key: cord-0847020-20b379xf authors: Hossain, Mobarak title: COVID-19 and gender differences in mental health in low- and middle-income countries: Young working women are more vulnerable date: 2021-11-02 journal: SSM Ment Health DOI: 10.1016/j.ssmmh.2021.100039 sha: d04007bb49be8eccf5ae11e58d7462981b0082ef doc_id: 847020 cord_uid: 20b379xf This study examines gender differences in the relationship between COVID-19-triggered economic hardship and mental health complaints, defined by self-reported anxiety/depression, of young people (17–29) in four low- and middle-income countries (LMICs). To do this, we use two waves of the Young Lives (YL) phone survey. Logistic regression results show that young women, on average, were more likely to report anxiety than men in Peru and Vietnam in the first survey wave (June–July 2020). However, this disparity continued to persist in all four countries in the second wave (August–October 2020) as the pandemic prolonged. Notably, we find that young women that faced economic hardship by losing job or income were more likely to report anxiety than their male counterparts. As COVID-19 cases are skyrocketing in many LMICs while shutting down economic activities, the vulnerability of young women may likely increase. This issue requires urgent policy attention by awareness-raising campaigns, more hotline services for emergency help, social security programs for women, and available women's sexual and reproductive health services at a specific section in hospitals. Economic hardship in terms of job and income loss during COVID-19 has reached a new global high. This has resulted in deteriorating mental health in both high-and low-income countries (Porter et al., 2021a; Salameh et al., 2020; Witteveen & Velthorst, 2020) . While a global issue, research from different platforms has J o u r n a l P r e -p r o o f warned that young women in vulnerable communities in the developing world are at a greater risk of suffering from anxiety and mental stress due to rising financial hardship (Plan International, 2020; UN, 2020) . In addition to hardship, the greater mental health risk for women can be driven by, first, the possibility of increasing existing gender-based violence (Egger et al., 2021) . During the pre-pandemic era, 18 percent of ever-partnered women and girls aged 15 to 49 experienced physical and sexual violence by their partners. Helpline calls related to domestic violence have drastically increased during the pandemic in some places (UN Women, 2020a) . Women could also be totally isolated by their abusers, which may reduce hotline calls (UN Women, 2020b) . Reports also suggest a spike in online harassment of women since social distancing started (UN Women, 2020a) . Second, the burden of unpaid care may increase as women spend 3 times as many hours as men in unpaid care and domestic work while outnumbering men living in extreme poverty (UN, 2020) . Moreover, men's job loss in low-and middle-income countries (LMICs) like India increases women's care burden and violence (Agarwal, 2021) . Hence, although recent evidence suggests that men have encountered more COVID-19-induced economic hardship in some LMICs (Hossain, 2021) , it may, in turn, affect women's mental health. Third, the freedom of girls may be further curtailed in line with patriarchal norms as the pandemic pulls them out of work and educational institutions (Kola et al., 2021; Plan International, 2020; UNFPA, 2020) . Fourth, girls and young women will find it more challenging now to access sexual and reproductive services due to economic hardship and containment measures, which affect their mental health as recent evidence suggests (Basu et al., 2021) . All these factors are likely to intensify mental stress more for young women that are active in the labor market and have experienced job and/or income loss. The Despite the caution about the negative consequences of economic hardship particularly for young vulnerable women in low-income settings, there is limited research investigating this link. This study sheds light on this issue by examining two questions. First, are young women (17-29) more likely to experience anxiety than their male counterparts during the COVID-19? Second, if there are any gender differences in facing anxiety, does this differ between those that faced economic hardship and those that did not? To answer these questions, we analyze two waves 1 of Young Lives phone survey carried out during the pandemic from Ethiopia, two states of India (Andhra Pradesh [AP] and Telangana State [TS]), Peru and Vietnam. (Revathi et al., 2021) . Surveys from two different time points help understand the changes in mental health conditions during the pandemic. Mental health complaint is defined by self-reported anxiety as also used by previous research (Witteveen & Velthorst, 2020) . The selected countries are from low-and middle-income groups, categorized by the World Bank (World Bank, n.d.). Violence against women in these countries has notably increased during the pandemic (Agarwal, 2021; Gebrewahd et al., 2020; Porter et al., 2021b) , which also used to be frequently reported before COVID-19 (Bulte & Lensink, 2019; Cullen, 2020) . Women are also engaged in more unpaid household activities and informal jobs in these countries (Hossain, 2021) . As argued, because of these gender disparities and social norms, working women's mental health may have been more negatively affected due to the pandemic. This is opposite to what research finds in a high-income setting, the United States (US), that men's mental health has worsened during the pandemic (Ellison et al., 2021) , which we argue because of different gendered expectations in some high-income contexts. We use two waves of YL COVID-19 phone survey data collected between 8 June and 12 July and between week 3 in August and week 3 in October in 2020 from Ethiopia, India (AP and TS), Peru and Vietnam (Revathi et al., 2021) . YL is part of a longitudinal survey involving 12,000 young people since 2002 from these countries selected following a sentinel-site sampling design. A total of 20 sites were selected from each country with a 'pro-poor' bias including a higher proportion of poor children. However, non-poor households were also added to the sample with whom poor children's experiences could be compared. Despite having this pro-poor bias in the survey, previous YL analyses demonstrate that the wealth distribution in the data closely resembles nationally representative household surveys such as the Demographic and Health Survey (DHS) (Escobal & Flores, 2008; Kumra, 2008; Nguyen, 2008; Outes-Leon & Sanchez, 2008) . The YL COVID-19 survey includes all household members of YL cohort participants (aged 17-29 in the study sample) to observe the impact of the pandemic on them and their families. However, young people, in this study, refer to the YL participants, instead of any 'young' member in the households. This is because the dependent variable on mental health complaints in terms of anxiety was only collected from YL children. The study includes young people aged 17 to 29 that were active in the labor market partially or fully as the study mainly focuses on how economic hardship by J o u r n a l P r e -p r o o f job and wage loss affects mental health. Hence, we select participants that worked at least for an hour in the labor market during the past year from the point of the YL second wave COVID-19 survey. We acknowledge that this variable is limited to capturing how long labor market participants worked for and how many of them are full or part-time employees. The resulting observations in the first and second waves respectively include: 1,029 and 1,459 from Ethiopia, 829 and 1,759 from India, 745 and 1,401 from Peru, and 1581 and 2015 from Vietnam. 2 Mental health complaint/anxiety. We use a self-rated mental health complaint indicator about the level of anxiety among young people. Nervousness and anxiety were used in research to study the effect of economic hardship on well-being (Ahnquist & Wamala, 2011) . So was perceived mental health (Clark et al., 2019) . However, anxiety was measured differently in two waves, for which we analyze the surveys separately. To elaborate, the YL phone survey from the first wave measured anxiety asking to what extent participants are 'nervous' about the current circumstances in five Likert scales-(1) neither applies nor does not apply, (2) somewhat does not apply, (3) does not apply at all, (4) strongly applies, and (5) somewhat applies. We divide the categories into two for two reasons: (a) to align with the measure in wave two and (b) some categories have few or no observations in some countries. We code 'strongly applies' and 'somewhat applies' as 1 denoting anxiety and the first three as 0 meaning 'no anxiety' (see Table A1 in the appendix for the questionnaire). In the second wave, the questions were asked somewhat differently. Participants were given seven options to indicate their type of anxiety whether these 2. Statistical software STATA was used to carry out all the analyses. J o u r n a l P r e -p r o o f apply to them or not (Table A1 in the appendix). We code 1 when participants answered 'yes' meaning anxiety and 0 when they indicated 'no'. The seven options in the second wave were validated using the Generalized Anxiety scale and the Patient Health Questionnaire depression scale-8 (PHQ-8) (Porter et al., 2021a) . However, the question in the first wave was not clinically validated. Thus, the mental health complaint measure-specifically, anxiety-in both waves cannot be fully compared. This is the main limitation of the study, which future studies can focus on by comparing our results with other possible measures. Nonetheless, we observe a highly consistent pattern in the outcome variable when compared by gender, wealth and location of participants in both waves (see both panels in Table A2 in the appendix). Economic Hardship. As we have briefly indicated, we construct the economic hardship variable combining two indicators-whether someone lost (a) her/his job or (b) income. When either of the situations occurred to someone, we code it as 1 indicating economic hardship and 0 otherwise. However, the income loss indicator was measured slightly differently in two waves. In the first wave, income loss indicates when the participants were suspended without payment and/or faced a wage cut due to the COVID-19 crisis. In the second wave, income loss was measured by whether monthly income went down during the past month (compared to the date of survey) due to the pandemic. While the indicator is not strictly comparable in two waves it captures the same phenomenon-job and income loss. It is notable to mention that many participants in the first wave indicated either job or income loss as 'not applicable' (NA) consisting of around 29 percent in Ethiopia, 53 percent in India, 48 percent in Peru and 22 percent in Vietnam when compared with the study sample (see Table A3 in the appendix to compare with the J o u r n a l P r e -p r o o f left panel in Table A2 in the appendix). As explained in the robustness section, we run models both with and without NA and find that NA values are not biasing our findings. Wealth. 