Impact of COVID-19 Lock-Downs on Nature Connection in Southern and Eastern Africa
Abstract
:1. Introduction
2. Materials and Methods
2.1. Survey Procedure
2.2. Survey Method and Statistical Analysis
3. Results
3.1. Comparative Changes in Perception and Behavior
3.2. Confirmatory Factor Analysis
3.3. Structural Equation Modeling for the Research Hypotheses
4. Discussion
4.1. Distancing from Nature during Lock-Down Measures
4.2. Perception of Recovery in Human Health in Nature during the COVID-19 Pandemic
4.3. Study Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Hypothesis: Direction | Malawi | Rwanda | South Africa | Tanzania | Zambia | ||
---|---|---|---|---|---|---|---|
H1a: Stress level → | Appreciation of urban forest | Estimate | 0.106 | 0.419 | 0.363 | 0.027 | 0.375 |
S.E. | 0.118 | 0.136 | 0.152 | 0.174 | 0.114 | ||
CR | 0.898 | 3.081 | 3.175 | 0.002 | 3.281 | ||
p | 0.497 | 0.002 | 0.001 | 0.998 | 0.001 | ||
Result | Reject | Accept | Accept | Reject | Accept | ||
H1b: Indoor activity → | Appreciation of urban forest | Estimate | 0.091 | 0.447 | 0.114 | 0.314 | 0.285 |
S.E. | 0.134 | 0.160 | 0.167 | 0.215 | 0.142 | ||
CR | 0.679 | 2.787 | 0.680 | 1.463 | 2.006 | ||
p | 0.497 | 0.005 | 0.496 | 0.143 | 0.045 | ||
Result | Reject | Accept | Reject | Reject | Accept | ||
H2: Appreciation of urban forest → | Perception of health recovery | Estimate | 0.454 | 0.571 | 0.563 | 0.067 | 0.402 |
S.E. | 0.172 | 0.155 | 0.177 | 0.082 | 0.097 | ||
CR | 2.647 | 3.695 | 3.175 | 0.812 | 4.123 | ||
p | 0.008 | 0.000 | 0.001 | 0.417 | 0.000 | ||
Result | Accept | Accept | Accept | Reject | Accept | ||
Model fit test | Chi2 | 119.963 | 64.672 | 130.390 | 151.270 | 140.689 | |
p-value | 0.000 | 0.079 | 0.000 | 0.000 | 0.000 | ||
GFI | 0.838 | 0.859 | 0.838 | 0.769 | 0.812 | ||
AGFI | 0.747 | 0.781 | 0.747 | 0.639 | 0.707 | ||
NFI | 0.780 | 0.848 | 0.774 | 0.722 | 0.810 | ||
IFI | 0.859 | 0.961 | 0.847 | 0.795 | 0.869 | ||
TLI | 0.807 | 0.946 | 0.792 | 0.720 | 0.822 | ||
CFI | 0.854 | 0.959 | 0.843 | 0.788 | 0.865 | ||
RMSEA | 0.122 | 0.048 | 0.052 | 0.167 | 0.057 |
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Country, Surveyed Area | Forested Area (% of Land Surface) | Population (×1000) | GDP Growth Rates | GDP/ People ($) | Survey Respondents | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Total (Pers.) | Female (%) | Age (%) | ||||||||||
′19 | ′20 | ′21 | ~29 | ~39 | ~49 | 50~ | ||||||
Malawi, Lilongwe | 22,417 sq.km (23.7%) | 19,129 | 5.5 | 0.9 | 2.2 | 636 | 95 | 46.3 | 29.5 | 43.2 | 25.3 | 2.1 |
Rwanda, Kigali | 2760 sq.km (11.1%) | 12,952 | 10.1 | 3.5 | 6.7 | 797 | 65 | 47.6 | 73.8 | 16.9 | 3.1 | 5.2 |
South Africa, Pretoria | 170,500 sq.km (14.0%) | 59,308 | 0.2 | −5.8 | 4.0 | 5655 | 94 | 42.5 | 39.4 | 26.6 | 26.6 | 7.4 |
Tanzania, Dodoma | 457,450 sq.km (51.6%) | 59,734 | 6.3 | 2.0 | 4.6 | 1076 | 74 | 37.8 | 12.2 | 48.6 | 39.2 | 0.0 |
Zambia, Lusaka | 448,140 sq.km (60.2%) | 18,383 | 1.5 | −3.5 | 2.3 | 985 | 102 | 51.9 | 8.8 | 39.2 | 48.0 | 3.9 |
Category | Items (Since COVID-19, …) | Var. | Cronbach’s α | ||||
---|---|---|---|---|---|---|---|
MA | RW | SA | TA | ZA | |||
