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|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|
Health Informatics Clinical Institute, Epworth HealthCare, Victoria, Australia
|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.|
|Affiliated Organisations:||Swinburne University, Australia|
|Appears in Collections:||Health Informatics|
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