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  • Health Disparities and Chronic Disease in Texas: Intersections of Biological Vulnerability and Social Determinants of Health

  • Department of Natural Sciences and Mathematics, Richardson, TX.

Abstract

Chronic diseases, including cardiovascular disease, type 2 diabetes, and neurodegeneration, are traditionally treated as isolated clinical entities. However, mounting evidence suggests they arise from a shared physiological foundation of persistent low-grade inflammation, insulin resistance, and oxidative stress. This review examines these interconnected biological pathways and evaluates how they are shaped by structural determinants such as healthcare access and socioeconomic stress. Using Texas as a primary case study, a state with disproportionately high rates of metabolic dysfunction and significant rural-urban healthcare disparities, this paper argues for a network-based understanding of chronic illness. By shifting clinical focus from treating isolated "downstream" organ failures to interrupting "upstream" systemic dysregulation, we can support earlier intervention and more equitable prevention strategies

Keywords

Metaflammation, Insulin Resistance, Texas Public Health, Systems Medicine, SGLT2 Inhibitors, Health Disparities

Introduction

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In the United States, approximately 6 in 10 adults live with at least one chronic condition, and 4 in 10 live with two or more. Chronic diseases remain the leading cause of mortality and healthcare expenditure in the United States. According to the Centers for Disease Control and Prevention (CDC), cardiovascular disease alone accounts for approximately 695,000 deaths annually, representing nearly one in every five deaths nationwide. Type 2 diabetes affects more than 37 million Americans, with an additional 96 million adults classified as having prediabetes. These conditions frequently coexist with obesity, hypertension, and dyslipidemia, forming a cluster of metabolic disorders that share common pathophysiological pathways including chronic inflammation, insulin resistance, and endothelial dysfunction. Unlike acute crises, chronic diseases develop over years through identifiable risk pathways: prolonged metabolic stress, persistent inflammation, and dietary imbalance. Modern medicine is traditionally organized by organ systems; however, specialization often fragments our understanding. Increasingly, research suggests that chronic diseases are not separate conditions but interconnected manifestations of systemic metabolic and inflammatory imbalance. The interconnected biological mechanisms underlying chronic disease are illustrated in Figure 1.

 

 

 

Figure 1. (Systems-Level Mechanisms of Chronic Disease)

 

Chronic diseases develop through interconnected biological mechanisms including inflammation, insulin resistance, oxidative stress, and endothelial dysfunction.

BIOLOGICAL COMMON GROUND

At the core of the chronic disease network is Adipose Tissue, which has transitioned from a passive energy reservoir to a dynamic endocrine organ. In states of excess adiposity, hypertrophied adipocytes release pro-inflammatory cytokines (TNF-α, IL-6) and free fatty acids, triggering a cascade of systemic failure. The Adipose Tissue and Metaflammation underlying chronic disease are illustrated in Figure 2.

 

 

 

 

Figure 2. (Adipose Tissue and Metaflammation)

 

Adipose tissue contributes to chronic metabolic inflammation through secretion of pro-inflammatory cytokines such as TNF-α and IL-6.

 

 

 

Table 1. (Systemic Manifestations of Shared Pathological Mechanisms)

Mechanism

Cardiovascular (CVD)

Metabolic (T2DM)

Renal (CKD)

Neurological (AD)

Inflammation

Plaque & foam cell formation

Macrophage recruitment

Renal fibrosis

Neuroinflammation

Insulin Resistance

Reduced NO production

Impaired GLUT4 translocation

Podocyte injury

Impaired synaptic plasticity

Oxidative Stress

LDL oxidation

β-cell apoptosis

Glomerular injury

Mitochondrial DNA damage

Vascular Impact

Endothelial dysfunction

Retinopathy

Hyperfiltration

BBB permeability

 

THE METABOLIC-VASCULAR AXIS

Type 2 Diabetes (T2DM) and Cardiovascular Disease (CVD) represent the most significant endpoints of this systemic imbalance (pp. 12, 19). Chronic hyperglycemia accelerates atherosclerosis by promoting LDL oxidation and enhancing inflammatory signaling. Conversely, insulin resistance in the vascular endothelium impairs vasodilation, leading to hypertension and arterial stiffening. This bidirectional relationship explains why individuals with T2DM face substantially elevated cardiovascular risk. The Interaction between Type 2 Diabetes and Cardiovascular Disease Development underlying chronic disease is illustrated in Figure 3.

