Introduction

Gender disparity (GD) refers to the unequal sharing of opportunities, resources, wealth, and power between women and men. In the context of housing development, GD can be noticeable in several ways, for example, women have restricted access to capital, decision-making authority, and benefits from housing development projects (Rabia, et al 2019). For instance, women who have restricted access to capital and decision-making authority are less able to contribute to community development. This can lead to a lack of affordable housing, inadequate infrastructure and limited access to services such as healthcare and education (Qbal, et al. (2012). The concept of gender denotes to the socially built relationship between women and men. It refers to changeable and culturally variable rules and norms (Prudence, et al. 2007). Women represent almost sixty-eight percent of the world’s total population (UN Habitat, 2014), yet they own less than 1% of the world’s housing properties. This phenomenon has been observed in many Nigerian cities.

Housing has been defined by numerous scholars and authors, and the phase of these descriptions has two things in common. Housing is either a process or a product. In describing housing as a product, Chant (2012) defined housing as a completed object that can be touched and seen, while as a process, it encompasses all the interrelating entities and activities that must be in vogue and inclination to bring the product to completion. Conversely, Ezenagu (2000) argued that housing not only implies structure but also a host of comprehensive and complex participatory and evolutionary processes that consummate and result in giving shape to human settlements and housing needs. Housing has been understood as a male property and resource, with women having access only to its content and use. Thus, women are commonly not given instructions and brief information from and are not consulted during several housing development programs, although they play important roles and parts in building society. They are acknowledged as the main users, maintainers, and consumers of shelters, particularly in poor urban neighborhoods and rural areas.

Housing is an essential human need and a basic human right, yet access to adequate and affordable housing is unevenly distributed among different genders. Women, in particular, face numerous challenges in accessing safe and affordable housing due to discriminatory policies, social norms, and economic factors (Skaburskis, 1997). One major barrier to women’s access to housing is the gender wage gap, which results in women having lower incomes than men on average (Makinde, 2016a). This income gap makes it more difficult for women to afford housing and puts them at risk of homelessness. A study by the National Women’s Law Center found that in 2019, women working full-time, year-round, earned only 82% for every dollar earned by men, with even larger gaps for women of color (NWLC, 2021).

Another challenge faced by women in accessing housing is discrimination and disparity in the housing market. Women who are single or have children may face discrimination from landlords or real estate agents who assume they are less financially stable or responsible than their male counterparts (National Association of Realtors, 2022). Additionally, women may face sexual harassment or assault from landlords or other tenants, making them feel unsafe in their homes. Furthermore, women’s domestic responsibilities also play a role in their access to housing. Women often have caregiving responsibilities for children, elderly parents, or other family members, which can limit their ability to work and earn income, making it harder to afford housing. Women may also be more likely to prioritize the safety and well-being of their families over their own housing needs, leading to their staying in unsafe or inadequate housing (Housing and Urban Development, 2022).

Although men undoubtedly dominate housing development, few women are involved in its construction and development. In contrast, most women do not participate in housing. Engagement and involvement in housing development might consequently be influenced by numerous factors, among which is gender, even though gender may interact singularly or in unpredictable blends with other socio-institutional occurrences, for instance, marital status, ethnicity, income, age, household structure, and educational level, in influencing the degree of women’s and men’s engagement and involvement in housing development. From the pilot survey, it was observed that an increase in the Iwo Central Local Government population does not lead to a corresponding growth in housing development. Therefore, this study examines the effects of GD on housing development. Few studies have examined the relationship between housing and gender. Munir et al. (2021) examined the impact of GD on housing development in Pakistan. The study found that women faced significant barriers to accessing housing, including limited credit access, lack of property rights and discrimination in the housing market. These barriers were particularly pronounced for women who were unmarried or divorced. The study also found that GD in a wider society, including education and employment, was associated with lower levels of housing development overall.

The United Nations Human Settlements Program, (2012) examined the impact of GD on housing development. The study found that women faced similar barriers to housing access, including discrimination in the housing market and limited access to credit. The study also found that GD in education and employment was associated with lower overall housing development. Kabeer and Waddington (2015) examined the impact of GD on housing conditions in Bangladesh. The study found that women were more likely to live in homes with poor sanitation and inadequate water supply. This was partly due to gender-based discrimination in access to capital and services, in addition to gender norms that restricted women’s mobility and involvement in decision-making.

Oluwumi et al. (2020) investigated GD and women’s discrimination against real estate firms in Lagos. This study only examined women’s discrimination in the real estate industry, not in housing development. The study did not examine housing development types. Henry (2000) examined housing development and gender in low-income outskirts of Jinja Municipality, Uganda. This research identified GD in housing development in Uganda. The study was conducted in Uganda and not in Nigeria. Adeoye, (2018) examined the factors determining gender differentials in contribution to urban informal housing development in southwestern Nigeria. This study analyzed the factors influencing women’s and men’s involvement in housing development in southwestern Nigeria. This study did not examine the features of GD. Asiyanbola (2010) examined gender and participation in housing development in Ibadan, Nigeria. This study investigated the differences in the overall perception of women’s awareness, involvement, and actual participation in housing development. This study did not examine the effects of GD on housing development.

Parenthetically, the following research questions are stated to address the problem. What are the socioeconomic characteristics of respondents’ housing development in Iwo? What are the types of housing developments in Iwo? what are the features of GD in the study area? what are the effects of GD on housing developments in the study area? GD on housing is a noteworthy problem that affects millions of people worldwide, and it is essential to understand the specific ways in which this problem manifests in different contexts. By investigating the effects of GD on housing development in Iwo, this study can contribute to the growing body of literature on this topic and identify strategies to address this problem in the Nigerian context. Iwo is a rapidly developing city that has undergone significant changes in recent years. Despite this progress, however, significant gaps remain in access to affordable and secure housing, particularly for women. This study can help inform policies and programs aimed at promoting gender equality and improving access to housing for all members of the public.

In addition, housing is a basic human need and plays a critical role in the overall well-being and quality of life of people (Makinde, 2016b). Adequate and affordable housing is essential for physical, emotional, and mental health, education, and economic mobility (Baker & Bentley, 2023). Gender is a key socioeconomic factor in housing development that cannot be overemphasized. This study has contributed by emphasizing and providing facts on the impacts of GD on housing development as one of the important socioeconomic attributes of housing that cannot be overstated. Therefore, understanding and addressing the ways in which GD affects housing development is important for promoting communities’ overall well-being and development. Figure 1 shows the conceptual framework of the study, which was derived from a compressive literature review.

Figure 1. Conceptual framework of the study.

2.Literature Review

Gender disparity (GD) refers to the unequal distribution of resources, power, and opportunities between women and men. In the context of housing development, GD manifests as women having reduced access to resources such as land and financing, which significantly hinders their ability to secure adequate housing. Housing development encompasses the planning, designing, construction, and maintenance of housing units, including both new developments and the rehabilitation of existing housing stock. For this study, housing development focuses on the impact of GD on housing availability and quality in Iwo.

2.1Housing

Housing refers to the provision of dwellings, shelters, or homes for people. It is a fundamental need for human beings because it provides shelter and security and a sense of belonging and identity. According to the United Nations (2019), housing is a basic human right and an essential constituent of the right to an acceptable standard of living. However, the availability and affordability of housing vary greatly across countries, regions, and social groups. In numerous parts of the world, there is a shortage of affordable housing, especially for low-income households. This is repeatedly due to a lack of investment in the development of new housing as well as inadequate provision of infrastructure, such as water and sanitation systems, which can make it problematic for people to live in certain areas (Mani, et al 2024).

According to Makinde, (2014a), "Housing development is the process of creating, preserving, and maintaining housing units and communities. This includes new construction, rehabilitation, and preservation of existing housing, as well as the delivery of essential services and infrastructure. Housing development also impacts the environment and sustainability. Housing development can protect natural resources, minimize environmental impacts, and improve residents’ quality of life. An approach that highlights smart growth, sustainable design, and green building practices can help create healthier, more livable communities (Makinde, 2014b). A solution to challenges in housing development is to ensure that new housing units are affordable for moderate and low-income households. The lack of affordable housing is an important concern and problem in Nigeria, with 7.2 million extremely low-income renter households facing a severe shortage of available and affordable housing. Another major solution to the challenge of housing development is the delivery of necessary services and infrastructure. This includes the construction of roads, sewage systems, water, and other public amenities, as well as the provision of healthcare facilities, schools, and other services essential for the well-being of communities (Olusola, 2020).

There are different types of housing development, each with its own unique characteristics and planned to meet the requirements of different groups of people (Devlin, 1994). Some of the most common types of housing development are as follows:

Single-family homes: These are standalone homes intended for one family. They are typically built on a single lot and have their own yards and gardens. Single-family homes account for the majority of new housing production in the United States.

Townhouses: Townhouses are multi-unit to one another, often sharing walls with neighboring units. These houses are typically smaller than single-family homes and are intended for denser forms of housing. Townhouses are a popular type of housing for first-time homebuyers, farmers, and people looking for low-maintenance housing.

Apartments: Apartment buildings are multi-unit structures that provide individual living spaces for renters. They are typically located in urban areas and are intended for denser forms of living. Apartments account for most U.S. rental housing.

Senior housing: Senior housing is intended for older adults and is designed to meet specific needs. It can take many forms, including independent living, assisted living, and skilled nursing facilities. Senior housing is an important component of long-term care and persistence and provides older adults with a range of housing options to meet their changing needs (Devlin, 1994).

Cohousing: A type of housing development intended to promote a sense of community among residents. Typically, it involves shared common spaces and a shared commitment to a sustainable lifestyle. According to the Cohousing Association of the United States (COHOUS), cohabitation is a type of deliberate community consisting of private homes complemented by communal facilities (CohoUS, 2021). Gulcimen et al. (2021) analyzed the environmental impacts of different housing types. The study found that multi-story apartment buildings had the lowest environmental impact because of their compactness and the ability to share resources such as heating and cooling systems. Wang, et al (2020) found that cohousing (cohabiting) can provide numerous benefits, including social connections, reduced living costs, and environmental sustainability. However, the study also identified challenges such as the need for consensus-based decision-making and potential conflicts among residents.

