Exploring the Association of Urban Agricultural Practices with Farmers’ Psychosocial Well-Being in Dar es Salaam and Greater Lomé: A Perceptual Study

Abstract

African urban agriculture (UA) has garnered attention for its contributions to food security and socio-economic improvement. However, its impact on the psychological well-being of farmers has received minimal focus. This study explores the psychosocial effects of UA by surveying 733 farmers in Dar es Salaam and Greater Lomé. Utilizing the Mental Health Continuum–Short Form (MHC-SF) and bespoke questionnaires, our research evaluates the emotional benefits of urban farming. Findings from regression analyses and spatial assessments conducted using Python and QGIS 3.32.2-Lima indicate significant variations in UA-related happiness across different city zones, with peripheral farmers experiencing greater satisfaction than their urban counterparts. Notably, female farmers reported higher levels of happiness, underscoring UA’s potential to empower women. This study advocates for the integration of UA into urban planning frameworks to foster psychologically beneficial urban environments.

1. Introduction

1.1. Context and Problem

Urban agriculture (UA) is known to be practiced worldwide and is increasingly being promoted, particularly in low-income countries. UA is an activity practiced in Africa with particular characteristics: UA not only helps reduce urban poverty and improve food security for urban households, but also utilizes composted household waste, making it a sustainable method for managing urban environments. UA, then, is not only leisure [1].

To better understand the impact and potential of UA in African cities, this study poses the following research questions: What motivates the sustainability of UA in African cities, specifically in Greater Lomé and Dar es Salaam, in terms of health-related aspects? How do the spatial distribution, socio-economic, and psychosocial benefits of UA impact community health in these cities? How can architectural design enhance the practice of UA to promote a more equitable distribution of psychological well-being benefits? What is the relationship between UA outcomes and the psychological well-being of farmers, particularly urban women farmers?

UA has mixed effects on the health of practitioners, consumers, and city dwellers where it is practiced [2,3]. According to Ba et al., (2016) [4], nitrate toxicity, for instance, generated through UA practices, is harmful to the health of consumers and even farmers due to their pollution. Chronic exposure to pesticides is associated with a variety of health problems, including neurological disorders and cancers [5]. Moreover, urban soils can be contaminated by heavy metals and toxic chemicals from industrial activities and road traffic [6]. Urban farmers often struggle with accessing sufficient water for irrigation. The urban setting means water is not always readily available for agricultural use, especially during dry seasons or in arid regions [7]. Also, the proximity of crops, animals, and dense human populations can facilitate the spread of pests and diseases, affecting yield and food safety. Humid conditions and stagnant water, common in UA areas, can encourage the proliferation of disease vectors such as mosquitoes. [8].

Besides those listed outcomes, African UA also has positive sides, each contributing to its growing prominence across cities and towns. Cultivating, processing, and distributing food in or around urban areas has become increasingly important due to economic, social, environmental, and health-related factors [9], and these objectives are met by UA. In fact, many African urban centers concern vast areas. UA is also an income-generating activity, especially as many women are involved. Its contribution to health through food security is among the reasons for promoting it [10]. The health aspects of this activity are often not studied by urban planners, and even though UA is practiced on urban land, UA can benefit health if it is planned [9].

1.2. Aims and Objectives of the Study

The research investigates UA’s psychosocial association with farmers, consumers, and city dwellers. This study attempts to answer the following question: what motivates the maintenance of UA in African cities, specifically in Greater Lomé and Dar es Salaam, in terms of health-related aspects? This includes its spatial distribution, socio-economic and psychosocial benefits, its effect on community health, and how architectural design could enhance its practice.

The central idea of this study is that, through thoughtful urban planning and architectural design incorporating UA, it is possible to achieve a more equitable spatial, economic, and social distribution of the psychological well-being benefits associated with this activity. To achieve this, the study analyzes the relationship between UA outcomes and farmers’ psychological well-being [11], highlighting the positive association between UA and urban women farmers’ lives [12].

Therefore, the project is structured around four primary objectives. The first two objectives will be explored through a literature review, while the last two will be studied by analyzing primary data collected in the field. The objectives are mapping UA, assessing UA benefits and challenges, studying the association between the psychosocial elements and UA, and estimating architectural and urban planning contributions to UA.

1.2.1. UA Mapping

The initial phase involves a comprehensive mapping of UA, grounded in a literature review from a global perspective to a more localized focus. This review will explore prevalent farming locations within urban settings, progressively narrowing from an international scope to specific insights on Africa, Sub-Saharan Africa, and ultimately, Togo and Tanzania.

1.2.2. Assessment of UA Benefits and Challenges

The second objective includes examining the benefits associated with UA, as identified through the existing literature. This assessment will highlight the positive outcomes of UA practices and acknowledge and explore potential disadvantages, offering a balanced view of UA.

1.2.3. Association between Psychosocial Elements and UA

A hypothesis is that engagement in UA activities positively correlates with enhanced social well-being and psychological health among UA farmers. Following this hypothesis, the third aspect of the study, which is one of the pillars of this research, delves into the psychosocial effects UA has on UA farmers. This investigation investigates how engagement in UA activities influences social well-being and psychological health.

1.2.4. Architectural and Urban Planning Contributions to UA

Finally, the other hypothesis stated by this research is that strategic architectural design and urban planning significantly enhance UA’s spatial distribution and overall benefits, optimizing its integration into urban landscapes. This hypothesis draws upon another pillar of the study, which seeks to illustrate how architectural design and urban planning strategies can enhance the spatial distribution of UA and amplify its benefits. This objective will explore the potential of design and planning to optimize the integration of UA into urban landscapes, thereby closing the loop on the study’s comprehensive examination of UA in this research.

2. Literature Review

2.1. UA Mapping

UA, circumscribed in this study as any cultivation activity producing food or animal husbandry within an urban and peri-urban spatial perimeter [13], is an increasingly popular practice worldwide, particularly in low- and middle-income countries (LMICs), on which the study is more focused. The Food and Agriculture Organization of the United Nations (FAO) attests that UA and associated businesses employ 200 million individuals, playing a role in feeding 800 million people residing in urban areas [14]. It is also reported that in African nations, approximately 40% of city residents participate in agricultural activities, a figure that increases to 50% in countries across Latin America [14]. In Africa, this activity has specific characteristics, such as using vast tracts of land and its role as a source of income, particularly for women [11], thus contributing to food security and the population’s health. It rarely plays a leisure role, as it does in building balconies in Western countries.

