Inflammation Marker hs-CRP Tied to Obesity in Nigerian Adults with Type 2 Diabetes

A new study from Southwest Nigeria has found that a single, routinely measurable blood marker of inflammation tracks more closely with obesity than two other well-known immune signaling molecules in people living with type 2 diabetes. The research, published as an open-access paper in BMC Endocrine Disorders, examined high-sensitivity C-reactive protein (hs-CRP), tumour necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6) in 151 Nigerian adults with type 2 diabetes and 100 age- and sex-matched healthy controls. Its central finding is deceptively simple: all three inflammatory markers were elevated in people with diabetes compared with healthy controls, but only hs-CRP and TNF-α remained independently associated with obesity once the researchers statistically accounted for age, sex, medication use, and asymptomatic malaria infection. When all three biomarkers were placed into the same statistical model, hs-CRP alone held its association with obesity, suggesting that this liver-derived protein may be the most faithful blood-based mirror of excess body fat in this population.

The significance of the work lies partly in where it was done. Most of what the scientific community knows about the inflammatory biology of obesity and type 2 diabetes comes from cohorts in North America, Europe, and East Asia. Evidence from sub-Saharan Africa has been sparse, and the studies that do exist often fail to adjust for factors that could confound the results, such as the medications patients take or the endemic infections they quietly carry. Asymptomatic malaria, which is common in parts of Nigeria, is a particularly important consideration because malaria parasites provoke immune activation and can raise inflammatory markers independently of body weight. By screening participants with rapid diagnostic tests for malaria and adjusting for the results, the researchers attempted to strip away one of the major sources of noise that has muddied earlier measurements in similar settings.

The study’s design was cross-sectional, meaning the researchers measured biomarkers, body measurements, and clinical characteristics at a single point in time rather than following participants over months or years. Participants with type 2 diabetes were recruited alongside healthy controls who were frequency-matched by age and sex, a technique that ensures the comparison group has a similar distribution of these demographic variables. Blood plasma concentrations of the three inflammatory markers were quantified using enzyme-linked immunosorbent assay, or ELISA, a laboratory technique that uses antibodies to capture and detect specific proteins, producing a measurable signal proportional to the amount of the target molecule in the sample. Obesity was defined using the conventional threshold of a body mass index of 30 kilograms per square meter or higher, and abdominal adiposity was assessed through waist circumference measurements.

The results were striking in their consistency. All three inflammatory markers were significantly higher in participants with type 2 diabetes than in the healthy controls, with p-values below 0.001, indicating that the differences were extremely unlikely to have arisen by chance. When the researchers examined how the biomarkers related to body measurements, hs-CRP showed the strongest correlations, with a Spearman rank correlation coefficient of 0.42 with body mass index and 0.38 with waist circumference, both statistically significant. Spearman correlation is a non-parametric measure that captures monotonic relationships between variables without assuming they follow a straight line, making it robust to the skewed distributions typical of inflammatory marker data, which often span orders of magnitude between individuals.

To move beyond simple correlations, the team built multivariable logistic regression models, a statistical framework used when the outcome of interest is binary, in this case whether a participant met the obesity threshold or not. Each model estimated an adjusted odds ratio, which expresses how the odds of obesity change for each unit increase in the biomarker while holding other variables constant. In models fully adjusted for age, sex, metformin use, statin use, and malaria rapid diagnostic test status, hs-CRP showed an adjusted odds ratio of 1.35 with a 95 percent confidence interval of 1.10 to 1.66, and TNF-α showed an adjusted odds ratio of 1.06 with a confidence interval of 1.01 to 1.12. IL-6, by contrast, did not reach statistical significance, with an adjusted odds ratio of 1.04 and a confidence interval spanning unity from 0.99 to 1.09. The confidence interval is the key detail: because it crosses 1.0, the data cannot rule out the possibility of no true association for IL-6.

The most informative analysis came when all three biomarkers competed against each other in a single model. In that head-to-head comparison, hs-CRP retained a significant association with obesity, with an adjusted odds ratio of 1.32 and a confidence interval of 1.08 to 1.62, while TNF-α and IL-6 both lost their independent associations. This pattern makes biological sense. IL-6 and TNF-α are short-lived signaling molecules released primarily by immune cells and adipose tissue, and their blood concentrations fluctuate rapidly, exhibit strong circadian variation, and are influenced by recent meals, stress, and transient infections. hs-CRP, produced by the liver largely in response to IL-6 signaling, is a downstream integrator of inflammatory activity. Because it is more stable in the bloodstream and can be measured with high-sensitivity assays at very low concentrations, it tends to provide a smoother, more reliable readout of chronic low-grade inflammation than the upstream cytokines themselves.

The researchers also took the important step of running sensitivity analyses using log-transformed biomarker concentrations. Inflammatory markers are notoriously right-skewed, with most people clustering at low values and a minority showing very high levels, and this skew can distort the estimates of linear statistical models. Log transformation compresses the upper tail of the distribution and renders the data closer to a normal shape, allowing the researchers to verify that their conclusions were not artifacts of the original scale of measurement. The sensitivity analyses yielded materially similar findings, which strengthens confidence that the association between hs-CRP and obesity is not a statistical fluke of how the data were handled.

Despite the robustness of the core finding, the authors are careful to flag the study’s limitations, and they are right to do so. The most consequential is the near-universal use of metformin among the participants with type 2 diabetes: 98 percent were taking the drug. Metformin is known to have anti-inflammatory effects and can influence both body weight and inflammatory marker levels, but with virtually every diabetic participant on the medication there was essentially no contrast in exposure, making it impossible to estimate the drug’s independent effect. Statin use, which also modulates inflammation, was adjusted for in the models, but residual confounding by medication dose, duration, and adherence cannot be excluded. The cross-sectional design imposes a further constraint: because biomarkers and obesity were measured simultaneously, the study cannot determine whether inflammation drives obesity, whether excess adipose tissue drives inflammation, or whether both arise from a shared underlying cause. Adipose tissue itself secretes IL-6 and TNF-α, so the most plausible reading is that greater fat mass fuels the inflammatory signal, but proving that requires longitudinal follow-up.

What the study does offer is a practical signal with real clinical potential. hs-CRP is inexpensive, widely available, and already measured in many clinical laboratories for cardiovascular risk assessment. If future prospective studies confirm that hs-CRP reliably identifies people with type 2 diabetes who carry obesity-related inflammatory burden, it could help clinicians target intensive weight management, closer monitoring, or anti-inflammatory interventions to the patients most likely to benefit. The authors explicitly note that establishing such clinical utility requires prospective research, and they resist overclaiming. Still, in a region where diabetes prevalence is rising sharply and research infrastructure for metabolic disease is limited, the study fills a genuine evidence gap. It demonstrates that the inflammation-obesity axis observed in wealthy countries is also detectable in Nigerian adults with type 2 diabetes, even after accounting for the infections and treatments that make this population distinct, and it points to a simple blood test as a potential window into the metabolic risks that excess body fat carries.

Subject of Research: Associations between inflammatory biomarkers and obesity in Nigerian adults with type 2 diabetes

Article Title: Associations of hs-CRP, TNF-α, and IL-6 with obesity in Nigerian adults with type 2 diabetes: a cross-sectional study

Article References: Nwaejigh, P. C., Ajigbotoluwa, T. A., Akinjinmi, A. A., Maduka, F. C., Osuji, T. G., Okelezo, M. E., Fatunmbi, O. J., & Udofia, S. S. (2026). Associations of hs-CRP, TNF-α, and IL-6 with obesity in Nigerian adults with type 2 diabetes: a cross-sectional study. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02547-w

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02547-w

Keywords: type 2 diabetes, obesity, inflammation, hs-CRP, TNF-alpha, interleukin-6, biomarkers, Nigeria, sub-Saharan Africa, cross-sectional study, metformin, asymptomatic malaria