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Dietary patterns and abnormal glucose tolerance among Japanese: findings from the National Health and Nutrition Survey, 2012
Previous studies have associated dietary patterns with diabetes risk in Western countries, but such studies among the Japanese population are scarce. The present study aimed to investigate dietary patterns associated with abnormal glucose tolerance determined by elevated glycated Hb (HbA1c) levels....
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Published in: | Public health nutrition 2019-09, Vol.22 (13), p.2460-2468 |
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description | Previous studies have associated dietary patterns with diabetes risk in Western countries, but such studies among the Japanese population are scarce. The present study aimed to investigate dietary patterns associated with abnormal glucose tolerance determined by elevated glycated Hb (HbA1c) levels.
The 2012 National Health and Nutrition Survey (NHNS) database was used for the cross-sectional study. Dietary patterns were analysed by factor analysis of twenty-five food items from the dietary intake survey and household-based semi-weighed dietary records. OR and 95 % CI for elevated HbA1c levels (≥6·5 %) according to dietary patterns were estimated using logistic regression models.
Japan.
The study population comprised 9550 Japanese aged ≥40 years registered in the nationwide NHNS.
Three dietary patterns were identified: (i) high-bread and low-rice; (ii) high-meat and low-fish; and (iii) vegetable. The high-bread and low-rice pattern, characterised by high frequent consumption of bread, milk and dairy products, and fruits, and low rice intake, was associated with marginally decreased prevalence of elevated HbA1c levels (Ptrend=0·047). The vegetable pattern, characterised by vegetables, mushrooms, soyabeans and soybean products, was significantly inversely associated with elevated HbA1c levels (4th v. 1st quartile: multivariable OR=0·68; 95 % CI 0·49, 0·95; Ptrend=0·007).
Our findings suggest that the vegetable pattern is associated with decreased prevalence of elevated HbA1c levels among Japanese. |
doi_str_mv | 10.1017/S1368980019000120 |
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The 2012 National Health and Nutrition Survey (NHNS) database was used for the cross-sectional study. Dietary patterns were analysed by factor analysis of twenty-five food items from the dietary intake survey and household-based semi-weighed dietary records. OR and 95 % CI for elevated HbA1c levels (≥6·5 %) according to dietary patterns were estimated using logistic regression models.
Japan.
The study population comprised 9550 Japanese aged ≥40 years registered in the nationwide NHNS.
Three dietary patterns were identified: (i) high-bread and low-rice; (ii) high-meat and low-fish; and (iii) vegetable. The high-bread and low-rice pattern, characterised by high frequent consumption of bread, milk and dairy products, and fruits, and low rice intake, was associated with marginally decreased prevalence of elevated HbA1c levels (Ptrend=0·047). The vegetable pattern, characterised by vegetables, mushrooms, soyabeans and soybean products, was significantly inversely associated with elevated HbA1c levels (4th v. 1st quartile: multivariable OR=0·68; 95 % CI 0·49, 0·95; Ptrend=0·007).
