Life Satisfaction and Its Relation to Leisure and Self-Reported Health with an Example from Mexico

Definition

Life satisfaction is a concept related to an individual’s evaluation of their life, which is determined by taking into account all of the aspects that could affect it. Such an evaluation usually takes into consideration more than just economic conditions. In this paper, we present the relationship of life satisfaction with two of its main determinants, namely, self-reported health and leisure satisfaction. To exemplify this relationship, we utilize data from Mexico.

1. Introduction

Recently, happiness indicators have gained relevance in public discussions in many nations, with some countries prioritizing them over traditional macroeconomic indicators such as economic growth, as capitalism has sacrificed both social and environmental well-being to maximize economic earnings [1]. The economics of happiness is not a new concept, as the classical economists had already shown interest in it; however, this discipline has traditionally focused on the study of wealth, leaving aside issues related to the happiness of a society [2].

Bentham [3] asserted that “Nature has placed mankind under the governance of two sovereign masters, pain and pleasure” and further defined the principle of utility, which “approves or disapproves of every action whatsoever according to the tendency which it appears to have to augment or diminish the happiness of the party whose interest is in question”. By saying “of every action whatsoever”, Bentham attempted to extend this principle beyond particular individuals to the actions of the government.

The “felicific calculus” endeavored to measure human pain and pleasure [2]. In fact, from Bentham’s documents, it is possible to find, among others, the following reflections: the impossibility of fully measuring the intensity of feelings, as, except in the case of small amounts, it is incorrect to assume that an amount of money implies an equal amount of happiness, and the impossibility of qualitatively comparing different feelings, unless they are equated in pecuniary terms [4]. It is important to mention that the term “felicific calculus” is commonly used to refer to the calculus performed by Bentham; however, Bentham never used such terminology [5].

However, social science methods have evolved to allow for the application of surveys to measure happiness by utilizing questions related to life satisfaction, which are now applied worldwide [6]. In fact, in social sciences such as sociology and economics, the quantification of subjective well-being is now a well-established practice [7].

Among the different approaches to study happiness, the hedonic rests on a personal calculation of pleasant and unpleasant experiences with the goal of maximizing human satisfaction. This involves anticipating future situations to choose the best path to guarantee greater well-being. There is a close relationship between Bentham’s utilitarian philosophy and this hedonistic approach, since the individual effort to guarantee higher levels of satisfaction is privileged [8].

Hedonic happiness is divided into experiential and evaluative components. The first consists of the search for satisfactory experiences, while the second estimates the balance resulting from positive and negative experiences [9]. According to Kahneman [10], the assumption of hedonic commentary on the current situation has considerable support for a record of momentary individual evaluation.

Meanwhile, the eudaimonic approach to happiness, from the peripatetic philosophy, considers a comprehensive evaluation of satisfaction with life, considering happiness as a process built from the pursuit of personal goals and their fulfillment. This includes people’s perception regarding the use of their virtues and potential in accordance with the development of their own being [8]. Therefore, the eudaimonic evaluation of happiness includes the estimation of good living over a long period of time.

In recent times, it has been found that there is a weak but statistically robust positive correlation between income and average happiness [11]. Moreover, income, besides satisfying basic needs, fulfills a positional defining role for people, which suggests the importance of relative income in people’s lives [2]. Furthermore, new findings have revealed “perceived social support and income level to be the most consistent predictors of global and domain-specific life satisfaction” [12] (p. 19443).

It has also been proposed that life satisfaction is positively correlated with participation in leisure activities. In this context, a weak but positive statistical correlation between holiday trips and happiness has been found; however, returning to work after a vacation period causes considerable stress due to the accumulated work [13]. Moreover, traveling can help to cope with psychological issues associated with stress from daily life [14]. In the same vein, leisure satisfaction has been found to have a positive influence on life satisfaction among university students [15].

Concerning health and life satisfaction, evidence suggests that the probability of wanting to live shorter lives while enjoying good health increases in those persons with low levels of life satisfaction; meanwhile, in persons with high levels of life satisfaction, the probability of desiring to live longer, even in poor health conditions, increases [16]. There is evidence, in the case of older adults, that indicates that high levels of life satisfaction can contribute to lowering the risk of pain, lowering the number of chronic conditions, and increasing the levels of self-reported health (SRH), among other benefits. Further, life satisfaction is not related to ailments and behaviors such as diabetes, cancer, smoking, and family interaction [17].

