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Abstract

This article contributes to the limited well-being literature on the Gulf region by investigating the state of self-perceived well-being and its determinants in Qatar using data from the 2010 wave of the World Values Survey. We examine multiple indicators of well-being by using the self-rated state of health and the Seligman PERMA (Positive Emotion, Engagement, Relationships, Meaning, and Accomplishment) model while controlling for other confounding variables. An ordered Probit model is estimated to account for the ordinal nature of the well-being indicators. Results show that an individual’s demographic factors, socioeconomic status, degree of religiosity, employment status, and confidence level in the governmental institutions are key determinants of the level of self-perceived well-being in Qatar. Results also show some regional differences in the level of well-being across the Qatari cities. Increasing the level of well-being in Qatar and narrowing the demographic, socioeconomic, and regional disparities requires a multifaceted approach by targeting the vulnerable groups.

Keywords

well-being determinants Qatar World Values Survey ordered probit model

Introduction

Happiness and well-being are fundamental human rights. Article 25 of the Universal Declaration of Human Rights in 1948 states that “Everyone has the right to a standard of living adequate for the health and well-being of himself and of his family, including food, clothing, housing, medical care and necessary social services.” The World Health Organization (WHO) in 1946 included well-being as an essential element in their definition of health. Goal number 3 of the UN Sustainable Development Goals (SDG) calls for ensuring healthy lives and promoting the well-being of all ages.

Promoting the well-being of individuals results in several positive outcomes. Happy people are physically healthier, live longer, more productive, and cope more effectively with challenges (Lyubomirsky et al., 2005). Policymakers in several countries have become concerned about the state of happiness and well-being within their societies. For example, the British government took an initiate and began monitoring happiness and life satisfaction regularly. The United Arab Emirates, Nigeria, and Venezuela each have created a Happiness Ministry aiming at implementing plans, programs, and policies to achieve a happier society.

Nations traditionally measure citizens’ well-being and prosperity using economic indicators such as income per capita. In 2011, the UN General Assembly adopted a resolution which recognized happiness as a “fundamental human goal” and called for “a more inclusive, equitable and balanced approach” to economic growth that promotes the happiness and well-being of all peoples. The resolution notes that the GDP indicator “was not designed to and does not adequately reflect the happiness and well-being of people in a country” (United Nations General Assembly, 2011).

Qatar, a United Nations (UN) member, without a Happiness Ministry, readily agreed to the UN 2011 resolution. Although Qatar is ranked number one worldwide in terms of per-capita real GDP, it is ranked 29 in the World Happiness Report in 2019, with a significant portion of their happiness attributed to GDP. There is a concern that high levels of income and wealth in Qatar may not necessarily be translated into higher well-being for its citizens. The 2018 Sustainable Economic Development Assessment (SEDA) report revealed that oil-rich countries in the Gulf, including Qatar, tend to perform worse than average in converting wealth into well-being (Hrotko et al., 2018).

The empirical evidence on the role of GDP in promoting a nation’s level of happiness is mixed and controversial. Although the “Easterlin paradox” attributed to Richard Easterlin suggests no link between average level of happiness and GDP across and within countries (Easterlin et al., 2010), Stevenson and Wolfers (2008) reassessed this paradox in a broad set of countries and found a strong positive relationship between GDP per capita and the average levels of subjective well-being (SWB) across countries. They also found no evidence for the existence of a satiation point, after which the GDP has no effect on well-being.

In his influential work, Seligman (2012) hypothesized that PERMA (Positive Emotion, Engagement, Relationships, Meaning, and Accomplishment) are measurable elements that makeup well-being. Goodman et al. (2018) compared Seligman’s PERMA model of well-being with Diener’s model of SWB and reported strong evidence that SWB is the final common path of the PERMA elements and that the factor underlying PERMA is capturing the same type of well-being as SWB.

The main objective of this study is to examine the self-perceived state of health, psychological well-being, and their determinants in Qatar using a nationally representative sample of Qatari households. In particular, this study has three aims. The first aim is to overcome other studies’ sample limitations by expanding the sample size of Qatari’s household using the World Values Survey (WVS) as a national representative weighted data on Qatar. The second aim of this article is to explore multiple indicators to measure the state of the self-perceived well-being by using the state of health, the components of the Seligman (2012) PERMA model, and life satisfaction, respectively, while controlling for other confounding variables. The third aim is to contribute to the ongoing discussion and policy debate on how to increase the quality of life and boost the level of well-being in Qatar.

Extensive research on happiness and SWB has been conducted in developed nations, the United States, and Europe. In addition, investigations continue to grow on the determinants of well-being in developing countries as well. Nonetheless, the field remains ripe for further inquiry in the Middle East and Qatar. The authors of this study are unaware of any comprehensive study conducted in Qatar on the research topic.

