Dietary patterns and diet quality among diverse older adults: The university of Alabama at Birmingham study of aging

OBJECTIVES: To characterize dietary patterns among a diverse sample of older adults (≥ 65 years). DESIGN: Cross-sectional. SETTING: Five counties in west central Alabama. PARTICIPANTS: Community-dwelling Medicare beneficiaries (N=416; 76.8 ±5.2 years, 56% female, 39% African American) in the Univers...

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Veröffentlicht in:The Journal of nutrition, health & aging health & aging, 2013, Vol.17 (1), p.19-25
Hauptverfasser: Hsiao, Pao Ying, Mitchell, D. C, Coffman, D. L, Allman, R. M, Locher, J. L, Sawyer, P, Jensen, Gordon L, Hartman, T. J
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container_end_page 25
container_issue 1
container_start_page 19
container_title The Journal of nutrition, health & aging
container_volume 17
creator Hsiao, Pao Ying
Mitchell, D. C
Coffman, D. L
Allman, R. M
Locher, J. L
Sawyer, P
Jensen, Gordon L
Hartman, T. J
description OBJECTIVES: To characterize dietary patterns among a diverse sample of older adults (≥ 65 years). DESIGN: Cross-sectional. SETTING: Five counties in west central Alabama. PARTICIPANTS: Community-dwelling Medicare beneficiaries (N=416; 76.8 ±5.2 years, 56% female, 39% African American) in the University of Alabama at Birmingham (UAB) Study of Aging. MEASUREMENTS: Dietary data collected via three, unannounced 24-hour dietary recalls was used to identify dietary patterns. Foods were aggregated into 13 groups. Finite mixture modeling (FMM) was used to classify individuals into three dietary patterns. Differences across dietary patterns for nutrient intakes, sociodemographic, and anthropometric measurements were examined using chi-square and general linear models. RESULTS: Three dietary patterns were derived. A “More healthful” dietary pattern, with relatively higher intakes of fruit, vegetables, whole grains, eggs, nuts, legumes and dairy, was associated with lower energy density, higher quality diets as determined by Healthy Eating Index (HEI)-2005 scores and higher intakes of fiber, folate, vitamins C and B6, calcium, iron, magnesium, and zinc. The “Westernlike” pattern was defined by an intake of starchy vegetables, refined grains, meats, fried poultry and fish, oils and fats and was associated with lower HEI-2005 scores. The “Low produce, high sweets” pattern was characterized by high saturated fat, and low dietary fiber and vitamin C intakes. The strongest predictors of better diet quality were female gender and non-Hispanic white race. CONCLUSION: The dietary patterns identified may provide a useful basis on which to base dietary interventions targeted at older adults. Examination of nutrient intakes regardless of the dietary pattern suggests that older adults are not meeting nutrient recommendations and should continue to be encouraged to choose high quality diets.
doi_str_mv 10.1007/s12603-012-0082-4
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C ; Coffman, D. L ; Allman, R. M ; Locher, J. L ; Sawyer, P ; Jensen, Gordon L ; Hartman, T. J</creator><creatorcontrib>Hsiao, Pao Ying ; Mitchell, D. C ; Coffman, D. L ; Allman, R. M ; Locher, J. L ; Sawyer, P ; Jensen, Gordon L ; Hartman, T. J</creatorcontrib><description>OBJECTIVES: To characterize dietary patterns among a diverse sample of older adults (≥ 65 years). DESIGN: Cross-sectional. SETTING: Five counties in west central Alabama. PARTICIPANTS: Community-dwelling Medicare beneficiaries (N=416; 76.8 ±5.2 years, 56% female, 39% African American) in the University of Alabama at Birmingham (UAB) Study of Aging. MEASUREMENTS: Dietary data collected via three, unannounced 24-hour dietary recalls was used to identify dietary patterns. Foods were aggregated into 13 groups. Finite mixture modeling (FMM) was used to classify individuals into three dietary patterns. Differences across dietary patterns for nutrient intakes, sociodemographic, and