Higher neighborhood disadvantage is associated with weaker interactions among cardiometabolic drivers

Joel Hernandez Sevillano; Masih A Babagoli; Yitong Chen; Shelley H Liu; Pranav Mellacheruvu; Janet Johnson; Borja Ibanez; Oscar Lorenzo; Jeffrey I Mechanick

doi:10.1016/j.ijcrp.2024.200322

Higher neighborhood disadvantage is associated with weaker interactions among cardiometabolic drivers

Int J Cardiol Cardiovasc Risk Prev. 2024 Aug 19:23:200322. doi: 10.1016/j.ijcrp.2024.200322. eCollection 2024 Dec.

Authors

Joel Hernandez Sevillano^{1

2}, Masih A Babagoli³, Yitong Chen⁴, Shelley H Liu⁴, Pranav Mellacheruvu⁵, Janet Johnson¹, Borja Ibanez^{2

6

7}, Oscar Lorenzo^{8

9}, Jeffrey I Mechanick¹

Affiliations

¹ Kravis Center for Clinical Cardiovascular Health at the Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
² Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.
³ Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁴ Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
⁵ Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
⁶ Cardiology Department, IIS-Fundación Jiménez Díaz University Hospital, Madrid, Spain.
⁷ CIBER de Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain.
⁸ IIS-Fundación Jiménez Díaz, Autónoma University, Madrid, Spain.
⁹ Biomedical Research Network on Diabetes and Associated Metabolic Disorders (CIBERDEM), Carlos III National Health Institute, Madrid, Spain.

Abstract

Background: Adiposity, dysglycemia, and hypertension are metabolic drivers that have causal interactions with each other. However, the effect of neighborhood-level disadvantage on the intensity of interactions among these metabolic drivers has not been studied. The objective of this study is to determine whether the strength of the interplay between these drivers is affected by neighborhood-level disadvantage.

Methods: This cross-sectional study analyzed patients presenting to a multidisciplinary preventive cardiology center in New York City, from March 2017 to February 2021. Patients' home addresses were mapped to the Area Deprivation Index to determine neighborhood disadvantage. The outcomes of interest were correlation coefficients (range from -1 to +1) among the various stages (0 - normal, 1 - risk, 2 - predisease, 3 - disease, and 4 - complications) of abnormal adiposity, dysglycemia, and hypertension at presentation, stratified by neighborhood disadvantage.

Results: The cohort consisted of 963 patients (age, median [IQR] 63.8 [49.7-72.5] years; 624 [65.1 %] female). The correlation among the various stages of adiposity, dysglycemia, and hypertension was weaker with increasing neighborhood disadvantage (P for trend <0.001). Specifically, the correlation describing adiposity, dysglycemia, and hypertension interaction was weaker in the high neighborhood disadvantage group compared to the intermediate neighborhood disadvantage group (median [IQR]: 0.34 [0.27, 0.44] vs. median [IQR]: 0.39 [0.34, 0.45]; P < 0.001) and compared to the low neighborhood disadvantage group (median [IQR]: 0.34 [0.27, 0.44] vs. median [IQR]: 0.54 [0.52, 0.57]; P < 0.001), as well as weaker in the intermediate neighborhood disadvantage group compared to the low neighborhood disadvantage group (median [IQR]: 0.39 [0.34, 0.45] vs. 0.54 median [IQR]: 0.54 [0.52, 0.57]; P < 0.001).

Conclusions: Interactions among the various stages of abnormal adiposity, dysglycemia, and hypertension with each other are weaker with increasing neighborhood disadvantage. Factors related to neighborhood-level disadvantage, other than abnormal adiposity, might play a crucial role in the development of dysglycemia and hypertension.

Keywords: Adiposity; Dysglycemia; Hypertension; Social determinants of health.