Several demographic and socioeconomic determinants of well-being have been identified in the literature. These include sex (Di Tella et al., 2001), marital status (Diener et al., 2000), age of the respondent (Selim, 2008), education level (Michalos, 2017), income level (Ferrer-i-Carbonell, 2005), employment status (Clark et al., 2001; McKee-Ryan et al., 2005), having children (Myrskylä & Margolis, 2014; Nelson et al., 2013), and region of residence (Lawless & Lucas, 2011).

Sex is a key determinant of SWB. There is considerable empirical evidence on the existence of gender-based inequality in the level of SWB. It has been argued that this gender inequality reflects the different social experiences and conditions of men’s and women’s lives. Also, men and women differ in their lifestyle behaviors and the number and levels of chronic stressors and life events experienced by them. There are also gender differences in the way they cope with any stressor (Denton et al., 2004). Marital status may also have an impact on the level of the SWB of an individual. It has been argued that marriage provides support in dealing with problems, and married people suffer less from loneliness (Frey & Stutzer, 2010).

Several theories have been presented to explain the relationship between age and well-being, and the empirical evidence on this link is mixed. The set point theory in psychology argues that individuals are born with a predisposition to a certain level of happiness, based on genetics and personality and that any deviations from this pre-set level are temporary and that the levels of well-being will not change across the lifespan. According to the socio-emotional selectivity theory, individuals experience more life satisfaction as age increases because, with passing the time and shrinking time horizons, they spend more time in activities that contribute to their well-being instead of pursuing goals that are expected to pay off in the future (Charles & Carstensen, 2009). For a review of the literature on how SWB evolves with age, see Ulloa et al. (2013). In a recent study, Graham and Pozuelo (2017) found consistent evidence on the existence of a U-shaped relationship between age and happiness in 44 of the 46 countries that their study examined and that the timing of the turn differs depending on average country-level happiness and on individuals’ position in the well-being distribution.

Education could affect well-being by increasing the chance of a better occupational status and higher incomes, helping individuals to make progress toward their goals and to adapt to a changing world. Education also allows people to take more advantage of activities that generate happiness, particularly music, painting, literature, and history (Scitovsky, 1976). On the contrary, higher education raises aspirations and may increase distress when these expectations are not achieved. Employment status has also been linked to psychological well-being. Work provides a basis for meaning, identity, and positive social relationships leading to happiness (Lyubomirsky et al., 2005). Studies have found that unemployment sharply decreases well-being (Clark et al., 2001; Pinto & Graham, 2019).

Several studies reported that geographical location could also have an impact on the SWB of its inhabitants. There are natural geographical disparities in the level of the country-wide determinants of well-being. Cities differ in the range of shops, restaurants, cultural and recreational activities, the quality of health and education facilities, level of pollution, congestion, and crime levels, all of which have a direct impact on an individual’s well-being (Orviska et al., 2014).

Having friends to count on, the level of distrust in the governmental institutions and religiousness have also been identified as critical determinants of well-being. The literature on the role of social capital has stressed the importance of social relationships for SWB. People with more social connections report higher life evaluations, as many of the most pleasurable personal activities involve socializing and the benefits of social connections extend to people’s health (Helliwell et al., 2009). It has been found that the political and institutional environment related to the efficient satisfaction of voters’ preferences is likely to affect SWB (Wagner et al., 2009). For a detailed discussion on the linkage between the level of trust in the governmental institution and SWB, see Hudson (2006). There is considerable empirical evidence on the positive effect of spirituality and religiousness on health, both mental and physical, survival, quality of life, and SWB (Moreira-Almeida et al., 2014). Religiousness provides resources for coping with stress, hardship, depression and anxiety, give social support, encourage human virtues, and increase positive emotions such as meaning, purpose in life, and peace (AbdAleati et al., 2016; Koenig, 2012).

There is a growing literature on the determinants of health, well-being, and life satisfaction, in a wide range of countries, including the Gulf region, and using different analytical methods and data sets (see, for example, Abdel-Khalek, 2004; Ngoo et al., 2015; Selim, 2008). Nonetheless, the empirical evidence on this research topic in Qatar is sparse especially at the national level. For example, Baroun (2006), using a sample of 941 Kuwaiti adolescents, investigated the correlation among physical health, mental health, happiness, anxiety, and religiosity and whether there are sex differences on those variables. The study reported significantly higher mean scores for boys than girls on all the well-being indicators except anxiety. In another study, Abdel-Khalek (2004) studied the correlates of happiness among a sample of 140 Kuwaiti undergraduates. The author found that mental health was associated with religiosity and self-efficacy in the students. Self-rated happiness was positively associated with religiosity and self-efficacy. The study also found that males reported higher self-efficacy and better mental health than females. Abdel-Khalek and Lester (2017) examined the association among religiosity, generalized self-efficacy, mental health, and happiness in a sample of 702 Muslim, Arab, college students. The findings revealed that mental health and self-rated happiness were both associated with religiosity and self-efficacy. Males scored higher than females on self-efficacy and mental health. In a recent study, D’raven and Pasha-Zaidi (2016) examined whether the descriptions of happiness provided by a sample of Emirati university students are consistent with the PERMA model pathways. The results showed that how happiness was described overlapped with the PERMA pathways in culturally consistent ways.

