Metabolic obesity phenotypes and obesity‐related cancer risk in the National Health and Nutrition Examination Survey
Abstract Introduction Body mass index (BMI) fails to identify up to one‐third of normal weight individuals with metabolic dysfunction who may be at increased risk of obesity‐related cancer (ORC). Metabolic obesity phenotypes, an alternate metric to assess metabolic dysfunction with or without obesit...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-07-01
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| Series: | Endocrinology, Diabetes & Metabolism |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/edm2.433 |
| _version_ | 1827903879596998656 |
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| author | Maci Winn Prasoona Karra Heinz Freisling Marc J. Gunter Benjamin Haaland Michelle L. Litchman Jennifer A. Doherty Mary C. Playdon Sheetal Hardikar |
| author_facet | Maci Winn Prasoona Karra Heinz Freisling Marc J. Gunter Benjamin Haaland Michelle L. Litchman Jennifer A. Doherty Mary C. Playdon Sheetal Hardikar |
| author_sort | Maci Winn |
| collection | DOAJ |
| description | Abstract Introduction Body mass index (BMI) fails to identify up to one‐third of normal weight individuals with metabolic dysfunction who may be at increased risk of obesity‐related cancer (ORC). Metabolic obesity phenotypes, an alternate metric to assess metabolic dysfunction with or without obesity, were evaluated for association with ORC risk. Methods National Health and Nutrition Examination Survey participants from 1999 to 2018 (N = 19,500) were categorized into phenotypes according to the metabolic syndrome (MetS) criteria and BMI: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight/obese (MHO) and metabolically unhealthy overweight/obese (MUO). Adjusted multivariable logistic regression models were used to evaluate associations with ORC. Results With metabolic dysfunction defined as ≥1 MetS criteria, ORC cases (n = 528) had higher proportions of MUNW (28.2% vs. 17.4%) and MUO (62.6% vs. 60.9%) phenotypes than cancer‐free individuals (n = 18,972). Compared with MHNW participants, MUNW participants had a 2.2‐times higher ORC risk [OR (95%CI) = 2.21 (1.27–3.85)]. MHO and MUO participants demonstrated a 43% and 56% increased ORC risk, respectively, compared to MHNW, but these did not reach statistical significance [OR (95% CI) = 1.43 (0.46–4.42), 1.56 (0.91–2.67), respectively]. Hyperglycaemia, hypertension and central obesity were all independently associated with higher ORC risk compared to MHNW. Conclusions MUNW participants have a higher risk of ORC than other abnormal phenotypes, compared with MHNW participants. Incorporating metabolic health measures in addition to assessing BMI may improve ORC risk stratification. Further research on the relationship between metabolic dysfunction and ORC is warranted. |
| first_indexed | 2024-03-13T00:19:51Z |
| format | Article |
| id | doaj.art-ebf02c918437483aa5097ea33daa6d29 |
| institution | Directory Open Access Journal |
| issn | 2398-9238 |
| language | English |
| last_indexed | 2024-03-13T00:19:51Z |
| publishDate | 2023-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Endocrinology, Diabetes & Metabolism |
| spelling | doaj.art-ebf02c918437483aa5097ea33daa6d292023-07-11T17:25:36ZengWileyEndocrinology, Diabetes & Metabolism2398-92382023-07-0164n/an/a10.1002/edm2.433Metabolic obesity phenotypes and obesity‐related cancer risk in the National Health and Nutrition Examination SurveyMaci Winn0Prasoona Karra1Heinz Freisling2Marc J. Gunter3Benjamin Haaland4Michelle L. Litchman5Jennifer A. Doherty6Mary C. Playdon7Sheetal Hardikar8Department of Population Health Sciences University of Utah Salt Lake City Utah USAHuntsman Cancer Institute University of Utah Salt Lake City Utah USANutrition and Metabolism Branch International Agency for Research on Cancer Lyon FranceNutrition and Metabolism Branch International Agency for Research on Cancer Lyon FranceHuntsman Cancer Institute University of Utah Salt Lake City Utah USAUniversity of Utah College of Nursing Salt Lake City Utah USADepartment of Population Health Sciences University of Utah Salt Lake City Utah USAHuntsman Cancer Institute University of Utah Salt Lake City Utah USADepartment of Population Health Sciences University of Utah Salt Lake City Utah USAAbstract Introduction Body mass index (BMI) fails to identify up to one‐third of normal weight individuals with metabolic dysfunction who may be at increased risk of obesity‐related cancer (ORC). Metabolic obesity phenotypes, an alternate metric to assess metabolic dysfunction with or without obesity, were evaluated for association with ORC risk. Methods National Health and Nutrition Examination Survey participants from 1999 to 2018 (N = 19,500) were categorized into phenotypes according to the metabolic syndrome (MetS) criteria and BMI: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight/obese (MHO) and metabolically unhealthy overweight/obese (MUO). Adjusted multivariable logistic regression models were used to evaluate associations with ORC. Results With metabolic dysfunction defined as ≥1 MetS criteria, ORC cases (n = 528) had higher proportions of MUNW (28.2% vs. 17.4%) and MUO (62.6% vs. 60.9%) phenotypes than cancer‐free individuals (n = 18,972). Compared with MHNW participants, MUNW participants had a 2.2‐times higher ORC risk [OR (95%CI) = 2.21 (1.27–3.85)]. MHO and MUO participants demonstrated a 43% and 56% increased ORC risk, respectively, compared to MHNW, but these did not reach statistical significance [OR (95% CI) = 1.43 (0.46–4.42), 1.56 (0.91–2.67), respectively]. Hyperglycaemia, hypertension and central obesity were all independently associated with higher ORC risk compared to MHNW. Conclusions MUNW participants have a higher risk of ORC than other abnormal phenotypes, compared with MHNW participants. Incorporating metabolic health measures in addition to assessing BMI may improve ORC risk stratification. Further research on the relationship between metabolic dysfunction and ORC is warranted.https://doi.org/10.1002/edm2.433cancer riskepidemiologymetabolic obesity phenotypesmetabolic syndromeobesity‐related cancer |
| spellingShingle | Maci Winn Prasoona Karra Heinz Freisling Marc J. Gunter Benjamin Haaland Michelle L. Litchman Jennifer A. Doherty Mary C. Playdon Sheetal Hardikar Metabolic obesity phenotypes and obesity‐related cancer risk in the National Health and Nutrition Examination Survey Endocrinology, Diabetes & Metabolism cancer risk epidemiology metabolic obesity phenotypes metabolic syndrome obesity‐related cancer |
| title | Metabolic obesity phenotypes and obesity‐related cancer risk in the National Health and Nutrition Examination Survey |
| title_full | Metabolic obesity phenotypes and obesity‐related cancer risk in the National Health and Nutrition Examination Survey |
| title_fullStr | Metabolic obesity phenotypes and obesity‐related cancer risk in the National Health and Nutrition Examination Survey |
| title_full_unstemmed | Metabolic obesity phenotypes and obesity‐related cancer risk in the National Health and Nutrition Examination Survey |
| title_short | Metabolic obesity phenotypes and obesity‐related cancer risk in the National Health and Nutrition Examination Survey |
| title_sort | metabolic obesity phenotypes and obesity related cancer risk in the national health and nutrition examination survey |
| topic | cancer risk epidemiology metabolic obesity phenotypes metabolic syndrome obesity‐related cancer |
| url | https://doi.org/10.1002/edm2.433 |
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