Association between depression, anxiety, stress and perceived quality of life in a Malaysian B40 urban community during the COVID-19 lockdown: A cross-sectional study

Background: In Malaysia, B40 communities are those with a median monthly household earning of under RM 3166. With the prolonged COVID-19 pandemic and the resulting lockdown, the livelihoods of those in these areas has been severely impacted. This has increased their vulnerability to psychological afflictions and has led to a poorer perception of their quality of life (QoL) in comparison to the rest of the population. We investigated the association between perceived levels of depression, anxiety and stress and their impact on quality of life (QoL) among B40 residents in a low-cost urban housing area in Kuala Lumpur, Malaysia. Methods: A cross-sectional study was conducted between July 2020 and February 2021 in the Seri Pantai housing settlement. The validated Malay versions of the depression, anxiety, and stress scale-21 (DASS-21) and the World Health Organization Quality of Life, brief (WHOQOL-BREF) were distributed to the participants using Google forms. The statistical significance of the association between subscales of depression, anxiety, stress and QoL domains were assessed using the Pearson’s correlation test. Results: Of the 180 participants, the majority were Malays (87.2%) and females (82.2%). The average scores were the highest for stress (5.66 ± 4.59) and the score in the environment domain of QoL (59.27 ± 17.23) was the lowest. A statistically significant negative correlation was found between the subscales of DASS-21 and the four domains of the QoL, with the social relationships and psychological domains showing a highly significant association (p < 0.001). The strongest correlation was observed between the psychological domain and depression (r= -.520) followed by psychological domain and stress (r= -.496). Conclusion: The strongest correlation was observed between psychological domain and depression. This suggests a need to address potential devastating mental health consequences of the COVID-19 pandemic and its effect on the QoL of residents in B40 communities.