2.2Gender and Influencing Factors

Gender is defined as the socially constructed behaviors, roles, and identities that society considers suitable for men and women. In relation to the World Health Organization (WHO), gender is defined as the socially constructed expressions, roles, identities, and behaviors of boys, girls, women, men, and gender-dissimilar people. It affects how people observe each other and themselves, how they interact and act, and the distribution of resources and power in society (World Health Organization, 2021). Gender is also an important factor in many areas of social life, including work, family, and politics. For example, gender stereotypes and biases can influence hiring decisions in the workplace and opportunities for promotion and advancement (Heilman & Eagly, 2008). In a family, gender roles can outline the division of responsibilities and labor, as well as attitudes toward parenting and childcare (Kimmel & Ferber, 2016). In politics, gender can have an emotional impact on the participation and representation of women in decision-making processes (Paxton, Hughes, & Green, 2006). In line with the World Economic Forum (WEF), GD is not only a pressing moral and social issue and a critical economic challenge. If not addressed, it perpetuates the inefficient use of a country’s human capital potential, leading to slower economic growth (World Economic Forum, 2020).

The social and cultural traits associated with being male or female are referred to as gender. It is a socially manufactured idea that includes various roles, actions, and standards that are accepted by women and men in a specific society (Healy and Zucca, 2004). Sex, which describes the biological and physiological traits that separate males and females, is not the same as gender (WHO, 2017). Health, education, employment, interpersonal connections, and housing development are just a few of the many facets of life that gender significantly influences. The options and possibilities available to people may be constrained by gender norms and stereotypes, which can also lead to disparity and discrimination. For instance, gender-based violence is a major problem that touches millions of people worldwide and is frequently caused by gender stereotypes and power disparities (WHO, 2021).

Being male or female is associated with various social, cultural, and psychological attributes (Nordiska, 1996). Gender is a complicated and multifaceted concept. Although people frequently think of gender as a simple idea, with people either identifying as male or female, there is actually a wide variety of gender identities (Saleemi and Kofol, 2022). These include:

Cisgender: Those who identify as gender that matches their biological sex are known as cisgender. One example of a cisgender person is someone who was born with male reproductive organs and who identified as a male. The most prevalent gender identity is this one (Richards, Bouman and Seal, 2016).

Transgender: Those who identify as transgender are those whose biological sex led them to be born with a gender that is different from the one they actually prefer (Small, 2024). The term "transgender" refers, for instance, to a person who was born a male but now identifies as a female. Discrimination, harassment, and limited access to healthcare are just a few of the difficulties that transgender people may encounter (James, Herman, Rankin, Keisling, Mottet, & Anafi, 2016).

Genderqueer: The word "genderqueer" is used to describe individuals who do not solely classify as female or male or who reject traditional biological gender categories. Those who identify as genderqueer may identify as a mix of female and male, as neither female nor male, or as a whole different gender (Lombardi, Wilchins, Priesing, & Malouf, 2001).

Nonbinary: The word ‘nonbinary’ is used to describe individuals who do not exclusively categorize as either male or female but rather as a gender that is not part of the binary system. Those who identify as non-binary may choose to identify as either male or female, neither male nor female, or as a completed other gender (Budge, Rossman, &Howard, 2014).

Agender: Those who do not identify with any gender or who do not feel a sense of gender are referred to as Agender. Agender people can identify in various ways, including as neither male nor female or as a blend of the two (Richardsetal, 2016).

2.3Factors Influencing Gender Disparity in Housing Development

In terms of housing development, GD refers to the unequal distribution of resources, opportunities and access to services. GD in housing can occur in several ways, such as unequal access to affordable housing, inadequate living conditions, and a lack of housing opportunities (Nordiska, 1996). More so than men, women, particularly those with low incomes and women of color, are negatively impacted by this disparity, presenting serious social and economic problems for households. Persistent GD between men and women is a major aspect of GD in housing development. Because women typically earn less money and have less financial clout than males, they find it difficult to access quality, affordable housing. Women’s access to housing is affected by this income disparity, particularly in locations with high housing costs. Therefore, women may be compelled to live in congested, inadequate, or unattractive environments (Stewart, and Cloutier 2021).

The higher parental duties that women endure are indeed crucial aspects of GD in housing development. In general, women are less able to work and earn an income because they spend more time than males taking care of their children, ageing parents, and other family members. This regulation limits women’s ability to access adequate housing or improve their living conditions, making it difficult for them to overcome poverty (Philippine Commission on Women, 2015). In addition, discrimination against women limits their capacity to own property and prevents them from obtaining housing finance such as loans and mortgages. Lenders and landlords may discriminate against women based on their gender or marital status, making it difficult for them to access credit or affordable housing (Center for American Progress, 2018). This discrimination can also limit women’s ability to access property rights, leading to economic exclusion and poverty (Carol and Anjali 2011).

2.4Features of Gender Disparity

GD is a persistent and pervasive concern that affects people around the world, particularly women and girls. This disparity manifests in different ways and has several negative consequences for respondents and society as a whole. One of the most significant features of GD is the gender pay gap, which discusses the disparity between the wages of women and men in the workforce. In line with the World Economic Forum, the worldwide gender pay gap is 16%, implying that women make an average of 85% of every dollar made by men (World Economic Forum, 2020). This gap is particularly pronounced in certain industries, such as finance and technology, and has been shown to persist even when factors such as education and experience are considered (Blau & Kahn, 2017).

Another key feature of GD is the under-representation of women in leadership positions. Women are considerably less likely than men to hold power and authority positions in both the private and public sectors (World Economic Forum, 2020). This lack of representation can limit women’s ability to shape policies and decision-making processes, thus perpetuating gender inequality in various areas. A third feature of GD is the prevalence of gender-based violence, which includes domestic violence, sexual assault, and harassment. Women are disproportionately affected by gender-based violence, which can have serious physical and psychological consequences for victims (World Health Organization, 2021). This violence can also limit women’s capacity to contribute fully to society and access resources and opportunities.

A fourth feature of GD is the limited access that women often have to healthcare, particularly reproductive healthcare. Women may face barriers in accessing contraception, maternal healthcare, and treatment for reproductive health issues (United Nations Population Fund, 2021). These barriers can cause severe concerns for women’s well-being and health and perpetuate GD by limiting women’s capability to contribute fully to society. Finally, GD is perpetuated by stereotypes and discrimination that affect women in various aspects of their lives. Women are frequently subject to gender-based inequality and discrimination in the workplace, education, and other areas, which can limit their opportunities and perpetuate GD (International Labor Organization, 2021). Additionally, gender stereotypes can contribute to a culture that undervalues women and limits their potential.

2.5Effects of Gender Disparity on Housing Development

The development of housing is just one of many areas of life where GD has a significant effect. Housing is an essential human necessity and a component of welfare that has significant impacts on both social and economic growth (Santos and Klasen, 2021). GD affects housing availability, pricing, and quality, which poses serious problems, particularly for women (Adeosun, and Owolabi, 2021). The type of housing that women can obtain is also affected by GD (Marcus and Somji, 2024). Women are frequently forced to live in poor housing due to deficiencies in utilities such as water, electricity, and sanitary facilities. In certain instances, women are even denied access to housing, leaving them homeless and open to exploitation (Adeosun, and Owolabi, 2021). According to studies by the International Housing Coalition, (2021) women are significantly affected by poor housing conditions, including inadequate ventilation, poor lighting, and a lack of basic services, such as bathrooms and cooking facilities (IHC, 2021). The well-being and health of women and their relatives are significantly impacted by these issues (Marcus and Somji, 2024). A significant factor in GD is housing ownership. Women encounter major obstacles to housing access in many nations, especially if they are single or do not have a male income (Santos and Klasen, 2021). "Women confront many disparities and violence while obtaining housing, including gender bias, age, region, income, tribe, and marital status, according to a study by UN Women (UN Women, 2021). Access to affordable and sustainable housing, essential to women’s well-being and financial independence, is challenging because of these factors. Housing development for women is affected by GD. Women in many nations earn less than men, which prevents them from being able to afford appropriate housing. Women are more likely to be poor than men, and they are also less likely to have access to credit, which makes it difficult for them to develop good housing, according to a report from Habitat for Humanity (Habitat for Humanity, 2021). Women who want to increase their economic independence and security encounter significant obstacles because of disparities.

Chant, (2012) investigated the impact of GD on housing in urban areas. The study found that women often face significant barriers to accessing housing due to their low incomes and lack of control over their resources. Women also face discrimination in the housing market, with landlords and property managers preferring male tenants. This can lead to women being forced to live in inadequate and unsafe housing or relying on informal settlements with inadequate sanitation and water facilities. Meth et al. (2019) studied the impact of GD on housing formalization in India and South Africa. This study found that GD in India contributes to women’s lack of access to housing. Women in South Africa and India often have lower incomes and educations than men, which limits their ability to access formal housing. Women also face cultural barriers that prevent them from owning property or inheriting land, which can make it difficult to access adequate housing. UN Women (2018) examined the impact of GD on housing in the Pacific Islands. The study found that women in the Pacific Islands face and experience significant challenges and problems in accessing adequate and affordable housing. Women have lower incomes than men, which limits their ability to access formal housing. Women also face cultural barriers, including discriminatory laws and social norms that prevent them from owning property or accessing credit. This can force women to rely on informal settlements or live in overcrowded and unsafe conditions.

2.6Feminist Theory and the Concept of Intersectionality

The understanding of the effects of GD on housing development is rooted in feminist theory and the concept of intersectionality. Feminist theory posits that women’s opportunities and experiences are molded by their gender, and this disparity is further compounded by other factors, for instance, sexuality, class, and race (Crenshaw, 1989). Intersectionality, a concept developed by Crenshaw, highlights the ways in which these different identities intersect and mutually construct one another, creating unique experiences of oppression and privilege. In the context of housing development, GD can manifest in several ways. For instance, women may have fewer accesses to resources and opportunities for home ownership, leading to a higher probability of renting or living in substandard or overcrowded housing (Vásquez-Vera, et al. 2023). Additionally, women may be more likely to experience housing discrimination, both in the rental market and in the process of procuring a mortgage (Sanders, & Scanlon, 2000; Turner, et al 2002). Furthermore, women are often responsible for the care and maintenance of the household, which can limit their ability to participate in the housing development process and make decisions about the design and location of their homes (Wacquant, 1996).

