The Lipid Accumulation Product and All‐cause Mortality in Patients at High Cardiovascular Risk: A PreCIS Database Study
The BMI is the most frequently used marker to evaluate obesity‐associated risks. An alternative continuous index of lipid over accumulation, the lipid accumulation product (LAP), has been proposed, which is computed from waist circumference (WC, cm) and fasting triglycerides (TGs) (mmol/l): (WC − 65...
Saved in:
| Published in | Obesity (Silver Spring, Md.) Vol. 18; no. 9; pp. 1836 - 1844 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Oxford, UK
Blackwell Publishing Ltd
01.09.2010
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 1930-7381 1930-739X 1930-739X |
| DOI | 10.1038/oby.2009.453 |
Cover
| Abstract | The BMI is the most frequently used marker to evaluate obesity‐associated risks. An alternative continuous index of lipid over accumulation, the lipid accumulation product (LAP), has been proposed, which is computed from waist circumference (WC, cm) and fasting triglycerides (TGs) (mmol/l): (WC − 65) × TG (men) and (WC − 58) × TG (women). We evaluated LAP and BMI as predictors of mortality in a high‐risk cohort. Study population included 5,924 new consecutive patients seen between 1995 and 2006 at a preventive cardiology clinic. Fifty‐eight percent of patients were discordant for their LAP and BMI quartiles. Patients whose LAP quartile was greater than BMI quartile had higher mortality compared with those with LAP quartile was lower than BMI quartile (8.2 vs. 5.4% at 6 years, P = 0.007). After adjustment for age, gender, smoking, diabetes mellitus, blood pressure, low‐density lipoprotein‐cholesterol (LDL‐C) and high‐density lipoprotein‐cholesterol (HDL‐C), (ln)LAP was independently associated with mortality (hazard ratio (HR) = 1.46, P < 0.001). BMI was not associated with increased mortality (HR = 1.06, P = 0.39). Adding LAP to a model including traditional risk factors for atherosclerosis increased its predictive value (C statistic 0.762 vs. 0.750, P = 0.048). Adding BMI to the same model did not change its predictive value (0.749 vs. 0.750, P = 0.29). Subgroup analyses showed that LAP predicted mortality in the nondiabetic patients (adjusted HR for (ln)LAP 1.64, P < 0.001), but did not reach significance in the diabetic patients (HR = 1.21, P = 0.11). In conclusion, LAP and not BMI predicted mortality in nondiabetic patients at high risk for cardiovascular diseases. LAP may become a useful tool in clinical practice to stratify the risk of unfavorable outcome associated with obesity. |
|---|---|
| AbstractList | The BMI is the most frequently used marker to evaluate obesity‐associated risks. An alternative continuous index of lipid over accumulation, the lipid accumulation product (LAP), has been proposed, which is computed from waist circumference (WC, cm) and fasting triglycerides (TGs) (mmol/l): (WC − 65) × TG (men) and (WC − 58) × TG (women). We evaluated LAP and BMI as predictors of mortality in a high‐risk cohort. Study population included 5,924 new consecutive patients seen between 1995 and 2006 at a preventive cardiology clinic. Fifty‐eight percent of patients were discordant for their LAP and BMI quartiles. Patients whose LAP quartile was greater than BMI quartile had higher mortality compared with those with LAP quartile was lower than BMI quartile (8.2 vs. 5.4% at 6 years, P = 0.007). After adjustment for age, gender, smoking, diabetes mellitus, blood pressure, low‐density lipoprotein‐cholesterol (LDL‐C) and high‐density lipoprotein‐cholesterol (HDL‐C), (ln)LAP was independently associated with mortality (hazard ratio (HR) = 1.46, P < 0.001). BMI was not associated with increased mortality (HR = 1.06, P = 0.39). Adding LAP to a model including traditional risk factors for atherosclerosis increased its predictive value (C statistic 0.762 vs. 0.750, P = 0.048). Adding BMI to the same model did not change its predictive value (0.749 vs. 0.750, P = 0.29). Subgroup analyses showed that LAP predicted mortality in the nondiabetic patients (adjusted HR for (ln)LAP 1.64, P < 0.001), but did not reach significance in the diabetic patients (HR = 1.21, P = 0.11). In conclusion, LAP and not BMI predicted mortality in nondiabetic patients at high risk for cardiovascular diseases. LAP may become a useful tool in clinical practice to stratify the risk of unfavorable outcome