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Article

Can Campus Green Spaces Be Restorative? A Case Study from Tanzania

by
Argyro Anna Kanelli
1,
Maria Lydia Vardaka
1,
Chrisovaladis Malesios
2,
Zainab Jamidu Katima
3 and
Olga-Ioanna Kalantzi
1,*
1
Department of Environment, University of the Aegean, 81100 Mytilene, Greece
2
Department of Agricultural Economics and Rural Development, Agricultural University of Athens, 11855 Athens, Greece
3
Department of Chemical and Process Engineering, College of Engineering and Technology, University of Dar es Salaam, Dar es Salaam P.O. Box 35131, Tanzania
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(3), 1094; https://doi.org/10.3390/su16031094
Submission received: 26 November 2023 / Revised: 23 January 2024 / Accepted: 25 January 2024 / Published: 27 January 2024
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Abstract

:
Evidence from studies in the global north has shown the beneficial effects of green spaces (GS) for our psychological and physiological health. In this study, we examine whether the connection between GS, wellbeing, and restoration is also applicable to low/middle-income countries (LMICs), using Tanzania as a case study. During May–July 2021, an online survey was conducted among 108 students and/or staff of the University of Dar es Salaam. Information was provided regarding exposure to campus’s green spaces (CGSs) measured by the NDVI and subjective questions relevant to accessibility/availability of CGS, duration and frequency of visits, as well as perceived greenness. Self-reported questions were also used for assessing the quality of CGSs and motives for using them. Mental wellbeing and restoration were measured with the Warwick–Edinburgh Mental Wellbeing Short Scale ((S)WEMWBS) and the Restoration Outcome Scale (ROS), respectively, while the Nature Relatedness Scale (NR-6) was used to determine the feelings and thoughts of our participants towards nature. Generalized linear regression indicated a positive relationship between the need to be close to nature and relaxation as motivators for visiting CG; (S)WEMWBS (p < 0.05). The same correlation was observed for the ROS (p < 0.01). The ROS was also positively associated with the NDVI (p < 0.01), age group of 18–25 (p < 0.05), and employment status (full time p < 0.01, part time p < 0.05). Our findings confirm that GS can be considered an effective tool for promoting SDG 3 and SDG 11 in LMICs. More importantly, urban planners should focus on the motives for using such places in order to make them inclusive and multifunctional.

1. Introduction

In 2017, almost 11% of the global population suffered from a mental disorder [1]. Six years later, the WHO calls for action to change attitudes and approaches towards mental health and mental health care [2], not only due to the increased incidents of mental illness worldwide but because mental health problems pose a serious threat to public health as well [3,4]. More than a billion people have developed a medical condition which is rooted in a mental disease [5,6]. Given the fact that by 2050 more than half of the world population will live in urban areas, putting more pressure in peoples’ everyday life and emotional state [7], attention has shifted to the promotion of resilient cities, which will foster sustainable development, wellbeing, and inclusive growth.
The integration of nature-based solutions and green infrastructure into urban planning and development are broadly recognized as essential tools for achieving this goal. Contact with nature is associated with multiple psychological benefits and positive affects on wellbeing and human health [8,9]. Under this scope, a growing body of literature has focused on the beneficial properties of urban green spaces (UGSs) on wellbeing. Studies have shown that high percentages of greenness can improve anxiety, stress, and depression, as they are associated with lower levels of mental health indicators [10,11,12]. The quantity and quality of UGSs are crucial elements which favor the positive correlation between UGSs and mental health [13,14,15,16,17,18,19]. Exposure to UGSs [20,21,22,23,24,25], time spent and frequency [21,26,27,28,29], proximity or accessibility [24,30,31,32,33], perceived greenness, or view to such open spaces [34,35,36,37,38] contribute to the relief of stress, risk reduction for depression, and recovery from mental fatigue. UGSs have restorative properties [39,40,41,42,43], improve cognitive function, generate positive feelings, and promote spirituality [44,45,46,47,48,49].
In addition to their psychological benefits, UGSs also provide a variety of physiological benefits. Through the encouragement of physical activity [50,51,52,53] and the provision of ecosystem services such as temperature, noise, and air quality regulation, exposure to UGSs leads to lower levels of blood pressure, cholesterol, and mortality [54,55,56]. Reduction in respiratory diseases, obesity, and risks for cancer are additional examples describing this relationship [37,57,58,59,60,61]. Apart from its psychological and physiological benefits, urban nature also encourages social health [62,63,64], such as social interactions and the feeling of belonging [65,66,67].
The younger generation is perceived to be at a higher risk for developing mental health disorders compared to their predecessors [68,69]. University students confront problems of anxiety, fatigue, or depression given the academic and socio-economic pressures they face [70,71]. Several studies have investigated the effect of schools’ or universities’ outdoor areas on students’ wellbeing and academic performance [72,73,74,75,76,77,78]. However, most studies are conducted in Europe, North America, China, and Japan [79,80,81,82,83,84,85,86,87].
There is a lack of evidence in terms of the relationship between UGSs and mental health in low–middle-income countries (LMICs). The citizens of these countries face multiple challenges such as overpopulation, a rapid and unplanned urbanization, low quality infrastructure, and the expansion of unorganized settlements known as slums, which favor the spread of communicable diseases [11,88,89,90]. At the same time, extreme urbanicity leads to the inability of cities to generate adequate jobs and wealth and, therefore, to social instability and poor living conditions [91,92]. All the above, along with other individual, social, and cultural factors, negatively impact the population’s mental health [93,94,95,96,97,98].
Taking all of the above into consideration, the present study examines whether the association between university green spaces and wellbeing is also applicable in LMICs, using Tanzania as a case study. Focusing on students and staff from the University of Dar es Salaam, we test two hypotheses: whether the GSs of the university offer restorative experiences and mental health benefits for those interacting with them, and if understudied factors such as the quality of these places, motivation for using them, and nature connectedness correlate with these outcomes.

