Periconceptional dietary quality and metabolic syndrome at 3 years postpartum
Open accessAbstract
BACKGROUND: The period around pregnancy is a critical window in the primordial prevention of cardiovascular disease, but little is known about the role of dietary patterns in cardiometabolic health. Our objective was to determine the association between alignment of periconceptional diet with the 2020 to 2025 Dietary Guidelines for Americans and the risk of metabolic syndrome. METHODS AND RESULTS: We used data from the Nulliparous Pregnancy Outcomes Study: monitoring mothers-to-Be Heart Health Study, a pregnancy cohort study that followed pregnant participants to a median of 3 years postpartum (n=4423). Usual dietary intake in the 3 months around conception was estimated from a Food Frequency Questionnaire. Alignment with the Dietary Guidelines was measured using the Healthy Eating Index-2020, where higher scores represent greater alignment. Postpartum metabolic syndrome was defined using the American Heart Association/National Heart, Lung, and Blood Institute guideline. The prevalence of metabolic syndrome at 3 years postpartum was 20%. After adjusting for confounders, the prevalence of metabolic syndrome was flat up to a periconceptional Healthy Eating Index-2020 total score of ≈60, and then declined steeply as scores increased. Compared with a Healthy Eating Index-2020 score of 60, having scores of 70, 80, and 90 were associated with 2, 4, and 7 fewer cases of metabolic syndrome per 100 individuals, respectively (prevalence differences: -0.02 [95% CI, -0.03, 0]; -0.04 [-0.08, -0.1]; -0.07 [-0.13, -0.02]). CONCLUSIONS: Dietary interventions around conception and systems-level changes to support high diet quality may be important for improving postpartum cardiometabolic health, and helping to reverse or slow the decline in women's cardiometabolic health.
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The quality of periconceptional diets is associated with the probability of developing metabolic syndrome many years later during pregnancy.
“Notably, the quality of periconceptional diets has also been associated with the probability of developing metabolic syndrome many years later during pregnancy, making it crucial to consider early nutritional exposures (7).”
From Maternal nutritional status and the risk of metabolic syndrome in pregnancy: implications for public health nutrition (2026) · cites this paper as [7]
The Discussion (page not available) reports that higher periconceptional diet quality was associated with a lower prevalence of metabolic syndrome 2 to 7 years postpartum. The claim gets the association broadly right but places the outcome during pregnancy; the study measured it after pregnancy. (LLM, conf=0.88)
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The Physical Activity Guidelines for Americans
Piercy, K. L., Troiano, R. P., Ballard, R. M., Carlson, S. A., Fulton, J. E., Galuska, D. A., George, S. M., & Olson, R. D. (2018) · JAMA · doi:10.1001/jama.2018.14854 · Cited by 9,755 · cited 1× · see citing works
“49 We linked the census tract and block group of the participant’s address at enrollment to the 2010 data from the US Census Bureau to calculate the percent of the neighborhood living below the poverty line.”
