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 Table of Contents  
Year : 2022  |  Volume : 5  |  Issue : 3  |  Page : 101-107

Mental stress and well-being among low-income older adults during COVID-19 pandemic

Asian Demographic Research Institute, Shanghai University, Shanghai, China

Date of Submission27-Apr-2022
Date of Decision03-Jul-2022
Date of Acceptance25-Jul-2022
Date of Web Publication9-Aug-2022

Correspondence Address:
Paolo Miguel Manalang Vicerra
No. 99 Shangda Road, Shanghai University, Shanghai 200444
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/shb.shb_110_22

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Introduction: Insecurities with food and economic resources, housing discontent, and mental stress were experienced by vulnerable populations, especially older adults, during the COVID-19 pandemic. Methods: This study examined the association of poverty based on resource scarcity with life satisfaction as an indicator of well-being during the COVID-19 outbreak in Thailand. It also tested the mediating effect of mental stress. Structural equation modeling was used to analyze data from the 2021 Survey on Housing and Support Services for Poor Older Adults which involved low-income Thais aged at least 55 years. On testing for multigroup differences, the model was applied separately to urban and rural samples. Results: Findings from the urban sample indicated that resource scarcity was associated with life satisfaction based on the direct (β = 0.686, P < 0.01), indirect (β = 0.105, P < 0.05), and total effects (β = 0.790, P < 0.001). Mental stress (β = 0.304, P < 0.05) was also associated with life satisfaction. For the rural sample, resource scarcity was associated with life satisfaction (β = 0.159, P < 0.05) only when mental stress acted as a mediator. Conclusion: This theme is important to better understand the well-being status of older people in an aging society with a developing economy. Recognizing that the physical and policy environment for urban and rural residences have an influence on the mental health and well-being of this age group can contribute to addressing their needs in times of social shocks like the COVID-19 pandemic.

Keywords: Aging, economic scarcity, low- and middle-income country, mental stress, pandemic

How to cite this article:
Vicerra PM. Mental stress and well-being among low-income older adults during COVID-19 pandemic. Asian J Soc Health Behav 2022;5:101-7

How to cite this URL:
Vicerra PM. Mental stress and well-being among low-income older adults during COVID-19 pandemic. Asian J Soc Health Behav [serial online] 2022 [cited 2023 Sep 23];5:101-7. Available from: http://www.healthandbehavior.com/text.asp?2022/5/3/101/353632

  Introduction Top

The proportion of older adults in Thailand has increased over the years. This trend is expected to continue in the future. About 19% of the total population of the country in 2020 was at least 60 years old, and this is estimated to increase to 33% in 2040.[1] Figures from the National Statistics Office[2] indicate that approximately 40% of the people in this age group have been reported to being below the poverty line in 2017. In addition, almost half of the older population continue work to earn an income,[2] whereas others receive support either from their children or through welfare programs as few were enrolled in the pension system.[3] Living in such a challenging economic situation may have an impact on mental stress and overall well-being.

Worry refers to the propensity of individuals to think and process identified threats.[4] It is a form of mental stress differentiated from anxiety, whereby worry involves cognitive processing of apparent threats, resulting in emotional difficulties. Continuous ruminations on such threats can lead to a lack of solutions which becomes disconcerting. The ineffectual contemplations on different matters, including the COVID-19 outbreak, have been linked to negative outcomes on health and well-being.[5],[6]

One indicator of well-being is life satisfaction.[7] It is the evaluation of one's life based on emotion and mood.[8] Different emotions can influence this self-evaluation, such as happiness and stress, that it can have an impact on overall health. Looking into life satisfaction among older adults is important to assess the effects of inequalities as well as policy and program outcomes.[9] To comprehend life satisfaction, individuals' backgrounds and characteristics need to be understood, particularly their economic status.

This article investigates the life satisfaction of the older population of Thailand about a year after the imposition of the first lockdown measures. As the COVID-19 pandemic continues to affect the lives of many people, the social problems become magnified, especially in terms of economic activity.[10] The current study focuses on poverty and how it may be associated with life satisfaction in the context of the pandemic. Although it has been explored in Thai society that facets of the experience of poverty during adult ages contribute to having years of good life,[7] the mechanism on how it comes about has yet to be understood with depth. In this article, a model involving resource inadequacy and household discontent was tested to find if they have a direct association with life satisfaction. Furthermore, part of the analytic model was to test if any association that would have been found was mediated by mental stress. Psychological well-being may be essential toward life satisfaction outcomes rather than having the experience of poverty by itself.

