Design and data
Data from the 2018 Asia Best Workplace Mainland China (ABWMC) programme were employed to address these aims. ABWMC is an academic/company partnership programme that aims to support companies in building a healthy workplace. The ABWMC programme was designed by Peking University and organized by the American International Assurance Co. All companies may voluntarily join the programme and are free to withdraw. The inclusion criteria were as follows: (1) registered legal companies in China; (2) agreement to participate in the programme; and (3) at least 100 workers who are full-time employees. We used information from baseline employee questionnaires. The inclusion criteria for participating employees were as follows: (1) aged 18 years old or above; (2) full-time employees; and (3) agreement to participate in the programme.
The human resource departments of each company delivered the questionnaires to all employees. When first opening the link, content related to informed consent was shown, and employees were able to choose whether to complete the questionnaire or quit. If the employees submitted the questionnaire through the link, we considered that they agreed to participate. The self-check function of the online survey system automatically identified missing data, logical errors and illegal characters.
Measurements
- Smoking harm awareness
Smoking harm awareness was measured by the following question: ‘Do you think smoking can cause any of the following diseases? A: stroke, B: heart disease, C: lung cancer, D: cardiovascular disease, E: chronic obstructive pulmonary disease, F: asthma or G: I don’t know.’ Only the participants who chose all answers from A to F were classified as having smoking harm awareness.
- SHS exposure
In the survey, the participants were asked the following question: ‘How many days a week do you usually suffer from SHS exposure at workplace for more than 15 minutes? A: almost every day, B: 4-6 days, C:1-3 days or D: never’. Only the participants who chose D were classified as having no SHS exposure.
- Tobacco-related health education
We defined tobacco-related health education as follows: (1) organized by company level; (2) all employees have opportunities to join; and (3) the contents should be related to tobacco control or smoking cessation. This definition was explained to the respondents when conducted the survey.
Such activities were measured by two questions. The participants were asked the following questions: ‘Does your company provide you with tobacco related health education? A: Yes or B: No’. Respondents who answered ‘Yes’ were then asked ‘Have you ever participated such activities? A: Yes or B: No’.
We further classify all respondents into three categories: have tobacco-related health education and also attend such activities (both of the questions answered ‘Yes’=2); have tobacco-related health education but not attend such activities (first question answered ‘Yes’, second answered ‘No’=1 ); without tobacco-related health education (Otherwise=0)
- Perceived workplace environment
There were two variables for this characteristic. The first variable was for the employees to believe that they work in a healthy environment, and the second variable was for the employees to believe that the company policy protects health. For the first variable, participants were asked the following question: ‘Do you think your working environment is healthy? A: I totally agree, B: I Agree, C: Just ok, D: I do not agree, or E: I totally disagree. Only the participants who chose A and B were classified as believing that they work in a healthy environment.
For the second variable, participants were asked the following question: ‘Do you think your company’s policy can protect your health? A: I totally agree, B: I Agree, C: Just ok, D: I do not agree, or E: I totally disagree. Only the participants who chose A and B were classified as believing that their workplace policy protects the health of employees.
All the participants need answer these questions.
- Health information-seeking behaviour
In the survey, the participants were asked the following question: ‘How often do you search for health knowledge? A: Always, B: Very often, C: Sometimes, D: Occasionally, or E: Never. Only the participants who chose A and B were classified as having such behaviour regularly.
- Other covariates
We controlled for several variables of individual characteristics, such as gender, age, marital status, education, ethnicity and job position. For job position, we further classified all employees into two categories as follows: administrative employees (participants with administrative rank) and non-administrative employees (participants without administrative rank).
Data analytical plan
Our data have a hierarchical structure, therefore we firstly try to use multilevel analyses by setting individual-level and company-level factors. This type of analysis will take into account the fact that workers' responses are correlated within companies. We run four standardized models (Null model, Random coefficients regression model, Intercepts as model; Slopes as outcomes model). However, when we finished the Null model, we find intraclass correlation coefficient (ICC) is too low (lower than 0.059), is 0.051, indicating that only about 5.1% of the total variation on SHS exposure was attributable to differences between companies/clusters [15]. In other word, we can use usual method to perform analyses. Therefore, we use logistic regression for our statistics.
Our data analysis was conducted in three steps. First, we examined the distribution of the categorical and continuous variables. Second, Spearman correlation tests were used to examine unadjusted correlation between study variables. Third, we performed binary logistic regression for multivariable analysis.
The dependent variables included the smoking-related variables (smoking harm awareness and SHS exposure), working environment variable (perceived workplace environment) or health information-seeking behaviour. The explanatory variable indicated if the company provided tobacco-related health education (yes=1 or otherwise=0).
To examine whether there was an interaction effect between job position and health education, we further conducted regression analysis using two models. Model 1 only entered the main effects of health education, job position and covariates. Model 2 also added an interaction term between job position and health education.
We used SPSS 24.0(SPSS Inc, Beijing, China)statistical software to conduct all analyses.
Ethics
All participants were informed that the research team would analyze the data anonymously. This study was approved by the Peking University (ethical approval number: IRB00001052-18055).