Directional Relationship Between Vitamin D Status and Prediabetes: A New Approach from Artificial Neural Network in a Cohort of Workers with Overweight-Obesity

Luisella Vigna, Amedea Silvia Tirelli, Enzo Grossi, Stefano Turolo, Laura Tomaino, Filomena Napolitano, Massimo Buscema, Luciano Riboldi

Research output: Contribution to journalArticle

Abstract

Objective: Despite the increasing literature on the association of diabetes with inflammation, cardiovascular risk, and vitamin D (25(OH)D) concentrations, strong evidence on the direction of causality among these factors is still lacking. This gap could be addressed by means of artificial neural networks (ANN) analysis. Methods: Retrospective observational study was carried out by means of an innovative data mining analysis—known as auto-contractive map (AutoCM)—and semantic mapping followed by Activation and Competition System on data of workers referring to an occupational-health outpatient clinic. Parameters analyzed included weight, height, waist circumference, body mass index (BMI), percentage of fat mass, glucose, insulin, glycated hemoglobin (HbA1c), creatinine, total cholesterol, low- and high-density lipoprotein cholesterol, triglycerides, uric acid, fibrinogen, homocysteine, C-reactive protein (CRP), diastolic and systolic blood pressure, and 25(OH)D. Results: The study included 309 workers. Of these, 23.6% were overweight, 40.5% were classified into the first class of obesity, 23.3% were in the second class, and 12.6% were in the third class (BMI > 40 kg/m). All mean biochemical values were in normal range, except for total cholesterol, low- and high-density lipoprotein cholesterol, CRP, and 25(OH)D. HbA1c was between 39 and 46 mmol/mol in 51.78%. 25(OH)D levels were sufficient in only 12.6%. Highest inverse correlation for hyperglycemia onset was with BMI and waist circumference, suggesting a protective role of 25(OH)D against their increase. AutoCM processing and the semantic map evidenced direct association of 25(OH)D with high link strength (0.99) to low CRP levels and low high-density lipoprotein cholesterol levels. Low 25(OH)D led to changes in glucose, which affected metabolic syndrome biomarkers, first of which was homeostatic model assessment index and blood glucose, but not 25(OH)D. Conclusions: The use of ANN suggests a key role of 25(OH)D respect to all considered metabolic parameters in the development of diabetes and evidences a causation between low 25(OH)D and high glucose concentrations.

Original languageEnglish
Pages (from-to)681-692
JournalJournal of the American College of Nutrition
Volume38
Issue number8
DOIs
Publication statusPublished - Jan 1 2019

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Prediabetic State
Vitamin D
C-Reactive Protein
HDL Cholesterol
Body Mass Index
Obesity
Waist Circumference
Semantics
Glucose
Causality
Cholesterol
Blood Pressure
Data Mining
Glycosylated Hemoglobin A
Homocysteine
Occupational Health
Ambulatory Care Facilities
Uric Acid
Information Systems
Hyperglycemia

Keywords

  • artificial neural network
  • auto-contractive map
  • inflammation
  • obesity
  • occupational health
  • prediabetes
  • sedentary workers
  • Vitamin D

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Nutrition and Dietetics

Cite this

@article{d526c7a0b8104ea9913daf2865fcc997,
title = "Directional Relationship Between Vitamin D Status and Prediabetes: A New Approach from Artificial Neural Network in a Cohort of Workers with Overweight-Obesity",
abstract = "Objective: Despite the increasing literature on the association of diabetes with inflammation, cardiovascular risk, and vitamin D (25(OH)D) concentrations, strong evidence on the direction of causality among these factors is still lacking. This gap could be addressed by means of artificial neural networks (ANN) analysis. Methods: Retrospective observational study was carried out by means of an innovative data mining analysis—known as auto-contractive map (AutoCM)—and semantic mapping followed by Activation and Competition System on data of workers referring to an occupational-health outpatient clinic. Parameters analyzed included weight, height, waist circumference, body mass index (BMI), percentage of fat mass, glucose, insulin, glycated hemoglobin (HbA1c), creatinine, total cholesterol, low- and high-density lipoprotein cholesterol, triglycerides, uric acid, fibrinogen, homocysteine, C-reactive protein (CRP), diastolic and systolic blood pressure, and 25(OH)D. Results: The study included 309 workers. Of these, 23.6{\%} were overweight, 40.5{\%} were classified into the first class of obesity, 23.3{\%} were in the second class, and 12.6{\%} were in the third class (BMI > 40 kg/m). All mean biochemical values were in normal range, except for total cholesterol, low- and high-density lipoprotein cholesterol, CRP, and 25(OH)D. HbA1c was between 39 and 46 mmol/mol in 51.78{\%}. 25(OH)D levels were sufficient in only 12.6{\%}. Highest inverse correlation for hyperglycemia onset was with BMI and waist circumference, suggesting a protective role of 25(OH)D against their increase. AutoCM processing and the semantic map evidenced direct association of 25(OH)D with high link strength (0.99) to low CRP levels and low high-density lipoprotein cholesterol levels. Low 25(OH)D led to changes in glucose, which affected metabolic syndrome biomarkers, first of which was homeostatic model assessment index and blood glucose, but not 25(OH)D. Conclusions: The use of ANN suggests a key role of 25(OH)D respect to all considered metabolic parameters in the development of diabetes and evidences a causation between low 25(OH)D and high glucose concentrations.",
keywords = "artificial neural network, auto-contractive map, inflammation, obesity, occupational health, prediabetes, sedentary workers, Vitamin D",
author = "Luisella Vigna and {Silvia Tirelli}, Amedea and Enzo Grossi and Stefano Turolo and Laura Tomaino and Filomena Napolitano and Massimo Buscema and Luciano Riboldi",
year = "2019",
month = "1",
day = "1",
doi = "10.1080/07315724.2019.1590249",
language = "English",
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}