The remainder of this paper is organized as follows. In the second part, a brief international historical background on pursuing happiness as public policy is presented; this section, besides presenting information for Mexico, also presents the cases of Bhutan and New Zealand, as these are pioneering countries in incorporating happiness in their public policy plans. Section 3 is divided into two subsections, presenting first the relationship between life satisfaction and leisure satisfaction and then the relationship between life satisfaction and SRH. Section 4 exemplifies, by way of estimating a multivariate linear regression, the associations among life satisfaction, satisfaction with leisure, and SRH, using cross-sectional data from Mexico’s 32 federal entities from 2021.

2. Happiness as Public Policy: Bhutan, New Zealand, and Mexico

2.1. Bhutan

Bhutan is a pioneering country with regard to prioritizing social well-being in public policy [18]. In fact, Article 9, numeral 2, of the Constitution of the Kingdom of Bhutan [19] states that “The State shall strive to promote those conditions that will enable the pursuit of Gross National Happiness.” In the same vein, in Article 20, numeral 1, the Bhutanese Constitution establishes that the government shall provide well-being and happiness to people. Further, Article 9, numeral 13, guarantees both rest and leisure, including periodic paid holidays and limiting working hours. Moreover, since 1729, the legal code of the Kingdom of Bhutan has stated that “if the Government cannot create happiness […] for its people, there is no purpose for the Government to exist” [20].

The Bhutanese concept of happiness is more complex than in most industrialized nations, as it considers not only material well-being, which is often associated with happiness in developed nations, but also the accomplishment of spiritual, social, and physical needs [18]. Concerning spiritual development, the Bhutanese concept of happiness is influenced by both “the nationally prevalent Vajrayana Tantric Buddhist principles and Bon animist beliefs that preceded them” [21].

During 1972, the concept of Gross National Happiness (GNH) was introduced by the Fourth King of Bhutan [20,22] and served as a philosophical guide for the reining monarchy to elaborate public policies. GNH was based on four principles, namely, “Equitable Economic Development, Environmental Preservation, Cultural Resilience, Good Governance” [22]. In fact, it is alleged that GNH rejects the “mono-dimensionality” of traditional approaches to measuring development, such as those centered on GDP, due to their incapacity to mirror the quality of development [21]. Moreover, GNH is considered a moral concept, as “It strives for the happiness of all human and sentient beings, which is critical for a sustainable and thriving environment” [23].

However, with Bhutan gradually opening up to the rest of the world, GNH was examined and received critiques from both foreigners and nationals, who considered its statistical methodology unsound. In response to such criticisms and skepticism, the GNH index was created [22], with its main objective being to serve as an instrument to guide Bhutan and its people towards happiness, mainly by ameliorating “the conditions of not-yet-happy people” [20]. This index attempts, by way of applying rigorous scientific tools, to mirror citizens’ real quality of life in a more precise way than GDP per capita [24].

To achieve its purpose, the GNH index utilizes nine indicators, namely, psychological well-being, health, use of time, education, cultural diversity, good government, community vitality, ecological diversity and resilience, and standard of living [24,25,26], but it also explores factors such as income per capita, literacy, sleep, fundamental rights, and family [27].

Finally, as mentioned above, GNH and the GNH index attempt to provide a different metric to measure progress and development, as they reject the approaches concerning GDP and GDP per capita. In this context, Bhutan has been considered an example of development from the perspective of the so-called “sustainable degrowth”, which consists of reducing both consumption and production in an equitable manner for human well-being to increase, enhancing local and global ecological sustainability in both the short and long term [23].

2.2. New Zealand

In 2001, the Ministry of Social Development (MSD) was created by the labor-led government. In the same year it was created, the MSD released its first “Social Report”, collating social well-being indicators in nine areas [28]. During 2008, the so-called “Five Ways to Wellbeing”, whose main objective was to promote personal well-being, were devised by the “Centre for Wellbeing at the New Economics Foundation” as “Connect, Be Active, Take Notice, Keep Learning, and Give” and have since been adopted by different New Zealander organizations to endorse well-being [29].

