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Polygenic risk score for obesity and the quality, quantity, and timing of workplace food purchases: A secondary analysis from the ChooseWell 365 randomized trial.

ABSTRACT: BACKGROUND:The influence of genetic risk for obesity on food choice behaviors is unknown and may be in the causal pathway between genetic risk and weight gain. The aim of this study was to examine associations between genetic risk for obesity and food choice behaviors using objectively assessed workplace food purchases. METHODS AND FINDINGS:This study is a secondary analysis of baseline data collected prior to the start of the "ChooseWell 365" health-promotion intervention randomized control trial. Participants were employees of a large hospital in Boston, MA, who enrolled in the study between September 2016 and February 2018. Cafeteria sales data, collected retrospectively for 3 months prior to enrollment, were used to track the quantity (number of items per 3 months) and timing (median time of day) of purchases, and participant surveys provided self-reported behaviors, including skipping meals and preparing meals at home. A previously validated Healthy Purchasing Score was calculated using the cafeteria traffic-light labeling system (i.e., green = healthy, yellow = less healthy, red = unhealthy) to estimate the healthfulness (quality) of employees' purchases (range, 0%-100% healthy). DNA was extracted and genotyped from blood samples. A body mass index (BMI) genome-wide polygenic score (BMIGPS) was generated by summing BMI-increasing risk alleles across the genome. Additionally, 3 polygenic risk scores (PRSs) were generated with 97 BMI variants previously identified at the genome-wide significance level (P < 5 × 10-8): (1) BMI97 (97 loci), (2) BMICNS (54 loci near genes related to central nervous system [CNS]), and (3) BMInon-CNS (43 loci not related to CNS). Multivariable linear and logistic regression tested associations of genetic risk score quartiles with workplace purchases, adjusted for age, sex, seasonality, and population structure. Associations were considered significant at P < 0.05. In 397 participants, mean age was 44.9 years, and 80.9% were female. Higher genetic risk scores were associated with higher BMI. The highest quartile of BMIGPS was associated with lower Healthy Purchasing Score (-4.8 percentage points [95% CI -8.6 to -1.0]; P = 0.02), higher quantity of food purchases (14.4 more items [95% CI -0.1 to 29.0]; P = 0.03), later time of breakfast purchases (15.0 minutes later [95% CI 1.5-28.5]; P = 0.03), and lower likelihood of preparing dinner at home (Q4 odds ratio [OR] = 0.3 [95% CI 0.1-0.9]; P = 0.03) relative to the lowest BMIGPS quartile. Compared with the lowest quartile, the highest BMICNS quartile was associated with fewer items purchased (P = 0.04), and the highest BMInon-CNS quartile was associated with purchasing breakfast at a later time (P = 0.01), skipping breakfast (P = 0.03), and not preparing breakfast (P = 0.04) or lunch (P = 0.01) at home. A limitation of this study is our data come from a relatively small sample of healthy working adults of European ancestry who volunteered to enroll in a health-promotion study, which may limit generalizability. CONCLUSIONS:In this study, genetic risk for obesity was associated with the quality, quantity, and timing of objectively measured workplace food purchases. These findings suggest that genetic risk for obesity may influence eating behaviors that contribute to weight and could be targeted in personalized workplace wellness programs in the future. TRIAL REGISTRATION:Clinicaltrials.gov NCT02660086.

SUBMITTER: Dashti HS

PROVIDER: S-EPMC7373257 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Polygenic risk score for obesity and the quality, quantity, and timing of workplace food purchases: A secondary analysis from the ChooseWell 365 randomized trial.