A few paltry studies have been conducted in Qatar and using unrepresentative samples with sample selection bias and limited happiness and well-being indicators. For example, Al-Attiyah and Nasser (2016) used a sample of 319 participants from Qatar University and other government schools to examine whether there are differences by gender and age concerning life satisfaction. The study found significant differences in life satisfaction for gender but not age. In another study, Abdel-Khalek (2013) used a sample of 372 Qatari adolescents and examined the association between self-reported well-being and gender, sex-related differences in religiosity, and health and happiness. The study found those who considered themselves religious self-reported higher well-being and good health.

The rest of the article is organized as follows: Section “Data and Methods” describes the data and the econometric methodology. Section “Results” presents the estimation results, which are discussed in the “Discussion” section. Section “Limitations of the Study” discusses the study limitations, and the “Conclusion and Policy Implications” section concludes the article with some policy recommendations.

Data and Methods

This article uses data from the 2010 WVS for Qatar to answer its research questions. Although the WVS has several waves spanning from 1981 to 2020, data on Qatar are solely available for the year 2010, wave six of the survey, which is to some extent not up-to-date and may not necessarily reflect the current situation.

The WVS is a cross-sectional survey that collects data on a wide range of variables from a nationally representative sample of the Qatari population. The survey’s sampling frame comes from the Electricity and Water Company (Kahramaa), which is the sole provider of water and electricity service in Qatar and covers almost all Qatari households. A more detailed explanation of how the Qatari world value survey sample is designed in a reliable and representative way (see Inglehart et al., 2014). The Qatari sample included in the WVS is constructed by dividing Qatar into zones, and a respondent is then randomly selected within each zone using two-stage sampling. In the first stage, households are randomly selected with proportionate stratification. In the second stage, an adult (18 years or older) within each household is randomly selected. The WVS sampled 1,455 households and collected information from 1,060 completed interviews.

All the interviewed individuals are Qatari citizens (Inglehart et al., 2014). Due to missing data for some of the variables, the sample used in this study comprised 1,023 observations. Access to the WVS is not restricted and the data are publicly available for legitimate academic use with appropriate citation.

The level of an individual’s well-being is usually measured in the literature using self-reports in questionnaires in which an individual reports how he or she feels and to what extent their psychological needs are met. It has been documented that these self-reported subjective measures are reliable and valid at the national level (OECD, 2013; Spector, 1997).

The outcome variables in this study, the state of the self-perceived well-being, are constructed based on the response to the following seven questions in the WVS which capture the elements that make up well-being based on the PERMA model of Seligman (2012). (a) The question pertains to the state of health and asks the participant, “All in all, how would you describe your state of health these days?” The answers were “very good, good, fair, poor.” (b) Pertaining to life satisfaction the question asked, “All things considered, how satisfied are you with your life as a whole these days?” The answers ranged from 1—completely dissatisfied to 10—completely satisfied. (c) Happiness—“Taking all things together would you say you are very happy, rather happy, not very happy, not at all happy and don’t know.” (d) Some people feel they have completely free choice and control over their lives, while other people feel that what they do has no real effect on what happens to them. Please use this scale where 1 means “no choice at all” and 10 means “a great deal of choice” to indicate how much freedom of choice and control you feel you have over the way your life turns out. (e) Now I am going to read off a list of voluntary organizations. For each organization, could you tell me whether you are an active member, an inactive member, or don’t belong or have other types of organization? “Active,” “Inactive,” “Don’t belong.” (f) Now let’s turn to another topic. How often, if at all, do you think about the meaning and purpose of life? “Often,” “Sometimes,” “rarely,” “never.” (g) Relationship: How important are friends in your life? “Very important,” “rather important,” “not very important,” “not at all important.”

An individual’s well-being is a latent index and is observed in the data as an ordinal variable. An individual reports a given level of well-being $(S_{i} = r$ where $r \in [0, R]$ ) if the latent variable lies between arbitrary and unknown threshold values, $λ_{r}$ , whose values are estimated from the data. In such ordinal measures of the dependent variable, it is standard to use an ordered probit model as in Equation 1. The merit of the ordered probit model is that it explicitly accounts for the ordinal nature of the dependent variable. However, Ordinary Least Squares treats the differences between the different rankings of the dependent variable similarly (Greene, 2012).

\Pr (S_{i} = r) = Φ (λ_{r + 1} - β_{k i} X_{k i}) - Φ (λ_{r} - β_{k i} X_{k i})

(1)

Where $Φ (.)$ is the cumulative normal distribution, $X_{k i}$ is a $K$ vector of individual-level and socioeconomic characteristics including the respondent’s age, sex, marital status, number of children, highest education level, employment status, the scale of income, the degree of religiosity, and the region of residence. The analyses also control for a set of covariates that measure the level of an individual’s confidence in the press, the courts, the police, and the government. Also, we control for the day-of-the-week fixed effects as it has been shown that the SWB indicators could be sensitive to the factors such as the day of the week or the season in which the interview was conducted. $u_{i}$ is the standard random error term. For a list and definition of the variable used in the analyses, refer to Table S1 in the supplementary materials.