Our findings suggest that the vegetable pattern is associated with decreased prevalence of elevated HbA1c levels among Japanese.</description><identifier>ISSN: 1368-9800</identifier><identifier>EISSN: 1475-2727</identifier><identifier>DOI: 10.1017/S1368980019000120</identifier><identifier>PMID: 30837027</identifier><language>eng</language><publisher>Cambridge, UK: Cambridge University Press</publisher><subject>Aged ; Alcohol ; Blood tests ; Bread ; Cross-Sectional Studies ; Dairy products ; Diabetes ; Diabetes mellitus ; Diet ; Diet - statistics & numerical data ; Dietary intake ; Factor analysis ; Female ; Food ; Glucose ; Glucose Intolerance - epidemiology ; Glucose tolerance ; Glycated Hemoglobin - analysis ; Health care ; Health risks ; Hemoglobin ; Households ; Humans ; Japan - epidemiology ; Male ; Meat ; Meta-analysis ; Methods ; Middle Aged ; Mushrooms ; Nutrition ; Nutrition research ; Nutrition Surveys ; Nutritional Epidemiology ; Polls & surveys ; Population studies ; Questionnaires ; Regression analysis ; Regression models ; Research Paper ; Rice ; Shellfish ; Soybeans ; Studies ; Systematic review ; Vegetables</subject><ispartof>Public health nutrition, 2019-09, Vol.22 (13), p.2460-2468</ispartof><rights>The Authors 2019</rights><rights>The Authors 2019 2019 The Authors</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c538t-800a5c9aafd4306dcff7018a75cefd82909cd1d590cee8798a3df675fb4f7b43</citedby><cites>FETCH-LOGICAL-c538t-800a5c9aafd4306dcff7018a75cefd82909cd1d590cee8798a3df675fb4f7b43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10260638/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S1368980019000120/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793,72960</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30837027$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Okada, Emiko</creatorcontrib><creatorcontrib>Takahashi, Kunihiko</creatorcontrib><creatorcontrib>Nakamura, Koshi</creatorcontrib><creatorcontrib>Ukawa, Shigekazu</creatorcontrib><creatorcontrib>Takabayashi, Saeka</creatorcontrib><creatorcontrib>Nakamura, Mieko</creatorcontrib><creatorcontrib>Sasaki, Satoshi</creatorcontrib><creatorcontrib>Tamakoshi, Akiko</creatorcontrib><creatorcontrib>Takimoto, Hidemi</creatorcontrib><title>Dietary patterns and abnormal glucose tolerance among Japanese: findings from the National Health and Nutrition Survey, 2012</title><title>Public health nutrition</title><addtitle>Public Health Nutr</addtitle><description>Previous studies have associated dietary patterns with diabetes risk in Western countries, but such studies among the Japanese population are scarce. The present study aimed to investigate dietary patterns associated with abnormal glucose tolerance determined by elevated glycated Hb (HbA1c) levels.
The 2012 National Health and Nutrition Survey (NHNS) database was used for the cross-sectional study. Dietary patterns were analysed by factor analysis of twenty-five food items from the dietary intake survey and household-based semi-weighed dietary records. OR and 95 % CI for elevated HbA1c levels (≥6·5 %) according to dietary patterns were estimated using logistic regression models.
Japan.
The study population comprised 9550 Japanese aged ≥40 years registered in the nationwide NHNS.
Three dietary patterns were identified: (i) high-bread and low-rice; (ii) high-meat and low-fish; and (iii) vegetable. The high-bread and low-rice pattern, characterised by high frequent consumption of bread, milk and dairy products, and fruits, and low rice intake, was associated with marginally decreased prevalence of elevated HbA1c levels (Ptrend=0·047). The vegetable pattern, characterised by vegetables, mushrooms, soyabeans and soybean products, was significantly inversely associated with elevated HbA1c levels (4th v. 1st quartile: multivariable OR=0·68; 95 % CI 0·49, 0·95; Ptrend=0·007).
