Exposure to OPFRs Is Associated with Obesity and Dysregulated Serum Lipid Profiles: Data from 2017–2018 NHANES
Abstract
:1. Introduction
2. Methods
2.1. Study Population
2.2. Detection of Urinary Concentrations of OPFR Biomarkers
2.3. The Definition of Outcomes
2.4. Covariates
2.5. Statistical Analysis
3. Results
3.1. Baseline Characteristics of Study Participants
3.2. Overview of OPFR Metabolites in Urine Samples
3.3. Associations of Urinary OPFR Metabolites, BMI, and Obesity
3.4. Stratification Analyses of Associations of Urinary BCEP/BDCPP Concentrations and Obesity
3.5. Association of Urinary Concentrations of OPFR Metabolites and Serum Lipid Profiles
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variables | All Participants (n = 1334) |
---|---|
Age, years, mean ± SD | 45.19 ± 17.59 |
Sex, n (%) | |
Male | 656 (49.18) |
Female | 678 (50.82) |
BMI, kg/m2, mean ± SD | 29.42 ± 7.88 |
Race, n (%) | |
Mexican American | 206 (15.44%) |
Other Hispanic | 122 (9.15%) |
Non-Hispanic White | 449 (33.66%) |
Non-Hispanic Black | 297 (22.26%) |
Other race: including multiracial | 260 (19.49%) |
Smoking status, n (%) | |
Current smoker | 839 (62.89%) |
Former smoker | 206 (15.44%) |
Non-smoker | 289 (21.66%) |
Drinking, n (%) | 158 (11.84%) |
Physical activity, n (%) | |
None | 675 (50.60%) |
Moderate activity | 299 (22.41%) |
Vigorous activity | 360 (26.99%) |
Education level, n (%) | |
Less than 9th grade | 103 (8.25%) |
9–11th grade | 146 (11.70%) |
High school graduate/GED or equivalent | 281 (22.52%) |
Some college or AA degree | 406 (32.53%) |
College graduate or above | 312 (25.00%) |
Marital status, n (%) | |
Married/living with partner | 747 (59.76%) |
Widowed/divorced/separated | 241 (19.28%) |
Never married | 262 (20.96%) |
Family PIR, n (%) | |
<1 | 248 (18.59%) |
1–1.99 | 322 (24.14%) |
2–3.99 | 296 (22.19%) |
≥4 | 289 (21.66%) |
Missing | 179 (13.42%) |
Hypertension, n (%) | 334 (25.04%) |
Diabetes, n (%) | 105 (7.87%) |
Stroke, n (%) | 32 (2.40%) |
Coronary artery disease, n (%) | 20 (1.50%) |
Heart failure, n (%) | 20 (1.50%) |
Heart attack, n (%) | 237 (13.41%) |
Variables | All Participants (n = 1334) |
---|---|
Urinary creatinine (mg/dL), median (Q1–Q3) | 118.00 (63.00–181.00) |
Urinary metabolites of OPFRs (ng/mL), GM (95% CI) | |
BCIPP | 0.335 (0.313–0.357) |
BCEP | 1.046 (0.979–1.118) |
BDCPP | 0.136 (0.129–0.143) |
DBUP | 0.132 (0.125–0.138) |
DPHP | 0.764 (0.718–0.812) |
Variables | Model 1 | Model 2 | ||
---|---|---|---|---|
β (95% CI) | p Value | β (95% CI) | p Value | |
BCIPP | 0.32 (0.03, 0.62) | 0.0323 | 0.17 (−0.15, 0.49) | 0.3030 |
BCEP | 0.33 (0.09, 0.57) | 0.0068 | 0.27 (0.02, 0.52) | 0.0338 |
BDCPP | 0.71 (0.46, 0.96) | <0.0001 | 0.56 (0.25, 0.87) | 0.0004 |
DBUP | 0.35 (0.03, 0.67) | 0.0310 | 0.07 (−0.28, 0.41) | 0.6987 |
DPHP | 0.26 (−0.00, 0.52) | 0.0528 | −0.08 (−0.40, 0.24) | 0.6195 |
Variables | Models | OR (95% CI) | p Value |
---|---|---|---|
BCIPP | Model 1 | 1.05 (0.97, 1.13) | 0.2557 |
Model 2 | 1.02 (0.93, 1.11) | 0.7364 | |
