Keywords:

Anxiety, COVID-19, Depression, Low-Income Family, Stress, Malaysia

Introduction

Malaysia is currently heading towards a developed country with high income that will attract more investors outside Malaysia. As the COVID-19 pandemic also hits Malaysia and worsens its spread globally, Malaysia is one of the countries that have been affected a lot by this current pandemic. COVID-19 or coronavirus is a newly discovered coronavirus that causes an infectious disease which results in a majority of people infected by this virus will have mild to moderate respiratory symptoms (WHO, 2019). One of the most infected sectors is Malaysia’s economic sector. The spread of the COVID-19 virus decreases labour supply and output while lockdowns, company closures, and social isolation disrupt the economy globally (Chudik, 2020). As we can see, lots of people lose their job because of this pandemic, especially citizen that has been classified in B40 which classifications are based on their household income.

B40, M40, and T20 are household groups that exist in the household income distribution structure in Malaysia. According to the Department of Statistics Malaysia (2020), B40 is a household income under RM4,360, M40 is a household income between RM4,360 to RM9,619, and T20 is a household group whose income exceeds RM9,619. While B40 group in Pahang has been classified into four groups which are B1, B2, B3, and B4, these groups are particularly vulnerable and at high risk when it comes to economic pressure in a country (Zarinah et al., 2018). Hence, the government of Malaysia has introduced economic assistance to help Malaysians, especially for the B40 household group so that they can survive during this economic turmoil such as Bantuan Prihatin Nasional (Husain, 2020).

Based on previous studies, economic instability has a positive relationship to depression (Siefert et al., 2000). This is due to individual concerns about the financial level, unemployment when being fired and the future of the family which disrupt the emotional balance among low-income families (Ladwig et al., 2001). Lower socioeconomic status is related to lower educational achievement, unemployment, and financial debt which are linked to a higher incidence of mental illness such as depression (Chang et al., 2021; Ross et al., 2020). Basically, the rate of depression, anxiety, or stress slightly higher in low socioeconomic status based on previous research (Ibrahim et al., 2019). Lockdown or movement control order has slightly given some effect to depression, anxiety, and stress rate but the recorded number of COVID-19 cases in the low-income country does not accurately represent the pandemic’s true scope (Aung et al., 2021). But generally, the COVID-19 pandemic really gives a big impact on society as mentioned in (Wang et al., 2021) high unemployment, declining household income, rising costs, and disrupted student learning were some of the negative social and economic effects. Low individual income was linked to more psychological distress in general (Chan et al., 2019). The objectives of this study were to:

a) Examine the level of depression, anxiety, and stress among B40 households in the state of Pahang, Malaysia.

b) determine the level of depression in B40 households among public, private, and self-employed workers in the state of Pahang, Malaysia.

Methods

A survey study was conducted on 128 respondents (n=128) from the state of Pahang, Malaysia which includes 11 districts. This study was also conducted online by using Google form that has two sections, Section A and Section B. Section A includes demographic data such as educational level, job scopes, households’ incomes, number of family members, lifestyles, religious practices, and family relationship while Section B is the Depression, Stress, and Anxiety Scale (DASS-21) form. The link was distributed to local leaders by using social media platforms such as Facebook, Telegram, and others. The data was distributed and collected within one month. In other to evaluate depression, anxiety, and stress level among respondents, the data was categorized into three levels, low, medium, and high. For descriptive analysis, the data was computed by looking at mean, standard deviation, and percentage. Meanwhile, for inferential analysis, one-way ANOVA was used to explore significant levels between these aspects by using Statistical Package for the Social Sciences (SPSS) version 23.

Results

Table 1 shows percentages of depression, anxiety, and stress among low-income families during COVID-19 pandemic, based on DASS-21. Firstly, the analysis showed among all respondents, 31% had moderate, and 40% had severe depression and 22% had extremely severe depression. Then, 15% had moderate, and 16% had had severe and 68 % had extremely severe anxiety. In addition, 31% had moderate, and 36% had severe stress and 18% had extremely severe stress scores based on the DASS-21 inventory. From the data, it shows that among B40 respondents had severe levels of depression and stress (40% and 36% respectively) and for anxiety; the data shows about 68% of respondents faced extremely severe.

Table 2 shows mean and standard deviation of depression among low-income family during COVID-19 pandemic, based on DASS-21. For this survey, about 30 respondents currently working for the government sector, 70 respondents are from the private sector and self-employed are 28 of the total respondents. The mean for those three sectors is 3.6, 3.7, and 4.1 respectively, standard deviation showed 0.10 for the government sector, 0.9 for the private sector, and 0.8 for self-employed. Analysis showed that self-employed respondents had experienced the highest depression compared to respondents who were employed for government and private sectors.

Table 3 shows one-way ANOVA of depression among low-income family during COVID-19 pandemic, based on DASS21. Results show that there was a significant difference effect of depression among low-income families during MCO COVID 19 at the p<0.05 level p=0.027 0.047.

Table 4 shows multiple comparisons of depression (according to working sector using Tukey Test) among low-income family during COVID-19 pandemic, based on DASS-21. The result showed that the government sector and self-employed groups differed slightly at p<0.051.

It can be concluded that depression among low-income family during the pandemic is slightly differs during the study period.

