David Morganstein

Lost productive work time costs from health conditions in the United States: results from the American Productivity Audit.

Learning ObjectivesRecall the overall magnitude of lsot productive time (LPT) and its dollar cost as found in the American Productivity Audit, and the respective contributions of absenteeism and decreased producitivity at work.Be aware of how LPT varies with a number of demographic and workrelated factors.Compare the factors predisposing to LPT for personal and family-related reasons. The American Productivity Audit (APA) is a telephone survey of a random sample of 28,902 U.S. workers designed to quantify the impact of health conditions on work. Lost productive time (LPT) was measured for personal and family health reasons and expressed in hours and dollars. Health-related LPT cost employers

SWAN: A Multicenter, Multiethnic, Community-Based Cohort Study of Women and the Menopausal Transition

225.8 billion/year (

Confounders contributing to the reported associations of coffee or caffeine with disease

1685/employee per year); 71% is explained by reduced performance at work. Personal health LPT was 30% higher in females and twice as high in smokers (≥1 pack/day) versus nonsmokers. Workers in high-demand, low-control jobs had the lowest average LPT/week versus the highest LPT for those in low-demand, high-control jobs. Family health-related work absence accounted for 6% of all health-related LPT. Health-related LPT costs are substantial but largely invisible to employers. Costs vary significantly by worker characteristics, suggesting that intervention needs vary by specific subgroups.

Practical Sampling Techniques

Study of Womens Health Across the Nation (SWAN) is the first national study to describe women at midlife, an understudied age group. Its multidisciplinary approach provides the opportunity to consider the contributions of both culture and biology so that one may better understand health of women. The SWAN employs a prospective design that includes sufficient pre- and postmenopausal observations to ensure the separation of menopause-related and age-related physiological changes. Other attributes include the comprehensive standardized data collection related to biological, behavioral, physiological, social, environmental, and cultural factors; specialized data collection methodologies suitable to address the monthly and yearly variation in behavioral and biological patterns; general ability to community-dwelling populations recruited from major United States population centers; sufficiently large sample size and numbers of data points to ensure reliable estimates of associations and relevant effect sizes; and inclusion of sufficient numbers of racial/ethnic minorities to provide comparative information with the non-Hispanic Caucasian population. Because of these attributes, SWAN can contribute new and substantive knowledge about womens health in general and the menopause transition in particular.

Comparing statistical software for microcomputers

The role of caffeine or coffee in causing or promoting the incidence of serious disease is equivocal. Two design factors may account for the discrepancies in reported findings on the effects of coffee drinking: (a) imprecision of measurement and (b) confounding variables. A study of 2,714 white U.S. adults disclosed that, of 32 risk factors analyzed by linear and logistic regression, only sex and cigarette smoking were found to be important potential confounders of caffeine and coffee intake. Partial R2 values of the other 30 risk factors were relatively small and were inconsistent for each sex. It is unlikely that any of these factors could explain any of the reported associations between caffeine or coffee consumption and certain diseases. However, certain weak associations with caffeine or coffee intake should be included in the study design when they are known to be risk factors of a disease under investigation. These factors for men are dietary fat intake, vitamin C intake, and body mass index; and for women are vitamin use, alcohol intake, stress, and perceived health status.

Mentoring in the ASA: A Commentary

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Lost Productive Time and Cost Due to Common Pain Conditions in the US Workforce

Abstract The ever-expanding list of statistical packages presents the analyst using a microcomputer with an evaluation problem in the selection of software. In this study, the authors describe the personal computer environment in which the analyst must operate. They propose criteria which can facilitate evaluation of various packages and briefly describe some of the most recent entries into the marketplace.

Cost of Lost Productive Work Time Among US Workers With Depression

The past several years has seen growth in mentoring programs in the ASA and the initiation of awards recognizing the important contributions of outstanding mentors in our association. This issue of The American Statistician contains a number of articles, both invited and contributed, on the benefits these efforts offer to bothmentors andmentees. After a few comments on activities in the ASA and a discussion of the role of mentoring, the three invited articles are discussed and contrasted. The ASA has long been aware of the benefits of mentoring. Several years ago, the Committee on Minorities in Statistics began an annual mentoring activity at the Joint Statistical Meetings (JSMs). The Survey Research Methods section also developed a program that connectedmore seniormembers with younger, newer members of the section in an effort to support them. More recently, both the Washington Statistical Society (WSS) and the Biopharmaceutical Section instituted mentoring programs. The Committee on Applied Statisticians offered a clearinghouse for matching mentors and mentees and prepared materials to support individuals who wanted to mentor and to help organizations, such as sections or chapters, develop a mentoring program. Supported by a presidential initiative, mentoring programs—where interested mentees are matched to appropriatementors—have been part of the past three Conferences on Statistical Practice (CSP) and Joint Statistical Meetings (JSMs). For more than a decade, the WSS has bestowed the Jeanne E. Griffith Mentoring Award, an annual award for an outstanding mentor in government. The award is intended to encourage mentoring of junior staff in the federal, state, or local government statistical community and is presented annually to a supervisor, technical director, team coordinator, or staff member. Many organizations have seen the benefit in recognizing outstanding individuals who help develop younger, less senior people. The Presidential Awards for Excellence in Science, Mathematics, and Engineering Mentoring (PAESMEM) is an award established by theWhite House in 1995 to recognize individuals and organizations that have demonstrated excellence inmentoring individuals from groups that are underrepresented in STEM education and workforce. JSM 2016 saw the first annual ASA Mentoring Award bestowed to an outstanding statistician who has demonstrated a career-long record in supporting younger statisticians and statistical researchers.