Introduction
Quality of life (QoL) is defined as an individual's perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns (World Health Organization Quality of Life [WHOQOL], 2012).This humanistic element was introduced to expand the focus of measuring health holistically beyond the norm of mortality and morbidity (WHOQOL, 1994).Globally, there are more than 150 measures available which are used to assess perceived quality of life (Gill, 1994).This includes the Short Form-36 Health Survey (Rand, 1980), The Quality-of-Life Scale (Flanagan, 1978) and EuroQoL-5D or EQ-5D (Devlin & Brooks, 2017).However, the tool used most worldwide is the WHOQOL questionnaire -the WHOQOL-100 being the original complete version and the WHOQOL-BREF assessment being the abbreviated version, which are applicable cross-culturally and translated accordingly, and include translation to the Malay language (Cheung et al., 2019;Hasanah et al., 2003;Iqbal et al., 2020).
The Department of Statistics Malaysia (DOSM, 2020) categorized the Malaysian population into T20 (top 20), M40 (middle 40) and B40 (bottom 40) according to monthly household income.B40 communities are those with monthly household earnings of under RM 4850 and a mean monthly income of RM 3166.
Perceived QoL has been shown to differ between various communities and is affected by several factors such as income stability, health status, and socioeconomic status (Bielderman et al., 2015;Cruz et al., 2011;Khan & Tahir, 2014;Shahar et al., 2019;Wan Puteh et al., 2019).Locally, a study done by Wan Puteh et al. in 2019 found that statistically significant low QoL was observed in single, male, low-income households, and in households with chronic illness.These results concurred with those reported by Cruz et al. (2011) and Skevington and McCrate (2012).
Poor mental health is associated with low perceived QoL (Bujang et al., 2015;Clavecillas & Perez, 2020;Farris et al., 2020;Gan & Hue, 2019;Tan and Yadav, 2013).Lower socioeconomic groups are two to three times more likely to suffer from mental health issues than those in higher socioeconomic groups (Kim & Cho, 2020).Meta-analysis by Lorant et al. (2003) also revealed significant evidence of the correlation between socioeconomic inequality and depression.Income inequality during rapid urbanization in Malaysia has led to the urban poor being more susceptible to mental health disorders than the others.The DASS-21 (Depression, Anxiety and Stress Scale -21 items) questionnaire has been proven to be reliable and valid in the context of Malaysians, and was used to assess the mental health of the participants in this study (Musa et al., 2007;Oei et al., 2013;Ramli et al., 2009).
The current COVID-19 lockdown has led to a substantial increase in symptoms of depression, anxiety, and stress among the general population (Farris et al., 2020;Patel et al., 2020).Income loss, social isolation, and poor physical health were shown to be factors which exacerbated mental ill-health (Pfefferbaum & North, 2020).In a study conducted midpandemic, Ali et al. (2020) assessed the QoL and levels of DAS (Depression, Anxiety, Stress) in the general population of India.Out of 847 participants, 61.9% were found to have psychological symptoms of DAS, and 36.1% were reported having poor QoL after 45 days of lockdown.
In Malaysia, Gan and Hue (2019) investigated the levels of anxiety, depression and QoL among medical students using the Hospital Anxiety and Depression Scale (HADS) and WHOQOL-BREF.Among 149 medical students, the prevalence rates of anxiety and depression were 33% and 11% respectively.Anxiety was significantly associated with lower psychological, social, and environmental scores, while depression was significantly associated with lower physical, psychological, and environmental scores.
Recently, a sample of 326 participants was recruited from several urban communities in Malaysia and participants were assigned the DASS-21 and WHOQOL-BREF (Farris et al., 2020).Similar to previous studies by Shamsuddin et al. (2013) andAziella et al. (2017), it was shown that anxiety had the highest prevalence (41.7%) among the participants.The sample was only drawn from urban communities because the authors presumed a higher prevalence of mental issues in urban settings (Farris et al., 2020).This supports Gruebner et al. (2017) who proved that in the urban population, there are higher odds of developing mood disorders (1.4-fold) and anxiety disorders (1.2 fold) than in the rural population.
The academic community has extensively explored the relationship between perceived QoL and DASS-21 (Ali et al., 2020;Clavecillas & Perez, 2020;Farris et al., 2020;Patil, 2021).However, studies on the association between DAS and QoL are still scarce in the international literature and few studies have been conducted among the B40 community in Malaysia (Bujang et al., 2015;Gan & Hue, 2019).Moreover, the study of these associations is of particular importance during the ongoing COVID-19 pandemic.Understanding the association between DAS and QoL may shed light on the need for future policies relating to the welfare of the urban poor.Thus, the aim of this research is to investigate the association between DAS and QoL in a low socioeconomic community in a developing country during the pandemic lockdown.

Study design and setting
This cross-sectional study was conducted among the inhabitants of the Seri Pantai Community Housing Program, also known as Program Perumahan Rakyat (PPR) in Kuala Lumpur, Malaysia.The PPR is a community housing project which was developed by the National Housing Department (Jabatan Perumahan Negara) in 1998 in an effort to improve the housing environment of the low income (B40) urban dwellers (Hami Erina, 2013).The low-cost, high-rise apartments of Seri Pantai PPR comprises two, 21-storey blocks with approximately 20 households per floor.

Participant recruitment and data collection
The recruitment of participants and data collection took place from July 2020 to February 2021 with the help of community leaders.These community leaders are residents of PPR Seri Pantai who are a link between the local government bodies and the PPR residents.Due to the current COVID-19 lockdown, face-to-face interviews were not possible.Hence, an online questionnaire using Google forms was designed, which was disseminated by the community leaders to all eligible participants.Eligible participants were all residents of PPR Seri Pantai aged ≥ 18 years of age, and we included all of those who were willing to participate.We employed a convenience sampling technique to include as many eligible residents as possible to participate in the survey.This was essential due to the ongoing pandemic as access to the community was not possible due to the imposed lockdown.To improve participation, the community leaders informed the community about the purpose of the survey and a convenient time for completing the data collection form was ascertained.The community leaders informed the residents about the need to read through and understand the consent form provided alongside the questionnaire.After the participant recorded their consent using a tick box, the survey form became available for them to complete.A total of 180 participants completed all elements of the survey.

Study instrument
We used the Malay version of the WHOQOL-BREF questionnaire to assess the QoL of the respondents and the DASS-21 to study the perceived depression, anxiety, and stress of the respondents.Sociodemographic data, including age, gender, race, educational level, marital status, and occupation were also recorded.

