Research on the Dose Response Relationship between Metabolic Diseases and Cadmium Exposure Based on Urinary Biomarker Detection

Background & Objectives Cadmium (Cd), a pervasive environmental pollutant, enters the human body through longterm lowdose exposure via dietary sources (e.g., contaminated rice), tobacco smoking, and industrial emissions. While highdose cadmium nephrotoxicity is well established, systematic evidence on its lowdose effects on metabolic diseases remains limited. This study investigated the association and doseresponse relationship between low level environmental cadmium exposure—using urinary cadmium (creatininecorrected) as a biomarker—and metabolic diseases including hypertension, type 2 diabetes, hyperlipidemia, obesity, and nonalcoholic fatty liver disease (NAFLD) in an adult health examination cohort from Zoucheng City, Shandong Province, China. Methods A total of ____ participants were enrolled. Demographic characteristics, lifestyle factors, and disease histories were collected using standardized questionnaires. Physical examinations provided clinical data. Urinary cadmium concentrations (μg/g creatinine) were quantified via inductively coupled plasma mass spectrometry (ICPMS). Multiple logistic regression models adjusted for confounders (age, sex, smoking, alcohol consumption, BMI, etc.). Restricted cubic spline (RCS) models with four knots (10th, 50th, 70th, 90th percentiles) were employed to characterize nonlinear doseresponse relationships. Key Results Positive Associations: Elevated urinary cadmium levels showed statistically significant positive correlations with all metabolic diseases (P < 0.05). Nonlinear DoseResponse: RCS analyses revealed distinct nonlinear trends (P_nonlinearity < 0.01). Disease risks increased steeply at low exposure ranges (e.g., urinary Cd < 1.0 μg/g creatinine), exhibiting a “lowdose, highslope” pattern. Risk escalation plateaued at higher concentrations. DiseaseSpecific Risks: NAFLD (adjusted OR [95% CI]: 1.82 [1.45–2.30] per logunit Cd increase) and hypertension (1.78 [1.50–2.11]) demonstrated the strongest associations. Conclusions & Implications This study demonstrates that lowdose environmental cadmium exposure is a significant risk factor for metabolic diseases. The steep risk escalation at low concentrations suggests current safety thresholds may inadequately protect metabolic health. Our findings provide critical epidemiological evidence for revising environmental cadmium standards and guiding public health interventions (e.g., highrisk population screening, pollution source control). This work underscores the need to address longterm lowdose heavy metal toxicity in environmental health policies.

Authors

Publication Details

Journal
International Journal of Research and Innovation in Social Science
Published
2025-01-01
DOI
https://doi.org/10.47772/ijriss.2025.907000262
Primary Topic
Medical Research and Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on the Dose Response Relationship between Metabolic Diseases and Cadmium Exposure Based on Urinary Biomarker Detection

Hao Feng, Rania Hussien, Siti Ruzita
International Journal of Research and Innovation in Social Science
Medical Research and Treatments
article

Research on the Dose Response Relationship between Metabolic Diseases and Cadmium Exposure Based on Urinary Biomarker Detection

Hao Feng, Rania Hussien, Siti Ruzita
article en

Abstract

Background & Objectives Cadmium (Cd), a pervasive environmental pollutant, enters the human body through longterm lowdose exposure via dietary sources (e.g., contaminated rice), tobacco smoking, and industrial emissions. While highdose cadmium nephrotoxicity is well established, systematic evidence on its lowdose effects on metabolic diseases remains limited. This study investigated the association and doseresponse relationship between low level environmental cadmium exposure—using urinary cadmium (creatininecorrected) as a biomarker—and metabolic diseases including hypertension, type 2 diabetes, hyperlipidemia, obesity, and nonalcoholic fatty liver disease (NAFLD) in an adult health examination cohort from Zoucheng City, Shandong Province, China. Methods A total of ____ participants were enrolled. Demographic characteristics, lifestyle factors, and disease histories were collected using standardized questionnaires. Physical examinations provided clinical data. Urinary cadmium concentrations (μg/g creatinine) were quantified via inductively coupled plasma mass spectrometry (ICPMS). Multiple logistic regression models adjusted for confounders (age, sex, smoking, alcohol consumption, BMI, etc.). Restricted cubic spline (RCS) models with four knots (10th, 50th, 70th, 90th percentiles) were employed to characterize nonlinear doseresponse relationships. Key Results Positive Associations: Elevated urinary cadmium levels showed statistically significant positive correlations with all metabolic diseases (P < 0.05). Nonlinear DoseResponse: RCS analyses revealed distinct nonlinear trends (P_nonlinearity < 0.01). Disease risks increased steeply at low exposure ranges (e.g., urinary Cd < 1.0 μg/g creatinine), exhibiting a “lowdose, highslope” pattern. Risk escalation plateaued at higher concentrations. DiseaseSpecific Risks: NAFLD (adjusted OR [95% CI]: 1.82 [1.45–2.30] per logunit Cd increase) and hypertension (1.78 [1.50–2.11]) demonstrated the strongest associations. Conclusions & Implications This study demonstrates that lowdose environmental cadmium exposure is a significant risk factor for metabolic diseases. The steep risk escalation at low concentrations suggests current safety thresholds may inadequately protect metabolic health. Our findings provide critical epidemiological evidence for revising environmental cadmium standards and guiding public health interventions (e.g., highrisk population screening, pollution source control). This work underscores the need to address longterm lowdose heavy metal toxicity in environmental health policies.

International Journal of Research and Innovation in Social ScienceVol. IX(VII)
Openalex Percentile: Top 67%
Medical Research and Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.