 

 

 

Figure 3. (Interaction between Type 2 Diabetes and Cardiovascular Disease Development)

 

Persistent hyperglycemia accelerates endothelial dysfunction and promotes atherosclerotic plaque formation.

RENAL AND NEUROLOGICAL CONSEQUENCES

The kidneys and the brain are highly sensitive to the "slow burn" of metabolic stress:

  • Diabetic Nephropathy: Chronic hyperglycemia and hypertension generate reactive oxygen species (ROS) that damage the delicate filtration units (nephrons).
  • The "Type 3 Diabetes" Hypothesis: Emerging research identifies impaired insulin signaling within the brain as a driver of Alzheimer’s disease. Insulin resistance in neuronal tissue mirrors peripheral metabolic dysfunction, leading to decreased mitochondrial efficiency and cognitive decline.

The Metabolic Effects on Kidney and Brain underlying chronic disease are illustrated in Figure 4.

 

 

 

Figure 4. (Metabolic Effects on Kidney and Brain)

 

Chronic metabolic dysregulation contributes to organ damage, including diabetic nephropathy and neurodegenerative changes.

STRUCTURAL DETERMINANTS

Texas serves as a critical case study for how biological vulnerability meets structural inequity. Obesity rates in many Texas counties exceed 35-40%. Texas demonstrates some of the most pronounced chronic disease disparities in the United States. Approximately 14–15% of adults in Texas have diagnosed diabetes, a prevalence higher than the national average. Obesity affects roughly one in three adults, and in several rural counties the prevalence exceeds 40%. Cardiovascular disease remains the leading cause of death in the state, accounting for nearly 25% of all mortality. Rural communities face additional barriers including limited access to preventive care, longer travel distances to specialty clinics, and reduced availability of dialysis centers and cardiovascular specialists. These structural barriers amplify biological vulnerability and contribute to delayed diagnosis and poorer clinical outcomes.

These biological processes are shaped by:

  • Healthcare Access: Texas reports one of the highest uninsured rates in the country, delaying diagnosis until late-stage complications emerge.
  • Specialty Deserts: Rural counties face severe shortages of endocrinologists and pulmonologists, creating barriers to life-sustaining treatments like dialysis.
  • Environmental Exposure: Urban air pollution in Houston and Dallas-Fort Worth exacerbates respiratory and vascular inflammation, contributing to elevated COPD and CVD risk.

The Social Determinants of Health and Chronic Disease are illustrated in Figure 5.

 

 

 

Figure 5. (Social Determinants of Health and Chronic Disease)

 

Social determinants such as healthcare access, environmental exposure, and food insecurity play an important role in chronic disease risk.

Chronic disease disparities in Texas highlight the importance of addressing both biological and structural determinants simultaneously. Public health interventions that combine community-based prevention, improved healthcare access, and environmental health initiatives may significantly reduce disease burden. Expanding telemedicine services in rural regions, improving nutritional access in food deserts, and strengthening preventive screening programs can facilitate earlier diagnosis and intervention. Such strategies demonstrate how systemic approaches to health policy can complement biological therapies in reducing chronic disease risk.

 

Table 2. (Key Risk Factors Driving Chronic Disease)

Risk Factor

Biological Mechanism

Associated Diseases

Obesity

Adipose inflammation, cytokine release

T2DM, CVD, CKD

Insulin resistance

Impaired glucose uptake, endothelial dysfunction

Diabetes, hypertension

Oxidative stress

ROS generation, mitochondrial damage

Atherosclerosis, neurodegeneration

Sedentary lifestyle

Reduced metabolic efficiency

Obesity, diabetes

Poor diet

Dyslipidemia and systemic inflammation

CVD, metabolic syndrome

 

EMERGING THERAPIES

Recent pharmacological advancements have shifted the focus from treating isolated endpoints to interrupting upstream processes. SGLT2 inhibitors and GLP-1 receptor agonists have demonstrated cardioprotective and renal-protective benefits that extend far beyond simple glucose control. These "pleiotropic" drugs treat the body as an interconnected system, addressing inflammation and metabolic strain simultaneously.

The systemic benefits of these treatments have been shown by extensive clinical trials. The SGLT2 inhibitor empagliflozin dramatically decreased cardiovascular mortality by almost 38% in individuals with type 2 diabetes and existing cardiovascular disease, according to the EMPA-REG OUTCOME trial. Similarly, serious adverse cardiovascular events, such as myocardial infarction and stroke, have been shown to be reduced by GLP-1 receptor agonists such semaglutide and liraglutide. These drugs support the idea that managing chronic diseases should focus on upstream metabolic dysfunction rather than discrete organ damage by lowering systemic inflammation, enhancing endothelial function, and encouraging weight loss in addition to glycemic control.

  1. Future Directions in Systems Medicine

Advances in systems biology and precision medicine are reshaping the approach to chronic disease prevention and management. Rather than focusing solely on downstream organ damage, emerging strategies emphasize early identification of metabolic dysregulation through integrated biomarkers, genetic risk profiling, and digital health monitoring. Multi-omics technologies, including genomics, metabolomics, and proteomics, allow clinicians to identify patterns of inflammation, oxidative stress, and insulin resistance before clinical disease manifests.

Artificial intelligence and predictive analytics are also increasingly used to identify high-risk populations and guide personalized interventions. In states such as Texas, where structural disparities contribute to delayed diagnosis and treatment, integrating systems medicine with population-level prevention strategies may help reduce long-term disease burden. By combining early detection, targeted therapeutics, and improved access to preventive care, healthcare systems can transition from reactive treatment to proactive disease prevention.

  1. Limitations

While this review synthesizes current evidence on shared biological mechanisms linking chronic diseases, several limitations should be acknowledged. First, the article primarily relies on published epidemiological and clinical literature rather than primary experimental data. Second, although Texas is used as a representative case study for structural health disparities, regional variability exists within the state and across the United States. Finally, the rapidly evolving landscape of metabolic therapeutics and systems medicine means that future research may further refine our understanding of these interconnected pathways.

 

Table 3 (Chronic Disease Burden in the United States and Texas)

Condition

United States Prevalence

Texas Estimate

Diabetes

37 million adults

3 million adults

Prediabetes

96 million adults

8–9 million adults

Obesity

42% adults

34–38% adults

Cardiovascular Disease

Leading cause of death

Leading cause of death

 

CONCLUSION

The rising prevalence of chronic disease in the United States demands a transition from reactive, organ-specific care to a network-based "systems medicine" approach. The growing burden of chronic disease requires a paradigm shift from reactive treatment toward proactive prevention. Integrating systems medicine with public health strategies can address both the biological roots of disease and the structural inequities that amplify health disparities. By targeting shared metabolic pathways and improving early access to care, healthcare systems can move toward a more equitable and sustainable model of chronic disease prevention.

ACKNOWLEDGEMENTS

The author would like to acknowledge the researchers, clinicians, and public health professionals whose work on chronic disease prevention, management, and treatment provided the foundation for this study. Their contributions to medical science and patient care have advanced our understanding of the complex challenges posed by chronic illnesses.

The author is grateful to their mentor who fostered an interest in scientific inquiry and evidence-based medicine. Appreciation is also extended to family and friends for their encouragement and support throughout the research and writing process.

This research was conducted independently and received no external funding. The author declares no conflicts of interest.

