Correlations of Salivary and Blood Glucose Levels among Six Saliva Collection Methods
Abstract
:1. Introduction
2. Materials and Methods
2.1. Ethics Statement
2.2. Participants
2.3. Samples Collection
2.4. Statistics
3. Results
3.1. Sample Characteristics
3.2. Validation of Diagnostic Performance by ROC
3.3. Correlation Studies
3.3.1. Population Correlations
3.3.2. Individual Correlations
3.3.3. Stability of Individual Correlations
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Sun, J.; Ren, J.; Hu, X.; Hou, Y.; Yang, Y. Therapeutic effects of Chinese herbal medicines and their extracts on diabetes. Biomed. Pharmacother. 2021, 142, 111977. [Google Scholar] [CrossRef] [PubMed]
- Cortese, F. Genetic or non-genetic factors: Which ones are the main determinants of type 2 diabetes? This is the question. Eur. J. Prev. Cardiol. 2021, 28, 1858–1860. [Google Scholar] [CrossRef] [PubMed]
- Adeghate, E.A.; Kalász, H.; Al Jaberi, S.; Jennifer, A.; Kornelia, T. Tackling type 2 diabetes-associated cardiovascular and renal comorbidities: A key challenge for drug development. Expert Opin. Investig. Drugs 2021, 30, 85–93. [Google Scholar] [CrossRef] [PubMed]
- Franziska, G.H.; Kristina, L.K.; Inge, K.H.; Peter, H.A.; Banoo, B.; Anja, J.; Hans, J.N.L.; Karen, B.M.; Isik, S.J.; Pernille, R. The prevalence of diabetes among tuberculosis patients in Denmark. BMC Infect. Dis. 2022, 22, 64. [Google Scholar]
- Chan, J.; Wong, C.; Or, P.; Chen, E.; Chang, W. Risk of mortality and complications in patients with schizophrenia and diabetes mellitus: Population-based cohort study. Br. J. Psychiatry 2021, 219, 375–382. [Google Scholar] [CrossRef]
- Powars, D.R.; Chan, L.S.; Hiti, A.; Hiti, A.; Ramicone, E.; Johnson, C. Outcome of sickle cell anemia: A 4-decade observational study of 1056 patients. Medicine 2005, 84, 363–376. [Google Scholar] [CrossRef]
- Janapala, R.N.; Jayaraj, J.S.; Fathima, N.; Kashif, T.; Sachmechi, I. Continuous glucose monitoring versus self-monitoring of blood glucose in type 2 diabetes mellitus: A systematic review with meta-analysis. Cureus 2019, 11, 37–43. [Google Scholar] [CrossRef] [Green Version]
- Sim, R.; Lee, S.W.H. Patient preference and satisfaction with the use of telemedicine for glycemic control in patients with type 2 diabetes: A review. Patient Prefer. Adherence 2021, 15, 283. [Google Scholar] [CrossRef]
- Shang, T.; Zhang, J.Y.; Thomas, A. Products for monitoring glucose levels in the human body with noninvasive optical, noninvasive fluid sampling, or minimally invasive technologies. J. Diabetes Sci. Technol. 2022, 16, 168–214. [Google Scholar] [CrossRef]
- Bamgboje, D.; Christoulakis, I.; Smanis, I. Continuous non-invasive glucose monitoring via contact lenses: Current approaches and future perspectives. Biosensors 2021, 11, 189. [Google Scholar] [CrossRef]
- Zhang, Y.; Sun, J.; Liu, L.; Qiao, H. A review of biosensor technology and algorithms for glucose monitoring. J. Diabetes Complicat. 2021, 35, 107929. [Google Scholar] [CrossRef]
