AIMC Topic: Nutrition Surveys

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Machine Learning-Based Analysis of Lifestyle Risk Factors for Atherosclerotic Cardiovascular Disease: Retrospective Case-Control Study.

JMIR medical informatics
BACKGROUND: The risk of developing atherosclerotic cardiovascular disease (ASCVD) varies among individuals and is related to a variety of lifestyle factors in addition to the presence of chronic diseases.

Predicting depression using serum perfluoroalkyl and polyfluoroalkyl substances levels via interpretable machine learning.

Journal of affective disorders
BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals with widespread environmental persistence and human exposure. Currently, no studies have used machine learning (ML) to predict depression based on PFAS exposure. This stud...

METS-VF as a novel predictor of gallstones in U.S. adults: a cross-sectional analysis (NHANES 2017-2020).

BMC gastroenterology
BACKGROUND AND AIMS: Obesity is a well-established risk factor for gallstone formation, but traditional anthropometric measures (e.g., BMI, waist circumference) inadequately assess metabolically active visceral adiposity. The novel Metabolic Score fo...

Association between atherogenic index of plasma and hypertension combined with diabetes mellitus in United States adults: an analysis of the NHANES surveys from 2011 to 2016.

Journal of health, population, and nutrition
INTRODUCTION: Observational studies have indicated that individuals with hypertension (HTN) and diabetes mellitus (DM) tend to exhibit elevated plasma atherogenic index of plasma (AIP), defined as log (triglyceride [TG]/high-density lipoprotein chole...

The application and predictive value of the weight-adjusted-waist index in BC prevalence assessment: a comprehensive statistical and machine learning analysis using NHANES data.

BMC cancer
BACKGROUND: Obesity is a known risk factor for breast cancer (BC), but conventional metrics such as body mass index (BMI) may insufficiently capture central adiposity. The weight-adjusted waist index (WWI) has emerged as a potentially superior anthro...

Interpretable machine learning approaches for predicting prostate cancer by using multiple heavy metal exposures based on the data from NHANES 2003-2018.

Ecotoxicology and environmental safety
Environmental pollution plays a major role in the development of prostate cancer (PCA). However, there has been no research on machine learning (ML) modelling between multiple heavy metal exposures and PCA risk. Based on the 8022 samples from the 200...

Precision nutrition in epigenetic aging: SHAP-optimized machine learning identifies omega-3 constituent-specific associations with aging biomarkers.

Biogerontology
This cross-sectional investigation seeks to examine the association between dietary omega-3 fatty acids (including α-linolenic acid [ALA], eicosapentaenoic acid [EPA], and docosahexaenoic acid [DHA]) and biomarkers of cellular aging, specifically DNA...

Predicting mortality risk in Alzheimer's disease using machine learning based on lifestyle and physical activity.

Scientific reports
Alzheimer's disease (AD), a progressive neurodegenerative disorder, significantly impacts patient survival, prompting the need for accurate prognostic tools. Lifestyle factors and physical activity levels have been identified as critical modifiable r...

Potential effects of endocrine-disrupting chemicals on preserved ratio impaired spirometry revealed by five different approaches.

Ecotoxicology and environmental safety
OBJECTIVE: Evidence from prior studies indicates that certain endocrine-disrupting chemicals (EDCs), such as phenols and phthalates, may serve as environmental risk factors for chronic obstructive pulmonary disease (COPD). However, no studies have ex...

Explainable machine learning-driven models for predicting Parkinson's disease and its prognosis: obesity patterns associations and models development using NHANES 1999-2018 data.

Lipids in health and disease
BACKGROUND: Parkinson's disease (PD) is a prevalent neurodegenerative condition, the effect of obesity on PD remains controversial. We aimed to investigate the associations of obesity patterns on PD and all-cause mortality, while developing machine l...