UA in Africa is marked by a diversity of practices and crops, including not only vegetables and fruit but also medicinal plants, adapted to the specific needs of local communities [15]. Faced with climatic challenges such as drought, urban farmers are trying to adopt economical irrigation techniques and grow species that can be resilient [16]. This agriculture is deeply integrated into local economies, generating jobs and stimulating small businesses that supply inputs and process agricultural produce [17]. It also plays a role in urban resilience, helping cities to cope with food crises and reduce urban heat islands through the greening of spaces [18]. In addition, UA offers significant economic opportunities for women and young people, influencing social norms and promoting emancipation in many communities [19]. However, access to land remains a major challenge, exacerbated by non-formalized land tenure systems and the pressure of urban development [20]. Finally, the use of organic waste to produce compost illustrates a commitment to sustainable practices, transforming waste into valuable resources to improve the fertility of urban soils and manage urban waste more effectively [21].

UA in Greater Lomé, the capital of Togo, and Dar es Salaam, the largest city in Tanzania, illustrates the potential and challenges inherent in this practice [22]. In Greater Lomé, as early as the first Master Plan in 1981, UA was somewhat generalized by being included in “green spaces”, with 15 to 20% of the population engaged in this activity, over 50% of them women, using UA for land conservation, sale, and household food [23,24]. Although urban planners in Greater Lomé recognize UA, their commitment seems lukewarm; Grand Lomé’s Schéma Directeur d‘Aménagement Urbain 2019–2030 did provide for Zones d‘Aménagement Agricole (ZAA), but inconsistencies in the 2020 document reveal a particular neglect of UA. In Dar es Salaam, the 2012–2032 Master Plan was preserved and planned for urban and peri-UA, recognizing its importance as far back as the 1979 plan. However, as in Greater Lomé, 60% of the population practice UA, with a majority of women, despite the difficulties. UA products are even integrated into the local cuisines of both cities, testifying to their cultural and economic importance [25,26].

2.2. UA Benefits and Drawbacks

UA is an essential component of cities’ socio-economic and environmental fabric worldwide, particularly highlighted in low- and middle-income countries (LMICs) for its multiple contributions to food security, income generation [27], and improved public health. In Africa, this activity is distinguished by its specific features, notably the size of the cultivated areas and its predominant role in the household economy, with significant participation by women. These characteristics underline the importance of UA not only as a means of subsistence but also as a vector for sustainable urban development [28].

However, despite these promising prospects, UA in Africa faces significant challenges that cloud its effectiveness and viability [29]. In this complex context, exploring new ways to strengthen and justify the practice of UA in African cities becomes imperative. Beyond the economic and food benefits, this research aims to shed light on other motivations supporting the commitment to UA. The aim is to unveil solid arguments for its development, particularly about the positive associations between UA and farmers’ psychological well-being and social cohesion within urban communities [30].

2.2.1. Psychosocial Associations

Psychosocial well-being is a comprehensive construct that encompasses emotional or psychological well-being, in addition to social and collective well-being [31]. Happiness is the subjective enjoyment of an individual’s holistic life [32]. For many people, the concept of happiness is synonymous with “subjective well-being”, which is commonly assessed by enquiring about their life satisfaction (evaluative), the balance of positive and negative emotions they experience (affective), and their feelings of meaning and purpose (eudaimonic). In her 2007 work, The How of Happiness, positive psychology expert Sonja Lyubomirsky defines happiness as the feeling of joy, contentment, or positive well-being and a perception that one’s life is fulfilling, significant, and valuable.

Science is often characterized by exploring phenomena that can be perceived, quantified, or evaluated. As a result, the concept of happiness seems elusive and intangible, and it is generally considered that the study of happiness is not proper scientific research [33]. However, the term is increasingly used in international institutions’ documents to assess the quality of life in cities, countries, or continents with precise, quantifiable indicators [34]. As a result, scientists have also begun to attach greater importance to this subject. Norrish and Vella-Brodrick (2008) [33] argue that studying happiness is a valid scientific topic, exploring how increasing happiness can help improve physical, mental, and social health. After an integrative literature review, the researchers Scorsolini-Comin and Santos (2010) [35] underlined the relevance of the consideration of subjective well-being (SWB) in health studies.

Morris (2012) [36] also believes that studying happiness as a science, whether drawn from evolutionary theory and neuroscience psychology or biology, psychosomatic and psychosocial medicine, cybernetics, and sociobiology [37], is paramount to making appropriate public policy decisions. He adds that for happiness to be a scientific indicator, we must consider its hedonic definition. He argues that “part of the importance of a well-founded science of happiness derives from the promise it offers of facilitating more effective decisions about public policy and social organization” ([36], p. 1). Helliwell and Aknin (2018) [38] even argue for a “social science of happiness” that makes an empirical study of the subject and enables strong links between researchers and policymakers. In their article entitled “The Science of Happiness for Policymakers: An Overview”, the authors also attest to how many scientists are calling for scientific measures of happiness to become an integral part of policy decisions and their recommendation to conduct interdisciplinary research on the subject [39]. This is how the measurement of subjective well-being and happiness comes into play in this research, consisting of the farmer’s cognitive and affective evaluations of their lives [40,41].

It is also gradually seen in the introduction of happiness or well-being measurement in spatial planning research as part of the improvement of public health [42,43,44,45,46]. Moreover, positive psychology and happiness studies motivate interdisciplinary research, creating policy and practice implications and recommendations [47]. The linear regression performed by Baschera and Hahn (2022) [42] showed that urban planning predicts happiness and well-being. These include time use perception, community vitality, ecological diversity and resilience, and living standards. The Mental Health Continuum–Short Form (MHC-SF) is often used to adequately study well-being [48,49,50].

Moreover, it is stated that spending additional time in a home garden is linked to increased subjective well-being [51]. In fact, on page 1, it is written that “Domestic (home) gardens provide opportunities for psychological and physical health benefits, yet these environments have received less attention in terms of their therapeutic value compared to other urban green spaces” [52]. Another research study also pointed out that gardening is also associated with greater happiness among urban residents [53], especially for women [54]: “It made me feel brighter in myself” [55].

The study focuses on several main areas. Firstly, it seeks to precisely identify the psychological health advantages and disadvantages associated with the practice of UA in African urban contexts, emphasizing the risks of pollution and toxicity of agricultural products. Secondly, it aims to demonstrate how UA can contribute to the psychological well-being of farmers, notably by empowering women through income generation and the acquisition of greater economic and social autonomy. This part of the research focuses on how the income generated by UA can positively influence the psychological state of farmers, offering them prospects for improving their quality of life and that of their families [56].

