Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016)

Thomas Mageto; Efron Njuguna; Dolleen Osundwa

doi:doi:10.11648/j.sjams.20180601.12

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Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016)

Thomas Mageto, Efron Njuguna, Dolleen Osundwa

Published in Science Journal of Applied Mathematics and Statistics (Volume 6, Issue 1)

Received: 4 January 2018 Accepted: 15 January 2018 Published: 31 January 2018

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Abstract

This study sought to model risk factors of diabetes (A case study of Focus Medical Center in Kiambu, Kenya) for the year 2016. We considered sample of size 181 patients and carried descriptive statistics, bivariate analysis, Chi-Square test and Hosmer and Lemeshow test. The independence test between response variable (diabetes) and predictor variables (age, obesity, alcohol, smoking and hypertension) was carried. The variables age, obesity, alcohol and hypertension were found to be statistically significant at α =0.05 level of significant. A multiple logistic regression model was fitted and the fitted regression model indicated that the predictor variables age, obesity and alcohol were statistically significant. The results of the odds ratios show that age, obesity and alcohol consumption are positively associated with diabetes. The fitted reduced multiple logistic regression model was subjected to an overall goodness-of-fit test and results indicate that there is no significant difference between the observed and predicted probability. Based on the results of this study, we recommend that special attention should be given to individuals advanced in age, consume alcohol or who are obese for screening as there is a high possibility of testing positive for diabetes for health care givers to monitor and manage the condition. Further, healthy lifestyles should be promoted among the general population and in particular, the diabetic patients to increase the chance of properly managing the condition. A further study ought to be conducted to assess treatment interventions of diabetes to ascertain the effectiveness and recommend the best medication for patients suffering from diabetes.

Published in	Science Journal of Applied Mathematics and Statistics (Volume 6, Issue 1)
DOI	10.11648/j.sjams.20180601.12
Page(s)	7-15
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Diabetes, Multiple Logistic Regression, Risk Factors, Odd Ratio, Sample Size, Hosmer and Lemeshow Test

References

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[7]	Cox, W. M., et al (1996). Diabetic patients' alcohol use and qaulity life: relationships with prescribed treatment compliance among older males. Acoholism, Clinical and Experimental Research 20 (2), 327-31.
[8]	Will, C. Julie, et al. (2001). Cigarette smoking and diabetes mellitus: evidence of a positive association from a large prospective cohort study. International Journal of Epidemiology vol. 30 (3) 540-546.
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[10]	Mancia, G. (2005). The association of hypertension and diabetes: prevalence, cardiovascular risk and protection by blood pressure reduction. Acta Diabetol 42, 17-25.
[11]	Maty, S. C., et al. (2005). Education, Income, Occupation, and the 34-year Incidence (1965-1999) of type 2 diabetes in Alameda County Study. International Journal Epidemiology 34 (6), 1274-81.
[12]	Yuko, Morikawa, et al. (1997). Ten-year follow-up study on the relation between the development of non-insulin-dependent diabetes mellitus and occupation. Ameican Journal of Industrial Medicine 31, 80-84.
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[17]	Ejim, E. C., et al (2013). Cardiovascular risk factors in middle-aged and elderly residents in South-East Nigeria: the influence of urbanization. Journal of the National Association Medicine of Resident Doctors of Nigeria, 22 (4), 286-91.
[18]	Amoah, A. G., et al (2000). A national diabetes care and education programme: the Ghan model. Diabetic Research and Clinical Practice, 49 (2-3), 149-157.
[19]	Kavanagh, A., et al (2010). Socialeconomic position, gender, health behaviors and biomarkers of cardiovascular disease and diabetes. Social Science and Medicine, 71 (6), 1150-60.
[20]	Robbins, J. M., et al (2001). Social economic status and type 2 diabetes in African American and non-Hispanic white women and men: Evidence fron the third National Health and Nutrition Examination Survey. American Journal of Public Health, 91 (1), 76-83.
[21]	Agardh, E., et al (2011). Type 2 diabetes incidence and social-economic position: a systematic review and meta-analysis. International Journal of Epidemiology 1-15.
[22]	Faerch, K., et al (2009). Predictions of future fasting and 2-h post-OGTT plasma glucose levels in middle-aged men and women. Diabetic Medicine, 26 (4), 377-83.
[23]	Assah, F. K., et al (2011). Urbanization, physical activity, and metabolic health in sub-saharan Africa. Diabetes Care 34, 491-496.
[24]	Guthold, R., et al (2008). Worldwide Variability in Physical Inactivity. A 51-County Survey. American Journal of Preventive Medicine 34 (6), 486-494.
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[27]	Florez, J. C., J. (2003). Hirschhorn and D. Altshuler. The inherited basis of diabetes mellitus: implications for the generic analysis of complex traits. Annual review of genomics and genetics, 4, 257-91.
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APA Style