In addition, in many societies, men are typically the principal breadwinners, and women are in charge of caregiving and domestic tasks. This can lead to women being more likely to live in poverty and deficiency and less likely to have the financial resources to purchase a home or participate in housing development projects. Furthermore, women are frequently involved in housing development decision-making processes, such as urban planning, architecture, and real estate development. This lack of representation can lead to housing developments that are not designed with the preferences and needs of women in mind and considerations (Harcourt, and Escobar, 2002). GD can have a significant effect on housing development, both through direct discrimination and through the ways in which women’s roles and responsibilities shape their access to resources and opportunities.

2.7Resident Socioeconomic Characteristics

Resident socioeconomic characteristics, including sex, age, income level, occupation, education, marital status, family size, ethnicity composition, and race, have a significant impact on housing development and have resulted in unequal access to affordable housing and adequate living conditions for different groups of people (Olusola, 2020). For example, the income level of people is a major factor in accessing affordable housing. The lack of affordable housing is a noteworthy issue and concern in the United States, with 7.2 million extremely low-income renter households facing a severe dearth of affordable housing and an available rental home environment. This finding indicates that respondents and families with low incomes are disproportionately affected by the affordable housing crisis and are more likely to experience housing insecurity and homelessness (Makinde, 2014a). Race and ethnicity also play a significant role in access to affordable housing (Kim, et al. 2019). Persons of color are more likely to experience discrimination in the housing market and to live in areas with limited access to opportunity and high concentrations of poverty. This can lead to a lack of access to decent, safe, and affordable housing, along with limited access to jobs, education, and other opportunities essential for upward mobility. In addition, education can influence access to affordable housing. Individuals with lower levels of educational and academic accomplishment are more likely to experience housing insecurity and homelessness. This is because persons with lower educational levels are more likely to have lower-paying jobs, which can make it harder for them to afford housing (Makinde, 2014b).

Policy and International Department, RCN (2012) examined the connection between health outcomes and respondents’ socioeconomic characteristics. The study found that respondents with lower socioeconomic status were more likely to experience poor health consequences, including lower life expectancy, higher rates of chronic diseases, and higher mortality rates. Kim et al. (2019) studied the relationship between socioeconomic status and educational outcomes in Developing Countries. The study found that socioeconomic status was a significant predictor of education outcomes, with respondents from lower socioeconomic backgrounds having lower levels of education attainment. Emmanuel and Zucman, (2020) examined the relationship between socioeconomic characteristics and income disparity in the United States. The outcome of the study found that income disparity has increased significantly since the 1980s, with the top 2% of recipients experiencing the largest gains in income. The study also found that socioeconomic factors such as education and occupation were strong predictors of income disparity. Unterhalter, et al. (2022) examined the features of GD in education. Unterhalter, argued that GD in education is characterized by several features, including: gendered patterns of participation and achievement, curricula and pedagogy, hierarchies of knowledge, and patterns of employment and career opportunities. Unterhalter, argued that these features of GD in education are shaped by broader social, economic, and political structures and are reinforced by gendered norms and values.

2.8Working definition of gender disparity

GD refers to unequal and unsatisfactory treatment, perceptions of respondents because of gender. It occurs when one gender (usually women) is disadvantaged and discriminated against compared with the other gender (usually men. GD can occur in numerous aspects of life, including employment, education, access to resources and services, and politics. Some examples of GD include unequal pay, limited access to education or job opportunities, discrimination and harassment, limited reproductive rights, and restricted roles and expectations based on gender discrimination. GD can have negative consequences for respondents and society as a whole, including limiting opportunities and potential, perpetuating poverty, and increasing social and economic inequalities.

2.9The Research Gap, Necessity, and Objectives of the Study

The study of the effects of gender disparity on housing development is important for several reasons. Gender disparity in housing is a significant problem that affects millions of people worldwide, and it is essential to understand the specific ways in which this problem manifests in different contexts. By investigating the effects of gender inequality on housing development in the study area, this study contributes to the growing body of literature in this area and identifies strategies to address this problem in the global context. Iwo is a rapidly developing city that has experienced significant changes in recent years. Despite this progress, significant gaps remain in access to affordable and secure housing, particularly for women. This study will help inform policies and programs aimed at promoting gender equality and improving access to housing for all community members. Housing is a basic human need and plays a critical role in the overall well-being and quality of life of many families. Adequate and affordable housing is essential for physical, emotional, and mental health, education, and economic mobility. Therefore, understanding and addressing the ways in which gender disparity affects housing development is important for promoting communities’ overall well-being and development.

3.The Study Area

The general intent of this study is to examine the effects of GD on housing development in the Iwo local government area of Osun State, Nigeria. Iwo is a rapidly developing city; however, it faces significant challenges related to GD in housing. This study explores the specific ways in which GD affects housing development in Iwo and identifies strategies to promote gender equality and improve access to housing for all members of the community. Iwo has four local government areas because of its large population. This study focused only on the Iwo Central Local Government where GD had been noticed.

Iwo has been observing the disparity of gender in housing development, and it is obvious that the disparity continues to grow because of gender inequality. These inequalities are very noticeable in the Iwo central local government. Therefore, the experience of Iwo regarding GD in housing development is a critical and important aspect that has brought the need for the study. Iwo city has over 30 prehistoric and influential kings all lower than the Oluwo of Iwo land, the only paramount ruler and consenting authority. Iwo city has an area of 245km²and a population of 343,913 according to 1.6% annual population change (2006 – 2022) from Nigerian National Census Figures. The city migrated from Ile-Ife in the 14^th century and is located in Osun State, Western Nigeria. The headquarters of the three local government areas are Iwo, centrally located in Iwo, Ola-Oluwa in Bode-Osi. Furthermore, Ayedire in Ile-Ogbo. Iwo now has four additional local governments: Iwo West, Iwo East, Ayedire southeast, and Ola-Oluwa southeast. The city is located between the latitudes 7⁰38¹N and longitude 4⁰11¹E. Figure 2. Map of Iwo City.

Figure 2. Maps of Osun and the location of Iwo city and Nigeria Map.

4.Research Methodology

The sources of data for this study were secondary and primary data. Primary data were obtained mainly through the administration of questionnaires to residents (landlords or tenants) in the study area. The questionnaires were administered to the targeted residents (landlord or tenants). The questionnaire focused on the effects of GD on housing development. The study area, the Iwo Central LGA, comprises 15 political wards. The estimated population of Iwo LGA is 191,348, consisting of 96,419 males and 94,929 females, according to 1.6% annual population change (2006 – 2022) from Nigerian National Population Census figures. Data were collected from 15 ward areas in Iwo Central LGA. The sample size selected for the study was 50% of the targeted population residents (landlord or tenant), which is believed to have a statistically significant effect on the results outcome and is large enough to prevent erroneous inference, also due to resource limitations and constraints. The study population comprised either landlords or tenants. This study first adopted a systematic sampling method to identify residential buildings. A systematic random sampling technique was used to select dwelling units in the study area. After the first building was selected randomly, every other 5th building in the study area was selected for questionnaire administration. The rationale behind the selection of a systematic random sampling procedure is that it is necessary to understand the whole population's characteristics. The aim is to produce a sample that best represents the target population in the study area. Systematic sampling was adopted because it is a convenient and simple way of establishing a sample population that is free from bias or favouritism. In addition, there is no need to number each member of the sample. The sampling procedure is fast and simple.

Based on a preliminary survey, this study focused on selected areas that seem to have high GD in housing development. Data collection was based on three (3) areas in Iwo Central LGA, concentrating on residential buildings in these areas due to the high prevalence of GD. The areas selected included Feesu, Isale-Oba, and Adeeke, comprising 408, 146, and 102 properties, respectively. Based on Table 1, approximately 50% of the total number of residents was selected for the assessment. A total of three hundred and twenty-eight (328) questionnaires were distributed to the residents (landlords or tenants) in the study area.

To obtain information from residents (landlord or tenant), systematic sampling techniques were used. Starting with a random start, after which the first building is chosen. This is because of the large size of the population and the homogenous nature of the population. Table 2 presents the percentage of the area selected for the sample in the selected areas.

Table 1: Summary of the study population, sampling frame, size, and sampling technique.

S/N

Study Population

Sampling Frame

Sampling Size

50%

Sampling Technique

Residential Buildings

656

328

Systematic sampling technique

Table 2: Population of residents selected as a sample in the study area.

Selected Areas	Total number of properties in the selected areas	50% Sample Units
Feesu	408	204
Isale-Oba	146	73
Adeeke	102	51
Total	656	328

The respondents were given a questionnaire to use as a schedule for interviews. The respondents in the study area were selected using a systematic sample technique. After the first (1^st) was randomly selected, every other odd building was selected for questionnaire administration in the study area. In each of the selected areas, the landlords or tenants were interviewed.

5.Discussion of the Findings

In total, 53% retrieval rate was attained. This was sufficient to generalize the effect of GD on housing development. Table 3 presents the response rate and questionnaire distribution.

Table 3: Questionnaire distribution and response rate.

Respondents (Building Occupiers)	Number Distributed	Number Retrieved	Percentage (%)
Feesu	204	78	38(%)
Isale Oba	73	36	49 (%)
Adeeke	51	39	76 (%)
Total	328	153	53 (%)

5.1Socioeconomic Characteristics of Respondents

The socioeconomic characteristics of the respondents consisted of educational qualification, gender, age, marital status, level of education, occupation, income level, household size, household position, average monthly income level, tenancy, length of residency and ethnicity, as revealed in Table 4.

Table 4: Socioeconomic Characteristics of Respondents.

