How Gender Shapes Quality of Life in Abu Dhabi: Exploring Inequalities in Roles and Responsibilities

Gender disparities in well-being represent a critical yet understudied issue, particularly in diverse socio-cultural contexts like Abu Dhabi. This study examines these disparities across four distinct groups: working adults, the unemployed, retirees, and migrant domestic workers, leveraging data from the fifth cycle of the Quality-of-Life Survey. This comprehensive approach investigates key well-being determinants such as mental health, social support, economic satisfaction, and life satisfaction, providing nuanced insights into how men and women experience well-being differently. Findings reveal significant gender-based differences within each group. Working adults exhibited disparities in economic perceptions, work-life balance, and mental health, while the unemployed faced pronounced gaps in mental health outcomes and access to social support. Among retirees, differences in financial stability, social engagement, and mental health highlight the compounded challenges for women. Migrant domestic workers displayed disparities in job security, physical and mental health, and social networks, with women reporting greater resilience but fewer external support mechanisms. Understanding these disparities is crucial for designing equitable policies that address systemic barriers to well-being. This study underscores the importance of integrating gender-sensitive and culturally attuned interventions to enhance life satisfaction, mental health, and social equity across these groups. The findings offer actionable insights for policymakers and stakeholders, contributing to a deeper understanding of the intersection of gender and well-being in Abu Dhabi's rapidly evolving socio-economic landscape.

• Gender Disparities
• Well-Being Determinants
• Working Adults
• Unemployed
• Retirees
• Domestic Workers
• Mental Health
• Abu Dhabi

1. Introduction

Well-being is a multidimensional concept encompassing various aspects of life, including physical health, mental health, social relationships, financial stability, and environmental factors. These dimensions play a critical role in shaping individuals' quality of life and overall life satisfaction ( Diener et al., 2017 ; Hood et al., 2016 ). In Abu Dhabi, the interplay of cultural norms, rapid urbanization, and evolving societal structures presents unique challenges and opportunities in understanding well-being across diverse demographic groups ( Badri et al., 2023 ; Dodeen & Hassan, 2021 ).

Gender disparities in well-being have been widely studied, revealing differences in health, economic participation, and psychological resilience between men and women ( Carmel, 2019 ; OECD, 2017 ; Blanchflower & Bryson, 2024 ). While global trends indicate that women often report poorer health and higher stress levels, cultural and socio-economic factors can moderate these disparities, making local context crucial to understanding well-being outcomes ( Helliwell et al., 2023 ; Carmel et al., 2018 ). Well-being and quality of life are influenced by multiple determinants, including mental health, life satisfaction, social support, economic stability, and work-life balance ( Blanchflower & Bryson, 2024 ; Carmel & Bernstein, 2003 ; Diener et al., 2017 ). Women tend to report higher levels of mental health challenges, such as anxiety, stress, and depression, largely due to societal expectations and gendered social roles ( Salk et al., 2017 ; Carmel, 2019 ). Economic independence remains a critical determinant, with women facing greater financial stress, unequal pay, and reduced access to opportunities compared to men ( OECD, 2017 ; Bracke et al., 2015 ). Furthermore, access to healthcare, educational attainment, and social inclusion are gendered factors that contribute to systemic inequities in both subjective and objective well-being ( Veenhoven, 2018 ; Ermiş-Mert, 2023 ).

This study focuses on four key groups: working adults, the unemployed, retirees, and domestic workers—each representing distinct life stages and occupational contexts with unique well-being challenges. Working adults face disparities in work-life balance, job satisfaction, and workplace stress, with women more likely to experience career stagnation and disproportionate caregiving responsibilities ( Pace & Sciotto, 2022 ; Haar et al., 2014 ). Gender disparities in work-life balance are well documented, with women frequently experiencing stress due to unequal distribution of domestic responsibilities ( Delina & Raya, 2013 ; Rehman & Roomi, 2012 ). Additionally, women in male-dominated industries face limited career progression opportunities, which negatively affect professional self-efficacy and mental well-being ( Morgenroth et al., 2021 ; Bari & Robert, 2016 ).