associated with obesity. The BMI is the most frequently used marker to evaluate obesity-associated risks. An alternative continuous index of lipid over accumulation, the lipid accumulation product (LAP), has been proposed, which is computed from waist circumference (WC, cm) and fasting triglycerides (TGs) (mmol/l): (WC - 65) x TG (men) and (WC - 58) x TG (women). We evaluated LAP and BMI as predictors of mortality in a high-risk cohort. Study population included 5,924 new consecutive patients seen between 1995 and 2006 at a preventive cardiology clinic. Fifty-eight percent of patients were discordant for their LAP and BMI quartiles. Patients whose LAP quartile was greater than BMI quartile had higher mortality compared with those with LAP quartile was lower than BMI quartile (8.2 vs. 5.4% at 6 years, P = 0.007). After adjustment for age, gender, smoking, diabetes mellitus, blood pressure, low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C), (ln)LAP was independently associated with mortality (hazard ratio (HR) = 1.46, P < 0.001). BMI was not associated with increased mortality (HR = 1.06, P = 0.39). Adding LAP to a model including traditional risk factors for atherosclerosis increased its predictive value (C statistic 0.762 vs. 0.750, P = 0.048). Adding BMI to the same model did not change its predictive value (0.749 vs. 0.750, P = 0.29). Subgroup analyses showed that LAP predicted mortality in the nondiabetic patients (adjusted HR for (ln)LAP 1.64, P < 0.001), but did not reach significance in the diabetic patients (HR = 1.21, P = 0.11). In conclusion, LAP and not BMI predicted mortality in nondiabetic patients at high risk for cardiovascular diseases. LAP may become a useful tool in clinical practice to stratify the risk of unfavorable outcome associated with obesity. The BMI is the most frequently used marker to evaluate obesity‐associated risks. An alternative continuous index of lipid over accumulation, the lipid accumulation product (LAP), has been proposed, which is computed from waist circumference (WC, cm) and fasting triglycerides (TGs) (mmol/l): (WC − 65) × TG (men) and (WC − 58) × TG (women). We evaluated LAP and BMI as predictors of mortality in a high‐risk cohort. Study population included 5,924 new consecutive patients seen between 1995 and 2006 at a preventive cardiology clinic. Fifty‐eight percent of patients were discordant for their LAP and BMI quartiles. Patients whose LAP quartile was greater than BMI quartile had higher mortality compared with those with LAP quartile was lower than BMI quartile (8.2 vs. 5.4% at 6 years, P = 0.007). After adjustment for age, gender, smoking, diabetes mellitus, blood pressure, low‐density lipoprotein‐cholesterol (LDL‐C) and high‐density lipoprotein‐cholesterol (HDL‐C), (ln)LAP was independently associated with mortality (hazard ratio (HR) = 1.46, P < 0.001). BMI was not associated with increased mortality (HR = 1.06, P = 0.39). Adding LAP to a model including traditional risk factors for atherosclerosis increased its predictive value (C statistic 0.762 vs. 0.750, P = 0.048). Adding BMI to the same model did not change its predictive value (0.749 vs. 0.750, P = 0.29). Subgroup analyses showed that LAP predicted mortality in the nondiabetic patients (adjusted HR for (ln)LAP 1.64, P < 0.001), but did not reach significance in the diabetic patients (HR = 1.21, P = 0.11). In conclusion, LAP and not BMI predicted mortality in nondiabetic patients at high risk for cardiovascular diseases. LAP may become a useful tool in clinical practice to stratify the risk of unfavorable outcome associated with obesity. The BMI is the most frequently used marker to evaluate obesity-associated risks. An alternative continuous index of lipid over accumulation, the lipid accumulation product (LAP), has been proposed, which is computed from waist circumference (WC, cm) and fasting triglycerides (TGs) (mmol/l): (WC - 65) × TG (men) and (WC - 58) × TG (women). We evaluated LAP and BMI as predictors of mortality in a high-risk cohort. Study population included 5,924 new consecutive patients seen between 1995 and 2006 at a preventive cardiology clinic. Fifty-eight percent of patients were discordant for their LAP and BMI quartiles. Patients whose LAP quartile was greater than BMI quartile had higher mortality compared with those with LAP quartile was lower than BMI quartile (8.2 vs. 5.4% at 6 years, P = 0.007). After adjustment for age, gender, smoking, diabetes mellitus, blood pressure, low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C), (ln)LAP was independently associated with mortality (hazard ratio (HR) = 1.46, P < 0.001). BMI was not associated with increased mortality (HR = 1.06, P = 0.39). Adding LAP to a model including traditional risk factors for atherosclerosis increased its predictive value (C statistic 0.762 vs. 0.750, P = 0.048). Adding BMI to the same model did not change its predictive value (0.749 vs. 0.750, P = 0.29). Subgroup analyses showed that LAP predicted mortality in the nondiabetic patients (adjusted HR for (ln)LAP 1.64, P < 0.001), but did not reach significance in the diabetic patients (HR = 1.21, P = 0.11). In conclusion, LAP and not BMI predicted mortality in nondiabetic patients at high risk for cardiovascular diseases. LAP may become a useful tool in clinical practice to stratify the risk of unfavorable outcome associated with obesity. The BMI is the most frequently used marker to evaluate obesity-associated risks. An alternative continuous index of lipid over accumulation, the lipid accumulation product (LAP), has been proposed, which is computed from waist circumference (WC, cm) and fasting triglycerides (TGs) (mmol/l): (WC - 65) x TG (men) and (WC - 58) x TG (women). We evaluated LAP and BMI as predictors of mortality in a high-risk cohort. Study population included 5,924 new consecutive patients seen between 1995 and 2006 at a preventive cardiology clinic. Fifty-eight percent of patients were discordant for their LAP and BMI quartiles. Patients whose LAP quartile was greater than BMI quartile had higher mortality compared with those with LAP quartile was lower than BMI quartile (8.2 vs. 5.4% at 6 years, P = 0.007). After adjustment for age, gender, smoking, diabetes mellitus, blood pressure, low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C), (ln)LAP was independently associated with mortality (hazard ratio (HR) = 1.46, P < 0.001). BMI was not associated with increased mortality (HR = 1.06, P = 0.39). Adding LAP to a model including traditional risk factors for atherosclerosis increased its predictive value (C statistic 0.762 vs. 0.750, P = 0.048). Adding BMI to the same model did not change its predictive value (0.749 vs. 0.750, P = 0.29). Subgroup analyses showed that LAP predicted mortality in the nondiabetic patients (adjusted HR for (ln)LAP 1.64, P < 0.001), but did not reach significance in the diabetic patients (HR = 1.21, P = 0.11). In conclusion, LAP and not BMI predicted mortality in nondiabetic patients at high risk for cardiovascular diseases. LAP may become a useful tool in clinical practice to stratify the risk of unfavorable outcome associated with obesity.The BMI is the most frequently used marker to evaluate obesity-associated risks. An alternative continuous index of lipid over accumulation, the lipid accumulation product (LAP), has been proposed, which is computed from waist circumference (WC, cm) and fasting triglycerides (TGs) (mmol/l): (WC - 65) x TG (men) and (WC - 58) x TG (women). We evaluated LAP and BMI as predictors of mortality in a high-risk cohort. Study population included 5,924 new consecutive patients seen between 1995 and 2006 at a preventive cardiology clinic. Fifty-eight percent of patients were discordant for their LAP and BMI quartiles. Patients whose LAP quartile was greater than BMI quartile had higher mortality compared with those with LAP quartile was lower than BMI quartile (8.2 vs. 5.4% at 6 years, P = 0.007). After adjustment for age, gender, smoking, diabetes mellitus, blood pressure, low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C), (ln)LAP was independently associated with mortality (hazard ratio (HR) = 1.46, P < 0.001). BMI was not associated with increased mortality (HR = 1.06, P = 0.39). Adding LAP to a model including traditional risk factors for atherosclerosis increased its predictive value (C statistic 0.762 vs. 0.750, P = 0.048). Adding BMI to the same model did not change its predictive value (0.749 vs. 0.750, P = 0.29). Subgroup analyses showed that LAP predicted mortality in the nondiabetic patients (adjusted HR for (ln)LAP 1.64, P < 0.001), but did not reach significance in the diabetic patients (HR = 1.21, P = 0.11). In conclusion, LAP and not BMI predicted mortality in nondiabetic patients at high risk for cardiovascular diseases. LAP may become a useful tool in clinical practice to stratify the risk of unfavorable outcome associated with obesity. |