In 2018, Indicators Aotearoa New Zealand (IANZ) was launched, elaborating more than 100 well-being statistics in 22 subjects. It is recognized that the creation of IANZ might not have been possible without the previous governmental work of more than 10 years on well-being [28].

Before the COVID-19 outbreak, New Zealand almost achieved full employment and presented high indicators of life satisfaction. Nevertheless, in comparison with other OECD countries, both “income and productivity growth have been low and lagging”. Conversely, the country presented high and growing levels of inequality [28]. In a context of crisis such as the COVID-19 pandemic, a budgetary policy focusing on social issues becomes critical, as “budgeting needs to quickly respond to the needs of the moment in saving lives and sustaining people’s well-being, businesses and the economy” [30].

In May 2019, the so-called “Wellbeing Budget” was created during the mandate of Prime Minister Jacinta Ardern as part of the governmental plan of the center-left labor-led coalition. The budget was elaborated considering that material wealth does not necessarily mirror a population’s well-being. In this sense, New Zealand’s government considers that attention should be paid to five principles to boost citizens’ standard of living, namely, “improving mental health […] reducing child poverty […] addressing the inequalities faced by indigenous Māori and Pacific Island people […] thriving in a digital age; and […] transitioning to a low-emission sustainable economy” [31].

The implementation of the Wellbeing Budget caused New Zealand to receive international praise due to its innovation, so the Government continued promoting social well-being implementations via budgetary policy. In 2020, “Wellbeing Budget 2020: Rebuilding Together” was launched [30]. The New Zealand Treasury [32] also reports the following: “Wellbeing Budget 2021: Securing Our Recovery”, “Wellbeing Budget 2022: A Secure Future”, and “Wellbeing Budget 2023: Support for today Building for tomorrow”.

Finally, by way of redirecting its budget towards areas that do not create national wealth but are important for social development, New Zealand became the second nation to prioritize well-being over economic growth. However, it is important to remark that the Wellbeing Budget attempts to promote economic growth without disparaging social areas of development [1].

2.3. Mexico

In Mexico, President Andrés Manuel López Obrador stated that the measurement of GDP should be eliminated to focus on measuring the happiness and well-being of the population [33], as measuring GDP growth is senseless in the absence of a better income distribution [34]. The President López Obrador also mentioned that the efforts of the 2018–2024 administration were focused on delivering resources to the poorest sectors of society to improve consumption, thereby boosting the economy as a whole [33]. In fact, this so-called “new Mexican model” was designed to formulate economic policies based on five principal pillars, namely, democracy, justice, honesty, austerity, and well-being [35].

The type of well-being pursued in Mexico seeks to create conditions for people themselves to construct their happiness, arguing that economic growth, competitivity, and increases in productivity are means to achieve a “superior goal”, namely, people’s well-being. The foundations of this economic conception are that an economic model that only focuses on material progress without considering justice is an unviable project doomed to failure and that economic inequality leads to social conflicts [35]. However, the main challenge to implement these policies lies in overcoming the heterogeneous conditions of the economic agents and in defining the role of the means of production themselves, as well as that of clean energies [36].

To measure well-being, President López Obrador proposed the creation of a new index, whose formulation would involve a multidisciplinary team of experts such as mathematicians, economists, sociologists, and anthropologists [34]. This index was supposed to include parameters related to well-being, inequality, and happiness; however, years after its announcement, it seems that this Mexican well-being index will not be released [37].

Nonetheless, the National Institute of Statistics and Geography (INEGI) [38] elaborates, since some years ago, the “Well-being Indicators by Federal Entity”, including the calculation of a life satisfaction indicator. This statistic, according to the INEGI [39], is obtained by asking the question “how satisfied are you currently with your life?” to the people in the survey’s sample. The measurement scale ranges from 0 to 10, with 0 being the lowest rating and 10 the highest. The data indicate that Mexico achieved a life satisfaction average score of 8.4 points in 2021 [38]. A similar indicator to measure life satisfaction is utilized in Germany [6].

