Lipid profile patterns associated with pre-diabetes: a comparative study with normoglycemic and diabetic individuals

Q: What are the key findings of this study?

Pre-diabetes was independently associated with higher odds of mixed dyslipidemia compared to normoglycemia (31.7% vs 11.7%; adjusted OR 3.114, 95% CI 1.477-6.566, p=0.003).

Q: What is the clinical evidence from this study?

Study design: Cross-Sectional. Population: Pre-diabetes and Type 2 Diabetes Mellitus (n=360). Intervention: Pre-diabetes (HbA1c 5.7% to 6.4%) vs. Normoglycemia (HbA1c <5.7%). Primary outcome: Mixed dyslipidemia (elevation of TG and TC, and/or LDL-C, VLDL-C) (OR 3.114, 95% CI 1.477-6.566, p=0.003).

Q: What does this research mean for the field?

Pre-diabetes is independently associated with an over threefold increase in the odds of mixed dyslipidemia compared to normoglycemia. Novelty: ClaimNovelty.INCREMENTAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Muhammad Irtza Tanveer; Hamid Khalil; Manahil Choudry; Tehseen Javed Javed; Ahmad Masood Akbar; Hanzalah Samee

doi:10.37723/jumdc.v17i3.1473

September 25, 2026Journal of University Medical & Dental CollegeOpen Access

Lipid profile patterns associated with pre-diabetes: a comparative study with normoglycemic and diabetic individuals

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Key result

Pre-diabetes is linked to ~3.1-fold higher odds of mixed dyslipidemia compared to normoglycemia.

OR 3.114
95% CI 1.477-6.566
P=0.003
n=360

Why the study?

Disturbed glucose metabolism is associated with dyslipidemia, and this study aimed to identify lipid profile patterns specifically associated with pre-diabetes as an intermediate state between normoglycemia and overt diabetes.

What lipid profile patterns and parameters are associated with pre-diabetes compared with normoglycemic and diabetic individuals?

Key Points

To identify lipid profile patterns associated with pre-diabetes and compare these profiles across normoglycemic, pre-diabetic, and diabetic individuals.
Analytical cross-sectional study conducted at the Punjab Institute of Cardiology including 360 adults, evenly stratified into normoglycemic (n=120), pre-diabetic (n=120), and diabetic (n=120) groups defined by American Diabetes Association criteria.
Overnight fasting blood samples were evaluated for HbA1c and lipid parameters, including triglycerides, total cholesterol, HDL-C, LDL-C, non-HDL-C, and VLDL-C.
Group differences and lipid pattern odds were evaluated via one-way ANOVA with post hoc Tukey testing, chi-square tests, and multivariable logistic regression adjusted for age, gender, smoking, and BMI.
Deranged lipid profiles occurred in 80.8% of normoglycemic, 85.8% of pre-diabetic, and 90.8% of diabetic participants, with significant differences in triglycerides, non-HDL-C, and VLDL-C across groups (p<0.001).
Univariate regression showed pre-diabetes was associated with reduced odds of isolated low HDL-C (OR=0.495, 95% CI: 0.279-0.878, p=0.016) and a 250% increase in odds of mixed dyslipidemia (OR=3.509, 95% CI: 1.783-6.903, p<0.001).
After adjusting for age, gender, smoking, and BMI, mixed dyslipidemia remained an independent predictor of pre-diabetes (adjusted OR=3.114, 95% CI: 1.477-6.566, p=0.003).

Study Design

Type

Cross-Sectional (n=360)

Multicenter

No

Structured PICO

What lipid profile patterns and parameters are associated with pre-diabetes compared with normoglycemic and diabetic individuals?

P

Population

360 adults (mean age 46.1 years, 45% female) without prior glucose- or lipid-lowering therapy, divided equally into normoglycemic, pre-diabetic, and diabetic groups at a single cardiology outpatient center in Pakistan.