The ASA Statement on <i>p</i> -Values: Context, Process, and Purpose
Wasserstein, R. L., & Lazar, N. A. (2016) · The American Statistician · doi:10.1080/00031305.2016.1154108 · Cited by 6,306 · see citing works
Validation of a self-administered diet history questionnaire using multiple diet records
Block, G., Woods, M., Potosky, A., & Clifford, C. (1990) · Journal of Clinical Epidemiology · doi:10.1016/0895-4356(90)90099-b · Cited by 1,197 · see citing works
Validation of the Edinburgh postnatal depression scale (EPDS) in non-postnatal women
Cox, J. (1996) · Journal of Affective Disorders · doi:10.1016/0165-0327(96)00008-0 · Cited by 810 · see citing works
Parikh, N. I., Gonzalez, J. M., Anderson, C. A. M., Judd, S. E., Rexrode, K. M., Hlatky, M. A., Gunderson, E. P., Stuart, J. J., Vaidya, D., & On behalf of the American Heart Association Council on Epidemiology and Prevention; Council on Arteriosclerosis, T. A. V. B. C. O. C. A. S. N. A. T. S. C. (2021) · Circulation · doi:10.1161/cir.0000000000000961 · Cited by 743 · see citing works
Weintraub, W. S., Daniels, S. R., Burke, L. E., Franklin, B. A., Goff, D. C., Hayman, L. L., Lloyd-Jones, D., Pandey, D. K., Sanchez, E. J., Schram, A. P., et al. (2011) · Circulation · doi:10.1161/cir.0b013e3182285a81 · Cited by 541 · see citing works
Mehta, L. S., Warnes, C. A., Bradley, E., Burton, T., Economy, K., Mehran, R., Safdar, B., Sharma, G., Wood, M., Valente, A. M., et al. (2020) · Circulation · doi:10.1161/cir.0000000000000772 · Cited by 464 · see citing works
Kris‐Etherton, P. M., Petersen, K. S., Velarde, G., Barnard, N. D., Miller, M., Ros, E., O'Keefe, J. H., Williams, K., Horn, L. V., Na, M., et al. (2020) · Journal of the American Heart Association · doi:10.1161/jaha.119.014433 · Cited by 132 · see citing works
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Research works printed but not linked: 66
- [1]Hirode G, Wong RJ. Trends in the prevalence of metabolic syndrome in the United States, 2011–2016. JAMA. 2020; 323: 2526– 2528. doi: 10.1001/jama.2020.4501 32573660 PMC7312413 · DOI
- [2]Gami AS, Witt BJ, Howard DE, Erwin PJ, Gami LA, Somers VK, Montori VM. Metabolic syndrome and risk of incident cardiovascular events and death: a systematic review and meta‐analysis of longitudinal studies. J Am Coll Cardiol. 2007; 49: 403– 414. doi: 10.1016/j.jacc.2006.09.032 17258085 · DOI · Paper page
- [3]Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC Jr, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005; 112: 2735– 2752. doi: 10.1161/circulationaha.105.169404 16157765 · DOI · Paper page
- [4]Ford ES, Li C. Metabolic syndrome and health‐related quality of life among U.S. adults. Ann Epidemiol. 2008; 18: 165– 171. doi: 10.1016/j.annepidem.2007.10.009 18280918 · DOI
- [5]Gillman MW. Primordial prevention of cardiovascular disease. Circulation. 2015; 131: 599– 601. doi: 10.1161/circulationaha.115.014849 25605661 PMC4349501 · DOI
- [6]McGill HC Jr, McMahan CA. Determinants of atherosclerosis in the young. Pathobiological Determinants of Atherosclerosis in Youth (PDAY) Research Group. Am J Cardiol. 1998; 82: 30t– 36t. doi: 10.1016/s0002-9149(98)00720-6 9860371 · DOI · Paper page
- [9]Brown HL, Warner JJ, Gianos E, Gulati M, Hill AJ, Hollier LM, Rosen SE, Rosser ML, Wenger NK. Promoting risk identification and reduction of cardiovascular disease in women through collaboration with obstetricians and gynecologists: a presidential advisory from the American Heart Association and the American College of Obstetricians and Gynecologists. Circulation. 2018; 137: e843– e852. doi: 10.1161/cir.0000000000000582 29748185 · DOI · Paper page