The WHOQOL-BREF questionnaire
Harper et al. (1998) has validated the 26-item WHOQOL-BREF as a reliable alternative to WHOQOL-100.The WHOQOL-BREF has been demonstrated to be suitable for assessing the perceived QoL of community-dwelling populations.It comprises 26 items, categorised into a physical domain (seven items), a psychological domain (six items), a social relations domain (three items), and an environment domain (eight items).Each item is ranked using a 5-point Likert scale.The 5-point Likert scale measures the level of agreement to a given statement.The points 1, 2, 3, 4 and 5 each corresponds to 'strongly disagree,' 'disagree,' 'neither agree nor disagree,' 'agree,' and 'strongly agree' respectively.The total scores were transformed into scores out of 100, with 0 being the least favorable QoL and 100 being the most favorable (Cruz et al., 2011;Harper et al., 1998).The questionnaire provides a brief, comprehensive, and multilingual measurement of QoL (Berwick et al., 1991).As a sizable portion of the population were more comfortable using Malay language, a validated Malay version of the multidimensional WHOQOL-BREF questionnaire was adopted (Cheung et al., 2019;Hasanah et al., 2003;Skevington et al., 2004;Iqbal et al., 2020).

The DASS-21 questionnaire
The DASS-21 is a 21-item questionnaire used in assessing the level of self-perceived depression, anxiety, and stress in participants aged 14 and above (Nordin et al., 2017).It is the shorter version of the DASS-42 questionnaire and consists of three domains: depression, anxiety, and stress.Each domain is allocated seven questions, with a Likert scale ranging from zero to three (Lovibond et al., 1995).The points on the scale indicate level of agreement to a given statement, with point 0 indicating 'never,' 1 'sometimes,' 2 'often,' and 3 'almost always.'The Malay version of this questionnaire was adequately translated with high validity and internal reliability (Ramli et al., 2009).The DASS-21 requires a shorter time to complete compared to DASS-42 and no special training is required (Musa et al., 2007;Oei et al., 2013).

Statistical analysis
The IBM Statistical Package for Social Sciences version 27.0 was used for data analysis.The qualitative variables included age, gender, ethnicity, marital status, educational level and occupation.The quantitative variables included the WHOQOL and DASS-21 scores.Both WHOQOL-BREF and DASS-21 scores were expressed as mean AE standard deviation.Pearson's correlation was used to compare the scores of the DASS-21 and WHOQOL domains.A p value ≤ 0.05 was considered statistically significant.There were no participants with missing data as all questions in the online form were compulsory.

Ethics statement
This study received Institutional Review Board approval from Taylor's University Center for Research Management (HEC 2019/058).All participants were provided with detailed information about the purpose of the study.Written informed consent was obtained from the participants before completion of the online questionnaire.The consent was obtained for participation as well as for the publication of the survey data.Information collected from participants was treated in confidence, and the anonymity of the participants was maintained throughout.

Sociodemographic characteristics
A total of 180 individuals participated in the study (see Underlying data (Patil, 2021)).The average age of respondents was 42.1 AE 11.4.The majority of the respondents were females (82.2%), more than 80% of them were Malays, 62.2% were married, 78.3% had secondary level education, and 46.1% were working (Table 1).

Summary of WHOQOL and DASS-21 scores
Table 2 shows the summary of the scores obtained in the four domains of QoL and the depression, anxiety, and stress subscales.The average scores for the four QoL domains were 66.36 AE 14.27 (physical), 66.96 AE 15.56 (psychological), 64.52 AE 20.38 (social) and 59.28 AE 17.23 (environment).The psychological domain showed the highest scores while the opposite was observed in the environment domain.The DASS-21 scores were highest for stress (5.66 AE 4.59), followed by anxiety (4.91 AE 4.35) and depression (4.66 AE 4.60).
Correlation between domains of the WHOQOL and DASS-21 scores Statistically significant negative associations were observed between all subscales of DASS-21 and all domains of QoL (Table 3) with the exception of the environment domain.The correlation between the QoL domains and DASS subscales were highly significant (p < 0.001).
As shown in Figure 1, the strongest correlation was observed between depression and the psychological domain (r = −0.520,p < 0.001) followed by stress and psychological domain (r = −0.496,p < 0.001).
The scores for depression showed a strong negative correlation in comparison with the social domain scores (r = -0.448,p < 0.001) and the scores for stress had a correlation coefficient of −0.427, p < 0.001) (Figure 2).

