Research Article
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Biomedical modelling through path analysis approach

Year 2024, Volume: 73 Issue: 3, 684 - 694, 27.09.2024
https://doi.org/10.31801/cfsuasmas.1328284

Abstract

Since blood disease markers are one of the most prevalent health problems in this era, the aim of this study is to forecast pathological subjects from a population through biomedical variables of individuals using the currently produced path analysis (PA) model. In terms of the dataset, 539 subjects were used to implement this study. A mathematical approach based on the PA has been used to create a reliable biomedical model in this research that investigates if there exists a relation between the various anemia types and the biomedical variables through observational variables (the blood variables, age, and sex) and anemia types. Other linear approaches were taken into consideration for comparison, in terms of $R^2$ value of the model, which has a value of 0.699. The findings reveal that the model has great predictive potential. It is believed that the developed model, which includes observational variables, will help healthcare providers predictively plan appropriate treatment programs for their patients.

Thanks

The authors would like to many thanks to the editors of the journal.

References

  • Narwal, Y., Rathee, S., Fractional order mathematical modeling of lumpy skin disease, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 73(1) (2024), 192-210. https://DOI:10.31801/cfsuasmas.1207144
  • Sari, M., Ahmad, A. A., Anemia modelling using the multiple regression analysis, International Journal of Analysis and Applications, 17(5) (2019), 838-49. https://doi.org/10.28924/2291-8639-17-2019-838
  • Sari, M., Ahmad, A. A., Uslu, H., Medical model estimation with particle swarm optimization, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 70(1) (2021), 468-82. https://DOI: 10.31801/cfsuasmas.644071
  • Malehi, A. S., Pourmotahari, F., Angali, K. A., Statistical models for the analysis of skewed healthcare cost data: a simulation study, Health Economics Review, 5(1) (2015), 11. https://doi.org/10.1186/s13561-015-0045-7
  • Liddell, C., Owusu-Brackett, N., Wallace, D., A mathematical model of sickle cell genome frequency in response to selective pressure from malaria, Bull. Math. Biol., 76 (2014), 2292-2305. https://DOI: 10.1007/s11538-014-9993-z
  • Li, X., Dao, M., Lykotrafitis, G., Karniadakis, G. E., Biomechanics and biorheology of red blood cells in sickle cell anemia, J. Biomech., 50 (2017), 34-41. https://doi.org/10.1016/j.jbiomech.2016.11.022
  • Kim, A., Rivera, S., Shprung, D., Limbrick, D., Gabayan, V., Nemeth, E., Ganz, T., Mouse models of anemia of cancer, PLoS One, 9 (2014), e93283. https://doi.org/10.1371/ journal.pone.0093283
  • Sirachainan, N., Iamsirirak, P., Charoenkwan, P., Kadegasem, P., Wongwerawattanakoon, P., Sasanakul, W., Chansatitporn, N., Chuansumrit, A., New mathematical formula for differentiating thalassemia trait and iron deficiency anemia in thalassemia prevalent area: a study in healthy school-age children, Southeast Asian J Trop. Med. Public. Health., 45 (2014), 174.
  • Roth, I. L., Lachover, B., Koren, G., Levin, C., Zalman, L., Koren, A., Detection of β -thalassemia carriers by red cell parameters obtained from automatic counters using mathematical formulas, Mediterr. J Hematol. Infect. Dis., (2018), 10. https://doi:10.4084/MJHID.2018.008
  • Ngwira, A., Kazembe, L. N., Analysis of severity of childhood anemia in Malawi: a Bayesian ordered categories model, Open Access Medical Statistics, 6 (2016), 9-20. https://doi.org/10.2147/OAMS.S95159
  • Jimenez, C. V., Iron-deficiency anemia and thalassemia trait differentiated by simple hematological tests and serum iron concentrations, Clin. Chem., 39 (1993), 2271-2275.
  • Soleimani, N., Relationship between anaemia, caused from the iron deficiency, and academic achievement among third grade high school female students, Procedia-Soc. Behav. Sci., 29 (2011), 1877-1884. https://doi.org/10.1016/j.sbspro.2011.11.437
  • Piplani, S., Madaan, M., Mannan, R., Manjari, M., Singh, T., Lalit, M., Evaluation of various discrimination indices in differentiating Iron deficiency anemia and Beta Thalassemia trait: A practical low cost solution, Annals of Pathology and Laboratory Medicine, 3 (2016), A551-559.
  • De La Fuente, J., A path analysis model of protection and risk factors for university academic stress: analysis and psychoeducational implications for the COVID-19 emergency, Frontiers in Psychology, 13(12) (2021), 562372. https://doi.org/10.3389/fpsyg.2021.562372
  • Zhou, Y., Ding, Y., Guo, M., Path analysis method in an epidemic model and stability analysis, Frontiers in Physics, 11 (2023), 1158814. https://doi.org/10.3389/fphy.2023.1158814
  • Ortiz, R. M., Rodriguez, R., Depaoli, S., Weffer, S. E., Increased physical activity reduces the odds of elevated systolic blood pressure independent of body mass or ethnicity in rural adolescents, J Hypertens, 3(3) (2014), 1-8. https://DOI:10.4172/2167-1095.1000150
