening was performed in 60-minute blocks for approximately 30 workers/block with individualized feedback and lifestyle counseling. Risk profiles stratified by occupational roles are differentiated using the χ2-test for categorical and Student's t-test for continuous variables.
  
  
  RESULTS
  Most construction workers and clerks/professionals were male (83.2% and 71.2%, respectively) and Chinese (78.7% and 90.9%, respectively). Construction workers were older (mean: 44.9 years, SD 11.5) and less well-educated (6.1% received tertiary education) than clerks/professionals (35.0 years, 10.7; 72.6% received tertiary education), but more likely to be hypertensive (22.6% vs. 15.4%, p<0.001), overweight/obese (71.7% vs. 56.6%, p<0.001), centrally obese (53.1% vs. 35.5%, p<0.001), and have undesirable levels of high-density lipoprotein (41.6% vs. 35.8%, p<0.05) and diabetic levels of non-fasting blood glucose (4.3% vs. 1.6%, p<0.05). Up to 12.6% of construction workers and 9.7% of office clerks/professions had three or more metabolic syndrome risk factors. While construction workers were more likely than clerks/professionals to be daily smokers, they reported better work-related physical activity and diet.
  
  
  CONCLUSIONS
  Simple worksite health risk screening can identify potentially high-cardiopulmonary-risk construction industry employee subgroups for onward confirmatory referral. Separate cardiopulmonary health promotion strategies that account for the varying lifestyle profiles of the two employee subgroups in the industry appear justified.
authors.affiliation: Division of Behavioural Sciences, School of Public Health, 5/F William MW Mong Block, 21 Sassoon Road, Pokfulam, The University of Hong Kong, Hong Kong SAR, China.
authors.forename: Sze Pui Pamela
authors.initials: SP
authors.lastname: Tin
authors.affiliation: Division of Behavioural Sciences, School of Public Health, 5/F William MW Mong Block, 21 Sassoon Road, Pokfulam, The University of Hong Kong, Hong Kong SAR, China.
authors.forename: Wendy W T
authors.initials: WW
authors.lastname: Lam
authors.affiliation: Division of Behavioural Sciences, School of Public Health, 5/F William MW Mong Block, 21 Sassoon Road, Pokfulam, The University of Hong Kong, Hong Kong SAR, China.
authors.forename: Sungwon
authors.initials: S
authors.lastname: Yoon
authors.affiliation: Division of Behavioural Sciences, School of Public Health, 5/F William MW Mong Block, 21 Sassoon Road, Pokfulam, The University of Hong Kong, Hong Kong SAR, China.
authors.forename: Na
authors.initials: N
authors.lastname: Zhang
authors.affiliation: Division of Behavioural Sciences, School of Public Health, 5/F William MW Mong Block, 21 Sassoon Road, Pokfulam, The University of Hong Kong, Hong Kong SAR, China.
authors.forename: Nan
authors.initials: N
authors.lastname: Xia
authors.affiliation: Division of Behavioural Sciences, School of Public Health, 5/F William MW Mong Block, 21 Sassoon Road, Pokfulam, The University of Hong Kong, Hong Kong SAR, China.
authors.forename: Weiwei
authors.initials: W
authors.lastname: Zhang
authors.affiliation: Division of Behavioural Sciences, School of Public Health, 5/F William MW Mong Block, 21 Sassoon Road, Pokfulam, The University of Hong Kong, Hong Kong SAR, China.
authors.forename: Ke
authors.initials: K
authors.lastname: Ma
authors.affiliation: Division of Behavioural Sciences, School of Public Health, 5/F William MW Mong Block, 21 Sassoon Road, Pokfulam, The University of Hong Kong, Hong Kong SAR, China.
authors.forename: Richard
authors.initials: R
authors.lastname: Fielding
mesh_terms: D000328:Adult; D060389:Construction Industry / Q000706:statistics & numerical data*; D003376:Counseling; D005247:Feeding Behavior; D005260:Female; D006293:Health Promotion / Q000379:methods*; D006331:Heart Diseases / Q000453:epidemiology* / Q000517:prevention & control; D006723:Hong Kong / Q000453:epidemiology; D006801:Humans; D006973:Hypertension / Q000453:epidemiology* / Q000517:prevention & control; D008019:Life Style; D008075:Lipoproteins, HDL / Q000097:blood; D008297:Male; D008403:Mass Screening / Q000379:methods; D009765:Obesity / Q000453:epidemiology; D018570:Risk Assessment; D012307:Risk Factors; D011795:Surveys and Questionnaires; D017132:Workplace / Q000706:statistics & numerical data*
chemical_list: D008075:Lipoproteins, HDL