E

Exposure

Pre-diabetes (defined by ADA criteria as HbA1c 5.7% to 6.4%) and diabetes (HbA1c ≥ 6.5%) evaluated via overnight fasting blood samples (8 to 12 hours) for HbA1c and lipid profile parameters

C

Comparator

Normoglycemic individuals (HbA1c <5.7%) and diabetic individuals (HbA1c ≥ 6.5%)

O

Outcome

Prevalence and association of qualitative lipid profile patterns (normal lipid profile, isolated hypertriglyceridemia, isolated hypercholesterolemia, isolated low HDL-C, atherogenic dyslipidemia, and mixed dyslipidemia) across glycemic groups, defined using NCEP ATP III criteriasurrogate

Main Result

Odds Ratio: 3.114 (95% CI 1.477–6.566)

Absolute Event Rate: 31.7% vs 11.7%

p-value: p=0.003

Limitations

Single-centre design and recruitment from a cardiology/OPD-referral population limit generalizability to community-based populations.
Cross-sectional design precludes establishing temporal or causal relationships between glycemic status and lipid abnormalities.
LDL-C was estimated using the Friedewald formula, which may be unreliable when triglyceride levels exceed 400 mg/dL.
Direct measures of insulin resistance, such as HOMA-IR, were not available.
Single-centre design and recruitment from a cardiology/OPD-referral population may limit generalizability to community-based populations
Cross-sectional design precludes establishing temporal or causal relationships between glycemic status and lipid abnormalities
LDL-C was estimated using the Friedewald formula, which may be unreliable when triglyceride levels exceed approximately 400 mg/dL
Direct measures of insulin resistance, such as HOMA-IR, were not available

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Implication

Mixed dyslipidemia is an independent predictor of pre-diabetes, indicating that qualitative lipid profile abnormalities emerge early during glycemic dysregulation and may aid in early cardiovascular risk assessment.

Abstract

BACKGROUND & OBJECTIVE: Disturbed glucose metabolism is associated with dyslipidemia, a potent risk factor for cardiovascular diseases. Pre-diabetes is the intermediate state between normoglycemia and overt diabetes. Our study aims to find lipid profile patterns associated with pre-diabetes. METHODOLOGY:This analytical cross-sectional study was conducted at the OPD of Punjab Institute of Cardiology, Lahore. This study included 360 individuals in total, 120 individuals from each glycemic group. Glycemic status was defined using the guidelines of the American Diabetes Association. Blood samples were drawn after overnight fasting and tested for lipid profile parameters and HbA1c. One-way ANOVA was applied to compare lipid profile parameters between glycemic groups. A chi-square test was applied to assess the association between various lipid profile patterns and glycemic groups. Regression analysis was applied to determine the odds of each pattern associated with pre-diabetes. RESULTS: Lipid abnormalities increased with changes of glycemic status, i.e., 80.2% in the normoglycemic group, 85.8% in the pre-diabetic group and 90.8% in the diabetic group. Isolated low HDL-C, Atherogenic dyslipidemia and mixed dyslipidemia were significantly associated with change in glycemic status. Univariate regression analysis showed that the odds of getting mixed dyslipidemia increased by 250% in pre-diabetes (OR=3.509, 95%CI: 1.783-6.903, p<0.001). After adjustment for confounders, mixed dyslipidemia remained the independent predictor of pre-diabetes (OR=3.114, 95%CI: 1.477-6.566, p=0.003). CONCLUSION:Qualitative lipid profile abnormalities better define glycemic status. Mixed dyslipidemia is associated with pre-diabetes, while atherogenic lipid profiles are pronounced in diabetes, representing increased cardiovascular risk with worsening glycemic states.

Discussion

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Cite This Study

Tanveer et al. (2026) conducted a cross-sectional in Pre-diabetes and Type 2 Diabetes Mellitus (n=360). Pre-diabetes (HbA1c 5.7% to 6.4%) vs. Normoglycemia (HbA1c <5.7%) was evaluated on Mixed dyslipidemia (elevation of TG and TC, and/or LDL-C, VLDL-C) (OR 3.114, 95% CI 1.477-6.566, p=0.003). Pre-diabetes was independently associated with higher odds of mixed dyslipidemia compared to normoglycemia (31.7% vs 11.7%; adjusted OR 3.114, 95% CI 1.477-6.566, p=0.003).

synapsesocial.com/papers/6af0db863c845ca7837ced72 https://doi.org/10.37723/jumdc.v17i3.1473

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Lipid profile patterns associated with pre-diabetes: a comparative study with normoglycemic and diabetic individuals

Key Points

Study Design

Structured PICO

Main Result

Limitations

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

Lipid profile patterns associated with pre-diabetes: a comparative study with normoglycemic and diabetic individuals

Key Points

Study Design

Structured PICO

Main Result

Limitations

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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