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A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC)
Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular dis...
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Published in: | PLoS medicine 2016-04, Vol.13 (4), p.e1001988-e1001988 |
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creator | Murphy, Neil Cross, Amanda J Abubakar, Mustapha Jenab, Mazda Aleksandrova, Krasimira Boutron-Ruault, Marie-Christine Dossus, Laure Racine, Antoine Kühn, Tilman Katzke, Verena A Tjønneland, Anne Petersen, Kristina E N Overvad, Kim Quirós, J Ramón Jakszyn, Paula Molina-Montes, Esther Dorronsoro, Miren Huerta, José-María Barricarte, Aurelio Khaw, Kay-Tee Wareham, Nick Travis, Ruth C Trichopoulou, Antonia Lagiou, Pagona Trichopoulos, Dimitrios Masala, Giovanna Krogh, Vittorio Tumino, Rosario Vineis, Paolo Panico, Salvatore Bueno-de-Mesquita, H Bas Siersema, Peter D Peeters, Petra H Ohlsson, Bodil Ericson, Ulrika Palmqvist, Richard Nyström, Hanna Weiderpass, Elisabete Skeie, Guri Freisling, Heinz Kong, So Yeon Tsilidis, Kostas Muller, David C Riboli, Elio Gunter, Marc J |
description | Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown.
The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of |
doi_str_mv | 10.1371/journal.pmed.1001988 |
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The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed.
These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.</description><identifier>ISSN: 1549-1676</identifier><identifier>ISSN: 1549-1277</identifier><identifier>EISSN: 1549-1676</identifier><identifier>DOI: 10.1371/journal.pmed.1001988</identifier><identifier>PMID: 27046222</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adiposity ; Biology and Life Sciences ; Biomarkers - blood ; Body fat ; Body Mass Index ; Body Size ; C-Peptide - blood ; Cancer and Oncology ; Cancer och onkologi ; Cancer therapies ; Cardiovascular disease ; Case-Control Studies ; Chi-Square Distribution ; Clinical Medicine ; Colorectal cancer ; Colorectal Neoplasms - diagnosis ; Colorectal Neoplasms - epidemiology ; Community medicine, Social medicine: 801 ; Complications and side effects ; Diabetes ; Europe - epidemiology ; Female ; Genetic aspects ; Genotype & phenotype ; Health sciences: 800 ; Health Status ; Helsefag: 800 ; Humans ; Hyperinsulinism - blood ; Hyperinsulinism - diagnosis ; Hyperinsulinism - epidemiology ; Incidence ; Insulin ; Investigations ; Klinisk medicin ; Logistic Models ; Male ; Medical and Health Sciences ; Medical disciplines: 700 ; Medicin och hälsovetenskap ; Medicine and Health Sciences ; Medisinske Fag: 700 ; Metabolism ; Middle Aged ; Multivariate Analysis ; Nutrition research ; Obesity ; Obesity - blood ; Obesity - diagnosis ; Obesity - epidemiology ; Obesity, Metabolically Benign - blood ; Obesity, Metabolically Benign - diagnosis ; Obesity, Metabolically Benign - epidemiology ; Odds Ratio ; Peptides ; Phenotype ; Phenotypes ; Prospective Studies ; Protective Factors ; Researchers ; Risk Assessment ; Risk Factors ; Samfunnsmedisin, sosialmedisin: 801 ; Studies ; VDP ; Waist Circumference ; Weight control</subject><ispartof>PLoS medicine, 2016-04, Vol.13 (4), p.e1001988-e1001988</ispartof><rights>COPYRIGHT 2016 Public Library of Science</rights><rights>2016 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Murphy N, Cross AJ, Abubakar M, Jenab M, Aleksandrova K, Boutron-Ruault M-C, et al. (2016) A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC). PLoS Med 13(4): e1001988. doi:10.1371/journal.pmed.1001988</rights><rights>info:eu-repo/semantics/openAccess</rights><rights>2016 Murphy et al 2016 Murphy et al</rights><rights>2016 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Murphy N, Cross AJ, Abubakar M, Jenab M, Aleksandrova K, Boutron-Ruault M-C, et al. (2016) A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC). 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Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown.
The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed.