Stress level | I am unsatisfied with the restricted daily life (activity, visitation, work, school). | ST1 | 0.826 | 0.860 | 0.831 | 0.801 | 0.878 |
I am unsatisfied with limited communication opportunities with other people. | ST2 | ||||||
It has decreased communication with other people (except family). | ST3 | ||||||
It has increased the communication with my family. * | ST4 | ||||||
Indoor activity | I don’t have enough leisure activities. | ID1 | 0.821 | 0.792 | 0.803 | 0.841 | 0.862 |
The screen time for visiting websites and watching TV has increased. | ID2 | ||||||
I prefer online activities to be offline (shopping, learning, communicating, etc.). | ID3 | ||||||
Appreciation of urban forests | I get a positive feeling when I visit urban forests. * | PR1 | 0.793 | 0.774 | 0.836 | 0.810 | 0.775 |
It became more challenging to go to the outdoor natural environment in urban forests. | PR2 | ||||||
I love to experience the outdoor nature around me, particularly during the pandemic. * | PR3 | ||||||
Perception of health recovery in nature | Through nature experience in the urban forest, I felt my mental recovery. * | HE1 | 0.786 | 0.797 | 0.775 | 0.852 | 0.784 |
Through nature experience in the urban forest, I felt my body recover. * | HE2 |
Country | Malawi | Rwanda | South Africa | Tanzania | Zambia |
---|---|---|---|---|---|
Month | January–June | January–June | January–June | January–June | January–June |
School Workplace Public events Gathering Transport Stay at home Movement Travel abroad Mask |
Visit Frequency | Staying Time | Transport Time | |||||||
---|---|---|---|---|---|---|---|---|---|
Month | January | June | t-value | January | June | t-value | January | June | t-value |
Malawi | 2.61 | 2.15 | 3.009 ** | 3.07 | 3.51 | −2.993 ** | 3.66 | 3.96 | −3.243 ** |
Rwanda | 3.66 | 2.38 | 6.022 *** | 3.48 | 2.48 | 4.309 *** | 3.49 | 3.00 | 2.075 * |
South Africa | 2.77 | 2.34 | 4.535 *** | 2.71 | 1.96 | 5.647 *** | 3.06 | 2.98 | 1.051 |
Tanzania | 3.44 | 2.00 | 8.021 *** | 2.97 | 2.00 | 7.083 *** | 3.16 | 3.49 | −2.042 * |
Zambia | 3.32 | 2.59 | 4.630 *** | 3.25 | 2.67 | 4.338 *** | 3.48 | 3.27 | 1.902 |
Average | 3.11 | 2.30 | 11.110 *** | 3.08 | 2.55 | 7.214 *** | 3.37 | 3.35 | 0.350 |
Stress Level | Indoor Activity | Appreciation of Urban Forests | Perception of Health Recovery | |
---|---|---|---|---|
Malawi | 3.74 ± 0.39 | 4.10 ± 0.28 a,b | 3.51 ± 0.36 | 3.81 ± 0.40 b |
Rwanda | 3.70 ± 0.42 | 3.89 ± 0.46 b | 3.62 ± 0.45 | 3.80 ± 0.47 b |
South Africa | 3.82 ± 0.48 | 3.80 ± 0.46 b | 3.74 ± 0.43 | 3.93 ± 0.42 a,b |
Tanzania | 3.93 ± 0.38 | 3.99 ± 0.40 a,b | 3.61 ± 0.48 | 4.23 ± 0.40 a |
Zambia | 3.57 ± 0.44 | 4.29 ± 0.39 a | 3.54 ± 0.48 | 4.05 ± 0.48 a,b |
F-value | 2.042 | 4.895 | 0.968 | 3.450 |
p-value | 0.088 | 0.001 | 0.425 | 0.009 |
Category | Variables | Malawi | Rwanda | South Africa | Tanzania | Zambia | |
---|---|---|---|---|---|---|---|
Stress level | ß-coeff. | ST1 | 0.708 | 0.912 | 0.675 | 0.875 | 0.852 |
ST2 | 0.695 | 0.704 | 0.762 | 0.958 | 0.967 | ||
ST3 | 0.683 | 0.834 | 0.828 | 0.509 | 0.788 | ||
ST4 | 0.890 | 0.716 | 0.718 | 0.486 | 0.616 | ||