Finally, in 2024, Mexico ranked 25th out of 143 on the list of the happiest countries in the world, according to the World Happiness Report, which is compiled every year based on people’s perceived happiness and on economic and social data [40].

3. Life Satisfaction: Its Relationship with Leisure and Self-Reported Health

3.1. Leisure and Life Satisfaction

The Universal Declaration of Human Rights (UDHR) was adopted by the General Assembly of the United Nations on 10 December 1948 as a response to the barbaric acts perpetrated during World War II [41]. Currently, in its Article 24, the UDHR states that “Everyone has the right to rest and leisure, including reasonable limitation of working hours and periodic holidays with pay” [42].

Nonetheless, until the 1960s, there were few works on leisure in the social sciences; however, from then on, various research agendas in the social sciences were undertaken, with an increase during the following two decades [43]. In one of the pioneering books on the subject, Parker [44] pointed out that until the second half of the 1970s, the sociology of leisure had been disdained because it was considered that there were no material benefits that could be obtained from this type of work. In recent years, Stebbins [45] maintained that this subdiscipline “[…] may be described as an estranged child of mainstream sociology”, even when some governments have incorporated the right to free time as one of the dimensions that must be guaranteed to their population through public policies, as in the cases of the Kingdom of Bhutan and New Zealand.

It should be noted that leisure itself has been a target for contemporary marketing; however, this dimension has been studied through the sociology of consumption [43], which has focused on activities derived from free time that can be commodified, including the necessary inputs to carry them out. The well-being produced from the practice of leisure, while including activities that can be considered commodities, also takes into account those that are free or not directly associated with a market niche but that allow the enjoyment of simple pleasures [6].

Leisure is situated in a dichotomy where work is the counterpart. The time dedicated to leisure is subjectively defined as a period in which one is not performing work for which payment is received to meet the need for material goods or services, even when these serve to carry out leisure activities [46].

According to Elias and Dunning [46], during working hours or in routines perceived as necessary for life, people are required to firmly contain their drives, affections, and emotions, while in the practice of leisure, actions are allowed to flow with less constraint because an imaginary, even fictitious, scenario is generated in which the excitement learned during non-recreational life is imitated but cannot always be manifested. In leisure time, people’s feelings are allowed, par excellence, to be excited beyond what is permitted most of the time.

It is difficult to devise a leisure time quantification method that allows us to assess, even by using time as a unit of measurement, the greater or lesser impact that this dimension has on people’s lives. According to Elias [47], the frequency of leisure activities is perceived differently by human beings in relation to the structures in which they have been socialized, which leads to a moral distinction between work and leisure. He points out that people who dedicate part of their free time to work, exceeding their work obligations, decide to do so because they have a deep-rooted principle of duty that makes them perceive leisure as an immoral and useless act.

Freedom of choice is a fundamental element that determines the well-being generated by leisure. Each person has individual preferences that come into play when determining how they will spend their free time [48]. Lapa [48] mentioned that when there is greater freedom and control to determine leisure activities, greater satisfaction is produced. This is clear in the family environment, where there are power relations that better position certain members to choose the family activity. For example, in a study on this topic, Siegenthaler and O’Dell [49] found that while a father reported great pleasure during a family outing, the mother felt stressed, and the daughter reported boredom.

The most reliable approximation to the well-being or satisfaction produced by leisure time is recorded through each person’s perception. Trying to implement an objective unit for this purpose is a futile effort because people experience the same situation in different ways, so self-reported satisfaction is more significant [49].

Individuals’ socialization regarding work and leisure time, as well as their perception of the freedom to choose their free-time activities, has led to the convention that this variable should be constructed based on subjectivity, thus respecting what is reported by the interviewees. For these reasons, since 2014, the INEGI has conducted satisfaction surveys based on people’s perception [50].

Figure 1 illustrates the association between leisure satisfaction and life satisfaction in Mexico during 2021. According to the data, Mexicans achieved a general average score of 7.7 out of 10 in leisure satisfaction [38]. The figure shows that the Mexican states with high levels of leisure satisfaction also obtained a high level of life satisfaction; this is particularly notorious in the cases of Coahuila, Colima, and Nuevo Leon. Conversely, the state with the highest unsatisfaction with respect to leisure time was Puebla, where an average life satisfaction among the lowest in the country was also reported.

