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Major dietary patterns of community dwelling adults and their associations with impaired blood glucose and central obesity in Eastern Ethiopia: Diet-disease epidemiological study
Unhealthy dietary intake is an important preventable risk factor for obesity and impaired blood glucose (IBG), ultimately increasing the risk of non-communicable diseases. When compared to individual food intakes, dietary patterns are a stronger predictor of health outcomes and should be systematica...
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Published in: | PloS one 2023-04, Vol.18 (4), p.e0283075-e0283075 |
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creator | Mekonnen, Berhanu Abebaw Oumer, Abdu Ale, Ahmed Hamza, Aragaw Dagne, Imam Umer, Abdurezak Adem Fentie, Dilnessa Yigezu, Muluken Tariku, Zerihun Abate, Shambel |
description | Unhealthy dietary intake is an important preventable risk factor for obesity and impaired blood glucose (IBG), ultimately increasing the risk of non-communicable diseases. When compared to individual food intakes, dietary patterns are a stronger predictor of health outcomes and should be systematically evaluated where such evidence is lacking. This study evaluated dietary patterns and their association with the risk of central obesity and IBG among adults.
A community-based survey was conducted among 501 randomly-selected adults from Eastern Ethiopia. Data was collected using a semi-structured questionnaire during a face-to-face interview that included sociodemographic and lifestyle factors, as well as a validated 89-item food frequency questionnaire (collected over one month). Principal component analysis was used to derive the dietary pattern. While central obesity was assessed using waist and/or hip circumference measurements, fasting blood sugar was used for IBG. A multivariable logistic regression model was fitted with an odds ratio, 95% confidence intervals, and p-values reported.
A total of 501 adults (95.3%) were interviewed, with a mean age of 41 years (±12). Five major dietary patterns explaining 71% of the total variance were identified: "nutrient-dense foods", "high fat and protein", "processed foods", "alcohol drinks", and "cereal diets". While 20.4% (17.0-24.2%) had IBG, 14.6% (11.8-17.9) were centrally obese, and 94.6% (92.3-96.3) had an increased waist-to-hip circumference ratio. Central obesity is associated with upper wealth status (AOR = 6.92; 2.91-16.5), physical inactivity (AOR = 21.1; 2.77-161.4), a diet high in nutrient-dense foods (AOR = 1.75; 0.75-4.06), processed foods (AOR = 1.41; 0.57-3.48), and cereal diets (AOR = 4.06; 1.87-8.82). The burden of IBG was associated with upper wealth status (AOR = 2.36; 1.36-4.10), physical inactivity (AOR = 2.17; 0.91-5.18), upper tercile of nutrient-dense foods (AOR = 1.35; 0.62-2.93), fat and protein diet (AOR = 1.31; 0.66-2.62), and cereal diet consumption (AOR = 3.87; 1.66-9.02).
IBG and central obesity were prevalent and predicted by upper tercile consumption of nutrient-dense foods, high fat and protein diets, processed foods, and cereal diets, which could guide dietary interventions. |
doi_str_mv | 10.1371/journal.pone.0283075 |
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A community-based survey was conducted among 501 randomly-selected adults from Eastern Ethiopia. Data was collected using a semi-structured questionnaire during a face-to-face interview that included sociodemographic and lifestyle factors, as well as a validated 89-item food frequency questionnaire (collected over one month). Principal component analysis was used to derive the dietary pattern. While central obesity was assessed using waist and/or hip circumference measurements, fasting blood sugar was used for IBG. A multivariable logistic regression model was fitted with an odds ratio, 95% confidence intervals, and p-values reported.