BCEP | Model 1 | 1.12 (1.05, 1.20) | 0.0005 |
Model 2 | 1.10 (1.02, 1.18) | 0.0096 | |
BDCPP | Model 1 | 1.21 (1.13, 1.30) | <0.0001 |
Model 2 | 1.19 (1.09, 1.30) | 0.0001 | |
DBUP | Model 1 | 1.10 (1.01, 1.20) | 0.0273 |
Model 2 | 1.04 (0.95, 1.14) | 0.4258 | |
DPHP | Model 1 | 1.09 (1.01, 1.17) | 0.0206 |
Model 2 | 1.00 (0.92, 1.09) | 0.9820 |
Variables | Models | TG | TC | HDL-c | LDL-c | ||||
---|---|---|---|---|---|---|---|---|---|
β (95% CI) | p Value | β (95% CI) | p Value | β (95% CI) | p Value | β (95% CI) | p Value | ||
BCIPP | Model 1 | −2.74 (−6.65, 1.18) | 0.1714 | −0.08 (−1.59, 1.42) | 0.9125 | −0.09 (−0.66, 0.48) | 0.7540 | −0.70 (−2.55, 1.16) | 0.4628 |
Model 2 | −3.31 (−7.75, 1.13) | 0.1444 | 0.05 (−1.63, 1.73) | 0.9519 | 0.24 (−0.36, 0.84) | 0.4345 | −1.22 (−3.31, 0.86) | 0.2499 | |
BCEP | Model 1 | 0.61 (−2.62, 3.84) | 0.7117 | −0.51 (−1.71, 0.70) | 0.4090 | −0.54 (−1.00, −0.09) | 0.0199 | −0.41 (−1.94, 1.12) | 0.6018 |
Model 2 | 0.16 (−3.43, 3.75) | 0.9305 | −0.39 (−1.71, 0.92) | 0.5580 | −0.32 (−0.79, 0.16) | 0.1887 | −1.20 (−3.37, 0.97) | 0.2794 | |
BDCPP | Model 1 | −0.88 (−4.45, 2.70) | 0.6304 | −0.78 (−2.06, 0.50) | 0.2309 | −0.55 (−1.04, −0.07) | 0.0250 | −0.41 (−2.11, 1.28) | 0.6315 |
Model 2 | −2.25 (−6.88, 2.38) | 0.3418 | −0.82 (−2.46, 0.82) | 0.3279 | 0.29 (−0.30, 0.89) | 0.3299 | −1.20 (−3.37, 0.97) | 0.2794 | |
DBUP | Model 1 | 1.04 (−3.56, 5.64) | 0.6579 | −0.45 (−2.05, 1.15) | 0.5831 | −0.40 (−1.01, 0.21) | 0.1998 | −0.31 (−2.49, 1.86) | 0.7787 |
Model 2 | 0.69 (−4.55, 5.93) | 0.7961 | −0.76 (−2.55, 1.03) | 0.4055 | 0.10 (−0.54, 0.75) | 0.7587 | −1.30 (−3.75, 1.15) | 0.2994 | |
DPHP | Model 1 | −5.67 (−9.34, −2.00) | 0.0025 | −0.67 (−1.99, 0.66) | 0.3221 | −0.59 (−1.09, −0.08) | 0.0226 | −1.03 (−2.78, 0.73) | 0.2527 |
Model 2 | −7.41 (−12.13, −2.68) | 0.0022 | −0.17 (−1.83, 1.49) | 0.8420 | −0.06 (−0.65, 0.54) | 0.8545 | −1.20 (−3.44, 1.03) | 0.2925 |
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Li, H.; Li, F.; Zhou, C.; Bu, J.; Yang, H.; Zhong, L.; Xing, W.; Li, L. Exposure to OPFRs Is Associated with Obesity and Dysregulated Serum Lipid Profiles: Data from 2017–2018 NHANES. Metabolites 2024, 14, 124. https://doi.org/10.3390/metabo14020124
Li H, Li F, Zhou C, Bu J, Yang H, Zhong L, Xing W, Li L. Exposure to OPFRs Is Associated with Obesity and Dysregulated Serum Lipid Profiles: Data from 2017–2018 NHANES. Metabolites. 2024; 14(2):124. https://doi.org/10.3390/metabo14020124
Chicago/Turabian StyleLi, He, Fenglin Li, Chaoyi Zhou, Jifan Bu, Hao Yang, Liangchen Zhong, Weilong Xing, and Liangzhong Li. 2024. "Exposure to OPFRs Is Associated with Obesity and Dysregulated Serum Lipid Profiles: Data from 2017–2018 NHANES" Metabolites 14, no. 2: 124. https://doi.org/10.3390/metabo14020124
APA StyleLi, H., Li, F., Zhou, C., Bu, J., Yang, H., Zhong, L., Xing, W., & Li, L. (2024). Exposure to OPFRs Is Associated with Obesity and Dysregulated Serum Lipid Profiles: Data from 2017–2018 NHANES. Metabolites, 14(2), 124. https://doi.org/10.3390/metabo14020124