Our findings suggest that the vegetable pattern is associated with decreased prevalence of elevated HbA1c levels among Japanese.</description><subject>Aged</subject><subject>Alcohol</subject><subject>Blood tests</subject><subject>Bread</subject><subject>Cross-Sectional Studies</subject><subject>Dairy products</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diet</subject><subject>Diet - statistics & numerical data</subject><subject>Dietary intake</subject><subject>Factor analysis</subject><subject>Female</subject><subject>Food</subject><subject>Glucose</subject><subject>Glucose Intolerance - epidemiology</subject><subject>Glucose tolerance</subject><subject>Glycated Hemoglobin - analysis</subject><subject>Health care</subject><subject>Health risks</subject><subject>Hemoglobin</subject><subject>Households</subject><subject>Humans</subject><subject>Japan - epidemiology</subject><subject>Male</subject><subject>Meat</subject><subject>Meta-analysis</subject><subject>Methods</subject><subject>Middle Aged</subject><subject>Mushrooms</subject><subject>Nutrition</subject><subject>Nutrition research</subject><subject>Nutrition Surveys</subject><subject>Nutritional Epidemiology</subject><subject>Polls & surveys</subject><subject>Population studies</subject><subject>Questionnaires</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Research Paper</subject><subject>Rice</subject><subject>Shellfish</subject><subject>Soybeans</subject><subject>Studies</subject><subject>Systematic review</subject><subject>Vegetables</subject><issn>1368-9800</issn><issn>1475-2727</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp1UU1v1TAQjBCIlsIP4IIsceFAwE7i2OZSofJRUFUO7T3a2Os8V4n9sJ1Klfjx-NFH-RIX2_LMzs7uVNVTRl8xysTrC9b2UklKmaLlaOi96pB1gteNaMT98i5wvcMPqkcpXRUOF0I8rA5aKltBG3FYfXvnMEO8IVvIGaNPBLwhMPoQF5jJNK86JCQ5zBjBaySwBD-Rz7AFjwnfEOu8cX5KxMawkLxBcg7ZBV-KTxHmvPkheL7m6Hbf5GKN13jzkjTF7-PqgYU54ZP9fVRdfnh_eXJan335-Onk7VmteStzXQYArhWANV1Le6OtFZRJEFyjNbJRVGnDDFdUI0qhJLTG9oLbsbNi7Nqj6vhWdruOCxqNPkeYh210S5l8COCGPxHvNsMUrgdGm572rSwKL_YKMXxdMeVhcUnjPJclhDUNDZOSKyY7XqjP_6JehTWWdRRW0yvJO0V3ltgtS8eQUkR754bRYZft8E-2pebZ72PcVfwMsxDavSgsY3Rmwl-9_y_7HXsxsAQ</recordid><startdate>20190901</startdate><enddate>20190901</enddate><creator>Okada, Emiko</creator><creator>Takahashi, Kunihiko</creator><creator>Nakamura, Koshi</creator><creator>Ukawa, Shigekazu</creator><creator>Takabayashi, Saeka</creator><creator>Nakamura, Mieko</creator><creator>Sasaki, Satoshi</creator><creator>Tamakoshi, Akiko</creator><creator>Takimoto, Hidemi</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>7RQ</scope><scope>7RV</scope><scope>7T2</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>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20190901</creationdate><title>Dietary patterns and abnormal glucose tolerance among Japanese: findings from the National Health and Nutrition Survey, 2012</title><author>Okada, Emiko ; Takahashi, Kunihiko ; Nakamura, Koshi ; Ukawa, Shigekazu ; Takabayashi, Saeka ; Nakamura, Mieko ; Sasaki, Satoshi ; Tamakoshi, Akiko ; Takimoto, Hidemi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c538t-800a5c9aafd4306dcff7018a75cefd82909cd1d590cee8798a3df675fb4f7b43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Aged</topic><topic>Alcohol</topic><topic>Blood tests</topic><topic>Bread</topic><topic>Cross-Sectional Studies</topic><topic>Dairy products</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Diet</topic><topic>Diet - statistics & numerical data</topic><topic>Dietary intake</topic><topic>Factor analysis</topic><topic>Female</topic><topic>Food</topic><topic>Glucose</topic><topic>Glucose Intolerance - epidemiology</topic><topic>Glucose tolerance</topic><topic>Glycated Hemoglobin - analysis</topic><topic>Health care</topic><topic>Health risks</topic><topic>Hemoglobin</topic><topic>Households</topic><topic>Humans</topic><topic>Japan - epidemiology</topic><topic>Male</topic><topic>Meat</topic><topic>Meta-analysis</topic><topic>Methods</topic><topic>Middle Aged</topic><topic>Mushrooms</topic><topic>Nutrition</topic><topic>Nutrition research</topic><topic>Nutrition Surveys</topic><topic>Nutritional Epidemiology</topic><topic>Polls & surveys</topic><topic>Population studies</topic><topic>Questionnaires</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Research