2. Materials and Methods

2.1. Study Sample

An online survey was conducted during May–July 2021 addressed to students and staff from the University of Dar es Salaam, more specifically at Mwalimu Nyerere Campus. Dar Es Salaam is located on the Swahili Coast, with a population of over 7 million (2023) and an area of 1393 km2. Currently it is the largest city of Tanzania and one of the fastest growing cities in the world. The University of Dar Es Salaam is situated 13 km west of the city center, occupies 1625 acres, and is the oldest and largest public university in Tanzania. We chose this particular time period because between May and October Tanzania has a warm climate which favors vegetation richness, without heavy rainfalls and cloud coverage, thus providing clear satellite images of GSs.
Overall, 188 respondents completed the online questionnaire. After screening, 17 participants were excluded because they reported suffering from a mental disorder and 63 respondents gave incomplete data. Thus, our final sample was 108 participants. Recruitment was performed via internet student groups, social media, and word of mouth. At the beginning of the questionnaire a short description of the survey’s aims was provided, and participants gave their consent for the processing of their data. The survey was carried out in accordance with the Declaration of Helsinki, and ethical approval was obtained by the Bioethics Committee of the University of the Aegean (8723/13 April 2022).

2.2. Online Survey

The main purpose of the survey was to investigate if interaction with the university’s greenspaces positively affected students’ and staff’s mental wellbeing and restoration. For this reason, it was divided into five parts.

2.2.1. Demographics

The first part of the survey included questions related to our samples’ demographic characteristics. Respondents had to provide information about their gender, age, educational level, monthly income, work, and family status.