To further the analyses between poverty, mental stress, and life satisfaction, the differentiation between the experience of older persons in rural and urban locations had also been performed in this study. The respective lifestyles and general context between the two residential classifications may bring about different results, whereby urban dwellers may have increased financial needs because of higher costs of living. The conjecture is that this can further negatively affect their mental stress working toward lower life satisfaction. By doing the aforementioned analyses, the study aims to contribute to the multidimensional view of poverty and how it is possibly related to mental stress and overall well-being in the context of a low- and middle-income country during an unprecedented public health crisis.

Nonincome dimensions of poverty

Deficiency in income is usually related to the experience of poverty in the life satisfaction literature.[11],[12] Admittedly, using income level to analyze the situation of the older population may have limitations as it is possible that some members of said age group have insufficient liquid funds but have other assets that can sustain their standard of living.[13] Despite this though, it is important to recognize that poverty is multidimensional.[14] In other words, several domains can characterize poverty experience whereby it can take the form of poor nutritional status and food insecurity or lack of assets pertaining to land and housing.

From the points above, it may be assumed that the experience of poverty is reflective of unmet needs. Different groups of people, such as the older population, may have varying needs.[15] It is necessary to understand that people in advanced ages may be under different circumstances; hence, their health and social status are dissimilar to that of the younger ones. This view of poverty as deficiency on perceived needs and its relation to life satisfaction has been used in previous studies.[11],[16] Cheung and Chou,[16] for example, observed that among older adults in Hong Kong, lower life satisfaction was associated with asset-based poverty (e.g., possessing cash, stocks, and properties among others), expenditure-based poverty (e.g., spending on clothes, hired help, and travel), and material deprivation (e.g., having essential items like food and other related items).

Poverty may also be seen as a circumstantial experience; therefore, it may change depending on personal and social situations.[7] The context of location and state of homes is linked to such situations.[17] Housing-related factors have been observed to affect stress levels which can have manifestations in physical and psychological health and well-being.[17],[18] Included in these housing factors are the view of the adequacy of dwellings to suit people's needs such as maintaining personal space despite sheltering in place. These points of comfort have been viewed as essential during the COVID-19 pandemic.[19]

The high poverty incidence among the older people in Thailand leads to a precarious social standing and exposes them to vulnerabilities. As a response to the COVID-19 outbreak, lockdown and other similar measures such as physical distancing were enacted in Thailand in March 2020. Sheltering in place was a primary means of controlling the transmission of the virus, but it resulted in the loss of employment and income of people including those in the older age group. Income loss and other negative effects of the pandemic could aggravate the older population's anxiety and depression symptoms.[20] The different aspects of poverty and mental stress among the older Thai people are themes that have yet to be explored in the context of Thailand. It is important to consider these issues to have a more encompassing understanding of well-being during a health emergency situation. Ultimately, such an understanding of the social situation can contribute to social policies and programs.

  Methods Top

Data and sample

The survey used in this study was the 2021 Survey on Housing and Support Services for Poor Older Adults. Respondents were individuals from five regions of Thailand aged at least 55 years.[21] They were identified either as having earned <40,000 baht (about US$ 1330 at the time of writing) annually or beneficiaries of the cash transfer program known as the “Card of the Poor” welfare program. Information on the living condition of this age group was the goal of the survey, but data collection was done when lockdown measures were lifted around May to June 2021. In addition, COVID-19-related data were gathered. The 2139 respondents were recruited using multistage cluster and stratification sampling designs. The questions included in the said survey were formulated with guidance from experts and tested accordingly for validity and reliability.[21]

The cases where a proxy answered all the items in the survey on behalf of the respondent were excluded as they may not be reflective of the older adults' perception of their situation. The resulting analytic sample was 2025. To assess if there was a sample selectivity bias due to the exclusion criterion, the current analytic sample was compared with the total sample of the survey. There was no statistical difference found between the samples based on the distribution of key sociodemographic characteristics, particularly age, sex, residence, and education attainment.


Resource insecurity

For this latent factor, the daily essentials are some of the identified components of material deprivation in the literature.[22] A variable on food insecurity during the COVID-19 pandemic situation was based on the question asking the respondents if they had to skip a meal at any point during the pandemic. Two income perception variables were also included in measuring this latent factor. The first item inquired if the respondents had lower income during the pandemic compared with what they earned before the pandemic. The second variable was about income adequacy, where the respondents indicated whether they had sufficient (or insufficient) funds in some months or even throughout the duration of the outbreak.