Paper</topic><topic>Rice</topic><topic>Shellfish</topic><topic>Soybeans</topic><topic>Studies</topic><topic>Systematic review</topic><topic>Vegetables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Okada, Emiko</creatorcontrib><creatorcontrib>Takahashi, Kunihiko</creatorcontrib><creatorcontrib>Nakamura, Koshi</creatorcontrib><creatorcontrib>Ukawa, Shigekazu</creatorcontrib><creatorcontrib>Takabayashi, Saeka</creatorcontrib><creatorcontrib>Nakamura, Mieko</creatorcontrib><creatorcontrib>Sasaki, Satoshi</creatorcontrib><creatorcontrib>Tamakoshi, Akiko</creatorcontrib><creatorcontrib>Takimoto, Hidemi</creatorcontrib><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>Calcium & Calcified Tissue Abstracts</collection><collection>Career & Technical Education Database</collection><collection>Nursing & Allied Health Database</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</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 Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Public health nutrition</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Okada, Emiko</au><au>Takahashi, Kunihiko</au><au>Nakamura, Koshi</au><au>Ukawa, Shigekazu</au><au>Takabayashi, Saeka</au><au>Nakamura, Mieko</au><au>Sasaki, Satoshi</au><au>Tamakoshi, Akiko</au><au>Takimoto, Hidemi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dietary patterns and abnormal glucose tolerance among Japanese: findings from the National Health and Nutrition Survey, 2012</atitle><jtitle>Public health nutrition</jtitle><addtitle>Public Health Nutr</addtitle><date>2019-09-01</date><risdate>2019</risdate><volume>22</volume><issue>13</issue><spage>2460</spage><epage>2468</epage><pages>2460-2468</pages><issn>1368-9800</issn><eissn>1475-2727</eissn><abstract>Previous studies have associated dietary patterns with diabetes risk in Western countries, but such studies among the Japanese population are scarce. The present study aimed to investigate dietary patterns associated with abnormal glucose tolerance determined by elevated glycated Hb (HbA1c) levels.
The 2012 National Health and Nutrition Survey (NHNS) database was used for the cross-sectional study. Dietary patterns were analysed by factor analysis of twenty-five food items from the dietary intake survey and household-based semi-weighed dietary records. OR and 95 % CI for elevated HbA1c levels (≥6·5 %) according to dietary patterns were estimated using logistic regression models.
Japan.
The study population comprised 9550 Japanese aged ≥40 years registered in the nationwide NHNS.
Three dietary patterns were identified: (i) high-bread and low-rice; (ii) high-meat and low-fish; and (iii) vegetable. The high-bread and low-rice pattern, characterised by high frequent consumption of bread, milk and dairy products, and fruits, and low rice intake, was associated with marginally decreased prevalence of elevated HbA1c levels (Ptrend=0·047). The vegetable pattern, characterised by vegetables, mushrooms, soyabeans and soybean products, was significantly inversely associated with elevated HbA1c levels (4th v. 1st quartile: multivariable OR=0·68; 95 % CI 0·49, 0·95; Ptrend=0·007).
Our findings suggest that the vegetable pattern is associated with decreased prevalence of elevated HbA1c levels among Japanese.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><pmid>30837027</pmid><doi>10.1017/S1368980019000120</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Aged Alcohol Blood tests Bread Cross-Sectional Studies Dairy products Diabetes Diabetes mellitus Diet Diet - statistics & numerical data Dietary intake Factor analysis Female Food Glucose Glucose Intolerance - epidemiology Glucose tolerance Glycated Hemoglobin - analysis Health care Health risks Hemoglobin Households Humans Japan - epidemiology Male Meat Meta-analysis Methods Middle Aged Mushrooms Nutrition Nutrition research Nutrition Surveys Nutritional Epidemiology Polls & surveys Population studies Questionnaires Regression analysis Regression models Research Paper Rice Shellfish Soybeans Studies Systematic review Vegetables |
title | Dietary patterns and abnormal glucose tolerance among Japanese: findings from the National Health and Nutrition Survey, 2012 |
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