population-based approach to define body-composition phenotypes
Background: Abnormal body compositions such as high adiposity (HA), low muscle mass (LM), or a combination of the 2 [high adiposity with low muscle mass (HA-LM)] are relevant phenotypes, but data on their prevalence and impact on health are still limited. This is largely because of a lack of a conse...
Saved in:
Published in | The American journal of clinical nutrition Vol. 99; no. 6; pp. 1369 - 1377 |
---|---|
Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Society for Clinical Nutrition
01.06.2014
American Society for Clinical Nutrition, Inc |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Background: Abnormal body compositions such as high adiposity (HA), low muscle mass (LM), or a combination of the 2 [high adiposity with low muscle mass (HA-LM)] are relevant phenotypes, but data on their prevalence and impact on health are still limited. This is largely because of a lack of a consensus definition for these conditions. Of particular interest is the HA-LM phenotype, also termed “sarcopenic obesity,” which may confer greater health risk.Objective: We propose a new approach for operationalizing abnormal body-composition phenotypes in a representative adult population.Design: Whole-body dual-energy X-ray absorptiometry data obtained from the 1999–2004 NHANES were analyzed for 13,236 subjects aged ≥18 y (maximum weight and height of 136 kg and 1.96 m, respectively). Sex- and body mass index (BMI)–specific decile groups of appendicular skeletal muscle index (ASMI; kg/m2) and fat mass index (FMI; kg/m2) were developed. Cutoffs for HA and LM were incorporated into a diagnostic framework to characterize 4 specific body-composition phenotypes—low adiposity with high muscle mass, high adiposity with high muscle mass, low adiposity with low muscle mass, and HA-LM—and a subclassification of the phenotypes into classes I, II, and III.Results: Abnormal phenotypes were prevalent across the age spectrum and BMI categories. The association between ASMI or FMI and age was modified by sex and BMI. The prevalence of HA-LM in the whole sample was 10.3% in women and 15.2% in men. The prevalence of all subclasses of HA-LM in obese women and men was 14.7% and 22.9%, respectively. HA-LM class III was more prevalent in obese men (2.3%) than in obese women (0.3%).Conclusions: We developed sex- and BMI-specific reference curves to harmonize the classification of body-composition phenotypes. The application of this classification will be particularly useful in the identification of cases of sarcopenic obesity. The association of these phenotypes with metabolic deregulation and increased disease risk awaits verification. |
---|---|
AbstractList | Background: Abnormal body compositions such as high adiposity (HA), low muscle mass (LM), or a combination of the 2 [high adiposity with low muscle mass (HA-LM)] are relevant phenotypes, but data on their prevalence and impact on health are still limited. This is largely because of a lack of a consensus definition for these conditions. Of particular interest is the HA-LM phenotype, also termed “sarcopenic obesity,” which may confer greater health risk.Objective: We propose a new approach for operationalizing abnormal body-composition phenotypes in a representative adult population.Design: Whole-body dual-energy X-ray absorptiometry data obtained from the 1999–2004 NHANES were analyzed for 13,236 subjects aged ≥18 y (maximum weight and height of 136 kg and 1.96 m, respectively). Sex- and body mass index (BMI)–specific decile groups of appendicular skeletal muscle index (ASMI; kg/m2) and fat mass index (FMI; kg/m2) were developed. Cutoffs for HA and LM were incorporated into a diagnostic framework to characterize 4 specific body-composition phenotypes—low adiposity with high muscle mass, high adiposity with high muscle mass, low adiposity with low muscle mass, and HA-LM—and a subclassification of the phenotypes into classes I, II, and III.Results: Abnormal phenotypes were prevalent across the age spectrum and BMI categories. The association between ASMI or FMI and age was modified by sex and BMI. The prevalence of HA-LM in the whole sample was 10.3% in women and 15.2% in men. The prevalence of all subclasses of HA-LM in obese women and men was 14.7% and 22.9%, respectively. HA-LM class III was more prevalent in obese men (2.3%) than in obese women (0.3%).Conclusions: We developed sex- and BMI-specific reference curves to harmonize the classification of body-composition phenotypes. The application of this classification will be particularly useful in the identification of cases