Maternal dietary patterns during pregnancy derived by reduced-rank regression and birth weight in the Chinese population

Few studies have investigated the association between maternal dietary patterns (DP) during pregnancy, derived from reduced-rank regression (RRR), and fetal growth. This study aims to identify DP during pregnancy associated with macro- and micronutrient intakes, using the RRR method, and to examine...

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Veröffentlicht in:British journal of nutrition 2020-05, Vol.123 (10), p.1176-1186
Hauptverfasser: Liu, Danmeng, Cheng, Yue, Mi, Baibing, Zeng, Lingxia, Qu, Pengfei, Li, Shanshan, Zhang, Ruo, Qi, Qi, Wu, Chenlu, Gao, Xiangyu, Liu, Yezhou, Dang, Shaonong, Yan, Hong
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container_title British journal of nutrition
container_volume 123
creator Liu, Danmeng
Cheng, Yue
Mi, Baibing
Zeng, Lingxia
Qu, Pengfei
Li, Shanshan
Zhang, Ruo
Qi, Qi
Wu, Chenlu
Gao, Xiangyu
Liu, Yezhou
Dang, Shaonong
Yan, Hong
description Few studies have investigated the association between maternal dietary patterns (DP) during pregnancy, derived from reduced-rank regression (RRR), and fetal growth. This study aims to identify DP during pregnancy associated with macro- and micronutrient intakes, using the RRR method, and to examine their relationship with birth weight (BW). We used data of 7194 women from a large-scale cross-sectional survey in Northwest China. Dietary protein, carbohydrate, haem Fe density and the ratio of PUFA and MUFA:SFA were used as the intermediate variables in the RRR model to extract DP. Generalised estimating equation models were applied to evaluate the associations between DP and BW and related outcomes (including BW z-score, low birth weight (LBW) and small for gestational age (SGA)). Four DP during pregnancy were identified. Socio-demographically disadvantaged pregnant women were more likely to have lower BW and lower adherence to DP1 (high legumes, soyabean products, vegetables and animal-source foods, with relative low wheat and oils). Women with medium and high adherence to DP1 had significantly increased BW (medium 28·6 (95 % CI 7·1, 50·1); high 25·2 (95 % CI 2·7, 47·6)) and BW z-score and had significantly reduced risks of LBW and SGA. The associations were stronger among women with babies
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This study aims to identify DP during pregnancy associated with macro- and micronutrient intakes, using the RRR method, and to examine their relationship with birth weight (BW). We used data of 7194 women from a large-scale cross-sectional survey in Northwest China. Dietary protein, carbohydrate, haem Fe density and the ratio of PUFA and MUFA:SFA were used as the intermediate variables in the RRR model to extract DP. Generalised estimating equation models were applied to evaluate the associations between DP and BW and related outcomes (including BW z-score, low birth weight (LBW) and small for gestational age (SGA)). Four DP during pregnancy were identified. Socio-demographically disadvantaged pregnant women were more likely to have lower BW and lower adherence to DP1 (high legumes, soyabean products, vegetables and animal-source foods, with relative low wheat and oils). Women with medium and high adherence to DP1 had significantly increased BW (medium 28·6 (95 % CI 7·1, 50·1); high 25·2 (95 % CI 2·7, 47·6)) and BW z-score and had significantly reduced risks of LBW and SGA. The associations were stronger among women with babies &lt;3100 g. There is no association between other DP and outcomes. Higher adherence to the DP that was high in legumes, soyabean products, vegetables and animal-source foods was associated with improved BW in the Chinese pregnant women, particularly among those with disadvantageous socio-demographic conditions.