- [11]Sattar N, Greer IA. Pregnancy complications and maternal cardiovascular risk: opportunities for intervention and screening? BMJ. 2002; 325: 157– 160. doi: 10.1136/bmj.325.7356.157 12130616 PMC1123678 · DOI
- [12]Rich‐Edwards JW, Fraser A, Lawlor DA, Catov JM. Pregnancy characteristics and women's future cardiovascular health: an underused opportunity to improve women's health? Epidemiol Rev. 2014; 36: 57– 70. doi: 10.1093/epirev/mxt006 24025350 PMC3873841 · DOI · Paper page
- [13]Lane‐Cordova AD, Khan SS, Grobman WA, Greenland P, Shah SJ. Long‐term cardiovascular risks associated with adverse pregnancy outcomes: JACC review topic of the week. J Am Coll Cardiol. 2019; 73: 2106– 2116. doi: 10.1016/j.jacc.2018.12.092 31023435 · DOI
- [14]Gooding HC, Gidding SS, Moran AE, Redmond N, Allen NB, Bacha F, Burns TL, Catov JM, Grandner MA, Harris KM, et al. Challenges and opportunities for the prevention and treatment of cardiovascular disease among young adults: report from a National Heart, Lung, and Blood Institute Working Group. J Am Heart Assoc. 2020; 9: e016115. doi: 10.1161/JAHA.120.016115 32993438 PMC7792379 · DOI
- [15]Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, Himmelfarb CD, Khera A, Lloyd‐Jones D, McEvoy JW, et al. 2019 ACC/AHA Guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019; 140: e596– e646. doi: 10.1161/cir.0000000000000678 30879355 PMC7734661 · DOI · Paper page
- [16]van Horn L, Carson JA, Appel LJ, Burke LE, Economos C, Karmally W, Lancaster K, Lichtenstein AH, Johnson RK, Thomas RJ, et al. Recommended dietary pattern to achieve adherence to the American Heart Association/American College of Cardiology (AHA/ACC) guidelines: a scientific statement from the American Heart Association. Circulation. 2016; 134: e505– e529. doi: 10.1161/cir.0000000000000462 27789558 · DOI
- [17]Yu E, Malik VS, Hu FB. Cardiovascular disease prevention by diet modification: JACC health promotion series. J Am Coll Cardiol. 2018; 72: 914– 926. doi: 10.1016/j.jacc.2018.02.085 30115231 PMC6100800 · DOI
- [18]Lichtenstein AH, Appel LJ, Vadiveloo M, Hu FB, Kris‐Etherton PM, Rebholz CM, Sacks FM, Thorndike AN, van Horn L, Wylie‐Rosett J. 2021 dietary guidance to improve cardiovascular health: a scientific statement from the American Heart Association. Circulation. 2021; 144: e472– e487. doi: 10.1161/cir.0000000000001031 34724806 · DOI · Paper page
- [19]Bodnar LM, Kirkpatrick SI, Parisi SM, Jin Q, Naimi AI. Periconceptional dietary patterns and adverse pregnancy and birth outcomes. J Nutr. 2024; 154: 680– 690. doi: 10.1016/j.tjnut.2023.12.013 38122847 PMC10900249 · DOI
- [20]Bodnar LM, Cartus AR, Kirkpatrick SI, Himes KP, Kennedy EH, Simhan HN, Grobman WA, Duffy JY, Silver RM, Parry S, et al. Machine learning as a strategy to account for dietary synergy: an illustration based on dietary intake and adverse pregnancy outcomes. Am J Clin Nutr. 2020; 111: 1235– 1243. doi: 10.1093/ajcn/nqaa027 32108865 PMC7266693 · DOI
- [21]Raghavan R, Dreibelbis C, Kingshipp BL, Wong YP, Abrams B, Gernand AD, Rasmussen KM, Siega‐Riz AM, Stang J, Casavale KO, et al. Dietary patterns before and during pregnancy and birth outcomes: a systematic review. Am J Clin Nutr. 2019; 109: 729S– 756S. doi: 10.1093/ajcn/nqy353 30982873 · DOI
- [22]Raghavan R, Dreibelbis C, Kingshipp BL, Wong YP, Abrams B, Gernand AD, Rasmussen KM, Siega‐Riz AM, Stang J, Casavale KO, et al. Dietary patterns before and during pregnancy and maternal outcomes: a systematic review. Am J Clin Nutr. 2019; 109: 705s– 728s. doi: 10.1093/ajcn/nqy216 30982868 · DOI