1	Gender	Number of respondents	Percentage (%)	7	Househol, d Position	Number of respondents	Percentage (%)
	Male	71	46.4		Father	55	35.9
	Female	82	52.9		Mother	34	22.2
	Total	153	100		Child	41	26.8
					Relatives/Dependent	23	15.0
2	Age	Number of respondents	Percentage (%)		Total	153	100.0
	18-30	80	52.3
	31-40	36	23.5	8	Average monthly income level	Number of respondents	Percentage (%)
	41–50	31	20.3		LESS THAN N18,000	81	52.9
	51-60	6	3.9		N18,000–N50,000	23	15.0
	Total	153	100.0		N51,000–N150,000	25	16.3
					N151,000–N300,000	18	11.8
3	Marital Status	Number of respondents	Percentage (%)		Above N 300,000	6	3.9
	SINGLE	76	49.7		Total	153	100.0
	MARRIED	64	41.8
	DIVORCED	11	7.2	9	Tenancy	Number of respondents	Percentage (%)
	SEPARATED	2	1.3		Owner	69	45.1
	Total	153	100.0		Rented	71	46.4
					Others, specify	13	8.5
4	Level of Education	Number of respondents	Percentage (%)		Total	153	100
	PRIMARY	4	2.6
	SECONDARY	68	44.4	10	Length of Residency	Number of respondents	Percentage (%)
	OND/NCE	30	19.6		1 year	37	24.2
	HND	28	18.3		1-5 years	37	24.2
	B.SC/B.A	23	15.0		6-10 years	26	17.0
	Total	153	100.0		11-15 years	28	18.3
					Over 15 years	25	16.3
5	Occupation	Number of respondents	Percentage (%)		Total	153	100
	STUDENT	59	38.6
	CIVIL SERVICE	52	34.0	11	Ethnicity	Number of respondents	Percentage (%)
	TRADING	21	13.7		Igbo	11	7.2
	SELF-EMPLOYED	15	9.8		Hausa	16	10.5
	UNEMPLOYED	6	3.9		Yoruba	105	68.6
	Total	153	100.0		Urhobo	16	10.5
					Itsekiri	3	2.0
6	Household Size	Number of respondents	Percentage (%)		Other, specify	2	1.3
	1-2	34	22.2		Total	153	100.0
	3-4	43	28.1
	5-6	50	32.7
	7-8	26	17.0
	Total	153	100.0

Table 4 presents the socioeconomic characteristics of the respondents, encompassing data from 153 individuals. Of these respondents, 71 (46.4%) were male and 82 (52.9%) were female. The percentages indicate the relative distribution of each gender within the population and highlight a slightly higher proportion of females (52.9%) compared to males (46.4%).

Table 4 also illustrates the age-group distribution of the 153 respondents. The data reveal that the "18 to 30" age group is the largest, with 80 respondents (52.3%), indicating that a substantial segment of the population falls within this youthful demographic. The "31 to 40" age group comprises 36 respondents (23.5%), while the proportion of respondents in older age categories continues to decline. Overall, a significant majority of the population belongs to the "18 to 30" age group (52.3%), followed by a gradual decrease in representation among older age cohorts.

Furthermore, Table 4 includes data on the marital status of the 153 respondents. Four categories were utilized—single, married, divorced, and separated. The largest group was the "Single" category, with 76 respondents (49.7%), followed by the "Married" category, which included 64 respondents (41.8%). The "Divorced" category comprised 11 respondents (7.2%), and the "Separated" category represented 2 respondents (1.3%). The combined proportion of respondents who were single or married amounted to 91.5%, indicating that most participants fell into these two categories.

Educational qualifications of the respondents are also depicted in Table 4. Of the 153 respondents, the majority attained a secondary-level education (68 respondents, 44.4%). Other notable categories included OND/NCE (30 respondents, 19.6%), HND (28 respondents, 18.3%), and B.Sc./B.A. degrees (23 respondents, 15.0%). A small proportion (4 respondents, 2.6%) had only primary-level education. These data underscore the prominence of secondary education as the highest qualification for a substantial segment of the sample.

Occupational distribution, as shown in Table 4, indicates that students constituted the largest occupational category (59 respondents, 38.6%), followed closely by those employed in civil service positions (52 respondents, 34.0%). Other occupational groups included trading (21 respondents, 13.7%), self-employment (15 respondents, 9.8%), and unemployment (6 respondents, 3.9%). Overall, a significant proportion of the population comprised students and civil servants, with smaller segments engaged in trading or self-employment and a very modest group unemployed.

Household size distribution is also reported in Table 4. Among the 153 households, the "5 to 6" members category was the largest (50 households, 32.7%), reflecting a preference or prevalence of moderately large households. Households with "3 to 4" members followed (43 households, 28.1%), while smaller households with "1 to 2" members (34 households, 22.2%) and larger households with "7 to 8" members (26 households, 17.0%) were comparatively less common.

Table 4 further elucidates the roles of respondents within their households. Fathers represented the largest category (55 respondents, 35.9%), followed by children (41 respondents, 26.8%), mothers (34 respondents, 22.2%), and relatives/dependents (23 respondents, 15.0%). This distribution suggests that a substantial portion of the respondents were either heads of households or children, with a smaller yet notable representation of mothers and dependents.

With regard to income levels, Table 4 reveals that 81 respondents (52.9%) reported earning less than N18,000, suggesting that a majority of the population fell into a lower income bracket. The next largest income groups were N51,000 to N150,000 (25 respondents, 16.3%) and N18,000 to N50,000 (23 respondents, 15.0%). Higher-income categories included N151,000 to N300,000 (18 respondents, 11.8%) and above N300,000 (6 respondents, 3.9%). Thus, the data point to a pronounced concentration of respondents in lower-income brackets, supporting prior findings that socioeconomic factors—such as education and occupation—play a vital role in shaping income disparities (Emmanuel and Zucman, 2020).

Housing tenure and ownership status, as detailed in Table 4, indicate that 62 respondents (40.5%) owned their homes, while 71 respondents (46.4%) rented their accommodations. Thirteen respondents (8.5%) reported other forms of tenure requiring further specification. These figures highlight that most respondents either owned or rented their housing, with a smaller proportion falling into other categories.

Regarding the length of time spent in a given situation or context, the respondents’ duration is relatively evenly distributed among those who spent "less than a year" (37 respondents, 24.2%), "1 to 5 years" (37 respondents, 24.2%), and "6 to 10 years" (26 respondents, 17.0%). Those who spent "11 to 15 years" accounted for 28 respondents (18.3%), and the "over 15 years" group comprised 21 respondents (13.7%). These data suggest a fairly balanced temporal distribution of the respondents’ experience levels or durations.

Ethnic distribution, presented in Table 4, shows that Yoruba respondents comprised the majority of the population (105 respondents, 68.6%). The other major ethnic groups included Hausa and Urhobo (16 respondents each, 10.5%), and Igbo (11 respondents, 7.2%). Smaller ethnic categories were Itsekiri (3 respondents, 2.0%) and others requiring specification (2 respondents, 1.3%). This ethnic composition indicates a predominance of Yoruba respondents, with other ethnic groups represented to a lesser extent.

These findings align with the scholarship of Emmanuel and Zucman (2020), reinforcing the notion that socioeconomic factors, such as education and occupation, serve as significant predictors of income inequality within populations. The patterns observed in Table 4 corroborate this linkage, emphasizing how variations in education, income, and occupational status contribute to the broader socioeconomic dynamics of the study area.

5.2Housing Development Types

This data shows the type of house each respondent lives in, including single-family homes, apartments, townhouses, senior housing, mansions, traditional housing, duplexes, detached houses, and so on, as listed below.

Table 5: Types of Houses Lived in.

House's type	Number of respondents	Percentage (%)
Single-family homes	48	31.4
Townhouse	17	11.1
Apartment	51	33.3
Senior housing	12	7.8
Traditional housing	8	5.2
Duplex	8	5.2
Detached house	3	2.0
Bungalow	2	1.3
Mansion	2	1.3
Condominiums	2	1.3
Total	153	100.0

Table 5 presents the types of houses in which the respondents live. The data included information on 153 respondents, and the types of houses were categorized into multiple groups. The "Single Family Homes" category consists of 48 respondents, representing 31.4% of the total population. This category includes respondents living in standalone houses designed for single families. The "Townhouses" category includes 17 respondents, accounting for 11.1% of the population. This category includes respondents living in houses that are part of a connected row or terrace. The "Apartment" category comprises 51 respondents, making up 33.3% of the population. This category includes respondents living in apartments in large residential buildings. The "Senior Housing" category consists of 12 respondents representing 7.8% of the population. This category includes respondents living in housing specifically designed for senior citizens. The "Traditional Housing" category includes 8 respondents, accounting for 5.2% of the population. This category includes respondents living in houses that adhere to traditional architectural styles and cultural norms. The "Duplex" category consists of 8 respondents, representing 5.2% of the population. This category includes respondents who live in houses divided into two separate units. The "Detached House" category includes 3 respondents, accounting for 2.0% of the population. This category includes respondents living in standalone houses that are not connected to other structures.

The "Bungalow" category consists of 2 respondents, representing 1.3% of the population. This category includes respondents living in small, single-story houses. The "Mansion" category includes 2 respondents, accounting for 1.3% of the population. This category includes respondents living in large, luxurious residences. The "Condominiums" category consists of 2 respondents, representing 1.3% of the population. This category includes respondents living in units within a larger residential building, typically with shared amenities. The majority of respondents lived in single-family homes (31.4%), followed by apartments (33.3%). There was also a notable presence of townhouses (11.1%) and senior housing (7.8%). The remaining categories, such as traditional housing, duplexes, detached houses, bungalows, mansions, and condominiums, comprised smaller proportions of the total population. In summary, the data show that respondents mostly live in apartment-type housing. The findings of this study agree with Stromann-Andersen et al. (2014). This study found that multi-story apartment/buildings had the lowest environmental impact due to their compactness and ability to share resources, such as heating and cooling systems.

5.3Features Influencing Gender Disparity in the Study Area

These data represent the features that influence GD according to the respondents’ perspectives. The results presented in Table 6 indicate the features that contributed to and influenced gender disparity in the study area. The relative significant index (RSI) of factors influencing gender disparity in the study area indicates that 5 variables out of 10 identified variables had an RSI above average of 3.90, which were considered major significant factors influencing gender disparity in the study area. These include societal mindsets, lack of bodily autonomy, lack of employment equality, lack of political representation, and lack of religious freedom, with positive deviations and RSIs of 4.23, 4.06, 4.00, 3.99, and 3.99. The study revealed that among all factors, job segregation, uneven access to education, lack of legal protection, racism, and poor medical care were with negative deviations and RSI of 3.86, 3.80, 3.77, 3.73, and 3.58, respectively, which were considered less significant factors influencing gender disparity in the study area.

Table 6: Features Influencing Gender Disparity in the Study Area.

