The accelerator, the brake, and the terrain: associations of reward-related eating, self-regulation, and the home food environment with diet quality during pregnancy and postpartum in the pregnancy eating attributes study (PEAS) cohort

Tonja R Nansel, Leah M Lipsky, Myles Faith, Aiyi Liu, Anna Maria Siega-Riz, Tonja R Nansel, Leah M Lipsky, Myles Faith, Aiyi Liu, Anna Maria Siega-Riz

Abstract

Background: Neurobehavioral factors, including reward-related eating and self-regulation, in conjunction with the food environment, may influence dietary behaviors. However, these constructs have not been examined in pregnancy and postpartum, a time of changing appetite and eating behaviors, and when dietary intake has implications for maternal and child health. This study examined associations of reward-related eating, self-regulation, and the home food environment with pregnancy and postpartum diet quality.

Methods: Participants in the Pregnancy Eating Attributes Study observational cohort were enrolled at ≤12 weeks gestation and followed through one-year postpartum. Pregnancy and postpartum Healthy Eating Index-2015 (HEI-total), and adequacy and moderation scores, respectively, were calculated by pooling 24-h diet recalls administered each trimester and during 2, 6, and 12 months postpartum. Participants completed four measures of reward-related eating - Modified Yale Food Addiction Scale (mYFAS), Power of Food Scale (PFS), Multiple Choice Procedure (MCP), and Reinforcing Value of Food Questionnaire (RVFQ); two measures of self-regulation - Barratt Impulsiveness Scale (BIS) and Delay of Gratification Inventory (DGI); and a Home Food Inventory (HFI), yielding obesogenic (OBES) and fruit/vegetables (FV) scores. Linear regression analyses estimated associations of reward-related eating, self-regulation, and home food environment with diet quality during pregnancy and postpartum, adjusting for sociodemographic characteristics.

Results: Pregnancy HEI-total was inversely associated with PFS (β = - 0.14 ± 0.05, p = 0.009), mYFAS(β = - 0.14 ± 0.06, p = 0.02), 2 of the 5 RVFQ indices, MCP (β = - 0.14 ± 0.05, p = 0.01), and DGI food subscale (β = 0.23 ± 0.05, p < 0.001), but associations of postpartum HEI-total with reward-related eating measures and self-regulation were small and not statistically significant. Pregnancy and postpartum HEI-total were associated inversely with HFI-OBES (β = - 0.17 ± 0.06, p = 0.004 and β = - 0.19 ± 0.07, p = 0.006, respectively), and positively with HFI-FV (β = 0.21 ± 0.05, p < 0.001 and β = 0.17 ± 0.06, p = 0.009, respectively).

Conclusions: Associations of poorer diet quality with greater reward-related eating during pregnancy but not postpartum suggests the need to better understand differences in the determinants of eating behaviors and approaches to circumvent or moderate reward-related eating to facilitate more optimal diet quality across this critical period.

Trial registration: Clinicaltrials.gov . URL - Registration ID - NCT02217462 . Date of registration - August 13, 2014.

Keywords: Delay of gratification; Diet quality; Home food environment; Impulsivity; Postpartum; Pregnancy; Reward-related eating; Self-regulation.

Conflict of interest statement

The authors have no competing interests to declare.

Figures

Fig. 1
Fig. 1
Flow of recruitment and participation in the Pregnancy Eating Attributes Study (PEAS)
Fig. 2
Fig. 2
Interactions of home food environment and self-regulation with reward-related eating on diet quality. RVFQ, Reinforcing Value of Food Questionnaire; MCP, Multiple Choice Procedure; HFI-FV, fruit and vegetable home food environment score; HFI-OBES, obesogenic home food environment score; BIS-15, Barratt Impulsiveness Scale; DGI, Delaying Gratification Inventory