- Alizadeh, A.; Burns, A.; Lenigk, R.; Rachel, G.; Jeffrey, A.; Adam, P.; Margaret, M.C.; Ruairi, B. A wearable patch for continuous monitoring of sweat electrolytes during exertion. Lab A Chip 2018, 18, 2632–2641. [Google Scholar] [CrossRef]
- Ahmad, R.; Haque, M. Oral health messiers: Diabetes mellitus relevance. Diabetes Metab. Syndr. Obes. Targets Ther. 2021, 14, 3001. [Google Scholar] [CrossRef]
- Turner, A.P.F. Biosensors: Sense and sensibility. Chem. Soc. Rev. 2013, 42, 3184–3196. [Google Scholar] [CrossRef] [Green Version]
- Palomar, B.M.; Atienza, M.; Hernández, L.B.; Cantero, J.L. Associations of Salivary Total Antioxidant Capacity with Cortical Amyloid-Beta Burden, Cortical Glucose Uptake, and Cognitive Function in Normal Aging. J. Gerontol. Ser. A 2021, 76, 1839–1845. [Google Scholar] [CrossRef]
- Chakraborty, P.; Deka, N.; Patra, D.C.; Debnath, K.; Mondal, S.P. Hydrothermally Grown Porous Cobalt Oxide Nanostructures for Enzyme-Less Glucose Detection. J. Electron. Mater. 2021, 50, 3699–3705. [Google Scholar] [CrossRef]
- Cui, Y.; Zhang, H.; Zhu, J.; Lu, P.; Zhili, D.; Tian, L.; Jiasheng, Z.; Lu, X.; Zhenhua, L.; Song, W.; et al. Unstimulated Parotid Saliva Is a Better Method for Blood Glucose Prediction. Appl. Sci. 2021, 11, 11367. [Google Scholar] [CrossRef]
- Cui, Y.; Yang, M.Y.; Zhang, H.; Zhu, J.; Zhenhua, L.; Song, W.; Weiqiang, L. Developments in diagnostic applications of saliva in Human Organ Diseases. Med. Nov. Technol. Devices 2022, 13, 100115. [Google Scholar] [CrossRef]
- Krishnaveni, P.; Ganesh, V. Electron transfer studies of a conventional redox probe in human sweat and saliva bio-mimicking conditions. Sci. Rep. 2021, 11, 7663. [Google Scholar] [CrossRef]
- Caixeta, D.C.; Aguiar, E.; Cardoso-Sousa, L.; Coelho, L.M.D. Salivary molecular spectroscopy: A rapid and non-invasive monitoring tool for diabetes mellitus during insulin treatment. PLoS ONE 2019, 15, e0223461. [Google Scholar] [CrossRef]
- Rodrigues, R.; Vieira, W.; Siqueira, W.L.; Bernardo, A.; Luiz, R. Saliva as a tool for monitoring hemodialysis: A systematic review and meta-analysis. Braz. Oral Res. 2021, 35, e016. [Google Scholar] [CrossRef]
- Zhao, M.; Leung, P.S. Revisiting the use of biological fluids for noninvasive glucose detection. Future Med. Chem. 2020, 12, 645–647. [Google Scholar] [CrossRef] [Green Version]
- Chakraborty, P.; Deka, N.; Patra, D.C.; Debnath, K.; Mondal, S.P. Salivary glucose sensing using highly sensitive and selective non-enzymatic porous NiO nanostructured electrodes. Surf. Interfaces 2021, 26, 101324. [Google Scholar] [CrossRef]
- Goel, R.K.; Munjal, A.; Talukdar, A. Saliva as a potential diagnostic and monitoring tool in diabetes mellitus. J. Curr. Med. Res. Opin. 2021, 4, 1088–1095. [Google Scholar]
- Kumar, S.; Padmashree, S.; Jayalekshmi, R. Correlation of salivary glucose, blood glucose and oral candidal carriage in the saliva of type 2 diabetics: A case-control study. Contemp. Clin. Dent. 2014, 5, 312. [Google Scholar] [CrossRef] [PubMed]