  • Cohen, C., Einav, M., Hawlena, H., Path analyses of cross-sectional and longitudinal data suggest that variability in natural communities of blood-associated parasites is derived from host characteristics and not interspecific interactions, Parasites & Vectors, 8(1) (2015), 429. https://doi: 10.1186/s13071-015-1029-5
  • Masser, B. M., White, K. M., Hyde, M. K., Terry, D. J., Robinson, N. G., Predicting blood donation intentions and behavior among Australian blood donors: testing an extended theory of planned behavior model, Transfusion, 49(2) (2009), 320-9. https://doi.org/10.1111/j.1537-2995.2008.01981.x
  • Suh, Y. J., Lee, J. E., Lee, D. H., Yi, H. G., Lee, M. H., Kim, C. S., Nah, J. W., Kim, S. K., Prevalence and relationships of iron deficiency anemia with blood cadmium and vitamin D levels in Korean women, Journal of Korean medical science, 31(1) (2016), 25-32. https://doi:10.3346/jkms.2016.31.1.25
  • Kamran, A., Azadbakht, L., Sharifirad, G., Mahaki, B., Mohebi, S., The relationship between blood pressure and the structures of Pender’s health promotion model in rural hypertensive patients, Journal of education and health promotion, 4 (2015). https://doi: 10.4103/2277-9531.154124
  • van den Berg, J. J., Neilands, T. B., Johnson, M. O., Chen, B., Saberi, P., Using path analysis to evaluate the healthcare empowerment model among persons living with HIV for antiretroviral therapy adherence, AIDS patient care and STDs, 30(11) (2016), 497-505. https://doi: 10.1089/apc.2016.0159
  • World Health Organization. Worldwide Prevalence of Anaemia 1993-2005: WHO Global Database on Anaemia, (2008). https://www.who.int/publications/i/item/9789241596657
  • Hebert, P. C., Wells, G., Blajchman, M. A., Marshall, J., Martin, C., Pagliarello, G., Tweeddale, M., Schweitzer, I., Yetisir, E., A multicenter, randomized, controlled clinical trial of transfusion requirements in critical care, N. Engl. J Med., 340 (1999), 409-417. https://doi:10.1056/NEJM199902113400601
  • Ahmad, A. A., Sari, M., Parameter estimation to an anemia model using the particle swarm optimization, Sigma: Journal of Engineering & Natural Sciences, 37(4) (2019), 1331-1343.
  • Streiner, D. L., Finding our way: an introduction to path analysis, The Canadian Journal of Psychiatry, 50(2) (2015), 115-22. https://doi.org/10.1177/070674370505000207
  • Rondanelli, M., Perna, S., Alalwan, T., A., Cazzola, R., Gasparri, C., Infantino, V., Perdoni, F., Iannello, G., Pepe, D., Guido, D., A structural equation model to assess the pathways of body adiposity and inflammation status on dysmetabolic biomarkers via red cell distribution width and mean corpuscular volume: a cross-sectional study in overweight and obese subjects, Lipids in Health and Disease, 19 (2020), 1-1. https://doi.org/10.1186/s12944-020-01308-5
  • Mohammed, S. J., Ahmed, A. A., Ahmad, A. A., Mohammed, M. S., Anemia prediction based on rule classification, In 2020 13th International Conference on Developments in eSystems Engineering (DeSE) IEEE, (2020), 427-431. https://DOI: 10.1109/DeSE51703.2020.9450234
  • Nguyen, P. H., Scott, S., Avula, R., Tran, L. M., Menon, P., Trends and drivers of change in the prevalence of anaemia among 1 million women and children in India, 2006 to 2016, BMJ global health, 3 (2018), e001010. https://doi.org/10.1136/bmjgh-2018-001010
  • Kawo, K. N., Asfaw, Z. G., Yohannes, N., Multilevel analysis of determinants of anemia prevalence among children aged 6–59 months in ethiopia: classical and bayesian approaches, Anemia, (2018). https://doi.org/10.1155/2018/3087354
  • Reso, M. C., Dewi, Y. L., Budihastuti, U. R., Path analysis on the biological and socialeconomic determinants of anemia in pregnant mothers in bantul, yogyakarta, Journal of Maternal and Child Health, 4(6) (2019), 415-26. https://DOI:10.26911/thejmch.2019.04.06.03
  • Little, M., Zivot, C., Humphries, S., Dodd, W., Patel, K., Dewey, C., Burden and determinants of anemia in a rural population in South India: a cross-sectional study, Anemia, 2018. https://doi.org/10.1155/2018/7123976
  • Huang, X. Z., Yang, Y. C., Chen, Y., Wu, C. C., Lin, R. F., Wang, Z. N., Zhang, X., Preoperative anemia or low hemoglobin predicts poor prognosis in gastric cancer patients: a meta-analysis, Dis. Markers, (2019). https://doi: 10.1155/2019/7606128
  • Ahmad, A. A., Sari, M., Anemia prediction with multiple regression support in system medicinal internet of things, Journal of Medical Imaging and Health Informatics, 10(1) (2020), 261-7. https://doi.org/10.1166/jmihi.2020.2839
  • Ahmad, A. A., Alzaidi, K., Sari, M., Uslu, H., Prediction of anemia with a particle swarm optimization-based approach, An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 13(2) (2023). https://DOI: 10.11121/ijocta.2023.1269
Year 2024, Volume: 73 Issue: 3, 684 - 694, 27.09.2024
https://doi.org/10.31801/cfsuasmas.1328284