References

    1. Olson CM, Strawderman MS. Modifiable behavioral factors in a biopsychosocial model predict inadequate and excessive gestational weight gain. J Am Diet Assoc. 2003;103(1):48–54. doi: 10.1053/jada.2003.50001.
    1. Shin D, Lee KW, Song WO. Dietary patterns during pregnancy are associated with risk of gestational diabetes mellitus. Nutrients. 2015;7(11):9369–9382. doi: 10.3390/nu7115472.
    1. Shapiro AL, Kaar JL, Crume TL, Starling AP, Siega-Riz AM, Ringham BM, et al. Maternal diet quality in pregnancy and neonatal adiposity: the healthy start study. Int J Obes (Lond) 2016;40(7):1056–1062. doi: 10.1038/ijo.2016.79.
    1. Wen LM, Flood VM, Simpson JM, Rissel C, Baur LA. Dietary behaviours during pregnancy: findings from first-time mothers in Southwest Sydney, Australia. Int J Behav Nutr Phys Act. 2010;7:13. doi: 10.1186/1479-5868-7-13.
    1. Rifas-Shiman SL, Rich-Edwards JW, Kleinman KP, Oken E, Gillman MW. Dietary quality during pregnancy varies by maternal characteristics in project viva: a US cohort. J Am Diet Assoc. 2009;109(6):1004–1011. doi: 10.1016/j.jada.2009.03.001.
    1. Siega-Riz AM, Bodnar LM, Savitz DA. What are pregnant women eating? Nutrient and food group differences by race. Am J Obstet Gynecol. 2002;186(3):480–486. doi: 10.1067/mob.2002.121078.
    1. Kominiarek MA, Rajan P. Nutrition recommendations in pregnancy and lactation. Med Clin North Am. 2016;100(6):1199–1215. doi: 10.1016/j.mcna.2016.06.004.
    1. Martin-Gronert MS, Ozanne SE. Maternal nutrition during pregnancy and health of the offspring. Biochem Soc Trans. 2006;34(Pt 5):779–782. doi: 10.1042/BST0340779.
    1. Alonso-Alonso M, Woods SC, Pelchat M, Grigson PS, Stice E, Farooqi S, et al. Food reward system: current perspectives and future research needs. Nutr Rev. 2015;73(5):296–307. doi: 10.1093/nutrit/nuv002.
    1. Alsio J, Olszewski PK, Levine AS, Schioth HB. Feed-forward mechanisms: addiction-like behavioral and molecular adaptations in overeating. Front Neuroendocrinol. 2012;33(2):127–139. doi: 10.1016/j.yfrne.2012.01.002.
    1. Lowe MR, Butryn ML. Hedonic hunger: a new dimension of appetite? Physiol Behav. 2007;91(4):432–439. doi: 10.1016/j.physbeh.2007.04.006.
    1. Lutter M, Nestler EJ. Homeostatic and hedonic signals interact in the regulation of food intake. J Nutr. 2009;139(3):629–632. doi: 10.3945/jn.108.097618.
    1. Stoeckel LE, Weller RE, Cook EW, 3rd, Twieg DB, Knowlton RC, Cox JE. Widespread reward-system activation in obese women in response to pictures of high-calorie foods. Neuroimage. 2008;41(2):636–647. doi: 10.1016/j.neuroimage.2008.02.031.
    1. Leigh SJ, Morris MJ. The role of reward circuitry and food addiction in the obesity epidemic: an update. Biol Psychol. 2018;131:31–42. doi: 10.1016/j.biopsycho.2016.12.013.
    1. Van Dillen LF, Andrade J. Derailing the streetcar named desire. Cognitive distractions reduce individual differences in cravings and unhealthy snacking in response to palatable food. Appetite. 2016;96:102–110. doi: 10.1016/j.appet.2015.09.013.
    1. Mies GW, Treur JL, Larsen JK, Halberstadt J, Pasman JA, Vink JM. The prevalence of food addiction in a large sample of adolescents and its association with addictive substances. Appetite. 2017;118:97–105. doi: 10.1016/j.appet.2017.08.002.
    1. Schuz B, Schuz N, Ferguson SG. It's the power of food: individual differences in food cue responsiveness and snacking in everyday life. Int J Behav Nutr Phys Act. 2015;12:149. doi: 10.1186/s12966-015-0312-3.
