Dietary patterns before and during pregnancy and small for gestational age in Japan: a prospective birth cohort study.

Birth weight Dietary patterns Maternal nutrition Partial least squares Pregnancy Principal component analysis Prospective birth cohort studies Reduced rank regression Small for gestational age

Journal

Nutrition journal
ISSN: 1475-2891
Titre abrégé: Nutr J
Pays: England
ID NLM: 101152213

Informations de publication

Date de publication:
16 09 2022
Historique:
received: 12 11 2021
accepted: 30 08 2022
entrez: 16 9 2022
pubmed: 17 9 2022
medline: 21 9 2022
Statut: epublish

Résumé

Although small for gestational age (SGA) is a serious problem worldwide, the association of dietary patterns before and during pregnancy with SGA risk is unclear. We evaluated this association among Japanese pregnant women using three methods: reduced rank regression (RRR) and partial least squares (PLS), methods for extracting dietary patterns that can explain the variation of response variables, and principal component analysis (PCA), a method for extracting dietary patterns of the population. Between July 2013 and March 2017, 22,493 pregnant women were recruited to the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study, a population-based prospective birth cohort study in Japan. Information on dietary intake was obtained using food frequency questionnaires, and dietary patterns were extracted using RRR, PLS, and PCA. Information on birth weight was obtained from obstetric records, and the birth weight SD score and SGA were defined by the method of the Japan Pediatric Society. The associations of dietary patterns with birth weight SD score and SGA risk were investigated using multiple linear regression and multiple logistic regression, respectively. A total of 17,728 mother-child pairs were included. The birth weight SD score was 0.15 ± 0.96, and the prevalence of SGA was 6.3%. The dietary patterns extracted by RRR and PLS were similar and characterized by a high intake of cereals and fruits and a low intake of alcoholic and non-alcoholic beverages in both pre- to early pregnancy and from early to mid-pregnancy. Higher adoption of the RRR and PLS patterns in both periods was associated with an increased birth weight SD score and lower risk of SGA. In contrast, the PCA1 pattern was not associated with birth weight SD score or SGA risk in either period. Although the PCA2 pattern was associated with increased birth weight SD score from early to mid-pregnancy, no other associations with birth weight SD score or SGA risk were observed. The dietary pattern with a high intake of cereals and fruits and a low intake of alcoholic and non-alcoholic beverages before and during pregnancy was associated with a decreased SGA risk in Japan.

Sections du résumé

BACKGROUND
Although small for gestational age (SGA) is a serious problem worldwide, the association of dietary patterns before and during pregnancy with SGA risk is unclear. We evaluated this association among Japanese pregnant women using three methods: reduced rank regression (RRR) and partial least squares (PLS), methods for extracting dietary patterns that can explain the variation of response variables, and principal component analysis (PCA), a method for extracting dietary patterns of the population.
METHODS
Between July 2013 and March 2017, 22,493 pregnant women were recruited to the Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study, a population-based prospective birth cohort study in Japan. Information on dietary intake was obtained using food frequency questionnaires, and dietary patterns were extracted using RRR, PLS, and PCA. Information on birth weight was obtained from obstetric records, and the birth weight SD score and SGA were defined by the method of the Japan Pediatric Society. The associations of dietary patterns with birth weight SD score and SGA risk were investigated using multiple linear regression and multiple logistic regression, respectively.
RESULTS
A total of 17,728 mother-child pairs were included. The birth weight SD score was 0.15 ± 0.96, and the prevalence of SGA was 6.3%. The dietary patterns extracted by RRR and PLS were similar and characterized by a high intake of cereals and fruits and a low intake of alcoholic and non-alcoholic beverages in both pre- to early pregnancy and from early to mid-pregnancy. Higher adoption of the RRR and PLS patterns in both periods was associated with an increased birth weight SD score and lower risk of SGA. In contrast, the PCA1 pattern was not associated with birth weight SD score or SGA risk in either period. Although the PCA2 pattern was associated with increased birth weight SD score from early to mid-pregnancy, no other associations with birth weight SD score or SGA risk were observed.
CONCLUSIONS
The dietary pattern with a high intake of cereals and fruits and a low intake of alcoholic and non-alcoholic beverages before and during pregnancy was associated with a decreased SGA risk in Japan.