- [23]Miller PE, Reedy J, Kirkpatrick SI, Krebs‐Smith SM. The United States food supply is not consistent with dietary guidance: evidence from an evaluation using the healthy eating Index‐2010. J Acad Nutr Diet. 2015; 115: 95– 100. doi: 10.1016/j.jand.2014.08.030 25441965 PMC4276446 · DOI
- [24]Hirsch JA, Zhao Y, Melly S, Moore KA, Berger N, Quinn J, Rundle A, Lovasi GS. National trends and disparities in retail food environments in the USA between 1990 and 2014. Public Health Nutr. 2023; 26: 1052– 1062. doi: 10.1017/s1368980023000058 36644895 PMC10191888 · DOI
- [25]Haas DM, Ehrenthal DB, Koch MA, Catov JM, Barnes SE, Facco F, Parker CB, Mercer BM, Bairey‐Merz CN, Silver RM, et al. Pregnancy as a window to future cardiovascular health: design and implementation of the nuMoM2b heart health study. Am J Epidemiol. 2016; 183: 519– 530. doi: 10.1093/aje/kwv309kwv309 26825925 PMC4782765 · DOI
- [26]Haas DM, Parker CB, Wing DA, Parry S, Grobman WA, Mercer BM, Simhan HN, Hoffman MK, Silver RM, Wadhwa P, et al. A description of the methods of the Nulliparous Pregnancy Outcomes Study: monitoring mothers‐to‐be (nuMoM2b). Am J Obstet Gynecol. 2015; 212: 539.e1– 539.e24. doi: 10.1016/j.ajog.2015.01.019 PMC4387083 25648779 · DOI
- [27]Catov JM, McNeil RB, Marsh DJ, Mercer BM, Merz CNB, Parker CB, Pemberton VL, Saade GR, Chen YD, Chung JH, et al. Early pregnancy atherogenic profile in a first pregnancy and hypertension risk 2 to 7 years after delivery. J Am Heart Assoc. 2021; 10: e017216. doi: 10.1161/JAHA.120.017216 33619977 PMC8174276 · DOI
- [28]Block G, Coyle LM, Hartman AM, Scoppa SM. Revision of dietary analysis software for the Health Habits and History Questionnaire. Am J Epidemiol. 1994; 139: 1190– 1196. doi: 10.1093/oxfordjournals.aje.a116965 8209877 · DOI
- [29]Block G, Hartman AM, Dresser CM, Carroll MD, Gannon J, Gardner L. A data‐based approach to diet questionnaire design and testing. Am J Epidemiol. 1986; 124: 453– 469. doi: 10.1093/oxfordjournals.aje.a114416 3740045 · DOI
- [30]Block G, Wakimoto P, Jensen C, Mandel S, Green RR. Validation of a food frequency questionnaire for Hispanics. Prev Chronic Dis. 2006; 3: A77. 16776878 PMC1636705
- [33]Kristal AR, Feng Z, Coates RJ, Oberman A, George V. Associations of race/ethnicity, education, and dietary intervention with the validity and reliability of a food frequency questionnaire: the Women's health trial feasibility study in minority populations. Am J Epidemiol. 1997; 146: 856– 869. doi: 10.1093/oxfordjournals.aje.a009203 9384206 · DOI
- [34]Siega‐Riz AM, Savitz DA, Zeisel SH, Thorp JM, Herring A. Second trimester folate status and preterm birth. Am J Obstet Gynecol. 2004; 191: 1851– 1857. doi: 10.1016/j.ajog.2004.07.076 15592264 · DOI
- [35]Bodnar LM, Simhan HN, Parker CB, Meier H, Mercer BM, Grobman WA, Haas DM, Wing DA, Hoffman MK, Parry S, et al. Racial or ethnic and socioeconomic inequalities in adherence to national dietary guidance in a large cohort of US pregnant women. J Acad Nutr Diet. 2017; 117: 867– 877. doi: 10.1016/j.jand.2017.01.016 28320597 PMC5446928 · DOI
- [36]Petersen JM, Naimi AI, Kirkpatrick SI, Bodnar LM. Equal weighting of the healthy eating index‐2010 components may not be appropriate for pregnancy. J Nutr. 2022; 152: 1886– 1894. doi: 10.1093/jn/nxac120 35641231 PMC9361739 · DOI
- [37]Shams‐White MM, Pannucci TE, Lerman JL, Herrick KA, Zimmer M, Meyers Mathieu K, Stoody EE, Reedy J. Healthy eating index‐2020: review and update process to reflect the dietary guidelines for Americans, 2020–2025. J Acad Nutr Diet. 2023; 123: 1280– 1288. doi: 10.1016/j.jand.2023.05.015 37201748 PMC10524328 · DOI