2.2.2. Campus’s Greenspaces Assessment

Data were collected for GSs within the university campus using both objective and subjective measurements. We examined the greenness of the university’s outdoor area using the Normalized Difference Vegetation Index (NDVI). The NDVI is a well-established tool in environmental and climate change studies which provides information on vegetation cover [99,100,101]. It has been applied in multiple research studies due to its simplicity, better potential range, and capacity to rapidly detect changes in vegetation cover via multispectral remote sensing data obtained by space sensors [102,103,104,105]. The NDVIi represents the smoothed NDVI (sNDVI) observed at time step i and its ratio yields a measure of photosynthetic activity within values between −1 and 1 [106,107]. Lower scores reflect poor vegetation while higher scores indicate the opposite result. The NDVI is computed by the difference between near-infrared light (NIR) (which the vegetation strongly reflects), and red light (which the vegetation absorbs) divided by their sum [108], see (Equation (1)).
NDVI = (NIR − RED)/(NIR + RED)
For our calculations, we used a cloud free Sentinel-2 L2A satellite image at a resolution of 10 m, extracted on 25 May 2021 from the European Space Agency Copernicus Open Access Hub. Geographic data management and calculations were made via QGIS. After computing the NDVI for the whole campus, colleagues from the University of Dar Es Salaam advised that we focus on four specific campus’s green spaces (CGSs) that students visit the most: Mdigrii; College of Engineering and Technology (CoET); Close to the University Bridge and the Old Library; and Around the New Library. Respondents were given the option to choose another area within the university in addition to the four pre-selected options. We later attributed lower NDVI scores to this category (other area) as we did not have its exact coordinates and it was included mainly for verifying the respondents’ preferences regarding the CGSs. Study Locations can be seen in Figure 1.
Part two included the following self-reported questions:
  • For verifying that our study locations were indeed the outdoor areas that students or staff prefer, we asked them to indicate the CGSs that they visit the most. In total, five choices were available: 1 = “Mdigrii”, 2 = “CoET”, 3 = “Close to the University Bridge and Old Library”, 4 = “Around the New Library”, and a 5 = “Other”.
  • Perceived greenness of the CGSs, measured on a scale of 1 = “no green at all” to 5 = “extremely green”.
  • Distance from participants’ residence to the university, measured on a scale of 1 = “≤100 m” to 5 = “≥5 km”,
  • Ease of access to the CGSs. Respondents had to choose between “no” or “yes”, and
  • Qualitative traits of CGSs. Particularly participants had to indicate the degree of importance (from 1 = “not at all” to 5 = “extremely important”) they attributed to the following characteristics: safety, amenities, environmental quality, clean/well-maintained, and other facilities.

2.2.3. Use Patterns of CGSs

In order to assess the interactions between our sample and CGSs, we used self-reported questions on the time that the students or staff spend there (1 = none, 8 = > 8 h) and the frequency of their visits on a weekly basis (1 = “never”, 5 = “every day”). Regarding their motives for visiting CGSs, five choices were provided (physical activity, socializing, studying, relaxing, being close to nature) and subjects had to assess their importance from a range of 1 to 5 (1 = “not at all” to 5 = “extremely important”). A binary question (1 = “no”, 2 = “yes”) was also asked for distinguishing the participants who visit CGSs regardless of their daily courses.

2.2.4. Nature Relatedness

Many studies have established a strong connection between nature engagement and better mental health states [109,110,111,112]. Thus, in Part 4 of our survey, we examined our sample’s nature orientation, using a short version of the Nature Relatedness Scale (NR-6). NR-6 consists of 6 questions measured on a 5-point Likert scale where 1 = “strongly disagree” and 5 = “strongly agree”. A total score was calculated by averaging all six items, with higher scores indicating higher levels of nature relatedness.

2.2.5. Mental Wellbeing and Restoration

For the assessment of the mental health and restorative benefits of CGSs, we asked participants to fill in two separate questionnaires, after completing a visit to one of the four study locations. The Warwick–Edinburgh Mental Wellness Short Scale ((S)WEMWBS) was used for determining their mental wellbeing, a term covering both feelings and functioning, covering eudemonic and hedonic wellbeing as well as psychological functioning and subjective wellbeing.
The (S)WEMWBS is made of seven questions, and each item is scored on a 5-scale range (1 = “not at all” to 5 = “all the time”). Therefore, higher scores reflect better mental health states [44,113,114,115,116,117,118].
The Restoration Outcome Scale (ROS) was used for evaluating their perceived restorative outcomes. Restoration refers to our capacity to replenish cognitive resources depleted by everyday life [39]. The ROS includes three items referring to the feelings of relaxation, calmness, and enthusiasm, one item that examines attention restoration, and two items which focus on cleanings one’s worries and thoughts. Again, each question takes a score from 1 = “not at all” to 5 = “all the time” and higher scores indicate better restoration outcomes [83,119,120].

