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Dietary calcium intake was related to the onset of pre‐eclampsia: The TMM BirThree Cohort Study
This study aimed to explore the relationship between dietary electrolyte intake and the prevalence of hypertensive disorders of pregnancy (HDP) subtypes. Our analysis included 19 914 pregnant women from the Tohoku Medical Megabank Project Birth and Three‐Generation Cohort Study. A food frequency que...
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Published in: | The journal of clinical hypertension (Greenwich, Conn.) Conn.), 2023-01, Vol.25 (1), p.61-70 |
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creator | Ohseto, Hisashi Ishikuro, Mami Obara, Taku Murakami, Keiko Onuma, Tomomi Noda, Aoi Takahashi, Ippei Matsuzaki, Fumiko Ueno, Fumihiko Iwama, Noriyuki Kikuya, Masahiro Metoki, Hirohito Sugawara, Junichi Kuriyama, Shinichi |
description | This study aimed to explore the relationship between dietary electrolyte intake and the prevalence of hypertensive disorders of pregnancy (HDP) subtypes. Our analysis included 19 914 pregnant women from the Tohoku Medical Megabank Project Birth and Three‐Generation Cohort Study. A food frequency questionnaire was used to estimate dietary calcium, potassium, sodium, and magnesium intakes. HDP was determined based on the medical records during regular antenatal care. Logistic regression analysis assessed the relationship between dietary electrolytes intake quintiles, and HDP subtypes with adjustment for basic characteristics. Dietary electrolyte intakes were applied for the prediction model. Of the cohort, 547 participants delivered with pre‐eclampsia (PE), 278 with superimposed PE (SP), and 896 with gestational hypertension (GH). PE was associated with low crude calcium intake (odds ratio of the first quintile [623 mg/day] and 95% confidence interval, 1.31 [1.00–1.70]) and P for trend was .02. SP was not associated with any nutritional intake; however, the combined outcome of PE and SP was related to low crude calcium and potassium and energy‐adjusted calcium, potassium, and magnesium intakes (P for trend, .01, .048, .02, .04, and .02, respectively). The same tendency was observed for GH. A prediction model that included crude calcium and potassium intakes performed better than a model without them. In conclusion, low dietary calcium, potassium, and magnesium were associated with higher HDP subtypes prevalence. The prediction model implied that crude calcium and potassium intakes might play a critical role in PE and SP pathogenesis. |
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Our analysis included 19 914 pregnant women from the Tohoku Medical Megabank Project Birth and Three‐Generation Cohort Study. A food frequency questionnaire was used to estimate dietary calcium, potassium, sodium, and magnesium intakes. HDP was determined based on the medical records during regular antenatal care. Logistic regression analysis assessed the relationship between dietary electrolytes intake quintiles, and HDP subtypes with adjustment for basic characteristics. Dietary electrolyte intakes were applied for the prediction model. Of the cohort, 547 participants delivered with pre‐eclampsia (PE), 278 with superimposed PE (SP), and 896 with gestational hypertension (GH). PE was associated with low crude calcium intake (odds ratio of the first quintile [<251 mg/day] to the fifth quintile [>623 mg/day] and 95% confidence interval, 1.31 [1.00–1.70]) and P for trend was .02. SP was not associated with any nutritional intake; however, the combined outcome of PE and SP was related to low crude calcium and potassium and energy‐adjusted calcium, potassium, and magnesium intakes (P for trend, .01, .048, .02, .04, and .02, respectively). The same tendency was observed for GH. A prediction model that included crude calcium and potassium intakes performed better than a model without them. In conclusion, low dietary calcium, potassium, and magnesium were associated with higher HDP subtypes prevalence. The prediction model implied that crude calcium and potassium intakes might play a critical role in PE and SP pathogenesis.