Introduction

Happiness is one of the essential emotions affecting people’s lives1. The nature of happiness has not been clearly defined uniformly and can be defined as more than an emotional experience. It is a complex concept that can be described as pleasure, life satisfaction, positive emotions, a meaningful life, or a feeling of contentment2. The common definition of happiness is ‘the degree to which individuals positively evaluate the overall quality of their present life as a whole’. In other words, this is about how much one likes life3. According to the World Happiness Report (2021–2023), Iran ranked relatively low as 100 among 143 countries4.

Happiness correlates with various factors5 such as socio-economic conditions, political environment6, cultural values and social norms. Indeed happiness levels could vaery from different geographical areas7. For example, in Asia the gap between the highest and the lowest happiness index is quite large. The happiness score in United Arab Emirates, Singapore, and Taiwan was reported to be 6.73, 6.52, and 6.50, respectively; while the happiness scores in Iran was 4.924. In addition, studies consistently showed that sociodemographic factors such as age, gender, income, education, employment status, and the place of living correlate with happiness8. Specifically, it is argued that in many but not all countries, the younger adults are happier than old adults4. Adulthood is divided into three periods including young or early adulthood (20–39), middle adulthood (40–59), and old age (60 and over)9. Young adults are usually healthy, and young adulthood is considered as the healthiest period of life10. In addition, this age group usually face societal challenges and perhaps happiness at this age might have long-term impact on their overall well-being. Young adulthood is the experience of leaving home, completing school, entering the workforce, forming a romantic partnership, and transitioning into or moving toward parenthood11,12. Therefore, critical developmental processes occur during young adulthood. The mature aspects of executive functioning are paired with increased motivational/emotional influences affecting decision-making13.

Iran has a young population and almost 40% are aged 20–3914. Thus, it is important to know how this population feel and how they encounter several limitations they experience. Therefore, this study aimed to investigate the socio-economic determinants of happiness among in this age range group in Iran. We hypothesized that happiness among people aged 20–39 might be influenced by gender, education, employment, income, and the place of living8. A conceptual framework is depicted in Fig. 1.

Fig. 1
figure 1

Conceptual frameworks of happiness.

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Methods

Participants

We conducted a national cross-sectional survey to collect data on happiness and its correlates among a representative sample of young adults in Iran. Inclusion criteria were age 20–39 years, Iranian nationality, responding to the study questionnaires, and complete responses. Trained interviewers collected the data using paper and pencil for documentation. The study was conducted in accordance with the Helsinki Declaration.

The following formula15 was used to estimate the sample size:

$$n=\frac{\:\:{z}_{{\upalpha\:}/2\:\:\times\:p\left(1-p\right)}^{2}}{{d}^{2}}\:$$

Considering the happiness proportion (P) equal to 50%, the Z value of 1.96, the precision (d) equal to 1%, and the design effect of 1.5, the sample size was estimated at 14,406. To recruit samples, based on population density throughout the country, multistage sampling was applied. The country was classified into five regions (first unit). Within each region, one province was randomly chosen (second unit). Subsequently, two cities and two rural areas were randomly selected in each province (third unit). To ensure equal representation, every household in the urban and rural areas had the same chance of being sampled. The households to be sampled were selected within each census section. Finally, sampling units (the individuals) were selected randomly from all eligible persons residing in the same household.

In all, 13,173 young adults aged 20–39 years old completed the questionnaire (6017 male and 7156 female). The mean age of respondents was 31.5 (SD = 4.8) years. Most participants were well educated (67.7%); about half of the sample were employed (48.2%), and the vast majority of individuals had intermediate economic status (61.1%) and living in urban place (67.3%). The characteristics of the study sample are shown in Table 1.

