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Breastfeeding duration is associated with offspring’s adherence to prudent dietary pattern in adulthood: results from the Nutritionist’s Health Study

Published online by Cambridge University Press:  06 June 2019

Ilana Eshriqui
Affiliation:
Graduation Program in Public Health Nutrition, School of Public Health, University of São Paulo, São Paulo, Brazil
Luciana Dias Folchetti
Affiliation:
School of Public Health, University of São Paulo, Brazil
Angélica Marques Martins Valente
Affiliation:
Graduation Program in Epidemiology, School of Public Health, University of São Paulo, São Paulo, Brazil
Bianca de Almeida-Pititto
Affiliation:
Department of Preventive Medicine, Federal University of São Paulo, São Paulo, Brazil
Sandra Roberta G. Ferreira*
Affiliation:
Department of Epidemiology, School of Public Health, University of São Paulo, São Paulo, Brazil
*
Address for correspondence: Sandra Roberta G. Ferreira, Department of Epidemiology, School of Public Health, University of São Paulo, São Paulo, Brazil. Email: [email protected]

Abstract

Little is known about the long-term effect of breastfeeding on dietary habits. We examined the association between breastfeeding duration and adherence to current dietary patterns of young women. This was a cross-sectional analysis of 587 healthy women aged ≤45 years, undergraduates or nutrition graduates. Maternal characteristics and breastfeeding duration [<6; 6–<12; ≥12 months (reference)] were recalled. Diet was assessed using a food frequency questionnaire and patterns were identified using factor analysis by principal component. Adherence to patterns was categorized in tertiles; the first (T1 = reference) was compared to T2 + T3 (moderate-to-high adherence). Logistic regression was performed considering the minimal sufficient adjustment recommended by the directed acyclic graph. Median age was 22 (interquartile range (IQR) 20; 27) years and body mass index (BMI) 22.2 (IQR 20.4; 25.0) kg/m2. The four dietary patterns identified (Processed, Prudent, Brazilian and Lacto-vegetarian) explained 27% of diet variance. Women breastfed for <6 months showed lower chance of moderate-to-high adherence to the Prudent pattern (odds ratio (OR) = 0.53, p = 0.04). Breastfeeding was not associated with the other patterns. Maternal pre-pregnancy BMI was directly associated with moderate-to-high adherence to the Processed pattern (OR = 2.01, p = 0.03) and inversely to the Prudent pattern (OR = 0.52, p = 0.02). Higher adherence to the Brazilian pattern was associated with proxies of low socioeconomic status and the Lacto-vegetarian pattern with the opposite. Confirmation in prospective studies of the association found in this study between breastfeeding with the Prudent pattern in adult offspring could suggest that early feeding practices influence long-term dietary habits, which could then affect the risk of nutrition-related diseases.

Type
Original Article
Copyright
© Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2019