</description><identifier>ISSN: 1524-6175</identifier><identifier>EISSN: 1751-7176</identifier><identifier>DOI: 10.1111/jch.14606</identifier><identifier>PMID: 36579409</identifier><language>eng</language><publisher>United States: John Wiley & Sons, Inc</publisher><subject>Alcohol ; antenatal care ; Blood pressure ; Body mass index ; Calcium ; Calcium, Dietary ; Cohort analysis ; Cohort Studies ; cohort study ; Earthquakes ; Educational attainment ; Electrolytes ; Family medical history ; Female ; food frequency questionnaire ; Gestational age ; Humans ; Hypertension ; Hypertension, Pregnancy-Induced ; In vitro fertilization ; Magnesium ; Medical records ; Missing data ; Nutrition ; Original ; Potassium ; Pre-Eclampsia - epidemiology ; prediction model ; Preeclampsia ; Pregnancy ; Prenatal care ; pre‐eclampsia ; pre‐eclampsia superimposed on chronic hypertension ; Regression analysis ; Risk Factors ; Statistical analysis</subject><ispartof>The journal of clinical hypertension (Greenwich, Conn.), 2023-01, Vol.25 (1), p.61-70</ispartof><rights>2022 The Authors. published by Wiley Periodicals LLC.</rights><rights>2022 The Authors. The Journal of Clinical Hypertension published by Wiley Periodicals LLC.</rights><rights>2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5756-c0108e665607b77e4a3ce85333265ba208942396e54969e1bb75ca2a873a0b973</citedby><cites>FETCH-LOGICAL-c5756-c0108e665607b77e4a3ce85333265ba208942396e54969e1bb75ca2a873a0b973</cites><orcidid>0000-0002-3080-6107 ; 0000-0002-1894-3328 ; 0000-0001-6716-9095</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2890732392/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2890732392?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,11562,25753,27924,27925,37012,37013,44590,46052,46476,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36579409$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ohseto, Hisashi</creatorcontrib><creatorcontrib>Ishikuro, Mami</creatorcontrib><creatorcontrib>Obara, Taku</creatorcontrib><creatorcontrib>Murakami, Keiko</creatorcontrib><creatorcontrib>Onuma, Tomomi</creatorcontrib><creatorcontrib>Noda, Aoi</creatorcontrib><creatorcontrib>Takahashi, Ippei</creatorcontrib><creatorcontrib>Matsuzaki, Fumiko</creatorcontrib><creatorcontrib>Ueno, Fumihiko</creatorcontrib><creatorcontrib>Iwama, Noriyuki</creatorcontrib><creatorcontrib>Kikuya, Masahiro</creatorcontrib><creatorcontrib>Metoki, Hirohito</creatorcontrib><creatorcontrib>Sugawara, Junichi</creatorcontrib><creatorcontrib>Kuriyama, Shinichi</creatorcontrib><title>Dietary calcium intake was related to the onset of pre‐eclampsia: The TMM BirThree Cohort Study</title><title>The journal of clinical hypertension (Greenwich, Conn.)</title><addtitle>J Clin Hypertens (Greenwich)</addtitle><description>This study aimed to explore the relationship between dietary electrolyte intake and the prevalence of hypertensive disorders of pregnancy (HDP) subtypes. Our analysis included 19 914 pregnant women from the Tohoku Medical Megabank Project Birth and Three‐Generation Cohort Study. A food frequency questionnaire was used to estimate dietary calcium, potassium, sodium, and magnesium intakes. HDP was determined based on the medical records during regular antenatal care. Logistic regression analysis assessed the relationship between dietary electrolytes intake quintiles, and HDP subtypes with adjustment for basic characteristics. Dietary electrolyte intakes were applied for the prediction model. Of the cohort, 547 participants delivered with pre‐eclampsia (PE), 278 with superimposed PE (SP), and 896 with gestational hypertension (GH). PE was associated with low crude calcium intake (odds ratio of the first quintile [<251 mg/day] to the fifth quintile [>623 mg/day] and 95% confidence interval, 1.31 [1.00–1.70]) and P for trend was .02. SP was not associated with any nutritional intake; however, the combined outcome of PE and SP was related to low crude calcium and potassium and energy‐adjusted calcium, potassium, and magnesium intakes (P for trend, .01, .048, .02, .04, and .02, respectively). The same tendency was observed for GH. A prediction model that included crude calcium and potassium intakes performed better than a model without them. In conclusion, low dietary calcium, potassium, and magnesium were associated with higher HDP subtypes prevalence. The prediction model implied that crude calcium and potassium intakes might play a critical role in PE and SP pathogenesis.