Table 1 The characteristics of the study sample.
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Measures

Happiness: Happiness was measured using the Oxford Happiness Questionnaire (OHQ). The questionnaire contains 29 items rated on a 6-point Likert scale (strongly disagree = 1, moderately disagree = 2, slightly disagree = 3, slightly agree = 4, moderately agree = 5, strongly agree = 6)16. The total score on the questionnaire also ranges from 1 (not happy) to 6 (too happy).

The psychometric properties of the Iranian version of the OHQ are well documented. The forward-backward translation procedure was applied to translate the OHQ from English into Persian to validate the Iranian version. An independent expert with good English knowledge translated the items into Persian. Then, a consolidated forward version was produced. The result of factor analysis showed a one-factor structure. It also supported the convergent and divergent validity of the OHQ Iranian version. Cronbach’s alpha coefficient and test-retest reliability were 0.90 and 0.79, respectively17. In the present study, Cronbach’s alpha coefficient was 0.896.

Independent variables

Age, gender, education, occupation, and income were treated as independent variables. Education was measured by the duration of formal education. Occupation (employment) was categorized as employed, stay-at-home parent (females who were deliberately not working outside the home), student, and unemployed (those who were seeking a job when we were collecting the data). Income was measured at the family level, indicating very good/good, intermediate, and poor/very poor income.

Statistical analysis

Descriptive statistics were used to explore the data. Logistic regression analysis was performed to assess the relationship between happiness and demographic and sociodemographic variables. As such, based on happiness ratings, participants were classified into two groups (scores of less than 4 was considered unhappy, and scores of 4 and above were considered happy) to create a binary outcome18,19. Sociodemographic information was considered as an independent variable. The results were presented as odds ratios and 95% confidence intervals. All statistical analyses were performed using SPSS software (IBM Corp, Version 23.0. Armonk, NY: IBM Corp) and AMOS software (version 23). Path analysis was conducted to identify a causal pattern of the independent variables20.

Results

Descriptive analysis

The mean (SD) happiness score was 4.09 (0.58), suggesting a condition named ‘rather happy, pretty happy’. The mean (SD) happiness score for males was 4.09 (0.59), and it was 4.08 (0.56) for females. In addition, overall, 55.4% (n = 7293) of the respondents were ‘happy’, and the remaining 44.6% (n = 5880) were ‘unhappy’ (Table 2).

Table 2 Overall distribution of Oxford happiness score (n = 13173).
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Findings

In multiple logistic regression analysis, gender and the place of living are not significant, whereas age (OR for age > 30 = 1.092, 95% CI 1.016–1.174, P = 0.016), education (OR for 10–12 = 0.761, 95% CI 0.681–0.852, P < 0.001), occupation (OR for unemployed = 0.522, 95% CI 0.422–0.646, P < 0.001), and income (OR for poor/very poor = 0.615, 95% CI 0.545–0.694, P < 0.001) are significant (Table 3).

Table 3 The results obtained from logistic regression analysis indicating the odds ratio for happiness (n = 13137).
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Happiness by gender

Further, separate analyses for men and women showed that age (OR for age > 30 = 1.118, 95% CI 1.002–1.247, P = 0.046), education (OR for 10–12 = 0.766, 95% CI 0.638–0.920, P = 0.004), occupation (OR for unemployed = 0.506, 95% CI 0.405–0.631, P < 0.001), and income (OR for intermediate = 1.171, 95% CI 1.027–1.336, P = 0.019, and OR for poor/very poor = 0.701, 95% CI 0.586–0.837, P < 0.001) still were significant for men, but the association between happiness with education (OR for 10–12 = 0.756, 95% CI 0.655–0.872, P < 0.001) and income (OR for intermediate = 0.860, 95% CI 0.766–0.965, P = 0.010, and OR for poor/very poor = 0.561, 95% CI 0.476–0.661, P < 0.001) remained significant only for women. The detailed results are shown in Table 4.