2.3. Data Analysis

Statistical analysis included descriptive statistics (mean ± standard deviation–SD) and frequencies (percentage %). In addition, the relationship between our dependent variables ((S)WEMWBS and ROS) and our 13 predictor variables was investigated by statistical modeling and specifically by the fit of a generalized linear model (GLM). Exploratory factor analysis (EFA) was also used for simplifying our model where applicable. As validity criteria of our construct variables, we chose % of variance (≥50%) [121,122,123]. Based on previous conceptual models such as those proposed by [124,125,126], our initial model included the following as independent variables: the provision of CGSs (made of items residential distance to university, NDVI, perceived greenness, and qualitative traits of CGSs—safety, environmental quality, clean/well-maintained, amenities, other facilities), exposure to CGSs (constructed from the items of time spent, frequency, and ease of access to CGSs), motivation for visiting CGSs (extracted by the following items: physical activity, socializing, studying, relaxing, and being close to nature), nature relatedness (measured by NR-6) and demographic characteristics (gender, age, educational level, monthly income, and work status; family status was not included as almost 93% of our sample declared single). Nonetheless, the provision of CGSs did not meet the validity criteria, and thus these four items were separately used as predictor variables. Similarly, two constructs reflecting motivation were extracted: motivation A (physical activity/socializing) and motivation B (relaxing/being close to nature). For qualitative characteristics, a single construct was made consisting of the following items: safety, environmental quality, and clean/well-maintained (Table 1). The normality of our dependent variables was tested through visual plots (histogram and normal probability plots). Furthermore, a backward elimination stepwise procedure was followed in order to derive the parameter estimates of the generalized linear regression models, which further ensured that the obtained results did not suffer from potential multicollinearity issues that could affect the validity and robustness of the obtained outcomes.

3. Results

3.1. Sociodemographic Characteristics

The majority of participants were students (87%), male (61%), and between 18 and 25 years old (91%). Of the participants, 84% had acquired a bachelor’s degree or were attending undergraduate studies, and 93% were single. More than half of the subjects preferred not to state their monthly income (58%) (Table 2).

3.2. Campus’s Greenspaces Assessment

Initially, the NDVI was calculated for the entire university campus area and then individually for the five study locations that were selected. The categorization of the NDVI values was divided into 3 classes: (a) areas of barren rocks, sand, or snow which usually show very low values (<0.1); (b) those with sparse or low vegetation such as shrubs and grasslands (about 0.2–0.5); and (c) those with dense or high vegetation such as the one found in temperate and tropical forests (about >0.6) [127]. The university area had high NDVI values (0.7 ± 0.2), as did the majority of the 4 selected CGS: Mdigrii (0.7 ± 0.06), CoET (0.7 ± 0.06), and Old Library (0.8 ± 0.01); meanwhile, lower NDVI values were noted in the New Library (0.5 ± 0.07). The NDVI for option “Other” was set at 0.2. (Figure 2).
Only a small part of our sample (2.7%) visited another greenspace within the university apart from our study locations. In general, CGSs are perceived as “moderately green” (46%). A similar percentage (42%) lived at a distance of ≤100 m from the university and 94% of them considered CGSs to be “easy accessed”. The hierarchical order of the qualitative characteristics were as follows: safety was rated as “extremely important” by 54%, followed by environmental quality (“very important”, 41%), amenities (“important”, 32%), clean/well-maintained (“little important”, 35%), and other facilities (“not at all important”, 48%) (Table 3).

3.3. Use Patterns of CGS

Students or university staff either visit the study locations “twice per week” (30%) or “every day” (30%). Additionally, 25% of them spend “less than half an hour” in CGSs and 18% spend “2–3 h”. The most important reason for visiting CGSs was studying (45%), followed by physical activity (32%), socializing (22%), and relaxing (29%), with being close to nature as the fifth (41%) (Table 4).

3.4. NR-6, Mental Health, and Restoration

In the NR-6, participants had a mean score of 3.9 ± 0.8, and thus relatively high levels of nature connectedness. The (S)WEMWBS total score equals to 2663 with a mean of 24.7 ± 4.5. Given that the scores of the (S)WEMWBS range from 1 to 35, where <19.5 indicates low wellbeing, 19.6–27,4 moderate wellbeing, and 27.5 > high wellbeing, our sample’s mental health is described as mediocre. Regarding the ROS, on a scale of 1 to 7 our subjects scored 4.9 ± 1.1.

