American Journal of Health Promotion

To compare the effectiveness of different combinations of social comparison feedback and financial incentives to increase physical activity.

Randomized trial (Clinicaltrials.gov number, NCT02030080).

Philadelphia, Pennsylvania.

Two hundred eighty-six adults.

Twenty-six weeks of weekly feedback on team performance compared to the 50th percentile (n = 100) or the 75th percentile (n = 64) and 13 weeks of weekly lottery-based financial incentive plus feedback on team performance compared to the 50th percentile (n = 80) or the 75th percentile (n = 44) followed by 13 weeks of only performance feedback.

Mean proportion of participant-days achieving the 7000-step goal during the 13-week intervention.

Generalized linear mixed models adjusting for repeated measures and clustering by team.

Compared to the 75th percentile without incentives during the intervention period, the mean proportion achieving the 7000-step goal was significantly greater for the 50th percentile with incentives group (0.45 vs 0.27, difference: 0.18, 95% confidence interval [CI]: 0.04 to 0.32; P = .012) but not for the 75th percentile with incentives group (0.38 vs 0.27, difference: 0.11, 95% CI: −0.05 to 0.27; P = .19) or the 50th percentile without incentives group (0.30 vs 0.27, difference: 0.03, 95% CI: −0.10 to 0.16; P = .67).

Social comparison to the 50th percentile with financial incentives was most effective for increasing physical activity.

To evaluate the impact of a health-promoting price intervention on food sales and profit.

Nonrandomized evaluation study.

Two hospital cafeterias.

Hospital employees (2800) were the priority population.

During baseline phase, healthy versions of existing unhealthy items were introduced. The intervention phase included marketing and price incentives/disincentives for healthy and unhealthy items, with a 35% price differential.

Average and proportional change in sales and impact on financial outcomes were assessed.

Two-way factorial analyses of variance and two-proportion Z-score tests were run to assess change in sales. Independent samples t tests were used to test for changes in profit.

Significant impact was demonstrated on all burger sales in the desired direction during intervention (P < .001). Most notably, the average weekly turkey burger sales at Penrose Hospital (PH) increased 13-fold (10.85-145.59) and became the majority of the market share (51.8%, P < .001). For salads, significant interaction between phase and food type was found at St. Francis Medical Center (SFMC) (P = .002) but not at PH (P = .304). Healthy PH salads were popular at baseline and intervention, comprising the majority of the market share throughout the entire study (68.4%-70.2%, respectively, P = .238). Cafeteria gross sales and burger profit (P < .001) increased at both cafeterias.

Incentivizing consumers through price interventions changed hospital cafeteria food sales in the desired direction while improving the bottom line.

We assessed factors associated with tobacco vendor compliance with India’s Cigarettes and Other Tobacco Products Act (COTPA) provisions regulating tobacco sales and point-of-sale (POS) environments.

Study design was a cross-sectional random sample of tobacco vendors in Mumbai, India (2010).

School-adjacent neighborhoods were the study setting.

Study subjects were tobacco vendors (n = 436).

Face-to-face interviews, and audits of POS environments were used to assess compliance.

Factors associated with compliance were identified using logistic regression.

About 4% of vendors were fully compliant. Although 80% reported compliance with the ban on tobacco sales to minors, only 10% displayed signage about the ban. About 84% were compliant with the two–tobacco advertisement limit; of those displaying advertisements, 67% were compliant with size limits, 68% with content restrictions, and 8% with health warning requirements. Knowledge about fines for noncompliance was associated with compliance with the ban on sales to minors (odds ratio [OR], 2.12; 95% confidence interval [CI], 1.26, 3.56) and signage requirement (OR, 4.42; 95% CI, 1.76, 11.13). Greater compliance with the two-advertisement limit was associated with higher store income from tobacco (OR, .26; 95% CI, .09, .73) and lower neighborhood socioeconomic status (p < .01); the latter was associated with advertisement size limits compliance (p < .05).

Compliance with COTPA provisions was low. Interventions modifying vendor knowledge about provisions and fines may increase compliance, and they should target stores that are reliant on tobacco sales.

To test whether employer matching of employees’ monetary contributions increases employees’ (1) participation in deposit contracts to promote weight loss and (2) weight loss.

A 36-week randomized trial.

Large employer in the northeast United States.

One hundred thirty-two obese employees.