| Author | Ioachimescu, Adriana G. Hoogwerf, Byron J. Hoar, Brian M. Brennan, Danielle M. |
| Author_xml | – sequence: 1 givenname: Adriana G. surname: Ioachimescu fullname: Ioachimescu, Adriana G. – sequence: 2 givenname: Danielle M. surname: Brennan fullname: Brennan, Danielle M. – sequence: 3 givenname: Brian M. surname: Hoar fullname: Hoar, Brian M. – sequence: 4 givenname: Byron J. surname: Hoogwerf fullname: Hoogwerf, Byron J. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/20035284$$D View this record in MEDLINE/PubMed |
| BookMark | eNp90cluFDEQBmALBZEFbpyRJQ5cmMFuL21zG4YlkQYFkSDBqVXjdhMHT3vwAuobj8Az8iQ4TMghEpxsyV_9LlUdor0xjBahh5TMKWHqWVhP84YQPeeC3UEHVDMya5n-uHdzV3QfHaZ0SQiXRNB7aL96JhrFD9B0fmHxym1djxfGlE3xkF0Y8bsY-mIyhrE-eP_rx08DJVn8NsQM3uUJu4qqtWNOGDI-dp8v8BJi78I3SKbmRPzepS_P8aKG2eXJGX4JGdZQQ85y6af76O4APtkH1-cR-vD61fnyeLY6fXOyXKxmhkvOZ1aa3igptW5ly4eGWDb0zaC40FwOjFDoQRLVEm0HKswgreVCNC2Tag0VsSP0ZJe7jeFrsSl3G5eM9R5GG0rqWq60Vi2nVT6-JS9DiWNtrquTJo0SSoqqHl2rst7YvttGt4E4dX9nWsHTHTAxpBTtcEMouQpSXV3ZFdddXVnlzS1uXP6zhBzB-X8V0V3Rd-ft9N8PutMXn6iSnP0GyrmokA |
| CitedBy_id | crossref_primary_10_1093_inthealth_ihu065 crossref_primary_10_3390_jcdd11100316 crossref_primary_10_1002_dmrr_2819 crossref_primary_10_1016_j_nutres_2012_06_019 crossref_primary_10_1093_humrep_dew076 crossref_primary_10_1007_s10157_019_01813_7 crossref_primary_10_1007_s10865_020_00161_2 crossref_primary_10_1371_journal_pone_0149731 crossref_primary_10_1038_s41598_017_07811_7 crossref_primary_10_3109_09513590_2014_937336 crossref_primary_10_1089_met_2018_0122 crossref_primary_10_5551_jat_20628 crossref_primary_10_1016_j_repc_2020_09_010 crossref_primary_10_1080_10641963_2021_2007943 crossref_primary_10_1186_s12944_015_0061_y crossref_primary_10_1016_j_dsx_2019_11_012 crossref_primary_10_1111_cen_12287 crossref_primary_10_1016_j_jad_2024_12_081 crossref_primary_10_1186_s12882_022_03026_9 crossref_primary_10_3390_ijerph13121231 crossref_primary_10_1371_journal_pone_0050428 crossref_primary_10_3390_nu15143168 crossref_primary_10_1016_j_atherosclerosis_2018_10_015 crossref_primary_10_1038_jhh_2014_97 crossref_primary_10_1177_00912174241265559 crossref_primary_10_1371_journal_pone_0198105 crossref_primary_10_1016_j_pcd_2020_12_001 crossref_primary_10_20945_2359_3997000000536 crossref_primary_10_1111_apt_12186 crossref_primary_10_2147_CIA_S330313 crossref_primary_10_1007_s00592_015_0715_2 crossref_primary_10_1139_apnm_2014_0487 crossref_primary_10_1177_2047487314558771 crossref_primary_10_1016_j_arteri_2023_04_002 crossref_primary_10_1080_00325481_2018_1444901 crossref_primary_10_15324_kjcls_2017_49_4_374 crossref_primary_10_1002_jcla_25095 crossref_primary_10_1016_j_jacc_2012_01_039 crossref_primary_10_1186_s12902_019_0348_5 crossref_primary_10_1186_s13098_015_0089_1 crossref_primary_10_3389_fendo_2023_1179990 crossref_primary_10_1186_s12902_020_00661_x crossref_primary_10_1371_journal_pone_0311312 crossref_primary_10_5812_ijem_109285 crossref_primary_10_1038_oby_2011_42 crossref_primary_10_5551_jat_33514 crossref_primary_10_1097_PSY_0000000000000879 crossref_primary_10_1186_s12872_018_0798_0 crossref_primary_10_1111_dme_12052 crossref_primary_10_1186_1471_2261_12_78 crossref_primary_10_1007_s11325_014_1053_2 crossref_primary_10_1080_01635581_2022_2093388 crossref_primary_10_1586_17474124_2015_1049155 crossref_primary_10_3389_fendo_2024_1302296 crossref_primary_10_1080_10920277_2016_1241183 crossref_primary_10_1080_2331205X_2019_1639880 crossref_primary_10_1080_13813455_2020_1861027 crossref_primary_10_1186_s12944_021_01569_8 crossref_primary_10_1186_s12944_023_01945_6 crossref_primary_10_1186_s12888_025_06631_8 crossref_primary_10_1016_j_ijcard_2011_08_049 crossref_primary_10_1007_s40200_022_01114_z crossref_primary_10_1186_s12882_018_0996_0 crossref_primary_10_1080_07435800_2022_2053540 crossref_primary_10_1590_1516_3180_2018_0293240119 crossref_primary_10_1016_j_artere_2023_09_005 crossref_primary_10_1016_j_numecd_2023_09_026 crossref_primary_10_1038_s41430_021_01045_7 crossref_primary_10_1016_j_gastrohep_2014_03_009 crossref_primary_10_1016_j_repce_2020_09_007 crossref_primary_10_3389_fcvm_2023_1249401 crossref_primary_10_1007_s10067_020_05218_w