of sarcopenic obesity. The association of these phenotypes with metabolic deregulation and increased disease risk awaits verification. Abnormal body compositions such as high adiposity (HA), low muscle mass (LM), or a combination of the 2 [high adiposity with low muscle mass (HA-LM)] are relevant phenotypes, but data on their prevalence and impact on health are still limited. This is largely because of a lack of a consensus definition for these conditions. Of particular interest is the HA-LM phenotype, also termed "sarcopenic obesity," which may confer greater health risk. We propose a new approach for operationalizing abnormal body-composition phenotypes in a representative adult population. Whole-body dual-energy X-ray absorptiometry data obtained from the 1999-2004 NHANES were analyzed for 13,236 subjects aged ≥18 y (maximum weight and height of 136 kg and 1.96 m, respectively). Sex- and body mass index (BMI)-specific decile groups of appendicular skeletal muscle index (ASMI; kg/m2) and fat mass index (FMI; kg/m2) were developed. Cutoffs for HA and LM were incorporated into a diagnostic framework to characterize 4 specific body-composition phenotypes -- low adiposity with high muscle mass, high adiposity with high muscle mass, low adiposity with low muscle mass, and HA-LM -- and a subclassification of the phenotypes into classes I, II, and III. Abnormal phenotypes were prevalent across the age spectrum and BMI categories. The association between ASMI or FMI and age was modified by sex and BMI. The prevalence of HA-LM in the whole sample was 10.3% in women and 15.2% in men. The prevalence of all subclasses of HA-LM in obese women and men was 14.7% and 22.9%, respectively. HA-LM class III was more prevalent in obese men (2.3%) than in obese women (0.3%). We developed sex- and BMI-specific reference curves to harmonize the classification of body-composition phenotypes. The application of this classification will be particularly useful in the identification of cases of sarcopenic obesity. The association of these phenotypes with metabolic deregulation and increased disease risk awaits verification. Abnormal body compositions such as high adiposity (HA), low muscle mass (LM), or a combination of the 2 [high adiposity with low muscle mass (HA-LM)] are relevant phenotypes, but data on their prevalence and impact on health are still limited. This is largely because of a lack of a consensus definition for these conditions. Of particular interest is the HA-LM phenotype, also termed "sarcopenic obesity," which may confer greater health risk.BACKGROUNDAbnormal body compositions such as high adiposity (HA), low muscle mass (LM), or a combination of the 2 [high adiposity with low muscle mass (HA-LM)] are relevant phenotypes, but data on their prevalence and impact on health are still limited. This is largely because of a lack of a consensus definition for these conditions. Of particular interest is the HA-LM phenotype, also termed "sarcopenic obesity," which may confer greater health risk.We propose a new approach for operationalizing abnormal body-composition phenotypes in a representative adult population.OBJECTIVEWe propose a new approach for operationalizing abnormal body-composition phenotypes in a representative adult population.Whole-body dual-energy X-ray absorptiometry data obtained from the 1999-2004 NHANES were analyzed for 13,236 subjects aged ≥18 y (maximum weight and height of 136 kg and 1.96 m, respectively). Sex- and body mass index (BMI)-specific decile groups of appendicular skeletal muscle index (ASMI; kg/m²) and fat mass index (FMI; kg/m²) were developed. Cutoffs for HA and LM were incorporated into a diagnostic framework to characterize 4 specific body-composition phenotypes-low adiposity with high muscle mass, high adiposity with high muscle mass, low adiposity with low muscle mass, and HA-LM-and a subclassification of the phenotypes into classes I, II, and III.DESIGNWhole-body dual-energy X-ray absorptiometry data obtained from the 1999-2004 NHANES were analyzed for 13,236 subjects aged ≥18 y (maximum weight and height of 136 kg and 1.96 m, respectively). Sex- and body mass index (BMI)-specific decile groups of appendicular skeletal muscle index (ASMI; kg/m²) and fat mass index (FMI; kg/m²) were developed. Cutoffs for HA and LM were incorporated into a diagnostic framework to characterize 4 specific body-composition phenotypes-low adiposity with high muscle mass, high adiposity with high muscle mass, low adiposity with low muscle mass, and HA-LM-and a subclassification of the phenotypes into classes I, II, and III.Abnormal phenotypes were prevalent