Discussion and Conclusion

From the above data, descriptive analysis shows that depression among B40 or the low-income families in Pahang State during COVID-19 pandemic was quite severe and should not be taken lightly. This is because of economic turmoil that happens during the outbreak of COVID-19 that affected around the globe and resulted in retrenchment and so on. 40% of respondents that showed the severe depression rate can increase to extremely severe or can lead to suicidal cases which usually happened to people with a high level of depression without seeking any professional help. Due to this scenario, uncertainty in economic factors for instance loss of job due to COVID-19 seems to increase in mental health issues that happen daily. Furthermore, many people seem to have a sense of anxiety because of the outbreak which can affect all regardless of age, sex, or medical history. Based on our findings, there is a significant difference in the result based on our sample by using descriptive analysis of data but when the researcher tries to analyze the data inferentially, there is no significant difference between the level of depression among B40 households’ income and employment sector. This might happen because the sample size in this study is small (N=128). Certainly, there are limitations to the study. First, the sample size in this study is too small which cannot be generalized to all. Another potential limitation is that the study was conducted within a short time. This study also measured based on the symptom of depression, anxiety, and stress only without considering the traits that the respondents might feel. Another suggestion for future studies is to focus more on intervention rather than the only survey so that the issue can be counter effectively. The prevalence of anxiety is much higher than either depression or stress, with some differences in their correlates except for age. These differences need to be further explored for the development of better intervention programs and appropriate support services targeting this group.

All in all, the baseline data collected from this study indicates that there is a crucial need to establish psychosocial support system for community in Malaysia, particularly for low-income family in the state of Pahang. As suggested by Bakar (2020), the support system to combat mental health issues like depression, anxiety, and stress during this pandemic crisis of COVID-19 shall be comprise of psychological First Aid (PFA) and effective provision of counseling services.

Acknowledgement

The authors are grateful to both the Faculty of Islamic Studies, KUIPSAS and Faculty of Education, UKM for funding the publishing process of the manuscript via internal research grants (Codes: RUG-KUIPSAS-2020-08 and GG-2020-023).

References

1. Chudik, K.M.M.H.P.M.R.A.R. (2020). Economic consequences of Covid-19: A multi-country analysis VOX. CEPR Policy Portal. 19 October 2020. https://voxeu.org/article/economic-consequences-covid-19-multi-country-analysis
2. Aung, M.N., Koyanagi, Y., & Yuasa, M. (2021). Health inequality among different economies during early phase of COVID-19 pandemic. The Journal of the Egyptian Public Health Association, 96(1), 3. https://doi.org/10.1186/s42506-021-00067-0
3. Bakar, A.Y.A. (2020). Psychosocial support for healthcare frontliners during COVID-19 pandemic in Malaysia. Asian Journal of Psychiatry, 54, 102272.
4. Chan, C.M.H., Wong, J.E., Yeap, L.L.L., Wee, L.H., Jamil, N.A., & Nantha, S.Y. (2019). Workplace bullying and psychological distress of employees across socioeconomic strata: A cross-sectional study. BMC Public Health, 19(Suppl 4), 1–8. https://doi.org/10.1186/s12889-019-6859-1
5. Chang, M.W., Brown, R., & Wegener, D.T. (2021). Perceived stress linking psychosocial factors and depressive symptoms in low-income mothers. BMC Public Health, 21(1), 1–11. https://doi.org/10.1186/s12889-020-10118-4
6. Husain, N.H. (2020, November 10). The ACA benefits 8.1 million people. https://www.sinarharian.com.my/article/109455/BERITA/Nasional/BPR-beri-manfaat-kepada-81-juta-rakyat
7. Ibrahim, N., Amit, N., Shahar, S., Wee, L.H., Ismail, R., Khairuddin, R., Siau, C.S., & Safien, A.M. (2019). Do depression literacy, mental illness beliefs and stigma influence mental health help-seeking attitude? A cross-sectional study of secondary school and university students from B40 households in Malaysia. BMC Public Health, 19(Suppl 4), 1–8. https://doi.org/10.1186/s12889-019-6862-6
8. Department of Statistics. (2020). Household income and expenditure m40 and b40 by state. 40–43.
9. Ladwig, K.H., Mittag, M.B., Erazo, N., & Gündel, H. (2001). Identifying somatization disorder in a population-based health examination survey: Psychosocial burden and gender differences. Psychosomatics, 42(6), 511–518. https://doi.org/10.1176/appi.psy.42.6.511
10. Ross, S.G., Bruggeman, B., Maldonado, M., & Deiling, M. (2020). Examining personal, perceived, treatment, and self-stigma in college students: The role of parent beliefs and mental health literacy. Journal of College Student Psychotherapy, 34(3), 183–197. https://doi.org/10.1080/87568225.2019.1580657
11. Siefert, K., Bowman, P.J., Heflin, C.M., Danziger, S., & Williams, D.R. (2000). Social and environmental predictors of maternal depression in current and recent welfare recipients. American Journal of Orthopsychiatry, 70(4), 510–522. https://doi.org/10.1037/h0087688
12. Wang, H., Zhang, M., Li, R., Zhong, O., Johnstone, H., Zhou, H., … & Rozelle, S. (2021). Tracking the effects of COVID-19 in rural China over time. International Journal for Equity in Health, 20(1), 1–13. https://doi.org/10.1186/s12939-020-01369-z
13. WHO. (2019). Coronavirus. https://www.who.int/health-topics/coronavirus#tab=tab_1
14. Zarinah, A., Syuhada, F.P., & Zanariah, I. (2018). Family B40: Pressure and strength. Journal of Advanced Research in Social and Behavioral Sciences, 10(1), 91–102.