Dashti Hassan S HS Hivert Marie-France MF Levy Douglas E DE McCurley Jessica L JL Saxena Richa R Thorndike Anne N AN

PLoS medicine 20200721 7

<h4>Background</h4>The influence of genetic risk for obesity on food choice behaviors is unknown and may be in the causal pathway between genetic risk and weight gain. The aim of this study was to examine associations between genetic risk for obesity and food choice behaviors using objectively assessed workplace food purchases.<h4>Methods and findings</h4>This study is a secondary analysis of baseline data collected prior to the start of the "ChooseWell 365" health-promotion intervention randomi ...[more]

PMID: 32692747

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Project description:BackgroundStudies on the link between chronotype (i.e., propensity for morning or evening preference) and dietary intake have relied on self-reported data, estimating consumption, and chronotype from questionnaires.ObjectivesThis study examined the associations between genetically proxied evening chronotype, objectively estimated workplace dietary choices, and the effectiveness of a behavioral intervention in hospital employees enrolled in the ChooseWell 365 study.MethodsChooseWell 365 was a randomized trial of a 12-mo automated, personalized intervention to prevent weight gain and improve diet. Cafeteria sales data were used to measure the timing and healthfulness of workplace food purchases of employees during the 12-mo-long baseline, intervention, and postintervention follow-up periods. A genome-wide polygenic score for evening chronotype was calculated for all participants and the population was divided into quartiles; the highest quartile indicated the most evening chronotype. Associations between polygenic score quartiles and workplace purchases at baseline, 12 mo, and 24 mo and changes from baseline at 12 and 24 mo were tested using adjusted multivariable linear regression models.ResultsAt baseline, the highest chronotype quartile was associated with self-reported breakfast skipping. Over the 24-mo study, the highest quartile was associated with later timing of the first workplace purchase, but not with the healthfulness of purchases. There were no differences by the chronotype quartile in the effectiveness of the ChooseWell 365 intervention in improving employees' healthy food choices at work.ConclusionsA chronotype polygenic score was associated with breakfast skipping and later workplace mealtimes of hospital employees, but not with the nutritional quality of objectively measured workplace food purchases. In addition, employees across the chronotype spectrum benefited from the workplace healthy eating intervention.This trial was registered at clinicaltrials.gov as NCT02660086 (https://clinicaltrials.gov/ct2/show/NCT02660086?cond=NCT02660086&draw=2&rank=1).

Project description:BackgroundEmployed adults may skip meals due to time or financial constraints, challenging work schedules, or limited workplace food choices. Little is known about the relationship between employees' meal skipping patterns and workplace dietary choices and health.ObjectiveTo examine whether hospital employees' meal skipping patterns were associated with workplace food purchases, dietary quality, and cardiometabolic risk factors (ie, obesity, hypertension, and prediabetes/diabetes).DesignThis is a secondary cross-sectional analysis of baseline data from the ChooseWell 365 randomized controlled trial. Employees reported meal-skipping frequency in a baseline survey. The healthfulness of workplace food purchases was determined with a validated Healthy Purchasing Score (HPS) (range = 0 to 100 where higher scores = healthier purchases) calculated using sales data for participants' purchases in the 3 months before study enrollment. Dietary quality was measured with the 2015 Healthy Eating Index (range = 0 to 100 where higher score = healthier diet) from two 24-hour recalls. Cardiometabolic risk factors were ascertained from clinic measurements.Participants/settingParticipants were 602 hospital employees who regularly visited workplace cafeterias and enrolled in ChooseWell 365, a workplace health promotion study in Boston, MA, during 2016-2018.Main outcome measuresPrimary outcomes were HPS, 2015 Healthy Eating Index, and cardiometabolic risk factors.Statistical analysesRegression analyses examined differences in HPS, 2015 Healthy Eating Index, and cardiometabolic variables by meal skipping frequency, adjusting for demographic characteristics.ResultsParticipants' mean (standard deviation) age was 43.6 (12.2) years and 478 (79%) were women. Overall, 45.8% skipped breakfast, 36.2% skipped lunch, and 24.9% skipped dinner ≥ 1 day/week. Employees who skipped breakfast ≥ 3 days/week (n = 102) had lower HPS (65.1 vs 70.4; P < 0.01) and 2015 Healthy Eating Index score (55.9 vs 62.8; P < 0.001) compared with those who never skipped. Skipping lunch ≥ 3 days/week and dinner ≥ 1 day/week were associated with significantly lower HPS compared with never skipping. Employees who worked nonstandard shifts skipped more meals than those who worked standard shifts. Meal skipping was not associated with obesity or other cardiometabolic variables.ConclusionsSkipping meals was associated with less healthy food purchases at work, and skipping breakfast was associated with lower dietary quality. Future research to understand employees' reasons for skipping meals may inform how employers could support healthier dietary intake at work.