Results

Table 1 presents descriptive statistics for the examined sample. The average age of the respondents is 37.8 years, 46% of the respondents are males, 69% are married, 9.8% are unemployed, 86.5% are from the middle class, 17% have an education level less than secondary, and 93.77% are religious individuals. 41.1% of the interviewed individuals are from Doha, 35.5% are from Rayan, 5.8% are from Wakra, 11.5% are from Omm Slal, 4.8% are from Alkhour, and 1.35% are from Chemal.

Table 1.

Descriptive Statistics.

Variable	Unweighted (%)	Weighted (%)
Thinking about meaning and purpose of life
Often	66.79	66.97
Sometimes	22.45	22.33
Rarely	7.55	7.55
Never	3.21	3.15
Important in life: Friends
Very important	73.02	72.85
Rather important	25.38	25.56
Not very important	1.42	1.4
Not at all important	0.19	0.19
Active/inactive membership: Sport or/recreational organization
Do not belong	78.58	78.52
Inactive member	12.55	12.63
Active member	8.87	8.86
How much freedom of choice and control/over own life
1	1.60	1.71
2	0.75	0.76
3	1.13	1.14
4	1.04	1.11
5	8.11	8.11
6	8.77	8.89
7	13.68	13.85
8	17.92	17.84
9	17.08	16.84
10	29.72	29.56
State of health
Very good	50.47	50.31
Good	38.21	38.17
Fair	10.28	10.42
Poor	1.04	1.1
Feeling of happiness
Very happy	56.32	56.39
Rather happy	41.79	41.58
Not very happy	1.60	1.71
Not at all happy	0.28	0.32
Satisfaction with your life
1	1.13	1.14
2	0.38	0.41
3	0.94	0.98
4	1.04	1.01
5	8.4	8.55
6	9.06	9.09
7	12.45	12.60
8	20.85	20.85
9	15.19	14.91
10	30.47	30.37
Level of confidence in government
A great deal	51.60	51.46
Quite a lot	31.42	31.35
Not very much	15.09	15.36
None at all	1.23	1.19
No answer	0.66	0.65
Level of confidence in courts
A great deal	67.08	66.93
Quite a lot	23.87	23.94
Not very much	7.36	7.42
None at all	0.66	0.69
No answer	1.04	1.02
Level of confidence in police
A great deal	75.09	74.9
Quite a lot	20.75	21.02
Not very much	2.92	2.82
None at all	0.57	0.6
No answer	0.66	0.66
Level of confidence in press
A great deal	41.13	41.07
Quite a lot	30.28	30.22
Not very much	24.06	24.26
None at all	3.87	3.81
No answer	0.66	0.64
Gender
Males	46.04	45.85
Females	53.96	54.15
Age (Mean)	37.80	37.77
Marital status
Married	68.96	68.85
Single	23.49	23.62
Divorced or widow	7.55	7.52
Employment status
Employed	57.08	56.78
Unemployed	9.81	9.98
Student	12.74	12.76
House wife	19.62	19.69
Education level
Less than secondary	16.98	17.21
Secondary	28.49	28.33
University	34.34	34.18
Income level
1	2.17	2.26
2	1.79	1.89
3	1.89	1.85
4	4.53	4.50
5	18.40	18.52
6	17.74	17.53
7	21.79	21.96
8	17.74	17.63
9	6.98	6.85
10	5.94	5.98
Region of residence
Doha	43.68	41.15
Rayan	33.68	35.46
Wakra	4.43	5.77
Omm Slal	11.70	11.49
Alkhour	4.43	4.80
Chemal	2.08	1.33
Religiousness
Religious	93.77	93.79
Nonreligious	6.23	6.21

Note. The descriptive statistics are population weighted using the sampling weight in the WVS. WVS = World Values Survey.

The descriptive statistics reveal that 41.5% of the respondents are rather happy, 1.71% are not very happy and 0.32% are not at all happy, 38% reported good health, and about 12% reported fair or poor health. 78.5% of the respondents are not members of a sport or a recreational organization. 98% of the respondents view friends as either very or rather important in life. About 11% of the Qatari rarely or never think about the meaning and purpose of life. About 13% have a low to moderate freedom of choice and control over their own life, and 88% have more than a moderate level of life satisfaction. 75% of the respondents have a great deal of confidence in the police, 67% have a great deal of confidence in the judicial system, 55% have a great deal of confidence in the government, and 41% have a great deal of confidence in the Qatari press. These figures on the prevalence of a high degree of freedom and trust in the institution should be dealt with caution given the political nature of some of these questions and the response to these types of questions may reflect social desirability bias and fear of reprisals.