3.2. Self-Reported Health and Life Satisfaction

SRH is an evaluation performed by individuals themselves that indicates their self-perceived condition; therefore, it is not always accurate in terms of the respondent’s real health status. In addition, these types of evaluations are usually carried out by applying a single question. This approach, in some cases, has two main advantages: low cost and simple interpretation [51]. In this sense, SRH mirrors an individual’s self-perception of health, “including its biological, psychological and social dimensions, that is inaccessible to any external observer” [52]. It is important to mention that “SRH is today frequently used as the only measure of health when more extensive measurements of health are lacking” [53].

In recent times, SRH has gained importance due to its predictive power on individuals’ past, present, and future health statuses. In particular, evidence suggests that SRH is an important predictor of “new morbidity […] decline in functional ability […] recovery from illness […] and health care utilization” [54]. In fact, subjective SRH indicators, such as those consisting of a single question, are frequently utilized in “epidemiological health research” [52]. Moreover, SRH has proved to be an accurate and stable predictor of mortality, sometimes better than techniques explicitly designed with this objective [53].

Regarding life satisfaction, there is a close linkage among health, well-being, and happiness. In fact, it is considered that the main factor determining well-being is good health, while deteriorated health has “lasting and negative” impacts on well-being [18]. Moreover, it was found that life dissatisfaction increases both healthcare utilization and cost. It is important to highlight that this relationship was found to be persistent “after adjusting for demographic factors, comorbidity, socioeconomic factors, and health behaviors” [55]. There is also a negative association between ill health and life satisfaction; indeed, prior to the COVID-19 outbreak, the main predictors of life satisfaction were health and the work–life balance, whereas throughout the pandemic, “different types of household structure” were among the most important determinants of life satisfaction [56].

In this context, self-reported mental health has been positively associated with life satisfaction. Evidence suggests that subjective mental health has a stronger association with life satisfaction than other identified factors [7]. It has been found that active people tend to have better mental health than inactive people. In fact, there are several indicators showing that physical activity plays not only a role in mental illness prevention, but also a curative role in some types of mental illnesses [57].

Moreover, exercising not only prevents overweight-related diseases, but also helps to maintain adequate mental health, as it helps in preventing depression and anxiety and reducing stress levels, besides stimulating the release of endorphins [58]. In this sense, it is considered that sports activity should be encouraged on the basis of its “health-giving” benefits [47].

Figure 2 illustrates the relationship between life satisfaction and SRH in the 32 Mexican federal entities in 2021, revealing that the federal entities where people perceived themselves to be healthier were those where a higher level of satisfaction with life was reported. In fact, the states of Coahuila, Colima, and Nuevo León presented SRH scores of 8.6, 8.7, and 8.6, respectively. On the contrary, states such as Tabasco, Oaxaca, Puebla, and Guerrero presented low SRH.

Tabasco reported the worst emotional balance in Mexico in 2021, followed by the state of Puebla. For its part, Guerrero was the state with the largest number of people suffering from symptoms of depression, as 20.7% of its population has felt symptoms associated with this condition. Other states with high levels of depression among their inhabitants were Tabasco, Durango, Zacatecas, and Michoacan. Conversely, Quintana Roo presented the lowest levels of depression among the Mexican states. Concerning anxiety, Puebla was the state where most people responded affirmatively to questions related to feeling nervous, inability to calm down, or uncontrolled worries. Other states that reported high levels of anxiety were Chiapas, Michoacán, Guerrero, and Zacatecas [59].

4. An Application to the Case of Mexico

4.1. Data and Method

To elaborate on this document, cross-sectional data on life satisfaction, leisure satisfaction, and SRH corresponding to the year 2021 for the 32 Mexico’s federal entities were obtained from the INEGI [38] $\left(N=32\right)$. The INEGI elaborates on the variables presented here according to the methodology stated by the OECD [38]. Accordingly, these statistics were prepared following the methods presented by the “OECD Guidelines on Measuring Subjective Well-being”, which considers that measuring subjective well-being is fundamental when analyzing the quality of life [60].