</description><subject>Alcohol</subject><subject>antenatal care</subject><subject>Blood pressure</subject><subject>Body mass index</subject><subject>Calcium</subject><subject>Calcium, Dietary</subject><subject>Cohort analysis</subject><subject>Cohort Studies</subject><subject>cohort study</subject><subject>Earthquakes</subject><subject>Educational attainment</subject><subject>Electrolytes</subject><subject>Family medical history</subject><subject>Female</subject><subject>food frequency questionnaire</subject><subject>Gestational age</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Hypertension, Pregnancy-Induced</subject><subject>In vitro fertilization</subject><subject>Magnesium</subject><subject>Medical records</subject><subject>Missing data</subject><subject>Nutrition</subject><subject>Original</subject><subject>Potassium</subject><subject>Pre-Eclampsia - epidemiology</subject><subject>prediction model</subject><subject>Preeclampsia</subject><subject>Pregnancy</subject><subject>Prenatal care</subject><subject>pre‐eclampsia</subject><subject>pre‐eclampsia superimposed on chronic hypertension</subject><subject>Regression analysis</subject><subject>Risk Factors</subject><subject>Statistical analysis</subject><issn>1524-6175</issn><issn>1751-7176</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp1kktuFDEQQFsIRD6w4ALIEhuymMSftt1mgQTDJ0GJWDCsrWp3TdpDT3uw3USz4wickZNgMiEiSHhjq-rpucquqnrC6DEr62Tl-mNWK6ruVftMSzbTTKv75Sx5PVMlslcdpLSiVAph6MNqTyipTU3NfgVvPGaIW-JgcH5aEz9m-ILkChKJOEDGjuRAco8kjAkzCUuyifjz-w90A6w3ycMLsijZxcUFee3joo-IZB76EDP5lKdu-6h6sIQh4eOb_bD6_O7tYn46O__4_mz-6nzmpJZq5iijDSolFdWt1liDcNiUggVXsgVOG1NzYRTK2iiDrG21dMCh0QJoa7Q4rM523i7Aym6iX5e2bABvrwMhXlqI2bsBbdtQ3aBpkTpZM90ZELrcAUw2FJ1QxfVy59pM7Ro7h2OOMNyR3s2MvreX4Zs1jeCcN0Xw_EYQw9cJU7ZrnxwOA4wYpmS5lqb0JZUs6LN_0FWY4lieyvLGUC1K17xQRzvKxZBSxOVtMYza30NgyxDY6yEo7NO_q78l__x6AU52wJUfcPt_k_0wP90pfwGFeLqi</recordid><startdate>202301</startdate><enddate>202301</enddate><creator>Ohseto, Hisashi</creator><creator>Ishikuro, Mami</creator><creator>Obara, Taku</creator><creator>Murakami, Keiko</creator><creator>Onuma, Tomomi</creator><creator>Noda, Aoi</creator><creator>Takahashi, Ippei</creator><creator>Matsuzaki, Fumiko</creator><creator>Ueno, Fumihiko</creator><creator>Iwama, Noriyuki</creator><creator>Kikuya, Masahiro</creator><creator>Metoki, Hirohito</creator><creator>Sugawara, Junichi</creator><creator>Kuriyama, Shinichi</creator><general>John Wiley & Sons, Inc</general><general>John Wiley and Sons Inc</general><general>Wiley</general><scope>24P</scope><scope>WIN</scope><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>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-3080-6107</orcidid><orcidid>https://orcid.org/0000-0002-1894-3328</orcidid><orcidid>https://orcid.org/0000-0001-6716-9095</orcidid></search><sort><creationdate>202301</creationdate><title>Dietary calcium intake was related to the onset of pre‐eclampsia: The TMM BirThree Cohort Study</title><author>Ohseto, Hisashi ; Ishikuro, Mami ; Obara, Taku ; Murakami, Keiko ; Onuma, Tomomi ; Noda, Aoi ; Takahashi, Ippei ; Matsuzaki, Fumiko ; Ueno, Fumihiko ; Iwama, Noriyuki ; Kikuya, Masahiro ; Metoki, Hirohito ; Sugawara, Junichi ; Kuriyama, Shinichi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5756-c0108e665607b77e4a3ce85333265ba208942396e54969e1bb75ca2a873a0b973</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Alcohol</topic><topic>antenatal care</topic><topic>Blood pressure</topic><topic>Body mass index</topic><topic>Calcium</topic><topic>Calcium, Dietary</topic><topic>Cohort analysis</topic><topic>Cohort Studies</topic><topic>cohort study</topic><topic>Earthquakes</topic><topic>Educational attainment</topic><topic>Electrolytes</topic><topic>Family medical history</topic><topic>Female</topic><topic>food