A total of 501 adults (95.3%) were interviewed, with a mean age of 41 years (±12). Five major dietary patterns explaining 71% of the total variance were identified: "nutrient-dense foods", "high fat and protein", "processed foods", "alcohol drinks", and "cereal diets". While 20.4% (17.0-24.2%) had IBG, 14.6% (11.8-17.9) were centrally obese, and 94.6% (92.3-96.3) had an increased waist-to-hip circumference ratio. Central obesity is associated with upper wealth status (AOR = 6.92; 2.91-16.5), physical inactivity (AOR = 21.1; 2.77-161.4), a diet high in nutrient-dense foods (AOR = 1.75; 0.75-4.06), processed foods (AOR = 1.41; 0.57-3.48), and cereal diets (AOR = 4.06; 1.87-8.82). The burden of IBG was associated with upper wealth status (AOR = 2.36; 1.36-4.10), physical inactivity (AOR = 2.17; 0.91-5.18), upper tercile of nutrient-dense foods (AOR = 1.35; 0.62-2.93), fat and protein diet (AOR = 1.31; 0.66-2.62), and cereal diet consumption (AOR = 3.87; 1.66-9.02).
IBG and central obesity were prevalent and predicted by upper tercile consumption of nutrient-dense foods, high fat and protein diets, processed foods, and cereal diets, which could guide dietary interventions.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0283075</identifier><identifier>PMID: 37079596</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Adults ; Agricultural production ; Biology and Life Sciences ; Blood ; Blood Glucose ; Blood sugar ; Cereals ; Communicable diseases ; Comparative analysis ; Cross-Sectional Studies ; Diabetes ; Diagnosis ; Diet ; Dietary intake ; Epidemiologic Studies ; Epidemiology ; Ethiopia - epidemiology ; Evaluation ; Exercise ; Fasting ; Feeding Behavior ; Food ; Food consumption ; Food intake ; Food processing ; Glucose ; Health aspects ; Health risks ; High fat diet ; High protein diet ; Hip ; Households ; Humans ; Independent Living ; Interviews ; Life style ; Lifestyles ; Medical research ; Medicine and Health Sciences ; Medicine, Experimental ; Mortality ; Nutrients ; Obesity ; Obesity - epidemiology ; Obesity - etiology ; Obesity, Abdominal - epidemiology ; Obesity, Abdominal - etiology ; Population ; Principal components analysis ; Processed foods ; Productivity ; Proteins ; Public health ; Questionnaires ; Regression models ; Risk factors ; Sample size ; Socioeconomics ; Statistical analysis ; Surveys ; Urban areas</subject><ispartof>PloS one, 2023-04, Vol.18 (4), p.e0283075-e0283075</ispartof><rights>Copyright: © 2023 Mekonnen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2023 Public Library of Science</rights><rights>2023 Mekonnen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 Mekonnen et al 2023 Mekonnen et al</rights><rights>2023 Mekonnen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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-c693t-91e7ae0fe6ff3f7ef261b417a47ed1680a0f3c4a5cc159f2d387c9ca3c98b92e3</citedby><cites>FETCH-LOGICAL-c693t-91e7ae0fe6ff3f7ef261b417a47ed1680a0f3c4a5cc159f2d387c9ca3c98b92e3</cites><orcidid>0000-0002-0839-9461</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2803890020?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2803890020?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,38516,43895,44590,53791,53793,74412,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37079596$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Asghari Jafarabadi, Mohammad</contributor><creatorcontrib>Mekonnen, Berhanu Abebaw</creatorcontrib><creatorcontrib>Oumer, Abdu</creatorcontrib><creatorcontrib>Ale, Ahmed</creatorcontrib><creatorcontrib>Hamza, Aragaw</creatorcontrib><creatorcontrib>Dagne, Imam</creatorcontrib><creatorcontrib>Umer, Abdurezak Adem</creatorcontrib><creatorcontrib>Fentie, Dilnessa</creatorcontrib><creatorcontrib>Yigezu, Muluken</creatorcontrib><creatorcontrib>Tariku, Zerihun</creatorcontrib><creatorcontrib>Abate, Shambel</creatorcontrib><title>Major dietary patterns of community dwelling adults and their associations with impaired blood glucose and central obesity in Eastern Ethiopia: Diet-disease epidemiological study</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Unhealthy dietary intake is an important preventable risk factor for obesity and impaired blood glucose (IBG), ultimately increasing the risk of non-communicable diseases. When compared to individual food intakes, dietary patterns are a stronger predictor of health outcomes and should be systematically evaluated where such evidence is lacking. This study evaluated dietary patterns and their association with the risk of central obesity and IBG among adults.