TY - JOUR

T1 - Directional Relationship Between Vitamin D Status and Prediabetes

T2 - A New Approach from Artificial Neural Network in a Cohort of Workers with Overweight-Obesity

AU - Vigna, Luisella

AU - Silvia Tirelli, Amedea

AU - Grossi, Enzo

AU - Turolo, Stefano

AU - Tomaino, Laura

AU - Napolitano, Filomena

AU - Buscema, Massimo

AU - Riboldi, Luciano

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Objective: Despite the increasing literature on the association of diabetes with inflammation, cardiovascular risk, and vitamin D (25(OH)D) concentrations, strong evidence on the direction of causality among these factors is still lacking. This gap could be addressed by means of artificial neural networks (ANN) analysis. Methods: Retrospective observational study was carried out by means of an innovative data mining analysis—known as auto-contractive map (AutoCM)—and semantic mapping followed by Activation and Competition System on data of workers referring to an occupational-health outpatient clinic. Parameters analyzed included weight, height, waist circumference, body mass index (BMI), percentage of fat mass, glucose, insulin, glycated hemoglobin (HbA1c), creatinine, total cholesterol, low- and high-density lipoprotein cholesterol, triglycerides, uric acid, fibrinogen, homocysteine, C-reactive protein (CRP), diastolic and systolic blood pressure, and 25(OH)D. Results: The study included 309 workers. Of these, 23.6% were overweight, 40.5% were classified into the first class of obesity, 23.3% were in the second class, and 12.6% were in the third class (BMI > 40 kg/m). All mean biochemical values were in normal range, except for total cholesterol, low- and high-density lipoprotein cholesterol, CRP, and 25(OH)D. HbA1c was between 39 and 46 mmol/mol in 51.78%. 25(OH)D levels were sufficient in only 12.6%. Highest inverse correlation for hyperglycemia onset was with BMI and waist circumference, suggesting a protective role of 25(OH)D against their increase. AutoCM processing and the semantic map evidenced direct association of 25(OH)D with high link strength (0.99) to low CRP levels and low high-density lipoprotein cholesterol levels. Low 25(OH)D led to changes in glucose, which affected metabolic syndrome biomarkers, first of which was homeostatic model assessment index and blood glucose, but not 25(OH)D. Conclusions: The use of ANN suggests a key role of 25(OH)D respect to all considered metabolic parameters in the development of diabetes and evidences a causation between low 25(OH)D and high glucose concentrations.

AB - Objective: Despite the increasing literature on the association of diabetes with inflammation, cardiovascular risk, and vitamin D (25(OH)D) concentrations, strong evidence on the direction of causality among these factors is still lacking. This gap could be addressed by means of artificial neural networks (ANN) analysis. Methods: Retrospective observational study was carried out by means of an innovative data mining analysis—known as auto-contractive map (AutoCM)—and semantic mapping followed by Activation and Competition System on data of workers referring to an occupational-health outpatient clinic. Parameters analyzed included weight, height, waist circumference, body mass index (BMI), percentage of fat mass, glucose, insulin, glycated hemoglobin (HbA1c), creatinine, total cholesterol, low- and high-density lipoprotein cholesterol, triglycerides, uric acid, fibrinogen, homocysteine, C-reactive protein (CRP), diastolic and systolic blood pressure, and 25(OH)D. Results: The study included 309 workers. Of these, 23.6% were overweight, 40.5% were classified into the first class of obesity, 23.3% were in the second class, and 12.6% were in the third class (BMI > 40 kg/m). All mean biochemical values were in normal range, except for total cholesterol, low- and high-density lipoprotein cholesterol, CRP, and 25(OH)D. HbA1c was between 39 and 46 mmol/mol in 51.78%. 25(OH)D levels were sufficient in only 12.6%. Highest inverse correlation for hyperglycemia onset was with BMI and waist circumference, suggesting a protective role of 25(OH)D against their increase. AutoCM processing and the semantic map evidenced direct association of 25(OH)D with high link strength (0.99) to low CRP levels and low high-density lipoprotein cholesterol levels. Low 25(OH)D led to changes in glucose, which affected metabolic syndrome biomarkers, first of which was homeostatic model assessment index and blood glucose, but not 25(OH)D. Conclusions: The use of ANN suggests a key role of 25(OH)D respect to all considered metabolic parameters in the development of diabetes and evidences a causation between low 25(OH)D and high glucose concentrations.

KW - artificial neural network

KW - auto-contractive map

KW - inflammation

KW - obesity

KW - occupational health

KW - prediabetes

KW - sedentary workers

KW - Vitamin D

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