- [41]NHLBI Obesity Education Initiative Expert Panel on the Identification E, and Treatment of Obesity in Adults (US). Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults: The Evidence Report. National Heart, Lung, and Blood Institute; 1998. Accessed July 2. https://www.ncbi.nlm.nih.gov/books/NBK2003/
- [42]World Health Organization. Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser. 1995; 854: 1– 452. 8594834
- [43]Whelton PK, Carey RM, Aronow WS, Casey DE Jr, Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension. 2018; 71: e13– e115. doi: 10.1161/hyp.0000000000000065 29133356 · DOI · Paper page
- [44]Ross R, Neeland IJ, Yamashita S, Shai I, Seidell J, Magni P, Santos RD, Arsenault B, Cuevas A, Hu FB, et al. Waist circumference as a vital sign in clinical practice: a consensus statement from the IAS and ICCR Working Group on Visceral Obesity. Nat Rev Endocrinol. 2020; 16: 177– 189. doi: 10.1038/s41574-019-0310-7 32020062 PMC7027970 · DOI · Paper page
- [45]Koren G, Boskovic R, Hard M, Maltepe C, Navioz Y, Einarson A. Motherisk‐PUQE (pregnancy‐unique quantification of emesis and nausea) scoring system for nausea and vomiting of pregnancy. Am J Obstet Gynecol. 2002; 186: S228– S231. doi: 10.1067/mob.2002.123054 12011891 · DOI
- [46]Levine DW, Dailey ME, Rockhill B, Tipping D, Naughton MJ, Shumaker SA. Validation of the Women's Health Initiative Insomnia Rating Scale in a multicenter controlled clinical trial. Psychosom Med. 2005; 67: 98– 104. doi: 10.1097/01.psy.0000151743.58067.f0 15673630 · DOI
- [47]Spielberger CD, Gorsuch RL, Lushene RE. Manual for State‐Trait Anxiety Inventory (Self‐Evaluation Questionnaire). Palo Alto, CA: Consulting Psychologists Press; 1970.
- [50]Facco FL, Parker CB, Reddy UM, Silver RM, Koch MA, Louis JM, Basner RC, Chung JH, Nhan‐Chang CL, Pien GW, et al. Association between sleep‐disordered breathing and hypertensive disorders of pregnancy and gestational diabetes mellitus. Obstet Gynecol. 2017; 129: 31– 41. doi: 10.1097/AOG.0000000000001805 27926645 PMC5512455 · DOI · Paper page
- [51]American College of Obstetricians and Gynecologists. Hypertension in pregnancy. Report of the American College of Obstetricians and Gynecologists' Task Force on Hypertension in Pregnancy. Obstet Gynecol. 2013; 122: 1122– 1131. doi: 10.1097/01.Aog.0000437382.03963.88 24150027 · DOI
- [52]Reedy J, Lerman JL, Krebs‐Smith SM, Kirkpatrick SI, Pannucci TE, Wilson MM, Subar AF, Kahle LL, Tooze JA. Evaluation of the healthy eating index‐2015. J Acad Nutr Diet. 2018; 118: 1622– 1633. doi: 10.1016/j.jand.2018.05.019 30146073 PMC6718954 · DOI · Paper page
- [53]Harrell FE Jr, Lee KL, Pollock BG. Regression models in clinical studies: determining relationships between predictors and response. J Natl Cancer Inst. 1988; 80: 1198– 1202. doi: 10.1093/jnci/80.15.1198 3047407 · DOI
- [54]Royston P. Multiple imputation of missing values: further update of ice, with an emphasis on categorical variables. Stata J. 2009; 9: 466– 477. doi: 10.1177/1536867X0900900308 · DOI · Paper page
- [55]Kontopantelis E, White IR, Sperrin M, Buchan I. Outcome‐sensitive multiple imputation: a simulation study. BMC Med Res Methodol. 2017; 17: 2. doi: 10.1186/s12874-016-0281-5 28068910 PMC5220613 · DOI · Paper page
- [56]Zhang J, Dashti SG, Carlin JB, Lee KJ, Moreno‐Betancur M. Should multiple imputation be stratified by exposure group when estimating causal effects via outcome regression in observational studies? BMC Med Res Methodol. 2023; 23: 42. doi: 10.1186/s12874-023-01843-6 36797679 PMC9933305 · DOI
