Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya)

Thomas Mageto; Allan Zablon

doi:doi:10.11648/j.ajtas.20180702.12

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Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya)

Thomas Mageto, Allan Zablon

Published in American Journal of Theoretical and Applied Statistics (Volume 7, Issue 2)

Received: 15 January 2018 Accepted: 29 January 2018 Published: 27 February 2018

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Abstract

In this paper self-medication risk factors are investigated and multivariate model proposed. A random sample of four major hospitals was selected, one from each sub-county and sample of 728 patients selected from selected hospitals using stratified random sampling. The data was collected using semi structured questionnaires and analyzed in R program after cleaning for non-response. Preliminary analysis was carried to check for statistical significance of the risk factors of age, gender, income, marital, education, employment and insurance status. All proposed risk factors were statistically significant except employment factor when using chi-square test for each of discrete variables while both age and income continuous variables were significant at α =0.05 level of significance when fitting simple logistic regression model. The initial multivariate logistic regression model was fitted and variables of marital and insurance status of persons were statistically insignificant and therefore improved model was fitted less marital and insurance factors. The overall significance of the model was determined using Hosmer and Lemeshow goodness-of-fit test and the model recorded p-value of 0.7751 that indicates that there is no significant difference between observed and predicted probability, therefore the model would be used to predict chance of self-medication in the presence of significant risk factors. In conclusion therefore there is need to initiate legislation on policies that will guide self-medication that include provision of necessary knowledge and regulating the practice to avoid over dose, wrong prescriptions and emergence of human pathogen resistance microorganisms or serious consequences like resistance to medication in future guided by the prevalence results obtained from proposed model.

Published in	American Journal of Theoretical and Applied Statistics (Volume 7, Issue 2)
DOI	10.11648/j.ajtas.20180702.12
Page(s)	58-66
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

Medication, Prevalence, Multivariate Logistic Regression, Risk Factors, Chi-Square and Goodness-of-Fit

References

[1]	Nuha, M. A. Agabna, A. Osman Awatif and A. Alsaddig Rand, (2014). Self-medication. Sudan Journal of Rational Use of Medicine 6: 4-6.
[2]	Hermandez-Juyol, M. and J. R. Job-Quesada, (2002). Dentistry and self-medication: A current challange. Medicina Oral 7(5):344-7.
[3]	Darshan, Bennadi, (2014). Self-medication: A current challenge. Jounal of Basic and Clinical Pharmacy. 5(1): 19-23.
[4]	Jessica, Flanigan. (2012). Three arguments against prescription requirements. Journal of Medical Ethics.
[5]	Pankaj, Jain, et al. (2012). Statistical Study on Self Medication Pattern in Haryana, India. Indo Global Journal of Pharmaceutical Sciences: 2(1): 21-35.
[6]	Vidyavati, S. D., et al. (2016). Self Medication Reasons, Risks and Benefits. International Journal of Healthcare and Biomedical Research 4:21-24.
[7]	Kiyingi, K. S. and J. A. K. Lauwo, (1993). Drugs in Home: Danger and Waste. World Health Forum: 14: 381-384.
[8]	Vidyavati, S. D., et al. (2016). Self Medication Reasons, Risks and Benefits. International Journal of Healthcare and Biomedical Research 4:21-24.
[9]	Hughes, C., J. McElnary and G. Fleming (2001).. Benefits and Risks of Self Medication. Drug Saf 24:1027-37.
[10]	Ferney-Voltaire, Franc (2006). World Self-Medication Industry. Responsible Self-Care and Self-Medication. A Worldwide Review of Consumer Surveys.
[11]	El-Nimr, N. A., et al. (2015). Self-medication with drugs and complementary and alternative medicines in Alexandria, Egypt: prevalence, patterns and determinants. Eastern Mediterranean Health Journal 21(4).
[12]	Remington, T. L., et al. (2006). Handbook of Nonprescription Drugs: An Interactive Approach to Self Care. Washington DC: American Pharmacists Association pp. 66-90.
[13]	Osemene, K. P. and A. Lamikanra. (2012). A study of the Prevalence of Self-medication Practice among University Students in Sourthwest Nigeria. Tropical Journal of Pharmaceutical Research 11(4): 683-689.
[14]	Robert, V. Krejcie and W. Morgan Daryle, (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30, 607-610.