These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.</description><subject>Adiposity</subject><subject>Biology and Life Sciences</subject><subject>Biomarkers - blood</subject><subject>Body fat</subject><subject>Body Mass Index</subject><subject>Body Size</subject><subject>C-Peptide - blood</subject><subject>Cancer and Oncology</subject><subject>Cancer och onkologi</subject><subject>Cancer therapies</subject><subject>Cardiovascular disease</subject><subject>Case-Control Studies</subject><subject>Chi-Square Distribution</subject><subject>Clinical Medicine</subject><subject>Colorectal cancer</subject><subject>Colorectal Neoplasms - diagnosis</subject><subject>Colorectal Neoplasms - epidemiology</subject><subject>Community medicine, Social medicine: 801</subject><subject>Complications and side effects</subject><subject>Diabetes</subject><subject>Europe - epidemiology</subject><subject>Female</subject><subject>Genetic aspects</subject><subject>Genotype & phenotype</subject><subject>Health sciences: 800</subject><subject>Health Status</subject><subject>Helsefag: 800</subject><subject>Humans</subject><subject>Hyperinsulinism - blood</subject><subject>Hyperinsulinism - diagnosis</subject><subject>Hyperinsulinism - epidemiology</subject><subject>Incidence</subject><subject>Insulin</subject><subject>Investigations</subject><subject>Klinisk medicin</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Medical and Health Sciences</subject><subject>Medical disciplines: 700</subject><subject>Medicin och hälsovetenskap</subject><subject>Medicine and Health Sciences</subject><subject>Medisinske Fag: 700</subject><subject>Metabolism</subject><subject>Middle Aged</subject><subject>Multivariate Analysis</subject><subject>Nutrition research</subject><subject>Obesity</subject><subject>Obesity - blood</subject><subject>Obesity - diagnosis</subject><subject>Obesity - epidemiology</subject><subject>Obesity, Metabolically Benign - blood</subject><subject>Obesity, Metabolically Benign - diagnosis</subject><subject>Obesity, Metabolically Benign - epidemiology</subject><subject>Odds Ratio</subject><subject>Peptides</subject><subject>Phenotype</subject><subject>Phenotypes</subject><subject>Prospective Studies</subject><subject>Protective Factors</subject><subject>Researchers</subject><subject>Risk Assessment</subject><subject>Risk Factors</subject><subject>Samfunnsmedisin, sosialmedisin: 801</subject><subject>Studies</subject><subject>VDP</subject><subject>Waist Circumference</subject><subject>Weight control</subject><issn>1549-1676</issn><issn>1549-1277</issn><issn>1549-1676</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>3HK</sourceid><sourceid>DOA</sourceid><recordid>eNqVlN1u0zAUxyMEYjB4AwSRkNB20RHHjj9ukEo3oNLYpg12azmx03pz7WAng_JYPCHO1m4L2hAocmLZv__J8TnHJ0legGwHQALenrnOW2F2moWSOyDLAKP0QfIEFIiNACb44a35RvI0hLMsy1nGssfJRk4yhPM8f5L8GqcHKrRKphMR1GjibOudSU_aTi5TV6efVStKZ3QljFmmu6rWNrLvXdw90T9VejRX1rXLRoVUWJke63DeyybOOK-qVpho11bKp9qm7Vyle513jRI2PfIuNJHQFyqd2ovog56JVjsbydatVb3Ng671-nJna-9oOtl-ljyqhQnq-eq7mXz9sPdl8mm0f_hxOhnvjypGYTsSArIM4lzSrM5rjGtJEZW0xiWtQV6WJAcVJlTRkgklIJWClUVRFwIKKjNYws3k1ZXdxrjAV-EOHBDKCpQzjCIxvSKkE2e88Xoh_JI7ofnlgvMzLnyrK6N4BQlFhYzeCIoIgIwKgrAkQDIIICqirdGVrfBdNV05sLZaOo8zxYsMZxRGnt3LN97JG9FaCCBEJKeURO3-vVrTNXGUcfSanMoSUKQ4qrOSx5qBXDDCOMF1TVFVVwWGf3V9V5-OLwPRLToOclCwnn-3CmxXxuKtVKw5YYYnGOxYPeczd8ERzQEGxU1mKq9j3VhunRc83gFI4huiPBJbq194962LxcUXOlTKGGGV6_okEoYAZaBP4us_0LtTvaJmImZT29pFz6reKB8jginDtCA3kRhQM2VVPIaz8fbE5QG_cwcfH6kWurpTsD0QRKZVP9qZ6ELg05Pj_2AP_p09PB2yb26xcyVMOw_OdP0VDUMQrdPkQvCqvk4xyHjfw9aR5n0P46seFmUvb5fHtWjdtOBvXVuWXA</recordid><startdate>20160405</startdate><enddate>20160405</enddate><creator>Murphy, 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Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC)</title><author>Murphy, Neil ; Cross, Amanda J ; Abubakar, Mustapha ; Jenab, Mazda ; Aleksandrova, Krasimira ; Boutron-Ruault, Marie-Christine ; Dossus, Laure ; Racine, Antoine ; Kühn, Tilman ; Katzke, Verena A ; Tjønneland, Anne ; Petersen, Kristina E N ; Overvad, Kim ; Quirós, J Ramón ; Jakszyn, Paula ; Molina-Montes, Esther ; Dorronsoro, Miren ; Huerta, José-María ; Barricarte, Aurelio ; Khaw, Kay-Tee ; Wareham, Nick ; Travis, Ruth C ; Trichopoulou, Antonia ; Lagiou, Pagona ; Trichopoulos, Dimitrios ; Masala, Giovanna ; Krogh, Vittorio ; Tumino, Rosario ; Vineis, Paolo ; Panico, Salvatore ; Bueno-de-Mesquita, H Bas ; Siersema, Peter D ; Peeters, Petra H ; Ohlsson, Bodil ; Ericson, Ulrika ; Palmqvist, Richard ; Nyström, Hanna ; Weiderpass, Elisabete ; Skeie, Guri ; Freisling, Heinz ; Kong, So Yeon ; Tsilidis, Kostas ; Muller, David C ; Riboli, Elio ; Gunter, Marc J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c983t-aa390362d80f2f66fd848d8f6b8f12bb721c678e8b9aea38da9b55f5a3a8d03b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adiposity</topic><topic>Biology and Life Sciences</topic><topic>Biomarkers - blood</topic><topic>Body fat</topic><topic>Body Mass Index</topic><topic>Body Size</topic><topic>C-Peptide - blood</topic><topic>Cancer and Oncology</topic><topic>Cancer och onkologi</topic><topic>Cancer therapies</topic><topic>Cardiovascular disease</topic><topic>Case-Control Studies</topic><topic>Chi-Square Distribution</topic><topic>Clinical Medicine</topic><topic>Colorectal cancer</topic><topic>Colorectal Neoplasms - diagnosis</topic><topic>Colorectal Neoplasms - epidemiology</topic><topic>Community medicine, Social medicine: 801</topic><topic>Complications and side 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epidemiology</topic><topic>Obesity, Metabolically Benign - blood</topic><topic>Obesity, Metabolically Benign - diagnosis</topic><topic>Obesity, Metabolically Benign - epidemiology</topic><topic>Odds Ratio</topic><topic>Peptides</topic><topic>Phenotype</topic><topic>Phenotypes</topic><topic>Prospective Studies</topic><topic>Protective Factors</topic><topic>Researchers</topic><topic>Risk Assessment</topic><topic>Risk Factors</topic><topic>Samfunnsmedisin, sosialmedisin: 801</topic><topic>Studies</topic><topic>VDP</topic><topic>Waist Circumference</topic><topic>Weight control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Murphy, Neil</creatorcontrib><creatorcontrib>Cross, Amanda J</creatorcontrib><creatorcontrib>Abubakar, Mustapha</creatorcontrib><creatorcontrib>Jenab, Mazda</creatorcontrib><creatorcontrib>Aleksandrova, Krasimira</creatorcontrib><creatorcontrib>Boutron-Ruault, Marie-Christine</creatorcontrib><creatorcontrib>Dossus, 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(Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest Health and Medical</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest 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text</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SWEPUB Umeå universitet</collection><collection>SwePub Articles full text</collection><collection>SWEPUB Lunds universitet full text</collection><collection>SWEPUB Lunds universitet</collection><collection>Open Access: DOAJ - Directory of Open Access Journals</collection><collection>PLoS Medicine</collection><jtitle>PLoS medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Murphy, Neil</au><au>Cross, Amanda J</au><au>Abubakar, Mustapha</au><au>Jenab, Mazda</au><au>Aleksandrova, Krasimira</au><au>Boutron-Ruault, Marie-Christine</au><au>Dossus, Laure</au><au>Racine, Antoine</au><au>Kühn, Tilman</au><au>Katzke, Verena A</au><au>Tjønneland, Anne</au><au>Petersen, Kristina E N</au><au>Overvad, Kim</au><au>Quirós, J Ramón</au><au>Jakszyn, Paula</au><au>Molina-Montes, Esther</au><au>Dorronsoro, Miren</au><au>Huerta, José-María</au><au>Barricarte, Aurelio</au><au>Khaw, Kay-Tee</au><au>Wareham, Nick</au><au>Travis, Ruth C</au><au>Trichopoulou, Antonia</au><au>Lagiou, Pagona</au><au>Trichopoulos, Dimitrios</au><au>Masala, Giovanna</au><au>Krogh, Vittorio</au><au>Tumino, Rosario</au><au>Vineis, Paolo</au><au>Panico, Salvatore</au><au>Bueno-de-Mesquita, H Bas</au><au>Siersema, Peter D</au><au>Peeters, Petra H</au><au>Ohlsson, Bodil</au><au>Ericson, Ulrika</au><au>Palmqvist, Richard</au><au>Nyström, Hanna</au><au>Weiderpass, Elisabete</au><au>Skeie, Guri</au><au>Freisling, Heinz</au><au>Kong, So Yeon</au><au>Tsilidis, Kostas</au><au>Muller, David C</au><au>Riboli, Elio</au><au>Gunter, Marc J</au><au>Beck, Andrew H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC)</atitle><jtitle>PLoS medicine</jtitle><addtitle>PLoS Med</addtitle><date>2016-04-05</date><risdate>2016</risdate><volume>13</volume><issue>4</issue><spage>e1001988</spage><epage>e1001988</epage><pages>e1001988-e1001988</pages><issn>1549-1676</issn><issn>1549-1277</issn><eissn>1549-1676</eissn><abstract>Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia) have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic) overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown.
