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Howes EM, Parker MK, Misyak SA, DiFeliceantonio AG, Davy BM, Brown LEC, Hedrick VE. The Impact of Weight Bias and Stigma on the 24 h Dietary Recall Process in Adults with Overweight and Obesity: A Pilot Study. Nutrients 2024; 16:191. [PMID: 38257084 PMCID: PMC10818297 DOI: 10.3390/nu16020191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 12/07/2023] [Accepted: 01/03/2024] [Indexed: 01/24/2024] Open
Abstract
People with overweight and obesity tend to both underreport dietary energy intake and experience weight stigma. This exploratory pilot study aimed to determine the relationship between weight bias and weight stigma and energy intake reporting accuracy. Thirty-nine weight-stable adults with BMI ≥ 25 completed three 24 h dietary recalls; indirect calorimetry to measure resting metabolic rate; a survey measuring weight stigma, psychosocial constructs, and physical activity; and a semi-structured qualitative interview. Multiple linear regression was used to determine if weight bias internalization, weight bias toward others, and experiences of weight stigma were predictive of the accuracy of energy reporting. A thematic analysis was conducted for the qualitative interviews. Weight stigma was reported by 64.1% of the sample. Weight stigma constructs did not predict the accuracy of energy intake reporting. People with obesity underreported by a mean of 477 kcals (p = 0.02). People classified as overweight overreported by a mean of 144 kcals, but this was not significant (p = 0.18). Participants reported a desire to report accurate data despite concerns about reporting socially undesirable foods. Future research should quantify the impact of weight stigma on energy reporting in 24 h recalls using a larger, more diverse sample size and objective measures like doubly labeled water for validation.
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Affiliation(s)
- Erica M. Howes
- Department of Human Nutrition, Foods and Exercise, Virginia Tech, Blacksburg, VA 24061, USA; (M.K.P.); (S.A.M.); (A.G.D.); (B.M.D.); (V.E.H.)
| | - Molly K. Parker
- Department of Human Nutrition, Foods and Exercise, Virginia Tech, Blacksburg, VA 24061, USA; (M.K.P.); (S.A.M.); (A.G.D.); (B.M.D.); (V.E.H.)
| | - Sarah A. Misyak
- Department of Human Nutrition, Foods and Exercise, Virginia Tech, Blacksburg, VA 24061, USA; (M.K.P.); (S.A.M.); (A.G.D.); (B.M.D.); (V.E.H.)
| | - Alexandra G. DiFeliceantonio
- Department of Human Nutrition, Foods and Exercise, Virginia Tech, Blacksburg, VA 24061, USA; (M.K.P.); (S.A.M.); (A.G.D.); (B.M.D.); (V.E.H.)
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA 24016, USA
| | - Brenda M. Davy
- Department of Human Nutrition, Foods and Exercise, Virginia Tech, Blacksburg, VA 24061, USA; (M.K.P.); (S.A.M.); (A.G.D.); (B.M.D.); (V.E.H.)
| | | | - Valisa E. Hedrick
- Department of Human Nutrition, Foods and Exercise, Virginia Tech, Blacksburg, VA 24061, USA; (M.K.P.); (S.A.M.); (A.G.D.); (B.M.D.); (V.E.H.)
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Dakin C, Beaulieu K, Hopkins M, Gibbons C, Finlayson G, Stubbs RJ. Do eating behavior traits predict energy intake and body mass index? A systematic review and meta-analysis. Obes Rev 2023; 24:e13515. [PMID: 36305739 PMCID: PMC10078190 DOI: 10.1111/obr.13515] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 09/05/2022] [Accepted: 10/06/2022] [Indexed: 12/27/2022]
Abstract
At present, it is unclear whether eating behavior traits (EBT) predict objectively measured short-term energy intake (EI) and longer-term energy balance as estimated by body mass index (BMI). This systematic review examined the impact of EBT on BMI and laboratory-based measures of EI in adults ( ≥ 18 years) in any BMI category, excluding self-report measures of EI. Articles were searched up until 28th October 2021 using MEDLINE, PsycINFO, EMBASE and Web of Science. Sixteen EBT were identified and the association between 10 EBT, EI and BMI were assessed using a random-effects meta-analysis. Other EBT outcomes were synthesized qualitatively. Risk of bias was assessed with the mixed methods appraisal tool. A total of 83 studies were included (mean BMI = 25.20 kg/m2 , mean age = 27 years and mean sample size = 70). Study quality was rated moderately high overall, with some concerns in sampling strategy and statistical analyses. Susceptibility to hunger (n = 6) and binge eating (n = 7) were the strongest predictors of EI. Disinhibition (n = 8) was the strongest predictor of BMI. Overall, EBT may be useful as phenotypic markers of susceptibility to overconsume or develop obesity (PROSPERO: CRD42021288694).