REFERENCES

  1. The Alzheimer's Association (2023). Alzheimer's disease statistics for 2023. 19(4), 1598–1695, Alzheimer's & Dementia. https://doi.org/10.1002/alz.13016
  2. American Diabetes Association, 2023. Diabetes diagnosis and classification: Diabetes care standards, 2023. Diabetes Care, 46 (Supplement_1), S19–S40. This link: https://doi.org/10.2337/dc23-S002
  3. American Diabetes Association, 2023. Risk management and cardiovascular disease: Diabetes care standards, 2023. S158–S190 in Diabetes Care, 46 (Supplement_1). https://doi.org/10.2337/dc23-S010
  4. Alonso, A., Muntner, P., Benjamin, E. J., et al. (2023). Statistics on heart disease and stroke as of 2023. Circulation, 147(8), e93–e621. https://doi.org/10.1161/CIR.000000000001123
  5. Disease Control and Prevention Centers. (2023). report on national diabetes data. Department of Health and Human Services, United States.
  6. Centers for Disease Control and Prevention: https://www.cdc.gov/copd. (2023).
  7. chronic renal disease in the US. https://www.cdc.gov/kidney disease.
  8. The IDF Diabetes Atlas provides estimates of the prevalence of diabetes worldwide. 271–281 in Diabetes Research and Clinical Practice, 138. Cho, N. H., Shaw, J. E., Karuranga, S., et al. (2018).
  9. Environmental Protection Agency, https://doi.org/10.1016/j.diabres.2018.02.023 (2023).
  10. pollution caused by particulate particles (PM). Feeding Texas, https://www.epa.gov/pm-pollution (2023).
  11. Food instability and hunger in Texas. The URL is https://www.feedingtexas.org
  12. Global burden of hypertension and cardiovascular disease Liu, P., Roth, G. A., Forouzanfar, M. H., et al. (2017). 37–55 in The Lancet, 389 (10064). https://doi.org/10.1016/S0140-6736(16)30385-9
  13. GrundIn y, S. M., Cleeman, J. I., Brewer, H. B., et al. (2004). The metabolic syndrome definition. Circulation, 109(3), 433-438. https://doi.org/10.1161/01.CIR.0000111245.75752.C6
  14. Ogden, C. L., Fryar, C. D., Hales, C. M., and Carroll, M. D. (2020). obesity prevalence in the US. NCHS Data Brief, 360, 1–8.
  15. G. S. Hotamisligil (2017). immunometabolic diseases, inflammation, and metaflammation. Nature, 542 (7640), 177–185. https://doi.org/10.1038/nature21363
  16. Improving Global Outcomes for Kidney Disease (KDIGO). (2022). The KDIGO 2022 clinical practice guideline for managing diabetes in patients with chronic renal disease. S1–S127 in Kidney International, 102(4S).
  17. P. Libby (2021). The atherosclerosis landscape is evolving. Nature, 592 (7855), 524-533. Loyd: https://doi.org/10.1038/s41586-021-03392-8
  18. Ndumele, C. E., Braun, L. T., Jones, D. M., et al. (2019). utilizing risk assessment instruments to inform choices. Circulation, 139(25), e1162–e1177.
  19. Diabetes and Digestive and Kidney Diseases National Institute. (2023). Statistics on obesity and overweight. https://www.niddk.nih.gov National Aging Institute. (2023). Fact sheet on Alzheimer's illness. https://www.nia.nih.gov Ogden, Martin, C. B., Fryar, C. D., C. L., et al. (2020). American obesity prevalence trends. JAMA, 324(12), 1208–1210.
  20. Mensah, G. A., Johnson, C. O., Roth, G. A., et al. (2020). cardiovascular disease burden worldwide. American College of Cardiology Journal, 76(25), 2982-3021.
  21. Dixon, J., Egger, G., and Dixon, M. (2022). A unifying idea in the pathophysiology of chronic diseases is metaflammation. Environmental Research and Public Health International Journal, 19(8), 4786