</description><identifier>ISSN: 0007-1145</identifier><identifier>EISSN: 1475-2662</identifier><identifier>DOI: 10.1017/S0007114520000392</identifier><identifier>PMID: 32019629</identifier><language>eng</language><publisher>England: Cambridge University Press</publisher><subject>Adult ; Animal-based foods ; Babies ; Birth Weight ; Carbohydrates ; Childbirth &amp; labor ; China ; Cross-Sectional Studies ; Diet ; Diet - adverse effects ; Diet - statistics &amp; numerical data ; Diet Surveys ; Edible oils ; Feeding Behavior - physiology ; Female ; Fetal Development ; Fetuses ; Food ; Food sources ; Gestational Age ; Humans ; Infant, Low Birth Weight ; Infant, Newborn ; Infant, Small for Gestational Age ; Legumes ; Leguminous plants ; Low birth weight ; Male ; Maternal Nutritional Physiological Phenomena ; Mortality ; Nutrients ; Nutrition research ; Pregnancy ; Principal Component Analysis ; Proteins ; Regression Analysis ; Risk reduction ; Small for gestational age ; Statistical analysis ; Vegetables ; Weight ; Womens health</subject><ispartof>British journal of nutrition, 2020-05, Vol.123 (10), p.1176-1186</ispartof><rights>Copyright Cambridge University Press May 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c329t-f9829bb98784a04de8b9c8589880c09f31612f9dca74bf2d729930fb1d0fb7363</citedby><cites>FETCH-LOGICAL-c329t-f9829bb98784a04de8b9c8589880c09f31612f9dca74bf2d729930fb1d0fb7363</cites><orcidid>0000-0002-2644-5812 ; 0000-0001-7233-9247</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32019629$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liu, Danmeng</creatorcontrib><creatorcontrib>Cheng, Yue</creatorcontrib><creatorcontrib>Mi, Baibing</creatorcontrib><creatorcontrib>Zeng, Lingxia</creatorcontrib><creatorcontrib>Qu, Pengfei</creatorcontrib><creatorcontrib>Li, Shanshan</creatorcontrib><creatorcontrib>Zhang, Ruo</creatorcontrib><creatorcontrib>Qi, Qi</creatorcontrib><creatorcontrib>Wu, Chenlu</creatorcontrib><creatorcontrib>Gao, Xiangyu</creatorcontrib><creatorcontrib>Liu, Yezhou</creatorcontrib><creatorcontrib>Dang, Shaonong</creatorcontrib><creatorcontrib>Yan, Hong</creatorcontrib><title>Maternal dietary patterns during pregnancy derived by reduced-rank regression and birth weight in the Chinese population</title><title>British journal of nutrition</title><addtitle>Br J Nutr</addtitle><description>Few studies have investigated the association between maternal dietary patterns (DP) during pregnancy, derived from reduced-rank regression (RRR), and fetal growth. This study aims to identify DP during pregnancy associated with macro- and micronutrient intakes, using the RRR method, and to examine their relationship with birth weight (BW). We used data of 7194 women from a large-scale cross-sectional survey in Northwest China. Dietary protein, carbohydrate, haem Fe density and the ratio of PUFA and MUFA:SFA were used as the intermediate variables in the RRR model to extract DP. Generalised estimating equation models were applied to evaluate the associations between DP and BW and related outcomes (including BW z-score, low birth weight (LBW) and small for gestational age (SGA)). Four DP during pregnancy were identified. Socio-demographically disadvantaged pregnant women were more likely to have lower BW and lower adherence to DP1 (high legumes, soyabean products, vegetables and animal-source foods, with relative low wheat and oils). Women with medium and high adherence to DP1 had significantly increased BW (medium 28·6 (95 % CI 7·1, 50·1); high 25·2 (95 % CI 2·7, 47·6)) and BW z-score and had significantly reduced risks of LBW and SGA. The associations were stronger among women with babies &lt;3100 g. There is no association between other DP and outcomes. Higher adherence to the DP that was high in legumes, soyabean products, vegetables and animal-source foods was associated with improved BW in the Chinese pregnant women, particularly among those with disadvantageous socio-demographic conditions.</description><subject>Adult</subject><subject>Animal-based foods</subject><subject>Babies</subject><subject>Birth Weight</subject><subject>Carbohydrates</subject><subject>Childbirth &amp; labor</subject><subject>China</subject><subject>Cross-Sectional Studies</subject><subject>Diet</subject><subject>Diet - adverse effects</subject><subject>Diet - statistics &amp; numerical data</subject><subject>Diet Surveys</subject><subject>Edible oils</subject><subject>Feeding Behavior - physiology</subject><subject>Female</subject><subject>Fetal Development</subject><subject>Fetuses</subject><subject>Food</subject><subject>Food sources</subject><subject>Gestational Age</subject><subject>Humans</subject><subject>Infant, Low Birth Weight</subject><subject>Infant, Newborn</subject><subject>Infant, Small for Gestational Age</subject><subject>Legumes</subject><subject>Leguminous plants</subject><subject>Low birth weight</subject><subject>Male</subject><subject>Maternal Nutritional Physiological Phenomena</subject><subject>Mortality</subject><subject>Nutrients</subject><subject>Nutrition research</subject><subject>Pregnancy</subject><subject>Principal