A community-based survey was conducted among 501 randomly-selected adults from Eastern Ethiopia. Data was collected using a semi-structured questionnaire during a face-to-face interview that included sociodemographic and lifestyle factors, as well as a validated 89-item food frequency questionnaire (collected over one month). Principal component analysis was used to derive the dietary pattern. While central obesity was assessed using waist and/or hip circumference measurements, fasting blood sugar was used for IBG. A multivariable logistic regression model was fitted with an odds ratio, 95% confidence intervals, and p-values reported.
A total of 501 adults (95.3%) were interviewed, with a mean age of 41 years (±12). Five major dietary patterns explaining 71% of the total variance were identified: "nutrient-dense foods", "high fat and protein", "processed foods", "alcohol drinks", and "cereal diets". While 20.4% (17.0-24.2%) had IBG, 14.6% (11.8-17.9) were centrally obese, and 94.6% (92.3-96.3) had an increased waist-to-hip circumference ratio. Central obesity is associated with upper wealth status (AOR = 6.92; 2.91-16.5), physical inactivity (AOR = 21.1; 2.77-161.4), a diet high in nutrient-dense foods (AOR = 1.75; 0.75-4.06), processed foods (AOR = 1.41; 0.57-3.48), and cereal diets (AOR = 4.06; 1.87-8.82). The burden of IBG was associated with upper wealth status (AOR = 2.36; 1.36-4.10), physical inactivity (AOR = 2.17; 0.91-5.18), upper tercile of nutrient-dense foods (AOR = 1.35; 0.62-2.93), fat and protein diet (AOR = 1.31; 0.66-2.62), and cereal diet consumption (AOR = 3.87; 1.66-9.02).
IBG and central obesity were prevalent and predicted by upper tercile consumption of nutrient-dense foods, high fat and protein diets, processed foods, and cereal diets, which could guide dietary interventions.</description><subject>Adult</subject><subject>Adults</subject><subject>Agricultural production</subject><subject>Biology and Life Sciences</subject><subject>Blood</subject><subject>Blood Glucose</subject><subject>Blood sugar</subject><subject>Cereals</subject><subject>Communicable diseases</subject><subject>Comparative analysis</subject><subject>Cross-Sectional Studies</subject><subject>Diabetes</subject><subject>Diagnosis</subject><subject>Diet</subject><subject>Dietary intake</subject><subject>Epidemiologic Studies</subject><subject>Epidemiology</subject><subject>Ethiopia - epidemiology</subject><subject>Evaluation</subject><subject>Exercise</subject><subject>Fasting</subject><subject>Feeding Behavior</subject><subject>Food</subject><subject>Food consumption</subject><subject>Food intake</subject><subject>Food processing</subject><subject>Glucose</subject><subject>Health aspects</subject><subject>Health risks</subject><subject>High fat diet</subject><subject>High protein diet</subject><subject>Hip</subject><subject>Households</subject><subject>Humans</subject><subject>Independent Living</subject><subject>Interviews</subject><subject>Life style</subject><subject>Lifestyles</subject><subject>Medical research</subject><subject>Medicine and Health Sciences</subject><subject>Medicine, Experimental</subject><subject>Mortality</subject><subject>Nutrients</subject><subject>Obesity</subject><subject>Obesity - epidemiology</subject><subject>Obesity - etiology</subject><subject>Obesity, Abdominal - epidemiology</subject><subject>Obesity, Abdominal - etiology</subject><subject>Population</subject><subject>Principal components analysis</subject><subject>Processed foods</subject><subject>Productivity</subject><subject>Proteins</subject><subject>Public health</subject><subject>Questionnaires</subject><subject>Regression models</subject><subject>Risk factors</subject><subject>Sample size</subject><subject>Socioeconomics</subject><subject>Statistical analysis</subject><subject>Surveys</subject><subject>Urban