Identifiants

pubmed: 36114492
doi: 10.1186/s12937-022-00808-7
pii: 10.1186/s12937-022-00808-7
pmc: PMC9479276
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

57

Informations de copyright

© 2022. The Author(s).

Références

BJOG. 2011 Nov;118(12):1411-21
pubmed: 21729235
Eur J Obstet Gynecol Reprod Biol. 2008 Dec;141(2):95-9
pubmed: 18760523
Evid Based Complement Alternat Med. 2006 Mar;3(1):49-59
pubmed: 16550223
Lancet. 2014 Jul 12;384(9938):189-205
pubmed: 24853593
Eur J Clin Nutr. 2014 Feb;68(2):215-22
pubmed: 24327121
Eur J Epidemiol. 2014 Oct;29(10):725-34
pubmed: 25179792
Indian J Endocrinol Metab. 2013 Jan;17(1):60-8
pubmed: 23776854
Curr Genomics. 2011 Aug;12(5):371-8
pubmed: 22294879
Med Hypotheses. 2000 Jul;55(1):88-90
pubmed: 11021334
Carcinogenesis. 2009 Feb;30(2):308-14
pubmed: 19056931
Nutrients. 2016 Apr 28;8(5):
pubmed: 27136584
J Basic Clin Physiol Pharmacol. 2018 Oct 2;30(2):153-162
pubmed: 30281514
Eur J Clin Nutr. 2022 Feb;76(2):261-269
pubmed: 34131299
J Physiol. 2012 Mar 15;590(6):1377-87
pubmed: 22289909
Public Health Nutr. 2016 Feb;19(2):195-203
pubmed: 26784586
PLoS One. 2019 Aug 16;14(8):e0220942
pubmed: 31419246
Am J Epidemiol. 2004 May 15;159(10):935-44
pubmed: 15128605
Eur J Clin Nutr. 2019 Sep;73(9):1270-1282
pubmed: 30459338
J Nutr. 2014 Jul;144(7):1075-80
pubmed: 24790026
Nutr Rev. 2016 Feb;74(2):69-82
pubmed: 26747887
Am J Clin Nutr. 2016 Nov;104(5):1416-1423
pubmed: 27733407
Clin Pediatr Endocrinol. 2019;28(4):97-103
pubmed: 31666762
J Epidemiol. 2016 Sep 5;26(9):493-511
pubmed: 27374138
Eur J Clin Nutr. 2010 Feb;64(2):184-93
pubmed: 19920847
Eur J Clin Nutr. 2008 Apr;62(4):463-70
pubmed: 17392696
PLoS One. 2016 Aug 22;11(8):e0161298
pubmed: 27548287
Br J Nutr. 2018 Aug;120(4):435-444
pubmed: 29784070
Am J Clin Nutr. 2011 Aug;94(2):501-9
pubmed: 21697074
World Health Organ Tech Rep Ser. 1995;854:1-452
pubmed: 8594834
Endocrine. 2002 Oct;19(1):13-22
pubmed: 12583599
Nutrients. 2019 Feb 20;11(2):
pubmed: 30791647
Matern Child Nutr. 2017 Oct;13(4):
pubmed: 27928892
Front Psychiatry. 2019 Apr 04;10:207
pubmed: 31019473
PLoS Med. 2018 Dec 18;15(12):e1002717
pubmed: 30562348
Nutrients. 2019 Dec 18;12(1):
pubmed: 31861388
Paediatr Perinat Epidemiol. 2012 Jul;26 Suppl 1:285-301
pubmed: 22742616
Sci Rep. 2020 Mar 26;10(1):5491
pubmed: 32218503
Br J Nutr. 2012 Jan;107(1):135-45
pubmed: 21733314
Alcohol Res Health. 2003;27(2):134-42
pubmed: 15303623
Nutr J. 2020 Aug 3;19(1):80
pubmed: 32746847
Br J Nutr. 2020 May 28;123(10):1176-1186
pubmed: 32019629
Am J Epidemiol. 2008 Dec 15;168(12):1433-43
pubmed: 18945692
BJOG. 2015 Sep;122(10):1313-21
pubmed: 25677044
Science. 2018 Aug 3;361(6401):440
pubmed: 30072522
Toxicol Appl Pharmacol. 2016 Jun 1;300:77-81
pubmed: 27020608
Am J Epidemiol. 2004 Mar 1;159(5):467-74
pubmed: 14977642
Z Ernahrungswiss. 1990 Mar;29(1):39-46
pubmed: 2333720
Br J Nutr. 2010 Jun;103(11):1665-73
pubmed: 20211035
Am J Clin Nutr. 2007 Oct;86(4):1104-10
pubmed: 17921389
Am J Epidemiol. 1986 Jul;124(1):17-27
pubmed: 3521261
PLoS One. 2020 Jul 27;15(7):e0236330
pubmed: 32717744
Int J Epidemiol. 2020 Feb 1;49(1):18-19m
pubmed: 31504573