crossref_primary_10_1007_s10067_018_4143_x crossref_primary_10_3389_fmed_2022_831648 crossref_primary_10_1016_j_clnu_2024_02_006 crossref_primary_10_1136_bmjopen_2019_033991 crossref_primary_10_1089_met_2014_0093 crossref_primary_10_1186_s13098_018_0383_9 crossref_primary_10_1007_s40618_020_01349_8 crossref_primary_10_1007_s11255_020_02735_0 crossref_primary_10_3389_fnut_2024_1466288 crossref_primary_10_1016_j_cca_2015_04_020 crossref_primary_10_1080_00325481_2017_1375714 crossref_primary_10_1186_1476_511X_9_100 crossref_primary_10_3389_fendo_2022_825528 crossref_primary_10_3390_toxics13010046 crossref_primary_10_1590_S0004_27302010000700007 crossref_primary_10_1016_j_jesf_2022_09_001 crossref_primary_10_3803_EnM_2014_29_4_443 crossref_primary_10_1186_s12967_019_2074_1 crossref_primary_10_3389_fpubh_2022_955615 crossref_primary_10_1016_j_arteri_2024_04_002 crossref_primary_10_1016_j_clim_2020_108637 crossref_primary_10_1016_j_maturitas_2011_09_012 crossref_primary_10_1186_s12944_023_01981_2 crossref_primary_10_1530_EJE_16_0775 crossref_primary_10_1159_000516522 crossref_primary_10_2147_NSS_S361318 crossref_primary_10_26693_jmbs05_01_125 crossref_primary_10_3889_oamjms_2021_7027 crossref_primary_10_1002_osp4_713 crossref_primary_10_1155_2019_9014698 crossref_primary_10_1093_ckj_sfae362 |
| Cites_doi | 10.1038/sj.ijo.0803697 10.2337/diacare.23.4.465 10.1007/s11695-007-9168-1 10.1038/sj.ijo.0800813 10.1038/ijo.2008.11 10.1093/aje/kwh281 10.1001/jama.279.24.1955 10.1161/01.CIR.102.2.179 10.1097/00043798-199604000-00014 10.1111/j.1464-5491.2007.02302.x 10.1161/01.ATV.10.4.497 10.1016/S0140-6736(05)67663-5 10.2337/diacare.29.01.06.dc05-1805 10.2337/diab.41.7.826 10.1093/ajcn/79.3.379 10.1016/S0140-6736(06)69251-9 10.1136/bmj.311.7017.1401 10.2337/dc06-0441 10.7326/0003-4819-143-7-200510040-00005 10.1186/1471-2261-5-26 10.2337/diacare.19.6.629 10.1210/jc.2002-020570 10.1093/ajcn/34.8.1617 10.2337/diacare.22.9.1471 10.1001/jama.299.10.1185 10.1001/jama.1982.03320430047030 10.1001/jama.280.21.1843 10.1093/eurheartj/ehm026 10.1001/jama.295.13.1549 10.1161/01.CIR.0000161801.65408.8D |
| ContentType | Journal Article |
| Copyright | 2010 North American Association for the Study of Obesity (NAASO) Copyright Nature Publishing Group Sep 2010 |
| Copyright_xml | – notice: 2010 North American Association for the Study of Obesity (NAASO) – notice: Copyright Nature Publishing Group Sep 2010 |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM K9. 7X8 |
| DOI | 10.1038/oby.2009.453 |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Health & Medical Complete (Alumni) MEDLINE - Academic |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) ProQuest Health & Medical Complete (Alumni) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE CrossRef ProQuest Health & Medical Complete (Alumni) MEDLINE - Academic |
| 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 |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 1930-739X |
| EndPage | 1844 |
| ExternalDocumentID | 2724993921 20035284 10_1038_oby_2009_453 OBY1864 |
| Genre | article Validation Studies Journal Article |
| GroupedDBID | --- 05W 0R~ 123 1OC 29N 2FS 2WC 31~ 33P 39C 3SF 4.4 50Y 52U 52V 53G 70F 8-1 AAESR AAEVG AAFWJ AAHBH AAHQN AAIPD AAMMB AAMNL AANLZ AAONW AASGY AAWTL AAXRX AAYCA AAZKR ABCUV ABIVO ABJNI ABLJU ABQWH ABXGK ACAHQ ACCZN ACGFS ACGOF ACMXC ACPOU ACXBN ACXQS ADBBV ADBTR ADEOM ADIZJ ADKYN ADMGS ADOZA ADXAS ADZMN AEFGJ AEIGN AEIMD AENEX AEUYR AEYWJ AFBPY AFFPM AFGKR AFWVQ AFZJQ AGHNM AGXDD AGYGG AHBTC AHMBA AIACR AIDQK AIDYY AITYG AIURR ALMA_UNASSIGNED_HOLDINGS ALUQN ALVPJ AMBMR AMYDB ATUGU AZVAB BAWUL BFHJK BHBCM BKNYI BMXJE BOGZA BPHCQ BRXPI BVXVI CS3 DCZOG DIK DPXWK DRFUL DRMAN DRSTM DU5 E3Z EBS EJD EMOBN F5P FUBAC G-S GODZA HGLYW HZ~ KBYEO LATKE LEEKS LH4 LITHE LOXES LUTES LW6 LYRES MEWTI MRFUL MRMAN MRSTM MSFUL MSMAN MSSTM MXFUL MXMAN MXSTM MY~ O66 O9- OK1 P2W PQQKQ PROAC R.K ROL SUPJJ WBKPD WHG WHWMO WIH WIJ WIK WIN WOHZO WOQ WQJ WVDHM WXSBR YHZ AAHHS AAYXX ACCFJ AEEZP AEQDE AIWBW AJBDE ALIPV CITATION CGR CUY CVF ECM EIF NPM K9. 7X8 |
| ID | FETCH-LOGICAL-c4644-e6cdc866997674f20e3fd2f845946f301ada608709ef15cf6ee45527368ba4593 |
| ISSN | 1930-7381 1930-739X |