- Tjahajawati, S.; Rafisa, A.; Murniati, N. Correlation between taste threshold sensitivity and MMP-9, salivary secretion, blood pressure, and blood glucose levels in smoking and nonsmoking women. Int. J. Dent. 2020, 2020, 4178674. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Saitou, M.; Gaylord, E.A.; Xu, E.; May, A.J. Functional specialization of human salivary glands and origins of proteins intrinsic to human saliva. Cell Rep. 2020, 33, 108402. [Google Scholar] [CrossRef] [PubMed]
- Vuletić, L.; Špalj, S.; Rogić, D.; Peros, K. The rise in glucose concentration in saliva samples mixed with test foods monitored using a glucometer: An observational pilot study. J. Oral Biosci. 2019, 61, 201–206. [Google Scholar] [CrossRef]
- Kubala, E.; Strzelecka, P.; Grzegocka, M.; Danuta, L.K.; Helena, G.; Piotr, S.; Edward, K. A review of selected studies that determine the physical and chemical properties of saliva in the field of dental treatment. BioMed Res. Int. 2018, 2018, 6572381. [Google Scholar] [CrossRef]
- Bapat, S.; Nagarajappa, R.; Ramesh, G.; Bapat, K. Effect of propolis mouth rinse on oral microorganisms—A randomized controlled trial. Clin. Oral Investig. 2021, 25, 6139–6146. [Google Scholar] [CrossRef]
- Gupta, S.; Nayak, M.T.; Sunitha, J.D.; Dawar, G.; Sinha, N.; Rallan, N.S. Correlation of salivary glucose level with blood glucose level in diabetes mellitus. J. Oral Maxillofac. Pathol. 2017, 21, 334. [Google Scholar]
- Ephraim, R.K.D.; Anto, E.O.; Acheampong, E. Fasting salivary glucose levels is not a better measure for identifying diabetes mellitus than serum or capillary blood glucose levels: Comparison in a Ghanaian population. Heliyon 2019, 5, e01286. [Google Scholar] [CrossRef] [Green Version]
- Amer, S.; Yousuf, M.; Siddqiui, P.Q.; Alam, J. Salivary glucose concentrations in patients with diabetes mellitus–a minimally invasive technique for monitoring blood glucose levels. Pak. J. Pharm. Sci. 2001, 14, 33–37. [Google Scholar]
- Mishra, N.; Trivedi, A.; Gajdhar, S.K. Correlation of blood glucose levels, salivary glucose levels and oral colony forming units of Candida albicans in type 2 diabetes mellitus patients. J. Contemp. Dent. Pract. 2019, 20, 494–498. [Google Scholar]
- Karjalainen, J.; Salmela, P.; Ilonen, J. A comparison of childhood and adult type I diabetes mellitus. N. Engl. J. Med. 1989, 320, 881–886. [Google Scholar] [CrossRef]
- Zolotukhin, S. Metabolic hormones in saliva: Origins and functions. Oral Dis. 2013, 19, 219–229. [Google Scholar] [CrossRef] [Green Version]
- Abikshyeet, P.; Ramesh, V.; Oza, N. Glucose estimation in the salivary secretion of diabetes mellitus patients. Diabetes Metab. Syndr. Obes. 2012, 5, 149. [Google Scholar]
- Stehouwer, C.D.A.; Lambert, J.; Donker, A.J.M.; Hinsbergh, V.W.M. Endothelial dysfunction and pathogenesis of diabetic angiopathy. Cardiovasc. Res. 1997, 34, 55–68. [Google Scholar] [CrossRef]
