Please use this identifier to cite or link to this item: http://hdl.handle.net/11434/1965
Title: Comorbidities and Diabetes Type 2: A gender-driven probabilistic estimate of patient's risk factor.
metadata.dc.title.book: Optimizing health monitoring systems with wireless technology.
Epworth Authors: Wickramasinghe, Nilmini
Other Authors: Ossai, Chinedau
Keywords: Type 2 Diabetes
Comorbidities
Gender
Risk Factors
Health Informatics Clinical Institute, Epworth HealthCare, Victoria, Australia
Issue Date: 1-Dec-2020
Publisher: IGI Global
Abstract: The prevalence of diabetes type 2 among the population and the increasing rate of new diagnoses as well as other co-morbidities make it imperative that we develop a richer understanding of type 2 diabetes. An Australian survey of diabetes type 2 people for different co-morbidities was carried out to obtain information about the possible connections of the co-morbidities with type 2 diabetes. The analysis is done with the logit model and Pearson's chi-square and the results indicate that gender, age of the patients, and the duration of the diabetes type 2 diagnosis play a significant role in the exposure of individuals to different comorbidities. The influence of the duration of diagnosis and age of the patients is limited in comparison to the gender, which has females at a very high risk of developing the studied co-morbidities compared to males. The findings can improve diabetes type 2 management to boost high quality, proactive, and cost-effective caregiving for the patients.
URI: http://hdl.handle.net/11434/1965
DOI: 10.4018/978-1-5225-6067-8.ch005
ISBN: 9781522560678
Type: Chapter
Affiliated Organisations: Swinburne University, Australia
Appears in Collections:Health Informatics
Internal Medicine

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