Project description:ImportancePersonalized interventions that leverage workplace data and environments could improve effectiveness, sustainability, and scalability of employee wellness programs.ObjectiveTo test an automated behavioral intervention to prevent weight gain and improve diet using employee cafeteria purchasing data.Design, setting, and participantsThis individual-level randomized clinical trial of a 12-month intervention with 12 months of follow-up was conducted among employees of a hospital in Boston, Massachusetts, who purchased food at on-site cafeterias that used traffic-light labels (ie, green indicates healthy; yellow, less healthy; red, unhealthy). Participants were enrolled September 2016 to February 2018. Data were analyzed from May to September 2020.InterventionsFor 12 months, participants in the intervention group received 2 emails per week with feedback on previous cafeteria purchases and personalized health and lifestyle tips and 1 letter per month with peer comparisons and financial incentives for healthier purchases. Emails and letters were automatically generated using survey, health, and cafeteria data. Control group participants received 1 letter per month with general healthy lifestyle information.Main outcomes and measuresThe main outcome was change in weight from baseline to 12 months and 24 months of follow-up. Secondary outcomes included changes in cafeteria purchases, including proportion of green- and red-labeled purchases and calories purchased per day, from baseline (12 months preintervention) to the intervention (months 1-12) and follow-up (months 13-24) periods. Baseline Healthy Eating Index-15 (HEI-15) scores were compared to HEI-15 scores at 6, 12, and 24 months.ResultsAmong 602 employees enrolled (mean [SD] age, 43.6 [12.2] years; 478 [79.4%] women), 299 were randomized to the intervention group and 303 were randomized to the control group. Baseline mean (SD) body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) was 28.3 (6.6) and HEI-15 score was 60.4 (12.4). There were no between-group differences in weight change at 12 (0.2 [95% CI, -0.6 to 1.0] kg) or 24 (0.6 [95% CI, -0.3 to 1.4] kg) months. Compared with baseline, the intervention group increased green-labeled purchases by 7.3% (95% CI, 5.4% to 9.3%) and decreased red-labeled purchases by 3.9% (95% CI, -5.0% to -2.7%) and calories purchased per day by 49.5 (95% CI, -75.2 to -23.9) kcal more than the control group during the intervention period. In the intervention group, differences in changes in green (4.8% [95% CI, 2.9% to 6.8%]) and red purchases (-3.1% [95% CI, -4.3% to -2.0%]) were sustained at the 24-month follow-up. Differences in changes in HEI-15 scores were not significantly different in the intervention compared with the control group at 6 (2.2 [95% CI, 0 to 4.4]), 12 (1.8 [95% CI, -0.6 to 4.1]), and 24 (1.6, 95% CI, -0.7 to 3.8]) months.Conclusions and relevanceThe findings of this randomized clinical trial suggest that an automated behavioral intervention using workplace cafeteria data improved employees' food choices but did not prevent weight gain over 2 years.Trial registrationClinicalTrials.gov Identifier: NCT02660086.