- [57]Shrier I, Platt RW. Reducing bias through directed acyclic graphs. BMC Med Res Methodol. 2008; 8: 70. doi: 10.1186/1471-2288-8-70 18973665 PMC2601045 · DOI
- [58]Ukoha EP, Snavely ME, Hahn MU, Steinauer JE, Bryant AS. Toward the elimination of race‐based medicine: replace race with racism as preeclampsia risk factor. Am J Obstet Gynecol. 2022; 227: 593– 596. doi: 10.1016/j.ajog.2022.05.048 35640703 · DOI
- [59]Pearl J. Causal diagrams for empirical research. Biometrika. 1995; 82: 669– 688. doi: 10.1093/biomet/82.4.669 · DOI · Paper page
- [60]Hernán MA, Hernández‐Díaz S, Robins JM. A structural approach to selection bias. Epidemiology. 2004; 15: 615– 625. doi: 10.1097/01.ede.0000135174.63482.43 15308962 · DOI · Paper page
- [62]Greenland S, Senn SJ, Rothman KJ, Carlin JB, Poole C, Goodman SN, Altman DG. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 2016; 31: 337– 350. doi: 10.1007/s10654-016-0149-3 27209009 PMC4877414 · DOI · Paper page
- [63]Fabiani R, Naldini G, Chiavarini M. Dietary patterns and metabolic syndrome in adult subjects: a systematic review and meta‐analysis. Nutrients. 2019; 11: 2056. doi: 10.3390/nu11092056 31480732 PMC6770202 · DOI
- [64]Shab‐Bidar S, Golzarand M, Hajimohammadi M, Mansouri S. A posteriori dietary patterns and metabolic syndrome in adults: a systematic review and meta‐analysis of observational studies|Public Health Nutrition|Cambridge Core. Public Health Nutr. 2018; 21: 1681– 1692. doi: 10.1017/S1368980018000216 29559025 PMC10261419 · DOI
- [65]Calton EK, James AP, Pannu PK, Soares MJ. Certain dietary patterns are beneficial for the metabolic syndrome: reviewing the evidence. Nutr Res. 2014; 34: 559– 568. doi: 10.1016/j.nutres.2014.06.012 25150114 · DOI
- [66]Duffey KJ, Steffen LM, Horn LV, Jacobs DR, Popkin BM. Dietary patterns matter: diet beverages and cardiometabolic risks in the longitudinal Coronary Artery Risk Development in Young Adults (CARDIA) Study. Am J Clin Nutr. 2012; 95: 909– 915. doi: 10.3945/ajcn.111.026682 22378729 PMC3302365 · DOI
- [67]Deshmukh‐Taskar PR, O'Neil CE, Nicklas TA, Yang S‐J, Liu Y, Gustat J, Berenson GS. Dietary patterns associated with metabolic syndrome, sociodemographic and lifestyle factors in young adults: the Bogalusa Heart Study|Public Health Nutrition|Cambridge Core. Public Health Nutr. 2009; 12: 2493– 2503. doi: 10.1017/S1368980009991261 19744354 PMC2792890 · DOI
- [68]Wilson MM, Reedy J, Krebs‐Smith SM. American diet quality: where it is, where it is heading, and what it could Be. J Acad Nutr Diet. 2016; 116: 302– 310.e301. doi: 10.1016/j.jand.2015.09.020 26612769 PMC4733413 · DOI
- [70]Krebs‐Smith SM, Pannucci TE, Subar AF, Kirkpatrick SI, Lerman JL, Tooze JA, Wilson MM, Reedy J. Update of the healthy eating index: HEI‐2015. J Acad Nutr Diet. 2018; 118: 1591– 1602. doi: 10.1016/j.jand.2018.05.021 30146071 PMC6719291 · DOI
- [71]Liese AD, Krebs‐Smith SM, Subar AF, George SM, Harmon BE, Neuhouser ML, Boushey CJ, Schap TE, Reedy J. The dietary patterns methods project: synthesis of findings across cohorts and relevance to dietary guidance. J Nutr. 2015; 145: 393– 402. doi: 10.3945/jn.114.205336 25733454 PMC4336525 · DOI
- [72]National Academies of Sciences E, Medicine. Redesigning the Process for Establishing the Dietary Guidelines for Americans. Washington, DC: The National Academies Press; 2017. 29232083
- [73]Kipnis V, Subar AF, Midthune D, Freedman LS, Ballard‐Barbash R, Troiano RP, Bingham S, Schoeller DA, Schatzkin A, Carroll RJ. Structure of dietary measurement error: results of the OPEN biomarker study. Am J Epidemiol. 2003; 158: 14– 21; discussion 22‐16. doi: 10.1093/aje/kwg091 12835281 · DOI
