Abstract
Type 2 diabetes mellitus (T2DM) is a chronic disease affected with complex risk factors and has been regarded as one of the major social burdens due to its high occurrence. In this study, we aim to incorporate the idea of evidence based medicine (EBM) into our diabetes risk factor App development. We acquired and extracted the relative risk of different risk factors from relevant literature by searching academic databases. A total of 19 items of risk factors in our daily lives has been finally selected. To design App graphic interface, a total of three pages were designed to let user answer the questions and show the results of their level or risk to have T2DM. We validated the feasibility of our App in 100 users and the results were promising. Therefore, the personalized EBM diabetes risk factor calculator might be a feasible approach to remind those T2DM risky populations by revealing their potential risk factors, thus making implementation of personalized and prevention medicine achievable at hand.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Sundaram, M., Kavookjian, J., Patrick, J.H.: Health-related quality of life and quality of life in type 2 diabetes: relationships in a cross-sectional study. Patient 2(2), 121–133 (2009)
Stevens, M.J., Feldman, E.L., Greene, D.A.: The etiology of diabetic neuropathy: the combined roles of metabolic and vascular defects. Diabet. Med. 12(7), 566–579 (1995)
Franz, M.J., et al.: Nutrition principles for the management of diabetes and related complications. Diabetes Care 17(5), 490–518 (1994)
Rollo, M.E., et al.: EHealth technologies to support nutrition and physical activity behaviors in diabetes self-management. Diabetes Metab. Syndr. Obes. 9, 381–390 (2016)
Bodenheimer, T., Lorig, K., Holman, H., Grumbach, K.: Patient self-management of chronic disease in primary care. JAMA 288, 2469–2475 (2002)
Jo, S., Park, H.-A.: Development and evaluation of a smartphone application for managing gestational diabetes mellitus. Healthc. Inform. Res. 22(1), 11–21 (2016)
Williams, J.P., Schroeder, D.: Popular glucose tracking apps and use of mHealth by latinos with diabetes: review. JMIR Mhealth Uhealth 3(3), e84 (2015)
LNCS Homepage. http://www.cdc.gov/diabetes/statistics/prev/national/figbysex.htm
He, Y., Zeng, Q., Zhao, X.L.: Association of body mass index and waist circumstance with risk of hypertension and diabetes in Chinese adults. Med. J. Chin. PLA. 40(10), 803–808 (2015)
LNCS Homepage. http://www.cdc.gov/diabetes/statistics/prev/national/figbyeducation.html
Larrañaga, I., Arteagoitia, J.M., Rodriguez, J.L., Gonzalez, F., Esnaola, S., Piniés, J.A.: Socio-economic inequalities in the prevalence of type 2 diabetes, cardiovascular risk factors and chronic diabetic complications in the Basque Country, Spain. Diabetic Med. 22(8), 1047–1053 (2005)
Carlsson, S., Midthjell, K., Grill, V.: Smoking is associated with an increased risk of type 2 diabetes but a decreased risk of autoimmune diabetes in adults: an 11-year follow-up of incidence of diabetes in the nord-trøndelag study. Diabetologia 47(11), 1953–1956 (2004)
Gao, M., Li, J.J., Wu, Y.T.: Relationship between length of sleep and incidence risk of type 2 diabetes. Chin. J. Endocrinol. Metab. 30(5), 393–396 (2014)
Wang, H., Liu, D.M., Peng, Y.: Physical activity of moderate intensity and risk of type 2 diabetes mellitus. J. Jinggangshan Univ. (Nat. Sci.) (05), 115–120 (2011)
Tang, W., Cai, Y., Huang, X.P.: Survey of depression status in patients with type 2 diabetes mellitus and analysis of risk factors. J. Clin. Med. Pract. (2012)
Liu, J., Lan, S.Y.: The epidemiology study advances of risk factors of type 2 diabetes. J. Nantong Univ. (Med. Sci.). 26(03), 230–232 (2006)
Shi, Y., Dong, J.Y., Zhang, Z.L.: Meta-analysis on coffee drinking and type 2 diabetes. J. Nantong Univ. (Med. Sci.) (1), 89–94 (2012)