- Belazi, M.A.; Galli-Tsinopoulou, A.; Drakoulakos, D.; Fleva, A.; Papanayiotou, P.H. Salivary alterations in insulin-dependent diabetes mellitus. Int. J. Paediatr. Dent. 1998, 8, 29–33. [Google Scholar] [CrossRef]
- McChesney, K.; Aldridge, J. Weaving an interpretivist stance throughout mixed methods research. Int. J. Res. Method Educ. 2019, 42, 225–238. [Google Scholar] [CrossRef]
- Takeda, I.; Stretch, C.; Barnaby, P.; Kriti, B.; Kathryn, R. Understanding the human salivary metabolome. NMR Biomed. Int. J. Devoted Dev. Appl. Magn. Reson. Vivo 2009, 22, 577–584. [Google Scholar] [CrossRef]
- Jha, N.; Srinivasa, D.K.; Roy, G.; Jagdish, S.; Minocha, R.K. Epidemiological study of road traffic accident cases: A study from South India. Indian J. Community Med. 2004, 29, 20–24. [Google Scholar]
- Wang, Y.; Cui, H.; Zhang, Q.; Hayat, K. Proline-glucose Amadori compounds: Aqueous preparation, characterization and saltiness enhancement. Food Res. Int. 2021, 144, 110319. [Google Scholar] [CrossRef]
- Panchbhai, A.S. Correlation of salivary glucose level with blood glucose level in diabetes mellitus. J. Oral Maxillofac. Res. 2012, 3, e3. [Google Scholar] [CrossRef] [Green Version]
- Shahin, A.M.; Abdel Ati, R.I.; Fayd, S.M.; Mokhtar, M.A. Salivary Glucose level as Noninvasive Diagnostic Tool for Monitoring Glycemic Control of Type 1 Diabetic Children. Benha J. Appl. Sci. 2021, 6, 273–277. [Google Scholar] [CrossRef]
- Matthay, M.A.; Folkesson, H.G.; Clerici, C. Lung epithelial fluid transport and the resolution of pulmonary edema. Physiol. Rev. 2002, 82, 569–600. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Jasim, H.; Carlsson, A.; Hedenberg-Magnusson, B.; Ghafouri, B.; Ernberg, M. Saliva as a medium to detect and measure biomarkers related to pain. Sci. Rep. 2018, 8, 3220. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Herrala, M.; Mikkonen, J.J.W.; Pesonen, P. Variability of salivary metabolite levels in patients with Sjögren’s syndrome. J. Oral Sci. 2021, 63, 22–26. [Google Scholar] [CrossRef] [PubMed]
- Pedersen, A.M.L.; Belstrøm, D. The role of natural salivary defences in maintaining a healthy oral microbiota. J. Dent. 2019, 80, S3–S12. [Google Scholar] [CrossRef]
- Taherali, F.; Varum, F.; Basit, A.W. A slippery slope: On the origin, role and physiology of mucus. Adv. Drug Deliv. Rev. 2018, 124, 16–33. [Google Scholar] [CrossRef] [PubMed]
- Bostanci, N.; Mitsakakis, K.; Afacan, B.; Bao, K.; Karpíek, M. Validation and verification of predictive salivary biomarkers for oral health. Sci. Rep. 2021, 11, 1–12. [Google Scholar]
- Shashikanth, M.C.; Shambulingappa, P. Comparison of serum glucose and salivary glucose in diabetic patients. J. Indian Acad. Oral Med. Radiol. 2008, 20, 9. [Google Scholar]
- Puttaswamy, K.A.; Puttabudhi, J.H.; Raju, S. Correlation between salivary glucose and blood glucose and the implications of salivary factors on the oral health status in type 2 diabetes mellitus patients. J. Int. Soc. Prev. Community Dent. 2017, 7, 28. [Google Scholar] [CrossRef] [Green Version]