Abstract

References

  • Narwal, Y., Rathee, S., Fractional order mathematical modeling of lumpy skin disease, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 73(1) (2024), 192-210. https://DOI:10.31801/cfsuasmas.1207144
  • Sari, M., Ahmad, A. A., Anemia modelling using the multiple regression analysis, International Journal of Analysis and Applications, 17(5) (2019), 838-49. https://doi.org/10.28924/2291-8639-17-2019-838
  • Sari, M., Ahmad, A. A., Uslu, H., Medical model estimation with particle swarm optimization, Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 70(1) (2021), 468-82. https://DOI: 10.31801/cfsuasmas.644071
  • Malehi, A. S., Pourmotahari, F., Angali, K. A., Statistical models for the analysis of skewed healthcare cost data: a simulation study, Health Economics Review, 5(1) (2015), 11. https://doi.org/10.1186/s13561-015-0045-7
  • Liddell, C., Owusu-Brackett, N., Wallace, D., A mathematical model of sickle cell genome frequency in response to selective pressure from malaria, Bull. Math. Biol., 76 (2014), 2292-2305. https://DOI: 10.1007/s11538-014-9993-z
  • Li, X., Dao, M., Lykotrafitis, G., Karniadakis, G. E., Biomechanics and biorheology of red blood cells in sickle cell anemia, J. Biomech., 50 (2017), 34-41. https://doi.org/10.1016/j.jbiomech.2016.11.022
  • Kim, A., Rivera, S., Shprung, D., Limbrick, D., Gabayan, V., Nemeth, E., Ganz, T., Mouse models of anemia of cancer, PLoS One, 9 (2014), e93283. https://doi.org/10.1371/ journal.pone.0093283
  • Sirachainan, N., Iamsirirak, P., Charoenkwan, P., Kadegasem, P., Wongwerawattanakoon, P., Sasanakul, W., Chansatitporn, N., Chuansumrit, A., New mathematical formula for differentiating thalassemia trait and iron deficiency anemia in thalassemia prevalent area: a study in healthy school-age children, Southeast Asian J Trop. Med. Public. Health., 45 (2014), 174.
  • Roth, I. L., Lachover, B., Koren, G., Levin, C., Zalman, L., Koren, A., Detection of β -thalassemia carriers by red cell parameters obtained from automatic counters using mathematical formulas, Mediterr. J Hematol. Infect. Dis., (2018), 10. https://doi:10.4084/MJHID.2018.008
  • Ngwira, A., Kazembe, L. N., Analysis of severity of childhood anemia in Malawi: a Bayesian ordered categories model, Open Access Medical Statistics, 6 (2016), 9-20. https://doi.org/10.2147/OAMS.S95159
  • Jimenez, C. V., Iron-deficiency anemia and thalassemia trait differentiated by simple hematological tests and serum iron concentrations, Clin. Chem., 39 (1993), 2271-2275.
  • Soleimani, N., Relationship between anaemia, caused from the iron deficiency, and academic achievement among third grade high school female students, Procedia-Soc. Behav. Sci., 29 (2011), 1877-1884. https://doi.org/10.1016/j.sbspro.2011.11.437
  • Piplani, S., Madaan, M., Mannan, R., Manjari, M., Singh, T., Lalit, M., Evaluation of various discrimination indices in differentiating Iron deficiency anemia and Beta Thalassemia trait: A practical low cost solution, Annals of Pathology and Laboratory Medicine, 3 (2016), A551-559.
  • De La Fuente, J., A path analysis model of protection and risk factors for university academic stress: analysis and psychoeducational implications for the COVID-19 emergency, Frontiers in Psychology, 13(12) (2021), 562372. https://doi.org/10.3389/fpsyg.2021.562372
  • Zhou, Y., Ding, Y., Guo, M., Path analysis method in an epidemic model and stability analysis, Frontiers in Physics, 11 (2023), 1158814. https://doi.org/10.3389/fphy.2023.1158814
  • Ortiz, R. M., Rodriguez, R., Depaoli, S., Weffer, S. E., Increased physical activity reduces the odds of elevated systolic blood pressure independent of body mass or ethnicity in rural adolescents, J Hypertens, 3(3) (2014), 1-8. https://DOI:10.4172/2167-1095.1000150
  • Cohen, C., Einav, M., Hawlena, H., Path analyses of cross-sectional and longitudinal data suggest that variability in natural communities of blood-associated parasites is derived from host characteristics and not interspecific interactions, Parasites & Vectors, 8(1) (2015), 429. https://doi: 10.1186/s13071-015-1029-5
  • Masser, B. M., White, K. M., Hyde, M. K., Terry, D. J., Robinson, N. G., Predicting blood donation intentions and behavior among Australian blood donors: testing an extended theory of planned behavior model, Transfusion, 49(2) (2009), 320-9. https://doi.org/10.1111/j.1537-2995.2008.01981.x