Unemployment has distinct gendered implications, with men often facing identity crises and mental health challenges stemming from societal expectations of being the primary breadwinner ( Dooley et al., 1996 ; Artazcoz et al., 2004 ). In contrast, women encounter barriers such as financial instability, caregiving responsibilities, and restricted re-employment opportunities due to skill gaps and hiring biases ( OECD, 2017 ; Bracke et al., 2015 ). Research suggests that Unemployment is associated with poorer mental health among men compared to women, as employed men often derive their sense of self-worth and social identity from their jobs ( Bartley, 1994 ; Shin et al., 2024 ). Women, however, may experience slightly better mental well-being in unemployment if they assume traditional family roles, offering some psychological buffer ( Carmel & Bernstein, 2003 ; Artazcoz et al., 2004 ).

Retirement presents another dimension of gender disparity in well-being. Women retirees often experience financial insecurity due to lower lifetime earnings, interrupted career trajectories from caregiving roles, and limited pension benefits ( Hewko et al., 2018 ; Carmel, 2019 ). Economic disadvantages are further exacerbated by social isolation, particularly as women tend to outlive their spouses, reducing their available social networks ( United Nations, 2017 ; Bongaarts & Zimmer, 2002 ). Men, on the other hand, struggle with identity loss and reduced social engagement after retirement, particularly when their sense of purpose has been tied to professional roles ( Flower et al., 2019 ; Welsh et al., 2016 ). Additionally, gender differences in health and well-being post-retirement are influenced by disparities in healthcare access and pre-existing conditions ( Tesch-Römer et al., 2008 ).

Migrant domestic workers constitute a highly vulnerable group, with gendered challenges that severely impact their well-being. Women in this category frequently endure exploitative working conditions, long hours, inadequate pay, and lack of legal protections, exacerbating both physical and mental health risks ( Mkandawire-Valhmu, 2010 ; Sumerlin et al., 2024 ). Due to the private nature of domestic work, these individuals often experience social isolation and limited access to legal and healthcare services ( Nielsen & Sendjaya, 2014 ). Studies in Abu Dhabi suggest that while many female domestic workers exhibit resilience, their well-being is highly dependent on social support, awareness of local culture, and workplace conditions ( Yang et al., 2024 ). Research from other regions has confirmed that stress levels and poor employment conditions correlate with heightened anxiety and depression among female domestic workers ( Staland-Nyman et al., 2021 ; Kharkongor, 2023 ). Addressing these disparities requires gender-sensitive labor protections, better access to healthcare, and stronger community support programs.

Their inclusion is particularly important in the context of Abu Dhabi, where migrant domestic workers comprise a significant portion of the expatriate labor force and often operate within unique socio-legal frameworks that limit access to rights, protections, and support systems available to other working populations.

By analyzing these groups, this study provides a comprehensive perspective on how social, economic, and cultural factors intersect to shape gender disparities in well-being. Utilizing robust data from the Quality-of-Life Survey, the research aims to inform targeted policies and interventions that promote gender equity and enhance overall quality of life. As Abu Dhabi continues its socio-economic development, addressing these disparities will be essential for fostering social inclusion and sustainable well-being among its diverse population. Understanding gender disparities across different groups not only offers insights into universal challenges but also highlights region-specific factors that influence well-being outcomes, contributing to more effective policymaking and social development efforts.

2. Research Methods and Design

Respondents

The analysis included all related respondents that did not report any missing data regarding the determinants used in the analysis. For the analysis, 30,710 working adults, 3006 unemployed individuals, 3775 retirees, and 2041 domestic workers were included, ensuring that only respondents with no missing values for any of the well-being determinants examined were analysed. This approach enhances the robustness and accuracy of the findings by eliminating biases associated with incomplete data. By focusing on these fully completed responses, the study provides a reliable comparison of well-being determinants across genders within each group. This methodological rigor strengthens the validity of the results and supports the identification of meaningful gender disparities within the four distinct groups.