2.2.2. Architectural Design and Urban Planning Can Improve Spatial Distribution

Finally, the study proposes to explore the potential role of urban planning and architecture in optimizing the practice of UA. The idea involves rethinking urban spaces in such a way as to integrate UA areas harmoniously, creating environments conducive to the health, biodiversity, and resilience of urban communities [57,58,59]. It will be possible to see whether the space’s design can affect the happiness or well-being of its users, whether through the practice of activity or simply the time spent there [60].

Integrating UA into urban planning and architectural design can promote a more balanced spatial distribution and a homogenous economic and social distribution of the benefits associated with psychological well-being. This research aims to understand better why UA should be maintained and promoted and how urban planners and architects can contribute to spatial planning and holistic design to maximize its benefits.

3. Methods and Materials

This empirical and exploratory research deals with spatial planning, UA, and psychological health [61]. This study, therefore, applies various methods to bring out the involvement of these three fields in the research and the subject dealt with. The study sites are Greater Lomé, the capital of Togo, and Dar es Salaam, the largest city in Tanzania. The same research protocol was adopted for both cities at virtually the same time for two consecutive years. It is important to add that the researchers acknowledge the limitations of representativeness earlier in the manuscript.

The sample size (N) of the population studied is 733 farmers, 427 of whom are women. Farmers were between 18 and 70 years of age. Informed consent was obtained, as well as approval by an ethics committee or similar body. As far as inclusion criteria are concerned, there is no discrimination in terms of age, gender, level of education, household income, or people living with a disability. The only exclusion criterion is age, which must be no less than 18 and no more than 60.

The study has received the necessary ethical clearance to proceed with research involving human participants. The ethics approvals come from the EPFL Ethics Committee in Switzerland, ARDHI University in Dar es Salaam, and the Direction Nationale de la Recherche du Togo (Togo National Research Board).

3.1. Study Areas

Both cities are important UA activity centers. They have two major characteristics in common: the ports and the fact that they are both from Sub-Saharan Africa.

The “Port Autonome de Lomé”, Africa’s fourth-largest container port and West Africa’s leading transshipment hub, has achieved a significant growth of 15% in 2020, thanks to major investments and the digitization of import–export procedures. With a draught of 16.60 m, it accommodates super container ships and serves not only Togo but also hinterland countries such as Burkina Faso, Mali, and Niger. Port activities are crucial to the Togolese economy, accounting for almost 75% of tax revenues and over 80% of foreign trade. Between 2017 and 2021, the port’s turnover increased from 26 billion to 35 billion XOF. Efforts to modernize and dematerialize customs and logistics procedures are aimed at speeding up operations, reducing corruption, and making Lomé a regional logistics hub, enhancing its attractiveness to foreign investors.

The Port of Dar es Salaam, Tanzania’s main port, has a capacity of 14.1 million tons (MT) of dry cargo and 6.0 MT of liquid cargo. With a quay length of 2600 m and eleven deep-water berths, this strategically located port handles around 95% of Tanzania’s international trade. It is essential not only for Tanzania but also as a transit point for the landlocked East and Central Africa countries, such as Malawi, Zambia, DRC, Burundi, Rwanda, Zimbabwe, and Uganda. In addition, the port serves as an important freight link to the Middle and Far East, Europe, Australia, and America, reinforcing its central role in international trade.

3.1.1. Greater Lomé

Greater Lomé (Figure 1) is Togo’s capital and largest city, located southwest of the country along the Gulf of Guinea. It is Togo’s administrative, industrial, and commercial center and an important seaport in West Africa. The city is known for its lively market and features a mix of colonial and modern architecture, with palm-lined boulevards and accessible beaches. Greater Lomé remains a vibrant, welcoming place, reflecting Togo’s rich culture and diversity.

3.1.2. Dar es Salaam

Dar es Salaam (Figure 2) is Tanzania’s largest city and main economic center, although Dodoma is the official capital. Situated along the east coast of Africa, on the shores of the Indian Ocean, Dar es Salaam is a vibrant, cosmopolitan hub that serves as a gateway to the islands of Zanzibar and the country’s safari national parks. Historically a small fishing village, the city has grown to become a fascinating blend of cultures, architecture, and traditions.

3.2. Data Collection

In this study, psychological well-being is treated as a continuous variable. The multidimensional approach provides a nuanced understanding of specific objectives.

According to the United Nations Development Programme (UNDP), 68% of the population of six Tanzanian cities practice UA [62]. Several other estimates have been published, but the one that will be considered at this stage of the study is the UNDP estimate. In addition, mixed data from the grey literature and the researcher’s experience and observation showed that at least 20% of the population of Greater Lomé practice UA.

The following formula was applied to define the minimum sample to be questioned in the 2 cities, considering the populations of Greater Lomé and Dar es Salaam:

s = c² × p × (1 − p)/e²

where “s” is the minimum sample size required to obtain significant results for a given event and risk level, “c” is the Z score = 1.96 for a 95% CI, “p” is the probability of occurrence of the event in %, and “e” is the margin of error = 5% [63].

The result after the calculation of the sample population is as follows:

DAR ES SALAAM = 1.96² × 0.68 × (1 − 0.68)/0.05²
= 334.37
LOME = 1.96² × 0.2 × (1 − 0.2)/0.05²
= 156.74
DAR ES SALAAM + LOME = 491.11 farmers minimum

3.2.1. UA Field Types in Cities

Due to logistical constraints, the research strategy required targeting locations where a significant concentration of farmers could be reached simultaneously for questionnaire distribution. Consequently, any land cultivated by an individual for personal consumption, business, or both was identified as a critical data source. For this study, such cultivated land is called “farms”. The selection of study sites involved a process of spatial stratification, using administrative subdivisions to establish two distinct spatial strata based on a municipality/neighborhood gradient. Given the discrepancies between existing mapping data and actual conditions, preliminary site visits were conducted. These exploratory visits enabled us to gather the opinions of data collection supervisors in Greater Lomé and UA managers in Dar es Salaam to validate the selection of zones. Five municipalities were selected in Dar es Salaam, and three sizeable urban farming zones were chosen in Greater Lomé. Zooming in, seven areas in Greater Lomé and fifteen in Dar es Salaam were selected for inclusion in the study. This final selection encompassed intra-urban and peri-urban regions surrounding the two cities, providing a comprehensive view of the UA landscape.