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Affiliation(s)
- Clarissa Dakin
- Appetite Control and Energy Balance Research Group (ACEB), School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | - Kristine Beaulieu
- Appetite Control and Energy Balance Research Group (ACEB), School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | - Mark Hopkins
- School of Food Science & Nutrition, University of Leeds, Leeds, UK
| | - Catherine Gibbons
- Appetite Control and Energy Balance Research Group (ACEB), School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | - Graham Finlayson
- Appetite Control and Energy Balance Research Group (ACEB), School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, UK
| | - R James Stubbs
- Appetite Control and Energy Balance Research Group (ACEB), School of Psychology, Faculty of Medicine and Health, University of Leeds, Leeds, UK
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Whitton C, Healy JD, Dhaliwal SS, Shoneye C, Harray AJ, Mullan BA, McVeigh JA, Boushey CJ, Kerr DA. Demographic and psychosocial correlates of measurement error and reactivity bias in a four-day image-based mobile food record among adults with overweight and obesity. Br J Nutr 2022; 129:1-39. [PMID: 35587722 PMCID: PMC9899562 DOI: 10.1017/s0007114522001532] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 04/02/2022] [Accepted: 05/11/2022] [Indexed: 11/06/2022]
Abstract
Improving dietary reporting among people living with obesity is challenging as many factors influence reporting accuracy. Reactive reporting may occur in response to dietary recording but little is known about how image-based methods influence this process. Using a 4-day image-based mobile food record (mFRTM), this study aimed to identify demographic and psychosocial correlates of measurement error and reactivity bias, among adults with BMI 25-40kg/m2. Participants (n=155, aged 18-65y) completed psychosocial questionnaires, and kept a 4-day mFRTM. Energy expenditure (EE) was estimated using ≥4 days of hip-worn accelerometer data, and energy intake (EI) was measured using mFRTM. Energy intake: energy expenditure ratios were calculated, and participants in the highest tertile were considered to have Plausible Intakes. Negative changes in EI according to regression slopes indicated Reactive Reporting. Mean EI was 72% (SD=21) of estimated EE. Among participants with Plausible Intakes, mean EI was 96% (SD=13) of estimated EE. Higher BMI (OR 0.81, 95%CI 0.72-0.92) and greater need for social approval (OR 0.31, 95% CI 0.10-0.96), were associated with lower likelihood of Plausible Intakes. Estimated EI decreased by 3% per day of recording (IQR -14%,6%) among all participants. The EI of Reactive Reporters (n=52) decreased by 17%/day (IQR -23%,-13%). A history of weight loss (>10kg) (OR 3.4, 95% CI 1.5-7.8), and higher percentage of daily energy from protein (OR 1.1, 95%CI 1.0-1.2) were associated with greater odds of Reactive Reporting. Identification of reactivity to measurement, as well as Plausible Intakes, is recommended in community-dwelling studies to highlight and address sources of bias.
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Affiliation(s)
- Clare Whitton
- Curtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth6845, Australia
- Curtin Health Innovation Research Institute, Curtin University, Kent Street, GPO Box U1987, Perth6845, Australia
| | - Janelle D. Healy
- Curtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth6845, Australia
- Curtin Health Innovation Research Institute, Curtin University, Kent Street, GPO Box U1987, Perth6845, Australia
| | - Satvinder S. Dhaliwal
- Curtin Health Innovation Research Institute, Curtin University, Kent Street, GPO Box U1987, Perth6845, Australia
- Singapore University of Social Sciences, 463 Clementi Road, 599494, Singapore
- Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, 11800Minden, Pulau Pinang, Malaysia
- Duke-NUS Medical School, National University of Singapore, 8 College Rd, Singapore169857, Singapore
| | - Charlene Shoneye
- Curtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth6845, Australia
| | - Amelia J. Harray
- Curtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth6845, Australia
- Telethon Kids Institute, 15 Hospital Ave, Nedlands, WA6009, Australia
| | - Barbara A. Mullan
- Enable Institute, Curtin University, Kent Street, GPO Box U1987, Perth6845, Australia
| | - Joanne A. McVeigh
- Curtin School of Allied Health, Curtin University, Kent Street, GPO Box U1987, Perth6845, Australia
- Movement Physiology Laboratory, University of Witwatersrand, Johannesburg, South Africa
| | - Carol J. Boushey
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Deborah A. Kerr
- Curtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth6845, Australia
- Curtin Health Innovation Research Institute, Curtin University, Kent Street, GPO Box U1987, Perth6845, Australia
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