Survey instrument

This study utilized data from the fifth cycle of the Quality-of-Life Survey in Abu Dhabi, an extensive and comprehensive survey conducted between September 2023 and April 2024. Designed to capture a holistic view of residents’ well-being, the survey covered a broad spectrum of themes, including demographics, housing, income, education, health, family dynamics, social connections, mental well-being, and digital practices. The survey garnered responses from over 100,000 residents, reflecting the diversity of the population in Abu Dhabi.

For this study, we focused specifically on respondents in four main categories: the working adults, the unemployed, the retired, and domestic workers. For the working adults, the question asked (Which of the following best describes what you have been mainly doing in the last four weeks?). Nine choices were provided, and the selected ones were full-time, part-time, and self-employed. For the unemployed, the choice was (unemployed). For the retired, the choice selected was (Retired). Another survey question asked (Which of the following sectors does your employer belong to?). One of the choices was (domestic workers).

Using an extensive literature review and pre-analyses, the survey selected the following well-being determinants from QoL-5:

Analysis

To examine gender disparities across the four groups—working adults, the unemployed, retirees, and domestic workers—we will employ Analysis of Variance (ANOVA) to compare well-being determinants between males and females. ANOVA is particularly well-suited for this study as it allows for the identification of statistically significant differences between groups, providing insights into how gender influences various dimensions of well-being. This method is robust in analysing categorical independent variables (gender) against continuous dependent variables (well-being determinants) and is widely used in social and behavioural research to understand group-level variations. In addition to identifying significant differences, the analysis will report the mean values for each well-being determinant across the four groups, providing a clear understanding of how these determinants differ by gender. By leveraging ANOVA and reporting these descriptive statistics, the analysis aims to highlight key areas of disparity, informing targeted interventions and policy recommendations for each group.

3. Results

Table 1 provides some more details of respondents in the four groups.

Table 1

Table 1. Profile of respondents in the four groups.

Working adults	Number	Percentage
Gender
Male	23,002	65.5%
Female	7708	34.5%
Marital status
Married	23,186	75.5%
Single	5590	18.2%
Others	1933	6.3%
The unemployed	Number	Percentage
Gender
Male	1613	65.5%
Female	1453	34.5%
Marital status
Married	1943	63.4%
Single	676	22.1%
Others	444	14.1%
The Retired	Number	Percentage
Gender
Male	2880	65.1%
Female	895	34.9%
Marital status
Married	3258	86.3%
Single	132	3.5%
Others	385	10.2%
Domestic workers	Number	Percentage
Gender
Male	679	38.2%
Female	1470	61.8%
Marital status
Married	1479	68.9%
Single	679	30.1%
Others	106	1%

Table 2 shows the means, F-values, and significance for the working adults. The results of the ANOVA analysis for the working adults group reveal significant gender disparities across several well-being determinants. Men reported higher satisfaction levels in domains such as household income (mean = 2.603 for men vs. 2.556 for women), ability to pay for necessary expenses (mean = 2.690 for men vs. 2.596 for women), and satisfaction with household income (mean = 3.029 for men vs. 2.896 for women), highlighting a more favourable economic perception among male respondents. Women, however, reported slightly better job security (mean = 3.610 for women vs. 3.556 for men), which is an intriguing finding warranting further exploration into workplace dynamics.

In terms of lifestyle and health, men reported higher sleep quality (mean = 3.458 for men vs. 3.368 for women) and satisfaction with work-life balance (mean = 3.313 for men vs. 3.046 for women), while women demonstrated higher scores on negatively worded indicators, such as mental health (mean = 2.627 for women vs. 2.321 for men), indicating worse outcomes. Notably, subjective obesity (mean = 1.805 for women vs. 1.792 for men) showed no significant gender differences. Women also spent significantly more hours online (mean = 6.093 for women vs. 5.029 for men), a finding that could have implications for mental health and social engagement.

Social relationships exhibited nuanced differences: men reported higher

Table 2

Table 2. Gender disparities (the working adults, total: 30,710).