areas</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>COVID</sourceid><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNk81u1DAUhSMEoqXwBggsISFYzGDHiROzQVUpUKmoEn9by7FvMh45cbAdSl-LJ8Qzk1Yd1AXKIpHznXPtc32z7CnBS0Ir8mbtJj9IuxzdAEuc1xRX5b3skHCaL1iO6f1b3wfZoxDWGJe0ZuxhdkArXPGSs8Psz2e5dh5pA1H6KzTKGMEPAbkWKdf302DiFdKXYK0ZOiT1ZGNActAorsB4JENwyshoXNJcmrhCph-l8aBRY53TqLOTcgG2EgVD9NIi10DY2JoBncqwqYdO48q40ci36H3ayUKbADKpYDQaeuOs64xKyhAnffU4e9BKG-DJ_D7Kvn84_XbyaXF-8fHs5Ph8oRinccEJVBJwC6xtaVtBmzPSFKSSRQWasBpL3FJVyFIpUvI217SuFFeSKl43PAd6lD3f-Y7WBTHHHUReY1pzjFOsR9nZjtBOrsXoTZ8yFE4asV1wvhPSR6MsiIpyDqUqOM6bgmHM66JmFGOFa1pWTZ283s3VpqYHPWe1Z7r_ZzAr0blfgmBCakLL5PBqdvDu5wQhit4ElTonB3DTbuOcFbjME_riH_Tu481UJ9MJzNC6VFhtTMVxVbB0CTFniVreQaVn0zmVLmdr0vqe4PWeIDERfsdOTiGIs69f_p-9-LHPvrzFrkDauArOTtvLuQ8WO1B5F4KH9iZlgsVmtq7TEJvZEvNsJdmz2x26EV0PE_0LELkiag</recordid><startdate>20230420</startdate><enddate>20230420</enddate><creator>Mekonnen, Berhanu Abebaw</creator><creator>Oumer, Abdu</creator><creator>Ale, Ahmed</creator><creator>Hamza, Aragaw</creator><creator>Dagne, Imam</creator><creator>Umer, Abdurezak Adem</creator><creator>Fentie, Dilnessa</creator><creator>Yigezu, Muluken</creator><creator>Tariku, Zerihun</creator><creator>Abate, Shambel</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>COVID</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-0839-9461</orcidid></search><sort><creationdate>20230420</creationdate><title>Major dietary patterns of community dwelling adults and their associations with impaired blood glucose and central obesity in Eastern Ethiopia: Diet-disease epidemiological study</title><author>Mekonnen, Berhanu Abebaw ; Oumer, Abdu ; Ale, Ahmed ; Hamza, Aragaw ; Dagne, Imam ; Umer, Abdurezak Adem ; Fentie, Dilnessa ; Yigezu, Muluken ; Tariku, Zerihun ; Abate, Shambel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c693t-91e7ae0fe6ff3f7ef261b417a47ed1680a0f3c4a5cc159f2d387c9ca3c98b92e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Adult</topic><topic>Adults</topic><topic>Agricultural production</topic><topic>Biology and Life Sciences</topic><topic>Blood</topic><topic>Blood Glucose</topic><topic>Blood sugar</topic><topic>Cereals</topic><topic>Communicable diseases</topic><topic>Comparative analysis</topic><topic>Cross-Sectional Studies</topic><topic>Diabetes</topic><topic>Diagnosis</topic><topic>Diet</topic><topic>Dietary intake</topic><topic>Epidemiologic Studies</topic><topic>Epidemiology</topic><topic>Ethiopia - 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Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agriculture Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials science collection</collection><collection>Publicly Available Content Database</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 China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mekonnen, Berhanu Abebaw</au><au>Oumer, Abdu</au><au>Ale, Ahmed</au><au>Hamza, Aragaw</au><au>Dagne, Imam</au><au>Umer, Abdurezak Adem</au><au>Fentie, Dilnessa</au><au>Yigezu, Muluken</au><au>Tariku, Zerihun</au><au>Abate, Shambel</au><au>Asghari Jafarabadi, Mohammad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Major dietary patterns of community dwelling adults and their associations with impaired blood glucose and central obesity in Eastern Ethiopia: Diet-disease epidemiological study</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2023-04-20</date><risdate>2023</risdate><volume>18</volume><issue>4</issue><spage>e0283075</spage><epage>e0283075</epage><pages>e0283075-e0283075</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Unhealthy dietary intake is an important preventable risk factor for obesity and impaired blood glucose (IBG), ultimately increasing the risk of non-communicable diseases. When compared to individual food intakes, dietary patterns are a stronger predictor of health outcomes and should be systematically evaluated where such evidence is lacking. This study evaluated dietary patterns and their association with the risk of central obesity and IBG among adults.