    1. Nansel TR, Lipsky LM, Eisenberg MH, Haynie DL, Liu D, Simons-Morton B. Greater food reward sensitivity is associated with more frequent intake of discretionary foods in a nationally representative sample of young adults. Front Nutr. 2016;3:33. doi: 10.3389/fnut.2016.00033.
    1. Pursey KM, Collins CE, Stanwell P, Burrows TL. Foods and dietary profiles associated with 'food addiction' in young adults. Addict Behav Rep. 2015;2:41–48.
    1. Lemeshow AR, Rimm EB, Hasin DS, Gearhardt AN, Flint AJ, Field AE, et al. Food and beverage consumption and food addiction among women in the Nurses' health studies. Appetite. 2018;121:186–197. doi: 10.1016/j.appet.2017.10.038.
    1. Padmanabhan U, Summerbell CD, Heslehurst N. A qualitative study exploring pregnant women's weight-related attitudes and beliefs in UK: the BLOOM study. BMC Pregnancy Childbirth. 2015;15:99. doi: 10.1186/s12884-015-0522-3.
    1. Orloff NC, Hormes JM. Pickles and ice cream! Food cravings in pregnancy: hypotheses, preliminary evidence, and directions for future research. Front Psychol. 2014;5:1076. doi: 10.3389/fpsyg.2014.01076.
    1. Appelhans BM. Neurobehavioral inhibition of reward-driven feeding: implications for dieting and obesity. Obesity (Silver Spring) 2009;17(4):640–647. doi: 10.1038/oby.2008.638.
    1. Carr KA, Daniel TO, Lin H, Epstein LH. Reinforcement pathology and obesity. Curr Drug Abuse Rev. 2011;4(3):190–196. doi: 10.2174/1874473711104030190.
    1. van den Bos R, de Ridder D. Evolved to satisfy our immediate needs: self-control and the rewarding properties of food. Appetite. 2006;47(1):24–29. doi: 10.1016/j.appet.2006.02.008.
    1. Lee PC, Dixon JB. Food for thought: reward mechanisms and hedonic overeating in obesity. Curr Obes Rep. 2017;6(4):353–361. doi: 10.1007/s13679-017-0280-9.
    1. Daniel TO, Stanton CM, Epstein LH. The future is now: reducing impulsivity and energy intake using episodic future thinking. Psychol Sci. 2013;24(11):2339–2342. doi: 10.1177/0956797613488780.
    1. Guerrieri R, Nederkoorn C, Jansen A. How impulsiveness and variety influence food intake in a sample of healthy women. Appetite. 2007;48(1):119–122. doi: 10.1016/j.appet.2006.06.004.
    1. Appelhans BM, Woolf K, Pagoto SL, Schneider KL, Whited MC, Liebman R. Inhibiting food reward: delay discounting, food reward sensitivity, and palatable food intake in overweight and obese women. Obesity (Silver Spring, Md) 2011;19(11):2175–2182. doi: 10.1038/oby.2011.57.
    1. Rollins BY, Dearing KK, Epstein LH. Delay discounting moderates the effect of food reinforcement on energy intake among non-obese women. Appetite. 2010;55(3):420–425. doi: 10.1016/j.appet.2010.07.014.
    1. Ely AV, Howard J, Lowe MR. Delayed discounting and hedonic hunger in the prediction of lab-based eating behavior. Eat Behav. 2015;19:72–75. doi: 10.1016/j.eatbeh.2015.06.015.
    1. Higgs S. Cognitive processing of food rewards. Appetite. 2016;104:10–17. doi: 10.1016/j.appet.2015.10.003.
    1. Nunnery DL, Labban JD, Dharod JM. Interrelationship between food security status, home availability of variety of fruits and vegetables and their dietary intake among low-income pregnant women. Public Health Nutr. 2018;21(4):807–815. doi: 10.1017/S1368980017003032.
    1. Gorin AA, Wing RR, Fava JL, Jakicic JM, Jeffery R, West DS, et al. Weight loss treatment influences untreated spouses and the home environment: evidence of a ripple effect. Int J Obes (Lond) 2008;32(11):1678–1684. doi: 10.1038/ijo.2008.150.
    1. Kegler MC, Alcantara I, Haardorfer R, Gazmararian JA, Ballard D, Sabbs D. The influence of home food environments on eating behaviors of overweight and obese women. J Nutr Educ Behav. 2014;46(3):188–196. doi: 10.1016/j.jneb.2014.01.001.