Discussion
Notwithstanding the lack of agreement with previous literature by Gan and Hue (2019), our results have shown that the average score for the DASS-21 was highest for the stress subscale.This is also contrasting with a study by Basudan et al.  (2017) who described a higher level of anxiety compared to depression and stress among dental students in Saudi Arabia.Baum, Garafalo & Yali (1999) found that low socioeconomic status was reliably associated with chronic stress.
The scores for the environment domain were found to be the lowest, indicating that participants felt they had inadequate physical living conditions.This differed from a similar study by Wan Puteh et al. ( 2019) where poor health status (physical health) was found to be the determinant of low QoL.However, a Malaysian study by Zainal et al. (2012) offers a possible explanation for our findings, as it presents evidence that poor housing conditions can negatively affect the quality of life of the urban poor.
There was a statistically negative association between all subscales of DASS-21 and all domains of QoL.This supports another Malaysian study by Bujang et al. (2015) which found that all psychological aspects of DASS-21 have a negative impact on the community's QoL.The highest clinical relevance was observed between the psychological domain and depression.This is expected, as meta-analysis by Lorant et al. (2003) found that those in low socioeconomic groups have a higher probability of being depressed.This resonated with findings reported by Gan and Hue (2019) where depression was significantly associated with psychological domains.
Ettman et al. (2020) reported a three-fold increase in depression prevalence during the pandemic compared to before.This could be explained by the ground-to-halt economy, restricted social activities, compromised health, sleep disturbances and disruption to normal routine (Bignardi et al., 2020;Fountoulakis et al., 2021;Gaidhane et al., 2020;Majumdar et al., 2020;Rehman et al., 2021).Furthermore, social isolation due to lockdown is another risk factor for mental health issues (Banerjee & Rai, 2020).In addition, the robust causal relationship between life's stressful events and major depressive episodes further explains the high stress scores during the pandemic lockdown (Breslau & Davis, 1986;Hammen, 2005;Tafet & Nemeroff, 2016).

Conclusions
This study found that there is a significant negative association between depression, anxiety, stress and the perceived QoL with the strongest correlation being observed between depression and the psychological domain.Clinical relevance was also found between psychological and social domains of QoL with all of the DASS-21 subscales.This warrants further investigation to determine the causation and nature of this relationship in the context of B40 communities.In addition, the scope of this study needs to be widened to cover other B40 communities in other parts of the country to understand the pattern of association between QoL and the mental health subscales.Similarities and differences in the patterns could assist in planning strategies and measures to address potential associations.Undeniably, the COVID-19 lockdown has left a significant mark on the QoL and mental health status of individuals, adding further stressors to an already disadvantaged and vulnerable population.Therefore, poor QoL and the potentially devastating mental health consequences associated with the pandemic need to be addressed.Further research will pave the way for interventions to be proposed and executed effectively, and these interventions should be replicable in all B40 communities.Vulnerable populations require particular focus so that sustainable change can be implemented to help them through this uncertain season and beyond.