frequency questionnaire</topic><topic>Gestational age</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Hypertension, Pregnancy-Induced</topic><topic>In vitro fertilization</topic><topic>Magnesium</topic><topic>Medical records</topic><topic>Missing data</topic><topic>Nutrition</topic><topic>Original</topic><topic>Potassium</topic><topic>Pre-Eclampsia - epidemiology</topic><topic>prediction model</topic><topic>Preeclampsia</topic><topic>Pregnancy</topic><topic>Prenatal care</topic><topic>pre‐eclampsia</topic><topic>pre‐eclampsia superimposed on chronic hypertension</topic><topic>Regression analysis</topic><topic>Risk Factors</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ohseto, Hisashi</creatorcontrib><creatorcontrib>Ishikuro, Mami</creatorcontrib><creatorcontrib>Obara, Taku</creatorcontrib><creatorcontrib>Murakami, Keiko</creatorcontrib><creatorcontrib>Onuma, Tomomi</creatorcontrib><creatorcontrib>Noda, Aoi</creatorcontrib><creatorcontrib>Takahashi, Ippei</creatorcontrib><creatorcontrib>Matsuzaki, Fumiko</creatorcontrib><creatorcontrib>Ueno, Fumihiko</creatorcontrib><creatorcontrib>Iwama, Noriyuki</creatorcontrib><creatorcontrib>Kikuya, Masahiro</creatorcontrib><creatorcontrib>Metoki, Hirohito</creatorcontrib><creatorcontrib>Sugawara, Junichi</creatorcontrib><creatorcontrib>Kuriyama, Shinichi</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Online Library Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>ProQuest - 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Our analysis included 19 914 pregnant women from the Tohoku Medical Megabank Project Birth and Three‐Generation Cohort Study. A food frequency questionnaire was used to estimate dietary calcium, potassium, sodium, and magnesium intakes. HDP was determined based on the medical records during regular antenatal care. Logistic regression analysis assessed the relationship between dietary electrolytes intake quintiles, and HDP subtypes with adjustment for basic characteristics. Dietary electrolyte intakes were applied for the prediction model. Of the cohort, 547 participants delivered with pre‐eclampsia (PE), 278 with superimposed PE (SP), and 896 with gestational hypertension (GH). PE was associated with low crude calcium intake (odds ratio of the first quintile [<251 mg/day] to the fifth quintile [>623 mg/day] and 95% confidence interval, 1.31 [1.00–1.70]) and P for trend was .02. SP was not associated with any nutritional intake; however, the combined outcome of PE and SP was related to low crude calcium and potassium and energy‐adjusted calcium, potassium, and magnesium intakes (P for trend, .01, .048, .02, .04, and .02, respectively). The same tendency was observed for GH. A prediction model that included crude calcium and potassium intakes performed better than a model without them. In conclusion, low dietary calcium, potassium, and magnesium were associated with higher HDP subtypes prevalence. The prediction model implied that crude calcium and potassium intakes might play a critical role in PE and SP pathogenesis.</abstract><cop>United States</cop><pub>John Wiley & Sons, Inc</pub><pmid>36579409</pmid><doi>10.1111/jch.14606</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-3080-6107</orcidid><orcidid>https://orcid.org/0000-0002-1894-3328</orcidid><orcidid>https://orcid.org/0000-0001-6716-9095</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Alcohol antenatal care Blood pressure Body mass index Calcium Calcium, Dietary Cohort analysis Cohort Studies cohort study Earthquakes Educational attainment Electrolytes Family medical history Female food frequency questionnaire Gestational age Humans Hypertension Hypertension, Pregnancy-Induced In vitro fertilization Magnesium Medical records Missing data Nutrition Original Potassium Pre-Eclampsia - epidemiology prediction model Preeclampsia Pregnancy Prenatal care pre‐eclampsia pre‐eclampsia superimposed on chronic hypertension Regression analysis Risk Factors Statistical analysis |
title | Dietary calcium intake was related to the onset of pre‐eclampsia: The TMM BirThree Cohort Study |
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