Department of Periodontology, Manipal College of Dental Sciences, Manipal, Manipal Academy of Higher Education, Manipal, India.
UBC School of Population and Public Health, British Columbia, Vancouver, Canada.
Acta Odontol Scand. 2024 Mar 26;83:101-111. doi: 10.1080/00016357.2023.2267678.
To estimate the association of patient-related demographic, socioeconomic status, physical activity, stress, and dietary factors influencing the relationship between salivary and blood glucose levels in individuals with and without diabetes mellitus (DM).
This cross-sectional study was conducted on 166 participants with and without DM. Saliva and blood were collected to estimate the glucose levels. Age, gender, occupation, socioeconomic and education level, BMI, hip to waist circumference, stress, dietary pattern, lifestyle, physical activity, family history of diabetes, and type of diabetes were recorded. The association of saliva to predict blood glucose levels was analysed using Spearman Rank Correlation and how these patient-related factors influence the correlation was estimated for future machine learning models. The difference in medians for various groups was calculated using the Mann-Whitney U Test or Kruskal Wallis Test.
Blood glucose level is not significantly correlated to salivary glucose level. However, a statistically significant difference in the median blood glucose levels for diabetic participants (median = 137) compared to healthy controls (p-value < .05) was noted. The correlation between blood and salivary glucose was more positive for higher levels of glucose (Spearman 0.4). Age, alcohol consumption, monthly wages, intake of vegetables, and socioeconomic status affect blood glucose levels.
A correlation between saliva and blood glucose levels in healthy individuals was weak. Saliva should only be used as a monitoring tool rather than a diagnostic tool and is more reliable for patients with poorly controlled diabetes mellitus.
评估与患者相关的人口统计学、社会经济地位、体力活动、压力和饮食因素与糖尿病（DM）患者和非糖尿病患者唾液和血糖水平之间关系的相关性。
本横断面研究纳入了 166 例 DM 患者和非 DM 患者。采集唾液和血液以估计血糖水平。记录年龄、性别、职业、社会经济和教育水平、BMI、臀围与腰围比、压力、饮食模式、生活方式、体力活动、糖尿病家族史和糖尿病类型。使用 Spearman 秩相关分析评估唾液对预测血糖水平的相关性，并估计这些患者相关因素对未来机器学习模型的相关性。使用 Mann-Whitney U 检验或 Kruskal Wallis 检验计算各组中位数的差异。
血糖水平与唾液葡萄糖水平无显著相关性。然而，与健康对照组相比，糖尿病患者的中位血糖水平存在显著差异（中位数=137，p 值<0.05）。对于较高水平的葡萄糖，血液和唾液葡萄糖之间的相关性更为正相关（Spearman 0.4）。年龄、饮酒、月工资、蔬菜摄入量和社会经济地位影响血糖水平。
在健康个体中，唾液与血糖水平之间的相关性较弱。唾液只能作为监测工具，而不能作为诊断工具，对于血糖控制不佳的糖尿病患者更为可靠。