Wellbeing determinants	Male (23,002)		Female (7708)		ANOVA
	Mean	S.D.	Mean	S.D.	F-value	Sig,
C3: Household income (compared)	2.603	0.846	2.556	0.790	18.319	0.001
C4: Ability to pay for necessary expenses	2.690	0.790	2.596	0.833	46.398	0.001
C5: Satisfaction with household income	3.029	0.833	2.896	1.064	91.682	0.001
B7: Satisfaction (current residence)	3.711	1.064	3.653	1.025	31.509	0.001
D1: Job security	3.556	1.025	3.610	1.055	25.719	0.001
E3: Sleep quality	3.458	1.055	3.368	1.066	77.238	0.001
E6: Satisfaction (work-life balance)	3.313	1.066	3.046	1.031	464.96	0.001
F1: Subjective health	3.537	1.031	3.417	1.059	158.336	0.001
F3: Subjective (obesity)	1.792	1.059	1.805	1.061	1.635	0.201
COMP: (Mental health)	2.321	1.061	2.627	1.099	894.5	0.001
F6: Often eating healthy food	3.506	1.099	3.484	1.075	7.080	0.008
I2: Other people’s support	2.619	1.075	2.591	1.085	4.440	0.035
I9: Most people could be trusted?	2.776	1.085	2.586	1.051	336.77	0.001
I11: Quality time spent with family	3.030	1.051	2.955	1.073	31.77	0.001
I12: Satisfaction with family life	3.943	1.073	3.831	1.033	100.985	0.001
I13: Satisfaction with relations (others)	3.790	1.033	3.702	1.028	116.313	0.001
N2: Hours spent online	5.029	1.028	6.093	1.032	744.13	0.001
O1: Life satisfaction	7.003	1.032	7.109	1.166	19.825	0.001

satisfaction with family life (mean = 3.943 for men vs. 3.831 for women) and relationships with others (mean = 3.790 for men vs. 3.702 for women). Women, however, scored lower on perceptions of trust (mean = 2.586 for women vs. 2.776 for men) and support from others (mean = 2.591 for women vs. 2.619 for men). Interestingly, overall life satisfaction (mean = 7.109 for women vs. 7.003 for men) was slightly higher among women, albeit with a small but significant difference. These findings underscore the multifaceted nature of gender disparities in well-being among working adults, emphasizing the need for targeted interventions to address specific areas of concern for each gender.

Table 3 shows the means, F-values, and significance levels for the unemployed group, highlighting notable gender disparities across several well-being determinants. Female respondents reported higher household income perceptions (mean = 2.097 for females vs. 1.973 for males) and satisfaction with their current residence (mean = 2.118 for females vs. 2.001 for males). However, males showed slightly better outcomes in the ability to pay for necessary expenses (mean = 2.097 for males vs. 2.032 for females), though the difference was modest. Interestingly, no significant gender difference was observed in satisfaction with household income, suggesting similar financial challenges among unemployed males and females.

Table 3

Table 3. Gender disparities (the unemployed, total: 3006).

Wellbeing determinants	Male (1613)		Female (1453)		ANOVA
	Mean	S.D.	Mean	S.D.	F-value	Sig.
C3: Household income (compared)	1.973	0.920	2.097	0.935	13.742	0.001
C4: Ability to pay for necessary expenses	2.097	0.935	2.032	0.929	10.465	0.001
C5: Satisfaction with household income	2.032	0.929	2.001	0.997	0.485	0.486
B7: Satisfaction (current residence)	2.001	0.997	2.118	1.005	1.373	0.241
D1: Job security	------	------	------	------	------	------
E3: Sleep quality	------	------	------	------	------	------
E6: Satisfaction (work-life balance)	------	------	------	------	------	------
F1: Subjective health	3.391	1.190	3.425	1.071	1.373	0.241
F3: Subjective (obesity)	3.425	1.071	3.413	1.113	14.496	0.001
COMP: (Mental health)	3.413	1.113	1.698	1.010	16.812	0.001
F6: Often eating healthy food	1.698	1.010	1.799	1.058	19.349	0.001
I2: Other people’s support	2.341	1.191	2.581	1.214	37.469	0.001
I9: Most people could be trusted?	2.581	1.214	2.501	1.212	2.046	0.153
I11: Quality time spent with family	2.501	1.212	2.499	1.083	56.557	0.001
I12: Satisfaction with family life	2.499	1.083	2.540	1.042	62.464	0.001
I13: Satisfaction with relations (others)	2.540	1.042	2.525	1.057	11.382	0.001
N2: Hours spent online	5.905	4.440	6.440	4.788	18.730	0.001
O1: Life satisfaction	6.440	4.788	6.250	4.674	239.12	0.001