3.5. Association between CGS, Mental Health, and Restoration

Preliminary testing through visual plots (histogram and normal probability plots) indicated the approximate normality of the response variables, which is an important assumption for the validity of results obtained in regression modeling (Figure 3). Through GLM, we observed a positive correlation between motivation B and the (S)WEMWBS (p-value < 0.05); thus, the more participants visit CGSs for relaxation and being close to nature, the more they benefit in terms of mental health. Moreover, significant associations were found between age, employment status, the NDVI, motivation B, and the ROS. In fact, younger participants (p-value < 0.05) and those who work either full time (p-value < 0.01) or part time (p-value < 0.05) seem to score better ROS results; meanwhile, higher vegetation cover (p-value < 0.01) or visiting CGSs for relaxation and being close to nature are linked to improved restorative outcomes (p-value < 0.01). The predictor variables of our first model explain 6% of the effects that CGSs have on subjects’ wellbeing, while the same percentage for the second model rises to 20% (Table 5).

4. Discussion

In this study, we present novel evidence regarding the wellbeing and restorative benefits of university green spaces for young adults in a low-income country (Tanzania). Our GLM shows that higher levels of greenness have restorative effects for our participants, while we did not find a direct relationship between our predictors and mental health. Previous studies that have incorporated objective measurements of vegetation cover have shown similar results [11,73,77,89,128,129,130,131,132,133,134,135,136,137]. Our findings also link GS availability with better psychological outcomes under the scope of LMICs. GS availability is defined as the quantity of GS, measured by vegetation coverage, size, or number of GSs [125]. It is recommended that future urban policies take into account this parameter and focus on the provision of available GSs in LMICs. Other aspects that should be considered are population distribution and future scenarios for population proportion [138]. In the same context, the ecosystem services provided by GSs are also important, particularly in cities where air pollution or climate change mitigation are major challenges [139,140,141].
On the other hand, studies carried out in LMICs and developing countries have demonstrated an association between nature and psychological wellbeing. For example, [142] found that GSs lead to attention restoration and stress reduction, while [143] proved that nature is positively associated with perceived restoration by using the context of perceived sensory dimensions. Refs. [144,145] focused on people with chronic conditions and showed that duration of visits, park availability, and greater size benefit their mental health and wellbeing. Ref. [146] showed that park proximity benefits mental health; ref. [50] found that park use led to exercise and physical activity and to improvement in mood; ref. [147] found that green infrastructure fosters spirituality and wellbeing; and [148] presented findings which advocate that increased use of GSs promote our psychological health. Even though most of the aforementioned factors (proximity availability and exposure) were included in our hypothesis, we did not observe correlations with either mental health or restoration. This could be attributed to the multiple independent variables incorporated in our models, which might have removed part of the effects of CGSs on wellbeing.
Another interesting finding is the motivation for visiting CGSs primarily for relaxation purposes or for being close to nature and this motivation’s association with both the (S)WEMWBS and the ROS, even though these items were scored as fourth and fifth in the hierarchy of incentives for using them. The same results were reported by [149,150], but nature observation and appreciation, rich vegetation, interaction with nature, experiencing the environment, and fresh air have been highlighted as the main motivators for visiting open spaces as well [151,152,153,154,155,156,157,158]. Refs. [159,160,161] also observed that connecting with nature plays a critical role for people when deciding to visit GSs. Furthermore, [39] noted that nature exposure—passive or intense—amplifies our ability for better concentration and [40] that our soul and body feel instant relief when entering into a natural setting. Nevertheless, it was surprising that no association could be noted for NR-6 and wellbeing or psychological recovery. The previous literature has established a link between nature orientation, relation, or connectedness measured by self-rated instruments and mental health benefits, based on the theory that the feeling of belonging to the natural world (nature engagement) generates positive feelings [162,163,164,165,166,167].
An additional objective of our study was to investigate how sociodemographic characteristics relate to CGSs and the participants’ self- reported mental health and restoration. We found a positive correlation between the age group of 18–25 and the ROS, indicating that younger individuals are able to relax to a greater degree when surrounded by nature and able take in its restorative benefits [168]. This has also been confirmed by [143,169,170], who have identified that people between 17 and 27 years old perceive nature as “means for escaping” from daily routine, and a way to build their confidence and cope with loneliness.
Other studies focusing on university students found that perceived greenness, UGSs, or academic GSs help them reduce feelings of anxiety, depression, and uncertainty or, conversely, promote psychological rehabilitation and academic performance [34,72,87,171,172,173,174,175,176,177,178,179,180,181,182]. This has become even more apparent following the COVID-19 pandemic lockdowns that were implemented on a global level. During that period, school and university students became more vulnerable to mental illness due to social distancing. The opportunity to visit CGSs or UGSs provided them an alternative for fighting against isolation and negative feelings while at the same time led to more intense use of urban nature [183,184,185]. Even visual contact with natural elements was found to be beneficial for their mood [186,187]. As an outcome, the appreciation and value of GSs also increased in students’ perceptions [188,189,190,191]. Along the same lines, part-time and full-time employees had higher scores on the ROS scale. This is in line with other studies that have shown that the presence of “green” in the workplace or exposure to GSs during the working day lead to stress relief and improvement in employees’ wellbeing [114,192,193].
Last but not least, in this study, we examined five user-related characteristics of GSs. We observed that safety is prioritized over environmental quality, cleanness and maintenance, amenities, and other facilities. This is quite understandable given the increased crime rates that the city of Dar Es Salaam has faced over the past years. In addition, safety is seen as a vital qualitative trait of GSs by [194,195,196] implying that it should be taken into consideration when planning the establishment of open spaces. Τhe feeling of safety could be secured by incorporating security measures such as regular presence of guards or surveillance by digital means [197]. Nonetheless, urban planners should firstly evaluate the supply and demand of GSs and then invest in reforming the available open spaces and quality aspects that will increase their use by the public. These quality aspects might refer to aesthetics, attractiveness, biodiversity (e.g., species richness, naturalness), and recreation (e.g., facilities promoting physical activity and socializing) [177,198,199,200,201,202]. Cultural peculiarities should also be evaluated, as the above suggestions might have to be adjusted to the cultural background of each nation. By following this perspective, urban management in LMICs will be aligned with the global political agenda which promotes sustainable development. This is achieved through a set of goals and actions that serve the present and future peace and prosperity of our planet and its people. The Sustainable Development Goals (SDSs) put LMICs in the spotlight under SDG 11 “sustainable cities and communities”. This SDG and its sub-goals center around the upgrade of slums, urbanization, city adaptation to climate change, and the support of the least-developed countries. SDG 11.7 explicitly refers to the need of “universal access to safe, inclusive and accessible, green and public spaces, in particular for women and children, older persons and persons with disabilities”. In addition, SDG 3.4 calls for action on the promotion of mental health and well being, as well as a one-third reduction in non-communicable diseases through prevention and treatment.