anthropometric measurements were examined using chi-square and general linear models. RESULTS: Three dietary patterns were derived. A “More healthful” dietary pattern, with relatively higher intakes of fruit, vegetables, whole grains, eggs, nuts, legumes and dairy, was associated with lower energy density, higher quality diets as determined by Healthy Eating Index (HEI)-2005 scores and higher intakes of fiber, folate, vitamins C and B6, calcium, iron, magnesium, and zinc. The “Westernlike” pattern was defined by an intake of starchy vegetables, refined grains, meats, fried poultry and fish, oils and fats and was associated with lower HEI-2005 scores. The “Low produce, high sweets” pattern was characterized by high saturated fat, and low dietary fiber and vitamin C intakes. The strongest predictors of better diet quality were female gender and non-Hispanic white race. CONCLUSION: The dietary patterns identified may provide a useful basis on which to base dietary interventions targeted at older adults. Examination of nutrient intakes regardless of the dietary pattern suggests that older adults are not meeting nutrient recommendations and should continue to be encouraged to choose high quality diets.</description><identifier>ISSN: 1279-7707</identifier><identifier>EISSN: 1760-4788</identifier><identifier>DOI: 10.1007/s12603-012-0082-4</identifier><identifier>PMID: 23299373</identifier><language>eng</language><publisher>Paris: Springer-Verlag</publisher><subject><![CDATA[administration & dosage ; African Americans ; Aged ; Aged, 80 and over ; Aging ; Alabama ; analysis ; anthropometric measurements ; ascorbic acid ; Beneficiaries ; Biological and medical sciences ; Body Mass Index ; calcium ; chemistry ; Cluster Analysis ; Cross-Sectional Studies ; dairy consumption ; Dairy Products ; Data collection ; Diet ; diet recall ; dietary fiber ; Dietary Fiber - administration & dosage ; Dietary Fiber - analysis ; dietary recommendations ; eating habits ; Edible Grain ; Edible Grain - chemistry ; Eggs ; elderly ; energy density ; Energy Intake ; Fabaceae ; Fabaceae - chemistry ; Fatty Acids ; Fatty Acids - administration & dosage ; Fatty Acids - analysis ; Feeding Behavior ; Feeding. Feeding behavior ; Female ; Females ; fish ; folic acid ; Follow-Up Studies ; Food ; Fruit ; Fruit - chemistry ; fruit consumption ; Fundamental and applied biological sciences. Psychology ; Gender ; Geriatric Assessment ; Geriatric Assessment - methods ; Geriatrics ; Geriatrics/Gerontology ; Health care ; healthy diet ; Humans ; iron ; legumes ; Linear Models ; lipids ; Logistic Models ; Longitudinal Studies ; magnesium ; Male ; meat ; Medicare ; Medicine ; Medicine & Public Health ; methods ; Micronutrients ; Micronutrients - administration & dosage ; Micronutrients - analysis ; Mobility ; Neurosciences ; nutrient intake ; Nutrients ; Nutrition ; Nutrition research ; nutritional adequacy ; Nutritive Value ; nuts ; Nuts - chemistry ; Obesity ; oils ; Oils & fats ; Older people ; poultry ; Primary Care Medicine ; pyridoxine ; Quality of Life Research ; refined grains ; Rural Population ; Sociodemographics ; Socioeconomic Factors ; Surveys and Questionnaires ; sweets ; Urban Population ; vegetables ; Vegetables - chemistry ; Vertebrates: anatomy and physiology, studies on body, several organs or systems ; Whites ; whole grain foods ; zinc]]></subject><ispartof>The Journal of nutrition, health &amp; aging, 2013, Vol.17 (1), p.19-25</ispartof><rights>Serdi and Springer Verlag France 2013</rights><rights>2014 INIST-CNRS</rights><rights>Serdi and Springer-Verlag France 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c557t-c0c5fa78cbfb25ab97c5455bb8c4407e3dc5fd379edb415afd7a8e1f1dcdf3e3</citedby><cites>FETCH-LOGICAL-c557t-c0c5fa78cbfb25ab97c5455bb8c4407e3dc5fd379edb415afd7a8e1f1dcdf3e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12603-012-0082-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12603-012-0082-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,776,780,881,4010,27900,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=26803620$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23299373$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hsiao, Pao