- [74]Subar AF, Kipnis V, Troiano RP, Midthune D, Schoeller DA, Bingham S, Sharbaugh CO, Trabulsi J, Runswick S, Ballard‐Barbash R, et al. Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: the OPEN study. Am J Epidemiol. 2003; 158: 1– 13. doi: 10.1093/aje/kwg092 12835280 · DOI · Paper page
- [75]Subar AF, Freedman LS, Tooze JA, Kirkpatrick SI, Boushey C, Neuhouser ML, Thompson FE, Potischman N, Guenther PM, Tarasuk V, et al. Addressing current criticism regarding the value of self‐report dietary data. J Nutr. 2015; 145: 2639– 2645. doi: 10.3945/jn.115.219634 26468491 PMC4656907 · DOI · Paper page
- [76]Schafer JL, Graham JW. Missing data: our view of the state of the art. Psychol Methods. 2002; 7: 147– 177. doi: 10.1037/1082-989X.7.2.147 12090408 · DOI · Paper page
- [77]Stephenson J, Heslehurst N, Hall J, Schoenaker D, Hutchinson J, Cade JE, Poston L, Barrett G, Crozier SR, Barker M, et al. Before the beginning: nutrition and lifestyle in the preconception period and its importance for future health. Lancet. 2018; 391: 1830– 1841. doi: 10.1016/S0140-6736(18)30311-8 29673873 PMC6075697 · DOI · Paper page
- [79]Block G, Thompson FE, Hartman AM, Larkin FA, Guire KE. Comparison of two dietary questionnaires validated against multiple dietary records collected during a 1‐year period. J Am Diet Assoc. 1992; 92: 686– 693. doi: 10.1016/S0002-8223(21)00707-0 1607564 · DOI
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Wu, Y., Gao, Z., Gou, Y., Yan, L., & Duan, Y. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1862412
- Authors
- Bodnar, L. M., Jin, Q., Naimi, A. I., Simhan, H. N., Catov, J. M., Parisi, S. M., & Kirkpatrick, S. I.
- Affiliations
- University of Pittsburgh (US)
- Emory University (US)
- University of Waterloo (CA)
- Corresponding author
- Bodnar, Lisa M.
- ORCID
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- Journal of the American Heart Association
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- 2024-08-20
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- 13
- Issue
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- e035555-e035555
- ISSN
- 2047-9980 (ISSN-L)
- PMC
- PMC11963925
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- W4401698228
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- National Institutes of Health (UL1TR001108, UL1TR000124, UL1TR000439, UL1TR000153, 1TR000124)
- University of California, Irvine (U10 HD063048, U10 HD063047, U10 HD063037, U10 HD063041, U10 HD063020, U10 HD063053, U10 HD063072, U10 HD063036, UL1 TR000153, U10 HD063046)
- National Heart, Lung, and Blood Institute (U10HL119991, U10HL120006, U10HL119992, U10HL120034, HL119991, HL119990, U10HL119990, U10HL120019, U10HL119989, U10HL120018, U10HL119993)
- National Institute of Child Health and Human Development
- Office of Research on Women's Health
- National Center for Advancing Translational Sciences (TR001108)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD102313, U10-HL119992, U10HD063053, U10HD063046, U10HD063020, U10HD063072, HD063036, U10HD063048, U10HD063041, U10HD063047, U10HD063036, U10HD063037)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Birth, Development, and Health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Keywords
- diet quality, metabolic syndrome, Healthy Eating Index-2020, Dietary Guidelines for Americans, nulliparous women, pregnancy
- MeSH terms
- Diet, Healthy, Adult, Female, Humans, Pregnancy, Risk Factors, Time Factors, United States, Prevalence, Risk Assessment, Metabolic Syndrome, Postpartum Period
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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