    1. Ledoux TA, Mama SK, O'Connor DP, Adamus H, Fraser ML, Lee RE. Home availability and the impact of weekly stressful events are associated with fruit and vegetable intake among African American and Hispanic/Latina women. J Obes. 2012;2012:737891. doi: 10.1155/2012/737891.
    1. Patterson RE, Kristal AR, Shannon J, Hunt JR, White E. Using a brief household food inventory as an environmental indicator of individual dietary practices. Am J Public Health. 1997;87(2):272–275. doi: 10.2105/AJPH.87.2.272.
    1. Trapp GS, Hickling S, Christian HE, Bull F, Timperio AF, Boruff B, et al. Individual, social, and environmental correlates of healthy and unhealthy eating. Health Educ Behav. 2015;42(6):759–768. doi: 10.1177/1090198115578750.
    1. Nansel TR, Lipsky LM, Siega-Riz AM, Burger K, Faith M, Liu A. Pregnancy eating attributes study (PEAS): a cohort study examining behavioral and environmental influences on diet and weight change in pregnancy and postpartum. BMC Nutr. 2016;2:45. 10.1186/s40795-016-0083-5. Epub 2016 Jul15. PMID: 28663822; PMCID: PMC5486996.
    1. Kirkpatrick SI, Subar AF, Douglass D, Zimmerman TP, Thompson FE, Kahle LL, et al. Performance of the automated self-administered 24-hour recall relative to a measure of true intakes and to an interviewer-administered 24-h recall. Am J Clin Nutr. 2014;100(1):233–240. doi: 10.3945/ajcn.114.083238.
    1. Thompson FE, Dixit-Joshi S, Potischman N, Dodd KW, Kirkpatrick SI, Kushi LH, et al. Comparison of interviewer-administered and automated self-administered 24-hour dietary recalls in 3 diverse integrated health systems. Am J Epidemiol. 2015;181(12):970–978. doi: 10.1093/aje/kwu467.
    1. Rhee JJ, Sampson L, Cho E, Hughes MD, Hu FB, Willett WC. Comparison of methods to account for implausible reporting of energy intake in epidemiologic studies. Am J Epidemiol. 2015;181(4):225–233. doi: 10.1093/aje/kwu308.
    1. Most J, Dervis S, Haman F, Adamo KB, Redman LM. Energy intake requirements in pregnancy. Nutrients. 2019;11(8):1812. 10.3390/nu11081812. PMID: 31390778; PMCID: PMC6723706.
    1. US. Department of Health and Human Services and U.S. Department of Agriculture . 2015–2020 dietary guidelines for Americans. 8 2015.
    1. McGowan CA, McAuliffe FM. Maternal dietary patterns and associated nutrient intakes during each trimester of pregnancy. Public Health Nutr. 2013;16(1):97–107. doi: 10.1017/S1368980012000997.
    1. Rifas-Shiman SL, Rich-Edwards JW, Willett WC, Kleinman KP, Oken E, Gillman MW. Changes in dietary intake from the first to the second trimester of pregnancy. Paediatr Perinat Epidemiol. 2006;20(1):35–42. doi: 10.1111/j.1365-3016.2006.00691.x.
    1. Savard C, Lemieux S, Carbonneau É, Provencher V, Gagnon C, Robitaille J, et al. Trimester-specific assessment of diet quality in a sample of Canadian pregnant women. Int J Environ Res Public Health. 2019;16(3):311. doi: 10.3390/ijerph16030311.
    1. National Cancer Institute Division of Cancer Control & Population Sciences. Healthy Eating Index SAS code [Available from: . Accessed 19 Aug 2020.
    1. Cappelleri JC, Bushmakin AG, Gerber RA, Leidy NK, Sexton CC, Karlsson J, et al. Evaluating the power of food scale in obese subjects and a general sample of individuals: development and measurement properties. Int J Obes (Lond) 2009;33(8):913–922. doi: 10.1038/ijo.2009.107.