The estimated marginal effects of the ordered probit model for the seven outcome variables are presented in Table 2. Results show that compared with Qatari males, Qatari females are less likely to feel happy, be healthy, to consider friends important in life, while they have a higher probability of having a freedom of choice, being a member in a recreation facility, and thinking about the meaning and purpose in life.

Table 2.

Estimated Marginal Effects of the Ordered Probit Model of the Determinants of Well-Being.

Variables	Life satisfaction	Feeling of happiness	Health status	Freedom of choice	Friends are important	Purpose in life	Member in recreation
Female	−0.000725 (0.00199)	−0.100*** (0.0351)	−0.130*** (0.0355)	0.00669** (0.00295)	−0.0832*** (0.0320)	0.0640** (0.0325)	0.144*** (0.0290)
Age	−0.000127 (0.000466)	−0.00341 (0.00766)	−0.0134* (0.00692)	8.50e–05 (0.000545)	−0.0147** (0.00673)	0.000931 (0.00658)	−0.00482 (0.00642)
Age square	2.64e–07 (5.69e–06)	9.48e–06 (8.90e–05)	2.38e–05 (7.81e–05)	−3.74e–07 (6.46e–06)	0.000170** (7.70e–05)	−1.51e–05 (7.41e–05)	7.31e–05 (7.60e–05)
Children	0.000124 (0.000492)	0.0289*** (0.00898)	0.0166** (0.00826)	−0.000989 (0.000625)	0.0219*** (0.00736)	0.000932 (0.00819)	0.00296 (0.00753)
No education	−0.00531 (0.00402)	−0.0470 (0.0674)	−0.0332 (0.0623)	−0.00403 (0.00472)	−0.0608 (0.0571)	−0.0137 (0.0634)	0.0701 (0.0587)
Less than secondary	−0.00326 (0.00274)	0.0383 (0.0478)	0.0761 (0.0477)	0.00104 (0.00319)	−0.0826** (0.0413)	−0.0244 (0.0407)	−0.0223 (0.0377)
Secondary	−0.00167 (0.00209)	0.0456 (0.0384)	−0.00354 (0.0375)	−0.00100 (0.00269)	−0.0348 (0.0328)	−0.0480 (0.0344)	−0.0128 (0.0307)
Income	0.00259*** (0.000797)	0.0470*** (0.00881)	0.0493*** (0.00799)	−0.00279*** (0.000868)	0.0196*** (0.00742)	−0.00958 (0.00805)	−0.00735 (0.00687)
Unemployed	−0.000101 (0.00360)	0.109 (0.0669)	−0.131** (0.0608)	−0.00319 (0.00473)	−0.0648 (0.0524)	−0.0912 (0.0562)	0.150** (0.0665)
Housewife	−0.000851 (0.00257)	0.0448 (0.0472)	−0.0421 (0.0452)	0.00457 (0.00341)	0.0645 (0.0407)	−0.0362 (0.0431)	0.0227 (0.0392)
Student	0.00463 (0.00303)	0.0600 (0.0520)	0.0325 (0.0511)	0.00619 (0.00387)	−0.0350 (0.0468)	−0.0915** (0.0453)	−0.0538 (0.0410)
Divorce/widow	0.00562 (0.00360)	0.0387 (0.0639)	−0.0773 (0.0604)	−0.00244 (0.00453)	0.0266 (0.0557)	−0.0785 (0.0601)	−0.0142 (0.0583)
Single	0.000321 (0.00277)	0.0293 (0.0519)	−0.0259 (0.0500)	0.00554 (0.00368)	0.0952** (0.0457)	−0.0294 (0.0473)	−0.0666 (0.0414)
Religious	−0.00260 (0.00295)	0.0836 (0.0608)	0.137** (0.0558)	−0.00472 (0.00415)	0.0317 (0.0539)	−0.0299 (0.0614)	0.129*** (0.0462)
Rayan	−0.00197 (0.00203)	0.0914** (0.0380)	−0.0556 (0.0370)	0.00530* (0.00300)	0.0213 (0.0318)	0.0852** (0.0355)	−0.00431 (0.0299)
Wakra	0.00732* (0.00415)	−0.159** (0.0747)	−0.104 (0.0679)	0.00855 (0.00560)	0.0131 (0.0592)	0.0193 (0.0702)	−0.0157 (0.0584)
Ommslal	0.00151 (0.00289)	−0.000581 (0.0496)	0.0227 (0.0509)	0.00483 (0.00329)	0.118** (0.0476)	−0.114*** (0.0431)	0.0767* (0.0410)
Alkhour	−0.00808* (0.00468)	0.0294 (0.0810)	−0.0862 (0.0727)	−0.0105 (0.00640)	0.0857 (0.0723)	0.0390 (0.0670)	0.163** (0.0774)
Chemal	−0.0190** (0.00818)	−0.00391 (0.0886)	−0.0981 (0.0836)	−0.0144 (0.00932)	1.445*** (0.0721)	0.0391 (0.0991)	0.167 (0.107)
Confidence in government	0.00385** (0.00157)	−0.0119 (0.0263)	−0.0294 (0.0255)	−0.000338 (0.00175)	−0.0271 (0.0216)	0.0342 (0.0232)	−0.000866 (0.0208)
Confidence in police	0.00162 (0.00187)	−0.0592* (0.0360)	−0.0150 (0.0361)	0.00282 (0.00236)	−0.00798 (0.0293)	−0.0561* (0.0325)	−0.0895*** (0.0279)
Confidence in press	−0.000130 (0.00114)	−0.0698*** (0.0207)	−0.00670 (0.0189)	0.00360** (0.00156)	−0.0163 (0.0178)	−0.0250 (0.0175)	0.00518 (0.0181)
Confidence in courts	0.000738 (0.00166)	0.0168 (0.0292)	−0.00714 (0.0293)	0.00195 (0.00212)	−0.0101 (0.0250)	0.0262 (0.0277)	0.0170 (0.0254)
Day-of-the-week fixed effects
Tuesday	−0.000180 (0.00265)	0.0994** (0.0492)	−0.0494 (0.0465)	0.000558 (0.00351)	0.0207 (0.0425)	0.0400 (0.0449)	−0.0525 (0.0412)
Wednesday	0.00308 (0.00290)	0.0470 (0.0525)	−0.0492 (0.0499)	0.00189 (0.00373)	0.0101 (0.0463)	0.0113 (0.0470)	−0.0644 (0.0433)
Thursday	−0.00162 (0.00460)	0.0578 (0.0751)	0.0326 (0.0764)	−0.00185 (0.00585)	0.0493 (0.0693)	0.0410 (0.0687)	−0.0352 (0.0620)
Friday	0.00119 (0.00294)	0.114** (0.0521)	−0.0199 (0.0519)	0.00345 (0.00368)	0.0523 (0.0466)	−0.0229 (0.0474)	−0.0269 (0.0440)
Saturday	0.00126 (0.00345)	0.0543 (0.0617)	−0.107* (0.0584)	0.00455 (0.00430)	0.0374 (0.0527)	−0.0220 (0.0534)	−0.0714 (0.0492)
Sunday	−0.000318 (0.00295)	0.0759 (0.0557)	−0.0563 (0.0522)	−0.000161 (0.00396)	0.0110 (0.0467)	0.0427 (0.0501)	−0.0635 (0.0441)
Observations	1,023	1,023	1,023	1,022	1,023	1,023	1,023