across the age spectrum and BMI categories. The association between ASMI or FMI and age was modified by sex and BMI. The prevalence of HA-LM in the whole sample was 10.3% in women and 15.2% in men. The prevalence of all subclasses of HA-LM in obese women and men was 14.7% and 22.9%, respectively. HA-LM class III was more prevalent in obese men (2.3%) than in obese women (0.3%).RESULTSAbnormal phenotypes were prevalent across the age spectrum and BMI categories. The association between ASMI or FMI and age was modified by sex and BMI. The prevalence of HA-LM in the whole sample was 10.3% in women and 15.2% in men. The prevalence of all subclasses of HA-LM in obese women and men was 14.7% and 22.9%, respectively. HA-LM class III was more prevalent in obese men (2.3%) than in obese women (0.3%).We developed sex- and BMI-specific reference curves to harmonize the classification of body-composition phenotypes. The application of this classification will be particularly useful in the identification of cases of sarcopenic obesity. The association of these phenotypes with metabolic deregulation and increased disease risk awaits verification.CONCLUSIONSWe developed sex- and BMI-specific reference curves to harmonize the classification of body-composition phenotypes. The application of this classification will be particularly useful in the identification of cases of sarcopenic obesity. The association of these phenotypes with metabolic deregulation and increased disease risk awaits verification. Abnormal body compositions such as high adiposity (HA), low muscle mass (LM), or a combination of the 2 [high adiposity with low muscle mass (HA-LM)] are relevant phenotypes, but data on their prevalence and impact on health are still limited. This is largely because of a lack of a consensus definition for these conditions. Of particular interest is the HA-LM phenotype, also termed "sarcopenic obesity," which may confer greater health risk. We propose a new approach for operationalizing abnormal body-composition phenotypes in a representative adult population. Whole-body dual-energy X-ray absorptiometry data obtained from the 1999-2004 NHANES were analyzed for 13,236 subjects aged ≥18 y (maximum weight and height of 136 kg and 1.96 m, respectively). Sex- and body mass index (BMI)-specific decile groups of appendicular skeletal muscle index (ASMI; kg/m²) and fat mass index (FMI; kg/m²) were developed. Cutoffs for HA and LM were incorporated into a diagnostic framework to characterize 4 specific body-composition phenotypes-low adiposity with high muscle mass, high adiposity with high muscle mass, low adiposity with low muscle mass, and HA-LM-and a subclassification of the phenotypes into classes I, II, and III. Abnormal phenotypes were prevalent across the age spectrum and BMI categories. The association between ASMI or FMI and age was modified by sex and BMI. The prevalence of HA-LM in the whole sample was 10.3% in women and 15.2% in men. The prevalence of all subclasses of HA-LM in obese women and men was 14.7% and 22.9%, respectively. HA-LM class III was more prevalent in obese men (2.3%) than in obese women (0.3%). We developed sex- and BMI-specific reference curves to harmonize the classification of body-composition phenotypes. The application of this classification will be particularly useful in the identification of cases of sarcopenic obesity. The association of these phenotypes with metabolic deregulation and increased disease risk awaits verification. |
Author | Katzmarzyk, Peter T Smith, Steven R Broyles, Stephanie Siervo, Mario Heymsfield, Steven B Wells, Jonathan CK Stephan, Blossom CM Prado, Carla MM Mire, Emily |
Author_xml | – sequence: 1 fullname: Prado, Carla MM – sequence: 2 fullname: Siervo, Mario – sequence: 3 fullname: Mire, Emily – sequence: 4 fullname: Heymsfield, Steven B – sequence: 5 fullname: Stephan, Blossom CM – sequence: 6 fullname: Broyles, Stephanie – sequence: 7 fullname: Smith, Steven R – sequence: 8 fullname: Wells, Jonathan CK – sequence: 9 fullname: Katzmarzyk, Peter T |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24760978$$D View this record in MEDLINE/PubMed |
BookMark | eNqNkb1v2zAUxIkiQeykmbu1ArJ0kcPHT3EqiiBNCwTIEHcmKPKpliGLqigN_u9Lx_ESoECmt_zu8O7ukpz1sUdCPgFdcSPkrdv6fgXAV1RXUqsPZAmGVyVnVJ-RJaWUlQaUXJDLlLaUAhOVuiALJrSiRldL8m2Iw9y5qY19WbuEoXDDMEbnN8UUi4BN22NRx7AvfdwNMbUHshg22MdpP2D6SM4b1yW8fr1XZP3jfn33s3x8evh19_2x9KIyUxnq2vOK5Q8QQDeKaQZCCQzOU2TIRKMqpoNjzoADVB6DDoYKY6gEQ_kV-Xq0zb_9nTFNdtcmj13neoxzsqByfqa14e9ApdEq5xcZvXmDbuM89jmHBckZy6CATH1-peZ6h8EOY7tz496eSsyAPAJ-jCmN2FjfTi-VTqNrOwvUHsayh7FsHssex8q62ze6k_X_FV-OisZF6_6MbbK_nxkFmYuVQIXk_wC4kJ59 |