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References

Rich-Edwards, JW, Colditz, GA, Stampfer, MJ, et al.Birthweight and the risk for type 2 diabetes mellitus in adult women. Ann Intern Med. 1999; 130, 278284.CrossRefGoogle ScholarPubMed
Barker, DJ.The origins of the developmental origins theory. J Intern Med. 2007; 261, 412417.CrossRefGoogle ScholarPubMed
Gluckman, PD, Hanson, MA, Beedle, AS.Early life events and their consequences for later disease: a life history and evolutionary perspective. Am J Hum Biol. 2007; 19, 119.CrossRefGoogle ScholarPubMed
Singhal, A, Lucas, A.Early origins of cardiovascular disease: is there a unifying hypothesis? Lancet. 2004; 363, 16421645.CrossRefGoogle Scholar
Kelishadi, R, Farajian, S.The protective effects of breastfeeding on chronic non-communicable diseases in adulthood: a review of evidence. Adv Biomed Res. 2014; 3, 3.CrossRefGoogle ScholarPubMed
WHO. Global Strategy for Infant and Young Child Feeding, 2003. World Health Organization: Geneva.Google Scholar
Venancio, SI, Escuder, MM, Saldiva, SR, Giugliani, ER.Breastfeeding practice in the Brazilian capital cities and the federal district: current status and advances. J Pediatr (Rio J). 2010; 86, 317324.Google ScholarPubMed
Victora, CG, Bahl, R, Barros, AJ, et al.Breastfeeding in the 21st century: epidemiology, mechanisms, and lifelong effect. Lancet. 2016; 387, 475490.CrossRefGoogle ScholarPubMed
Cooke, LJ, Wardle, J, Gibson, EL, Sapochnik, M, Sheiham, A, Lawson, M.Demographic, familial and trait predictors of fruit and vegetable consumption by pre-school children. Public Health Nutr. 2004; 7, 295302.CrossRefGoogle ScholarPubMed
Scholtens, S, Brunekreef, B, Smit, HA, et al.Do differences in childhood diet explain the reduced overweight risk in breastfed children? Obesity (Silver Spring). 2008; 16, 24982503.CrossRefGoogle ScholarPubMed
Yuan, WL, Rigal, N, Monnery-Patris, S, et al.Early determinants of food liking among 5y-old children: a longitudinal study from the EDEN mother-child cohort. Int J Behav Nutr Phys Act. 2016; 13, 20.CrossRefGoogle ScholarPubMed
De Kroon, ML,Renders, CM, Buskermolen, MP, Van Wouwe, JP, van Buuren, S, Hirasing, RA.The Terneuzen Birth Cohort. Longer exclusive breastfeeding duration is associated with leaner body mass and a healthier diet in young adulthood. BMC Pediatr. 2011; 11, 33.CrossRefGoogle Scholar
Robinson, S, Ntani, G, Simmonds, S, et al.Type of milk feeding in infancy and health behaviours in adult life: findings from the Hertfordshire Cohort Study. Br J Nutr. 2013; 109, 11141122.CrossRefGoogle ScholarPubMed
Palou, A, Picó, C.Leptin intake during lactation prevents obesity and affects food intake and food preferences in later life. Appetite. 2009; 52, 249252.CrossRefGoogle ScholarPubMed
Gardner, DS, Rhodes, P.Developmental origins of obesity: programming of food intake or physical activity? Europe PMC Funders Author Manuscripts Adv Exp Med Biol. 2009; 646, 8393.CrossRefGoogle ScholarPubMed
Ong, ZY, Gugusheff, JR, Muhlhausler, BS.Perinatal overnutrition and the programming of food preferences: pathways and mechanisms. J Dev Orig Health Dis. 2012; 3, 299308.CrossRefGoogle ScholarPubMed
Mennella, JA, Jagnow, CP, Beauchamp, GK.Prenatal and postnatal flavor learning by human infants. Pediatrics. 2001; 107, E88.CrossRefGoogle ScholarPubMed
Lioret, S, Betoko, A, Forhan, A, et al.Dietary patterns track from infancy to preschool age: cross-sectional and longitudinal perspectives. J Nutr. 2015; 145, 775782.Google ScholarPubMed
Mikkilä, V, Räsänen, L, Raitakari, OT, Pietinen, P, Viikari, J.Consistent dietary patterns identified from childhood to adulthood: the cardiovascular risk in Young Finns Study. Br J Nutr. 2005; 93, 923931.CrossRefGoogle ScholarPubMed
Victora, CG, Barros, F, Lima, RC, Horta, BL, Wells, J.Anthropometry and body composition of 18 year old men according to duration of breast feeding: birth cohort study from Brazil. BMJ. 2003; 327, 901.CrossRefGoogle ScholarPubMed
Hu, FB.Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol. 2002; 13, 39.CrossRefGoogle ScholarPubMed
Wirfält, E, Drake, I, Wallström, P.What do review papers conclude about food and dietary patterns? Food Nutr Res. 2013; 57: 20523. doi: 10.3402/fnr.v57i0.20523 (Published online)CrossRefGoogle ScholarPubMed
Folchetti, LG, Silva, IT, Almeida-Pititto, B, Ferreira, SR.Nutritionists’ Health Study cohort: a web-based approach of life events, habits and health outcomes. BMJ Open. 2016; 6, e012081.CrossRefGoogle ScholarPubMed