Housing discontent

Another aspect of poverty is related to housing. To generate this latent factor, four perceived housing conditions were included. The respondents were asked whether they had the following issues with their domiciles: (1) house is small, (2) far from stores, (3) remote from a medical facility, and (4) unsafe environment. These items employed “yes” and “no” as response options.

Persistent worsening of life satisfaction

There were two questions to measure life satisfaction: (1) “Compared to before the first outbreak of COVID-19 (before March 2020), how has your life satisfaction change within the last month?” and (2) “Compared to the first outbreak of COVID-19 (during March–April 2020), how has your life satisfaction change within the last month?” Although there were three response options for both questions (i.e., “better,” “same,” and “worse”), this variable was treated dichotomously. That is, the responses for both items were either “worse” or otherwise.

Mental stress

This was created into a latent factor based on the four survey items where the respondents were asked if they were worried about the following instances during the current pandemic: (1) getting infected, (2) lacking in budget for medical treatment, (3) having difficulty with transportation, and (4) worsening health status. Each item was answerable with either “yes” or “no.”


Selected sociodemographic factors were included in the analysis as background factors. These covariates included age, sex, residence, employment status, and educational attainment.

Ethical consideration

The present study utilized secondary data. The Ethics Committee of the Institute for the Development of Human Resource Protection provided the approval for the conduct of the survey (COA-IHRP2020117). Neither patients nor the public were directly involved in the design, conduct, or reporting plans of the research. Verbal consent was noted during data collection such that respondents were ensured of anonymity and the purpose of the survey was shared in detail.

Statistical analysis

Structural equation modeling was used to test the conceptual path of association between the identified factors.[23] The conceptual model also aimed to analyze the direct effects of housing discontent and insufficient resources with lower well-being. Furthermore, part of the model was to test the mediating effect of mental stress on the association between poverty factors and life satisfaction. The analysis was performed primarily using the total analytic sample. Subsequently, a multiple sample analysis was tested by urban–rural residence because previous studies found residential differences in poverty, health, and well-being before and at the onset of the pandemic.[12],[24]

For the current models, the maximum likelihood estimation method was used to generate consistent estimates of parameters.[25] Before the analysis of the structural model, the measurement model was assessed for the identification of latent factors. Indicator variables for the respective latent factors had high factor loadings where all values were above 0.7 and had statistical significance such that P < 0.05.

The indices used to test goodness of fit were the standardized root mean squared residual (SRMR), root mean squared error of approximation (RMSEA), and comparative fit index (CFI). To have a good fit, the acceptable values where SRMR is <0.8; RMSEA is <0.08 and close to 0.06; and CFI is >0.9.[25] To further test for goodness of fit, the likelihood ratio test was also done for the model iterations.

  Results Top

The characteristic distribution of the total analytic sample and by urban–rural classification is presented in [Table 1]. About 59% of the sample resided in urban areas. Higher proportions of women and unemployed people were living in urban areas. The well-being of older persons in urban areas was also noticeably worse based on the responses. Around 65% of those who indicated having worse life satisfaction in the duration of the pandemic were living in urban locations compared with about 56% who were not experiencing worse life satisfaction.
Table 1: Sociodemographic characteristics and life satisfaction of the sample by residence

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The structural model using the total analytic sample is presented in [Figure 1]. It was found that resource insecurity (β = 0.43, P < 0.001) and housing discontent (β = 0.346, P < 0.001) were associated with mental stress surrounding the pandemic. In reference to the direct pathway to life satisfaction, housing discontent was observed to be lacking in association.
Figure 1: Structural model with structural coefficients of factors for explaining life satisfaction with reference to the total sample. Symbols used in the parameters signified statistical significance where ***P < 0.001, **P < 0.01, and *P < 0.05

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Resource insecurity and mental stress were the factors associated with life satisfaction based on the direct and total effects [Table 2]. Housing satisfaction was observed to have association with well-being when mediated with the mental stress factor (β = 0.106, P < 0.05).
Table 2: Standardized coefficients of direct, indirect, and total effects using the overall sample

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The model using the overall analytic sample fit the data well [Table 2]. As mentioned previously, a multi-sample analysis was performed. This was done to estimate if the structure of the relationships was maintained for different subsamples particularly. It was found that there was a difference between rural and urban samples [Table 3]. Separate analyses were then performed using the two samples. It was observed that similar to the analysis using the total sample, the mediation effects in the rural sample were significant. These findings support the association of the variables in the analytic model previously mentioned.
Table 3: Sobel estimates of mediation effect significance