    1. Forman EM, Butryn ML, Juarascio AS, Bradley LE, Lowe MR, Herbert JD, et al. The mind your health project: a randomized controlled trial of an innovative behavioral treatment for obesity. Obesity (Silver Spring, Md) 2013;21(6):1119–1126. doi: 10.1002/oby.20169.
    1. Yoshikawa T, Tanaka M, Ishii A, Watanabe Y. Immediate neural responses of appetitive motives and its relationship with hedonic appetite and body weight as revealed by magnetoencephalography. Med Sci Monit. 2013;19:631–640. doi: 10.12659/MSM.889234.
    1. Flint AJ, Gearhardt AN, Corbin WR, Brownell KD, Field AE, Rimm EB. Food-addiction scale measurement in 2 cohorts of middle-aged and older women. Am J Clin Nutr. 2014;99(3):578–586. doi: 10.3945/ajcn.113.068965.
    1. Epstein LH, Dearing KK, Roba LG. A questionnaire approach to measuring the relative reinforcing efficacy of snack foods. Eat Behav. 2010;11(2):67–73. doi: 10.1016/j.eatbeh.2009.09.006.
    1. Griffiths R, JR Troisi I, Silvermian K, Miumford G. Multiple-choice procedure: an efficient approach for investigating drug reinforcement in humans. Behav Pharmacol. 1993;4(1):3–14. doi: 10.1097/00008877-199302000-00001.
    1. Koffarnus MN, Franck CT, Stein JS, Bickel WK. A modified exponential behavioral economic demand model to better describe consumption data. Exp Clin Psychopharmacol. 2015;23(6):504–512. doi: 10.1037/pha0000045.
    1. Schmitz JM, Sayre SL, Hokanson PS, Spiga R. Assessment of the relative reinforcement value of smoking and drinking using a multiple-choice measurement strategy. Nicotine Tob Res. 2003;5(5):729–733. doi: 10.1080/1462220031000158618.
    1. Lim J, Wood A, Green BG. Derivation and evaluation of a labeled hedonic scale. Chem Senses. 2009;34(9):739–751. doi: 10.1093/chemse/bjp054.
    1. Spinella M. Normative data and a short form of the Barratt impulsiveness scale. Int J Neurosci. 2007;117(3):359–368. doi: 10.1080/00207450600588881.
    1. Hoerger M, Quirk SW, Weed NC. Development and validation of the delaying gratification inventory. Psychol Assess. 2011;23(3):725. doi: 10.1037/a0023286.
    1. Fulkerson JA, Nelson MC, Lytle L, Moe S, Heitzler C, Pasch KE. The validation of a home food inventory. Int J Behav Nutr Phys Act. 2008;5(1):55. doi: 10.1186/1479-5868-5-55.
    1. U.S. Census Bureau PD, Fertility & Family Statistics Branch . Current population survey: definitions and explanations. 2004.
    1. Blau LE, Lipsky LM, Dempster KW, Eisenbeerg Colman MH, Siega-Riz AM, Faith MSF, et al. Women's experience and understanding of food cravings in pregnancy: a qualitative study in women receiving prenatal care at the University of North Carolina- Chapel Hill. J Acad Nutr Diet. 2020;120(5):815–24. 10.1016/j.jand.2019.09.020. Epub 2019 Dec 6. PMID: 31813756; PMCID: PMC7186144.
    1. Davies K, Wardle J. Body image and dieting in pregnancy. J Psychosom Res. 1994;38(8):787–799. doi: 10.1016/0022-3999(94)90067-1.
    1. Lipsky LM, Strawderman MS, Olson CM. Maternal weight change between 1 and 2 years postpartum: the importance of 1 year weight retention. Obesity (Silver Spring, Md) 2012;20(7):1496–1502. doi: 10.1038/oby.2012.41.
    1. Garza KB, Ding M, Owensby JK, Zizza CA. Impulsivity and fast-food consumption: a cross-sectional study among working adults. J Acad Nutr Diet. 2016;116(1):61–68. doi: 10.1016/j.jand.2015.05.003.
    1. Guthrie JF, Lin BH, Frazao E. Role of food prepared away from home in the American diet, 1977-78 versus 1994-96: changes and consequences. J Nutr Educ Behav. 2002;34(3):140–150. doi: 10.1016/S1499-4046(06)60083-3.
    1. Quick facts: Chapel Hill, North Carolina [Internet]. [cited 07/30/2020]. Available from: .

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