  • Suh, Y. J., Lee, J. E., Lee, D. H., Yi, H. G., Lee, M. H., Kim, C. S., Nah, J. W., Kim, S. K., Prevalence and relationships of iron deficiency anemia with blood cadmium and vitamin D levels in Korean women, Journal of Korean medical science, 31(1) (2016), 25-32. https://doi:10.3346/jkms.2016.31.1.25
  • Kamran, A., Azadbakht, L., Sharifirad, G., Mahaki, B., Mohebi, S., The relationship between blood pressure and the structures of Pender’s health promotion model in rural hypertensive patients, Journal of education and health promotion, 4 (2015). https://doi: 10.4103/2277-9531.154124
  • van den Berg, J. J., Neilands, T. B., Johnson, M. O., Chen, B., Saberi, P., Using path analysis to evaluate the healthcare empowerment model among persons living with HIV for antiretroviral therapy adherence, AIDS patient care and STDs, 30(11) (2016), 497-505. https://doi: 10.1089/apc.2016.0159
  • World Health Organization. Worldwide Prevalence of Anaemia 1993-2005: WHO Global Database on Anaemia, (2008). https://www.who.int/publications/i/item/9789241596657
  • Hebert, P. C., Wells, G., Blajchman, M. A., Marshall, J., Martin, C., Pagliarello, G., Tweeddale, M., Schweitzer, I., Yetisir, E., A multicenter, randomized, controlled clinical trial of transfusion requirements in critical care, N. Engl. J Med., 340 (1999), 409-417. https://doi:10.1056/NEJM199902113400601
  • Ahmad, A. A., Sari, M., Parameter estimation to an anemia model using the particle swarm optimization, Sigma: Journal of Engineering & Natural Sciences, 37(4) (2019), 1331-1343.
  • Streiner, D. L., Finding our way: an introduction to path analysis, The Canadian Journal of Psychiatry, 50(2) (2015), 115-22. https://doi.org/10.1177/070674370505000207
  • Rondanelli, M., Perna, S., Alalwan, T., A., Cazzola, R., Gasparri, C., Infantino, V., Perdoni, F., Iannello, G., Pepe, D., Guido, D., A structural equation model to assess the pathways of body adiposity and inflammation status on dysmetabolic biomarkers via red cell distribution width and mean corpuscular volume: a cross-sectional study in overweight and obese subjects, Lipids in Health and Disease, 19 (2020), 1-1. https://doi.org/10.1186/s12944-020-01308-5
  • Mohammed, S. J., Ahmed, A. A., Ahmad, A. A., Mohammed, M. S., Anemia prediction based on rule classification, In 2020 13th International Conference on Developments in eSystems Engineering (DeSE) IEEE, (2020), 427-431. https://DOI: 10.1109/DeSE51703.2020.9450234
  • Nguyen, P. H., Scott, S., Avula, R., Tran, L. M., Menon, P., Trends and drivers of change in the prevalence of anaemia among 1 million women and children in India, 2006 to 2016, BMJ global health, 3 (2018), e001010. https://doi.org/10.1136/bmjgh-2018-001010
  • Kawo, K. N., Asfaw, Z. G., Yohannes, N., Multilevel analysis of determinants of anemia prevalence among children aged 6–59 months in ethiopia: classical and bayesian approaches, Anemia, (2018). https://doi.org/10.1155/2018/3087354
  • Reso, M. C., Dewi, Y. L., Budihastuti, U. R., Path analysis on the biological and socialeconomic determinants of anemia in pregnant mothers in bantul, yogyakarta, Journal of Maternal and Child Health, 4(6) (2019), 415-26. https://DOI:10.26911/thejmch.2019.04.06.03
  • Little, M., Zivot, C., Humphries, S., Dodd, W., Patel, K., Dewey, C., Burden and determinants of anemia in a rural population in South India: a cross-sectional study, Anemia, 2018. https://doi.org/10.1155/2018/7123976
  • Huang, X. Z., Yang, Y. C., Chen, Y., Wu, C. C., Lin, R. F., Wang, Z. N., Zhang, X., Preoperative anemia or low hemoglobin predicts poor prognosis in gastric cancer patients: a meta-analysis, Dis. Markers, (2019). https://doi: 10.1155/2019/7606128
  • Ahmad, A. A., Sari, M., Anemia prediction with multiple regression support in system medicinal internet of things, Journal of Medical Imaging and Health Informatics, 10(1) (2020), 261-7. https://doi.org/10.1166/jmihi.2020.2839
  • Ahmad, A. A., Alzaidi, K., Sari, M., Uslu, H., Prediction of anemia with a particle swarm optimization-based approach, An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 13(2) (2023). https://DOI: 10.11121/ijocta.2023.1269
There are 34 citations in total.