3.2.2. Duration and Data Collectors

Given the time constraints, the research is a cross-sectional study. This cross-sectional study data collection which was carried out in March 2022 in Greater Lomé and March 2023 in Dar es Salaam, very early in the morning until noon at the latest, provided a detailed overview of the conditions present during these specific periods. At these times, the team was sure to find farmers in their fields.

The researchers are senior planners, architects, and supply chain engineers from Tanzania, Togo, Cameroun, Congo, and South Africa, and quantitative surveys of urban farmers were administered by young urban planners from ARDHI University in Dar es Salaam and the University of Greater Lomé, who received specialized training for this task. The interviewers used the KoBo toolbox for data collection in difficult areas. Each interviewer used a tablet to conduct the survey and geolocate completed questionnaires offline. Data collectors were recruited and trained to go into the neighborhoods of the target areas in the cities and distribute the questionnaire to the farmers.

3.2.3. The Population

The leading players in the UA sector are growers, traders, retailers, and consumers. In Dar es Salaam for example, focusing specifically on producers, UA managers engaged with growers in distinct horticultural activities, resulting in a sample across five municipalities.

The sampling approach employed was a combination of convenience and systematic sampling techniques. The objective was to gather data from a broad population without surveying every person individually. This approach proved beneficial due to the population’s large and diverse nature. Sampling by convenience enabled us to select sites where urban agriculture is often practiced, based on our knowledge of the city. Systematic sampling was then used to approach farmers who were systematically found on the site. It should be noted that this method may be influenced by interviewer bias. For instance, interviewers might be more likely to approach individuals who appear happy, potentially affecting the outcome of the results.

The approach targeted production origins to assess the association between UA and urban health, namely the agricultural fields and farmers. These producers are classified into primary operators, employees, or volunteers. The strategy consisted of spontaneously approaching people engaged in farming activities in the study area without prior selection. During the engagement, people were asked about their ownership of a UA field.

To ensure proportionally sized results and to minimize clustering effects, a comparable number of farmers were surveyed over an identical number of days in each zone within the cities. For instance, in Lomé, five teams gathered between 10 and 14 questionnaires daily from each of the three identified sites over two days, accumulating more than 200 questionnaires in total. A similar approach was used in Dar es Salaam.

3.3. Using the Mental Health Continuum–Short Form (MHC-SF)

Measuring a person’s psychological well-being is an ambitious objective that requires appropriate tools in a scientific context. As this study could not be carried out on a cross-sectional basis, a standard questionnaire such as the Mental Health Continuum–Short Form (MHC-SF) was chosen for this purpose. The MHC-SF is a 14-item assessment tool designed to evaluate three aspects of well-being: emotional, social, and psychological. All three are sub-grouped into two types: emotional mental health (hedonic) and positive functioning. This tool comprises questions about farmers’ state of mind over the past month. It is protected by copyright [64]. However, its use is authorized without prior consent from the authors, provided the source is referenced correctly [64]. The tool is a self-administered questionnaire that can be used on paper, face-to-face, or by telephone. It is available in English, French, and at least six other translated languages. It can be used for adolescent and adult populations. The Cronbach’s alpha coefficient of the MSF is 0.96, and according to George and Mallery (2003) [65], a Cronbach’s alpha coefficient > 0.9 is excellent [66].

3.4. Data Analysis

3.4.1. Standard Mental Health Continuum–Short Form (MHC-SF) Questionnaire

A table, which is not presented in this article, was made from various data arranged in geographical coordinates (latitude, longitude, and altitude), answers to questions on psychological well-being following the standard Mental Health Continuum–Short Form (MHC-SF) questionnaire, and other direct questions assessing perceived well-being (e.g., “happy”, “interested in life”, “satisfied with life”). Demographic and socio-economic information, such as age, gender, household income, and farmers’ birthplaces where concerned, was also collected and presented in the raw table. Some variables were then converted into appropriate numerical formats to facilitate analysis.

A summary of some critical aspects of the data is given in

Table 1. Data description.

Category	Details
Psychological Well-being Variables	Responses range from 0 to 5, likely using a Likert scale to measure aspects of well-being
Demographic and Socio-economic Data	Age, gender, household income, native status (born in the city or not)
Geographical Data	Latitude and longitude provided for each observation for spatial analysis
Duration of Activity in the City	Indicates the duration farmers have practiced urban agriculture, from 1960 to 2023

.

3.4.2. Data Analysis Materials

The methodology used to analyze the data involved several stages. After coding in Microsoft Excel 16, descriptive, inferential, predictive, and spatial analyses were performed using Python 3.12.2. The data were cleaned, coded, and analyzed with Python. QGIS 3.32.2-Lima was used to visualize data in more detail.

3.4.3. Descriptive, Inferential, Predictive, and Spatial Statistics

Descriptive statistics were performed to provide information corresponding to the analysis of the Mental Health Continuum–Short Form (MHC-SF) emotional (hedonic) and positive functioning items. This information includes the same variables’ mean, median, and standard deviation.

In addition to the descriptive statistics used to summarize the characteristics of the data analyzed, the relationships between the psychological well-being target variable and the other explanatory variables were examined. This information includes the same variables’ mean, standard deviation, and median. The correlation is bivariate. The MHC-SF matrix was also used to deepen the analysis of psychological well-being.

A mixed approach is used to assess the correlation between the general variable of mental well-being and the other variables, as some of these variables are categorical and others are numerical.

Pearson’s correlation [67] was used for numerical variables such as “Household members count” and “How long have you been farming fields or raising animals in the city?”.

Spearman’s rank correlation [68] was used for ordinal categorical variables, such as “Age range”, if data can be significantly ordered.

Chi-square or Fisher’s exact tests [69,70] were used for categorical variables, such as “Gender” or “City”.

A spatial cluster analysis method applying the K-Means algorithm was used to identify groups of farmers with similar psychological well-being profiles in every city globally.

Next, the geographical distribution of clusters within each city was visualized using maps to observe areas of high or low concentrations of psychological well-being. In addition to Python, QGIS 3.32.2-Lima was used to create grids over the layers of the Greater Lomé and Dar es Salaam map shapefiles, clip the grid with the polygon, and perform the spatial analysis with the points thanks to the QGIS “Research tools”, “Geoprocessing tools”, and “Data management tools”.