In this document, to illustrate the existing relationship between the above-mentioned variables, we employed a multivariate regression estimated by the ordinary least squares (OLS) method. To develop the OLS method, consider Equation (1):

$${\mathbf{y}}_{n\times 1}={\mathbf{X}}_{n\times k} {\widehat{\mathsf{\beta }}}_{k\times 1}+{\widehat{\mathsf{\epsilon }}}_{n\times 1}$$

(1)

where $\mathbf{X}$ is the so-called “data matrix”, as it contains all of the observations of the independent variables; $\widehat{\mathsf{\beta }}$ is the vector of estimated parameters; vector $\mathbf{y}$ contains the observations of the dependent variable; and $\widehat{\mathsf{\epsilon }}$ is the vector of residuals. Following Gujarati and Porter [61] and Pindyck and Rubinfeld [62], we now illustrate the procedure to obtain the fundamental equation of the OLS method.

From Equation (1), we obtain

$$\widehat{\mathsf{\epsilon }}=\mathbf{y}-\mathbf{X}\widehat{\mathsf{\beta }}$$

(2)

Then

$$\widehat{\mathsf{\epsilon }}\text{'}\widehat{\mathsf{\epsilon }}=\left(\mathbf{y}-\mathbf{X}\widehat{\mathsf{\beta }}\right)\text{'}\left(\mathbf{y}-\mathbf{X}\widehat{\mathsf{\beta }}\right)=\mathbf{y}\text{'}\mathbf{y}-2\widehat{\mathsf{\beta }}\text{'}\mathbf{X}\text{'}\mathbf{y}+\widehat{\mathsf{\beta }}\text{'}\mathbf{X}\text{'}\mathbf{X}\widehat{\mathsf{\beta }}$$

(3)

We now partially derive Equation (3) with respect to $\widehat{\mathsf{\beta }}$.

$${\displaystyle \frac{\partial \left(\widehat{\mathsf{\epsilon }}\mathrm{\text{'}}\widehat{\mathsf{\epsilon }}\right)}{\partial \widehat{\mathsf{\beta }}}}=-2{\mathbf{X}}^{\mathrm{\text{'}}}\mathbf{y}+2{\mathbf{X}}^{\mathrm{\text{'}}}\mathbf{X}\widehat{\mathsf{\beta }}$$

(4)

Equating Equation (4) to 0, and using algebra, we obtain Equation (5):

$$\widehat{\mathsf{\beta }}={\left(\mathbf{X}\text{'}\mathbf{X}\right)}^{-1}\mathbf{X}\text{'}\mathbf{y}$$

(5)

In Equation (5), $\mathbf{X}\text{'}\mathbf{X}$ is an invertible matrix under the assumption that $\mathbf{X}$ has rank equal to k [62]. Equation (5) is the fundamental result of the OLS method [61].

However, the correct specification of the OLS models requires checking the validity of certain assumptions in the estimated residuals. Among the most important are no autocorrelation, no heteroskedasticity, no multicollinearity, and normality. In the same vein, it must be ensured that the linear specification of the model is adequate. It is worth mentioning that in econometric models containing cross-sectional information, given the presence of heterogeneous data, heteroskedasticity is a common problem [61]. Meanwhile, the presence of autocorrelation is generally associated with time series models [63].

In this document, a traditional log–log model, as specified in Equation (6), was estimated:

$$\ln {\left(Life\right)}_i=\alpha +{\beta }_1\ln {\left(Leisure\right)}_i+{\beta }_2\ln {\left(Health\right)}_i+{\epsilon }_i$$

(6)

These types of models, which are very popular in practice, are used to measure elasticities [61].

4.2. Results

This example attempts to illustrate the relevance of leisure satisfaction and SRH in determining life satisfaction. To achieve this, a traditional log–log ordinary regression, estimated using the OLS method, was performed (

Table 1. OLS regression.