CR | 0.840 | 0.855 | 0.813 | 0.829 | 0.879 | ||
AVE | 0.571 | 0.599 | 0.522 | 0.569 | 0.651 | ||
Indoor activity | ß-coeff. | ID1 | 0.753 | 0.573 | 0.554 | 0.720 | 0.762 |
ID2 | 0.787 | 0.716 | 0.913 | 0.993 | 0.884 | ||
ID3 | 0.792 | 0.910 | 0.831 | 0.753 | 0.827 | ||
CR | 0.890 | 0.735 | 0.797 | 0.879 | 0.879 | ||
AVE | 0.729 | 0.509 | 0.577 | 0.713 | 0.709 | ||
Appreciation of urban forests | ß-coeff. | PR1 | 0.631 | 0.628 | 0.864 | 0.674 | 0.756 |
PR2 | 0.611 | 0.849 | 0.779 | 0.678 | 0.770 | ||
PR3 | 0.998 | 0.735 | 0.757 | 0.976 | 0.673 | ||
CR | 0.833 | 0.760 | 0.839 | 0.800 | 0.731 | ||
AVE | 0.635 | 0.519 | 0.635 | 0.580 | 0.506 | ||
Health recovery perception | ß-coeff. | HE1 | 0.729 | 0.894 | 0.772 | 0.942 | 0.742 |
HE2 | 0.937 | 0.743 | 0.830 | 0.794 | 0.869 | ||
CR | 0.843 | 0.787 | 0.732 | 0.890 | 0.851 | ||
AVE | 0.732 | 0.651 | 0.578 | 0.803 | 0.742 | ||
Model fit summary | Chi2 | 103.768 | 60.609 | 92.394 | 137.957 | 136.846 | |
P-level | 0.000 | 0.105 | 0.000 | 0.000 | 0.000 | ||
GFI | 0.860 | 0.865 | 0.877 | 0.791 | 0.822 | ||
AGFI | 0.773 | 0.781 | 0.801 | 0.740 | 0.790 | ||
NFI | 0.810 | 0.858 | 0.840 | 0.846 | 0.815 | ||
IFI | 0.888 | 0.967 | 0.916 | 0.918 | 0.872 | ||
TLI | 0.840 | 0.952 | 0.910 | 0.894 | 0.881 | ||
CFI | 0.884 | 0.965 | 0.913 | 0.912 | 0.916 | ||
RMSEA | 0.071 | 0.054 | 0.056 | 0.051 | 0.063 |
Hypothesis: Direction | Malawi | Rwanda | South Africa | Tanzania | Zambia | |
---|---|---|---|---|---|---|
H1a: Stress level → | Appreciation of urban forests | Reject | Accept | Accept | Reject | Accept |
H1b: Indoor activity → | Appreciation of urban forests | Reject | Accept | Reject | Reject | Accept |
H2: Appreciation of urban forests → | Perception of health recovery | Accept | Accept | Accept | Reject | Accept |
Indirect Effect | Malawi | Rwanda | South Africa | Tanzania | Zambia | |
---|---|---|---|---|---|---|
Stress level → Urban forest → Health | Z-value | 0.850 | 2.363 | 1.909 | 0.152 | 2.576 |
p | 0.197 | 0.009 | 0.028 | 0.439 | 0.004 | |
Indoor activity → Urban forest → Health | Z-value | 0.657 | 2.226 | 0.667 | 0.713 | 1.806 |
p | 0.255 | 0.013 | 0.252 | 0.237 | 0.035 |
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Lee, J.-h.; Mkandawire, M.; Niyigena, P.; Xotyeni, A.; Itamba, E.; Siame, S. Impact of COVID-19 Lock-Downs on Nature Connection in Southern and Eastern Africa. Land 2022, 11, 872. https://doi.org/10.3390/land11060872
Lee J-h, Mkandawire M, Niyigena P, Xotyeni A, Itamba E, Siame S. Impact of COVID-19 Lock-Downs on Nature Connection in Southern and Eastern Africa. Land. 2022; 11(6):872. https://doi.org/10.3390/land11060872
Chicago/Turabian StyleLee, Ju-hyoung, Madalitso Mkandawire, Patrick Niyigena, Abonisiwe Xotyeni, Edwin Itamba, and Sylvester Siame. 2022. "Impact of COVID-19 Lock-Downs on Nature Connection in Southern and Eastern Africa" Land 11, no. 6: 872. https://doi.org/10.3390/land11060872
APA StyleLee, J. -h., Mkandawire, M., Niyigena, P., Xotyeni, A., Itamba, E., & Siame, S. (2022). Impact of COVID-19 Lock-Downs on Nature Connection in Southern and Eastern Africa. Land, 11(6), 872. https://doi.org/10.3390/land11060872