Study population
We used data from the 2008 National Health Interview Survey (NHIS), a multi-purpose health survey of a probability-based sample of the U.S. civilian noninstitutionalized population conducted by the CDC’s National Center for Health Statistics (NCHS). The majority of the interviews were conducted in person by trained interviewers from the U.S. Census Bureau, and 25% were completed by telephone. The interviewed sample for 2008 consisted of 74,236 persons in 29,421 families from 28,790 households yielding a household response rate of approximately 85%, a conditional sample adult response rate of 74%, and a final adult sample size of 11,826 with a sample adult response rate of 63% [17].
The focus of this analysis was currently employed adults who were 18 years of age and older. This group included adults currently working for pay at a job or business in the prior week or adults working at a job or business but not at work in the prior week. We excluded workers who were self-employed, working without pay, working in a family business, looking for work, or not working (Figure 1).
Occupational characteristics
Respondents were asked about the kind of work they did (occupation) and the current job or work situation (employed by a private company or federal, state or local government). Two-digit codes based on the Standard Occupational Classification [18] were assigned to each verbatim response by NCHS [19]. We collapsed the occupations into 5 general categories that included management occupations (codes 01–04), professional/technical occupations (codes 05–31), service occupations (codes 32–52), sales and office administrative support occupations (codes 53–64), and a general production category that included construction, production, transportation and maintenance occupations as well as farming, forestry and fishing occupations (codes 65–93).
Information was obtained on the number of people who worked at the respondent’s current job location. The possible response categories of 1–9 employees, 10–24 employees, 25–49 employees, 50–99 employees, 100–249 employees, 250–499 employees, 500–999 employees and 1,000 or more employees were collapsed into 4 groups (Table 1). Currently working respondents reported how many years they had worked at a main job or business. Years at work were categorized as 0–1, 2–5, 6–15 and 16 or more. Respondents answered ‘yes’ or ‘no’ to the question, “Do you have paid sick leave on this main job or business?”
Table 1
Percent of U.S. workforce with paid sick leave by occupational characteristics, NHIS, 2008
Cancer tests and medical care seeking
Respondents were asked if they had ever had a colorectal exam, the type of exam, when they had the exam and the reasons for the exam. We classified respondents who reported having had a colonoscopy during the past 10 years or sigmoidoscopy during the past 5 years for any reason as having had an endoscopy within recommended screening guidelines. Although FOBT is currently recommended with sigmoidoscopy [6], the use of sigmoidoscopy represents only a small fraction of endoscopic screening procedures, and this recommendation in 2008 may not be reflected in the data used for this analysis. We used the definition of screening by sigmoidoscopy during the past 5 years to permit comparisons with other published estimates. In addition, respondents were asked if they had ever used an FOBT home kit, and the date of their most recent test. Respondents, who had never had this test or had not had one during the prior year as recommended by national guidelines, were classified as not having the test. Women were asked if they had had a mammography and a Pap smear or Pap test, when they had the tests and the reasons for the test. Women who reported having had a mammogram during the prior 2 years or a Pap test during the prior 3 years as part of a routine exam were classified as having had a mammogram or Pap test respectively [6].
Respondents were asked if they had seen or talked to a general practice, internal medicine or family doctor during the prior 12 months and how many times during the prior 12 months they had seen a doctor or other health care professional in a doctor’s office, clinic or location other than a hospital, emergency room, or dental office or spoken to one by telephone. For this analysis we dichotomized the number of doctor visits as no visits versus one or more visits during the prior 12 months.
Age groups and gender
For analyses of cancer testing, we included working women 40 years and older in the analysis of mammography. During the time of this survey, recommendations for mammography included women from age 40 to 49 years [20]. All adult working women (18 years of age or older) were included in analyses of Pap testing. Colorectal cancer analyses (endoscopy and FOBT) focused on adults 50 years of age or older. Analyses of the outcomes of those individuals who had seen or spoken with a doctor and the number of visits included all working adults 18 years of age and older. Figure 1 presents a chart of population sub-groups for analyses. We assumed that most adults who were healthy enough to work could potentially benefit from early cancer detection, regardless of age, and therefore we did not apply an upper age limit for the use of any cancer screening test.
Other covariates
All variables were self-reported. These included age (classified by 10 year age groups), education (less than high school, high school or GED, some college and college graduates), race/ethnicity (Hispanic, non-Hispanic white, non-Hispanic black, and non-Hispanic other), poverty ratio (<100%, 100% to <200%, 200% to <400%, 400% or more), insurance status (private, public only, private and public, not covered and unknown), usual source of medical care (yes, no, and only emergency room care) and marital status (never married, married/partnered, and widowed/divorced). Missing data for income was imputed by using multiple imputation [17].
Statistical analysis
We used descriptive statistics to examine the distribution of occupational characteristics of the U.S. workforce with and without paid sick leave. In addition, we used the chi-square test to examine the association of having paid sick leave with the uptake of various cancer tests, the number of physician visits and whether members of this population have been seen by a doctor during the prior year. We used six multivariate logistic regression models that show the association between sick leave status and various socio-demographic characteristics with each of the cancer tests, number of physician visits, and whether members saw a doctor during the prior year. To enable easy interpretation of the models’ results, we computed and presented adjusted percentages (predicted margins), which are derived from the logistic regression model [21]. Overall associations were assessed with the Wald F statistic, and differences between categories within each adjusted variable were tested using general linear contrasts of the percentages.
To generalize the results to the population, each respondent was assigned a sampling weight. The weights accounted for selection probability and non-response. A P-value of less than 0.05 was considered statistically significant. We considered an estimate to be unstable and recommend caution in interpretation if the relative standard error, (calculated as [standard error/estimated percentage] x 100), was more than 30%. All statistical analyses were performed by using SAS 9.2 with SUDAAN release 10 (Research Triangle Institute, Research Triangle Park, NC) to adjust for the complex sampling design of the NHIS.