3.5. Research Steps Summarized

This section details the comprehensive methodology adopted for the study of the inter-relationships between UA, spatial planning, and psychological health within the urban settings of Greater Lomé and Dar es Salaam. The aim was to empirically explore how these dynamics affect the well-being of urban farmers, integrating various data collection and analysis techniques to ensure a robust understanding of these complex interactions.

Step 1: Study Design and Site Selection

The study employed an empirical and exploratory approach focusing on the interaction between urban agriculture (UA), spatial planning, and psychological health in Greater Lomé and Dar es Salaam. Site selection was based on urban farming zones within these cities, with detailed spatial stratification using administrative subdivisions to define study areas.

Step 2: Participant Selection and Ethical Considerations

A total of 733 farmers, aged between 18 and 70, were surveyed. Ethical approvals were obtained from relevant bodies in Switzerland, Tanzania, and Togo. Inclusion criteria ensured no discrimination based on demographic variables; the only exclusion criterion was age (18 to 60 years).

Step 3: Data Collection Methods

Mixed methods were used for data collection, incorporating both standardized and non-standardized questionnaires. Field data were collected using the KoBo toolbox and tablets for real-time geolocation and data entry, focusing on morning times when farmers were most likely to be found in their fields.

Step 4: Data Processing and Analysis

Data were initially coded and cleaned using Microsoft Excel and then analyzed using Python for descriptive, inferential, predictive, and spatial analyses. QGIS 3.32.2-Lima was employed for detailed spatial visualization and mapping of psychological well-being among urban farmers.

Step 5: Psychological Well-being Assessment

The Mental Health Continuum–Short Form (MHC-SF) was used to assess farmers’ psychological well-being, focusing on the emotional, social, and psychological health domains.

Step 6: Statistical Analysis

Descriptive statistics provided baseline data characteristics. Correlations between psychological well-being and various socio-demographic and economic variables were assessed using Pearson’s and Spearman’s rank correlations, and spatial clustering using the K-Means algorithm identified patterns within the cities.

Step 7: Visualization and Reporting

The spatial distribution of psychological well-being was mapped to identify high- and low-concentration areas within the cities. The final report includes detailed geographical mappings and statistical findings, illustrating the impact of UA on the psychological health of farmers in these urban settings.

The methodology adopted in this research provides a structured approach to understanding the complex layers of UA’s impact on psychological health. Focusing on the interactions between UA and psychological health in urban environments, the approach has been designed to capture a wide range of variables. The next section will delve into the results that these methodologies have enabled the research to gather.

4. Results: UA and Psychosocial Well-Being and the Place of Spatial Analysis

4.1. Generalities about UA Outcome and Related Psychological Well-Being

4.1.1. Happiness among the Urban Farmer Population Studied

A total of 92.36% of urban farmers feel generally happy while 7.64% do not, signifying a high prevalence of happiness among the urban farmer population studied.

4.1.2. Happiness among the Urban Farmer Population Studied since They Started Farming

Most farmers surveyed (74.35%) feel significantly happier since starting UA. Adding together, those who think “a little happier” represent almost 88% of respondents who think their happiness has improved due to UA. On the other hand, a minority (3.68%) feel less happy since starting UA, and around 8% have not noticed any change in their level of happiness.

4.1.3. Level of Happiness Linked to UA and Household Position in Greater Lomé and Dar es Salaam

The visualization of the distribution of farmers’ responses regarding their feelings of happiness related to the practice of UA according to their position in the household and trend lines show that UA-related feelings vary among the different positions occupied within the household. The more farmers occupy the position of first head of household, the higher their perception of happiness linked to the practice of UA.

4.1.4. Gender by Household Position in Greater Lomé and Dar es Salaam

The distribution gives us a visual representation of the gender distribution of the different roles within the household among the interviewees. It highlights the differences between the positions occupied by men and women in the study context.

Of the total of 542 men and women first heads of households, 61% of them are men farmers.

For second heads of households, women are almost twenty times more numerous than men, and there are slightly more men than women in the “Other” category, which is the category of people who are neither first nor second heads of households.

4.2. Measure of Emotional UA-Related “Well-Being” Using the Mental Health Continuum–Short Form (MHC-SF)

Table 2. Urban farmers’ happiness.

	During the Past Month, How Often Did You Feel Happy?	During the Past Month, How Often Did You Feel Interested in Life?	During the Past Month, How Often Did You Feel Satisfied with Life?
count	733	733	733
mean	3.17	3.75	3.55
std	2.01	1.63	1.72
min	0	0	0
25%	1	3	2
50%	4	5	4
75%	5	5	5
max	5	5	5

illustrates the emotional well-being results.

The outcomes show the following statistics for each question asked to the 733 farmers. Out of a total of 733 valid responses, the averages of the responses are 3.17 for the feeling of happiness, 3.75 for interest in life, and 3.55 for satisfaction with life, on a rating scale where 5 indicates a high frequency. The standard deviation shows the variability of responses, with 2.01 for the feeling of happiness, 1.63 for interest in life, and 1.72 for life satisfaction, indicating a moderate dispersion around the mean. The minimum score for each question is 0, indicating that some respondents have not experienced happiness, interest in life, or satisfaction in the previous month.

A total of 25%, or the top quartile, of farmers rated their happiness at one or less, their interest in life at three or less, and their satisfaction at two or less. The median, corresponding to 50% of respondents, felt happy, interested in life, or satisfied with life, with a score of 4, suggesting a generally positive trend.

A total of 75%, or the third quartile, of farmers rated their sense of happiness, interest in life, and satisfaction with life at five or below, indicating a high level of these feelings.

The maximum score for each question is 5, showing that some respondents still felt happiness, interest in life, and satisfaction during the month.

4.3. Measure of UA-Related “Positive Functioning” Using the Mental Health Continuum–Short Form (MHC-SF)

For positive functioning (

Table 3. Positive functioning table.

	Contribution to Society	Belonging to a Community	Society Is a Good Place	Belief in People’s Goodness
count	733	733	733	733
mean	3.49	3.58	3.51	3.37
std	1.65	1.59	1.60	1.64
min	0	0	0	0
25%	2	2	2	2
50%	4	4	4	4
75%	5	5	5	5
max	5	5	5	5

), the means vary slightly across dimensions, with 3.49 for contribution to society, 3.58 for belonging to a community, 3.51 for perception of society as a good place, and 3.37 for belief in the goodness of people, indicating a positive evaluation overall. Standard deviations are relatively similar across the dimensions (around 1.59 to 1.65), suggesting moderate variability in farmers’ perceptions in the two cities. The minimum score is 0 for all questions, showing that some individuals do not positively perceive their relationship with society or the community.

