Figure 1 depicts the life satisfaction of the societies in Indonesia, Myanmar, Malaysia, the Philippines, Singapore, Thailand, and Vietnam. Indonesia has the highest level of life satisfaction with a score of 31.49, while the lowest life satisfaction score in Indonesia is 1.5. Myanmar has the highest satisfaction score at 30.08, Malaysia at 26.06, the Philippines at 27.19, and the lowest life satisfaction score at 2.44. Singapore has the lowest life satisfaction score at 0.9 and the highest life satisfaction score at 25.84. Meanwhile, Thailand has the highest life satisfaction score at 19.03 and Vietnam at 28.81. When comparing these countries, it is known that Indonesia has the highest life satisfaction of 23.85 compared to the other six countries (Myanmar, Malaysia, the Philippines, Singapore, Thailand, and Vietnam). Meanwhile, Malaysia ranks lowest in terms of life satisfaction among the other countries, at 5.77.

Figure 2 depicts the happiness levels among ASEAN citizens. The highest score among Indonesian residents is that of moderate happiness, at 49.35. There is only one resident reporting unhappiness, while those feeling somewhat unhappy in Indonesia constitute 4.84, and those reporting high levels of happiness amount to 44.82. A majority of Myanmar residents express moderate happiness with a score of 54.3, equivalent to the proportion of moderately happy individuals in Malaysia, which stands at 66.64. Meanwhile, Filipinos report a high level of happiness at 51.18. The happiness levels in Singapore, Thailand, and Vietnam are categorized as moderate, with scores of 61.75, 51.49, and 49.2 respectively. Comparing the seven ASEAN nations, it is noted that six of them exhibit a moderate level of happiness. The exception is the Philippines, which reports a notably high level of happiness. Among the six nations with moderate happiness levels, Malaysia records the highest score. Myanmar reports the lowest happiness level at 3.43.

Figure 3 illustrates the per capita carbon dioxide (CO₂) emissions in metric tons for several countries in Southeast Asia. Malaysia exhibits the highest emissions at 8.09 metric tons per capita, followed by Singapore at 6.69 metric tons per capita. Thailand also registers relatively high emissions at 4.11 metric tons per capita. Meanwhile, Myanmar demonstrates the lowest emissions, standing at merely 0.48 metric tons per capita.

The significant differences in CO₂ emissions per capita among these countries may be attributed to factors such as the level of industrialization, consumption of fossil fuels, and utilization of renewable electricity. This assertion is supported by data obtained from the World Bank and Our World in Data using six indicators (Table 2). Firstly, Singapore exhibits the highest Electric Power Consumption (EPC) followed by Malaysia successively at 8844.69 and 4539.50 kWh per capita, respectively. Meanwhile, Myanmar has the lowest per capita electricity consumption at 220.39 kWh per capita. This aligns with findings from Salahuddin et al. (2018) which discovered that a 1% increase in electricity consumption would result in a 0.71% increase in CO₂ emissions. The causation is attributed to the use of fossil fuels as a source of electricity. This is in line with the second indicator, which indicates that Malaysia has the highest proportion of Fossil Fuel Energy Consumption (FFCTotal) to total energy consumption (96.63%), followed by Singapore (90.58%). Meanwhile, Myanmar has the lowest proportion of fossil energy consumption (44.29%). Thirdly, Singapore exhibits the highest Fossil Fuel Consumption per Capita (FFCCapita) (146258 kWh), indicating a very high level of energy consumption per individual. Fossil fuels are known to be a trigger for increasing CO₂ emissions. Li & Haneklaus (2021) found that a 1% increase in fossil fuel consumption leads to a long-term increase in CO₂ emissions per capita by 0.235%. Fourthly, Singapore has the highest GDP per Capita (82807.63 US). Lane (2011) states that CO₂ and GDP are interrelated. GDP, which is a manifestation of economic expansion, can lead to an increase in CO₂ emissions. Renewable Electricity Output (REO) can be utilized to mitigate the risk of increased CO₂ emissions due to economic expansion. Myanmar has the highest REO (58.85%), indicating reliance on renewable energy. Meanwhile, Singapore has the lowest renewable electricity output (1.82%). Li & Haneklaus (2021) states that a 1% increase in REO consumption per capita in the long term will reduce CO₂ emissions per capita by 0.259%. Although Singapore has higher economic activity compared to Malaysia, its total CO₂ emissions are lower. The cause may be the Total Population (POP) of the respective countries Singapore is known to have the smallest population (5.64 million) compared to other ASEAN countries.

Table 3 shows the output of ordered logistic regression analysis revealing that health condition, financial status, and television ownership are factors influencing the increase in life satisfaction. Factors exhibiting a negative impact on life satisfaction include CO₂ emissions per capita and male gender. Meanwhile, factors positively influencing happiness encompass having children, marriage, health condition, financial status, income, and television ownership. Factors negatively impacting happiness consist of CO₂ emissions per capita, male gender, urban residency, socio-economic status (inverted), and social media ownership. The prob>chi² metric is utilized to determine the goodness-of-fit of a model, where the expected score should be less than 0.05. We obtained a prob>chi2 value of 0.000 for both the satisfaction and happiness models, indicating that there are no issues with these models. While some researchers might employ Pseudo R² to estimate the model's goodness-of-fit, we chose not to use it due to its differing interpretation from the R-squared in Ordinary Least Square analysis (Bruin, 2011; Nwakuya & Mmaduka, 2019).