CitedBy_id | crossref_primary_10_1016_j_clnu_2017_09_021 crossref_primary_10_1038_nrdp_2017_34 crossref_primary_10_13066_kspm_2023_18_4_37 crossref_primary_10_1016_j_clnu_2021_01_005 crossref_primary_10_1186_s13098_015_0016_5 crossref_primary_10_1093_advances_nmab153 crossref_primary_10_34175_jno201601004 crossref_primary_10_1002_oby_24157 crossref_primary_10_1016_j_jocd_2022_01_002 crossref_primary_10_1038_ejcn_2015_185 crossref_primary_10_3389_fphys_2020_583825 crossref_primary_10_3390_jcm10153445 crossref_primary_10_1002_ncp_10374 crossref_primary_10_3945_an_115_008755 crossref_primary_10_1007_s11912_015_0488_3 crossref_primary_10_1111_nyas_12498 crossref_primary_10_1016_j_acra_2017_07_007 crossref_primary_10_3390_cancers14071846 crossref_primary_10_1515_revce_2016_0018 crossref_primary_10_1152_japplphysiol_00799_2015 crossref_primary_10_3945_cdn_117_001743 crossref_primary_10_2196_22989 crossref_primary_10_1016_j_clnu_2016_11_012 crossref_primary_10_1038_s41430_018_0340_6 crossref_primary_10_1155_2017_7307618 crossref_primary_10_1016_j_envpol_2021_118247 crossref_primary_10_3390_nu12030755 crossref_primary_10_1186_s40814_022_01137_6 crossref_primary_10_3945_ajcn_116_134221 crossref_primary_10_1093_ageing_afy143 crossref_primary_10_1016_j_clnu_2024_10_037 crossref_primary_10_20945_2359_3997000000124 crossref_primary_10_1007_s11690_017_0555_z crossref_primary_10_1016_j_maturitas_2014_12_023 crossref_primary_10_1152_japplphysiol_00162_2017 crossref_primary_10_1186_s12893_024_02408_0 crossref_primary_10_3945_ajcn_114_099697 crossref_primary_10_1007_s13679_016_0228_5 crossref_primary_10_1007_s11357_024_01245_6 crossref_primary_10_1016_j_nut_2022_111838 crossref_primary_10_1016_j_clnu_2019_11_024 crossref_primary_10_1080_07853890_2018_1511918 crossref_primary_10_1038_s41366_024_01511_9 crossref_primary_10_1016_S2213_8587_18_30204_3 crossref_primary_10_1210_clinem_dgac662 crossref_primary_10_1177_0148607114550189 crossref_primary_10_3389_fendo_2022_990442 crossref_primary_10_53435_funj_00978 crossref_primary_10_1513_AnnalsATS_202111_1221OC crossref_primary_10_1159_000518638 crossref_primary_10_1002_ncp_10230 crossref_primary_10_1016_j_jocd_2019_02_002 crossref_primary_10_1007_s11912_016_0522_0 crossref_primary_10_1016_j_ajo_2016_09_031 crossref_primary_10_13066_kspm_2023_18_3_1 crossref_primary_10_1183_09031936_00197314 crossref_primary_10_1371_journal_pone_0174180 crossref_primary_10_1002_jcsm_13714 crossref_primary_10_3389_fendo_2023_1077255 crossref_primary_10_1007_s11695_021_05530_7 crossref_primary_10_1016_j_ypmed_2022_107282 crossref_primary_10_1016_j_reuma_2015_03_005 crossref_primary_10_1016_j_clnu_2021_12_024 crossref_primary_10_1016_j_jocd_2021_07_013 crossref_primary_10_3889_oamjms_2022_9618 crossref_primary_10_1016_j_jhevol_2016_09_001 crossref_primary_10_1007_s00774_019_01071_3 crossref_primary_10_1016_j_clnu_2018_01_022 crossref_primary_10_1080_01635581_2022_2044059 crossref_primary_10_1016_j_jvs_2021_08_051 crossref_primary_10_1038_s41598_024_54102_z crossref_primary_10_13066_kspm_2024_19_1_31 crossref_primary_10_1016_j_clnu_2018_12_002 crossref_primary_10_3390_ijerph20021140 crossref_primary_10_1016_j_bone_2017_06_010 crossref_primary_10_1186_s12944_025_02437_5 crossref_primary_10_36384_01232576_559 crossref_primary_10_1016_j_advnut_2024_100364 crossref_primary_10_1002_rco2_70 crossref_primary_10_1016_j_jocd_2020_02_003 crossref_primary_10_1371_journal_pone_0142101 crossref_primary_10_3390_children8111047 crossref_primary_10_3390_nu15234932 crossref_primary_10_1016_j_clnesp_2022_10_010 crossref_primary_10_1080_01635581_2022_2081341 crossref_primary_10_3390_nu13072350 crossref_primary_10_1016_j_metabol_2018_12_012 crossref_primary_10_3390_ijerph14070809 crossref_primary_10_1159_000445380 crossref_primary_10_1186_s12891_018_2175_7 crossref_primary_10_1016_j_nut_2024_112526 crossref_primary_10_13066_kspm_2023_18_3_11 crossref_primary_10_1007_s00394_015_1000_4 crossref_primary_10_1016_j_bone_2024_117170 crossref_primary_10_1097_MCO_0000000000000216 crossref_primary_10_3390_nu9010023 crossref_primary_10_3390_jcm11082118 crossref_primary_10_1016_j_clnu_2020_11_031 crossref_primary_10_4093_dmj_2018_0141 crossref_primary_10_1016_j_clnesp_2018_07_005 crossref_primary_10_1002_jcsm_12712 crossref_primary_10_1111_jhn_12372 crossref_primary_10_1016_j_reumae_2015_03_013 crossref_primary_10_51745_najfnr_6_13_55_65 crossref_primary_10_1016_j_clnu_2016_12_028 crossref_primary_10_1097_MD_0000000000038422 crossref_primary_10_1080_27697061_2024_2333310 crossref_primary_10_3748_wjg_v22_i2_681 crossref_primary_10_1183_09059180_00010914 crossref_primary_10_3390_cancers15184600 crossref_primary_10_1007_s12018_016_9206_4 crossref_primary_10_1002_oby_23197 crossref_primary_10_1038_s41598_018_37347_3 crossref_primary_10_20945_2359_3997000000551 crossref_primary_10_1111_resp_14100 crossref_primary_10_1016_j_clnu_2023_03_006 crossref_primary_10_1007_s13410_015_0402_4 crossref_primary_10_1016_j_nut_2020_110765 crossref_primary_10_1017_S0029665115004206 crossref_primary_10_51745_najfnr_6_14_94_106 crossref_primary_10_1080_09637486_2021_1984401 crossref_primary_10_1038_s41366_021_00995_z crossref_primary_10_23736_S0031_0808_22_04784_X crossref_primary_10_1016_j_exger_2022_111991 crossref_primary_10_1038_s41430_020_0596_5 |