- Sharif, K.; Watad, A.; Bragazzi, N.L.; Lichtbroun, M.; Shoenfeld, Y. Physical activity and autoimmune diseases: Get moving and manage the disease. Autoimmun. Rev. 2018, 17, 53–72. [Google Scholar] [CrossRef]
Salivary Flow (mL/min) | Patients (n = 40) | Controls (n = 40) | ||
---|---|---|---|---|
Male | Female | Male | Female | |
UWS | 0.85 ± 0.18 | 0.85 ± 0.11 | 1.64 ± 0.16 | 0.89 ± 0.09 |
SWS | 1.73 ± 0.12 | 1.52 ± 0.13 | 2.28 ± 0.15 ** | 1.78 ± 0.12 |
UPS | 0.44 ± 0.09 | 0.43 ± 0.11 * | 0.82 ± 0.08 | 0.45 ± 0.07 |
SPS | 1.05 ± 0.09 | 0.91 ± 0.03 | 1.16 ± 0.08 | 0.91 ± 0.06 |
USS | 0.72 ± 0.11 | 0.71 ± 0.09 | 1.41 ± 0.12 | 0.76 ± 0.08 |
SSS | 1.47 ± 0.04 | 1.31 ± 0.33 | 1.94 ± 0.09 | 1.51 ± 0.14 |
Glucose Levels (mM) | SWS | UWS | SPS | UPS | SSS | USS |
---|---|---|---|---|---|---|
Patients (n = 40) | 1.53 ± 0.63 | 2.42 ± 0.66 | 1.84 ± 0.64 | 2.89 ± 0.76 ** | 1.79 ± 0.63 | 2.58 ± 0.52 |
Controls (n = 40) | 1.42 ± 0.60 * | 1.43 ± 0.40 | 1.50 ± 0.53 | 1.49 ± 0.49 | 1.54 ± 0.54 | 1.82 ± 0.31 |
No. | Patients (n = 10) | No. | Controls (n = 10) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
1 w | 2 w | 3 w | 4 w | CV % | 1 w | 2 w | 3 w | 4 w | CV % | ||
1 | 0.93 | 0.89 | 0.94 | 0.89 | 2.8 | 1 | 0.91 | 0.89 | 0.87 | 0.83 | 3.9 |
2 | 0.92 | 0.87 | 0.89 | 0.91 | 2.4 | 2 | 0.82 | 0.81 | 0.79 | 0.76 | 3.3 |
3 | 0.86 | 0.87 | 0.85 | 0.82 | 2.5 | 3 | 0.88 | 0.87 | 0.83 | 0.81 | 3.8 |
4 | 0.91 | 0.86 | 0.92 | 0.87 | 3.3 | 4 | 0.76 | 0.75 | 0.77 | 0.72 | 2.8 |
5 | 0.88 | 0.91 | 0.89 | 0.93 | 2.4 | 5 | 0.84 | 0.83 | 0.79 | 0.78 | 3.6 |
6 | 0.84 | 0.75 | 0.83 | 0.81 | 4.9 | 6 | 0.68 | 0.67 | 0.65 | 0.68 | 2.1 |
7 | 0.89 | 0.84 | 0.88 | 0.85 | 2.7 | 7 | 0.66 | 0.65 | 0.68 | 0.61 | 4.5 |
8 | 0.87 | 0.87 | 0.86 | 0.83 | 2.2 | 8 | 0.76 | 0.75 | 0.69 | 0.77 | 4.8 |
9 | 0.92 | 0.84 | 0.91 | 0.88 | 4.0 | 9 | 0.72 | 0.71 | 0.65 | 0.67 | 4.8 |
10 | 0.81 | 0.83 | 0.86 | 0.78 | 4.1 | 10 | 0.66 | 0.65 | 0.59 | 0.64 | 4.8 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Cui, Y.; Zhang, H.; Zhu, J.; Liao, Z.; Wang, S.; Liu, W. Correlations of Salivary and Blood Glucose Levels among Six Saliva Collection Methods. Int. J. Environ. Res. Public Health 2022, 19, 4122. https://doi.org/10.3390/ijerph19074122
Cui Y, Zhang H, Zhu J, Liao Z, Wang S, Liu W. Correlations of Salivary and Blood Glucose Levels among Six Saliva Collection Methods. International Journal of Environmental Research and Public Health. 2022; 19(7):4122. https://doi.org/10.3390/ijerph19074122
Chicago/Turabian StyleCui, Yangyang, Hankun Zhang, Jia Zhu, Zhenhua Liao, Song Wang, and Weiqiang Liu. 2022. "Correlations of Salivary and Blood Glucose Levels among Six Saliva Collection Methods" International Journal of Environmental Research and Public Health 19, no. 7: 4122. https://doi.org/10.3390/ijerph19074122
APA StyleCui, Y., Zhang, H., Zhu, J., Liao, Z., Wang, S., & Liu, W. (2022). Correlations of Salivary and Blood Glucose Levels among Six Saliva Collection Methods. International Journal of Environmental Research and Public Health, 19(7), 4122. https://doi.org/10.3390/ijerph19074122