Ying</creatorcontrib><creatorcontrib>Mitchell, D. C</creatorcontrib><creatorcontrib>Coffman, D. L</creatorcontrib><creatorcontrib>Allman, R. M</creatorcontrib><creatorcontrib>Locher, J. L</creatorcontrib><creatorcontrib>Sawyer, P</creatorcontrib><creatorcontrib>Jensen, Gordon L</creatorcontrib><creatorcontrib>Hartman, T. J</creatorcontrib><title>Dietary patterns and diet quality among diverse older adults: The university of Alabama at Birmingham study of aging</title><title>The Journal of nutrition, health &amp; aging</title><addtitle>J Nutr Health Aging</addtitle><addtitle>J Nutr Health Aging</addtitle><description>OBJECTIVES: To characterize dietary patterns among a diverse sample of older adults (≥ 65 years). DESIGN: Cross-sectional. SETTING: Five counties in west central Alabama. PARTICIPANTS: Community-dwelling Medicare beneficiaries (N=416; 76.8 ±5.2 years, 56% female, 39% African American) in the University of Alabama at Birmingham (UAB) Study of Aging. MEASUREMENTS: Dietary data collected via three, unannounced 24-hour dietary recalls was used to identify dietary patterns. Foods were aggregated into 13 groups. Finite mixture modeling (FMM) was used to classify individuals into three dietary patterns. Differences across dietary patterns for nutrient intakes, sociodemographic, and anthropometric measurements were examined using chi-square and general linear models. RESULTS: Three dietary patterns were derived. A “More healthful” dietary pattern, with relatively higher intakes of fruit, vegetables, whole grains, eggs, nuts, legumes and dairy, was associated with lower energy density, higher quality diets as determined by Healthy Eating Index (HEI)-2005 scores and higher intakes of fiber, folate, vitamins C and B6, calcium, iron, magnesium, and zinc. The “Westernlike” pattern was defined by an intake of starchy vegetables, refined grains, meats, fried poultry and fish, oils and fats and was associated with lower HEI-2005 scores. The “Low produce, high sweets” pattern was characterized by high saturated fat, and low dietary fiber and vitamin C intakes. The strongest predictors of better diet quality were female gender and non-Hispanic white race. CONCLUSION: The dietary patterns identified may provide a useful basis on which to base dietary interventions targeted at older adults. Examination of nutrient intakes regardless of the dietary pattern suggests that older adults are not meeting nutrient recommendations and should continue to be encouraged to choose high quality diets.</description><subject>administration &amp; dosage</subject><subject>African Americans</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Aging</subject><subject>Alabama</subject><subject>analysis</subject><subject>anthropometric measurements</subject><subject>ascorbic acid</subject><subject>Beneficiaries</subject><subject>Biological and medical sciences</subject><subject>Body Mass Index</subject><subject>calcium</subject><subject>chemistry</subject><subject>Cluster Analysis</subject><subject>Cross-Sectional Studies</subject><subject>dairy consumption</subject><subject>Dairy Products</subject><subject>Data collection</subject><subject>Diet</subject><subject>diet recall</subject><subject>dietary fiber</subject><subject>Dietary Fiber - administration &amp; dosage</subject><subject>Dietary Fiber - analysis</subject><subject>dietary recommendations</subject><subject>eating habits</subject><subject>Edible Grain</subject><subject>Edible Grain - chemistry</subject><subject>Eggs</subject><subject>elderly</subject><subject>energy density</subject><subject>Energy Intake</subject><subject>Fabaceae</subject><subject>Fabaceae - chemistry</subject><subject>Fatty Acids</subject><subject>Fatty Acids - administration &amp; dosage</subject><subject>Fatty