One out of four respondents rated two or less, indicating that a quarter of individuals have a less positive perception or feel less integrated. The median of 4 for all questions reflects an overall positive trend, with most respondents feeling positively integrated and contributing. A total of 75% of farmers have a rating of 5 or less, demonstrating high positive feelings towards their contribution and integration into society. The maximum score for each dimension is 5, indicating that some urban farmers feel strongly about their positive contribution to society, their belonging to a community, their positive view of society, and their belief in the goodness of people.

These results underline farmers’ generally positive perception of their role and place in society and their optimism about human nature and social improvement.

4.4. Comparison between the Two Cities Using the Mental Health Continuum–Short Form (MHC-SF)

Generally, farmers in Dar es Salaam report higher levels of emotional well-being and positive functioning than those in Greater Lomé, as evidenced by the higher averages for almost all the questions assessed. Residents of Dar es Salaam report feeling more interested in life and more satisfied with their lives, and they perceive their contribution to society and community more positively than those in Greater Lomé. Responses concerning the perception of society as a good place and belief in the fundamental goodness of people also show variations between cities, with Dar es Salaam showing higher averages.

4.5. General Study about the Correlation between Psychological Well-Being and Other Variables

The correlation matrix (Figure 3) below shows the relationships between geographical variables (latitude, longitude, altitude) and the various measures of psychological well-being. Here are a few key observations in the following sections.

4.5.1. Relationships between Well-Being Variables

Variables related to psychological well-being generally show positive and strong correlations, indicating that respondents who tend to feel happy are also more likely to feel satisfied with life, interested in life, and positively perceive their contribution to society and belonging to a community.

4.5.2. Relationship with Geographical Variables within the Continent

Correlation coefficients between geographical variables (latitude, longitude, altitude) and measures of psychological well-being are generally low. The relationship supposes that there is no apparent direct link between farmers’ geographical location on the continent and their perception of psychological well-being, at least not at the level of granularity analyzed here.

These results underline the importance of social and personal factors in the perception of psychological well-being rather than specific geographical factors.

For the categorical variables that show the average mental well-being by category, there are differences in mean mental well-being between the categories of each categorical variable.

4.5.3. Relation to General Mental Well-Being

Relationship between “General well-being” vs. “Number of household members” and “General well-being” vs. “Duration of involvement in UA”.

Turning to the second scatter plot, which cross-references general well-being with length of involvement in UA, the data show that those who started farming after 2000 display more consistent happiness levels.

General well-being vs. other variables

The results of the correlation calculations between the composite variable of general mental well-being and the other selected variables are as follows.

The most notable correlation is with the “City” variable, suggesting that general mental well-being can vary significantly from one city to another. The other variables show weak correlations with general mental well-being. These results indicate that social and environmental factors may substantially influence mental well-being more than individual characteristics or economic factors. However, these correlations do not necessarily imply causality, and other unexamined factors could influence these relationships.

4.6. Statistical Analysis of Women’s Psychosocial Empowerment through UA-Related Well-Being Outcomes

4.6.1. Calculating Average Happiness by Gender

This section of the report examines the average happiness levels among urban farmers in Greater Lomé and Dar es Salaam, as reported through a simple survey question regarding their happiness. Responses were coded as 1 for “yes” and 0 for “no”, allowing for a direct calculation of the percentage of individuals who consider themselves happy. This analysis specifically explores differences in happiness between women and men, aiming to identify any notable disparities in self-reported well-being within this population. Not all tables have been presented in this article to simplify understanding.

Averages

The results show the averages calculated for responses to the question “Do you feel happy?” for women and men, coded as 1 for “yes” and 0 for “no”. The averages are as follows: Women: 0.919118, or approximately 91.91%. Men: 0.917160, or approximately 91.72%.

These values suggest that, on average, around 91.91% of women and 91.72% of men in the study felt happy in Greater Lomé and Dar es Salaam.

The results of this analysis show the following:

Happiness levels are high

Both values are very close to 1, indicating that most people of both genders feel happy. The values may reflect a generally positive perception among farmers.

The narrow gender gap

The difference between women’s and men’s happiness averages is minimal (around 0.2%), suggesting no marked difference in this population’s self-reported happiness level between women and men. Both groups appear to be almost equally happy.

Although the women had a slightly higher average, this difference is probably insignificant without further statistical analysis. Therefore, a chi-square test was performed to determine whether the observed difference was statistically significant.

Analyzing happiness levels by gender among urban farmers in Greater Lomé and Dar es Salaam indicates high overall happiness, with minimal gender differences. The slight variance observed between women and men does not suggest significant disparities, pointing to a generally equitable perception of happiness across genders within this community. That is why further statistical tests, such as the chi-square test, are necessary to confirm the statistical insignificance of the observed differences.

4.6.2. Chi-Square Test

The results of the chi-square test indicate the following (

Table 4. Chi-square test results.

Test Details	Value
Chi-squared (χ2) Statistic	126.469
p-value	3.119
Degrees of Freedom	3
Expected Frequencies
- First Category	306.64 (Dar es Salaam), 68.36 (Greater Lomé)
- Second Category	26.98 (Dar es Salaam), 6.02 (Greater Lomé)
- Third Category	253.49 (Dar es Salaam), 56.51 (Greater Lomé)
- Fourth Category	22.90 (Dar es Salaam), 5.10 (Greater Lomé)

).

Here is how the Chi-square test is interpreted:

High χ² statistic: The high value of the χ² statistic indicates a substantial discrepancy between the observed and expected frequencies. The test suggests that the variables tested are probably not independent.

Extremely low p-value: The p-value is well below the commonly accepted threshold of 0.05, indicating that the differences observed in the data are statistically significant. With such a low p-value, you can reject the null hypothesis (which states no significant association between the variables tested) with high confidence.

Degrees of freedom (3): Degrees are based on the number of categories minus one in each variable. With 3 degrees of freedom, this corresponds to a 2 × 4 contingency table or similar, showing four categories compared between two groups.

Expected frequencies: Expected frequencies estimate what might be expected if the variables were independent. Differences between these expected and observed frequencies are the source of the high χ² statistic and the low p-value.

The chi-square test results, therefore, show a statistically significant association between the variables tested in the study. The results mean that the feeling of happiness is significantly associated with the city or gender of the participants. The exact nature of this association requires further analysis of the observed versus expected frequencies to understand how specific categories contribute to this result.

