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Background <p>Social determinants of health (SDOH) and metabolic syndrome (MetS) are related, but their combined effect on mortality risk remains unclear.</p> Methods <p>We analyzed data from NHANES (National Health and Nutrition Examination Survey) cycles between 2005 and 2018. The composite SDOH score was calculated by summing the weighted scores for each SDOH, categorizing participants into four groups: Q1 (0–1), Q2 (2–3), Q3 (4) and Q4 (≥ 5). Kaplan-Meier survival curves and multivariate Cox proportional hazards models were used to examine the relationship between SDOH and mortality outcome. Restricted cubic spline (RCS) analyses were conducted to explore nonlinear relationships. Subgroup analyses assessed the consistency and robustness of the findings across various demographic and clinical factors.</p> Results <p>Of the 7,366 patients with MetS, 1,193 died, including 407 from cardiovascular and cerebrovascular diseases and 269 from cancer. Cox regression analyses, using fully adjusted Model 2, revealed that higher SDOH levels had increased hazards for all-cause mortality (HR = 2.41, 95% CI: 1.87,3.12), cancer-related death (HR = 2.45, 95% CI: 1.54,3.89), and Cardio − cerebrovascular disease (HR = 2.62, 95% CI: 1.79,3.84). Kaplan-Meier analyses further supported these findings, demonstrating that participants with higher SDOH scores had lower survival rates. Additionally, RCS modeling confirmed a linear relationship between SDOH and mortality, with no indication of a nonlinear relationship (P for nonlinear &gt; 0.05).</p> Conclusion <p>Our findings indicate that adverse social determinants of health are strongly linked to an increased risk of all-cause mortality in individuals with MetS. However, due to the observational and cross-sectional nature of this study, it is important to interpret these results as associations rather than implying any causal relationships.</p>

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Association between social determinants of health with the all-cause and cause-specific (cancer and cardio-cerebrovascular) mortality among the population with metabolic syndrome: NHANES 2005–2018

  • 期刊论文

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  • 发表日期：

    2025年4月23日

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  • Xiaohan Ma,
  • Sheng Chen,
  • Lin Guo,
  • Shuaikang Wang,
  • Junchao Wu,
  • Lingling Wu,
  • Ting Zhang,
  • Hongjun Gao,
  • Encun Hou

摘要

Background

Social determinants of health (SDOH) and metabolic syndrome (MetS) are related, but their combined effect on mortality risk remains unclear.

Methods

We analyzed data from NHANES (National Health and Nutrition Examination Survey) cycles between 2005 and 2018. The composite SDOH score was calculated by summing the weighted scores for each SDOH, categorizing participants into four groups: Q1 (0–1), Q2 (2–3), Q3 (4) and Q4 (≥ 5). Kaplan-Meier survival curves and multivariate Cox proportional hazards models were used to examine the relationship between SDOH and mortality outcome. Restricted cubic spline (RCS) analyses were conducted to explore nonlinear relationships. Subgroup analyses assessed the consistency and robustness of the findings across various demographic and clinical factors.

Results

Of the 7,366 patients with MetS, 1,193 died, including 407 from cardiovascular and cerebrovascular diseases and 269 from cancer. Cox regression analyses, using fully adjusted Model 2, revealed that higher SDOH levels had increased hazards for all-cause mortality (HR = 2.41, 95% CI: 1.87,3.12), cancer-related death (HR = 2.45, 95% CI: 1.54,3.89), and Cardio − cerebrovascular disease (HR = 2.62, 95% CI: 1.79,3.84). Kaplan-Meier analyses further supported these findings, demonstrating that participants with higher SDOH scores had lower survival rates. Additionally, RCS modeling confirmed a linear relationship between SDOH and mortality, with no indication of a nonlinear relationship (P for nonlinear > 0.05).

Conclusion

Our findings indicate that adverse social determinants of health are strongly linked to an increased risk of all-cause mortality in individuals with MetS. However, due to the observational and cross-sectional nature of this study, it is important to interpret these results as associations rather than implying any causal relationships.