Note. Standard errors in parentheses.

p < .1. **p < .05. ***p < .01.

The results also show that the number of children is positively associated with reporting better health status, a higher feeling of happiness, and viewing friends to be important in life.

The results show a U-shaped association between age and life satisfaction, though none of the marginal effects are statistically significant. A similar non-statistically significant U-shaped association is also found between age and the feeling of happiness and being a member in a recreation facility, while the U-shaped association is statistically significant for finding friends important in life. A statistically significant association is found between age and the reported health status.

Most of the estimated marginal effects of the education categories are not statistically significant, but for those with less than secondary education who have a higher probability of being in the healthiest category and less probability of viewing friends to be important in life compared with those with a university education level.

The results show that income level has a statistically significant positive association with life satisfaction, the feeling of happiness, better health status, and viewing friends to be important in life while it is negatively associated with the freedom of choice.

Being unemployed is negatively associated, though not statistically significant, with life satisfaction, freedom of choice, finding friends necessary in life, and thinking about the meaning and purpose of life. Compared with employed individuals, unemployed Qatari are less likely to report better self-rated state of health while more likely to report being a member of a recreation organization.

Results show no statistically significant association between marital status and the examined well-being outcomes, except that being single instead of married is associated with a higher probability of being in the group who more view friends to be important in life.

We found that being a religious person is positively associated with self-rated health and being a member of a recreation organization.

The results reveal some differences in the reported level of well-being across the Qatari districts/neighborhoods as compared with the central city, Doha. Residents of Rayan report feeling more happy, having more freedom of choice, and more thinking about the meaning and purpose of life than residents of Doha while there is no statistically significant difference between residents of Rayan and Doha in the level of life satisfaction, health status, being a member in a recreation facility, and the importance of friends in life. Residents of Wakra, compared with the residents of Doha, have a lower probability of feeling happier while report having more life satisfaction. No statistically significant difference is found between the residence of Wakra and those of Doha regarding the reported health status, being a member in a recreation facility, freedom of choice, thinking about the purpose and meaning of life, and the importance of friends in life.

Residents of Ommslal find friends to be more important in life and are members of recreational facilities and are less likely to think about the meaning and purpose of life compared with the residents of Doha. None of the marginal effects of the other well-being outcomes for Ommslal is statistically significant. Residents of Alkhour, compared with those of Doha, are more likely to report being a member of a recreation facility, while less likely to report having more life satisfaction. Similarly, residents of Chemal, compared with those of Doha, are less likely to report having more life satisfaction while more likely to view friends to be important in life and none of the marginal effects of the other well-being outcomes for Chemal is statistically significant.