Auteurs

Takahiro Yamashita (T)

Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
Innovation Division, KAGOME CO., LTD, Nasushiobara, Japan.

Taku Obara (T)

Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan. obara-t@hosp.tohoku.ac.jp.
Division of Molecular Epidemiology, Environment and Genome Research Center, Graduate School of Medicine, Tohoku University, Sendai, Japan. obara-t@hosp.tohoku.ac.jp.
Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Japan. obara-t@hosp.tohoku.ac.jp.

Yudai Yonezawa (Y)

Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
Innovation Division, KAGOME CO., LTD, Nasushiobara, Japan.

Ippei Takahashi (I)

Division of Molecular Epidemiology, Environment and Genome Research Center, Graduate School of Medicine, Tohoku University, Sendai, Japan.

Mami Ishikuro (M)

Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
Division of Molecular Epidemiology, Environment and Genome Research Center, Graduate School of Medicine, Tohoku University, Sendai, Japan.

Keiko Murakami (K)

Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
Division of Molecular Epidemiology, Environment and Genome Research Center, Graduate School of Medicine, Tohoku University, Sendai, Japan.

Fumihiko Ueno (F)

Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
Division of Molecular Epidemiology, Environment and Genome Research Center, Graduate School of Medicine, Tohoku University, Sendai, Japan.

Aoi Noda (A)

Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
Division of Molecular Epidemiology, Environment and Genome Research Center, Graduate School of Medicine, Tohoku University, Sendai, Japan.
Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Japan.

Tomomi Onuma (T)

Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
Division of Molecular Epidemiology, Environment and Genome Research Center, Graduate School of Medicine, Tohoku University, Sendai, Japan.

Noriyuki Iwama (N)

Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
Department of Gynecology and Obstetrics, Graduate School of Medicine, Tohoku University, Sendai, Japan.

Hirotaka Hamada (H)

Department of Gynecology and Obstetrics, Graduate School of Medicine, Tohoku University, Sendai, Japan.

Junichi Sugawara (J)

Department of Gynecology and Obstetrics, Graduate School of Medicine, Tohoku University, Sendai, Japan.
Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.

Shigenori Suzuki (S)

Innovation Division, KAGOME CO., LTD, Nasushiobara, Japan.

Hiroyuki Suganuma (H)

Innovation Division, KAGOME CO., LTD, Nasushiobara, Japan.

Masatoshi Saito (M)

Department of Gynecology and Obstetrics, Graduate School of Medicine, Tohoku University, Sendai, Japan.

Nobuo Yaegashi (N)

Department of Gynecology and Obstetrics, Graduate School of Medicine, Tohoku University, Sendai, Japan.
Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.

Shinichi Kuriyama (S)

Division of Molecular Epidemiology, Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
Division of Molecular Epidemiology, Environment and Genome Research Center, Graduate School of Medicine, Tohoku University, Sendai, Japan.
Division of Disaster Public Health, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH