Type 2 diabetes mellitus (T2DM) is a significant and growing public health issue worldwide, which is defined by elevated blood sugar, insulin resistance, gradual β-cell failure, and disturbances in glucose and lipid metabolism.[1] Diabetes has become a significant public health problem in recent decades and has profound implications for cardiovascular disease, renal dysfunction, neuropathy, and premature death.[2] The 11th edition of the International Diabetes Federation (IDF) Diabetes Atlas estimated that, in 2024, there were 589 million adults aged 20-79 years with diabetes, which represents about 1 in every 9 adults in the world.[3] This number is projected to increase to 853 million by 2050.[3] In 2024, there were also around 3.4 million diabetes-related deaths, and global diabetes-related healthcare expenditure was over US$1 trillion.[4]

This burden is particularly alarming for low- and middle-income countries, where around 75% of adults with diabetes live.[5] The Middle East and North Africa (MENA) region has one of the highest diabetes burdens globally, with an estimated 85 million adults living with diabetes in 2024, and the number is projected to reach 163 million by 2050.[6] The burden is particularly high in Pakistan. According to the latest estimates from the IDF, in 2024 there were about 34.5 million adult residents in Pakistan who had diabetes, which translates to a 31.4% prevalence rate, making Pakistan one of the highest-ranked countries worldwide for adult diabetes prevalence.[7]

In addition to a diabetes diagnosis, glycemic control is also an important factor in the progression and long-term complications of diabetes. Even with improved pharmacologic therapy and diabetes monitoring, a considerable percentage of people with diabetes fail to meet recommended glycemic goals.[8] Most importantly, poor glycemic control is not just evidenced by raised glucose or HbA1c, but is strongly associated with oxidative stress, endothelial dysfunction, chronic low-grade inflammation, and dysfunction of lipid and metabolic pathways.[9] These processes can cause microvascular and macrovascular complications. Furthermore, the high percentage of individuals with diabetes who are undiagnosed or under poor control underscores the importance of more effective identification of biological processes that are related to poor glycemic control.[10] In 2024, about 251.7 million adults with diabetes were estimated to be undiagnosed in the world, accounting for 42.8% of the adult population with diabetes.[11]

Inflammation has increasingly been recognized as an important component of T2DM pathophysiology.[12] High blood sugar and insulin resistance can lead to increased activation of inflammatory pathways and changes in levels of inflammatory mediators in the blood.[12] Blood markers like C-Reactive Protein (CRP), Interleukin-6 (IL-6), and Tumor Necrosis Factor-alpha (TNF-α ) can be indicators of the inflammatory status in the whole body that accompanies metabolic dysfunction.[13] Complementary information on glycemic state, insulin resistance, and metabolic homeostasis can be obtained from metabolic biomarkers such as fasting blood glucose, HbA1c, fasting insulin, lipid parameters, and adipokines like adiponectin at the same time.[14] Importantly, these biomarkers may not respond to glycemic control in a consistent manner, and the relative relationship between the two, as well as between adequate and inadequate glycemic control, might offer clues beyond just glucose control.[14]

This difference between controlled and uncontrolled T2DM is therefore clinically relevant as patients with apparently similar duration and/or treatment history may have very different inflammatory and metabolic profiles. The discovery of biomarker patterns linked to poor glycemic control would have a number of advantages, including better risk stratification, earlier identification of patients who are at greater risk for developing diabetes-related complications, and the identification of potential new targets for more personalized diabetes treatment. The simultaneous comparison of inflammatory and metabolic biomarkers between controlled and uncontrolled T2DM, however, remains inconsistent for the same reason, especially in South Asian populations, where the burden of diabetes is very high. The results suggest that a more comprehensive assessment of diabetes should go beyond the use of only HbA1c and consider inflammatory activation and metabolic disturbance, which differ depending on glycemic control. Therefore, the present study aimed to compare selected inflammatory and metabolic biomarkers between patients with controlled and uncontrolled T2DM and to determine the association of these biomarkers with glycemic control.

An analytical cross-sectional study was conducted at the Department of Medicine, Bacha Khan Medical Complex, Swabi, over a period of six months, from 1 October 2025 to 31 March 2026.

A sample size was calculated using OpenEpi for comparing two independent means. In a previous cross-sectional study of T2DM patients, the mean level of high-sensitivity C-reactive protein (hs-CRP) was found to be 4.86 ± 2.37 mg/L in patients with uncontrolled diabetes and 2.63 ± 0.43 mg/L in those with controlled diabetes.[15] Based on these parameters, the total sample size was determined to be around 11 participants per group, including 22 participants in total, with a 95% confidence level and 80% statistical power. The sample size was conservatively increased to 100, including 50 controlled and 50 uncontrolled T2DM, as the calculated effect size was large and may lead to an unrealistically small sample size for a clinical study using a biomarker,

A non-probability consecutive sampling technique was used. Patients of either sex, aged 18 years or older, were included who had a documented diagnosis of T2DM for at least 6 months. Eligibility included patients receiving routine antidiabetic treatment who had their HbA1c and biochemical parameters inside the study period. Patients were classified as controlled T2DM (HbA1c<7%) and uncontrolled T2DM (HbA1c ≥7%) based on the standard clinical glycemic-control ranges. A few were excluded due to the possibility of having an acute or chronic inflammatory or metabolic status that could independently influence inflammatory or metabolic markers, including patients with type 1 diabetes mellitus, gestational diabetes, acute infections, chronic inflammatory or autoimmune diseases, active malignancy, chronic liver disease, advanced renal disease, recent surgery or trauma, or acute cardiovascular or cerebrovascular events. Patients taking systemic steroids or other drugs that have a significant effect on inflammatory markers were also excluded. Pregnant women and patients who were unable to provide informed consent were excluded.

After obtaining ethical approval from the relevant institutional review committee, eligible participants were approached and informed about the purpose and procedures of the study. Informed consent was obtained in writing prior to enrollment. A proforma for structured data collection was used to document demographic data, diabetes duration, treatment history, smoking, blood pressure, anthropometric data, and pertinent comorbidities. Body mass index (BMI) was determined as weight (kg)/height (m2).

Venous blood samples were taken after an overnight fast of about 8-12 hours in an aseptic manner. Fasting blood glucose, HbA1c levels, lipid profile, hs-CRP and other inflammatory and metabolic biomarkers included in the study protocol were measured in samples using standard laboratory methods. Complete blood count parameters were also noted if available, and inflammatory indicators were computed as the neutrophil-to-lymphocyte ratio (NLR) and the monocyte-to-lymphocyte ratio (MLR) using absolute neutrophil, lymphocyte, and monocyte counts. The main exposure was glycemic-control status based on HbA1c, and the main outcomes were the levels of inflammatory and metabolic biomarkers.

All data collected were entered, coded, and analyzed with IBM SPSS Statistics 26. Continuous variables were initially assessed for normality using the Shapiro–Wilk test. Data of normally distributed variables were presented as mean ± standard deviation; categorical variables were presented as frequencies and percentages. An independent-samples t-test was used to compare the controlled and uncontrolled diabetes groups with respect to continuous variables with normal distribution. The chi-square test was used to compare categorical variables. Multivariable logistic regression analysis was used to determine which biomarkers were independently associated with uncontrolled diabetes after controlling for other potential variables such as age, sex, BMI, diabetes duration, and pertinent comorbidities. Odds ratios with 95% confidence intervals were reported for effect estimates. A p-value of <0.05 was considered statistically significant.

In total, 100 patients with T2DM were included, of whom 50 patients had controlled diabetes, while the remaining 50 had uncontrolled diabetes. Demographic characteristics of the two groups were similar in overall demographic aspects, family history of diabetes, hypertension, and smoking status. In the meanwhile, uncontrolled patients had higher BMI, longer diabetes duration, and a higher rate of dyslipidemia. (Table 1)

Patients with uncontrolled T2DM had a significantly worse metabolic profile as assessed by glycemic and metabolic parameters. The fasting glucose, fasting insulin, HbA1c, HOMA-IR, total cholesterol, LDL-C and triglycerides were significantly elevated in the uncontrolled group, while HDL-C was significantly reduced. (Table 2)

Patients with uncontrolled diabetes also had significantly more systemic inflammatory activity, measured by inflammatory assessment, than patients with controlled diabetes (hs-CRP, IL-6, TNF-α, neutrophil count, monocyte count, NLR, and MLR). (Table 3)

The levels of abnormal metabolic and inflammatory markers were also significantly higher between uncontrolled T2DM and controlled T2DM. The differences in insulin resistance, hypertriglyceridemia, elevated hs-CRP, IL-6, TNF-α, NLR, and MLR were particularly marked. (Table 4)

HbA1c showed a significant positive correlation with fasting glucose, fasting insulin, HOMA-IR, total cholesterol, LDL-C, triglycerides, hs-CRP, IL-6, TNF-α, NLR, MLR, and inverse correlation with HDL-C (Table 5).

In the multivariable analysis, longer diabetes duration, dyslipidemia, insulin resistance, elevated hs-CRP, IL-6, TNF-α, NLR and triglycerides remained independently associated with uncontrolled diabetes after adjustment for potential confounding variables. (Table 6)

Table 1. Sociodemographic and Clinical Characteristics of Patients with Controlled and Uncontrolled T2DM

Table 2. Glycemic and Metabolic Biomarkers in Controlled and Uncontrolled T2DM

Table 3. Inflammatory Biomarkers in Controlled and Uncontrolled T2DM

Table 4. Distribution of Metabolic and Inflammatory Biomarker Abnormalities

Table 5. Correlation of HbA1c with Inflammatory and Metabolic Biomarkers

Table 6. Multivariable Logistic Regression Analysis of Factors Associated with Uncontrolled T2DM

The present study demonstrated clear differences in inflammatory and metabolic profiles between patients with controlled and uncontrolled T2DM. Patients with uncontrolled diabetes had significantly higher BMI, longer duration of diabetes, fasting blood glucose, HbA1c, fasting insulin, HOMA-IR, total cholesterol, LDL-C, and triglycerides, while HDL-C was significantly lower.

Likewise, hs-CRP, IL-6, and TNF-α, neutrophil count, monocyte count, NLR, and MLR were found to be significantly increased in the uncontrolled group. The results of these studies substantiate the notion that poor glycemic control is associated with insulin resistance in addition to chronic hyper-glycemia and systemic low-grade inflammation, as well as atherogenic dyslipidaemia.

The difference in glycemic parameters between the two groups was predicted and clinically significant. The mean fasting blood glucose levels were 181.4 ± 42.6 mg/dL in the uncontrolled group and 119.6 ± 17.8 mg/dL in the controlled group (both p<0.001), and mean HbA1C levels were 9.1 ± 1.6% in the uncontrolled group and 6.3 ± 0.4% in the controlled group (both p<0.001). This result corroborates the study conducted by Imran et al. (2021), which showed a significant positive correlation of hs-CRP with HbA1c as well as FPG levels among T2DM patients in Pakistan, thus suggesting a close relationship between chronic hyperglycemia and systemic inflammation.[16]  Recently, another study in India published in 2024 also found that fasting glucose and HbA1C levels were significantly higher, and that diabetic patients had significantly higher levels of IL-6 and TNF-α than prediabetic patients. TNF-α also demonstrated a significant correlation with HbA1c.[17]

The higher insulin and HOMA-IR values observed in our uncontrolled group further suggested greater insulin resistance among patients with poor glycemic control. HOMA-IR was 7.1 ± 3.8 in uncontrolled patients compared with 3.3 ± 1.5 in controlled patients (p<0.001). This result has biological significance as chronic hyperglycemia and excessive adiposity may lead to

inflammatory changes in adipose tissue, oxidative stress, and increased production of cytokines that, in turn, would disrupt insulin signaling. In a study of 405 patients with T2DM conducted in 2024, inflammatory patterns were clearly separated based on insulin-resistance status, and the study focused on how NLR, MLR, and PLR are associated with HOMA-IR, further strengthening the link between systemic inflammation and insulin resistance.[18] A recent 2026 study similarly reported significantly elevated TNF-α and IL-6 among patients with T2DM and demonstrated associations between these inflammatory mediators, HbA1c, and HOMA-IR.[19]

One of the most significant results of this study was the markedly elevated level of CRP in diabetes that was not under control. The mean hs-CRP was higher in uncontrolled patients (5.1 ± 2.8 mg/L) than in controlled (2.7 ± 1.4 mg/L) patients (p<0.001), and 74% of all uncontrolled patients had hs-CRP >3 mg/L, compared with 36% of all controlled patients. This is corroborated by Al-Rawaf et al., 2021, who found significantly higher levels of CRP in poorly controlled T2DM and reported that CRP, IL-6, TNF-α, and other pro-inflammatory cytokines were progressively higher with increasing HbA1c.[20]

The elevation of IL-6 and TNF-α in our uncontrolled group was also remarkable. IL-6 increased from 3.8 ± 1.6 to 6.7 ± 3.1 pg/mL, while TNF-α increased from 7.2 ± 2.4 to 10.4 ± 4.1 pg/mL, with both differences being highly significant. The findings of the present study are in agreement with Al-Rawaf et al who observed significantly higher levels of IL-6 and TNF-α in poorly controlled as compared to moderately managed T2DM.[20]  A similar study from the hospital setting was conducted in 2024 in Kashmir, which also reviewed the correlation between inflammatory activation and diabetes in a sample of South Asian population; in addition to NLR and PLR, it also looked at IL-6.[21] Moreover, a study conducted in 2025 on Iraqi patients showed high between-group differences in IL-6 and TNF-α levels, suggesting that inflammatory markers could be affected by metabolic improvement from antidiabetic therapy.[22]

The positive correlations that were found between HbA1c and hs-CRP (r = 0.492), IL-6 (r = 0.461), and TNF-α (r = 0.438) further support the idea that higher chronic glycemic exposure is associated with higher inflammatory activity. It is especially interesting as these correlations suggest that inflammatory markers may have more than just a relationship with the presence of diabetes, but also with the level of metabolic dysregulation. In the Indian study, there was a significant correlation between TNF-α and HbA1c (r=0.683) and a significant correlation between IL-6 and TNF-α, indicating the cross-connection between inflammatory and glycemic pathways.[17]  Relationships between inflammatory biomarkers and HbA1c and insulin resistance were also recently shown in the 2026 study, thus supporting our current findings that reflect the inflammatory–metabolic interface seen in our study.[19]

The hematological inflammatory parameters were similar. NLR increased significantly from 1.98 ± 0.61 in controlled patients to 2.58 ± 0.86 in uncontrolled patients, while MLR increased from 0.23 ± 0.07 to 0.31 ± 0.10. HbA1c was positively correlated with both NLR (r=0.351) and MLR (r=0.329). The results are also similar to a 2024 study, which found a strong positive association between NLR and HbA1c and suggested that NLR could be used to monitor glycemic control.[23] Likewise, a Turkish study of HbA1c-categorized patients showed significant differences in NLR between the diabetic and control groups and indicated that NLR could be a useful parameter in the assessment of glycemic status; the results are commonly available.[24] Importantly, a large-scale analysis in 2025 also revealed a significant association between NLR and insulin resistance, which, however, was not sufficient to make NLR useful as a diagnostic tool in itself. Therefore, our results support the use of NLR and MLR as cost-effective supplementary markers, not substitutes for other known markers like HbA1c.[25]

The findings should nevertheless be interpreted in light of the study design. The cross-sectional study design prevented inference of time-order, or temporal association, between inflammatory biomarkers and poor glycemic control. It is thus impossible to conclude whether higher inflammatory activation led to sub-optimal glycemic control or whether the gum disease caused persistent hyperglycaemia. Furthermore, obesity, the use of some drugs, subclinical infection, and other metabolic disorders can influence inflammatory biomarkers. Major inflammatory and systemic conditions were excluded but multivariable analysis was undertaken; residual confounding cannot be excluded. Concentrations of biomarkers may also differ between treatments, especially since some insulin and other antidiabetic medications have the potential to change metabolic and inflammatory pathways.

In summary, the current study establishes that uncontrolled T2DM was characterized by a pattern of coordinated metabolic deterioration and systemic inflammation, and not an elevation in HbA1c alone. Higher levels of hs-CRP, IL-6, TNF-α, NLR, and MLR were also correlated with greater insulin resistance and atherogenic lipid abnormalities, indicating that these may also be markers for the biologic burden of poor glycemic control. The findings are significant in Pakistan, where the situation of poor glycemic control is prevalent and a recent systematic review showed that the percentage of patients with poor glycemic control in published studies in Pakistan ranged from 44.7% to 86.4%. Future prospective studies are needed to identify the potential of the aforementioned inflammatory and metabolic biomarkers as predictors of future worsening of glycemic control and diabetes-related complications, and as targets for biomarker-driven interventions to enhance clinical outcomes.

A markedly different inflammatory-metabolic phenotype was found in uncontrolled T2DM characterized by increased insulin resistance, atherogenic dyslipidemia, and systemic inflammation. The independent associations of hs-CRP, IL-6, TNF-α, NLR, and HOMA-IR with poor glycemic control suggest that assessment of inflammatory and metabolic biomarkers may provide clinically relevant information beyond HbA1c alone. Incorporating these readily measurable biomarkers into diabetes risk assessment may help identify patients with a greater biological burden of disease and facilitate more individualized management. Prospective studies are warranted to determine whether these biomarkers can predict future deterioration in glycemic control and diabetes-related complications.

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