Health-related indicators revealed nuanced differences. Females reported higher scores for subjective health (mean = 3.425 for females vs. 3.391 for males), but also scored worse on subjective obesity (mean = 3.413 for females vs. 3.425 for males), reflecting gendered perceptions of health and body image. Mental health results showed significant gender disparity, with males reporting better mental health outcomes (mean = 3.413 for males vs. 1.698 for females), emphasizing the psychological toll of unemployment on women.

Social relationships displayed mixed outcomes. Females reported stronger support from others (mean = 2.581 for females vs. 2.341 for males) and higher satisfaction with family life (mean = 2.540 for females vs. 2.499 for males). However, males reported slightly better satisfaction with their relationships with others (mean = 2.540 for males vs. 2.525 for females) and a higher sense of trust in people (mean = 2.581 for males vs. 2.501 for females). Additionally, women spent more hours online (mean = 6.440 for females vs. 5.905 for males), which may reflect different coping mechanisms for unemployment.

Life satisfaction was marginally higher for males (mean = 6.440 for males vs. 6.250 for females), though the difference was small. These findings underscore the complex interplay of gender, social, and economic factors in shaping the well-being of unemployed individuals, emphasizing the need for gender-specific interventions that address unique challenges faced by men and women in this demographic.

Table 4 shows the means, F-values, and significance levels for the retired group, highlighting notable gender differences across several well-being determinants. Males reported higher satisfaction with household income (mean = 2.430 for males vs. 2.284 for females) and current residence (mean = 3.863 for males vs. 3.591 for females), suggesting greater economic and housing satisfaction among male retirees. In contrast, females reported slightly better satisfaction with their ability to pay for necessary expenses (mean = 2.395 for females vs. 2.284 for males) and higher satisfaction with household income (mean = 2.487 for females vs. 2.395 for males), indicating nuanced economic perspectives between genders.

Health-related indicators revealed significant gender disparities. Females exhibited worse outcomes in mental health (mean = 1.623 for females vs. 3.218 for males), highlighting a critical area of concern for interventions targeting female retirees. Additionally, subjective obesity scores (mean = 3.239 for males vs. 3.218

Table 4

Table 4. Gender disparities (the retired, total: 3775).

Wellbeing determinants	Male (2880)		Female (895)		ANOVA
	Mean	S.D.	Mean	S.D.	F-value	Sig.
C3: Household income (compared)	2.430	0.893	2.284	0.834	18.824	0.001
C4: Ability to pay for necessary expenses	2.284	0.834	2.395	0.882	25.189	0.001
C5: Satisfaction with household income	2.395	0.882	2.487	1.120	64.335	0.001
B7: Satisfaction (current residence)	3.863	1.155	3.591	1.280	54.127	0.001
D1: Job security	------	------	------	------	------	------
E3: Sleep quality	------	------	------	------	------	------
E6: Satisfaction (work-life balance)	------	------	------	------	------	------
F1: Subjective health	3.206	1.054	3.239	1.058	1.094	0.296
F3: Subjective (obesity)	3.239	1.058	3.218	1.055	113.552	0.001
COMP: (Mental health)	3.218	1.055	1.623	0.900	147.20	0.001
F6: Often eating healthy food	1.623	0.900	1.922	1.047	17.153	0.001
I2: Other people’s support	2.792	1.309	2.725	1.275	2.108	0.147
I9: Most people could be trusted?	2.613	1.101	2.371	1.037	50.745	0.001
I11: Quality time spent with family	3.838	1.093	3.635	1.163	32.525	0.001
I12: Satisfaction with family life	4.220	0.963	4.078	1.001	21.336	0.001
I13: Satisfaction with relations (others)	3.923	0.816	3.818	0.874	15.751	0.001
N2: Hours spent online	4.161	3.497	5.381	3.849	118.01	0.001
O1: Life satisfaction	7.294	2.755	7.929	2.544	9.349	0.002

for females) showed a small but notable difference. Eating habits also varied, with females more frequently reporting healthy eating practices (mean = 1.922 for females vs. 1.623 for males).

