Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach

Onuoha Chinyere Adaku; Nwakuya Maureen Tobechukwu; Ngobiri Nnaemeka Chinedu; Edache Bernard Ochekwu; Onuoha Philip

doi:doi:10.11648/j.aas.20230801.14

| Peer-Reviewed

Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach

Onuoha Chinyere Adaku, Nwakuya Maureen Tobechukwu, Ngobiri Nnaemeka Chinedu, Edache Bernard Ochekwu, Onuoha Philip

Published in Advances in Applied Sciences (Volume 8, Issue 1)

Received: 10 February 2023 Accepted: 25 February 2023 Published: 21 March 2023

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

This research was carried out among student in Nigerian schools. The logistic regression model and ordinal logistic model were fitted with Awareness to environmental issues (AEI) with two levels and Responsiveness to environmental issues (REI) with five levels as the response variable. The predictor variables are age, geographical zones, type of school and location of school. The fitted logistic regression was shown to be a good fit and the result revealed that the older the students the more responsive they are to environmental issues. The overall effect of zone and type of school were statistically significant though the type of school had a negative effect. The ordinal logistic regression was equally fitted and the results also show that the older the student the more aware they are of environmental issues. The result also shows that the zones, urban schools and students in senior secondary and university are associated with higher likelihood of being aware of environmental issues and these effects are significant. The summary of the results reveals that though there is awareness of environmental issues in Nigeria but responsiveness towards is very low among students. Hence, we recommend that courses on environmental issues and responsiveness towards them should be incorporated in the academic curriculum of students especially in the universities since age has a positive effect on both RIE and AEI.

Published in	Advances in Applied Sciences (Volume 8, Issue 1)
DOI	10.11648/j.aas.20230801.14
Page(s)	28-35
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), 2024. Published by Science Publishing Group

Keywords

Awareness to Environmental Issues, Responsiveness to Environmental Issues, Logistic Regression, Ordinal Logistic Regression

References

[1]	Agresti, A. (2002) Categorical Data Analysis, Second Edition. Hoboken, New Jersey: John Wiley & Sons, Inc.
[2]	Alzen, J. L., Langdon, L. S. & Otero, V. K. A (2018). logistic regression investigation of the relationship between the Learning Assistant model and failure rates in introductory STEM courses. IJ STEM Ed 5, 56. https://doi.org/10.1186/s40594-018-0152-1
[3]	Central Bank of Nigeria Bulletin Recorded (2021). Percentage of students’ population by geopolitical zone 2021. Under the report 50% of Nigeria are under 18 years.
[4]	Ennis D., Nwakuya T. M. and Biu O. E. (2022). Trend and Epidemiological Analysis of Coronavirus in Nigeria. Science Journal of Applied Mathematics and Statistics. Vol. 10 (1): 1-9. doi: 10.11648/j.sjams.20221001.11.
[5]	Fasano A. and Durante D, (2020). A class of conjugate priors for multinomial probit models which includes the multivariate normal one. https://arxiv.org/abs/2007.06944
[6]	Francis R. E. and Nwakuya M. T. (2022). Logistic Estimation Method in the Presence of Collinearity and It’s Application. International Journal of Data Science and Analysis; 8 (6): 187-193. doi: 10.11648/j.ijdsa.20220806.13.
[7]	Fullerton A. S. and Xu J., (2012). The proportional odds with partial proportionality constraints model for ordinal response variables. Social Science Research, vol. 41, no. 1, pp. 182–198.
[8]	Lelisho M. E., Wogi A. A. and Tareke S. A., (2022). Ordinal Logistic Regression Analysis in Determining Factors Associated with Socioeconomic Status of Household in Tepi Town, Southwest Ethiopia. The Scientific World Journal, vol. 2022, 9 pages, https://doi.org/10.1155/2022/2415692
[9]	Leukel, J., Özbek, G. and Sugumaran, V. (2022). Application of logistic regression to explain internet use among older adults: a review of the empirical literature. Univ Access Inf Soc. https://doi.org/10.1007/s10209-022-00960-1
[10]	Malhi Y., Franklin J., Seddon N., Solan N., Turner M. G., Field C. B. and Knowlton N., (2020). Climate change and ecosystems: threats, opportunities and solutions Phil. Trans. R. Soc. B 375 2019010420190104 http://doi.org/10.1098/rstb.2019.0104
[11]	McHugh M. L. (2009). The odds ratio: calculation, usage, and interpretation. Biochemia Medica, Vol. 19 (2): 120-126.
[12]	Nwakuya M. T. and Mmaduka M. (2019). Ordered Logistic Regression on the Mental Health of Undergraduate Students; International Journal of Probability and Statistics, Vol 8 (1), Pg 14-18.
[13]	Peng, C.-Y. J. (2016). Logistic Regression. In D. Wyse, E. Smith, L. E. Suter, and N. Selwyn (Eds.), The BERA/SAGE Handbook of Educational Research (Chapter 46). London: SAGE Publications; pp 1-2.
[14]	Scott M. Smith (2016). Determining Sample Size, How to Ensure You Get the Correct Sample Size. Qualties Enterprise Survey Technology Provider. www.qualtrics.com.
[15]	Singh, V., Dwivedi, S. N. & Deo, S. V. S. (2020). Ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation. BMC Med Res Methodol 20, 95. https://doi.org/10.1186/s12874-020-00985-1
[16]	Sperandei S. (2014). Understanding logistic regression analysis. Biochemia Medica (Zagreb); 15; 24 (1): 12-8. doi: 10.11613/BM.2014.003.
[17]	Wang Y, Sha Z, Tan X, Lan, H, Liu X, and Rao J, (2020). Modeling urban growth by coupling localized spatio-temporal association analysis and binary logistic regression. Computers, Environment and Urban Systems, vol. 81, Article ID 101482, 2020.

