Comparative analysis of dietary and physical activity behavior between prediabetic and normoglycemic populations
Jiarui Lin1, Shuhong Liu2, Lingling Gao3
1School of Nursing, Sun Yat-Sen University, Guangzhou, China.
Background:
The prevalence of prediabetes (preDM) is rising among adults, and lifestyle factors such as physical activity (PA) and diet play a critical role in preventing or delaying the progression to diabetes. However, the differences between PA and diet in prediabetic and normoglycemic individuals remain unclear.
Methods:
A cross-sectional study was conducted on Chinese adults without diabetes, who attended the Third Affiliated Hospital of Sun Yat-sen University in Guangzhou from December 2023 to August 2024. Participants were divided into the preDM group (n = 151) or the normoglycemic group (n = 302). We assessed diet using the Planetary Health Diet Score (PHD-S), which was derived from a Food Frequency Questionnaire (FFQ) reflecting the past year, and PA using one-week recall data. After controlling for confounding factors using the propensity score matching (PSM), we compared dietary and PA differences between the two groups using the independent-samples t-tests, rank-sum tests, chi-square tests, or Fisher's exact tests. Statistical analysis was performed using the R software.
Results:
The preDM group had higher PHD-S values for saturated oils (p = 0.007) and added sugars (p = 0.011), but lower values for fish (p = 0.021), soy foods (p = 0.002), and nuts (p < 0.001) compared to the normoglycemic group. Regarding PA, the preDM group showed significantly higher metabolic equivalent of task (MET) values for light PA compared to the normoglycemic group (p < 0.001). Concurrently, this group demonstrated fewer days of participation in moderate PA (p < 0.001) and vigorous PA (p = 0.032). Mediation analysis revealed that BMI significantly mediated the relationship between diet and uric acid levels in the preDM group, accounting for 29.3% of the mediation effect.
Conclusions:
Significant differences in diet and PA were observed between the preDM and normoglycemic groups. Although the preDM group showed higher PHD-S values of saturated oil and added sugar compared to the normoglycemic group, their PHD-S values of fish, soy foods, and nuts were lower. Moreover, the preDM group had higher levels of light PA. Our study demonstrated that more standardized and individualized health interventions are needed to improve the lifestyle behaviors of prediabetic individuals.
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