Shlisky, JD, Durward, CM, Zack, MK, Gugger, CK, Campbell, JK, Nickols-Richardson, SM.An energy-reduced dietary pattern, including moderate protein and increased nonfat dairy intake combined with walking promotes beneficial body composition and metabolic changes in women with excess adiposity: a randomized comparative trial. Food Sci Nutr. 2015; 3, 376393.CrossRefGoogle ScholarPubMed
Selem, SS, Carvalho, AM, Verly-Junior, E, et al.Validity and reproducibility of a food frequency questionnaire for adults of São Paulo, Brazil. Rev Bras Epidemiol. 2014; 17, 852859.CrossRefGoogle ScholarPubMed
USDA. National Nutrient Database for Standard Reference, Release 28 (online). Basic Report, Nutrient data for 11114, Cabbage, savoy, raw: United States Department of Agriculture, Agricultural Research Service; 2016.Google Scholar
Gaard, M, Tretli, S, Løken, EB.Dietary fat and the risk of breast cancer: a prospective study of 25,892 Norwegian women. Int J Cancer. 1995; 63, 1317.CrossRefGoogle ScholarPubMed
Parr, CL, Hjartåker, A, Scheel, I, Lund, E, Laake, P, Veierød, MB.Comparing methods for handling missing values in food-frequency questionnaires and proposing k nearest neighbours imputation: effects on dietary intake in the Norwegian Women and Cancer study (NOWAC). Public Health Nutr. 2008; 11, 361370.10.1017/S1368980007000365CrossRefGoogle Scholar
Castro, MA, Baltar, VT, Selem, SS, Marchioni, DM, Fisberg, RM.Empirically derived dietary patterns: interpretability and construct validity according to different factor rotation methods. Cad Saude Publica. 2015; 31, 298310.CrossRefGoogle ScholarPubMed
Newby, PK, Weismayer, C, Akesson, A, Tucker, KL, Wolk, A.Long-term stability of food patterns identified by use of factor analysis among Swedish women. J Nutr. 2006; 136, 626633.CrossRefGoogle ScholarPubMed
Textor, J, Hardt, J, Knüppel, S.DAGitty: a graphical tool for analyzing causal diagrams. Epidemiology. 2011; 22, 745.CrossRefGoogle ScholarPubMed
Olinto, MT, Willett, WC, Gigante, DP, Victora, CG.Sociodemographic and lifestyle characteristics in relation to dietary patterns among young Brazilian adults. Public Health Nutr. 2011; 14, 150159.CrossRefGoogle ScholarPubMed
Teixeira, JA, Castro, TG, Grant, CC, et al.Dietary patterns are influenced by socio-demographic conditions of women in childbearing age: a cohort study of pregnant women. BMC Public Health. 2018; 18, 301.CrossRefGoogle ScholarPubMed
Arruda, SP, da Silva, AA, Kac, G, Goldani, MZ, Bettiol, H, Barbieri, MA.Socioeconomic and demographic factors are associated with dietary patterns in a cohort of young Brazilian adults. BMC Public Health. 2014; 14, 654.CrossRefGoogle Scholar
USDA. A Series of Systematic Reviews on the Relationship Between Dietary Patterns and Health Outcomes. 2014. Evidence Analysis Library Division. United States Department of Agriculture: Virginia.Google Scholar
Grosso, G, Mistretta, A, Frigiola, A, et al.Mediterranean diet and cardiovascular risk factors: a systematic review. Crit Rev Food Sci Nutr. 2014; 54, 593610.CrossRefGoogle ScholarPubMed
Siervo, M, Lara, J, Chowdhury, S, Ashor, A, Oggioni, C, Mathers, JC.Effects of the Dietary Approach to Stop Hypertension (DASH) diet on cardiovascular risk factors: a systematic review and meta-analysis. Br J Nutr. 2015; 113, 115.CrossRefGoogle ScholarPubMed
Park, YM, Steck, SE, Fung, TT, et al.Mediterranean diet, Dietary Approaches to Stop Hypertension (DASH) style diet, and metabolic health in U.S. adults. Clin Nutr. 2016; 36, 13011309.CrossRefGoogle ScholarPubMed
Peltner, J, Thiele, S.Convenience-based food purchase patterns: identification and associations with dietary quality, sociodemographic factors and attitudes. Public Health Nutr. 2018; 21, 558570.CrossRefGoogle ScholarPubMed
Roberts, K, Cade, J, Dawson, J, Holdsworth, M.Empirically derived dietary patterns in UK adults are associated with sociodemographic characteristics, lifestyle, and diet quality. Nutrients. 2018; 10(2), 177.CrossRefGoogle ScholarPubMed
Kell, KP, Judd, SE, Pearson, KE, Shikany, JM, Fernández, JR.Associations between socio-economic status and dietary patterns in US black and white adults. Br J Nutr. 2015;113(11):17921799.CrossRefGoogle ScholarPubMed
Bertin, M, Touvier, M, Dubuisson, C, et al.Dietary patterns of French adults: associations with demographic, socio-economic and behavioural factors. J Hum Nutr Diet. 2016; 29, 241254.CrossRefGoogle ScholarPubMed