Reference

  1. The Alzheimer's Association (2023). Alzheimer's disease statistics for 2023. 19(4), 1598–1695, Alzheimer's & Dementia. https://doi.org/10.1002/alz.13016
  2. American Diabetes Association, 2023. Diabetes diagnosis and classification: Diabetes care standards, 2023. Diabetes Care, 46 (Supplement_1), S19–S40. This link: https://doi.org/10.2337/dc23-S002
  3. American Diabetes Association, 2023. Risk management and cardiovascular disease: Diabetes care standards, 2023. S158–S190 in Diabetes Care, 46 (Supplement_1). https://doi.org/10.2337/dc23-S010
  4. Alonso, A., Muntner, P., Benjamin, E. J., et al. (2023). Statistics on heart disease and stroke as of 2023. Circulation, 147(8), e93–e621. https://doi.org/10.1161/CIR.000000000001123
  5. Disease Control and Prevention Centers. (2023). report on national diabetes data. Department of Health and Human Services, United States.
  6. Centers for Disease Control and Prevention: https://www.cdc.gov/copd. (2023).
  7. chronic renal disease in the US. https://www.cdc.gov/kidney disease.
  8. The IDF Diabetes Atlas provides estimates of the prevalence of diabetes worldwide. 271–281 in Diabetes Research and Clinical Practice, 138. Cho, N. H., Shaw, J. E., Karuranga, S., et al. (2018).
  9. Environmental Protection Agency, https://doi.org/10.1016/j.diabres.2018.02.023 (2023).
  10. pollution caused by particulate particles (PM). Feeding Texas, https://www.epa.gov/pm-pollution (2023).
  11. Food instability and hunger in Texas. The URL is https://www.feedingtexas.org
  12. Global burden of hypertension and cardiovascular disease Liu, P., Roth, G. A., Forouzanfar, M. H., et al. (2017). 37–55 in The Lancet, 389 (10064). https://doi.org/10.1016/S0140-6736(16)30385-9
  13. GrundIn y, S. M., Cleeman, J. I., Brewer, H. B., et al. (2004). The metabolic syndrome definition. Circulation, 109(3), 433-438. https://doi.org/10.1161/01.CIR.0000111245.75752.C6
  14. Ogden, C. L., Fryar, C. D., Hales, C. M., and Carroll, M. D. (2020). obesity prevalence in the US. NCHS Data Brief, 360, 1–8.
  15. G. S. Hotamisligil (2017). immunometabolic diseases, inflammation, and metaflammation. Nature, 542 (7640), 177–185. https://doi.org/10.1038/nature21363
  16. Improving Global Outcomes for Kidney Disease (KDIGO). (2022). The KDIGO 2022 clinical practice guideline for managing diabetes in patients with chronic renal disease. S1–S127 in Kidney International, 102(4S).
  17. P. Libby (2021). The atherosclerosis landscape is evolving. Nature, 592 (7855), 524-533. Loyd: https://doi.org/10.1038/s41586-021-03392-8
  18. Ndumele, C. E., Braun, L. T., Jones, D. M., et al. (2019). utilizing risk assessment instruments to inform choices. Circulation, 139(25), e1162–e1177.
  19. Diabetes and Digestive and Kidney Diseases National Institute. (2023). Statistics on obesity and overweight. https://www.niddk.nih.gov National Aging Institute. (2023). Fact sheet on Alzheimer's illness. https://www.nia.nih.gov Ogden, Martin, C. B., Fryar, C. D., C. L., et al. (2020). American obesity prevalence trends. JAMA, 324(12), 1208–1210.
  20. Mensah, G. A., Johnson, C. O., Roth, G. A., et al. (2020). cardiovascular disease burden worldwide. American College of Cardiology Journal, 76(25), 2982-3021.
  21. Dixon, J., Egger, G., and Dixon, M. (2022). A unifying idea in the pathophysiology of chronic diseases is metaflammation. Environmental Research and Public Health International Journal, 19(8), 4786

Photo
Sahithi Uyyala
Corresponding author

Department of Natural Sciences and Mathematics, Richardson, TX

Photo
Kiran Panuganti
Co-author

Department of Natural Sciences and Mathematics, Richardson, TX.

Sahithi Uyyala, Kiran Panuganti, Health Disparities and Chronic Disease in Texas: Intersections of Biological Vulnerability and Social Determinants of Health, Int. J. of Pharm. Sci., 2026, Vol 4, Issue 7, 5613-5620, https://doi.org/10.5281/zenodo.21672917

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