Cites_doi | 10.1038/sj.ejcn.1601024 10.1097/01.mol.0000319118.44995.9a 10.1016/j.clnu.2012.08.016 10.1385/JCD:8:3:293 10.1093/oxfordjournals.aje.a009520 10.1038/oby.2004.111 10.1093/ajcn/69.5.1007 10.1371/journal.pone.0007038 10.1111/j.1532-5415.2004.52014.x 10.1210/jc.2004-0535 10.1111/j.1749-6632.2000.tb06498.x 10.1097/gme.0b013e31825d26b6 10.1056/NEJMoa1007137 10.1038/oby.2004.250 10.1093/ajcn/52.2.214 10.1038/oby.2005.42 10.1016/j.cger.2011.03.007 10.1002/sim.1692 10.1093/ajcn/81.5.1018 10.1002/art.37696 10.1097/MCO.0b013e32833aabd9 10.1111/j.1749-6632.2000.tb06515.x 10.1093/ajcn/64.3.472S 10.1016/j.numecd.2011.12.001 10.3945/ajcn.2008.26847 10.1016/j.orcp.2011.05.001 10.1007/BF02992693 10.1016/j.clnu.2012.06.010 10.1038/oby.2004.107 10.1093/gerona/55.12.M716 10.1016/S1470-2045(08)70153-0 |
ContentType | Journal Article |
Copyright | 2014 American Society for Nutrition. Copyright American Society for Clinical Nutrition, Inc. Jun 1, 2014 |
Copyright_xml | – notice: 2014 American Society for Nutrition. – notice: Copyright American Society for Clinical Nutrition, Inc. Jun 1, 2014 |
DBID | FBQ AAYXX CITATION CGR CUY CVF ECM EIF NPM 7QP 7T7 7TS 8FD C1K FR3 K9. NAPCQ P64 7X8 7S9 L.6 |
DOI | 10.3945/ajcn.113.078576 |
DatabaseName | AGRIS CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Calcium & Calcified Tissue Abstracts Industrial and Applied Microbiology Abstracts (Microbiology A) Physical Education Index Technology Research Database Environmental Sciences and Pollution Management Engineering Research Database ProQuest Health & Medical Complete (Alumni) Nursing & Allied Health Premium Biotechnology and BioEngineering Abstracts MEDLINE - Academic AGRICOLA AGRICOLA - Academic |
DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Nursing & Allied Health Premium Technology Research Database ProQuest Health & Medical Complete (Alumni) Engineering Research Database Industrial and Applied Microbiology Abstracts (Microbiology A) Calcium & Calcified Tissue Abstracts Physical Education Index Biotechnology and BioEngineering Abstracts Environmental Sciences and Pollution Management MEDLINE - Academic AGRICOLA AGRICOLA - Academic |
DatabaseTitleList | AGRICOLA Nursing & Allied Health Premium MEDLINE - Academic MEDLINE |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 3 dbid: FBQ name: AGRIS url: http://www.fao.org/agris/Centre.asp?Menu_1ID=DB&Menu_2ID=DB1&Language=EN&Content=http://www.fao.org/agris/search?Language=EN sourceTypes: Publisher |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine Diet & Clinical Nutrition |
EISSN | 1938-3207 |
EndPage | 1377 |
ExternalDocumentID | 3324641091 24760978 10_3945_ajcn_113_078576 US201500151045 |
Genre | Research Support, Non-U.S. Gov't Journal Article |
GroupedDBID | --- -ET -~X ..I .55 .GJ 0R~ 1HT 23M 2FS 2WC 3O- 4.4 48X 53G 5GY 5RE 5VS 6J9 85S 8R4 8R5 AABZA AACZT AAGQS AAHBH AAIKC AAJQQ AAMNW AAPGJ AAPQZ AAUQX AAUTI AAVAP AAWDT AAWTL AAXUO AAYOK ABBTP ABDNZ ABDPE ABIME ABJNI ABLJU ABOCM ABPTD ABWST ACFRR ACGFO ACGFS ACGOD ACNCT ACPRK ACPVT ACUFI ACUTJ ADBBV ADGZP ADHUB ADMTO ADRTK ADUKH ADVEK ADVLN AEGXH AENEX AETBJ AFFDN AFFNX AFFZL AFJKZ AFOFC AFRAH AFXAL AGINJ AGKRT AGNAY AGQXC AGUTN AHMBA AI. AIAGR AITUG AJEEA AKRWK ALMA_UNASSIGNED_HOLDINGS AMRAJ ANFBD AQDSO AQKUS BAWUL BAYMD BKOMP BTRTY C1A CDBKE DAKXR DIK E3Z EBS EIHJH EJD ENERS EX3 F5P F9R FBQ FDB FECEO FLUFQ FOEOM FOTVD FQBLK FRP GAUVT GJXCC GX1 H13 HF~ HZ~ IH2 J5H KBUDW KOP KQ8 KSI KSN L7B LPU MBLQV MHKGH MV1 MVM N4W NEJ NHB NHCRO NOMLY NOYVH NVLIB O9- ODMLO OHT OK1 OVD P2P P6G PCD PQQKQ PRG Q2X R0Z RHI RNS ROL SJN TCN TEORI TMA TNT TR2 TWZ UBH UHB UKR VH1 W2D W8F WH7 WHG WOQ WOW X7M XOL XSW YBU YHG YOJ YQJ YR5 YRY YSK YV5 YYQ YZZ ZCA ZCG ZGI ZUP ZXP ~KM AALRI AAYWO AAYXX ACVFH ADCNI AEUPX AFPUW AGCQF AIGII AKBMS AKYEP APXCP CITATION NU- A8Z ABSAR BCRHZ CGR CUY CVF ECM EIF NPM RHF ROX SV3 VXZ Z5M 7QP 7T7 7TS 8FD C1K EFKBS FR3 K9. NAPCQ P64 7X8 7S9 L.6 |