| IngestDate | Thu Sep 04 22:20:36 EDT 2025 Fri Jul 25 23:51:54 EDT 2025 Thu Apr 03 06:55:35 EDT 2025 Tue Jul 01 01:16:03 EDT 2025 Thu Apr 24 23:04:13 EDT 2025 Sun Sep 21 06:24:21 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 9 |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c4644-e6cdc866997674f20e3fd2f845946f301ada608709ef15cf6ee45527368ba4593 |
| Notes | Lilly USA, Endocrinology‐Diabetes, Indianapolis, Indiana, USA ObjectType-Article-1 SourceType-Scholarly Journals-1 content type line 14 ObjectType-Feature-2 content type line 23 ObjectType-Undefined-3 |
| OpenAccessLink | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1038/oby.2009.453 |
| PMID | 20035284 |
| PQID | 1030285865 |
| PQPubID | 105348 |
| PageCount | 9 |
| ParticipantIDs | proquest_miscellaneous_748998741 proquest_journals_1030285865 pubmed_primary_20035284 crossref_primary_10_1038_oby_2009_453 crossref_citationtrail_10_1038_oby_2009_453 wiley_primary_10_1038_oby_2009_453_OBY1864 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | September 2010 |
| PublicationDateYYYYMMDD | 2010-09-01 |
| PublicationDate_xml | – month: 09 year: 2010 text: September 2010 |
| PublicationDecade | 2010 |
| PublicationPlace | Oxford, UK |
| PublicationPlace_xml | – name: Oxford, UK – name: United States – name: Silver Spring |
| PublicationTitle | Obesity (Silver Spring, Md.) |
| PublicationTitleAlternate | Obesity (Silver Spring) |
| PublicationYear | 2010 |
| Publisher | Blackwell Publishing Ltd |
| Publisher_xml | – name: Blackwell Publishing Ltd |
| References | 2007; 17 1990; 10 1998; 280 1996; 19 2005; 111 2000; 23 2004; 160 2006; 295 1999; 23 1999; 22 2008; 32 1982; 247 1998; 279 1995; 311 2007; 28 2005; 143 2000; 102 2005; 366 2002; 87 2004; 79 2005; 5 2006; 29 2008; 299 2005; 15 2006; 368 1996; 3 2007; 24 1981; 34 1992; 41 e_1_2_7_5_2 e_1_2_7_4_2 e_1_2_7_3_2 e_1_2_7_2_2 e_1_2_7_9_2 e_1_2_7_8_2 e_1_2_7_7_2 e_1_2_7_6_2 e_1_2_7_19_2 McGee DL (e_1_2_7_32_2) 2005; 15 e_1_2_7_18_2 e_1_2_7_17_2 e_1_2_7_16_2 e_1_2_7_15_2 e_1_2_7_14_2 e_1_2_7_13_2 e_1_2_7_12_2 e_1_2_7_11_2 e_1_2_7_10_2 e_1_2_7_26_2 e_1_2_7_27_2 e_1_2_7_28_2 e_1_2_7_29_2 e_1_2_7_25_2 e_1_2_7_24_2 e_1_2_7_30_2 e_1_2_7_23_2 e_1_2_7_31_2 e_1_2_7_22_2 e_1_2_7_21_2 e_1_2_7_20_2 |
| References_xml | – volume: 279 start-page: 1955 year: 1998 end-page: 1961 article-title: Fasting insulin and apolipoprotein B levels and low‐density lipoprotein particle size as risk factors for ischemic heart disease publication-title: JAMA – volume: 32 start-page: 959 year: 2008 end-page: 966 article-title: Accuracy of body mass index in diagnosing obesity in the adult general population publication-title: Int J Obes (Lond) – volume: 111 start-page: 1883 year: 2005 end-page: 1890 article-title: Enlarged waist combined with elevated triglycerides is a strong predictor of accelerated atherogenesis and related cardiovascular mortality in postmenopausal women publication-title: Circulation – volume: 311 start-page: 1401 year: 1995 end-page: 1405 article-title: Waist circumference action levels in the identification of cardiovascular risk factors: prevalence study in a random sample publication-title: BMJ – volume: 10 start-page: 497 year: 1990 end-page: 511 article-title: Regional distribution of body fat, plasma lipoproteins, and cardiovascular disease publication-title: Arteriosclerosis – volume: 24 start-page: 1369 year: 2007 end-page: 1374 article-title: Serum uric acid, mortality and glucose control in patients with type 2 diabetes mellitus: a PreCIS database study publication-title: Diabet Med – volume: 247 start-page: 2543 year: 1982 end-page: 2546 article-title: Evaluating the yield of medical tests publication-title: JAMA – volume: 23 start-page: 465 year: 2000 end-page: 471 article-title: Visceral adiposity and risk of type 2 diabetes: a prospective study among Japanese Americans publication-title: Diabetes Care – volume: 366 start-page: 1640 year: 2005 end-page: 1649 article-title: Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case‐control study publication-title: Lancet – volume: 19 start-page: 629 year: 1996 end-page: 637 article-title: The dense LDL phenotype. Association with plasma lipoprotein levels, visceral obesity, and hyperinsulinemia in men publication-title: Diabetes Care – volume: 368 start-page: 666 year: 2006 end-page: 678 article-title: Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: a systematic review of cohort studies publication-title: Lancet – volume: 87 start-page: 5044 year: 2002 end-page: 5051 article-title: Abdominal obesity, muscle