Cite This Article

Plain Text BibTeX RIS

APA Style

Onuoha Chinyere Adaku, Nwakuya Maureen Tobechukwu, Ngobiri Nnaemeka Chinedu, Edache Bernard Ochekwu, Onuoha Philip. (2023). Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach. Advances in Applied Sciences, 8(1), 28-35. https://doi.org/10.11648/j.aas.20230801.14

Copy | Download

ACS Style

Onuoha Chinyere Adaku; Nwakuya Maureen Tobechukwu; Ngobiri Nnaemeka Chinedu; Edache Bernard Ochekwu; Onuoha Philip. Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach. Adv. Appl. Sci. 2023, 8(1), 28-35. doi: 10.11648/j.aas.20230801.14

Copy | Download

AMA Style

Onuoha Chinyere Adaku, Nwakuya Maureen Tobechukwu, Ngobiri Nnaemeka Chinedu, Edache Bernard Ochekwu, Onuoha Philip. Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach. Adv Appl Sci. 2023;8(1):28-35. doi: 10.11648/j.aas.20230801.14

Copy | Download

@article{10.11648/j.aas.20230801.14,
  author = {Onuoha Chinyere Adaku and Nwakuya Maureen Tobechukwu and Ngobiri Nnaemeka Chinedu and Edache Bernard Ochekwu and Onuoha Philip},
  title = {Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach},
  journal = {Advances in Applied Sciences},
  volume = {8},
  number = {1},
  pages = {28-35},
  doi = {10.11648/j.aas.20230801.14},
  url = {https://doi.org/10.11648/j.aas.20230801.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aas.20230801.14},
  abstract = {This research was carried out among student in Nigerian schools. The logistic regression model and ordinal logistic model were fitted with Awareness to environmental issues (AEI) with two levels and Responsiveness to environmental issues (REI) with five levels as the response variable. The predictor variables are age, geographical zones, type of school and location of school. The fitted logistic regression was shown to be a good fit and the result revealed that the older the students the more responsive they are to environmental issues. The overall effect of zone and type of school were statistically significant though the type of school had a negative effect. The ordinal logistic regression was equally fitted and the results also show that the older the student the more aware they are of environmental issues. The result also shows that the zones, urban schools and students in senior secondary and university are associated with higher likelihood of being aware of environmental issues and these effects are significant. The summary of the results reveals that though there is awareness of environmental issues in Nigeria but responsiveness towards is very low among students. Hence, we recommend that courses on environmental issues and responsiveness towards them should be incorporated in the academic curriculum of students especially in the universities since age has a positive effect on both RIE and AEI.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach
AU  - Onuoha Chinyere Adaku
AU  - Nwakuya Maureen Tobechukwu
AU  - Ngobiri Nnaemeka Chinedu
AU  - Edache Bernard Ochekwu
AU  - Onuoha Philip
Y1  - 2023/03/21
PY  - 2023
N1  - https://doi.org/10.11648/j.aas.20230801.14
DO  - 10.11648/j.aas.20230801.14
T2  - Advances in Applied Sciences
JF  - Advances in Applied Sciences
JO  - Advances in Applied Sciences
SP  - 28
EP  - 35
PB  - Science Publishing Group
SN  - 2575-1514
UR  - https://doi.org/10.11648/j.aas.20230801.14
AB  - This research was carried out among student in Nigerian schools. The logistic regression model and ordinal logistic model were fitted with Awareness to environmental issues (AEI) with two levels and Responsiveness to environmental issues (REI) with five levels as the response variable. The predictor variables are age, geographical zones, type of school and location of school. The fitted logistic regression was shown to be a good fit and the result revealed that the older the students the more responsive they are to environmental issues. The overall effect of zone and type of school were statistically significant though the type of school had a negative effect. The ordinal logistic regression was equally fitted and the results also show that the older the student the more aware they are of environmental issues. The result also shows that the zones, urban schools and students in senior secondary and university are associated with higher likelihood of being aware of environmental issues and these effects are significant. The summary of the results reveals that though there is awareness of environmental issues in Nigeria but responsiveness towards is very low among students. Hence, we recommend that courses on environmental issues and responsiveness towards them should be incorporated in the academic curriculum of students especially in the universities since age has a positive effect on both RIE and AEI.
VL  - 8
IS  - 1
ER  -