ID | FETCH-LOGICAL-c489t-dbbc382001e117f62721464edac0e2e24f6827da2a91a1e6ced7d90499051903 |
ISSN | 0002-9165 1938-3207 |
IngestDate | Fri Jul 11 05:10:18 EDT 2025 Fri Jul 11 12:16:01 EDT 2025 Fri Jul 25 06:43:22 EDT 2025 Wed Feb 19 02:24:42 EST 2025 Tue Jul 01 04:03:02 EDT 2025 Thu Apr 24 23:02:59 EDT 2025 Thu Apr 03 09:43:40 EDT 2025 |
IsDoiOpenAccess | false |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 6 |
Language | English |
License | 2014 American Society for Nutrition. |
LinkModel | OpenURL |
MergedId | FETCHMERGED-LOGICAL-c489t-dbbc382001e117f62721464edac0e2e24f6827da2a91a1e6ced7d90499051903 |
Notes | http://dx.doi.org/10.3945/ajcn.113.078576 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
OpenAccessLink | https://academic.oup.com/ajcn/article-pdf/99/6/1369/23831709/1369.pdf |
PMID | 24760978 |
PQID | 1532259741 |
PQPubID | 41076 |
PageCount | 9 |
ParticipantIDs | proquest_miscellaneous_1678527793 proquest_miscellaneous_1659767604 proquest_journals_1532259741 pubmed_primary_24760978 crossref_citationtrail_10_3945_ajcn_113_078576 crossref_primary_10_3945_ajcn_113_078576 fao_agris_US201500151045 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2014-06-01 |
PublicationDateYYYYMMDD | 2014-06-01 |
PublicationDate_xml | – month: 06 year: 2014 text: 2014-06-01 day: 01 |
PublicationDecade | 2010 |
PublicationPlace | United States |
PublicationPlace_xml | – name: United States – name: Bethesda |
PublicationTitle | The American journal of clinical nutrition |
PublicationTitleAlternate | Am J Clin Nutr |
PublicationYear | 2014 |
Publisher | American Society for Clinical Nutrition American Society for Clinical Nutrition, Inc |
Publisher_xml | – name: American Society for Clinical Nutrition – name: American Society for Clinical Nutrition, Inc |
References | Cavalcanti (10.3945/ajcn.113.078576_bib21) 2005; 8 Schoeller (10.3945/ajcn.113.078576_bib23) 2005; 81 Larsen (10.3945/ajcn.113.078576_bib30) 2010; 363 Pan (10.3945/ajcn.113.078576_bib25) 2004; 23 Villareal (10.3945/ajcn.113.078576_bib10) 2004; 12 Baumgartner (10.3945/ajcn.113.078576_bib18) 1998; 147 Roubenoff (10.3945/ajcn.113.078576_bib2) 2000; 54 Visser (10.3945/ajcn.113.078576_bib12) 2013; 23 Kelly (10.3945/ajcn.113.078576_bib20) 2009; 4 Heber (10.3945/ajcn.113.078576_bib13) 1996; 64 Prado (10.3945/ajcn.113.078576_bib3) 2008; 9 Roubenoff (10.3945/ajcn.113.078576_bib14) 2004; 12 Bray (10.3945/ajcn.113.078576_bib4) 2004; 89 Hsu (10.3945/ajcn.113.078576_bib22) 2005; 13 10.3945/ajcn.113.078576_bib17 10.3945/ajcn.113.078576_bib16 Roubenoff (10.3945/ajcn.113.078576_bib7) 2000; 904 Baumgartner (10.3945/ajcn.113.078576_bib8) 2000; 904 Kewalramani (10.3945/ajcn.113.078576_bib27) 2010; 13 Siervo (10.3945/ajcn.113.078576_bib5) 2012; 6 Choi (10.3945/ajcn.113.078576_bib26) 2013; 20 Ellis (10.3945/ajcn.113.078576_bib31) 1990; 26–27 Baumgartner (10.3945/ajcn.113.078576_bib9) 2004; 12 Mott (10.3945/ajcn.113.078576_bib34) 1999; 69 Flegal (10.3945/ajcn.113.078576_bib15) 2009; 89 Santarpia (10.3945/ajcn.113.078576_bib29) 2013; 32 Janssen (10.3945/ajcn.113.078576_bib1) 2004; 52 Heymsfield (10.3945/ajcn.113.078576_bib19) 1990; 52 Roubenoff (10.3945/ajcn.113.078576_bib32) 2000; 55 Lee (10.3945/ajcn.113.078576_bib11) 2012; 64 Prado (10.3945/ajcn.113.078576_bib6) 2012; 31 Waters (10.3945/ajcn.113.078576_bib33) 2011; 27 10.3945/ajcn.113.078576_bib24 Kraegen (10.3945/ajcn.113.078576_bib28) 2008; 19 27037367 - Am J Clin Nutr. 2016 Apr;103(4):1190 |
References_xml | – volume: 54 start-page: S40 issue: suppl 3 year: 2000 ident: 10.3945/ajcn.113.078576_bib2 article-title: Sarcopenia and its implications for the elderly publication-title: Eur J Clin Nutr doi: 10.1038/sj.ejcn.1601024 – volume: 19 start-page: 235 year: 2008 ident: 10.3945/ajcn.113.078576_bib28 article-title: Free fatty acids and skeletal muscle insulin resistance publication-title: Curr Opin Lipidol doi: 10.1097/01.mol.0000319118.44995.9a – volume: 32 start-page: 157 year: 2013 ident: 10.3945/ajcn.113.078576_bib29 article-title: Body composition changes after weight-loss interventions for overweight and obesity publication-title: Clin Nutr doi: 10.1016/j.clnu.2012.08.016 – volume: 8 start-page: 293 year: 2005 ident: 10.3945/ajcn.113.078576_bib21 article-title: Reproducibility of DXA estimations of body fat in HIV lipodystrophy: implications for clinical research publication-title: J Clin Densitom doi: 10.1385/JCD:8:3:293 – volume: 147 start-page: 755 year: 1998 ident: 10.3945/ajcn.113.078576_bib18 article-title: Epidemiology of sarcopenia among the elderly in New Mexico publication-title: Am J Epidemiol doi: 10.1093/oxfordjournals.aje.a009520 – volume: 12 start-page: 913 year: 2004 ident: 