5. Strengths and Limitations

We chose to focus on LMICs, which are generally understudied. Our study is one of the first to examine possible connections between GSs and mental health in Tanzania. Our analysis included both objective and subjective measurements of greenness, thus providing a holistic approach when assessing inter-relations between psychological health and GS exposure. We also incorporated ways which can help the motivation towards GSs visitation, by examining non-conventional factors that are associated with the peoples’ needs and perceptions.
However, there are several limitations that should be mentioned. Our sample size is limited (n = 108) and mainly consists of university students (87%); therefore, it is not considered as representative of the total population of Tanzania and may lead to biased results. It is therefore recommended that future studies adjust their methodology accordingly and verify our results against the general population. Also, the cross-sectional design of our study does not allow us to draw causal relationships; thus, future researchers should use longitudinal data in order to verify the duration of GSs beneficial effects on wellbeing. Finally, we included multiple predictor variables in our analysis which might have had adverse effects on the expected outcomes.

6. Conclusions

Our study confirms the restorative properties that university greenspaces have for younger populations in an LMIC country. It also highlights understudied aspects that should be further examined as incentives that enhance the use of UGSs. As urbanization is expected to become a complicated challenge in the future, public policy should prioritize the integration of UGSs into urban planning and design.

Author Contributions

Conceptualization, A.A.K., M.L.V., Z.J.K. and O.-I.K.; methodology, A.A.K., M.L.V. and O.-I.K.; formal analysis, A.A.K., M.L.V. and C.M.; investigation, A.A.K., M.L.V. and O.-I.K.; writing—original draft preparation, A.A.K., M.L.V., C.M., Z.J.K. and O.-I.K.; writing—review and editing, C.M., Z.J.K. and O.-I.K.; supervision, O.-I.K.; project administration, O.-I.K.; All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethics Committee of the University of the Aegean (protocol code: 8723/13 April 2022) for studies involving humans.

