Haematological Inflammatory Indices and Cardiometabolic Risk Indicators in Young Apparently Healthy Adults in Port Harcourt, Nigeria: A Cross-Sectional Study with Limited Predictive Utility
Beauty Eruchi Echonwere-Uwikor
Department of Haematology and Blood Transfusion Science, Faculty of Medical Laboratory Science, Rivers State University, Nkpolu-Oroworukwo, Port Harcourt, Nigeria.
Erens Spiff Ekprikpo
*
Department of Haematology and Blood Transfusion Science, Faculty of Medical Laboratory Science, Rivers State University, Nkpolu-Oroworukwo, Port Harcourt, Nigeria.
Chiemeka Cynthia Ifunanya
Department of Medical Laboratory Science, Faculty of Medical Laboratory Science, Rivers State University, Nkpolu-Oroworukwo, Port Harcourt, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Background: Haematological inflammatory indices (NLR, PLR and SII) have been proposed as cardiometabolic risk markers, but data on young Africans are limited, and predictive claims are often overstated.
Aim: This study examined associations of the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammation index (SII) with cardiometabolic indicators and assessed the feasibility of composite-risk prediction.
Methods: This was a secondary analysis of de-identified data from 100 apparently healthy adults in Port Harcourt (ethical approval for secondary analysis: RSHMB/RSHREC/2026/120, dated 22 July 2026). NLR, PLR and SII were calculated from complete blood counts. Cardiometabolic indicators included BMI, waist circumference, WHR, SBP, DBP, fasting glucose, TC, TG, HDL-C and LDL-C. Risk-component burden was the count of harmonised components. Associations were assessed using Spearman’s ρ because of skewed indices. The feasibility of ROC analysis and logistic regression was assessed.
Results: No participant met the composite MetS proxy (0/99). Isolated abnormalities included elevated WHR (38.4%), abdominal obesity (22.2%) and elevated BP (20.0%). NLR showed a weak positive correlation with glucose (ρ=0.23, p=0.017) and a weak negative correlation with SBP (ρ=-0.20, p=0.048). PLR showed no significant correlations (ρ -0.15 to 0.15, all p>0.05). SII showed no significant correlations; the association with HDL-C was ρ=0.19, p=0.060. None of the indices correlated significantly with risk-component burden: NLR ρ=0.11 p=0.293, PLR ρ=-0.04 p=0.677, SII ρ=0.04 p=0.675. Binary prediction was not estimable because there were no cases.
Conclusions: In this young, low-risk cohort, NLR, PLR and SII showed limited associations with cardiometabolic indicators and did not track risk-component burden. The NLR–glucose association warrants replication. These indices should not be used as standalone predictors of composite risk in low-risk youth; they may serve as adjunct markers pending evaluation in larger, more diverse cohorts.
Keywords: Neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, systemic immune-inflammation index, cardiometabolic risk, blood pressure, fasting glucose