Limitations
The survey could not be done face-to-face due to COVID-19 lockdown restrictions.The sample size was small and the findings cannot be generalized to all of the B40 communities in Malaysia.Additionally, due to the cross-sectional nature of our study, the causal relationship between QoL and depression, anxiety and stress could not be established.There was an unequal distribution of sociodemographic factors whereby the majority of the participants were females (more than 80%) and Malays (87.2%).Firstly, I would like to thank the authors for allowing me to review their study on the association between QoL and mental health in an underprivileged urban community in Malaysia during the period of mobility restrictions in the covid 19 pandemic.
The study provides an important insight into an underprivileged community and their lived experiences during the recent pandemic.The impact on QoL during these restrictions is of importance to provide understanding for future humanitarian crisis.The study also allows for comparisons with other ethnographic groups creating a wider perspective.This is a well-composed and structured article.The authors appear to have a creditable background and research experience which gives the article credibility.Comparisons have been made with relevant contemporary research and this allows for a global overview of the topic and how this article fits within the body of evidence.I think that the authors are correct not to generalize and to highlight the subjectivity of examining one sample within a Malaysian urban community.However, the data does provide useful insight and knowledge into the lived experience of those experiencing humanitarian challenges.
The methodology and methods are clear and would allow for the study to be replicated.Ethical approval is clearly listed as is the data collection technique used and provides transparency to the reader.
The conclusion is clear, concise and informative with recommendations that would suggest areas for future research.

Gajanan Dattatray Velhal
Community Medicine, Seth G S Medical College and KEM Hospital, Mumbai, Maharashtra, India This article has attempted to study the association between quality of life and mental health in an underprivileged urban community in Malaysia during the period of mobility restrictions imposed to curb COVID-19 transmission.
The authors have attempted to explore an extremely relevant topic in the wake of the current situation with imposed restrictions, loss of financial security, and the need to sustain and survive during a crisis that is both medical and humanitarian in nature.
Although the study has been performed only in a single B40 community, the results justify the need to conduct such studies in several such communities to assess the extent of the problem and address the emerging issues.The authors possibly could look into the causal relationship between mental health and quality of life by adopting analytical type of study design for a better insight.Is the work clearly and accurately presented and does it cite the current literature?The work has been presented in an understandable manner, the language is easy to comprehend and the literature review conforms to the requirement of being recent.

○
Is the study design appropriate and does the work have academic merit?For the given objective, the design of the study looks appropriate.The work of the authors highlights the need to address significant issue affecting health and well-being.

○
Are sufficient details of methods and analysis provided to allow replication by others?The methodology used for this study has been detailed out clearly and the analysis is aligned to the objectives.The survey instruments used have been described in adequate detail and the data collection technique has been clearly described.

○
If applicable, is the statistical analysis and its interpretation appropriate?The statistical analysis is clearly mentioned and the results reflect the performed analysis.The interpretation of the obtained results is in line with the requirements.
○ Are all the source data underlying the results available to ensure full reproducibility?Yes the source data is available.The benefits of publishing with F1000Research: Your article is published within days, with no editorial bias • You can publish traditional articles, null/negative results, case reports, data notes and more • The peer review process is transparent and collaborative • Your article is indexed in PubMed after passing peer review • Dedicated customer support at every stage • For pre-submission enquiries, contact research@f1000.com

Figure 1 .
Figure 1.Correlation between the psychological domain scores of Quality of Life and the depression, anxiety, and stress scores.

Figure 2 .
Figure 2. Correlation between the social domain scores of Quality of Life and the depression, anxiety, and stress scores.

○
Are the conclusions drawn adequately supported by the results?The conclusions are drawn in line with the observations made by the authors.The recommendations made by the authors in the context of the pandemic highlight the further research and strategies required to address the problem.○Is the work clearly and accurately presented and does it cite the current literature?YesIs the study design appropriate and is the work technically sound?YesAre sufficient details of methods and analysis provided to allow replication by others?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesAre the conclusions drawn adequately supported by the results?YesCompeting Interests: No competing interests were disclosed.Reviewer Expertise: Epidemiology, Communicable & Non communicable diseases, Nutrition, Health Planning I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.Page 13 of 14F1000Research 2021, 10:693 Last updated: 06 MAR 2024

Table 2 .
Distribution of scores of the World Health Organization Quality of Life (WHOQOL) domains and the depression, anxiety, and stress scale (DASS-21) subscales.

Table 3 .
Correlation between scores of the World Health Organization Quality of Life (WHOQOL) domains and the depression, anxiety, and stress scale (DASS-21) subscales.

the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests:
No competing interests were disclosed.

have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.
Reviewer Report 15 February 2022 https://doi.org/10.5256/f1000research.55136.r122017© 2022 Velhal G.This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.