10.3945/ajcn.113.078576_bib10 article-title: Physical frailty and body composition in obese elderly men and women publication-title: Obes Res doi: 10.1038/oby.2004.111 – volume: 69 start-page: 1007 year: 1999 ident: 10.3945/ajcn.113.078576_bib34 article-title: Relation between body fat and age in 4 ethnic groups publication-title: Am J Clin Nutr doi: 10.1093/ajcn/69.5.1007 – volume: 4 start-page: e7038 year: 2009 ident: 10.3945/ajcn.113.078576_bib20 article-title: Dual energy X-ray absorptiometry body composition reference values from NHANES publication-title: PLoS ONE doi: 10.1371/journal.pone.0007038 – volume: 52 start-page: 80 year: 2004 ident: 10.3945/ajcn.113.078576_bib1 article-title: The healthcare costs of sarcopenia in the United States publication-title: J Am Geriatr Soc doi: 10.1111/j.1532-5415.2004.52014.x – volume: 89 start-page: 2583 year: 2004 ident: 10.3945/ajcn.113.078576_bib4 article-title: Medical consequences of obesity publication-title: J Clin Endocrinol Metab doi: 10.1210/jc.2004-0535 – ident: 10.3945/ajcn.113.078576_bib17 – volume: 904 start-page: 437 year: 2000 ident: 10.3945/ajcn.113.078576_bib8 article-title: Body composition in healthy aging publication-title: Ann N Y Acad Sci doi: 10.1111/j.1749-6632.2000.tb06498.x – volume: 20 start-page: 85 year: 2013 ident: 10.3945/ajcn.113.078576_bib26 article-title: Characteristics of metabolically obese, normal-weight women differ by menopause status: the Fourth Korea National Health and Nutrition Examination Survey publication-title: Menopause doi: 10.1097/gme.0b013e31825d26b6 – volume: 363 start-page: 2102 year: 2010 ident: 10.3945/ajcn.113.078576_bib30 article-title: Diets with high or low protein content and glycemic index for weight-loss maintenance publication-title: N Engl J Med doi: 10.1056/NEJMoa1007137 – volume: 12 start-page: 1995 year: 2004 ident: 10.3945/ajcn.113.078576_bib9 article-title: Sarcopenic obesity predicts instrumental activities of daily living disability in the elderly publication-title: Obes Res doi: 10.1038/oby.2004.250 – volume: 52 start-page: 214 year: 1990 ident: 10.3945/ajcn.113.078576_bib19 article-title: Appendicular skeletal muscle mass: measurement by dual-photon absorptiometry publication-title: Am J Clin Nutr doi: 10.1093/ajcn/52.2.214 – volume: 13 start-page: 312 year: 2005 ident: 10.3945/ajcn.113.078576_bib22 article-title: Heritability of body composition measured by DXA in the Diabetes Heart Study publication-title: Obes Res doi: 10.1038/oby.2005.42 – ident: 10.3945/ajcn.113.078576_bib24 – volume: 27 start-page: 401 year: 2011 ident: 10.3945/ajcn.113.078576_bib33 article-title: Sarcopenia and obesity publication-title: Clin Geriatr Med doi: 10.1016/j.cger.2011.03.007 – volume: 23 start-page: 1749 year: 2004 ident: 10.3945/ajcn.113.078576_bib25 article-title: A comparison of goodness of fit tests for age-related reference ranges publication-title: Stat Med doi: 10.1002/sim.1692 – volume: 81 start-page: 1018 year: 2005 ident: 10.3945/ajcn.113.078576_bib23 article-title: QDR 4500A dual-energy X-ray absorptiometer underestimates fat mass in comparison with criterion methods in adults publication-title: Am J Clin Nutr doi: 10.1093/ajcn/81.5.1018 – volume: 64 start-page: 3947 year: 2012 ident: 10.3945/ajcn.113.078576_bib11 article-title: Sarcopenic obesity is more closely associated with knee osteoarthritis than is nonsarcopenic obesity: a cross-sectional study publication-title: Arthritis Rheum doi: 10.1002/art.37696 – volume: 13 start-page: 382 year: 2010 ident: 10.3945/ajcn.113.078576_bib27 article-title: Muscle insulin resistance: assault by lipids, cytokines and local macrophages publication-title: Curr Opin Clin Nutr Metab Care doi: 10.1097/MCO.0b013e32833aabd9 – volume: 904 start-page: 553 year: 2000 ident: 10.3945/ajcn.113.078576_bib7 article-title: Sarcopenic obesity: does muscle loss cause fat gain? Lessons from rheumatoid arthritis and osteoarthritis publication-title: Ann N Y Acad Sci doi: 10.1111/j.1749-6632.2000.tb06515.x – volume: 64 start-page: 472S issue: suppl year: 1996 ident: 10.3945/ajcn.113.078576_bib13 article-title: Clinical detection of sarcopenic obesity by bioelectrical impedance analysis publication-title: Am J Clin Nutr doi: 10.1093/ajcn/64.3.472S – volume: 23 start-page: 511 year: 2013 ident: 10.3945/ajcn.113.078576_bib12 article-title: Sarcopenic obesity is associated with adverse clinical outcome after cardiac surgery publication-title: Nutr Metab Cardiovasc Dis doi: 10.1016/j.numecd.2011.12.001 – volume: 89 start-page: 500 year: 2009 ident: 10.3945/ajcn.113.078576_bib15 article-title: Comparisons of percentage body fat, body mass index, waist