Variable	Coefficients	t-Statistic
$\mathrm{Dependent} \mathrm{Variable}: \ln \left(Life\right)$
Constant	0.2547	1.2258
$\ln \left(Leisure\right)$	0.2932	3.0601 ***
$\ln \left(Health\right)$	0.6041	5.5302 ***

Note: Only the first four decimals are considered. *** represents $p<0.01$.

), as this specification allows for the measurement of elasticities [61].

Once the regression was computed, classical correct specification tests for OLS models were applied, obtaining adequate results according to the traditional significance levels (

Table 2. Correct specification tests.

Test	Value	p-Value
Jarque–Bera normality test	0.8333	0.6592
White heteroskedasticity test (no cross terms)	0.1531	0.9263
White heteroskedasticity test (cross terms)	3.0434	0.6933
Ramsey RESET test	0.1555	0.6962
F-statistic	41.0647	0.0000 ***
$R^2$	0.7390	–
Adjusted $R^2$	0.7210	–

Note: Only the first four decimals are considered. *** represents $p<0.01$.

).

To complement the results in Table 2, variance inflation factors (VIFs) were calculated, as these tests permit us to detect multicollinearity in linear regression analysis [61]. The results are summarized in

Table 3. Variance inflation factors (VIFs).

Variable	VIF
Constant	NA
$\ln \left(Leisure\right)$	1.4108
$\ln \left(Health\right)$	1.4108

Note: $1<VIF<5$ indicates moderate correlation [64]. NA—not applicable.

.

As final correct specification tests, we performed Quandt–Andrews unknown breakpoint tests in order to confirm that the model does not present structural changes. The results are summarized in

Table 4. Quandt–Andrews unknown breakpoint test.

Statistic	Value	p-Value
Maximum LR F-statistic	1.537630	0.9070
Maximum Wald F-statistic	4.612889	0.9070
Exponential LR F-statistic	0.350804	0.8244
Exponential Wald F-statistic	1.191547	0.7581
Average LR F-statistic	0.657266	0.7251
Average Wald F-statistic	1.971797	0.7251

Note: Null hypothesis—no breakpoints within 10% trimmed data. Number of breaks compared—25. Varying regressors—all equation variables.

.

As, according to the results in Table 2, Table 3 and Table 4, the OLS regression was correctly specified, it is possible to analyze the results in Table 1. The model indicates that life satisfaction increases by 0.29% when leisure satisfaction increases by 1%. In the same vein, if SRH increases by 1%, then life satisfaction increases by 0.60%. These results show that life satisfaction is more sensitive to changes in SRH than it is to variations in leisure satisfaction.

It is important to note that the regression’s intercept term was not statistically significant. However, it was not removed from the equation as, in linear regression analysis, it is better to explicitly utilize a constant, unless there is a solid theoretical reason to omit it [61].

5. Conclusions

In this paper, we presented the relationship of life satisfaction with both leisure satisfaction and SRH. We first made reference to the pioneer countries in considering happiness as part of their public policy, namely, Bhutan and New Zealand, and then we presented the case of Mexico. We conducted an extensive literature review concerning the relationship that life satisfaction has with both leisure satisfaction and SRH, which was further illustrated by using data from Mexico, which are consistent with the international evidence found in the literature.

Happiness and life satisfaction have gained attention as indicators of well-being, given that traditional measures such as GDP and GDP per capita do not entirely mirror human development in all of its dimensions. In this context, well-being indicators have been prioritized over traditional economic statistics by nations such as Bhutan and New Zealand. In Mexico, giving well-being a major role when designing public policies has at least been discussed.

Life satisfaction is related to both leisure and health. Firstly, freely deciding how to spend leisure time results in higher life satisfaction. Indeed, people involved in leisure activities without taking part in activity selection tend to report lower levels of satisfaction. Secondly, life satisfaction influences the amount spent on healthcare, while deteriorated health diminishes life satisfaction, as the latter corresponds to an evaluation of an individual’s life as a whole. Self-reported mental health, which is related to having an active lifestyle, is also considered a main determinant of life satisfaction.

Finally, the OLS regression, consistent with the literature reviewed, showed that SRH had a stronger positive association with life satisfaction than leisure satisfaction in 2021. However, it should be noted that leisure also ameliorated the perceptions that Mexican people have about their life.