The results show that the level of distrust in the government has a negative, though not statistically significant, association with most of the well-being indicators. Results also show that the level of distrust in the press has a statistically significant negative association with the feeling of happiness while a positive association with having more freedom of choice. An increase in the level of distrust in the police decreases the probability of being a member of a recreation organization and decreases the probability of more thinking about the meaning and purpose of life.

Discussion

This study contributed to the limited well-being literature in the gulf region by investigating the state of the self-perceived well-being and its determinants in Qatar using data from the WVS. Unlike previous studies which focused only on a single dimension of well-being or one sector of the economy, this study conducted a comprehensive analysis of the state of health, psychological self-perceived well-being by capturing the different dimensions of the PERMA model (Seligman, 2012) and using a nationally representative sample of the Qatari population.

The results reveal some gender differences in the state of well-being in Qatar in which Qatari females are less likely to feel happy and being healthy, while they have a higher probability of having a freedom of choice, and thinking about the meaning and purpose in life compared with males. The literature has mixed evidence on the gender difference in the level of psychological well-being. While some studies found that females are more satisfied with their life than males (Di Tella et al., 2001), other studies found no statistically significant gender differences (Frey & Stutzer, 2010).

It is essential to consider the Qatari social context and family setting when assessing the determinants of the Qatari women’s well-being where the women’s life is more interiorized into the marriage and family. Although some progress has been achieved regarding female empowerment in Qatar, many Qatari women are still dependent on and controlled by their families and spouses in the name of culture and religion. Statistics show that 41.5% of the Qatari females aged 15 years and above are economically inactive compared with 3.9% for males in 2017. About half of these economically inactive females are housewives, and 39.6% are full-time students, which indicates a high dependency on their husbands/parent’s income (Planning and Statistics Authority, 2018). An unmarried Qatari woman under the age of 25 needs electronic permission from her guardian (exit permit) to leave the country. Also, statistics reveal a considerable wage gap against Qatari females who are paid 25% to 50% less than men.

Our finding of a positive association between the number of children and better health status, and a higher feeling of happiness, is in line with earlier evidence on the importance of the environment of relationships for the healthy development of children (National Scientific Council on the Developing Child, 2004). Using data from Canada, Nelson et al. (2013) found evidence that parents (and especially fathers) report relatively higher levels of happiness, positive emotion, and meaning in life than nonparents.

We find a non-statistically significant U-shaped association between age and life satisfaction and the feeling of happiness which is in line with Graham and Pozuelo (2017) findings. We also found a statistically significant association between age and the reported health status, which is similar to several earlier studies’ findings. For example, Selim (2008) found a negative association between age and health status in Turkey, while Ngoo et al. (2015) found age to have no statistically significant association with life satisfaction in Asian countries. In another study, Al-Attiyah and Nasser (2016) examined whether there are differences in gender and age concerning life satisfaction using a sample from Qatar University and governmental schools and found significant life satisfaction differences for gender but not age.

Our results also show that education level, in general, has no statistically significant association with well-being outcomes, which is in line with the finding of several previous studies. For example, Ngoo et al. (2015) found education level to have no statistically significant effect on life satisfaction in Asian countries. However, these marginal effects solely measure education’s direct effect, while education could also affect well-being indirectly through income and labor market status. Using individual-level data from the European Social Survey, Cuñado and de Gracia (2012) found that the direct impact of education on happiness does not depend on the level of education (primary, secondary, or tertiary), while the authors found an indirect effect of education on happiness through income and labor status.

The statistically significant positive association that we found between income level and life satisfaction, the feeling of happiness, and better health status is in line with earlier empirical evidence that personal income, whether in absolute or relative terms, matters for well-being. It has been shown that the larger an individual’s income is in comparison with the income of the reference group, the happier the individual. Also, increases in family income relative to that of a reference group have beneficial effects on personal well-being (Ferrer-i-Carbonell, 2005). The positive association between income and well-being that we found is also in line with Stevenson and Wolfers (2008) evidence of a robust positive relationship between GDP per capita and the average levels of SWB across a broad set of countries.

We find unemployment status to be negatively associated with well-being in Qatar. This result is similar to the findings of several earlier studies on the adverse effects of unemployment on health and psychological well-being (Pinto & Graham, 2019). In a meta-analysis of the existing literature, McKee-Ryan et al. (2005) examined the impact of unemployment on worker well-being across 104 empirical studies. They found that unemployed individuals had lower psychological and physical well-being compared with their employed peers.

Results show no statistically significant association between marital status and the examined well-being outcomes. This result is not in line with Diener et al. (2000), who found that married people consistently report greater SWB than never-married individuals, who, in turn, report greater SWB than previously married individuals.