A community-based survey was conducted among 501 randomly-selected adults from Eastern Ethiopia. Data was collected using a semi-structured questionnaire during a face-to-face interview that included sociodemographic and lifestyle factors, as well as a validated 89-item food frequency questionnaire (collected over one month). Principal component analysis was used to derive the dietary pattern. While central obesity was assessed using waist and/or hip circumference measurements, fasting blood sugar was used for IBG. A multivariable logistic regression model was fitted with an odds ratio, 95% confidence intervals, and p-values reported.
A total of 501 adults (95.3%) were interviewed, with a mean age of 41 years (±12). Five major dietary patterns explaining 71% of the total variance were identified: "nutrient-dense foods", "high fat and protein", "processed foods", "alcohol drinks", and "cereal diets". While 20.4% (17.0-24.2%) had IBG, 14.6% (11.8-17.9) were centrally obese, and 94.6% (92.3-96.3) had an increased waist-to-hip circumference ratio. Central obesity is associated with upper wealth status (AOR = 6.92; 2.91-16.5), physical inactivity (AOR = 21.1; 2.77-161.4), a diet high in nutrient-dense foods (AOR = 1.75; 0.75-4.06), processed foods (AOR = 1.41; 0.57-3.48), and cereal diets (AOR = 4.06; 1.87-8.82). The burden of IBG was associated with upper wealth status (AOR = 2.36; 1.36-4.10), physical inactivity (AOR = 2.17; 0.91-5.18), upper tercile of nutrient-dense foods (AOR = 1.35; 0.62-2.93), fat and protein diet (AOR = 1.31; 0.66-2.62), and cereal diet consumption (AOR = 3.87; 1.66-9.02).
IBG and central obesity were prevalent and predicted by upper tercile consumption of nutrient-dense foods, high fat and protein diets, processed foods, and cereal diets, which could guide dietary interventions.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>37079596</pmid><doi>10.1371/journal.pone.0283075</doi><tpages>e0283075</tpages><orcidid>https://orcid.org/0000-0002-0839-9461</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
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issn | 1932-6203 1932-6203 |
language | eng |
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source | PubMed (Medline); Publicly Available Content Database; Coronavirus Research Database |
subjects | Adult Adults Agricultural production Biology and Life Sciences Blood Blood Glucose Blood sugar Cereals Communicable diseases Comparative analysis Cross-Sectional Studies Diabetes Diagnosis Diet Dietary intake Epidemiologic Studies Epidemiology Ethiopia - epidemiology Evaluation Exercise Fasting Feeding Behavior Food Food consumption Food intake Food processing Glucose Health aspects Health risks High fat diet High protein diet Hip Households Humans Independent Living Interviews Life style Lifestyles Medical research Medicine and Health Sciences Medicine, Experimental Mortality Nutrients Obesity Obesity - epidemiology Obesity - etiology Obesity, Abdominal - epidemiology Obesity, Abdominal - etiology Population Principal components analysis Processed foods Productivity Proteins Public health Questionnaires Regression models Risk factors Sample size Socioeconomics Statistical analysis Surveys Urban areas |
title | Major dietary patterns of community dwelling adults and their associations with impaired blood glucose and central obesity in Eastern Ethiopia: Diet-disease epidemiological study |
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