Informed Consent Statement

All subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the 1964 Declaration of Helsinki and its later amendments. Ethical approval was obtained by the Bioethics of the University of the Aegean (protocol code: 8723/13 April 2022).

Data Availability Statement

The data are available upon request.

Acknowledgments

We would like to thank Mahir Said for distributing our online survey to the university students and staff, and for providing us with details and information about the University of Dar Es Salaam and the study locations.

Conflicts of Interest

The authors declare no conflicts of interest.

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Sustainability 16 01094 g001
Figure 1. Study Locations. (a) Mdigrii, (b) College of Engineering and Technology, (c) Close to the University Bridge and the Old Library, and (d) Around the New Library.
Figure 1. Study Locations. (a) Mdigrii, (b) College of Engineering and Technology, (c) Close to the University Bridge and the Old Library, and (d) Around the New Library.
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Figure 2. Normalized Difference Vegetation Index (NDVI) for the University of Dar es Salaam Mwalimu Nyerere Main Campus. Low vegetation density is denoted in red. High vegetation density is depicted in green.
Figure 2. Normalized Difference Vegetation Index (NDVI) for the University of Dar es Salaam Mwalimu Nyerere Main Campus. Low vegetation density is denoted in red. High vegetation density is depicted in green.
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Figure 3. Normality of dependent variables. (a) Histogram of (S)WEMWBS, (b) normal Q–Q plots of (S)WEMWBS, (c) histogram of ROS, and (d) normal Q–Q plots of ROS.
Figure 3. Normality of dependent variables. (a) Histogram of (S)WEMWBS, (b) normal Q–Q plots of (S)WEMWBS, (c) histogram of ROS, and (d) normal Q–Q plots of ROS.
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Table 1. Validity measures for data analysis.
Table 1. Validity measures for data analysis.
Type of VariableVariable NameItems% of Explained Variance
Independent VariablesNDVI--
Perceived Greenness--
Residential Distance to University--
QualitySafety48.9
Environmental Quality
Clean/Well-Maintained
Exposure to CGSEase of Access51.4
Frequency
Duration
Motivation APhysical Activity60.8
Socializing
Motivation BRelaxation68.9
Being Close to Nature
NR-6--
Gender--
Age--
Educational Level--
Monthly Income--
Employment Status--
Dependent Variables(S)WEMWBS--
ROS--
Table 2. Participants characteristics, N = 108, by frequencies and percentages.
Table 2. Participants characteristics, N = 108, by frequencies and percentages.
Variable NameItemsFrequency (N)Percentage (%)
GenderMale6661.1
Female4238.9
Age18–259890.7
26–45109.3
Educational BackgroundHigh School Degree109.3
Bachelor’s degree9184.3
Postgraduate Degree (Master, PhD)76.5
Monthly Income (in TZS)<500,0003330.6
500,000–1,000,00043.7
1,000,000–2,000,00043.7
2,000,000–4,000,00010.9
>4,000,00032.8
DK/NA6358.3
Employment StatusStudent9487.0
Full Time109.3
Part Time21.9
Unemployed21.9
Marital StatusSingle10092.6
Married/Living with Partner87.4
Table 3. CGS assessment, N = 108, by frequencies and percentages.
Table 3. CGS assessment, N = 108, by frequencies and percentages.
Variable NameItemsFrequency (N)Percentage (%)
Most Visited CGSMdigrii21.9
CoET (College of Engineering and Technology)8074.1
Close to the University Bridge and the Old Library65.6
Around the New Library1715.7
Other32.7
Perceived GreennessNot Green At All10.9
Some Green87.4
Moderately Green5046.3
Very Green3734.3
Extremely Green1211.1
Residential Distance to University≤100 m4541.7
101–300 m1513.9
301–600 m87.4
600 m–1 km1715.7
>1 km2321.3
Ease of AccessNo76.5
Yes10193.5
Safety5th Choice (Not At All Important)1110.2