composition, and insulin resistance in premenopausal women publication-title: J Clin Endocrinol Metab – volume: 23 start-page: 180 year: 1999 end-page: 189 article-title: Relationship of low‐density lipoprotein particle size and measures of adiposity publication-title: Int J Obes Relat Metab Disord – volume: 5 start-page: 26 year: 2005 article-title: The “lipid accumulation product” performs better than the body mass index for recognizing cardiovascular risk: a population‐based comparison publication-title: BMC Cardiovasc Disord – volume: 28 start-page: 850 year: 2007 end-page: 856 article-title: Waist circumference and waist‐to‐hip ratio as predictors of cardiovascular events: meta‐regression analysis of prospective studies publication-title: Eur Heart J – volume: 15 start-page: 87 year: 2005 end-page: 97 publication-title: Diverse Populations Collaboration. Body mass index and mortality: a meta-analysis based on person-level data from twenty-six observational studies – volume: 32 start-page: 136 year: 2008 end-page: 143 article-title: Longitudinal changes in BMI and in an index estimating excess lipids among white and black adults in the United States publication-title: Int J Obes (Lond) – volume: 143 start-page: 473 year: 2005 end-page: 480 article-title: Estimated risks for developing obesity in the Framingham Heart Study publication-title: Ann Intern Med – volume: 79 start-page: 379 year: 2004 end-page: 384 article-title: Waist circumference and not body mass index explains obesity‐related health risk publication-title: Am J Clin Nutr – volume: 17 start-page: 905 year: 2007 end-page: 909 article-title: Waist circumference is useless to assess the prevalence of metabolic abnormalities in severely obese women publication-title: Obes Surg – volume: 41 start-page: 826 year: 1992 end-page: 834 article-title: Visceral obesity in men. Associations with glucose tolerance, plasma insulin, and lipoprotein levels publication-title: Diabetes – volume: 22 start-page: 1471 year: 1999 end-page: 1478 article-title: Age‐related increase in visceral adipose tissue and body fat and the metabolic risk profile of premenopausal women publication-title: Diabetes Care – volume: 29 start-page: 1417 year: 2006 end-page: 1419 article-title: Waist girth does not predict metabolic complications in severely obese men publication-title: Diabetes Care – volume: 295 start-page: 1549 year: 2006 end-page: 1555 article-title: Prevalence of overweight and obesity in the United States, 1999–2004 publication-title: JAMA – volume: 29 start-page: 151 year: 2006 end-page: 153 article-title: The lipid accumulation product is better than BMI for identifying diabetes: a population‐based comparison publication-title: Diabetes Care – volume: 3 start-page: 213 year: 1996 end-page: 219 article-title: Plasma triglyceride level is a risk factor for cardiovascular disease independent of high‐density lipoprotein cholesterol level: a meta‐analysis of population‐based prospective studies publication-title: J Cardiovasc Risk – volume: 299 start-page: 1185 year: 2008 end-page: 1187 article-title: Reinventing type 2 diabetes: pathogenesis, treatment, and prevention publication-title: JAMA – volume: 160 start-page: 741 year: 2004 end-page: 749 article-title: Association of visceral adipose tissue with incident myocardial infarction in older men and women: the Health, Aging and Body Composition Study publication-title: Am J Epidemiol – volume: 102 start-page: 179 year: 2000 end-page: 184 article-title: Hypertriglyceridemic waist: a marker of the atherogenic metabolic triad (hyperinsulinemia; hyperapolipoprotein B; small, dense LDL) in men? publication-title: Circulation – volume: 280 start-page: 1843 year: 1998 end-page: 1848 article-title: Abdominal adiposity and coronary heart disease in women publication-title: JAMA – volume: 34 start-page: 1617 year: 1981 end-page: 1621 article-title: The “metabolically‐obese,” normal‐weight individual publication-title: Am J Clin Nutr – ident: e_1_2_7_27_2 doi: 10.1038/sj.ijo.0803697 – ident: e_1_2_7_15_2 doi: 10.2337/diacare.23.4.465 – ident: e_1_2_7_22_2 doi: 10.1007/s11695-007-9168-1 – ident: e_1_2_7_18_2 doi: 10.1038/sj.ijo.0800813 – ident: e_1_2_7_6_2 doi: 10.1038/ijo.2008.11 – volume: 15 start-page: 87 year: 2005 ident: e_1_2_7_32_2 publication-title: Diverse Populations Collaboration. Body mass index and mortality: a meta-analysis based on person-level data from twenty-six observational studies – ident: e_1_2_7_16_2 doi: 10.1093/aje/kwh281 – ident: e_1_2_7_25_2 doi: 10.1001/jama.279.24.1955 – ident: e_1_2_7_11_2 doi: 10.1161/01.CIR.102.2.179 – ident: e_1_2_7_29_2 doi: 10.1097/00043798-199604000-00014 – ident: e_1_2_7_30_2 doi: 10.1111/j.1464-5491.2007.02302.x – ident: e_1_2_7_8_2 doi: 10.1161/01.ATV.10.4.497 – ident: e_1_2_7_4_2 doi: 10.1016/S0140-6736(05)67663-5 – ident: e_1_2_7_13_2 doi: 10.2337/diacare.29.01.06.dc05-1805 – ident: e_1_2_7_9_2 doi: 10.2337/diab.41.7.826 – ident: e_1_2_7_20_2 doi: 10.1093/ajcn/79.3.379 – ident: e_1_2_7_5_2 doi: 10.1016/S0140-6736(06)69251-9 – ident: e_1_2_7_28_2 doi: 10.1136/bmj.311.7017.1401 – ident: e_1_2_7_23_2 doi: 10.2337/dc06-0441 – ident: e_1_2_7_2_2 doi: 10.7326/0003-4819-143-7-200510040-00005 – ident: e_1_2_7_12_2 doi: 10.1186/1471-2261-5-26 – ident: e_1_2_7_24_2 doi: 10.2337/diacare.19.6.629 – ident: e_1_2_7_10_2 doi: 10.1210/jc.2002-020570 – ident: e_1_2_7_7_2 doi: 10.1093/ajcn/34.8.1617 – ident: e_1_2_7_17_2 doi: 10.2337/diacare.22.9.1471 – ident: e_1_2_7_31_2 doi: 10.1001/jama.299.10.1185 – ident: e_1_2_7_14_2 doi: 10.1001/jama.1982.03320430047030 – ident: e_1_2_7_19_2 doi: 10.1001/jama.280.21.1843 – ident: e_1_2_7_21_2 doi: 10.1093/eurheartj/ehm026 – ident: e_1_2_7_3_2 doi: 10.1001/jama.295.13.1549 – ident: e_1_2_7_26_2 doi: 10.1161/01.CIR.0000161801.65408.8D |
| SSID | ssj0046051 |
| Score | 2.3665276 |
| Snippet | The BMI is the most frequently used marker to evaluate obesity‐associated risks. An alternative continuous index of lipid over accumulation, the lipid... The BMI is the most frequently used marker to evaluate obesity-associated risks. An alternative continuous index of lipid over accumulation, the lipid... |
| SourceID | proquest pubmed crossref wiley |
| SourceType | Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 1836 |
| SubjectTerms | Adult Aged Atherosclerosis - blood Atherosclerosis - mortality Body Mass Index Cardiovascular Diseases - blood Cardiovascular Diseases - mortality Cause of Death Databases, Factual Diabetes Mellitus - blood Diabetes Mellitus - mortality Female Humans Lipid Metabolism Male Middle Aged Models, Biological Obesity - blood Obesity - mortality Retrospective Studies Risk Factors Triglycerides - blood Waist Circumference |
| Title | The Lipid Accumulation Product and All‐cause Mortality in Patients at High Cardiovascular Risk: A PreCIS Database Study |
| URI | https://onlinelibrary.wiley.com/doi/abs/10.1038%2Foby.2009.453 https://www.ncbi.nlm.nih.gov/pubmed/20035284 https://www.proquest.com/docview/1030285865 https://www.proquest.com/docview/748998741 |
| Volume | 18 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3db9MwELfKkBAvaHyuMJAf4IUqo2lcN-aN8qFtaIDEJo2nyHFsVKlNqrbRtP0h_L3c2U7qQoeAlyhKnLjN_XJ3vtz9jpDnRuQsT2IOEojziJmER7nSKpIpA_uswSDbbPeTT_zwjB2fD887nR9B1lK9yg_U1da6kv-RKhwDuWKV7D9Itr0pHIB9kC9sQcKw_WsZTyfzSdGTStUz34kLc66QxdXxsE6nkZL1Uvdm1tFGp3tNp7rEWkZkLEaG6jAvFTPOXR30l4XGTD7MJEWLF_DRepfWtxZAV_XrBPOsey5YaEOtxUEQajjC4i0sOVG1VUkFPKJSrrt7jReg9V1A1lW-T3UQrK1cKvgYLwoPV98v9MJSS44vF_Dvj8NABn6DF00gQzvlK5J-NEpsa90t2rlu8s-dqgVdxLfaAMf4XuWXjo2UOTLiAA7zmcWD44J1Dep-4dxuTt0gNwcjzrEzxrujj42Fx0_JsS-igMlehVMhubS_eNPT-W35srkasu7M6S6549ch9I0D1V3S0eU9cuvEZ1rcJxeALWqxRUNsUY8tCtiiLbZoiy06gSEeW1SuKGKLbmKLIrZeU0kdsmiDLGqR9YCcfXh_-vYw8k06IsXAl440V4VKORcCaaHMoK8TUwwMvOqCcQPmQxaS98EqCG3ioTJca2ZZ_3iaSxiUPCQ7ZVXqPUJHnOVMFiI3Apb5sMMMzGHAgxwMCsZll_SaB5opz2CPjVSmmc2kSNIMJIF9VUUGkuiSF-3ouWNuuWbcfiObzL_bSxwFjvcw5cMuoe1p0Lz4OU2WuqqXGfI2iRQ88i555ETaztNAoEteWhn_8Qdkn8ff4pSzx9fe5gm5vX5h9snOalHrp-ALr_JnFpg_AQo4sv4 |
| linkProvider | Flying Publisher |
| 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=The+lipid+accumulation+product+and+all-cause+mortality+in+patients+at+high+cardiovascular+risk%3A+a+PreCIS+database+study&rft.jtitle=Obesity+%28Silver+Spring%2C+Md.%29&rft.au=Ioachimescu%2C+Adriana+G&rft.au=Brennan%2C+Danielle+M&rft.au=Hoar%2C+Brian+M&rft.au=Hoogwerf%2C+Byron+J&rft.date=2010-09-01&rft.eissn=1930-739X&rft.volume=18&rft.issue=9&rft.spage=1836&rft_id=info:doi/10.1038%2Foby.2009.453&rft_id=info%3Apmid%2F20035284&rft.externalDocID=20035284 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1930-7381&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1930-7381&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1930-7381&client=summon |