Feature of gender disparity	SD	D	NAND	A	SA	TNR	SWV	Mean
Societal mindsets	18	0	4	56	75	153	647	4.23
Lack of bodily autonomy	7	20	5	46	75	153	621	4.06
Lack of employment equality	12	11	5	62	63	153	612	4.00
Lack of political representation	6	16	4	75	52	153	610	3.99
Lack of religious freedom	6	16	4	75	52	153	610	3.99
Job segregation	18	15	3	51	66	153	591	3.86
Uneven access to education	13	21	2	65	52	153	581	3.80
Lack of legal protection	22	6	3	76	46	153	577	3.77
Racism	14	14	6	84	35	153	571	3.73
Poor medical care	17	17	11	76	32	153	548	3.58
Average								39.01/10=3.90

Note: SD= Strongly Disagree D= Disagree NAND= Neither Agree nor Disagree A=Agree SA= Strongly Agree, Sum of Weighted Value = SWV, Total Number of Respondents = TNR

Table 6 presents the responses regarding features that influence GD in a specific area. The data include information from 153 respondents who were asked to indicate their level of disagreement or agreement with the statement on the influence of uneven access to education on gender inequalities. The responses were categorized into several options. The "Disagree" category consists of 17 respondents representing 11.1% of the total population. This category represents respondents who disagree with the statement that uneven access to education influences gender inequalities in their area. The "Strongly Disagree" category includes 17 respondents, accounting for 11.1% of the population. This category includes respondents who strongly disagree with the statement. The "Neither Agree or Disagree" category comprises 11 respondents, representing 7.2% of the population. This category represents respondents who neither agree nor disagree with the statement. The "Agree" category consists of 76 respondents representing 49.7% of the population. This category represents respondents who agree with the statement.

The "Strongly Agree" category includes 30 respondents, accounting for 19.6% of the population. This category includes respondents who strongly agree with the statement. For (Uneven Access to Education), most respondents expressed agreement with the statement, with 54.9% agreeing and 21.6% strongly agreeing. A smaller proportion disagreed (9.2%) or strongly disagreed (9.2%) with the statement. Some respondents did not agree or disagree (3.9%), and a few respondents selected other response options (1.3%). The result obtained on Lack of Legal Protections shows that a significant number of respondents strongly agreed (30.1%) that the lack of legal protections influences gender inequalities. The majority agreed (49.7%), whereas a smaller proportion disagreed (14.4%) or strongly disagreed (3.9%). Some respondents did not agree or disagree (2.0%). For (Job Segregation), the highest percentage of respondents strongly agreed (41.2%) that job segregation contributes to gender inequalities. A significant number of respondents agreed (33.3%), whereas a smaller proportion disagreed (11.8%) or strongly disagreed (9.8%). Some respondents did not agree or disagree (2.0%), and a few selected other response options (2.0%). Regarding lack of bodily autonomy, most respondents strongly agreed (49.0%) that lack of bodily autonomy is a factor influencing gender inequalities. Some respondents agreed (30.1%), whereas a smaller proportion disagreed (4.6%) or strongly disagreed (13.1%). Some respondents did not agree or disagree (3.3%). For (Poor Medical Care), the highest percentage of respondents strongly agreed (34.0%) that poor medical care contributes to gender inequalities.

A significant number agreed (42.5%), whereas a smaller proportion disagreed (8.5%) or strongly disagreed (13.7%). Some respondents did not agree or disagree (1.3%). Regarding the lack of political representation, most respondents strongly agreed (34.0%) that a lack of political representation influences gender inequalities. Some respondents agreed (49.0%), whereas a smaller proportion disagreed (3.9%) or strongly disagreed (10.5%). Some respondents did not agree or disagree (2.6%). Finally, for (Societal Mindsets), the highest percentage of respondents strongly agreed (49.0%) that societal mindsets contribute to gender inequalities. Some respondents agreed (36.6%), whereas a smaller proportion did not agree or disagree (2.6%). A small percentage disagreed (11.8%). In summary, the data revealed different perceptions regarding the factors influencing gender disparity. Uneven access to education, job segregation, lack of bodily autonomy, and poor medical care are commonly acknowledged as influential factors by most respondents. The lack of legal protection and political representation has also received significant attention. Societal mindsets were considered influential by most respondents. These insights highlight the complex nature of gender inequalities and the various factors that contribute to them. This finding agrees with Unterhalter et al. (2022), which recognized that features of GD in education are shaped by broader social, economic and political structures and reinforced by gender norms and values.

5.3.1The Relationship between Gender Disparity Characteristics and Housing Development in the Study Area.

Table 7 shows the regression analysis results for the relationship between the variables of gender disparity characteristics and housing development in the study area. The dependent variables suitable for multiple regression analysis, they were summarized into one composite variable. This was done and variables of the features of Gender Disparity were statistically obtained. The dependent variable, housing development, was regressed (multiple regression) on the nine identified independent Gender Disparity characteristic variables. It is useful to mention here that the variables used for this analysis were mostly obtained as either nominal or ranking data (scale of measurement) percentages, and mean were thereafter computed to obtain tertiary data (as ratio scale) to make them amenable to parametric test (multiple regression). This was made possible by computing the means of variables related to spatial units. The results showed F–value of 99.964 and P–value of 0.04, which is significant at the 0.05 level. The relationship between gender disparity features and housing development was found to be significant. This indicates a strong relationship between the dependent and independent variables. The following variables with P-values that were significant at 0.05 levels comprised: Lack of employment equality, Lack of political representation, Job segregation, uneven access to education, Lack of legal protection, and Poor medical care (P-values of 0.014, 0.000, 0.000, 0.050, 0.010, 0.003, 0.041and 0.002 respectively.

Table 7: Multiple Regression Analysis of the Relationship Between Gender Disparity and Housing Development in the Study Area.

Model Summary
Model	R	R Square	Adjusted R-squared value	Std. Error in Estimate
1	.996^a	.992	.982	.04854
a. Predictors: (Constant), Societal mindsets, Lack of bodily autonomy, Lack of employment equality, Lack of political representation, Lack of religion freedom, Job segregation, Uneven access to education, Lack of legal protection, Racism, Poor medical care

ANOVA ^b
Model		Sum of Squares	Df	Mean Square	F	Sig.
1	Regression	3.062	13	.236	99.964	.004^a
	Residual	.026	11	.002
	Total	3.088	24
a. Predictors: (Constant), Societal mindsets, Lack of bodily autonomy, Lack of employment equality, Lack of political representation, Lack of religion freedom, Job segregation, Uneven access to education, Lack of legal protection, Racism, Poor medical care.
b. Dependent Variable: Housing Development

Coefficients^a
Model		Unstandardized Coefficients		Standardized Coefficients	T	Sig.
Model		B	Std. Error	Beta	T	Sig.
1	(Constant)	-1.531	1.655		-.925	.375
	Societal mindsets	.363	.124	.521	2.937	.014
	Lack of bodily autonomy	1.464	.156	1.382	9.379	.000
	Lack of employment equality	1.149	.201	1.287	5.718	.000
	Lack of political representation	-1.244	.573	-1.253	-2.170	.050
	Lack of religious freedom	.493	.407	.481	1.211	.251
	Job segregation	-1.291	.414	-.848	-3.122	.010
	Uneven access to education	.109	.146	.142	.749	.003
	Lack of legal protection	-.564	.271	-.444	-2.084	.041
	Racism	.143	.191	.330	.748	.470
	Poor medical care	.205	.052	.211	3.899	.002
a. Dependent Variable: Housing Development

Note: P-values significant at 0.05 levels

Table 8 shows the computed Pearson’s correlation coefficient (r) among pairs of the nine (9) identified relevant features of Gender Disparity variables in the study area. The study indicated that housing development had positive and no significant correlations (0.017 and 0.731) with variable societal mindsets (A) and Racism (I), respectively. It has positive and significant correlations with Lack of bodily autonomy (B), Lack of employment equality (C), Lack of political representation (D), Lack of religious freedom (E), Job segregation (F), Lack of legal protection (H), and poor medical care (J), with coefficients of 0.699, 0.378, 0.616, 0.754, 0.333, 0.838, and 0.537, respectively. It had negative and significant correlations (0.277) with uneven access to education (G). The correlation was significant at the 0.01 and 0.05 levels.

Table 8: Correlation Coefficients among Features of Gender Disparity and Housing Development Using Pearson’s Correlation Coefficient (r) for the Study Area.

S/No	Variables	A (i)	B (ii)	C (iii)	D (iv)	E (v)	F (vi)	G (vii)	H (viii)	I (ix)	J (x)	K (xi)
(i)	Societal mindsets (A)	1
(ii)	Lack of bodily autonomy (B)	-.218	1
(iii)	Lack of employment equality (C)	.323	.464^*	1
(iv)	Lack of political representation (D)	-.005	.714^**	.835^**	1
(v)	Lack of religious freedom (E)	-.343	.955^**	.367	.679^**	1
(vi)	Job segregation (F)	.134	.557^**	.179	.297	.521^**	1
(vii)	Uneven access to education (G)	.266	.102	.435^*	.277	-.018	-.217	1
(viii)	Lack of legal protection (H)	-.218	.893^**	.468^*	.726^**	.912^**	.539^**	-.087	1
(ix)	Racism (I)	.126	.454^*	-.163	.037	.530^**	.547^**	-.489^*	.554^**	1
(x)	Poor medical care (J)	-.146	.213	.118	.300	.138	.585^**	-.358	.305	.019	1
(xi)	Housing Development (K)	.017	.699^**	.378^*	.616^**	.754^**	.333^**	-.277^*	.838^**	.731	.537**	1

**Correlation is significant at the 0.01 level (2-tailed).

* Correlation was significant at the 0.05 level (2-tailed).

5.4Effects of Gender Disparity Indices (EGDI) on Housing Development in the Study Area

Table 9 presents the results of the level of effects of gender disparity Indices on housing development in the study area according to the respondents’ perspectives. The result indicates that 3 variables out of 7 identified had an EGDI above average of 4.17, which are considered to have significant effects of gender disparity on housing development in the study area. These include: Denied access to housing, Homelessness, and Deprived access to services with positive deviation and EGDI of 4.36, 4.31, and 4.28, respectively. The study revealed that among all the 7 variables, Lack of property rights, Limited access to finance, deprived access to utility, and deprived access to basic education had negative deviations and EGDI of 4.13, 4.11, 4.09, and 3.95, respectively, which were considered significant but with unconventional effects of gender disparity on housing development in the study area.

Table 9: Effects of Gender Disparity Indices (EGDI) on Housing Development in the Study Area.