Details

Primary Language English
Subjects Applied Mathematics (Other)
Journal Section Research Articles
Authors

Arshed Ahmad 0000-0003-1393-1253

Murat Sarı 0000-0003-0508-2917

İbrahim Demir 0000-0002-2734-4116

Publication Date September 27, 2024
Submission Date July 16, 2023
Acceptance Date April 24, 2024
Published in Issue Year 2024 Volume: 73 Issue: 3

Cite

APA Ahmad, A., Sarı, M., & Demir, İ. (2024). Biomedical modelling through path analysis approach. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, 73(3), 684-694. https://doi.org/10.31801/cfsuasmas.1328284
AMA Ahmad A, Sarı M, Demir İ. Biomedical modelling through path analysis approach. Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat. September 2024;73(3):684-694. doi:10.31801/cfsuasmas.1328284
Chicago Ahmad, Arshed, Murat Sarı, and İbrahim Demir. “Biomedical Modelling through Path Analysis Approach”. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 73, no. 3 (September 2024): 684-94. https://doi.org/10.31801/cfsuasmas.1328284.
EndNote Ahmad A, Sarı M, Demir İ (September 1, 2024) Biomedical modelling through path analysis approach. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 73 3 684–694.
IEEE A. Ahmad, M. Sarı, and İ. Demir, “Biomedical modelling through path analysis approach”, Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat., vol. 73, no. 3, pp. 684–694, 2024, doi: 10.31801/cfsuasmas.1328284.
ISNAD Ahmad, Arshed et al. “Biomedical Modelling through Path Analysis Approach”. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics 73/3 (September 2024), 684-694. https://doi.org/10.31801/cfsuasmas.1328284.
JAMA Ahmad A, Sarı M, Demir İ. Biomedical modelling through path analysis approach. Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat. 2024;73:684–694.
MLA Ahmad, Arshed et al. “Biomedical Modelling through Path Analysis Approach”. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, vol. 73, no. 3, 2024, pp. 684-9, doi:10.31801/cfsuasmas.1328284.
Vancouver Ahmad A, Sarı M, Demir İ. Biomedical modelling through path analysis approach. Commun. Fac. Sci. Univ. Ank. Ser. A1 Math. Stat. 2024;73(3):684-9.

Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics.

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