Tong, X., Dong, J., Wu, Z.: Dairy consumption and risk of type 2 diabetes mellitus: a meta-analysis of cohort studies. Eur. J. Clin. Nutr. 65(9), 1027–1031 (2011)
Feskens, E.J.M., Sluik, D., Woudenbergh, G.J.V.: Meat consumption, diabetes, and its complications. Curr. Diabetes Rep. 13(2), 298–306 (2013)
Cooper, A.J., Sharp, S.J., Lentjes, M.A.H.: A prospective study of the association between quantity and variety of fruit and vegetable intake and incident type 2 diabetes. Diabetes Care 35(6), 1293–1300 (2012)
Colditz, G.A., et al.: Harvard report on cancer prevention volume 4: Harvard cancer risk index. Cancer Causes Control. 11(6), 477–488 (2000). Risk Index Working Group, Harvard Center for Cancer Prevention
Cradock, K.A., ÓLaighin, G., Finucane, F.M., Gainforth, H.L., Quinlan, L.R., Ginis, K.A.: Behaviour change techniques targeting both diet and physical activity in type 2 diabetes: a systematic review and meta-analysis. Int. J. Behav. Nutr. Phys. Act 14(1), 18 (2017)
Helander, E., Kaipainen, K., Korhonen, I., Wansink, B.: Factors related to sustained use of a free mobile app for dietary self-monitoring with photography and peer feedback: retrospective cohort study. J. Med. Internet Res. 16(4), e109 (2014)
Miller, R.L., Shinn, M.: Learning from communities: overcoming difficulties in dissemination of prevention and promotion efforts. Am. J. Community Psychol. 35(3–4), 169–183 (2005)
Bodenheimer, T., Lorig, K., Holman, H., Grumbach, K.: Patient self-management of chronic disease in primary care. JAMA 288(19), 2469–2475 (2002)
Gillett, M., et al.: Delivering the diabetes education and self management for ongoing and newly diagnosed (DESMOND) programme for people with newly diagnosed type 2 diabetes: cost effectiveness analysis. BMJ 341, c4093 (2010)
Chodosh, J., et al.: Meta-analysis: chronic disease self-management programs for older adults. Ann. Intern. Med. 143, 427–438 (2005)
Catherine, H.Y., et al.: A web-based intervention to support self-management of patients with type 2 diabetes mellitus: effect on self-efficacy, self-care and diabetes distress. BMC Med. Inform. Decis. Mak. 14, 117 (2014)
Alhuwail, D.: Diabetes applications for Arabic speakers: a critical review of available apps for android and iOS operated smartphones. Stud. Health Technol. Inform. 225, 587–591 (2016)
Ahn, Y., Bae, J., Kim, H.S.: The development of a mobile U-Health program and evaluation for self-diet management for diabetic patients. Nutr. Res. Pract. 10(3), 342–351 (2016)
Ried-Larsen, M., et al.: Implementation of interval walking training in patients with type 2 diabetes in Denmark: rationale, design, and baseline characteristics. Clin. Epidemiol. 8, 201–209 (2016)
Scheibe, M., Reichelt, J., Bellmann, M., Kirch, W.: Acceptance factors of mobile apps for diabetes by patients aged 50 or older: a qualitative study. Med. 2.0. 4(1), e1 (2015)
Acknowledgements
This work was supported by the grant from National Key R&D Program of China (2018YFC1314902), National Natural Science Foundation of China (No. 81501559, 81371663), Natural Science Foundation of the Higher Education Institutions of Jiangsu Province (No. 15KJB310015) and Science and Technology Project of Nantong City (MS12015180).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Wang, L. et al. (2018). The Development of a Smart Personalized Evidence Based Medicine Diabetes Risk Factor Calculator. In: Chen, H., Fang, Q., Zeng, D., Wu, J. (eds) Smart Health. ICSH 2018. Lecture Notes in Computer Science(), vol 10983. Springer, Cham. https://doi.org/10.1007/978-3-030-03649-2_29
Download citation
DOI: https://doi.org/10.1007/978-3-030-03649-2_29
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-03648-5
Online ISBN: 978-3-030-03649-2
eBook Packages: Computer ScienceComputer Science (R0)