4.7. QGIS Data Visualization of Clusters of the Cities of Greater Lomé and Dar es Salaam

Analysis of the map of UA in Dar es Salaam (Figure 4) reveals some fascinating insights into urban farmers’ perceptions of this practice’s psychological benefits. Notably, those with little or no perception of the psychological benefits associated with UA are predominantly located in the central area of Dar es Salaam. The choice of a grid system is influenced by the need to balance detail with standardization, clarity, manageability, and privacy in representing spatial data distributions across Dar es Salaam and Greater Lomé.

Examination of the map of Greater Lomé (Figure 5), focusing on UA and its benefits for psychological well-being, reveals a significant trend in the well-being of urban farmers. More specifically, farmers who express a feeling of ill-being or indifference towards the benefits of UA are mainly clustered in the northern peripheral areas of the city.

Comparison between Cities

When the results of the two cities are compared (Figure 6), the clustering patterns are not uniform, indicating a diversity in psychological well-being that could reflect cultural, economic, or environmental differences. The comparison of clustering patterns analysis in the two cities reveals essential insights into the spatial distribution of psychological well-being among urban farmers. This analysis contributes to understanding how different urban environments, possibly influenced by cultural, economic, and environmental factors, affect well-being. Discussing the spatial clusters helps to illustrate where positive or negative impacts are more pronounced. This understanding can inform urban planning and policy-making, potentially leading to targeted interventions that enhance well-being in specific areas.

5. Discussion

5.1. UA’s Contribution to Psychological Well-Being through Income

From the beginning, it is important to emphasize that the results should be viewed as exploratory due to the methodology employed.

5.1.1. Overall Consideration of All Urban Farmers

The general question “Do you feel happy?” measures farmers’ perceived well-being in a binary way. The exploratory majority percentage of over 90% of happy farmers could reflect a variety of positive factors influencing people’s well-being, such as personal satisfaction, a sense of community, economic security, or a favorable living environment [71]. This statement is confirmed on page 1 in the following words: “Positive mood was fully restored after gardening” [62].

Regarding the question, “Do you feel happier or less happy since you started farming in the city?”, the majority of positive results also suggests that UA is significantly associated with farmers’ emotional well-being. The figures for the 4% who felt less happy and the 8% who felt no difference since they started farming in the city indicate that, while UA may be a source of satisfaction for many [72], it does not have the same effect on all farmers. The challenges associated with the practice, such as resource management, workload, or economic uncertainties, may affect urban farmers’ happiness differently.

Although these questions suggest a subjective measure of farmers’ well-being in Greater Lomé and Dar es Salaam, the results are confirmed by the more detailed use of the standard Mental Health Continuum–Short Form (MHC-SF) questionnaire.

As for the results of finer statistical calculations, a majority say they are happy, and the majority said they were happier than when they were not doing UA—there is no correlation with other variables.

Descriptive data analysis revealed a general trend toward positive perceptions of psychological well-being among participants. Most farmers reported feeling happy, interested in life, and satisfied, underlining a relatively high level of psychological well-being.

Inferential and predictive analyses between psychological well-being variables suggest that these aspects are often experienced jointly; for example, those who feel happy are also likely to feel satisfied and engaged in their community [73]. The correlation between continental geographical factors between the two cities and some socio-economic indicators is weak, implying that psychological well-being may be more closely related to personal and behavioral factors than material or environmental conditions.

5.1.2. Empowering Women through UA

The general statistics regarding the link between gender and household leadership positions could indicate a cultural or societal trend in which men are more often recognized or self-appointed as the primary household leaders [74]. This may have implications for decisions related to UA and access to resources [75]. Secondary positions typically held by women could also reflect power and gender dynamics within households [76].

The links between social status within the household and the emotional well-being derived from UA show that those who occupy the position of head of the household experience greater UA-related happiness [75]. This matter could be attributed to the sense of autonomy and control involved in running a household and the responsibility of providing for the family, in which UA can play a substantial role. As primary heads of households, they may derive particular satisfaction from UA’s ability to improve their household’s well-being [76].

Despite these data, further statistical calculations show that both genders are equally affected. It is suggested that the practice of UA positively affects the psychological well-being of farmers of both genders [77]. However, in the samples, there were more women than men farmers in Dar es Salaam and fewer women than men in Greater Lomé. This means that, despite the disparities in status as head or second head of household, women feel empowered as much as men, thanks to UA; refer to “The Women’s Empowerment in Agriculture Index” of Alkire et al. (2013) [78]. The literature states that UA contributes to women’s empowerment [79] by providing them with an income and improving their social status. The outcomes mark a step towards social equality in contexts where women’s rights are often limited.

5.2. Urban Planning, Architectural Design, and Psychological Well-Being

5.2.1. Urban Farmers Are Slightly Happier in Dar es Salaam than in Greater Lomé

The analyses show differences in the spatial distribution of UA-related psychological well-being between Dar es Salaam and Greater Lomé. Dar es Salaam shows a more even distribution of well-being, thanks to better institutional integration of UA. These differences could be due to various factors, including economic opportunities, social support, access to education and health services, or even climatic and environmental differences between the two cities [80,81,82].

However, it is essential to note that although the averages are higher for Dar es Salaam in all categories, the presence of responses covering the whole scale (from 0 to 5) in both cities indicates a diversity of individual experiences and perceptions in each city. Standard deviations, which measure the dispersion of responses around the mean, also show considerable variability in farmers’ perceptions, suggesting that individual and contextual factors strongly influence emotional well-being and positive functioning.

In conclusion, this analysis suggests that while there are general differences in the perceptions of emotional well-being and positive functioning between residents of Greater Lomé and Dar es Salaam, with an apparent advantage for Dar es Salaam, individual experiences vary widely. These differences call for a deeper understanding of the social, economic, and cultural contexts that contribute to personal well-being in these cities [82].

5.2.2. Happiness Is Located in Specific Spatial Zones in Each City

Spatial analysis revealed distinct clusters of psychological well-being within the cities studied. The maps generated illustrated significant spatial disparities, indicating that some urban areas could be islands of high or low well-being [83]. The three main clusters identified by the K-Means analysis in each city showed that psychological well-being is heterogeneous, even within small geographical areas. The result may reflect differences in living conditions, economic opportunities, social networks, or available services and merits further investigation to understand the underlying causes of these patterns. The analysis, therefore, shows that psychological well-being varies within the populations studied, with distinct clusters reflecting different levels of well-being [84]. These variations are present at individual, community, and city levels and not at a regional or continental level in this study.