Acids - analysis</subject><subject>Feeding Behavior</subject><subject>Feeding. Feeding behavior</subject><subject>Female</subject><subject>Females</subject><subject>fish</subject><subject>folic acid</subject><subject>Follow-Up Studies</subject><subject>Food</subject><subject>Fruit</subject><subject>Fruit - chemistry</subject><subject>fruit consumption</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Gender</subject><subject>Geriatric Assessment</subject><subject>Geriatric Assessment - methods</subject><subject>Geriatrics</subject><subject>Geriatrics/Gerontology</subject><subject>Health care</subject><subject>healthy diet</subject><subject>Humans</subject><subject>iron</subject><subject>legumes</subject><subject>Linear Models</subject><subject>lipids</subject><subject>Logistic Models</subject><subject>Longitudinal Studies</subject><subject>magnesium</subject><subject>Male</subject><subject>meat</subject><subject>Medicare</subject><subject>Medicine</subject><subject>Medicine &amp; Public Health</subject><subject>methods</subject><subject>Micronutrients</subject><subject>Micronutrients - administration &amp; dosage</subject><subject>Micronutrients - analysis</subject><subject>Mobility</subject><subject>Neurosciences</subject><subject>nutrient intake</subject><subject>Nutrients</subject><subject>Nutrition</subject><subject>Nutrition research</subject><subject>nutritional adequacy</subject><subject>Nutritive Value</subject><subject>nuts</subject><subject>Nuts - chemistry</subject><subject>Obesity</subject><subject>oils</subject><subject>Oils &amp; fats</subject><subject>Older people</subject><subject>poultry</subject><subject>Primary Care Medicine</subject><subject>pyridoxine</subject><subject>Quality of Life Research</subject><subject>refined grains</subject><subject>Rural Population</subject><subject>Sociodemographics</subject><subject>Socioeconomic Factors</subject><subject>Surveys and Questionnaires</subject><subject>sweets</subject><subject>Urban Population</subject><subject>vegetables</subject><subject>Vegetables - chemistry</subject><subject>Vertebrates: anatomy and physiology, studies on body, several organs or systems</subject><subject>Whites</subject><subject>whole grain foods</subject><subject>zinc</subject><issn>1279-7707</issn><issn>1760-4788</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkU1v1DAQhiMEoqXwA7iAJYTEJeDP2OGAVMqnVIkDy9ma2E42VWJvbadS_z1OdymFA_hia95nxjPzVtVTgl8TjOWbRGiDWY0JrTFWtOb3qmMiG1xzqdT98qayraXE8qh6lNIFxly0qnlYHVFG25ZJdlzlD6PLEK_RDnJ20ScE3iJbguhygWnM1wjm4IcSunIxORQm6yICu0w5vUWbrUOLv5FWNPTodIIOZkCQ0fsxzqMftjCjlBd7I8NQIo-rBz1MyT053CfV5tPHzdmX-vzb569np-e1EULm2mAjepDKdH1HBXStNIIL0XXKcI6lY7bolsnW2Y4TAb2VoBzpiTW2Z46dVO_2ZXdLNztrnM8RJr2L41wm1gFG_afix60ewpVmQnIlaSnw6lAghsvFpaznMRk3TeBdWJKmeD2s4eK_aLGCMb4aUNAXf6EXYYm-LGKlMGNMNk2hyJ4yMaQUXX_bN8F6dV_v3dfFfb26r3nJeXZ34NuMX3YX4OUBgGRg6iN4M6bfXKPKNBQXju65VCQ_uHinxX_8_nyf1EPQMMRS-Md3igkvO1KcNIr9BO7c0uk</recordid><startdate>2013</startdate><enddate>2013</enddate><creator>Hsiao, Pao Ying</creator><creator>Mitchell, D. 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C</au><au>Coffman, D. L</au><au>Allman, R. M</au><au>Locher, J. L</au><au>Sawyer, P</au><au>Jensen, Gordon L</au><au>Hartman, T. J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dietary patterns and diet quality among diverse older adults: The university of Alabama at Birmingham study of aging</atitle><jtitle>The Journal of nutrition, health &amp; aging</jtitle><stitle>J Nutr Health Aging</stitle><addtitle>J Nutr Health Aging</addtitle><date>2013</date><risdate>2013</risdate><volume>17</volume><issue>1</issue><spage>19</spage><epage>25</epage><pages>19-25</pages><issn>1279-7707</issn><eissn>1760-4788</eissn><abstract>OBJECTIVES: To characterize dietary patterns among a diverse sample of older adults (≥ 65 years). DESIGN: Cross-sectional. SETTING: Five counties in west central Alabama. PARTICIPANTS: Community-dwelling Medicare beneficiaries (N=416; 76.8 ±5.2 years, 