Thomas Mageto, Efron Njuguna, Dolleen Osundwa. (2018). Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016). Science Journal of Applied Mathematics and Statistics, 6(1), 7-15. https://doi.org/10.11648/j.sjams.20180601.12

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ACS Style

Thomas Mageto; Efron Njuguna; Dolleen Osundwa. Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016). Sci. J. Appl. Math. Stat. 2018, 6(1), 7-15. doi: 10.11648/j.sjams.20180601.12

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AMA Style

Thomas Mageto, Efron Njuguna, Dolleen Osundwa. Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016). Sci J Appl Math Stat. 2018;6(1):7-15. doi: 10.11648/j.sjams.20180601.12

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@article{10.11648/j.sjams.20180601.12,
  author = {Thomas Mageto and Efron Njuguna and Dolleen Osundwa},
  title = {Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016)},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {6},
  number = {1},
  pages = {7-15},
  doi = {10.11648/j.sjams.20180601.12},
  url = {https://doi.org/10.11648/j.sjams.20180601.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20180601.12},
  abstract = {This study sought to model risk factors of diabetes (A case study of Focus Medical Center in Kiambu, Kenya) for the year 2016. We considered sample of size 181 patients and carried descriptive statistics, bivariate analysis, Chi-Square test and Hosmer and Lemeshow test. The independence test between response variable (diabetes) and predictor variables (age, obesity, alcohol, smoking and hypertension) was carried. The variables age, obesity, alcohol and hypertension were found to be statistically significant at α =0.05 level of significant. A multiple logistic regression model was fitted and the fitted regression model indicated that the predictor variables age, obesity and alcohol were statistically significant. The results of the odds ratios show that age, obesity and alcohol consumption are positively associated with diabetes. The fitted reduced multiple logistic regression model was subjected to an overall goodness-of-fit test and results indicate that there is no significant difference between the observed and predicted probability. Based on the results of this study, we recommend that special attention should be given to individuals advanced in age, consume alcohol or who are obese for screening as there is a high possibility of testing positive for diabetes for health care givers to monitor and manage the condition. Further, healthy lifestyles should be promoted among the general population and in particular, the diabetic patients to increase the chance of properly managing the condition. A further study ought to be conducted to assess treatment interventions of diabetes to ascertain the effectiveness and recommend the best medication for patients suffering from diabetes.},
 year = {2018}
}

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TY  - JOUR
T1  - Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016)
AU  - Thomas Mageto
AU  - Efron Njuguna
AU  - Dolleen Osundwa
Y1  - 2018/01/31
PY  - 2018
N1  - https://doi.org/10.11648/j.sjams.20180601.12
DO  - 10.11648/j.sjams.20180601.12
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 7
EP  - 15
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20180601.12
AB  - This study sought to model risk factors of diabetes (A case study of Focus Medical Center in Kiambu, Kenya) for the year 2016. We considered sample of size 181 patients and carried descriptive statistics, bivariate analysis, Chi-Square test and Hosmer and Lemeshow test. The independence test between response variable (diabetes) and predictor variables (age, obesity, alcohol, smoking and hypertension) was carried. The variables age, obesity, alcohol and hypertension were found to be statistically significant at α =0.05 level of significant. A multiple logistic regression model was fitted and the fitted regression model indicated that the predictor variables age, obesity and alcohol were statistically significant. The results of the odds ratios show that age, obesity and alcohol consumption are positively associated with diabetes. The fitted reduced multiple logistic regression model was subjected to an overall goodness-of-fit test and results indicate that there is no significant difference between the observed and predicted probability. Based on the results of this study, we recommend that special attention should be given to individuals advanced in age, consume alcohol or who are obese for screening as there is a high possibility of testing positive for diabetes for health care givers to monitor and manage the condition. Further, healthy lifestyles should be promoted among the general population and in particular, the diabetic patients to increase the chance of properly managing the condition. A further study ought to be conducted to assess treatment interventions of diabetes to ascertain the effectiveness and recommend the best medication for patients suffering from diabetes.
VL  - 6
IS  - 1
ER  -