The findings on the maps of the two cities underline the importance of a differentiated and targeted approach to UA support, considering the specificities and needs of farmers according to their geographical location [85]. There are several reasons for this situation in the northern outskirts of Greater Lomé and the center of Dar es Salaam. Firstly, these regions may be characterized by more limited access to essential resources for agriculture, such as water, quality agricultural inputs, or markets to sell produce in Greater Lomé. In the case of Dar es Salaam, this could be linked to high urban density, land pressure and competition for space, pollution, and noise, limited access to resources, isolation, restrictive urban regulation, or the stress of high food requirements in the city center [86]. These logistical and economic constraints can increase farmers’ stress and workload, reducing their overall satisfaction and well-being.

It is essential to develop tailored strategies to improve access to resources to improve the well-being of farmers in the northern outlying areas of Greater Lomé, strengthen support networks, and mitigate the environmental challenges specific to these regions [87,88,89]. Such an approach could help transform the UA experience for these farmers from indifference or discomfort to a more positive appreciation of their activity and its association with their quality of life.

The results in this research are exploratory and further studies are recommended to identify the specific factors influencing psychological well-being in these clusters [90]. Targeted interventions could be developed to support groups with lower psychological well-being, considering each community’s cultural and social specificities.

5.3. Recommendations

Here are some intuitive recommendations for action for urban planners, architects, and planners of UA in African cities as part of considering the benefits of UA practice on the well-being of city dwellers.

5.3.1. Integrating UA into Urban Planning, but Also Spatial and Architectural Designs That Promote Psychological Well-Being?

Urban planners and architects need to consider the integration of UA into urban development plans. The integration includes spatial data analysis [72], the designation of well-located, spatially, and socio-economically heterogeneous greenable spaces suitable for UA in new development projects [91], the programming and design of accompanying infrastructure for UA [92], and the revision of existing plans to incorporate urban agricultural zones [93].

It would also be beneficial to design urban spaces that encourage social interaction and the creation of support networks among urban farmers [94,95,96,97]. Green spaces for UA should be accessible, safe, and aesthetically pleasing to promote participation and support the psychological well-being of communities [98,99,100].

5.3.2. In-Depth Studies and Research and Institutional Capacity-Building

Studies and research should be encouraged to understand better the factors that influence psychological well-being in the context of UA [101,102,103]. The results should guide the development of policies and programs to maximize UA’s benefits on city dwellers’ well-being [97].

Local authorities and development organizations could also build institutional capacity to support UA through training urban farmers, supporting the marketing of agricultural products, and developing UA-friendly policies [104,105,106].

5.3.3. Supporting Women’s Empowerment through UA

With the results showing an equal level of well-being between men and women, UA can be a way of supporting this equality. The research recommends promoting UA as a means of economic and social empowerment for women [79]. The results can be achieved by facilitating women’s access to land, financing, information, training, and adapted agricultural technologies [107]. Initiatives could also decrease legal and cultural barriers limiting women’s participation in UA [108].

5.4. Limitations

When examining the results of the UA study and its association with psychological well-being, it is necessary to recognize a few limitations that could influence the interpretation of the data and the generalization of the results.

5.4.1. Other Factors Influencing Well-Being

A multitude of factors beyond UA practice alone can influence psychological well-being. These factors include but are not limited to, socio-economic conditions, access to mental health services, social support networks, and stress levels in other areas of life [109,110]. Therefore, although this study seeks to assess the association between UA and well-being, the differences observed between the two cities could also be attributable to these other uncontrolled variables.

5.4.2. Clustering of Farmers Surveyed

The method of selecting participants for the survey, mainly if the farmers surveyed were grouped in some regions of the towns, may introduce a clustering bias. The clustering means that the results may not fully represent the general UA population in each city. Farmers within the same cluster may share similar characteristics or be subject to particular environmental conditions that are not necessarily generalizable to the entire urban population practicing UA.

5.4.3. Psychological Well-Being Linked to Contact with Greenery

Another aspect of the association between UA and health, often put forward, is the psychological well-being linked to contact with plants and the color green, to the satisfaction of planting and seeing crops grow, but also to molecules such as endorphin secreted in the body after practicing UA as physical exercise [111,112,113]. This dimension of well-being is particularly emphasized in Western contexts, where interaction with nature may be less frequent in everyday urban life. However, it is essential to recognize that the intensity of these effects can vary considerably from person to person and that the role of exercise itself could be a confounding factor in the association between UA and psychological well-being.

6. Conclusions

The findings of this study report on the psychosocial well-being effects of UA. Local authorities could use this information in urban and development policies to target interventions to improve well-being in areas with lower happiness levels. Further research is advocated to examine the specific factors contributing to psychological well-being in the clusters identified, including qualitative studies that could provide insight into residents’ lived experiences. Finally, the methodological approach adopted, combining statistical and spatial analyses, could be applied to other urban contexts to assess well-being and inform policy more granularly.

UA is emerging as a crucial vector for food security and economic strengthening in African cities and as a significant means of improving psychological well-being. The study highlights the importance of UA in promoting happiness, satisfaction, and community involvement among urban farmers, revealing its potential as a tool for empowerment, particularly for women.

As another exploratory conclusion, there could be a need to promote UA and do more because it enables women to become emancipated and achieve the same happiness as men, which, culturally, is not the case. It seems that this conclusion underlines the importance of promoting initiatives that enable women to reach a level of happiness and empowerment equivalent to that of men, which, according to the text, is not yet a cultural norm.

The proposed recommendations, therefore, aim to encourage a spatial analysis of the association between UA and the well-being of city dwellers, especially farmers, and the strategic integration of UA into urban planning and policy development, with particular emphasis on women’s empowerment and psychological well-being. Urban planners, architects, and policymakers must recognize UA as an economic necessity and an opportunity to strengthen the social fabric and improve the quality of life in African urban environments.

Finally, the study’s limitations highlight the need for further, regular research to isolate the effect of UA on psychological well-being from the influences of other potential variables. Future studies could benefit from a methodological design that controls these confounding factors and provides a more detailed analysis of the mechanisms by which UA contributes to psychological well-being. By adopting a holistic and inclusive approach, UA can become a central pillar of sustainable urban planning, creating resilient, equitable, and thriving African cities where the well-being of all citizens is a priority.