We found that an increase in CO₂ emissions per capita reduces life satisfaction and happiness among ASEAN residents. This result is related to the contribution of carbon dioxide to climate change. These findings are consistent with Kumari et al. (2021), who found that a 1% increase in CO₂ emissions leads to a 0.12% decrease in subjective happiness. CO₂ exacerbates climate change, leading to higher temperatures, increased rainfall, humidity, and wind speed. Consequently, there is a higher likelihood of droughts, floods, hurricanes, and other extreme weather events. These conditions can potentially cause crop failures (Priyanto, 2021), ultimately resulting in food insecurity and health issues in low- and middle-income countries (Taghizadeh-Hesary & Taghizadeh-Hesary & , 2020). The climate crisis and the lack of climate technology also have long-term negative impacts on human happiness (Weijers & Agar, 2023). In several countries, such as China, Pakistan, and India, non-renewable energy consumption is the largest contributor to carbon emissions (Ansari et al., 2020) (Chen et al., 2019). According to (Lu & Sohail, 2022), CO₂ emissions are considered the main cause of environmental damage and GHG. Global happiness levels decline due to greenhouse gases, while economic prosperity increases life satisfaction (Apergis & Majeed, 2021). Other sources indicate that well-being and environmental conditions are reciprocal. More prosperous individuals tend to care more about their environment, and people living in better environments tend to be more prosperous. In countries with higher average happiness levels, people also tend to be more energy-efficient (Zidanšek, 2007). People living in green environments have higher well-being and life expectancy (Lu & Sohail, 2022).

These conditions imply that ASEAN policies should invest more in green technology and green spaces to increase their accessibility and supply (Apergis & Majeed, 2021). Enhancing economic growth can reduce CO₂ emissions by prioritizing environmentally friendly growth, sustainable happiness, and economic development (Kumari et al., 2021). Individual actions can maximize cumulative happiness, such as exercising, spending time with family, and shopping (Cloutier et al., 2020).

Our findings indicate that although women have higher levels of life satisfaction and happiness, this is associated with lower levels of affective balance. However, some literature mentions a paradox in the statement "women are happier than men," as women, despite being happier, are more likely to experience anxiety or depression (Zweig, 2015). Additionally, it is possible that certain social trends, such as increased neuroticism, decreased social cohesion, and increased household risk, have a greater impact on women than on men (Meisenberg & Woodley, 2015). An individual's subjective well-being tends to increase with the number of children. This result may be related to the belief that "the more children, the greater the well-being." Individuals expect their children to take care of them when they are old. This factor might also be influenced by the age of the children. However, some studies suggest that the influence of the number of children is also determined by their age (Kohler, 2015) (Shi, 2016).

These findings indicate that married individuals have higher subjective well-being compared to other marital statuses. Joint activities, the absence of loneliness, and mutual emotional support contribute to the enhancement of individuals' subjective well-being (Ngoo et al., 2015); (Wang & Wong, 2014). We also found that urban populations have lower happiness levels compared to rural populations. The most plausible reason is that rural communities have stronger social capital bonds and easier access to natural amenities compared to urban communities (Sørensen, 2021).

We use a baseline value of 1: Very Poor for this health variable. The study results indicate that healthier individuals have higher life satisfaction and happiness, as demonstrated by their increasing coefficient values. This finding is logical because healthy individuals have the freedom to engage in activities, whereas those with health issues are more likely to experience negative feelings daily. Previous research also found that individuals with higher levels of subjective well-being generally have better health and live longer. Those with high well-being levels are more likely to engage in healthy behaviors such as exercising, quitting smoking, and reducing alcohol consumption, which are significant factors contributing to their health. Additionally, an individual's psychological health appears to impact their endocrine, immunological, and cardiovascular systems (Diener et al., 2018). Better subjective well-being and health behaviors may be associated with higher self-efficacy, linked to behavioral change interventions that enhance positive affect. Conversely, healthy behaviors have the potential to increase subjective well-being (Stenlund et al., 2022).

Satisfaction with household finances was also found to influence subjective well-being. Households that are satisfied with their finances have higher subjective well-being. These results may be related to households taking on loans or debt. Households without debt are satisfied with household finances, so they have higher subjective well-being (Brown & Gray, 2016). We used an upper-class basis for this analysis. The results show that individuals with lower social status tend to feel less satisfied and less happy compared to those with higher social status. This is because individuals with upper-class status tend to have greater autonomy, power, and control. Additionally, they are more respected in society (Anderson et al., 2012). Most research finds a positive relationship between individual/household income and happiness. Increases in household income are associated with higher life evaluations, more positive feelings, and lower levels of negative feelings. Higher income leads to greater optimism, financial happiness, and material well-being, significantly impacting subjective well-being (Diener & Tay, 2013)

The influence of TV on well-being remains debated. We found that TV increases well-being. Those who watch TV have higher life satisfaction and happiness, thereby reducing the likelihood of psychological issues such as depression (Chadi & Hoffmann, 2021). This finding could be considered in policy-making to enhance national happiness, as television is a cheap and effective instrument. This study confirms that social media is an important variable for predicting subjective well-being. This relates to social comparison theory, where an individual's happiness results from comparing themselves to others. This comparison can decrease one's subjective happiness when comparing themselves to happier individuals, as often depicted on social media (Bai et al., 2021).