Mayén, AL, Marques-Vidal, P, Paccaud, F, Bovet, P, Stringhini, S.Socioeconomic determinants of dietary patterns in low- and middle-income countries: a systematic review. Am J Clin Nutr. 2014; 100, 15201531.CrossRefGoogle ScholarPubMed
Mayén, AL, Bovet, P, Marti-Soler, H, et al.Socioeconomic differences in dietary patterns in an East African country: evidence from the republic of seychelles. PLoS One. 2016; 11, e0155617.CrossRefGoogle Scholar
Chor, D, Cardoso, LO, Nobre, AA, et al.Association between perceived neighbourhood characteristics, physical activity and diet quality: results of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). BMC Public Health. 2016; 16, 751.CrossRefGoogle Scholar
Sichieri, R.Dietary patterns and their associations with obesity in the Brazilian city of Rio de Janeiro. Obes Res. 2002; 10, 4248.CrossRefGoogle ScholarPubMed
Abraham, EC, Godwin, J, Sherriff, A, Armstrong, J.Infant feeding in relation to eating patterns in the second year of life and weight status in the fourth year. Public Health Nutr. 2012; 15, 17051714.CrossRefGoogle ScholarPubMed
Grieger, JA, Scott, J, Cobiac, L.Dietary patterns and breast-feeding in Australian children. Public Health Nutr. 2011; 14, 19391947.CrossRefGoogle ScholarPubMed
Cooper, R, Hyppönen, E, Berry, D, Power, C.Associations between parental and offspring adiposity up to midlife: the contribution of adult lifestyle factors in the 1958 British Birth Cohort Study. Am J Clin Nutr. 2010; 92, 946953.CrossRefGoogle ScholarPubMed
Pei, Z, Flexeder, C, Fuertes, E, et al.Mother’s body mass index and food intake in school-aged children: results of the GINIplus and the LISAplus studies. Eur J Clin Nutr. 2014; 68, 898906.CrossRefGoogle ScholarPubMed
Cadenas-Sanchez, C, Henriksson, P, Henriksson, H, et al.Parental body mass index and its association with body composition, physical fitness and lifestyle factors in their 4-year-old children: results from the MINISTOP trial. Eur J Clin Nutr. 2017; 71, 12001205.CrossRefGoogle ScholarPubMed
Fleten, C, Nystad, W, Stigum, H, et al.Parent-offspring body mass index associations in the Norwegian Mother and Child Cohort Study: a family-based approach to studying the role of the intrauterine environment in childhood adiposity. Am J Epidemiol. 2012; 176, 8392.CrossRefGoogle ScholarPubMed
Masuyama, H, Mitsui, T, Nobumoto, E, Hiramatsu, Y.The effects of high-fat diet exposure in utero on the obesogenic and diabetogenic traits through epigenetic changes in adiponectin and leptin gene expression for multiple generations in female mice. Endocrinology. 2015; 156, 24822491.CrossRefGoogle ScholarPubMed
Roßbach, S, Foterek, K, Schmidt, I, Hilbig, A, Alexy, U.Food neophobia in German adolescents: determinants and association with dietary habits. Appetite. 2016; 101, 184191.CrossRefGoogle ScholarPubMed
Beauchamp, GK, Mennella, JA.Early flavor learning and its impact on later feeding behavior. J Pediatr Gastroenterol Nutr. 2009; 48, S25S30.CrossRefGoogle ScholarPubMed
Miralles, O, Sánchez, J, Palou, A, Picó, C.A physiological role of breast milk leptin in body weight control in developing infants. Obesity (Silver Spring). 2006; 14, 13711377.CrossRefGoogle ScholarPubMed
Schuster, S, Hechler, C, Gebauer, C, Kiess, W, Kratzsch, J.Leptin in maternal serum and breast milk: association with infants’ body weight gain in a longitudinal study over 6 months of lactation. Pediatr Res. 2011; 70, 633637.CrossRefGoogle Scholar
Natland, ST, Andersen, LF, Nilsen, TI, Forsmo, S, Jacobsen, GW.Maternal recall of breastfeeding duration twenty years after delivery. BMC Med Res Methodol. 2012; 12, 179.CrossRefGoogle ScholarPubMed
Chin, HB, Baird, DD, McConnaughey, DR, Weinberg, CR, Wilcox, AJ, Jukic, AM.Long-term recall of pregnancy-related events. Epidemiology. 2017; 28, 575579.CrossRefGoogle ScholarPubMed
Liu, J, Hickson, DA, Musani, SK, et al.Dietary patterns, abdominal visceral adipose tissue, and cardiometabolic risk factors in African Americans: the Jackson heart study. Obesity (Silver Spring). 2013; 21, 644651.CrossRefGoogle ScholarPubMed
Sonnenberg, L, Pencina, M, Kimokoti, R, et al.Dietary patterns and the metabolic syndrome in obese and non-obese Framingham women. Obes Res. 2005; 13, 153162.10.1038/oby.2005.20CrossRefGoogle ScholarPubMed
AlEssa, HB, Malik, VS, Yuan, C, et al.Dietary patterns and cardiometabolic and endocrine plasma biomarkers in US women. Am J Clin Nutr. 2017; 105, 432441.CrossRefGoogle ScholarPubMed
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