Identifying determinants of waste management access in Nouakchott, Mauritania: a logistic regression model

被引:1
|
作者
Abdem, Seyid Abdellahi Ebnou [1 ]
Azmi, Rida [1 ]
Diop, El Bachir [1 ]
Adraoui, Meriem [1 ]
Chenal, Jerome [1 ,2 ]
机构
[1] Univ Mohammed VI Polytech UM6P, Ctr Urban Syst CUS, Benguerir, Morocco
[2] Ecole Polytech Fed Lausanne EPFL, Urban & Reg Planning Community CEAT, Lausanne, Switzerland
来源
DATA & POLICY | 2024年 / 6卷
关键词
environmental challenges; logistic regression; Mauritania; Nouakchott; sustainable development; waste management; SUB-SAHARAN AFRICA; SOCIOECONOMIC-FACTORS; CHALLENGES; GENERATION;
D O I
10.1017/dap.2024.22
中图分类号
C93 [管理学]; D035 [国家行政管理]; D523 [行政管理]; D63 [国家行政管理];
学科分类号
12 ; 1201 ; 1202 ; 120202 ; 1204 ; 120401 ;
摘要
Access to waste management services is crucial for urban sustainability, impacting public health, environmental wellbeing, and overall quality of life. This study employs logistic regression analysis on survey data collected from 1,032 household heads residing in Nouakchott, the capital of Mauritania. The survey investigated key household factors that determine access to waste management services. The findings reveal a significant interplay among waste service provision, the presence of cisterns, housing type and size, and access to electricity. Socioeconomic disparity in service access, with poorer housing formats like shacks receiving substandard services. In contrast, areas with robust electrification report better service access, although inconsistencies remain amid power outages. The research highlights the challenges faced by Riyadh municipality, particularly rapid growth and inadequate infrastructure, which hinder waste management efficiency. Overall, the results not only illuminate Nouakchott's unique challenges in service provision but also propose actionable recommendations for a sustainable urban future. These recommendations aim to inform and guide targeted policies for improving living conditions and environmental sustainability in urban Mauritania.
引用
收藏
页数:22
相关论文
共 50 条
  • [1] Using Logistic Regression to Predict Access to Essential Services: Electricity and Internet in Nouakchott, Mauritania
    Abdem, Seyid Abdellahi Ebnou
    Chenal, Jerome
    Diop, El Bachir
    Azmi, Rida
    Adraoui, Meriem
    Koumetio, Cedric Stephane Tekouabou
    SUSTAINABILITY, 2023, 15 (23)
  • [2] Exploring the Determinants of School Attendance in Mauritania: A Logistic Regression Analysis
    Dine, Mohamedou Nasser
    AFRICA EDUCATION REVIEW, 2022, 19 (4-6) : 47 - 58
  • [3] A logistic regression model to facilitate setting of organic waste composting policy for sustainable waste management
    Al-Sari', Majed Ibrahim
    Haritash, A. K.
    ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2024,
  • [4] A logistic regression model for the decision to perform access surgery
    Loesche, WJ
    Taylor, G
    Giordano, J
    Hutchinson, R
    Rau, CF
    Chen, YM
    Schork, MA
    JOURNAL OF CLINICAL PERIODONTOLOGY, 1997, 24 (03) : 171 - 179
  • [5] The Logistic Model for Decision Making in Waste Management
    Somplak, Radovan
    Prochazka, Vit
    Pavlas, Martin
    Popela, Pavel
    16TH INTERNATIONAL CONFERENCE ON PROCESS INTEGRATION, MODELLING AND OPTIMISATION FOR ENERGY SAVING AND POLLUTION REDUCTION (PRES'13), 2013, 35 : 817 - 822
  • [6] Determinants of access to trainings on post - harvest loss management among maize farmers in Uganda: a binary logistic regression approach
    Midamba, Dick Chune
    Kizito, Ogei
    COGENT ECONOMICS & FINANCE, 2022, 10 (01):
  • [7] A logistic regression analysis of the contractor's awareness regarding waste management
    Institute for Environment and Development , University Kebangsaan Malaysia, Bangi 43600 Selangor D.E., Malaysia
    不详
    J. Appl. Sci., 2006, 9 (1904-1908):
  • [8] Model for identifying apple juice authenticity based on binary logistic regression
    Su G.
    Gao H.
    Wang Z.
    Liao X.
    Zhang Y.
    Zhang M.
    Hu X.
    Wu J.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2011, 27 (06): : 349 - 356
  • [9] Logistic regression, segmentation modeling and governance choice in the waste management industry
    Delmas, M
    Ghertman, M
    Obadia, J
    STATISTICAL MODELS FOR STRATEGIC MANAGEMENT, 1997, : 261 - 277
  • [10] Identifying Social Group-wise Household-Level Determinants of Poverty in Rural Odisha Using Logistic Regression Model
    Bigyanananda Mohanty
    A. K. P. C. Swain
    Journal of Statistical Theory and Practice, 2019, 13