Social relationships showed interesting dynamics. Males reported higher satisfaction with family life (mean = 4.220 for males vs. 4.078 for females), quality time spent with family (mean = 3.838 for males vs. 3.635 for females), and trust in others (mean = 2.613 for males vs. 2.371 for females). However, females spent more hours online (mean = 5.381 for females vs. 4.161 for males), which may reflect differing social engagement or coping strategies.

Overall life satisfaction was higher among females (mean = 7.929 for females vs. 7.294 for males), despite their reported challenges in mental health and trust. These findings underscore the complex interplay of gender, social, and economic factors in shaping well-being among retirees, emphasizing the need for targeted policies and interventions to address the unique challenges faced by both male and female retirees.

Table 5 shows the means, F-values, and significance levels for the migrant domestic workers, highlighting substantial gender disparities across various well-being determinants. Female respondents reported higher satisfaction with their

Table 5

Table 5. Gender disparities (the migrants-domestic workers, total: 2149).

Wellbeing determinants	Male (679)		Female (1470)		ANOVA
	Mean	S.D.	Mean	S.D.	F-value	Sig.
C3: Household income (compared)	------	------	------	------	------	------
C4: Ability to pay for necessary expenses	------	------	------	------	------	------
C5: Satisfaction with household income	------	------	------	------	------	------
B7: Satisfaction (current residence)	4.136	0.752	4.241	0.533	13.411	0.001
D1: Job security	3.929	0.828	4.151	0.596	46.525	0.001
E3: Sleep quality	4.070	0.789	4.258	0.545	38.45	0.001
E6: Satisfaction (work-life balance)	------	------	------	------	------	------
F1: Subjective health	3.838	0.937	4.037	0.752	27.135	0.001
F3: Subjective (obesity)	1.511	0.865	1.246	0.607	64.593	0.001
COMP: (Mental health)	1.720	0.945	1.406	0.733	57.769	0.001
F6: Often eating healthy food	3.465	1.138	3.505	1.083	0.567	0.453
I2: Other people’s support	2.302	1.053	1.762	0.717	102.10	0.001
I9: Most people could be trusted?	3.044	1.009	3.094	0.953	1.2023	0.273
I11: Quality time spent with family	------	------	------	------	------	------
I12: Satisfaction with family life	------	------	------	------	------	------
I13: Satisfaction with relations (others)	3.848	0.686	3.705	0.696	19.291	0.001
N2: Hours spent online	4.048	3.017	3.615	2.830	10.143	0.001
O1: Life satisfaction	8.270	2.054	8.600	1.612	15.715	0.001

current residence (mean = 4.241 for females vs. 4.136 for males) and job security (mean = 4.151 for females vs. 3.929 for males), indicating a greater sense of stability among women in this group. Similarly, women exhibited better sleep quality (mean = 4.258 for females vs. 4.070 for males) and subjective health (mean = 4.037 for females vs. 3.838 for males), suggesting relatively more favourable physical and lifestyle conditions.

In contrast, men demonstrated higher scores on negatively worded indicators, such as subjective obesity (mean = 1.511 for males vs. 1.246 for females) and mental health (mean = 1.720 for males vs. 1.406 for females), indicating worse outcomes in these domains. These findings highlight the complex interplay of physical and mental health challenges faced by male domestic workers.

Social dynamics also showed notable differences. Women reported lower levels of support from others (mean = 1.762 for females vs. 2.302 for males), which might reflect differing levels of social networks or assistance. Men, however, scored slightly higher on satisfaction with relationships with others (mean = 3.848 for males vs. 3.705 for females), but women reported marginally better life satisfaction (mean = 8.600 for females vs. 8.270 for males), emphasizing the nuanced nature of well-being perceptions in this group.