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APA Style

Thomas Mageto, Allan Zablon. (2018). Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya). American Journal of Theoretical and Applied Statistics, 7(2), 58-66. https://doi.org/10.11648/j.ajtas.20180702.12

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ACS Style

Thomas Mageto; Allan Zablon. Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya). Am. J. Theor. Appl. Stat. 2018, 7(2), 58-66. doi: 10.11648/j.ajtas.20180702.12

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AMA Style

Thomas Mageto, Allan Zablon. Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya). Am J Theor Appl Stat. 2018;7(2):58-66. doi: 10.11648/j.ajtas.20180702.12

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@article{10.11648/j.ajtas.20180702.12,
  author = {Thomas Mageto and Allan Zablon},
  title = {Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya)},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {7},
  number = {2},
  pages = {58-66},
  doi = {10.11648/j.ajtas.20180702.12},
  url = {https://doi.org/10.11648/j.ajtas.20180702.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20180702.12},
  abstract = {In this paper self-medication risk factors are investigated and multivariate model proposed. A random sample of four major hospitals was selected, one from each sub-county and sample of 728 patients selected from selected hospitals using stratified random sampling. The data was collected using semi structured questionnaires and analyzed in R program after cleaning for non-response. Preliminary analysis was carried to check for statistical significance of the risk factors of age, gender, income, marital, education, employment and insurance status. All proposed risk factors were statistically significant except employment factor when using chi-square test for each of discrete variables while both age and income continuous variables were significant at α =0.05 level of significance when fitting simple logistic regression model. The initial multivariate logistic regression model was fitted and variables of marital and insurance status of persons were statistically insignificant and therefore improved model was fitted less marital and insurance factors. The overall significance of the model was determined using Hosmer and Lemeshow goodness-of-fit test and the model recorded p-value of 0.7751 that indicates that there is no significant difference between observed and predicted probability, therefore the model would be used to predict chance of self-medication in the presence of significant risk factors. In conclusion therefore there is need to initiate legislation on policies that will guide self-medication that include provision of necessary knowledge and regulating the practice to avoid over dose, wrong prescriptions and emergence of human pathogen resistance microorganisms or serious consequences like resistance to medication in future guided by the prevalence results obtained from proposed model.},
 year = {2018}
}

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TY  - JOUR
T1  - Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya)
AU  - Thomas Mageto
AU  - Allan Zablon
Y1  - 2018/02/27
PY  - 2018
N1  - https://doi.org/10.11648/j.ajtas.20180702.12
DO  - 10.11648/j.ajtas.20180702.12
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 58
EP  - 66
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20180702.12
AB  - In this paper self-medication risk factors are investigated and multivariate model proposed. A random sample of four major hospitals was selected, one from each sub-county and sample of 728 patients selected from selected hospitals using stratified random sampling. The data was collected using semi structured questionnaires and analyzed in R program after cleaning for non-response. Preliminary analysis was carried to check for statistical significance of the risk factors of age, gender, income, marital, education, employment and insurance status. All proposed risk factors were statistically significant except employment factor when using chi-square test for each of discrete variables while both age and income continuous variables were significant at α =0.05 level of significance when fitting simple logistic regression model. The initial multivariate logistic regression model was fitted and variables of marital and insurance status of persons were statistically insignificant and therefore improved model was fitted less marital and insurance factors. The overall significance of the model was determined using Hosmer and Lemeshow goodness-of-fit test and the model recorded p-value of 0.7751 that indicates that there is no significant difference between observed and predicted probability, therefore the model would be used to predict chance of self-medication in the presence of significant risk factors. In conclusion therefore there is need to initiate legislation on policies that will guide self-medication that include provision of necessary knowledge and regulating the practice to avoid over dose, wrong prescriptions and emergence of human pathogen resistance microorganisms or serious consequences like resistance to medication in future guided by the prevalence results obtained from proposed model.
VL  - 7
IS  - 2
ER  -