4th Choice (A Little Important)76.4
3rd Choice (Important)1816.7
2nd Choice (Very Important)1413.0
1st Choice (Extremely Important)5853.7
Environmental Quality5th Choice (Not At All Important)65.7
4th Choice (A Little Important)1211.1
3rd Choice (Important)2119.4
2nd Choice (Very Important)4440.7
1st Choice (Extremely Important)2523.1
Amenities5th Choice (Not At All Important)2321.3
4th Choice (A Little Important)2825.9
3rd Choice (Important)3532.4
2nd Choice (Very Important)1715.7
1st Choice (Extremely Important)54.7
Clean/Well-Maintained5th Choice (Not At All Important)1614.8
4th Choice (A Little Important)3835.2
3rd Choice (Important)2119.4
2nd Choice (Very Important)2321.3
1st Choice (Extremely Important)109.3
Other Facilities5th Choice (Not At All Important)5248.1
4th Choice (A Little Important)2321.3
3rd Choice (Important)1312.0
2nd Choice (Very Important)109.3
1st Choice (Extremely Important)109.3
Table 4. Use patterns of CGSs, N = 108, by frequencies and percentages.
Table 4. Use patterns of CGSs, N = 108, by frequencies and percentages.
Variable NameItemsFrequency (N)Percentage (%)
Frequency of VisitsNever1110.2
Once A week2321.3
Twice/week3229.6
Three to four times/week109.3
Every Day3229.6
Duration of VisitsNone43.7
<0.5 h2725.0
0.5–1 h1312.0
1–2 h1211.1
2–3 h1917.6
3–5 h1413.0
5–8 h65.6
>8 h1312.0
Physical Activity5th Choice (Not At All Important)2220.4
4th Choice (A Little Important)2422.2
3rd Choice (Important)1614.8
2nd Choice (Very Important)3532.4
1st Choice (Extremely Important)1110.2
Socializing5th Choice (Not At All Important)1715.8
4th Choice (A Little Important)1110.2
3rd Choice (Important)2422.2
2nd Choice (Very Important)2119.4
1st Choice (Extremely Important)3532.4
Studying5th Choice (Not At All Important)65.6
4th Choice (A Little Important)1614.8
3rd Choice (Important)2220.4
2nd Choice (Very Important)1513.9
1st Choice (Extremely Important)4945.3
Relaxation5th Choice (Not At All Important)1413.0
4th Choice (A Little Important)3128.7
3rd Choice (Important)2321.3
2nd Choice (Very Important)2523.1
1st Choice (Extremely Important)1513.9
To Be Close to Nature5th Choice (Not At All Important)4440.7
4th Choice (A Little Important)2119.4
3rd Choice (Important)2018.5
2nd Choice (Very Important)1413.1
1st Choice (Extremely Important)98.3
Table 5. CGS effects on mental health and restoration, by generalized linear model.
Table 5. CGS effects on mental health and restoration, by generalized linear model.
Variable NameModel I *Model II **
95% Confidence Interval 95% Confidence Interval
BSEtp-ValueLower BoundUpper BoundBSEtp-ValueLower BoundUpper Bound
Motivation B1.0910.4302.5270.0130.2351.9470.2560.1112.3020.0230.0350.476
Age (=1) 1.2580.5822.1630.0330.1042.411
Employment (=2) 2.9560.9623.0720.0031.04174.865
Employment (=3) 2.8501.1002.5900.0110.6675.032
NDVI 2.7590.8133.3930.0011.1464.373
* R2 = 0.057, corrected model: p = 0.013. ** R2 = 0.198, corrected model: p = 0.001.
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Kanelli, A.A.; Vardaka, M.L.; Malesios, C.; Katima, Z.J.; Kalantzi, O.-I. Can Campus Green Spaces Be Restorative? A Case Study from Tanzania. Sustainability 2024, 16, 1094. https://doi.org/10.3390/su16031094

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Kanelli AA, Vardaka ML, Malesios C, Katima ZJ, Kalantzi O-I. Can Campus Green Spaces Be Restorative? A Case Study from Tanzania. Sustainability. 2024; 16(3):1094. https://doi.org/10.3390/su16031094

Chicago/Turabian Style

Kanelli, Argyro Anna, Maria Lydia Vardaka, Chrisovaladis Malesios, Zainab Jamidu Katima, and Olga-Ioanna Kalantzi. 2024. "Can Campus Green Spaces Be Restorative? A Case Study from Tanzania" Sustainability 16, no. 3: 1094. https://doi.org/10.3390/su16031094

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