Effects of gender disparity	SD	D	NAND	A	SA	TNR	SWV	Mean
Denied access to housing	4	5	5	57	82	153	667	4.36
Homelessness	2	6	3	73	69	153	660	4.31
Deprived access to services	5	7	2	65	74	153	655	4.28
Lack of property rights	7	7	2	79	58	153	633	4.13
Limited access to finance	9	2	5	84	53	153	629	4.11
Deprived of utility access	1	3	2	122	25	153	626	4.09
Deprived of basic education	4	3	5	125	16	153	605	3.95
Average								29.23/7 = 4.17

The results obtained on types of housing development in the study area show that apartment buildings had the highest percentage of housing development, at 33.3%, followed by single-family homes at 31.4%. Other types of housing development include townhouses, senior housing, traditional housing, duplexes, bungalows, mansions, and condominiums, which are in the minority. Table 9 presents responses related to the effects of GD on various aspects. For (Deprived access to basic education), most respondents agreed (81.7%) that GD affects access to basic education. A significant number strongly agreed (10.5%), whereas a smaller proportion disagreed (2.6%) followed by strongly disagreed (2.0%). Some respondents did not agree or disagree (3.3%), with an average of 3.9281. For (access to utility), the highest percentage of respondents strongly agreed (16.3%) that GD leads to inaccessibility to utility services. A significant number of respondents agreed (79.7%), whereas a smaller proportion disagreed (0.7%) or strongly disagreed (2.0%). Some respondents did not agree (1.3%) 4.2418. For (Inadequate Access to Services), most respondents strongly agreed (48.4%) that GD results in inadequate access to services. Some respondents agreed (42.5%), whereas a smaller proportion disagreed (3.3%) or strongly disagreed (4.6%). Some respondents did not agree (1.3%) 4.2810. For (Denied Access to Housing), a significant number of respondents strongly agreed (51.6%) that GD leads to denied access to housing. Some respondents agreed (37.3%), whereas a smaller proportion disagreed (2.6%) or strongly disagreed (3.3%). Some respondents did not agree (3.3%) 5.3203.

For (Homelessness), most respondents strongly agreed (45.1%) that GD contributes to homelessness. Some respondents agreed (47.7%), whereas a smaller proportion disagreed (1.3%) or strongly disagreed (3.9%). Some respondents neither agreed nor disagreed (2.0%) 4.3137. For lack of property rights, the highest percentage of respondents strongly agreed (37.9%) that GD results in a lack of property rights. Some respondents agreed (51.6%), whereas a smaller proportion disagreed (4.6%) or strongly disagreed (4.6%). Some respondents did not agree (1.3%) 4.1373. Finally, regarding limited access to financing, most respondents agreed (54.9%) that GD leads to limited access. Some respondents strongly agreed (34.6%), whereas a smaller proportion disagreed (5.9%) or strongly disagreed (1.3%). Some respondents did not agree (3.3%) 4.1111. In summary, the data reveal that respondents perceive GD to have significant effects in various areas. Inaccessibility to basic education, utility services, and adequate services is recognized as a key consequence of GD. Denied access to housing, homelessness, lack of property rights, and limited access to financing are also highlighted as negative effects. These insights emphasize the broad impact of GD on different aspects of respondents’ lives in a given area. This finding agrees with the study of Chant, (2012), which established that women often face more significant barriers to accessing housing due to their lower incomes and lack of employment disparities.

5.5Relationship between the Effects of Gender Disparity and Housing Development

To determine the relationship between the effects of gender disparity and housing development in the study area, a regression analysis was conducted. Seven independent variables were identified; which comprised: Denied access to housing, homelessness, deprived access to services, lack of property rights, limited access to finance, deprived access to utility, and deprived access to basic education. Table 10 presents the results of the regression analysis of the relationship between variables of the effects of gender disparity and housing development in the study area. The results showed an F–value of 1.082E4 and a P–value of 0.003 which is significant at the 0.05 level. The relationship between the effects of gender disparity and housing development in the study area is significant. This indicates a strong relationship between the dependent and independent variables. The following variables with P-values that were significant at 0.05 levels comprised: denied access to housing, homelessness, deprived access to services, lack of property rights, limited access to finance, deprived access to utility, and deprived access to basic education (P-values of 0.032, 0.003, 0.004, 0.001, 0.002, 0.002, and 0.004 respectively.

Table 10: Multiple Regression Analysis of the Relationship between the Effects of Gender Disparity and Housing Development in the Study Area.

Model Summary
Model	R	R Square	Adjusted R-squared value	Std. Error in Estimate
1	0.815^a	0.798	0.755	.00332
a. Predictors: (Constant), Denied access to housing, homeless, deprived access to services, Lack of property rights, Limited access to finance, Deprived access to utility, and basic education

ANOVA^b
Model			Sum of Squares		Df		Mean Square		F		Sig.
1	Regression	1.548		13		.119		1.082E4		.003^a
	Residual	.000		11		.000
	Total	1.548		24
a. Predictors: (Constant), Denied access to housing, homeless, deprived access to services, Lack of property rights, Limited access to finance, Deprived access to utility, and basic education
b. Dependent Variable: Housing Development

Coefficients^a
Model			Unstandardized Coefficients				Standardized Coefficients		t		Sig.
Model			B		Std. Error		Beta		t
1	(Constant)	.651		.175				3.725		.003
	Denied access to housing	-.105		.043		-.165		-2.448		.032
	Homelessness	.165		.043		.217		3.863		.003
	Deprived access to services	.252		.069		.361		3.663		.004
	Lack of property rights	.177		.041		.235		4.344		.001
	Limited access to finance	-.303		.074		-.257		-4.083		.002
	Deprived of utility access	.047		.024		.070		1.954		.077
	Deprived of basic education	.205		.052		.211		3.899		.002
a. Dependent Variable: Housing Development

P-values significant at 0.05 levels

Table 11 shows the results of the computed Pearson’s correlation coefficient (r) among pairs of the seven (7) identified relevant Gender Disparity characteristics variables and Housing Development in the study area. The study indicated that housing development has negative and significant correlations (0.602) with variable denied access to housing (A). It has positive and significant correlations with homelessness (B), deprived access to services (C), lack of property rights (D), limited access to finance (E), and deprived access to utility (F), with coefficients of 0.939, 0.912, 0.943, 0.939, and 0.446, respectively. The correlation was significant at the 0.01 and 0.05 levels. Furthermore, the study revealed that housing development has positive and no significant correlations with Deprived access to basic education (G), with a coefficient of 0.261.

Table 11: Correlation Coefficients among the Effects of Gender Disparity and Housing Development in the Study Area Using Pearson’s Correlation Co-efficient (r).

S/No	Variables	A (i)	B (ii)	C (iii)	D (iv)	E (v)	F (vi)	G (vii)	H (viii)
(i)	Denied access to housing (A)	1
(ii)	Homelessness (B)	-.713^**	1
(iii)	Deprived access to services (C)	-.475^*	.782^**	1
(iv)	Lack of property rights (D)	-.468^*	.817^**	.963^**	1
(v)	Limited access to finance (E)	-.728^**	.992^**	.793^**	.826^**	1
(vi)	Deprived access to utility (F)	-.128	.382	.244	.242	.363	1
(vii)	Deprived of basic education (G)	.140	.411^*	.178	.221	.397^*	-.068	1
(viii)	Housing Development (H)	-.602^**	.939^**	.912^**	.943^**	.939^**	.446^*	.261	1

**Correlation is significant at the 0.01 level (2-tailed).

* Correlation was significant at the 0.05 level (2-tailed).

6.Study Findings in Relation to Existing Literature

The findings of this study corroborate those of Munir et al. (2021), who investigated the impact of gender inequality on housing development in Pakistan. Munir et al. observed that women confronted substantial obstacles in accessing housing, including barriers such as denied access, homelessness, restricted access to services, limited property rights, reduced access to finance, utilities, and basic education, as well as discrimination in the housing market. These challenges were particularly acute for women who were unmarried or divorced, underscoring the multifaceted dimensions of gender-based disadvantage. Furthermore, Munir et al. identified a broader association between gender disparities in societal contexts—such as education and employment—and lower levels of overall housing development.

The present study’s alignment with Crenshaw’s (1989) feminist theory is particularly noteworthy. Crenshaw’s intersectional framework suggests that women’s experiences and opportunities, including those related to housing, are not only shaped by gender but are also compounded by additional axes of inequality. Our findings highlight societal mindsets, lack of bodily autonomy, limited employment equality, insufficient political representation, restricted religious freedom, occupational segregation, uneven educational access, and inadequate legal protections, all of which converge to reinforce gender-based disparities in housing.

In addition, these findings support the United Nations Human Settlements Program (2012), which similarly identified significant barriers to women’s access to housing. According to the UN-Habitat report, women frequently encounter discrimination in the housing market and face limited access to credit, highlighting the structural nature of these inequalities. This body of evidence further indicates that gender disparities in education and employment adversely affect housing development outcomes.

Our results are also consistent with Kabeer and Waddington (2015), who examined gender disparities in housing conditions in Bangladesh. Their study found that women were more likely to reside in homes with poor sanitation and inadequate water supply, conditions partially rooted in gender-based discrimination in resource allocation and the enforcement of restrictive gender norms that limit women’s mobility and decision-making power.

This research is in agreement with Henry (2000), who explored gender and housing development in low-income suburbs of Jinja Municipality, Uganda. Henry’s findings regarding the features and effects of gender disparity on housing closely parallel those observed in the current study. Furthermore, Adeoye (2018) examined factors influencing gender differentials in urban informal housing development in southwestern Nigeria and identified similar forms of inequality, including homelessness and reduced access to essential services, utilities, and education.

This study further endorses earlier work by Asiyanbola (2010; 2011), who explored gender and involvement in housing development in Ibadan, Nigeria. Their analysis of variations in women’s perceived involvement, awareness, and actual engagement in housing projects resonates with the conclusions drawn here. Similarly, Bengtsson et al. (2011) conducted a field experiment investigating the gender gap in rental housing, while Blau and Kahn (2017) examined the gender wage gap and its implications for housing development, both studies complementing the patterns identified in the present research.

Additionally, our findings affirm those of Meth et al. (2019), who compared gender inequality and housing development in South Africa and India, uncovering parallel issues of gender-based inequity. The current study’s outcomes also support the work of the International Labor Organization (2021), Sanders and Scanlon (2000), and Harcourt and Escobar (2002), which have addressed the politics of place, culture, and gender in mortgage lending discrimination, further illustrating that gender is a critical lens through which to understand and address disparities in housing and related development arenas.