56% female, 39% African American) in the University of Alabama at Birmingham (UAB) Study of Aging. MEASUREMENTS: Dietary data collected via three, unannounced 24-hour dietary recalls was used to identify dietary patterns. Foods were aggregated into 13 groups. Finite mixture modeling (FMM) was used to classify individuals into three dietary patterns. Differences across dietary patterns for nutrient intakes, sociodemographic, and anthropometric measurements were examined using chi-square and general linear models. RESULTS: Three dietary patterns were derived. A “More healthful” dietary pattern, with relatively higher intakes of fruit, vegetables, whole grains, eggs, nuts, legumes and dairy, was associated with lower energy density, higher quality diets as determined by Healthy Eating Index (HEI)-2005 scores and higher intakes of fiber, folate, vitamins C and B6, calcium, iron, magnesium, and zinc. The “Westernlike” pattern was defined by an intake of starchy vegetables, refined grains, meats, fried poultry and fish, oils and fats and was associated with lower HEI-2005 scores. The “Low produce, high sweets” pattern was characterized by high saturated fat, and low dietary fiber and vitamin C intakes. The strongest predictors of better diet quality were female gender and non-Hispanic white race. CONCLUSION: The dietary patterns identified may provide a useful basis on which to base dietary interventions targeted at older adults. Examination of nutrient intakes regardless of the dietary pattern suggests that older adults are not meeting nutrient recommendations and should continue to be encouraged to choose high quality diets.</abstract><cop>Paris</cop><pub>Springer-Verlag</pub><pmid>23299373</pmid><doi>10.1007/s12603-012-0082-4</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record>
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ispartof The Journal of nutrition, health & aging, 2013, Vol.17 (1), p.19-25
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1760-4788
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source MEDLINE; Alma/SFX Local Collection; SpringerLink Journals - AutoHoldings
subjects administration & dosage
African Americans
Aged
Aged, 80 and over
Aging
Alabama
analysis
anthropometric measurements
ascorbic acid
Beneficiaries
Biological and medical sciences
Body Mass Index
calcium
chemistry
Cluster Analysis
Cross-Sectional Studies
dairy consumption
Dairy Products
Data collection
Diet
diet recall
dietary fiber
Dietary Fiber - administration & dosage
Dietary Fiber - analysis
dietary recommendations
eating habits
Edible Grain
Edible Grain - chemistry
Eggs
elderly
energy density
Energy Intake
Fabaceae
Fabaceae - chemistry
Fatty Acids
Fatty Acids - administration & dosage
Fatty Acids - analysis
Feeding Behavior
Feeding. Feeding behavior
Female
Females
fish
folic acid
Follow-Up Studies
Food
Fruit
Fruit - chemistry
fruit consumption
Fundamental and applied biological sciences. Psychology
Gender
Geriatric Assessment
Geriatric Assessment - methods
Geriatrics
Geriatrics/Gerontology
Health care
healthy diet
Humans
iron
legumes
Linear Models
lipids
Logistic Models
Longitudinal Studies
magnesium
Male
meat
Medicare
Medicine
Medicine & Public Health
methods
Micronutrients
Micronutrients - administration & dosage
Micronutrients - analysis
Mobility
Neurosciences
nutrient intake
Nutrients
Nutrition
Nutrition research
nutritional adequacy
Nutritive Value
nuts
Nuts - chemistry
Obesity
oils
Oils & fats
Older people
poultry
Primary Care Medicine
pyridoxine
Quality of Life Research
refined grains
Rural Population
Sociodemographics
Socioeconomic Factors
Surveys and Questionnaires
sweets
Urban Population
vegetables
Vegetables - chemistry
Vertebrates: anatomy and physiology, studies on body, several organs or systems
Whites
whole grain foods
zinc
title Dietary patterns and diet quality among diverse older adults: The university of Alabama at Birmingham study of aging
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