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Author Information

Thomas Mageto

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

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

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APA Style

Thomas Mageto, Allan Zablon. (2018). Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya). American Journal of Theoretical and Applied Statistics, 7(2), 58-66. https://doi.org/10.11648/j.ajtas.20180702.12

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ACS Style

Thomas Mageto; Allan Zablon. Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya). Am. J. Theor. Appl. Stat. 2018, 7(2), 58-66. doi: 10.11648/j.ajtas.20180702.12

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AMA Style

Thomas Mageto, Allan Zablon. Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya). Am J Theor Appl Stat. 2018;7(2):58-66. doi: 10.11648/j.ajtas.20180702.12

Copy | Download

@article{10.11648/j.ajtas.20180702.12,
  author = {Thomas Mageto and Allan Zablon},
  title = {Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya)},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {7},
  number = {2},
  pages = {58-66},
  doi = {10.11648/j.ajtas.20180702.12},
  url = {https://doi.org/10.11648/j.ajtas.20180702.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20180702.12},
  abstract = {In this paper self-medication risk factors are investigated and multivariate model proposed. A random sample of four major hospitals was selected, one from each sub-county and sample of 728 patients selected from selected hospitals using stratified random sampling. The data was collected using semi structured questionnaires and analyzed in R program after cleaning for non-response. Preliminary analysis was carried to check for statistical significance of the risk factors of age, gender, income, marital, education, employment and insurance status. All proposed risk factors were statistically significant except employment factor when using chi-square test for each of discrete variables while both age and income continuous variables were significant at α =0.05 level of significance when fitting simple logistic regression model. The initial multivariate logistic regression model was fitted and variables of marital and insurance status of persons were statistically insignificant and therefore improved model was fitted less marital and insurance factors. The overall significance of the model was determined using Hosmer and Lemeshow goodness-of-fit test and the model recorded p-value of 0.7751 that indicates that there is no significant difference between observed and predicted probability, therefore the model would be used to predict chance of self-medication in the presence of significant risk factors. In conclusion therefore there is need to initiate legislation on policies that will guide self-medication that include provision of necessary knowledge and regulating the practice to avoid over dose, wrong prescriptions and emergence of human pathogen resistance microorganisms or serious consequences like resistance to medication in future guided by the prevalence results obtained from proposed model.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - Modeling Self Medication Risk Factors (A Case Study of Kiambu County, Kenya)
AU  - Thomas Mageto
AU  - Allan Zablon
Y1  - 2018/02/27
PY  - 2018
N1  - https://doi.org/10.11648/j.ajtas.20180702.12
DO  - 10.11648/j.ajtas.20180702.12
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 58
EP  - 66
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20180702.12
AB  - In this paper self-medication risk factors are investigated and multivariate model proposed. A random sample of four major hospitals was selected, one from each sub-county and sample of 728 patients selected from selected hospitals using stratified random sampling. The data was collected using semi structured questionnaires and analyzed in R program after cleaning for non-response. Preliminary analysis was carried to check for statistical significance of the risk factors of age, gender, income, marital, education, employment and insurance status. All proposed risk factors were statistically significant except employment factor when using chi-square test for each of discrete variables while both age and income continuous variables were significant at α =0.05 level of significance when fitting simple logistic regression model. The initial multivariate logistic regression model was fitted and variables of marital and insurance status of persons were statistically insignificant and therefore improved model was fitted less marital and insurance factors. The overall significance of the model was determined using Hosmer and Lemeshow goodness-of-fit test and the model recorded p-value of 0.7751 that indicates that there is no significant difference between observed and predicted probability, therefore the model would be used to predict chance of self-medication in the presence of significant risk factors. In conclusion therefore there is need to initiate legislation on policies that will guide self-medication that include provision of necessary knowledge and regulating the practice to avoid over dose, wrong prescriptions and emergence of human pathogen resistance microorganisms or serious consequences like resistance to medication in future guided by the prevalence results obtained from proposed model.
VL  - 7
IS  - 2
ER  -

Copy | Download