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Author Information

Thomas Mageto

Department of Statistics and Actuarial Science, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Efron Njuguna

Department of Statistics and Actuarial Science, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Dolleen Osundwa

Department of Statistics and Actuarial Science, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya

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APA Style

Thomas Mageto, Efron Njuguna, Dolleen Osundwa. (2018). Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016). Science Journal of Applied Mathematics and Statistics, 6(1), 7-15. https://doi.org/10.11648/j.sjams.20180601.12

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ACS Style

Thomas Mageto; Efron Njuguna; Dolleen Osundwa. Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016). Sci. J. Appl. Math. Stat. 2018, 6(1), 7-15. doi: 10.11648/j.sjams.20180601.12

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AMA Style

Thomas Mageto, Efron Njuguna, Dolleen Osundwa. Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016). Sci J Appl Math Stat. 2018;6(1):7-15. doi: 10.11648/j.sjams.20180601.12

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@article{10.11648/j.sjams.20180601.12,
  author = {Thomas Mageto and Efron Njuguna and Dolleen Osundwa},
  title = {Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016)},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {6},
  number = {1},
  pages = {7-15},
  doi = {10.11648/j.sjams.20180601.12},
  url = {https://doi.org/10.11648/j.sjams.20180601.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20180601.12},
  abstract = {This study sought to model risk factors of diabetes (A case study of Focus Medical Center in Kiambu, Kenya) for the year 2016. We considered sample of size 181 patients and carried descriptive statistics, bivariate analysis, Chi-Square test and Hosmer and Lemeshow test. The independence test between response variable (diabetes) and predictor variables (age, obesity, alcohol, smoking and hypertension) was carried. The variables age, obesity, alcohol and hypertension were found to be statistically significant at α =0.05 level of significant. A multiple logistic regression model was fitted and the fitted regression model indicated that the predictor variables age, obesity and alcohol were statistically significant. The results of the odds ratios show that age, obesity and alcohol consumption are positively associated with diabetes. The fitted reduced multiple logistic regression model was subjected to an overall goodness-of-fit test and results indicate that there is no significant difference between the observed and predicted probability. Based on the results of this study, we recommend that special attention should be given to individuals advanced in age, consume alcohol or who are obese for screening as there is a high possibility of testing positive for diabetes for health care givers to monitor and manage the condition. Further, healthy lifestyles should be promoted among the general population and in particular, the diabetic patients to increase the chance of properly managing the condition. A further study ought to be conducted to assess treatment interventions of diabetes to ascertain the effectiveness and recommend the best medication for patients suffering from diabetes.},
 year = {2018}
}

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TY  - JOUR
T1  - Modeling Diabetes Risk Factors (A Case Study of Focus Medical Centre in Kiambu, Kenya 2016)
AU  - Thomas Mageto
AU  - Efron Njuguna
AU  - Dolleen Osundwa
Y1  - 2018/01/31
PY  - 2018
N1  - https://doi.org/10.11648/j.sjams.20180601.12
DO  - 10.11648/j.sjams.20180601.12
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 7
EP  - 15
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20180601.12
AB  - This study sought to model risk factors of diabetes (A case study of Focus Medical Center in Kiambu, Kenya) for the year 2016. We considered sample of size 181 patients and carried descriptive statistics, bivariate analysis, Chi-Square test and Hosmer and Lemeshow test. The independence test between response variable (diabetes) and predictor variables (age, obesity, alcohol, smoking and hypertension) was carried. The variables age, obesity, alcohol and hypertension were found to be statistically significant at α =0.05 level of significant. A multiple logistic regression model was fitted and the fitted regression model indicated that the predictor variables age, obesity and alcohol were statistically significant. The results of the odds ratios show that age, obesity and alcohol consumption are positively associated with diabetes. The fitted reduced multiple logistic regression model was subjected to an overall goodness-of-fit test and results indicate that there is no significant difference between the observed and predicted probability. Based on the results of this study, we recommend that special attention should be given to individuals advanced in age, consume alcohol or who are obese for screening as there is a high possibility of testing positive for diabetes for health care givers to monitor and manage the condition. Further, healthy lifestyles should be promoted among the general population and in particular, the diabetic patients to increase the chance of properly managing the condition. A further study ought to be conducted to assess treatment interventions of diabetes to ascertain the effectiveness and recommend the best medication for patients suffering from diabetes.
VL  - 6
IS  - 1
ER  -

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