We found that being a religious person is positively associated with self-rated health and being a recreation organization member. This finding is consistent with Strawbridge et al. (2001) findings that religiousness is significantly associated with becoming physically active and enhancing social relationships. Several studies documented that participation in religious services is associated with more social involvement and better health outcomes (AbdAleati et al., 2016; Ferriss, 2002; Strawbridge et al., 2001). Religiousness could increase the ability of an individual to cope with stress and hardship, depression, and anxiety. In a systematic review of the literature, AbdAleati et al. (2016) found consistent evidence that religious practices and an improved sense of religiousness serve as protective factors for physical and mental health. In an earlier study, Hummer et al. (1999) found that involvement in religious services to be significantly associated with an increase in life expectancy.

The results reveal some degree of regional disparities in the level of well-being across Qatari cities, which is in line with the existing empirical evidence that geographical location could influence psychological well-being. Regions differ in terms of income levels, labor market opportunities, availability and/or access to health services, education, and recreation facilities. It has been argued that people who live in larger cities, though they have access to more shops, restaurants, and better health, education, and recreational facilities, may suffer from more pollution, congestion, and crime, all of which directly affect an individual level of well-being (Royuela & Surinach, 2005).

However, these results on the existence of regional disparities in the level of well-being should be interpreted with caution. Doha is the only major city in Qatar, and most of the other Qatari cities included in this study are like districts/neighborhoods that are close to each other, and one may not expect much difference from one region to another. Also, it is notable to mention that the number of respondents in the sample from the Qatari cites other than Doha is very small, which may drive these regional differences.

Our results are, in general, consistent with the findings of several earlier studies on the impact of the level of an individual’s trust in governmental institutions on SWB. For example, Hudson (2006) analyzed the impact of institutional trust on well-being and found that trust in some institutions positively impacts people’s well-being.

Limitations of the Study

This study is not free from limitations. One limitation is the cross-sectional design of the WVS, which limits the ability to make causal inferences. Also, due to data limitations, there could be some determinants that this study could not control for and hence were omitted, which might lead to omitted variable bias.

In addition, although the WVS has seven waves with the most recent wave covering the period 2017–2020, the survey collected data on Qatar in only wave six, in 2010 on which the current study relies on which is to some extent old and many changes have happened since then. The authors plan to revisit this research topic once new up-to-date data become available to account for the changes that happened since 2010.

Moreover, despite the validity and usefulness of the SWB measures used in this study, they are also not free from limitations. One limitation is that they tend to have a high noise-to-signal ratio. In an earlier study, Diener et al. (2013) found that about 20% to 40% of the variability in the life satisfaction scales is attributed to measurement errors or occasion-specific factors, such as a significant event affecting a large group of people simultaneously or a circumstantial event that affects an individual’s mood before the survey. For evidence on the validity and limitations of the measures of SWB, see OECD (2013).

Despite these limitations, this exploratory study’s findings would help inform and guide policymakers in Qatar in setting effective intervention measures aimed at increasing the level of well-being and happiness by identifying the vulnerable groups.

Conclusion and Policy Implications

The findings of this study reveal some degree of demographic, socioeconomic, and regional disparities in the state of well-being in Qatar. Boosting the level of well-being in Qatar and narrowing the demographic and socioeconomic inequalities requires a multifaceted approach that targets the vulnerable groups. One direction for policy intervention is that the Qatari ministry of development planning and statistics should conduct national surveys that include internationally harmonized well-being questions and using nationally representative samples. These surveys should be conducted regularly and the data should be reported on time to assess the progress in the state of well-being in the Qatari society. Another policy recommendation is the adoption of a well-being policy screening tool to assess the impact of any government policy or decision on the well-being of the Qatari population at large and the different sociodemographic groups. The government of Qatar could benefit from the pioneering experience of several other countries in this regard. For example, Bhutan constructed a gross national happiness indicator and introduced a screening tool to assess the impact of any policy draft on 22 factors that includes several SWB indicators. Policymakers in Qatar should not solely focus on improving the objective measures of prosperity such as income and life expectancy, but also incorporate the subjective measures, such as happiness or life satisfaction, and social engagement. One direction in this regard is to include in the Qatari constitution the objective of monitoring and achieving equitable and sustainable progress in the SWB. Another policy recommendation is to launch a national day of happiness in Qatar similar to the international day of happiness that is celebrated by the United Nations.

Encouraging civic engagement and strengthening collective decision-making is one way to gain public trust. This could be achieved by launching an online public engagement system where the public can conveniently and efficiently participate in government affairs using E-government.

Supplemental Material

sj-pdf-1-sgo-10.1177_21582440211008458 – Supplemental material for An Investigation of the Self-Perceived Well-Being Determinants: Empirical Evidence From Qatar

Supplemental material, sj-pdf-1-sgo-10.1177_21582440211008458 for An Investigation of the Self-Perceived Well-Being Determinants: Empirical Evidence From Qatar by Nesreen Nasser and Huda Fakhroo in SAGE Open

Footnotes

Author Contributions

Both the authors contributed equally to this work.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Nesreen Nasser

Supplemental Material

Supplemental material for this article is available online.

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