Men spent more hours online (mean = 4.048 for males vs. 3.615 for females), which may reflect differences in coping mechanisms or leisure activities. These findings underscore the need for targeted policies and interventions that address the specific challenges faced by migrant domestic workers, with a focus on improving mental health support, enhancing social connections, and addressing disparities in physical health and job security.

4. Discussions

The findings from this study highlight significant gender disparities in well-being across four distinct demographic groups in Abu Dhabi: working adults, the unemployed, retirees, and migrant domestic workers. These disparities reflect the complex interplay of socio-economic, health, and social determinants within each group, influenced by gender-specific challenges and cultural contexts. This discussion synthesizes the results with prior research, emphasizing the implications for policy and interventions.

Gender disparities among working adults reveal nuanced differences across economic, health, and social well-being determinants. Men reported higher satisfaction levels in economic indicators, such as household income, ability to pay for necessary expenses, and satisfaction with household income. These findings align with studies highlighting systemic biases favouring men in workplace environments and income opportunities ( Bari & Robert, 2016 ; Carmel, 2019 ). Women, however, exhibited better job security, a result that may reflect their employment concentration in relatively stable public sector roles, such as education, healthcare, and social services, where job continuity is high, but career advancement is often limited ( Ashour, 2020 ). Labor market research in the UAE confirms that female employment is disproportionately clustered in these sectors, particularly within government institutions ( Ashour, 2020 ; Haar et al., 2014 ; Pace & Sciotto, 2022 ).

Health-related disparities were pronounced, with men reporting higher sleep quality and satisfaction with work-life balance, while women experienced worse mental health outcomes. This mirrors global patterns where women face higher mental health challenges due to dual responsibilities at work and home ( Blanchflower & Bryson, 2024 ; Salk et al., 2017 ). Socially, men reported higher satisfaction with family life and relationships, but women’s slightly higher life satisfaction underscores the complexity of well-being, where relational resilience may play a role ( Rehman & Roomi, 2012 ; Diener et al., 2017 ).

Unemployed individuals displayed significant gender differences in well-being, particularly in mental health and social support. Women reported worse mental health outcomes, which is consistent with research indicating greater psychological tolls of unemployment on women due to compounded caregiving roles and economic vulnerability ( Artazcoz et al., 2004 ; Piccinelli & Wilkinson, 2000 ). However, they reported higher social support and stronger familial satisfaction, reflecting the buffering role of family networks ( Carmel & Bernstein, 2003 ).

Men, in contrast, exhibited better mental health outcomes but lower social support and familial satisfaction. This aligns with studies highlighting the stigma and identity crises men face during unemployment, which can weaken social ties and exacerbate feelings of isolation ( Dooley et al., 1996 ; Bartley, 1994 ). These results emphasize the need for gender-specific interventions, such as targeted mental health support for women and social reintegration programs for men.

Among retirees, gender disparities were evident in economic, health, and social dimensions. Men reported higher satisfaction with household income and current residence, reflecting greater financial security likely tied to higher lifetime earnings ( Carmel, 2019 ; Shin et al., 2024 ). Women, however, demonstrated better healthy eating habits and life satisfaction, suggesting adaptive strategies that mitigate some economic challenges ( Pinquart & Sörensen, 2001 ).

Health disparities were stark, with women reporting worse mental health outcomes, a pattern consistent with global research suggesting associations between gender and mental health inequalities in older age ( Tesch-Römer et al., 2008 ). Socially, men exhibited higher satisfaction with family life and trust in others, while women’s higher online engagement may indicate alternative coping mechanisms for maintaining social connections ( Flower et al., 2019 ; Carmel et al., 2018 ).

Migrant domestic workers exhibited unique gender disparities, with women reporting higher satisfaction in job security, sleep quality, and subjective health. These findings highlight women’s resilience and adaptation despite challenging working conditions ( Yang et al., 2024 ; Mkandawire-Valhmu, 2010 ). However, their lower levels of social support and reliance on fewer networks underscore vulnerabilities in accessing external assistance ( Nielsen & Sendjaya, 2014 ).