Copy | Download

Author Information

Onuoha Chinyere Adaku

Institute of Natural Resources, Environment, and Sustainable Development, University of Port Harcourt, Port Harcourt, Nigeria
Nwakuya Maureen Tobechukwu

Department of Mathematics and Statistics, University of Port Harcourt, Port Harcourt, Nigeria
Ngobiri Nnaemeka Chinedu

Department of Pure and Industrial Chemistry, University of Port Harcourt, Port Harcourt, Nigeria
Edache Bernard Ochekwu

Department of Plant Science and Biotechnology, University of Port Harcourt, Port Harcourt, Nigeria
Onuoha Philip

Department of Nursing, University of West Indies, St. Augustine, Trinidad and Tobago

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Onuoha Chinyere Adaku, Nwakuya Maureen Tobechukwu, Ngobiri Nnaemeka Chinedu, Edache Bernard Ochekwu, Onuoha Philip. (2023). Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach. Advances in Applied Sciences, 8(1), 28-35. https://doi.org/10.11648/j.aas.20230801.14

Copy | Download

ACS Style

Onuoha Chinyere Adaku; Nwakuya Maureen Tobechukwu; Ngobiri Nnaemeka Chinedu; Edache Bernard Ochekwu; Onuoha Philip. Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach. Adv. Appl. Sci. 2023, 8(1), 28-35. doi: 10.11648/j.aas.20230801.14

Copy | Download

AMA Style

Onuoha Chinyere Adaku, Nwakuya Maureen Tobechukwu, Ngobiri Nnaemeka Chinedu, Edache Bernard Ochekwu, Onuoha Philip. Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach. Adv Appl Sci. 2023;8(1):28-35. doi: 10.11648/j.aas.20230801.14

Copy | Download

@article{10.11648/j.aas.20230801.14,
  author = {Onuoha Chinyere Adaku and Nwakuya Maureen Tobechukwu and Ngobiri Nnaemeka Chinedu and Edache Bernard Ochekwu and Onuoha Philip},
  title = {Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach},
  journal = {Advances in Applied Sciences},
  volume = {8},
  number = {1},
  pages = {28-35},
  doi = {10.11648/j.aas.20230801.14},
  url = {https://doi.org/10.11648/j.aas.20230801.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aas.20230801.14},
  abstract = {This research was carried out among student in Nigerian schools. The logistic regression model and ordinal logistic model were fitted with Awareness to environmental issues (AEI) with two levels and Responsiveness to environmental issues (REI) with five levels as the response variable. The predictor variables are age, geographical zones, type of school and location of school. The fitted logistic regression was shown to be a good fit and the result revealed that the older the students the more responsive they are to environmental issues. The overall effect of zone and type of school were statistically significant though the type of school had a negative effect. The ordinal logistic regression was equally fitted and the results also show that the older the student the more aware they are of environmental issues. The result also shows that the zones, urban schools and students in senior secondary and university are associated with higher likelihood of being aware of environmental issues and these effects are significant. The summary of the results reveals that though there is awareness of environmental issues in Nigeria but responsiveness towards is very low among students. Hence, we recommend that courses on environmental issues and responsiveness towards them should be incorporated in the academic curriculum of students especially in the universities since age has a positive effect on both RIE and AEI.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Awareness and Responsiveness to Environmental Issues by Youths: A Logistic Regression Approach
AU  - Onuoha Chinyere Adaku
AU  - Nwakuya Maureen Tobechukwu
AU  - Ngobiri Nnaemeka Chinedu
AU  - Edache Bernard Ochekwu
AU  - Onuoha Philip
Y1  - 2023/03/21
PY  - 2023
N1  - https://doi.org/10.11648/j.aas.20230801.14
DO  - 10.11648/j.aas.20230801.14
T2  - Advances in Applied Sciences
JF  - Advances in Applied Sciences
JO  - Advances in Applied Sciences
SP  - 28
EP  - 35
PB  - Science Publishing Group
SN  - 2575-1514
UR  - https://doi.org/10.11648/j.aas.20230801.14
AB  - This research was carried out among student in Nigerian schools. The logistic regression model and ordinal logistic model were fitted with Awareness to environmental issues (AEI) with two levels and Responsiveness to environmental issues (REI) with five levels as the response variable. The predictor variables are age, geographical zones, type of school and location of school. The fitted logistic regression was shown to be a good fit and the result revealed that the older the students the more responsive they are to environmental issues. The overall effect of zone and type of school were statistically significant though the type of school had a negative effect. The ordinal logistic regression was equally fitted and the results also show that the older the student the more aware they are of environmental issues. The result also shows that the zones, urban schools and students in senior secondary and university are associated with higher likelihood of being aware of environmental issues and these effects are significant. The summary of the results reveals that though there is awareness of environmental issues in Nigeria but responsiveness towards is very low among students. Hence, we recommend that courses on environmental issues and responsiveness towards them should be incorporated in the academic curriculum of students especially in the universities since age has a positive effect on both RIE and AEI.
VL  - 8
IS  - 1
ER  -

Copy | Download