circumference, and waist-stature ratio in adults publication-title: Am J Clin Nutr doi: 10.3945/ajcn.2008.26847 – volume: 6 start-page: e1 year: 2012 ident: 10.3945/ajcn.113.078576_bib5 article-title: Ageing, adiposity indexes and low muscle mass in a clinical sample of overweight and obese women publication-title: Obes Res Clin Pract doi: 10.1016/j.orcp.2011.05.001 – volume: 26–27 start-page: 385 year: 1990 ident: 10.3945/ajcn.113.078576_bib31 article-title: Reference man and woman more fully characterized: variations on the basis of body size, age, sex, and race publication-title: Biol Trace Elem Res doi: 10.1007/BF02992693 – ident: 10.3945/ajcn.113.078576_bib16 – volume: 31 start-page: 583 year: 2012 ident: 10.3945/ajcn.113.078576_bib6 article-title: Sarcopenic obesity: a critical appraisal of the current evidence publication-title: Clin Nutr doi: 10.1016/j.clnu.2012.06.010 – volume: 12 start-page: 887 year: 2004 ident: 10.3945/ajcn.113.078576_bib14 article-title: Sarcopenic obesity: the confluence of two epidemics publication-title: Obes Res doi: 10.1038/oby.2004.107 – volume: 55 start-page: M716 year: 2000 ident: 10.3945/ajcn.113.078576_bib32 article-title: Sarcopenia: current concepts publication-title: J Gerontol A Biol Sci Med Sci doi: 10.1093/gerona/55.12.M716 – volume: 9 start-page: 629 year: 2008 ident: 10.3945/ajcn.113.078576_bib3 article-title: Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study publication-title: Lancet Oncol doi: 10.1016/S1470-2045(08)70153-0 – reference: 27037367 - Am J Clin Nutr. 2016 Apr;103(4):1190 |
SSID | ssj0012486 |
Score | 2.48592 |
Snippet | Background: Abnormal body compositions such as high adiposity (HA), low muscle mass (LM), or a combination of the 2 [high adiposity with low muscle mass... Abnormal body compositions such as high adiposity (HA), low muscle mass (LM), or a combination of the 2 [high adiposity with low muscle mass (HA-LM)] are... |
SourceID | proquest pubmed crossref fao |
SourceType | Aggregation Database Index Database Enrichment Source Publisher |
StartPage | 1369 |
SubjectTerms | Absorptiometry, Photon adiposity Adolescent Adult adults Aged Aged, 80 and over Aging Body Composition Body Mass Index clinical nutrition Cross-Sectional Studies dual-energy X-ray absorptiometry fat mass index Female Genotype & phenotype Growth Charts Health risk assessment Humans Male men Middle Aged muscles Musculoskeletal system National Health and Nutrition Examination Survey Nutrition Surveys Obesity Obesity - complications Obesity - diagnostic imaging Obesity - epidemiology phenotype Prevalence risk Sarcopenia - complications Sarcopenia - diagnostic imaging Sarcopenia - epidemiology Sex Characteristics skeletal muscle United States - epidemiology Whole Body Imaging women Young Adult |
Title | population-based approach to define body-composition phenotypes |
URI | https://www.ncbi.nlm.nih.gov/pubmed/24760978 https://www.proquest.com/docview/1532259741 https://www.proquest.com/docview/1659767604 https://www.proquest.com/docview/1678527793 |
Volume | 99 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3db9MwELdYJyFeEIyPBQYyEkJIVUriOE78WEGnia1FglT0LXIcZwKVZFozpPHXc1e7aak6NHhoVLlOHfku9-W7-xHyOoqlDopK-lUSKJ-nofJVoZUvdGhSUcYmXh4XjCfiZMo_zuLZRsU1Vpe0xUD_2llX8j9UhTGgK1bJ_gNluz-FAfgO9IUrUBiut6LxsH_R4W_5qI_Krkc42pSlqdCGLJry2sfUcZef1ce0rgZjr4tN0zRb15jUmw0lutrJetW4vxOnl6psXNbIXPXHG9jEoGx_Nq4WyGZ62cJDG_EeYVBlHYW9_rHokLItyprDgnbRiJCvs6acAJUgQCNmkWwHZseYk7oWFslx16YIDSOL3bIt2yPJsQ2G-q5rBKIZgG0TJzu6aE8-5cfTs7M8G82yPbLPwH1gPbI_PP389bQ7X2J8iQHaPZlt-oRLvNta4A97Za9Szc2uyNIkyR6Q-86XoEPLGA_JHVMfEO_DN9PSN9Q1fJ3TyYpsB-Tu2GVSPCLDId3mHbriHdo21PIO3eYduuadxyQ7HmXvT3wHp-FrnsrWL4tCRynm0JkwTCrBEgR156ZUOjDMMF6JlCWlYkqGKjRCmzIpJbrEaOYH0RPSq5vaHBIqMB1VcmMKznhhZCG05DCkmA7iKtYeGaz2LNeu1TwinsxzcDlxk3PcZHA-o9xuskfedjdc2C4rN089BCLk6hx0YD79wjBiB58QXBOPHK0ok7vXZJGDRgeVBV5z6JFX3c8gQ_FgTNWmuYI5AiaIRAT8b3NgeWAmGXnkqaV696iMw70ySZ_dYoXn5N76vTkivfbyyrwAu7YtXjom_Q2kMqHc |
linkProvider | Library Specific Holdings |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+population-based+approach+to+define+body-composition+phenotypes&rft.jtitle=The+American+journal+of+clinical+nutrition&rft.au=Prado%2C+Carla+M+M&rft.au=Siervo%2C+Mario&rft.au=Mire%2C+Emily&rft.au=Heymsfield%2C+Steven+B&rft.date=2014-06-01&rft.issn=1938-3207&rft.eissn=1938-3207&rft.volume=99&rft.issue=6&rft.spage=1369&rft_id=info:doi/10.3945%2Fajcn.113.078576&rft.externalDBID=NO_FULL_TEXT |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0002-9165&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0002-9165&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0002-9165&client=summon |