7.Summary of the Findings

The findings of this study demonstrate that gender disparity (GD) significantly hinders women’s access to housing in the examined area. In particular, prevailing inheritance laws and sociocultural norms frequently favor male family members, thereby limiting women’s rights to inherit property or secure legal ownership. The study further establishes that entrenched cultural conventions and discriminatory practices constrain women’s ability to independently own or rent housing units.

Economic factors also emerged as critical determinants of housing development outcomes. The study found that GD amplifies economic inequalities, restricting women’s financial resources and, in turn, their capacity to secure adequate housing. As a consequence of persistent gender wage gaps and occupational segregation, women often have lower incomes and fewer employment prospects, resulting in financial instability and reduced access to affordable, safe, and decent housing options.

The research confirmed that GD contributes to substandard living conditions for women. Compared to men, women are more likely to reside in overcrowded, unsafe, and inferior-quality housing. Moreover, they frequently encounter discriminatory practices—such as elevated rental prices, restricted property rights, and limited housing choices—when attempting to secure living arrangements. In marginalized communities, women bear the brunt of inadequate basic amenities, including access to clean water, electricity, and proper sanitation facilities, further exacerbating their vulnerability.

In addition, the study reveals that GD diminishes women’s decision-making power and participation in housing-related matters. Women often possess limited control over household resources and remain excluded from critical housing decisions. Domestic violence, insecurity of tenure, and patriarchal norms further erode women’s agency, impeding their active involvement in planning and decision-making processes within the housing development landscape.

7.1Policy implications of the findings

The findings of this study will aid in the formulation of relevant policies with the aim of providing information that will enhance gender balance in housing development. This policy seeks to promote gender equality and ensure equitable access to safe, affordable, and adequate housing for all residents, regardless of gender.

8.Conclusion and Recommendations

The study concluded that gender disparity (GD) in the study area significantly affects women’s access to housing development. Women are often subjected to discriminatory practices when seeking housing, such as higher rental rates, limited options, and restricted property ownership rights. This study highlights the urgent need for comprehensive and targeted interventions to address GD in housing development by creating an inclusive housing environment that ensures equal rights, opportunities, and access for all genders.

The identified predictors of GD that inhibit housing development include societal mindsets, lack of bodily autonomy, lack of employment equality, lack of political representation, lack of religious freedom, job segregation, uneven access to education, lack of legal protection, racism, and poor medical care. These predictors should be considered in the development of policy frameworks for housing development. Additionally, the identified effects of GD, such as lack of access to housing, utilities, and services; homelessness; lack of property rights; limited access to finance; and deprived access to basic education, must be addressed through legislation designed to mitigate these issues.

The study aligns with Intersectionality and feminist theory, concepts developed by Crenshaw, which highlight the ways different identities intersect and mutually construct one another, creating unique experiences of oppression and privilege. Understanding and addressing how GD affects housing development is crucial for promoting the overall well-being and development of communities.

This study provides valuable insights into the impacts of GD on housing development as a key socioeconomic attribute. The findings emphasize the need for informed policy frameworks that enhance housing development and address gender disparities effectively. To address these disparities, enhancing women’s access to housing finance through gender-responsive loan programs, microfinance schemes, and subsidies is crucial. Affordable housing options targeted toward low-income women and vulnerable groups must be provided, along with housing subsidies or rental assistance programs to alleviate financial burdens and ensure women’s access to safe and adequate housing. Strengthening women’s legal protection is essential by improving mechanisms to guard against domestic violence, eviction, and discrimination in the housing sector and establishing specialized courts or dispute resolution systems for prompt action on housing-related gender issues.

Fostering gender-responsive urban planning and design is vital to ensure safe and accessible housing infrastructure for women, incorporating women’s perspectives in project designs and addressing their specific needs, such as childcare facilities and proximity to essential services. Investments in gender-sensitive social infrastructure, including community centers, childcare facilities, and healthcare services, must be prioritized, along with ensuring equal provision of basic amenities such as water, sanitation, and electricity. Strengthening data collection and research on gender-disaggregated housing indicators will inform evidence-based policy formulation and effective interventions. Collaborating with women’s organizations and gender-focused NGOs will further address gender-specific housing concerns and advocate for equality in housing policies. Key actions include enacting gender-sensitive legislation, promoting women’s property rights, and engaging civil society organizations in collective efforts to ensure gender equality in housing. Addressing these disparities is not only a matter of social justice but a prerequisite for sustainable and inclusive development. By prioritizing gender equality, we can pave the way for a more equitable and prosperous future where everyone has access to safe, affordable, and dignified housing, regardless of gender.

Acknowledgements

We want to express our heartfelt gratitude to the Department of Architecture, Faculty of Environmental Sciences, LAUTECH, Nigeria Ogbomoso, Oyo State, Nigeria and Department of Estate Management, Faculty of Environmental Design and Management, Osun State University, Osogbo, Nigeria, for their unwavering support, resources, and invaluable contributions to the successful completion of this work.

Funding

This research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Conflicts of Interest

The authors declare no conflicts of interest related to this research.

Data availability statement

The data supporting this study are available from the corresponding author upon reasonable request.

Institutional Review Board Statement

Not applicable.

CRediT author statement:

Conceptualization: Dr. Olusola Oladapo Makinde; Methodology: Dr. Olusola Oladapo Makinde and Olubukunmi Temitope Makinde; Software: Dr. Olusola Oladapo Makinde; Formal Analysis:

Dr. Olusola Oladapo Makinde; Investigation: Olubukunmi Temitope Makinde; Resources: Dr. Olusola Oladapo Makinde; Data Curation: Dr. Olusola Oladapo Makinde and Olubukunmi Temitope Makinde; Writing-Original Draft: Dr. Olusola Oladapo Makinde; Writing-Review &

Editing: Dr. Olusola Oladapo Makinde and Olubukunmi Temitope Makinde; Visualization: Dr. Olusola Oladapo Makinde and Olubukunmi Temitope Makinde. All authors have reviewed and approved the final version of the manuscript.

References

Adeosun, O. T., & Owolabi, K. E. (2021). Gender inequality: Determinants and outcomes in Nigeria. Journal of Business and Socio-economic Development, 1(2), 165–181. https://doi.org/10.1108/JBSED-01-2021-0007

Adeoye, D. O. (2018). Factors influencing gender differentials in involvement in housing development in Ebonyi State, Nigeria. Ibadan Planning Journal, 7(1&2), 30–40. Retrieved from https://journals.ui.edu.ng/index.php/ipj/article/view/382/335

Asiyanbola, R. A. (2010). Urbanization, gender and transport research issues and insights in Nigeria: Towards a sustainable gender sensitive transport development. The Nigerian Journal of Sociology and Anthropology, 8(1), 159–176. https://doi.org/10.36108/NJSA/0102/80(0120)

Asiyanbola, R. A. (2011, July 7–9). Gender and urban housing settings in Africa–Nigeria. The International RC21 Conference 2011, Session 22: Reconstructing Gender in Urban Space (RT 22.1: Gendered Struggles to Belong). The Struggle to Belong: Dealing with Diversity in 21st Century Urban Settings, Amsterdam, The Netherlands.

Atser, J., & Beulah, O. (2007). A study of the demand and supply of housing in Uyo, Akwa Ibom State Nigeria. Journal of the Nigerian Institute of Town Planners, 20(1).

Baker, E., & Bentley, R. (2023). Housing and health: A time for action. International Journal of Housing Policy, 23(2), 197–200. https://doi.org/10.1080/19491247.2023.2204650

Bengtsson, R., Iverman, E., & Hinnerich, B. T. (2012). Gender and ethnic discrimination in the rental housing market. Applied Economics Letters, 19(1), 1–5. https://doi.org/10.1080/13504851.2011.564125

Blau, F. D., & Kahn, L. M. (2017). The gender wage gap: Extent, trends, and explanations. Journal of Economic Literature, 55(3), 789–865. https://doi.org/10.1257/jel.20160995

Center for American Progress. (2018, March 20). Fact sheet: The state of women in America: Housing and homelessness. https://www.americanprogress.org/article/state-women-america-housing-homelessness/

Chant, S. (2012). Gender and urban housing in the global south. In S. J. Smith (Ed.), International Encyclopedia of Housing and Home (pp. 255–263). Elsevier. https://doi.org/10.1016/B978-0-08-047163-1.00005-9

Crenshaw, K. (1989). Demarginalizing the intersection of race and sex: A black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. University of Chicago Legal Forum, 1989(1), 139–167. http://chicagounbound.uchicago.edu/uclf/vol1989/iss1/8

Devlin, A. S. (1994). Gender-role and housing preferences. Journal of Environmental Psychology, 14(3), 225–235. https://doi.org/10.1016/S0272-4944(94)80058-8

Gülcimen, S., Uzal, N., & Varışlı, T. (2021). Comparison of environmental performance of single-family house and multi-storey apartment in Turkey using life cycle assessment. Research Square. https://doi.org/10.21203/rs.3.rs-1027577/v1

Harcourt, W., & Escobar, A. (2002). Women and the politics of place. Development, 45(1), 7–14. https://doi.org/10.1057/palgrave.development.1110308

Healy, J., & Zucca, L. J. (2004). The gender equity gap in top corporate executive positions. Mid-American Journal of Business, 19(1), 55–62. https://doi.org/10.1108/19355181200400006

Henry, M. (2000). Gender and housing development in the low-income suburbs of Jinja Municipality: Uganda. (Gender Issues Research Report Series No. 17). Centre for Basic Research.