Men, in contrast, reported worse mental health outcomes and higher perceived obesity, suggesting distinct physical and psychological challenges faced by male domestic workers ( Staland-Nyman et al., 2021 ). Their higher online engagement may reflect differing coping strategies or leisure activities compared to women ( Sumerlin et al., 2024 ).

The results underscore the importance of gender-sensitive policies and interventions tailored to the unique needs of each demographic group. For working adults, policies should address workplace inequities by promoting flexible work arrangements, equal pay, and mental health support ( Hesketh & Williams, 2021 ). Unemployment programs should focus on enhancing social support networks for men and providing targeted mental health services for women ( Artazcoz et al., 2004 ; Bracke et al., 2015 ).

For retirees, financial planning initiatives and accessible mental health services can address economic insecurity and health disparities ( Shin et al., 2024 ; Carmel, 2019 ). Community programs promoting social engagement are particularly critical for both genders. For migrant domestic workers, stronger labor protections, healthcare access, and community-based support systems are essential to address systemic inequities and enhance well-being ( Mkandawire-Valhmu, 2010 ; Yang et al., 2024 ).

This study highlights the multifaceted nature of gender disparities in well-being across working adults, the unemployed, retirees, and migrant domestic workers in Abu Dhabi. The findings provide actionable insights for policymakers and stakeholders to design targeted interventions that address systemic barriers to gender equity. By fostering inclusive and culturally sensitive approaches, Abu Dhabi can enhance the quality of life for its diverse population and serve as a model for addressing gender disparities in well-being globally.

5. Conclusion

This study provides a comprehensive exploration of gender disparities in well-being among working adults, the unemployed, retirees, and migrant domestic workers in Abu Dhabi. The findings underscore the nuanced interplay of socio-economic, health, and social factors that shape well-being outcomes across these groups. Significant disparities emerged in areas such as mental health, social support, economic satisfaction, and life satisfaction, reflecting the multifaceted challenges that men and women experience differently within these demographic categories. For instance, working adults demonstrated disparities in economic perceptions and mental health, while the unemployed faced pronounced differences in mental health and social support. Retirees exhibited variations in financial stability and mental health outcomes, and migrant domestic workers showed unique challenges in job security, social connections, and mental well-being.

These findings emphasize the importance of gender-sensitive policies and interventions that address specific needs within each group. Promoting equitable workplace practices, enhancing social support networks, and addressing mental health disparities are critical steps toward fostering well-being for all genders. For example, culturally adapted mental health counseling services tailored to unemployed women could help address the psychological burdens they face, while community-based social integration programs for retired men may strengthen their sense of purpose and belonging. The study also highlights the importance of culturally sensitive approaches that align with Abu Dhabi's socio-cultural landscape, ensuring that interventions are both effective and contextually appropriate.

Despite its contributions, this study has limitations that warrant consideration. First, the reliance on self-reported data may introduce biases, as respondents’ perceptions may not always align with objective measures of well-being. Second, while the study examined a range of well-being determinants, other critical factors, such as intersectionality with age, education, or marital status, were not deeply explored. Future research could expand on these dimensions by incorporating additional biographic and socio-economic variables to provide a more holistic understanding of well-being disparities. Third, this study focused on four specific groups; future research could broaden its scope to include other underrepresented populations, such as youth outside formal employment or expatriates in other occupational roles, to capture a more comprehensive picture of gender disparities in Abu Dhabi.

This study underscores the complexity of gender disparities in well-being and highlights actionable insights for policymakers and practitioners. By addressing these disparities through targeted, evidence-based interventions, Abu Dhabi can move closer to achieving greater equity and enhancing the overall quality of life for all residents. These findings provide a foundation for further research and action, encouraging a continued focus on promoting inclusive and equitable well-being across diverse populations.

Source of Funding

This work has been conducted and supported by research offices in the Department of Community Development and Statistics Centre, Abu Dhabi. This research did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors.

Ethical Approval

Ethical consent regarding the protocol of the study was granted by the Department of Community Development (DCD) and the Statistics Centre Abu Dhabi (SCAD). Written informed consent was obtained from all the participants.

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