Project description:BackgroundIt is unknown whether behavioral interventions to improve diet are effective in people with a genetic predisposition to obesity.ObjectivesTo examine associations between BMI genetic risk and changes in weight and workplace purchases by employees participating in a randomized controlled trial of an automated behavioral workplace intervention to promote healthy food choices.MethodsParticipants were hospital employees enrolled in a 12-mo intervention followed by a 12-mo follow-up. Hospital cafeterias utilized a traffic-light labeling system (e.g., green = healthy, red = unhealthy) that was used to calculate a validated Healthy Purchasing Score (HPS; higher = healthier). A weighted genome-wide BMI genetic score was generated by summing BMI-increasing alleles.ResultsThe study included 397 adults of European ancestry (mean age, 44.9 y; 80.9% female). Participants in the highest genetic quartile (Q4) had a lower HPS and higher purchases of red-labeled items relative to participants in the lowest quartile (Q1) at baseline [Q4-Q1 Beta HPS, -4.66 (95% CI, -8.01 to -1.32); red-labeled items, 4.26% (95% CI, 1.45%-7.07%)] and at the 12-mo [HPS, -3.96 (95% CI, -7.5 to -0.41); red-labeled items, 3.20% (95% CI, 0.31%-6.09%)] and 24-mo [HPS, -3.70 (95% CI, -7.40 to 0.00); red-labeled items, 3.48% (95% CI, 0.54%-6.41%)] follow-up periods. In the intervention group, increases in HPS were similar in Q4 and Q1 at 12 mo (Q4-Q1 Beta, 1.04; 95% CI, -2.42 to 4.50). At the 24-mo follow-up, the change in BMI from baseline was similar between Q4 and Q1 (0.17 kg/m2; 95% CI, -0.55 to 0.89 kg/m2) in the intervention group, but higher in Q4 than Q1 (1.20 kg/m2; 95% CI, 0.26-2.13 kg/m2) in the control group. No interaction was evident between the treatment arm and genetic score for BMI or HPS.ConclusionsHaving a high BMI genetic risk was associated with greater increases in BMI and lower quality purchases over 2 y. The 12-mo behavioral intervention improved employees' food choices, regardless of the genetic burden, and may have attenuated weight gain conferred by having the genetic risk.

Project description:BACKGROUND:While leisure-time physical activity (PA) has been associated with reduced risk of cardiometabolic disease, less is known about the relationship between work-related PA and health. Work-related PA is often not a chosen behavior and may be associated with lower socioeconomic status and less control over job-related activities. This study examined whether high work-related PA and leisure-time PA reported by hospital employees were associated with healthier dietary intake and reductions in cardiometabolic risk. METHODS:This was a cross-sectional analysis of 602 hospital employees who used workplace cafeterias and completed the baseline visit for a health promotion study in 2016-2018. Participants completed the International Physical Activity Questionnaire and clinical measures of weight, blood pressure, HbA1c, and lipids. Healthy Eating Index (HEI) scores were calculated from two 24-h dietary recalls, and a Healthy Purchasing Score was calculated based on healthfulness of workplace food/beverage purchases. Regression analyses examined Healthy Purchasing Score, HEI, and obesity, hypertension, hyperlipidemia, and diabetes/prediabetes by quartile of work-related PA, leisure-time PA, and sedentary time. RESULTS:Participants' mean age was 43.6 years (SD = 12.2), 79.4% were female, and 81.1% were white. In total, 30.3% had obesity, 20.6% had hypertension, 26.6% had prediabetes/diabetes, and 32.1% had hyperlipidemia. Median leisure-time PA was 12.0 (IQR: 3.3, 28.0) and median work-related PA was 14.0 (IQR: 0.0, 51.1) MET-hours/week. Higher leisure-time PA was associated with higher workplace Healthy Purchasing Score and HEI (p's < 0.01) and lower prevalence of obesity, diabetes/prediabetes, and hyperlipidemia (p's < 0.05). Work-related PA was not associated with Healthy Purchasing Score, HEI, or cardiometabolic risk factors. Increased sedentary time was associated with lower HEI (p = 0.02) but was not associated with the workplace Healthy Purchasing Score. CONCLUSIONS:Employees with high work-related PA did not have associated reductions in cardiometabolic risk or have healthier dietary intake as did employees reporting high leisure-time PA. Workplace wellness programs should promote leisure-time PA and healthy food choices for all employees, but programs may need to be customized and made more accessible to meet the unique needs of employees who are physically active at work. TRIAL REGISTRATION:This trial was prospectively registered with clinicaltrials.gov (Identifier: NCT02660086) on January 21, 2016. The first participant was enrolled on September 16, 2016.

Dataset Information

Polygenic risk score for obesity and the quality, quantity, and timing of workplace food purchases: A secondary analysis from the ChooseWell 365 randomized trial.

Publications

Polygenic risk score for obesity and the quality, quantity, and timing of workplace food purchases: A secondary analysis from the ChooseWell 365 randomized trial.

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