AUTHOR=Zhang Fan , Chai Yongfei , Ren Jiajia , Xu Xiaoyu , Jing Cuiqi , Zhang Haimeng , Jiang Yuhong , Xie Hong TITLE=Association between processed red meat intake and cardiovascular risk factors in patients with type 2 diabetes: a cross-sectional study from China JOURNAL=Frontiers in Nutrition VOLUME=11 YEAR=2024 URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2024.1438953 DOI=10.3389/fnut.2024.1438953 ISSN=2296-861X ABSTRACT=Aim

To explore the association between Processed red meat (PRM) consumption and cardiovascular risk factors in Chinese adults with type 2 diabetes mellitus (T2DM).

Methods

Dietary survey, physical measurement, and blood biochemical examination were conducted on 316 patients with type 2 diabetes in Bengbu, China from May to July 2019. Possible confounding factors were identified by comparing between-group variability in the baseline table. To eliminate the effect of confounding factors, subgroup analysis was used to explore whether there were differences in the correlation between PRM intake status and the indicators in cardiovascular disease risk factors. A logistic regression model was used to analyze the association between PRM and the risk of abnormal levels of cardiovascular risk factors in T2DM patients. Restricted cubic spline plots were used to analyze the dose–response relationship between PRM intake and the indicators of cardiovascular disease risk factors.

Results

A total of 316 subjects were included in the study, of whom 139 (44.0%) were male and 177 (56.0%) were female. In the multiplicative interaction, there was an effect modifier for smoking (Pinteraction = 0.033) on the association between PRM intake and the risk of substandard FPG level control; sex (Pinteraction = 0.035), smoking status (Pinteraction = 0.017), and alcohol consumption (Pinteraction = 0.046) had effect modifying effects on the association between PRM intake and risk of abnormal systolic blood pressure. Sex (Pinteraction = 0.045) had an effect modifier on the association of PRM intake status with the risk of diastolic blood pressure abnormality. In addition, age had an effect modifier on the association of PRM intake status with risk of abnormal triglyceride index (Pinteraction = 0.004) and risk of abnormal HDL index (Pinteraction = 0.018). After adjusting for potential confounding variables, logistic regression showed that the OR for substandard HbA1c control in patients in the highest PRM intake group, T3 (3.4 ~ 57.2 g/d), was 1.620-fold higher than in the lowest intake, i.e., the no-intake group, T1 (0.0 ~ 0.0 g/d; OR = 2.620; 95% CI 1.198 ~ 5.732; p = 0.016). Whereas the OR for abnormal control of systolic blood pressure levels was 1.025 times higher (OR = 2.025; 95% CI 1.033 ~ 3.968; p = 0.040) in patients in the PRM low intake group T2 (0.1 ~ 3.3 g/d) than in the non-intake group T1 (0.0 ~ 0.0 g/d), the OR for substandard control of systolic blood pressure in patients in the highest group T3 (3.4 ~ 57.2 g/d) was 1.166 times higher than in the no-intake group T1 (OR = 2.166; 95% CI 1.007 ~ 4.660; p = 0.048). The OR for abnormal TG levels in patients in the highest PRM intake group T3 (3.4 ~ 57.2 g/d) was 1.095 times higher than in the no-intake group T1 (OR = 2.095; 95% CI 1.076 ~ 4.078; p = 0.030). Restricted cubic spline plots presented a nonlinear dose–response relationship between PRM intake and risk of substandard HbA1c and SBP control (P nonlinear <0.05), and an atypical inverted U-shaped association between PRM intake and TC and LDL-C levels (P nonlinear <0.05). The strength of the associations between PRM intake and the control levels of FPG, DBP, HDL-C, and TG were not statistically significant (p > 0.05).

Conclusion

PRM intake was generally low in patients with T2DM, but a nonlinear dose–response relationship between PRM intake and the risk of suboptimal control of HbA1c and SBP, with an atypical inverted U-shaped association with TC and LDL-C levels, was observed. Appropriate control of PRM intake may be important for tertiary prevention of T2DM and cardiovascular disease prevention. We need to better understand these relationships to promote improved cardiometabolism and global health.