Table 4 The results obtained from multiple logistic regression analysis indicating the odds ratio for happiness by gender.
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Happiness by age

Further separate analyses for age ≤ 30 and age > 30 showed that education, occupation, and income were still significant for age ≤ 30 and age > 30. Also, the place of living (OR for rural = 0.805, 95% CI 0.805–0.991, P = 0.033) was significant for age > 30. The detailed results are shown in Table 5.

Table 5 The results obtained from multiple logistic regression analysis indicating the odds ratio for happiness by age.
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The path analysis

The results of the path analysis indicated that the model has an acceptable fit21,22 (X2/df = 45.41, RMSEA = 0.058, CFI = 0.99, NFI = 0.99, NNFI = 0.98). Overall, the findings showed that income was a powerful predictor for happiness (ß = ± 0.09). However, the model explained about 1.5% of the variance observed, which we think is almost nothing (R2 = 0.015). The results are predicted in Fig. 2.

Fig. 2
figure 2

The results obtained from path analysis.

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Discussion

This study aimed to examine the sociodemographic factors of happiness among individuals aged 20–39 in Iran. The average score for happiness among young adults in Iran is 4.09 (out of 6.0. Similar to previous studies18,23, the findings from this study confirmed that happiness is associated with various sociodemographic factors.

Findings from multiple logistic regression analyses indicated a significant association between happiness and education for those who reported having 10–12 years of formal education (intermediate level of education). Further separate analyses by gender also showed that a significant association between happiness and education for both men and women with similar duration of formal education exists. Furthermore, performing separate analyses by age showed similar findings. Given that education might impact on employment opportunities and earning, it is possible to argue that such individuals usually can hardly meet their expectations and goals. As a result, they had lower levels of happiness. In contrast, individuals with a higher level of education were happier, likely due to better employment, higher income, and better health4. Our findings are consistent with the study carried out in Indonesia24.

A significant association was observed between happiness and occupation. Further separate analyses for men and women showed that occupation status was significant for men but not for women. One might argue that the reasons behind gender differences concerning the significance of occupation may be potentially related to social roles and cultural expectations. For instance, part of the negative relationship between unemployment and life satisfaction can be explained by the fact that unemployment is usually associated with a loss of income25. Thus, in a traditional society such as Iran, where culturally men are responsible for family expenses, the effect of employment on happiness is more pronounced.

The findings of the path analysis indicated that among the variables studied, income was a significant predictor of happiness. However, it was not very influential because the amount of R2 was very small. This indicates that other factors might play an influential role in happiness. As such we think in addition to economic factors a number of social and political issues should receive enough attention in predicting and interpreting perceived happiness among young adults. It seems that for this population equal opportunities for education and employment, gender equality, dignity, and living conditions might be involved in explaining other factor that contribute to happiness. Evidence suggests that in developed countries where the standard of living is high, freedom to make life choices matters a lot. However, the freedom to make life choices is usually are ignored for people in developing countries where the standard of living is low, and individuals struggle to sustain their livelihood and improve their living conditions26. Considering that Iran is a multicultural country, located in a conflict zone, and faces several challenges, including economic sanctions18, it appears that future studies in Iran in addition to sociodemographic variables, should focus more on the assessment of the relationship between happiness, cultural factors, equity, social supports, and health.

Strengths and limitations

The study benefited from a relatively large sample size with diverse socio-demographic backgrounds. However, multistage sampling can lead to unrepresentative samples, restricting the generalization of the results to all Iranians. Also, the study did not include any measures of health. As such, relating happiness to health in this population needs further investigation. To overcome this limitation, we recommend longitudinal studies exploring causal relationships to reveal differences in happiness across different health statuses. Ethics approval was obtained approximately 7 years ago, but due to some logistic problems, the study commenced with a delay; replication may be necessary for updated finding.

Conclusion

The findings from the current study indicated that low income and unemployment make people feel unhappy. Although, young adults in Iran reported feeling rather happy, understanding this population seems necessary to make them happier and more content, and governmental efforts should be more directed toward expanding employment opportunities and enhancing income levels for this age group.