Trajectories of Depressive Symptoms Among Web-Based Health Risk Assessment Participants.

BACKGROUND: Health risk assessments (HRAs), which often screen for depressive symptoms, are administered to millions of employees and health plan members each year. HRA data provide an opportunity to examine longitudinal trends in depressive symptomatology, as researchers have done previously with other populations. OBJECTIVE: The primary research questions were: (1) Can we observe longitudinal trajectories in HRA populations like those observed in other study samples? (2) Do HRA variables, which primarily reflect modifiable health risks, help us to identify predictors associated with these trajectories? (3) Can we make meaningful recommendations for population health management, applicable to HRA participants, based on predictors we identify? METHODS: This study used growth mixture modeling (GMM) to examine longitudinal trends in depressive symptomatology among 22,963 participants in a Web-based HRA used by US employers and health plans. The HRA assessed modifiable health risks and variables such as stress, sleep, and quality of life. RESULTS: Five classes were identified: A "minimal depression" class (63.91%, 14,676/22,963) whose scores were consistently low across time, a "low risk" class (19.89%, 4568/22,963) whose condition remained subthreshold, a "deteriorating" class (3.15%, 705/22,963) who began at subthreshold but approached severe depression by the end of the study, a "chronic" class (4.71%, 1081/22,963) who remained highly depressed over time, and a "remitting" class (8.42%, 1933/22,963) who had moderate depression to start, but crossed into minimal depression by the end. Among those with subthreshold symptoms, individuals who were male (P<.001) and older (P=.01) were less likely to show symptom deterioration, whereas current depression treatment (P<.001) and surprisingly, higher sleep quality (P<.001) were associated with increased probability of membership in the "deteriorating" class as compared with "low risk." Among participants with greater symptomatology to start, those in the "severe" class tended to be younger than the "remitting" class (P<.001). Lower baseline sleep quality (P<.001), quality of life (P<.001), stress level (P<.001), and current treatment involvement (P<.001) were all predictive of membership in the "severe" class. CONCLUSIONS: The trajectories identified were consistent with trends in previous research. The results identified some key predictors: we discuss those that mirror prior studies and offer some hypotheses as to why others did not. The finding that 1 in 5 HRA participants with subthreshold symptoms deteriorated to the point of clinical distress during succeeding years underscores the need to learn more about such individuals. We offer additional recommendations for follow-up research, which should be designed to reflect changes in health plan demographics and HRA delivery platforms. In addition to utilizing additional variables such as cognitive style to refine predictive models, future research could also begin to test the impact of more aggressive outreach strategies aimed at participants who are likely to deteriorate or remain significantly depressed over time.

Comparing work productivity in obesity and binge eating.

OBJECTIVE: To examine productivity impairment in individuals with obesity and/or binge eating. METHOD: Based on current weight and eating behavior, 117,272 employees who had completed a health risk appraisal and psychosocial functioning questionnaire were classified into one of four groups. Gender-stratified analyses compared groups on four measures: absenteeism, presenteeism, total work productivity impairment, and (non-work) activity impairment. RESULTS: Overall group differences were statistically significant for all measures with lowest impairment in non-obese men and women without binge eating (n = 34,090, n = 39,198), higher levels in individuals without binge eating (n = 15,570, n = 16,625), yet higher levels in non-obese men and women with binge eating (n = 1,381, n = 2,674), and highest levels in obese men and women with binge eating (Group 4, n = 2,739, n = 4,176). DISCUSSION: Health initiatives for obese employees should include screening and interventions for employees with binge eating.

Why men should be included in research on binge eating: results from a comparison of psychosocial impairment in men and women.

OBJECTIVE: Prevalence of binge eating has been shown to be as common in men as in women, yet few studies have included men. Men are especially underrepresented in treatment studies, raising the question of whether men who binge eat experience less distress or impairment than women. This study compared demographic and clinical correlates of binge eating in a large employee sample of men and women. METHOD: Cross-sectional data from 21,743 men and 24,608 women who participated in a health risk self assessment screening were used. Group differences in obesity, hypertension, dyslipidemia, Type 2 diabetes, depression, stress, sleep, sick days, work impairment, and nonwork activity impairment were tested using chi-square tests (categorical variables) and independent sample t-tests (continuous variables). RESULTS: Effect size estimates indicate that men (n = 1,630) and women (n = 2,754) who binge eat experience comparable levels of clinical impairment. They also report substantially greater impairment when compared with men and women who do not binge eat. DISCUSSION: The underrepresentation of men in treatment-seeking samples does not appear to reflect lower levels of impairment in men versus women. Efforts are needed to raise awareness of the clinical significance of binge eating in men so that this group can receive appropriate screening and treatment services.

Demographic and clinical characteristics of individuals utilizing an internet-based digital coaching program for recovering from binge eating.

OBJECTIVE: While digital coaching self-help interventions to facilitate behavioral change are offered increasingly on the Internet, few studies have examined who uses them. This study examined demographic and clinical characteristics of adults who accessed a self-help program for binge eaters made available to them via their employers or health plans. METHOD: Cross-sectional data from 4,051 men and women who registered for the online program during a 13-month period were used. Gender differences and differences across three diagnostic groupings based on self-reported symptoms were tested using t-tests and ANOVAs (dimensional variables) or Chi-Square analyses (categorical variables). RESULTS: More women (3,053) than men (998) accessed the program. A majority of participants reported binge eating below frequency levels required for a clinical diagnosis, yet reported high levels of motivation to overcome their eating binges. Few had received prior treatment for an eating disorder. Although women reported greater symptomatology on most variables, these differences typically reflected small effects. Comparisons of diagnostic subgroups found few differences between those with probable diagnoses of bulimia nervosa or binge eating disorder. DISCUSSION: Digital coaching programs may be a viable treatment option, particularly for individuals with infrequent binge eating who otherwise might not seek or receive treatment.

Association of binge eating with work productivity impairment, adjusted for other health risk factors.

OBJECTIVE: This study examined the association between binge eating and productivity impairment. METHODS: Using data drawn from individuals completing a health risk appraisal and the Work Productivity and Activity Impairment questionnaire, analyses examined associations between binge eating and obesity, health risks, and productivity impairment. Regression analysis tested associations between binge eating and Work Productivity and Activity Impairment scores, adjusting for demographics, obesity, and health risks. Unstandardized regression coefficients estimated annual productivity loss due to binge eating using a hypothetical employer. RESULTS: Significant associations were found between binge eating and impairment. Adjusting for demographics, obesity, and other risks, binge eating remained a significant correlate of productivity impairment. Estimated annual productivity loss due to binge eating in a company of 1000 employees was $107,965. CONCLUSIONS: Efforts to reduce productivity impairment need to target binge eating as a modifiable risk behavior.

Reductions in employee productivity impairment observed after implementation of web-based worksite health promotion programs.

OBJECTIVE: To assess changes in employee productivity impairment observed after the implementation of several Web-based health promotion programs. METHODS: Health risk assessments and self-report measures of productivity impairment were administered on-line to more than 43,000 participants of Web-based health promotion programs. RESULTS: Reductions in productivity impairment were observed after 1 month of program utilization. Productivity impairment at 90- and 180-day follow-ups also decreased relative to baseline. Improvements in employee health were associated with reductions in employee productivity impairment. CONCLUSION: The use of Web-based health promotion programs was associated with reductions in productivity impairment and improvements in employee health. After the implementation of Web-based health promotion programs, reductions in productivity impairment may be observed before reductions in direct health care costs.