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The BAriatic surger...
The BAriatic surgery SUbstitution and nutrition (BASUN) population: a data-driven exploration of predictors for obesity
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- Höskuldsdóttir, Gudrun (author)
- Gothenburg University,Göteborgs universitet,Institutionen för medicin,Institute of Medicine
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- Engström, My, 1977 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för vårdvetenskap och hälsa,Institute of Health and Care Sciences
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- Rawshani, Araz, 1986 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för medicin,Institute of Medicine
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- Wallenius, Ville, 1970 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper,Institute of Clinical Sciences
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- Lenér, Frida (author)
- Gothenburg University,Göteborgs universitet,Institutionen för medicin,Institute of Medicine
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- Fändriks, Lars, 1956 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för kliniska vetenskaper,Institute of Clinical Sciences
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- Mossberg, Karin, 1981 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för medicin,Institute of Medicine
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- Eliasson, Björn, 1959 (author)
- Gothenburg University,Göteborgs universitet,Institutionen för medicin,Institute of Medicine
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(creator_code:org_t)
- 2021-09-10
- 2021
- English.
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In: Bmc Endocrine Disorders. - : Springer Science and Business Media LLC. - 1472-6823. ; 21:1
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Abstract
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- Background: The development of obesity is most likely due to a combination of biological and environmental factors some of which might still be unidentified. We used a machine learning technique to examine the relative importance of more than 100 clinical variables as predictors for BMI. Methods: BASUN is a prospective non-randomized cohort study of 971 individuals that received medical or surgical treatment (treatment choice was based on patient's preferences and clinical criteria, not randomization) for obesity in the Vastra Gotaland county in Sweden between 2015 and 2017 with planned follow-up for 10 years. This study includes demographic data, BMI, blood tests, and questionnaires before obesity treatment that cover three main areas: gastrointestinal symptoms and eating habits, physical activity and quality of life, and psychological health. We used random forest, with conditional variable importance, to study the relative importance of roughly 100 predictors of BMI, covering 15 domains. We quantified the predictive value of each individual predictor, as well as each domain. Results: The participants received medical (n = 382) or surgical treatment for obesity (Roux-en-Y gastric bypass, n = 388; sleeve gastrectomy, n = 201). There were minor differences between these groups before treatment with regard to anthropometrics, laboratory measures and results from questionnaires. The 10 individual variables with the strongest predictive value, in order of decreasing strength, were country of birth, marital status, sex, calcium levels, age, levels of TSH and HbA1c, AUDIT score, BE tendencies according to QEWPR, and TG levels. The strongest domains predicting BMI were: Socioeconomic status, Demographics, Biomarkers (notably TSH), Lifestyle/habits, Biomarkers for cardiovascular disease and diabetes, and Potential anxiety and depression. Conclusions: Lifestyle, habits, age, sex and socioeconomic status are some of the strongest predictors for BMI levels. Potential anxiety and / or depression and other characteristics captured using questionnaires have strong predictive value. These results confirm previously suggested associations and advocate prospective studies to examine the value of better characterization of patients eligible for obesity treatment, and consequently to evaluate the treatment effects in groups of patients.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Endokrinologi och diabetes (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Endocrinology and Diabetes (hsv//eng)
Keyword
- Obesity
- Bariatric surgery
- Diet
- Prospective study
- Cohort study
- weight-loss
- gender
- association
- adults
- fat
- Endocrinology & Metabolism
Publication and Content Type
- ref (subject category)
- art (subject category)
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Höskuldsdóttir, ...
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Engström, My, 19 ...
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Rawshani, Araz, ...
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Wallenius, Ville ...
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Lenér, Frida
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Fändriks, Lars, ...
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Mossberg, Karin, ...
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Eliasson, Björn, ...
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Clinical Medicin ...
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and Endocrinology an ...
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Bmc Endocrine Di ...
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University of Gothenburg