TY - JOUR
T1 - Associations of Obesity and Neighborhood Factors With Urinary Stone Parameters
AU - Collaboration on Disparities in Kidney Stone Disease
AU - Crivelli, Joseph J.
AU - Redden, David T.
AU - Johnson, Robert D.
AU - Juarez, Lucia D.
AU - Maalouf, Naim M.
AU - Hughes, Amy
AU - Wood, Kyle D.
AU - Assimos, G.
AU - Oates, Gabriela R.
N1 - Funding Information:
The authors thank Shirley Zhang, Lauren Oliver, and Lakshmi Subramani for reviewing the charts to determine stone composition; John Hollingsworth, Ryan Hsi, and Phyllis Yan for providing diagnosis and procedure codes for conditions associated with gastrointestinal malabsorption; and John Asplin for valuable input on study design and results reporting. In addition, the authors are grateful to the University of Alabama at Birmingham Obesity Health Disparities Research Center (NIH U54MD000502) and the Guest Editors for the opportunity to submit this work. The research presented in this paper is that of the authors and does not reflect the official policy of the NIH. The IRB at the University of Alabama at Birmingham approved this study (protocol number 300006901). Biostatistical consultation (DTR) was supported by the University of Alabama at Birmingham Center for Clinical and Translational Science (NIH UL1TR003096). Funding was also provided through NIH K08DK115833 (KDW) and P20DK128160 (DGA). KDW reports conflicts of interest for Alnylam Pharmaceuticals and Steris Healthcare. No other financial disclosures were reported. Joseph J. Crivelli: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing - original draft, Writing - review & editing. David T. Redden: Formal analysis, Methodology, Resources, Visualization, Writing - review & editing. Robert D. Johnson: Data curation, Resources. Lucia D. Juarez: Methodology, Writing - review & editing. Naim M. Maalouf: Conceptualization, Funding acquisition, Writing - review & editing. Amy E. Hughes: Conceptualization. Kyle D. Wood: Conceptualization, Data curation, Resources, Writing - review & editing. Dean G. Assimos: Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing - review & editing. Gabriela R. Oates: Conceptualization, Methodology, Project administration, Resources, Supervision, Writing - review & editing.
Funding Information:
Biostatistical consultation (DTR) was supported by the University of Alabama at Birmingham Center for Clinical and Translational Science (NIH UL1TR003096). Funding was also provided through NIH K08DK115833 (KDW) and P20DK128160 (DGA).
Funding Information:
This article is part of a supplement entitled Obesity-Related Health Disparities: Addressing the Complex Contributors, sponsored by the National Institute on Minority Health and Health Disparities (NIMHD), part of the National Institutes of Health (NIH), an agency of the U.S. Department of Health and Human Services (HHS).
Publisher Copyright:
© 2022 American Journal of Preventive Medicine
PY - 2022/7
Y1 - 2022/7
N2 - Introduction: Obesity is associated with kidney stone disease, but it is unknown whether this association differs by SES. This study assessed the extent to which obesity and neighborhood characteristics jointly contribute to urinary risk factors for kidney stone disease. Methods: This was a retrospective analysis of adult patients with kidney stone disease evaluated with 24-hour urine collection (2001–2020). Neighborhood-level socioeconomic data were obtained for a principal component analysis, which identified 3 linearly independent factors. Associations between these factors and 24-hour urine measurements were assessed using linear regression as well as groupings of 24-hour urine results using multivariable logistic regression. Finally, multiplicative interactions were assessed testing effect modification by obesity, and analyses stratified by obesity were performed. Analyses were performed in 2021. Results: In total, 1,264 patients met the study criteria. Factors retained on principal component analysis represented SES, family structure, and housing characteristics. On linear regression, there was a significant inverse correlation between SES and 24-hour urine sodium (p=0.0002). On multivariable logistic regression, obesity was associated with increased odds of multiple stone risk factors (OR=1.61; 95% CI=1.15, 2.26) and multiple dietary factors (OR=1.33; 95% CI=1.06, 1.67). No significant and consistent multiplicative interactions were observed between obesity and quartiles of neighborhood SES, family structure, or housing characteristics. Conclusions: Obesity was associated with the presence of multiple stone risk factors and multiple dietary factors; however, the strength and magnitude of these associations did not vary significantly by neighborhood SES, family structure, and housing characteristics.
AB - Introduction: Obesity is associated with kidney stone disease, but it is unknown whether this association differs by SES. This study assessed the extent to which obesity and neighborhood characteristics jointly contribute to urinary risk factors for kidney stone disease. Methods: This was a retrospective analysis of adult patients with kidney stone disease evaluated with 24-hour urine collection (2001–2020). Neighborhood-level socioeconomic data were obtained for a principal component analysis, which identified 3 linearly independent factors. Associations between these factors and 24-hour urine measurements were assessed using linear regression as well as groupings of 24-hour urine results using multivariable logistic regression. Finally, multiplicative interactions were assessed testing effect modification by obesity, and analyses stratified by obesity were performed. Analyses were performed in 2021. Results: In total, 1,264 patients met the study criteria. Factors retained on principal component analysis represented SES, family structure, and housing characteristics. On linear regression, there was a significant inverse correlation between SES and 24-hour urine sodium (p=0.0002). On multivariable logistic regression, obesity was associated with increased odds of multiple stone risk factors (OR=1.61; 95% CI=1.15, 2.26) and multiple dietary factors (OR=1.33; 95% CI=1.06, 1.67). No significant and consistent multiplicative interactions were observed between obesity and quartiles of neighborhood SES, family structure, or housing characteristics. Conclusions: Obesity was associated with the presence of multiple stone risk factors and multiple dietary factors; however, the strength and magnitude of these associations did not vary significantly by neighborhood SES, family structure, and housing characteristics.
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U2 - 10.1016/j.amepre.2022.01.033
DO - 10.1016/j.amepre.2022.01.033
M3 - Article
C2 - 35725147
AN - SCOPUS:85132270619
SN - 0749-3797
VL - 63
SP - S93-S102
JO - American Journal of Preventive Medicine
JF - American Journal of Preventive Medicine
IS - 1
ER -