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On testing the models using the urban and rural samples, the indices for model fit were observed to be appropriate [Table 4]. The likelihood ratio test yielded statistically significant results for the total sample as well as the rural and urban subsamples. The other fit indices which were the RMSEA, CFI, and SRMR, also adhered to their respective acceptable thresholds.
Table 4: Goodness-of-fit indices of the models using the total sample and group samples by residence

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The structural coefficients of the models using rural and urban samples are presented in [Table 5]. For the model referring to the rural older persons, resource insecurity was observed to have a positive association with mental stress (β = 0.45, P < 0.05). In relation to life satisfaction, mental stress is the only factor within the model which has an association based on the direct effect (β = 0.353, P < 0.05). Resource insecurity was found to have an association with life satisfaction when the mediation of mental stress is considered.
Table 5: Standardized coefficients of the direct, indirect, and total effects using the overall sample

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The model utilizing the urban sample, on the other hand, had different factor associations. Both resource insecurity and housing discontent were found to be positively associated with mental stress. Resource insecurity was also observed to be associated with life satisfaction based on the direct, indirect, and total effects. Mental stress (β = 0.304, P < 0.05) was also associated with life satisfaction.

  Discussion Top

The pandemic situation has direct (e.g., getting the disease itself) and indirect (e.g., difficulties brought about by measures to control the spread of the virus) effects on people. Although lockdown and other similar means to curb the transmission of the virus have been essential in some countries as public health interventions, they certainly led to disruptions in people's lives. It was observed in this study that the older population in Thailand was vulnerable, and the changes brought about by the COVID-19 pandemic had further magnified their precarious socioeconomic situation.

Negative displays of psychological health, such as mental stress, have been found to be related to lower quality of life and well-being.[26] In the context of the COVID-19 pandemic, the vulnerable status of people has been further exposed since the prepandemic period.[27],[28] Financial resources and health-care access have been challenging for some older Thais in recent years,[20],[29] and the present controls on physical mobility within communities have impeded their capacity to improve their situation. This subsequently formed into stress as they view their health status to be compromised.

Constraints regarding daily essentials in the present study covered food and income insufficiency. Using the perception of needs as the perspective for measuring material deprivation is important when studying a group of people based on age.[15] The risky position of older persons in Thailand was observed to have a negative effect on the symptoms of anxiety and depression at the onset of the pandemic.[20] Based on the current model of analysis, the experience of food poverty and continued insufficiency in income has affected their mental stress and life satisfaction regardless of residence. This social aspect has been noted for other countries as well.[28]

It was found that housing unhappiness was associated with mental stress only among urban older adults. However, in reference to the total older adults in the study sample, mental stress mediated the relationship between issues with dwellings and worse life satisfaction. Having poor housing conditions was among the identified health inequities that people experienced during the COVID-19 pandemic.[27] As people with lower income tend to live in smaller spaces and they lack the capacity to move to other dwellings, their stress level has increased.[19] Previous explorations on housing in Thailand reported that these aspects of challenging conditions in urban dwellings were pressing and could affect the quality of life.[30] The perception of insufficiency and discomfort is important as it can influence individuals' emotional and mental dispositions.

The observations here allude to the shortcomings in social welfare and resilience policies. The observations offered indications for low-income older adults, but it should be noted that this is a heterogeneous group still. Vulnerabilities among those counted in the said group are linked to differences in lived experiences and they may manifest dissimilarities in their reactions to social and economic shocks such as the current pandemic. This highlights the need to understand the population's heterogeneity in regard to their needs regarding health and well-being.


There are limitations to this study. First, no causation was established as it employed data from a cross-sectional survey. In addition, the items utilized to indicate constraints in daily essentials and housing dissatisfaction were created from the available information from the dataset. The operationalization of respective variables was different from those found in the literature which warrants caution in interpreting the findings.

  Conclusion Top

The present study focused on the relationship between select poverty factors, mental stress, and life satisfaction. Understanding the general relationship between the experience of facets of poverty and life satisfaction is important but that relationship may be poorly understood without considering the mechanism on how it comes to fruition. The psychological state of older persons is an often overlooked aspect of well-being, but it can impact their lives due to physical and cognitive changes that they concurrently undergo due to old age. It was found that there were dissimilarities among older adults in the urban and rural areas. Different individuals having varied characteristics such as residence, education, and income capability have respective lifestyles, and therefore, their health and well-being outcomes will be correspondingly diverse. Future studies may focus on examining these to provide a more in-depth look at the social situation of vulnerable people, specifically low-income older adults.


We thank Dr. Thananon Buathong for allowing access and use of the data for this manuscript.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

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  [Figure 1]

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]


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