The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI) measurements to create four metabolic health/body size phenotype categories: (1) metabolically healthy/normal weight (BMI < 25 kg/m2), (2) metabolically healthy/overweight (BMI ≥ 25 kg/m2), (3) metabolically unhealthy/normal weight (BMI < 25 kg/m2), and (4) metabolically unhealthy/overweight (BMI ≥ 25 kg/m2). Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men]) were used (instead of BMI) to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was considered statistically significant. In multivariable-adjusted conditional logistic regression models with BMI used to define adiposity, compared with metabolically healthy/normal weight individuals, we observed a higher colorectal cancer risk among metabolically unhealthy/normal weight (odds ratio [OR] = 1.59, 95% CI 1.10-2.28) and metabolically unhealthy/overweight (OR = 1.40, 95% CI 1.01-1.94) participants, but not among metabolically healthy/overweight individuals (OR = 0.96, 95% CI 0.65-1.42). Among the overweight individuals, lower colorectal cancer risk was observed for metabolically healthy/overweight individuals compared with metabolically unhealthy/overweight individuals (OR = 0.69, 95% CI 0.49-0.96). These associations were generally consistent when waist circumference was used as the measure of adiposity. To our knowledge, there is no universally accepted clinical definition for using C-peptide level as an indication of hyperinsulinaemia. Therefore, a possible limitation of our analysis was that the classification of individuals as being hyperinsulinaemic-based on their C-peptide level-was arbitrary. However, when we used quartiles or the median of C-peptide, instead of tertiles, as the cut-point of hyperinsulinaemia, a similar pattern of associations was observed.
These results support the idea that individuals with the metabolically healthy/overweight phenotype (with normal insulin levels) are at lower colorectal cancer risk than those with hyperinsulinaemia. The combination of anthropometric measures with metabolic parameters, such as C-peptide, may be useful for defining strata of the population at greater risk of colorectal cancer.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>27046222</pmid><doi>10.1371/journal.pmed.1001988</doi><oa>free_for_read</oa></addata></record> |
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subjects | Adiposity Biology and Life Sciences Biomarkers - blood Body fat Body Mass Index Body Size C-Peptide - blood Cancer and Oncology Cancer och onkologi Cancer therapies Cardiovascular disease Case-Control Studies Chi-Square Distribution Clinical Medicine Colorectal cancer Colorectal Neoplasms - diagnosis Colorectal Neoplasms - epidemiology Community medicine, Social medicine: 801 Complications and side effects Diabetes Europe - epidemiology Female Genetic aspects Genotype & phenotype Health sciences: 800 Health Status Helsefag: 800 Humans Hyperinsulinism - blood Hyperinsulinism - diagnosis Hyperinsulinism - epidemiology Incidence Insulin Investigations Klinisk medicin Logistic Models Male Medical and Health Sciences Medical disciplines: 700 Medicin och hälsovetenskap Medicine and Health Sciences Medisinske Fag: 700 Metabolism Middle Aged Multivariate Analysis Nutrition research Obesity Obesity - blood Obesity - diagnosis Obesity - epidemiology Obesity, Metabolically Benign - blood Obesity, Metabolically Benign - diagnosis Obesity, Metabolically Benign - epidemiology Odds Ratio Peptides Phenotype Phenotypes Prospective Studies Protective Factors Researchers Risk Assessment Risk Factors Samfunnsmedisin, sosialmedisin: 801 Studies VDP Waist Circumference Weight control |
title | A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) |
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