2024
DOI: 10.1186/s12916-024-03452-6
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Associations of neighborhood sociodemographic environment with mortality and circulating metabolites among low-income black and white adults living in the southeastern United States

Kui Deng,
Meng Xu,
Melis Sahinoz
et al.

Abstract: Background Residing in a disadvantaged neighborhood has been linked to increased mortality. However, the impact of residential segregation and social vulnerability on cause-specific mortality is understudied. Additionally, the circulating metabolic correlates of neighborhood sociodemographic environment remain unexplored. Therefore, we examined multiple neighborhood sociodemographic metrics, i.e., neighborhood deprivation index (NDI), residential segregation index (RSI), and social vulnerabilit… Show more

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“…Decreased eGFR, increased albuminuria, and living in an area with socioeconomic deprivation have been increasingly recognized for contributing to CVD incidence and mortality. [17][18][19][20][21] In response to this gap, a new CVD risk assessment tool, termed the Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) equations, was introduced by the AHA in 2023, aiming to assess total CVD risk more accurately, precisely, and equitably across diverse populations. 22 This new tool incorporates traditional risk factors and eGFR in the base model, offers additional predictors of renal (urine albumin-to-creatinine ratio), metabolic (HbA1c), and social (social deprivation index [SDI]) risk in the add-on models for enhancement, and captures total CVD events, including HF, which was not included in previous models.…”
Section: Introductionmentioning
confidence: 99%
“…Decreased eGFR, increased albuminuria, and living in an area with socioeconomic deprivation have been increasingly recognized for contributing to CVD incidence and mortality. [17][18][19][20][21] In response to this gap, a new CVD risk assessment tool, termed the Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) equations, was introduced by the AHA in 2023, aiming to assess total CVD risk more accurately, precisely, and equitably across diverse populations. 22 This new tool incorporates traditional risk factors and eGFR in the base model, offers additional predictors of renal (urine albumin-to-creatinine ratio), metabolic (HbA1c), and social (social deprivation index [SDI]) risk in the add-on models for enhancement, and captures total CVD events, including HF, which was not included in previous models.…”
Section: Introductionmentioning
confidence: 99%