Over 24 weeks, participants were asked to lose 24 pounds and randomized to monthly weigh-ins or daily weigh-ins with monthly opportunities to deposit $1 to $3 per day that was not matched, matched 1:1, or matched 2:1. Deposits and matched funds were returned to participants for each day they were below their goal weight.

Rates of making ≥1 deposit, weight loss at 24 weeks (primary outcome), and 36 weeks.

Deposit rates were compared using χ² tests. Weight loss was compared using t tests.

Among participants eligible to make deposits, 29% made ≥1 deposit and matching did not increase participation. At 24 weeks, control participants gained an average of 1.0 pound, whereas 1:1 match participants lost an average of 5.3 pounds (P = .005). After 36 weeks, control participants gained an average of 2.1 pounds, whereas no match participants lost an average of 5.1 pounds (P = .008).

Participation in deposit contracts to promote weight loss was low, and matching deposits did not increase participation. For deposit contracts to impact population health, ongoing participation will need to be higher.

To evaluate changes in employees’ biometrics over time relative to outcome-based incentive thresholds.

Retrospective cohort analysis of biometric screening participants (n = 26 388).

Large employer primarily in Western United States.

Office, retail, and distribution workforce.

A voluntary outcome-based biometric screening program, incentivized with health insurance premium discounts.

Body mass index (BMI), cholesterol, blood glucose, blood pressure, and nicotine.

Followed were participants from their first year of participation, evaluating changes in measures.

On average, participants who did not meet the incentive threshold at baseline decreased their BMI (1%), glucose (8%), blood pressure (systolic 9%, diastolic 8%), and total cholesterol (8%) by year 2 with improvements generally sustained or continued during each additional year of participation.

On average, individuals at high health risk who participated in a financially incentivized biometric assessment program improved their health indices over time. Further research is needed to understand key determinants that drive health improvement indicated here.

This project examined potential changes in health behaviors following wellness coaching.

In a single cohort study design, wellness coaching participants were recruited in 2011, data were collected through July 2012, and were analyzed through December 2013. Items in the study questionnaire used requested information about 11 health behaviors, self-efficacy for eating, and goalsetting skills.

Worksite wellness center.

One-hundred employee wellness center members with an average age of 42 years; 90% were female and most were overweight or obese.

Twelve weeks of in-person, one-on-one wellness coaching.

Participants completed study questionnaires when they started wellness coaching (baseline), after 12 weeks of wellness coaching, and at a 3-month follow-up.

From baseline to week 12, these 100 wellness coaching participants improved their self-reported health behaviors (11 domains, 0- to 10-point scale) from an average of 6.4 to 7.7 (p < .001), eating selfefficacy from an average of 112 to 142 (on a 0- to 180-point scale; p < .001), and goal-setting skills from an average of 49 to 55 (on a 16- to 80-point scale; p < .001).

These results suggest that participants improved their current health behaviors and learned skills for continued healthy living. Future studies that use randomized controlled trials are needed to establish causality for wellness coaching.

To examine the mediating effect of vitality in the relationship between healthy lifestyle characteristics and health-care and productivity-related costs.

Observational prospective cohort study with 2 measurements. Online questionnaires were filled out in 2013 (T0) and 2014 (T1).

A random sample of a Dutch online interview panel was obtained.

Data of 4231 Dutch adults who had complete data at T0 and T1 were used in the present study. Participants were representative for the Dutch adult population in terms of age, gender, and having chronic disease(s).

Healthy Lifestyle Index (HLI), vitality, and health-care and productivity-related costs. The HLI consisted of the sum of 6 healthy lifestyle characteristics, including a healthy BMI (yes/no), meeting physical activity, fruit, vegetable, and alcohol consumption guidelines (yes/no), and smoking status (yes: non or former smoker/no: current smoker). Health-care and productivity-related costs were measured using a utilization questionnaire.

Linear regression analysis.

The HLI was related to vitality. In addition, vitality was related to health-care costs and productivity-related costs. Furthermore, vitality was found to transmit 28.4% of the effect of HLI on health-care costs and 39.4% of the effect of HLI on productivity-related costs.

Lifestyle was related to vitality and vitality to health-care and productivity-related costs. Vitality mediated the relationship between lifestyle and health-care and productivity-related costs. Therefore, we recommend to sustain and improve both vitality and lifestyle.