Component Analysis</subject><subject>Proteins</subject><subject>Regression Analysis</subject><subject>Risk reduction</subject><subject>Small for gestational age</subject><subject>Statistical analysis</subject><subject>Vegetables</subject><subject>Weight</subject><subject>Womens health</subject><issn>0007-1145</issn><issn>1475-2662</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNplkblOxDAQhi0EguV4ABpkiYYm4COJ7RKtuCQQBVBHTjzZNWSdYDvAvj2OOApo5vq_mWJ-hA4pOaWEirMHQoigNC9YKghXbAPNaC6KjJUl20SzSc4mfQfthvCcWkmJ2kY7nBGqSqZm6ONOR_BOd9hYiNqv8aDjNAnYjN66BR48LJx2zRob8PYNDK7X2IMZGzCZ1-4lNQsPIdjeYe2SbH1c4newi2XE1uG4BDxfWgcB8NAPY6djQvfRVqu7AAffeQ89XV48zq-z2_urm_n5bdZwpmLWKslUXSspZK5JbkDWqpGFVFKShqiW05KyVplGi7xumRFMKU7ampoUBC_5Hjr5ujv4_nWEEKuVDQ10nXbQj6FivKAFVYqxhB7_QZ_7cfrNRMmSliIXE0W_qMb3IXhoq8HbVfpcRUk12VL9syXtHH1fHusVmN-NHx_4J75viGc</recordid><startdate>20200528</startdate><enddate>20200528</enddate><creator>Liu, Danmeng</creator><creator>Cheng, Yue</creator><creator>Mi, Baibing</creator><creator>Zeng, Lingxia</creator><creator>Qu, Pengfei</creator><creator>Li, Shanshan</creator><creator>Zhang, Ruo</creator><creator>Qi, Qi</creator><creator>Wu, Chenlu</creator><creator>Gao, Xiangyu</creator><creator>Liu, Yezhou</creator><creator>Dang, Shaonong</creator><creator>Yan, Hong</creator><general>Cambridge University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QP</scope><scope>7RV</scope><scope>7T5</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AN0</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-2644-5812</orcidid><orcidid>https://orcid.org/0000-0001-7233-9247</orcidid></search><sort><creationdate>20200528</creationdate><title>Maternal dietary patterns during pregnancy derived by reduced-rank regression and birth weight in the Chinese population</title><author>Liu, Danmeng ; 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This study aims to identify DP during pregnancy associated with macro- and micronutrient intakes, using the RRR method, and to examine their relationship with birth weight (BW). We used data of 7194 women from a large-scale cross-sectional survey in Northwest China. Dietary protein, carbohydrate, haem Fe density and the ratio of PUFA and MUFA:SFA were used as the intermediate variables in the RRR model to extract DP. Generalised estimating equation models were applied to evaluate the associations between DP and BW and related outcomes (including BW z-score, low birth weight (LBW) and small for gestational age (SGA)). Four DP during pregnancy were identified. Socio-demographically disadvantaged pregnant women were more likely to have lower BW and lower adherence to DP1 (high legumes, soyabean products, vegetables and animal-source foods, with relative low wheat and oils). Women with medium and high adherence to DP1 had significantly increased BW (medium 28·6 (95 % CI 7·1, 50·1); high 25·2 (95 % CI 2·7, 47·6)) and BW z-score and had significantly reduced risks of LBW and SGA. The associations were stronger among women with babies &lt;3100 g. There is no association between other DP and outcomes. Higher adherence to the DP that was high in legumes, soyabean products, vegetables and animal-source foods was associated with improved BW in the Chinese pregnant women, particularly among those with disadvantageous socio-demographic conditions.</abstract><cop>England</cop><pub>Cambridge University Press</pub><pmid>32019629</pmid><doi>10.1017/S0007114520000392</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-2644-5812</orcidid><orcidid>https://orcid.org/0000-0001-7233-9247</orcidid></addata></record>
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subjects Adult
Animal-based foods
Babies
Birth Weight
Carbohydrates
Childbirth & labor
China
Cross-Sectional Studies
Diet
Diet - adverse effects
Diet - statistics & numerical data
Diet Surveys
Edible oils
Feeding Behavior - physiology
Female
Fetal Development
Fetuses
Food
Food sources
Gestational Age
Humans
Infant, Low Birth Weight
Infant, Newborn
Infant, Small for Gestational Age
Legumes
Leguminous plants
Low birth weight
Male
Maternal Nutritional Physiological Phenomena
Mortality
Nutrients
Nutrition research
Pregnancy
Principal Component Analysis
Proteins
Regression Analysis
Risk reduction
Small for gestational age
Statistical analysis
Vegetables
Weight
Womens health
title Maternal dietary patterns during pregnancy derived by reduced-rank regression and birth weight in the Chinese population
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