International Housing Coalition. (2021). Women and housing. https://www.internationalhousingcoalition.org/women-and-housing

International Labour Organization. (2021). Gender discrimination. https://www.ilo.org/global/topics/gender-equality/gender-discrimination/lang--en/index.htm

Iqbal, H., Afzal, S., & Inayat, M. (2012). Gender discrimination: Implications for Pakistan security. IOSR Journal of Humanities and Social Science, 1(4), 16–25. https://doi.org/10.9790/0837-0141625

Kabeer, N., & Waddington, H. (2015). Economic impacts of sanitation in Bangladesh: Summary report. Institute of Development Studies, University of Sussex. Retrieved from

Kim, S.-W., Cho, H., & Kim, L. Y. (2019). Socioeconomic status and academic outcomes in developing countries: A meta-analysis. Review of Educational Research, 89(6), 875–916. https://doi.org/10.3102/0034654319877155

Makinde, O. O. (2014a). Housing delivery system, need and demand. Environment, Development and Sustainability, 16(1), 49–69. https://doi.org/10.1007/s10668-013-9474-9

Makinde, O. O. (2014b). Influences of socio-cultural experiences on residents’ satisfaction in Ikorodu low-cost housing estate, Lagos State. International Journal of Sustainable Building Technology and Urban Development, 5(3), 205–221. https://doi.org/10.1080/2093761X.2014.927810

Makinde, O. O. (2016a). Evaluating indigenous environmental consciousness for residents of Ogbomoso in Nigeria. Journal of Geography and Regional Planning, 9(5), 87–103. https://doi.org/10.5897/jgrp2015.0524

Makinde, O. O. (2016b). Evaluating public housing quality in Ogun State, Nigeria. Environment, Development and Sustainability, 18(3), 679–695. https://doi.org/10.1007/s10668-016-9832-5

Makinde, O. O. (2020). Prefiguring housing quality in urban communities in Ibadan Nigeria. SIASAT Journal of Social, Cultural and Political Studies, 5(4), 65–76. https://doi.org/10.33258/siasat.v5i4.72

Mani, J. R., Bello, M., Oladimeji, Y. U., & Olayiwola, F. (2024). Standard of living, gender dimensions and women empowerment among Fulani pastoralist in Kaduna State, Nigeria. African Journal of Agricultural Research, 20(7), 530–546. https://doi.org/10.5897/AJAR2023.16556

Marcus, R., & Somji, A. (2024). Transforming gender norms for women’s economic rights and empowerment. ALIGN Report. London: ODI.

Meth, P., Buthelezi, S., & Rajasekhar, S. (2019). Gendered illegalities of housing formalisation in India and South Africa. Environment and Planning A: Economy and Space, 51(5), 1068–1088. https://doi.org/10.1177/0308518X18792898

Munir, F., Ahmad, S., Ullah, S., & Wang, Y. P. (2021). Understanding housing inequalities in urban Pakistan: An intersectionality perspective of ethnicity, income and education. Journal of Race, Ethnicity and the City, 3(1), 1–22. https://doi.org/10.1080/26884674.2021.1986442

Philippine Commission on Women. (2015). Gender equality and the Sustainable Development Goals. Retrieved from https://pcw.gov.ph/gender-equality-and-the-sustainable-development-goals/

Pohl, P., Tormey, M., & Dalton, N. (2007). Gender-based wage differentials among registered dietitians. The Health Care Manager, 26(1), 52–63. https://doi.org/10.1097/00126450-200701000-00007

Rabia, M., Tanveer, F., Gillani, M., Naeem, H., & Akbar, S. (2019). Gender inequality: A case study in Pakistan. Open Journal of Social Sciences, 7, 369–379. https://doi.org/10.4236/jss.2019.73031

Rakodi, C. S., & Bhatla, A. (2011). Gender and property rights: A critical issue in urban economic development. International Housing Coalition and Urban Institute.

Royal College of Nursing. (2012). Health inequalities and the social determinants of health. Policy & International Department, RCN.

Saez, E., & Zucman, G. (2020). The rise of income and wealth inequality in America: Evidence from distributional macroeconomic accounts. Journal of Economic Perspectives, 34(4), 3–26. https://doi.org/10.1257/jep.34.4.3

Saleemi, S., & Kofol, C. (2022). Women’s participation in household decisions and gender equality in children’s education: Evidence from rural households in Pakistan. World Development Perspectives, 25, 100395. https://doi.org/10.1016/j.wdp.2022.100395

Sanders, C. K., & Scanlon, E. (2000). Mortgage lending and gender. Affilia, 15(1), 9–30. https://doi.org/10.1177/08861090022093804

Santos, S. M., & Klasen, S. (2021). Gender inequality as a barrier to economic growth: A review of the theoretical literature. Review of Economics of the Household, 19, 581–614. https://doi.org/10.1007/s11150-020-09535-6

Schlyter, A. (Ed.). (1996). A place to live: Gender research on housing in Africa. The Nordic Africa Institute. http://www.diva-portal.org/smash/get/diva2:277422/FULLTEXT01.pdf

Skaburskis, A. (1997). Gender differences in housing demand. Urban Studies, 34(2), 275–320. https://doi.org/10.1080/0042098976186

Small, S. F. (2024). Gender marker laws and access to emergency rental assistance for transgender renters in the United States during COVID-19. Housing Policy Debate, 1–26. https://doi.org/10.1080/10511482.2024.2365255

Stewart, A., & Cloutier, D. (2021). More than a roof; challenges for older women renters in British Columbia, Canada. Journal of Women & Aging, 34(5), 582–595. https://doi.org/10.1080/08952841.2021.1948791

Turner, M. A., Ross, S. L., & Galster, G. C. (2002). Discrimination in metropolitan housing markets: National results from Phase I HDS 2000. Final report. The Urban Institute.

UN Habitat. (2014). The right to adequate housing. Office of the United Nations High Commissioner for Human Rights Fact Sheet No. 21/Rev.1. https://www.ohchr.org/sites/default/files/Documents/Publications/FS21_rev_1_Housing_en.pdf

UN Women. (2018). Gender and housing in the Pacific. Retrieved from https://www.unwomen.org/en/digital-library/publications/2018/10/gender-and-housing-in-the-pacific

UN Women. (2021). Women’s right to adequate housing. Retrieved from https://www.unwomen.org/en/what-we-do/housing-and-land-rights/womens-right-to-adequate-housing

United Nations Human Settlements Programme. (2012). Gender issue guide: Housing and slum upgrading. UN-Habitat. https://unhabitat.org/sites/default/files/2020/09/unhabitat_housing_and_slumupgrading.pdf

United Nations Population Fund. (2021). Reproductive health. Retrieved from https://www.unfpa.org/reproductive-health

United Nations. (2019). The right to adequate housing. Environment and Urbanization, 22(2), 230–245.

Unterhalter, E., Longlands, H., & Peppin Vaughan, R. (2022). Gender and intersecting inequalities in education: Reflections on a framework for measurement. Journal of Human Development and Capabilities, 23(4), 509–538. https://doi.org/10.1080/19452829.2022.2090523

Vásquez-Vera, C., Fernández, A., Sánchez-Ledesma, E., Bennett, M., & Borrell, C. (2023). Gender-based differences in the meanings and uses of housing for health and everyday life: An intersectional approach. Women’s Studies International Forum, 99, Article 102761. https://doi.org/10.1016/j.wsif.2023.102761

Wacquant, L. J. D. (1996). The rise of advanced marginality: Notes on its nature and implications. Acta Sociologica, 39(2), 121–139. https://doi.org/10.1177/000169939603900201

Wang, J., Hadjri, K., Bennett, S., & Morris, D. (2020). The role of cohousing in social communication and sustainable living environments. In A. G. Sayigh (Ed.), Global dwelling: Approaches to sustainability, design and participation (pp. 247–256). WIT Press. https://doi.org/10.2495/GD170201

World Economic Forum. (2020). The global gender gap report 2020. Retrieved from http://www3.weforum.org/docs/WEF_GGGR_2020.pdf

World Health Organization. (2021). Violence against women. Retrieved from https://www.who.int/news-room/fact-sheets/detail/violence-against-women

$D:\My Journal\Logo\kam logo.JPG$	Journal of Contemporary Urban Affairs
2025, Volume 9, Number 1, pages 115–142 Original scientific paper Gender Disparity and Housing Development: Examining Socioeconomic Barriers and Policy Solutions in Nigeria ^1Olusola Oladapo Makinde , ²Olubukunmi Temitope Makinde* ¹Department of Architecture, Faculty of Environmental Sciences, LAUTECH, Nigeria Ogbomoso, Oyo State, Nigeria ²Department of Estate Management, Faculty of Environmental Sciences, Osun State University, Osogbo, Nigeria ¹E-mail: makindeolusola2012@yahoo.com , ²E-mail: bukunmakinde2019@gmail.com
ARTICLE INFO: Article History: Received: 28 August 2024 Revised: 5 December 2024 Accepted: 10 December 2024 Available online: 13 December 2024 Keywords: Gender Disparity, Housing Development, Socioeconomic Barriers, Policy Solutions, Nigeria.	ABSTRACT Gender disparity (GD) significantly impacts housing development, especially in developing countries like Nigeria, where socioeconomic and cultural barriers constrain equitable housing access. This study investigates the features and effects of GD on housing development in Iwo Central Local Government Area, Osun State, Nigeria. Using a mixed-method approach, data were collected from 328 respondents through questionnaires and analyzed using descriptive and inferential statistics, including indices and ANOVA. Key findings highlight societal mindsets as the most influential feature of GD, followed by lack of bodily autonomy and employment equality, with respective relative significance indices (RSIs) of 4.23, 4.06, and 4.00. Denied access to housing and homelessness emerged as the most critical effects of GD, with effects indices (EGDIs) of 4.36 and 4.31. Regression analysis revealed a significant relationship between GD characteristics and housing development (F = 99.964, p = 0.04), emphasizing the pervasive impact of GD on housing equity. The study concludes that GD restricts women's access to adequate housing, perpetuating socioeconomic inequalities. Recommendations include promoting gender-responsive housing policies, enhancing women's access to affordable housing finance, and integrating gender equity into urban planning and housing design. Addressing GD is crucial for fostering inclusive, equitable, and sustainable housing development in Nigeria.

This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License (CC BY). $C:\Users\Hourakhsh\Desktop\CC_By_2020_licnece1.jpg$ Publisher’s Note: The Journal of Contemporary Urban Affairs remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
	JOURNAL OF CONTEMPORARY URBAN AFFAIRS (2025), 9(1), 115–142. https://doi.org/10.25034/ijcua.2025.v9n1-7 www.ijcua.com Copyright © 2025 by the author(s).
Highlights:		Contribution to the field statement:
- Gender disparity significantly impacts housing development in terms of availability, affordability, and quality. Societal mindsets and cultural norms are significant predictors of women’s access to housing. - Lack of financial autonomy among women is positively correlated with higher homelessness rates. - Unequal access to education significantly affects women’s participation in housing development processes. - Gender-responsive policies moderate the relationship between gender disparity and sustainable housing development.		This study bridges a critical gap in understanding the interplay between gender disparity and housing development, particularly in Nigeria's Iwo region. By integrating a mixed-methods approach, it highlights the socioeconomic and cultural barriers affecting equitable housing access. The findings advocate for gender-responsive policies, offering innovative solutions to foster inclusive and sustainable housing development.