Inflammatory Biomarkers as Indicators of Social Risk in Rural Health: Insights From Ecuador and the Philippine GIDA Experience

Dear Editor,

The recent article by Del Brutto et al, ¹ “High Social Risk and Biomarkers of Systemic Inflammation: A Population-Based Study in Middle-Aged and Older Adults Living in Rural Communities” was indeed interesting. The authors: Del Brutto, Rumbea, Arias, Arriaga and Mera provided compelling evidence that social risk, quantified through Gijon’s Social-Familial Evaluation Scale (SFES) is independently associated with systemic inflammation as measured by the Systemic Immune-Inflammation Index (SII) and the CRP/albumin ratio. The authors population-based and rigorous methodology offers critical understanding into the biologic embodiment of social adversity in rural settings, a concept gaining traction in global health equity frameworks. This letter aims to contextualize their findings within the health landscape of the Philippines, specifically its geographically isolated and disadvantaged areas (GIDAs), and to reason for the integration of inflammatory biomarkers in social risk surveillance systems for policy-directed interventions.

Decentralized and governed under a Universal Health Care (UHC), the country’s health system faces a critical challenge in remote and rural implementation. ² Over 30% of the nation’s municipalities are geographically isolated and disadvantaged areas. These low-resource settings are attributed by low health workforce density, environmental fragility, multidimensional poverty, and minimal access to preventive care. ³

Social determinants of health (SDH) in these areas often intersect and exacerbate one another. These include weak support networks, poor housing, food insecurity, and informal employment are common. ⁴ Like the Ecuadorian context described by Del Brutto et al, ¹ Filipino populations exhibit homogeneity in educational, socioeconomic, and ethnic conditions, making them ideal for systemic-level observational study.

Predominantly relevant to the Philippine GIDA context is the scholarly work’s reliance on the Gijon’s SFES, a multidimensional instrument incorporating 5 domains: support networks, social relationship, housing, economic conditions, and family situation. The Philippine Statistics Authority and the Department of Health (DOH) conducted local surveys that echo the utilization of this construct. For example, it was determined from a 2023 national health facility survey that 60% of GIDAs lacked community development workers, and only 24% had a functioning rural health unit (RHU) with both laboratory capacity and available physicians. ⁵ Moreover, health-seeking behavior and adult literacy were low while food insecurity remains principally high. ⁶

The findings of the study of Del Brutto et al ¹ can be translated to the Philippine context raising essential scientific and policy considerations. First, the connotation of social risk with elevated SII and CRP/albumin ratios points to chronic low-grade inflammation as a pathophysiologic response to structural deprivation. Inflammation is a known precursor to a range of noncommunicable diseases (NCDs) that disproportionately affect low-income rural populations, including hypertension, diabetes, and cerebrovascular disease. As such, biomarker-informed social diagnostics can act not only as indicators of inequity but also as predictors of future disease burden. This creates an opportunity for early detection, risk stratification, and localized interventions. ⁷

Second, the methodological framework of Del Brutto et al, ¹ cross-sectional population sampling, exclusion criteria based on comorbidities, and analytic modeling controlling for demographics and cardiovascular risk factors, presents a blueprint for implementation research in Philippine rural communities. Existing initiatives such as the Philippine Health Information Exchange (PHIE) and barangay-level health registries can be expanded to include low-cost inflammatory biomarker testing. The SII, derived from complete blood counts, and the CRP/albumin ratio, derived from basic chemistry panels, are technically feasible in district and provincial laboratories. ⁸

Importantly, these tools must be embedded in larger social diagnostics strategy. The study suggests that SDH not only predict adverse outcomes but may actively modulate immune function. This biologic embedding of social adversity calls for a shift from passive documentation of health inequities to biologically informed, real-time decision-making. For example, social risk scores could be triangulated with inflammatory biomarkers to guide differentiated models of care, ⁹ such as intensified case management, targeted conditional cash transfers, or mobile health deployments in high-burden barangays.

It is also worth noting that the observed associations remained significant in multivariate models adjusted for confounders such as age, education, and traditional cardiovascular risk factors. This suggests that the relationship between SDH and inflammation is robust and may be causally linked. While Del Brutto et al ¹ appropriately recognizes the limitation of cross-sectional design in establishing temporality, the biologic plausibility and prior longitudinal evidence from other cohorts provide strong grounds for prospective validation.

The findings further challenge traditional dichotomies in public health. In rural Philippine settings, the epidemiologic transition is ongoing, infectious diseases still coexist with rising NCDs, and health systems are stretched thin. ¹⁰ Conventional public health responses remain largely categorical, focused on vertical programs for TB, malaria, and maternal care, but miss the underlying systemic drivers of poor outcomes. ¹¹ The integration of biomarker-informed social diagnostics may provide a horizontal framework that cuts across disease silos and aligns with primary care transformation efforts.

Ethically, the use of inflammatory biomarkers for social risk surveillance must be guided by principles of justice and non-maleficence. ¹² Biomarker data must not be used to label or stigmatize communities but to prioritize and resource them. The Philippine UHC law provides for a service delivery network and a health promotion bureau capable of mobilizing resources to the most underserved areas. However, targeting remains a challenge due to the absence of reliable data that captures the intersection of biologic and social risk. ¹³ The work of Del Brutto et al ¹ offers a pathway to operationalize equity using objective, measurable, and actionable indicators.

In conclusion, the association between high social risk and systemic inflammation demonstrated in the Ecuadorian cohort resonates strongly with conditions prevalent in the Philippines’ GIDA communities. There is a pressing need for the Philippines to consider integrating biomarker-informed social risk assessment into its rural health information systems. Doing so could enhance the precision, relevance, and responsiveness of public health interventions and bring the promise of UHC closer to reality for the country’s most vulnerable populations.

Jomar L. AbanDon Mariano Marcos Memorial State University, Bacnotan, La Union, Philippines Email: [e-mail] Don Eliseo Lucero-Prisno IIILondon School of Hygiene and Tropical Medicine, UK Jerico Bautista OgayaFar Eastern University, Manila, PhilippinesUniversity of Makati, Philippines Christian Joseph N. OngDe La Salle University, Manila, Philippines