'Wealth' is a binary variable indicating whether someone is from a relatively poor or rich household. The YL team measured the variable using six proxy indicators including household possessions such as (1) the internet, a phone, radio, or television; (2) people-to-room ratio; (3) water source; (4) walls and roof quality; (5) a toilet; and (6) sanitization facilities. The variable in both waves is coded as Home Protective Environment (HEP) from COVID-19 in both datasets to indicate someone's wealth level (Scott et al., 2020) . The dataset contains this indicator as a binary measure, which the YL team derived from the HEP score. 3 Other variables used in the study include gender (female/male), urban-rural location, age, and a state dummy only for India. The lower bound of age is 17 as the legal age to work starts around this time in the selected countries. The upper age range of 29 is restricted by the dataset. Since the outcome variable is a binary variable, we fit equation 1 and run logit regression models on each country and wave separately. Our decision for crosssectional analysis is that mental health and economic hardship variables are not completely comparable in both waves, as explained. Here, (2) we add a parameter of the interaction between gender Gi and economic hardship Hi in which α is the corresponding coefficient. [ Figure 1 about here] Findings overall suggest that young women are more likely to suffer from COVID-19-related anxiety than men. As presented in Figure 1 , young women, active in the labor market, were 12.3 percentage points (p<0.001) more likely to be anxious at the first phase between June and July 2020 of the pandemic than men in Peru and 6 percentage points (p<0.05) in Vietnam after controlling for economic hardship, of the first phase in the latter two countries. These results conform to our expectation J o u r n a l P r e -p r o o f that the pandemic has had a more negative impact on young women in the labor market than men while the effect has continued and escalated in two countries. We observe that in the first phase of the pandemic, women that faced economic hardship were 19 percentage points more likely to experience anxiety than their male counterparts in Ethiopia and by 17 percentage points in Peru (p<0.05) as shown in the left panel of Figure 2 . Gender differences by hardship groups are not statistically significant in India and Vietnam. However, this picture changed in a matter of few months. As shown in the right panel of Figure 2 , between August and October, young women that faced hardship were significantly more likely to report being anxious than men in all countries after controlling for background characteristics. The differences were 17 percentage points in Ethiopia, 9 percentage points in India, 12 percentage points in Peru, and 8.2 percentage points in Vietnam. Although the gap in Peru appears to be lower compared to the first phase, as Figure 2 shows, the overall anxiety level in the country was higher at the second phase. Nonetheless, the notable factor in both panels of Figure 2 is that regardless of whether gender differences in the 'hardship' and 'no hardship' groups are significant, with a few exceptions, women were more anxious in most cases, particularly the ones that faced hardship. Besides, as the pandemic prolongs the well-being of young women also continues to be negatively affected. [ Figure 2 about here] We find mixed evidence about gender disparities by 'wealth', defined by certain household possessions. As Figure 3 illustrates, in the first phase of the J o u r n a l P r e -p r o o f pandemic, only in Peru, young women with hardship in both relatively rich and poor groups were more likely to report anxiety than men by around 15 percentage points. Besides, in the non-hardship group, poor young women were 8.12 percentage points more likely to report anxiety than men. [ Figure 3 about here] In the later phase, gender differences appeared significant in more countries. In Ethiopia, young women that faced hardship in both rich and poor groups were around 17 percentage points more likely to report anxiety. In India, unlike the first phase, relatively rich women with hardship were 11 percentage points more likely to report anxiety at the second phase. But the difference in the poor group is not statistically significant. In Peru, we also observe a similar trend to India where relatively young rich women were 13 percentage points more likely to report anxiety compared to men. Gender differences by wealth were not, however, significant in Vietnam in either of the survey waves. But as Figure 4 demonstrates, women were still slightly more likely to report anxiety in all groups in the country. [ Figure 4 about here] We run a number of robustness checks to determine that our results are not sensitive to some other alternative specifications. First, as shown in Table A2 in the appendix, in the first phase of the pandemic, the number of participants reporting economic hardship is much lower than that of the second phase. This is because many participants reported that hardship is 'not applicable' (NA) for them, which ranges from 53 percent in India to 22 percent in Vietnam when compared with the descriptive statistics including NA in Table A3 in the appendix. This indicates losing a significant number of observations. To address this potential source of bias in the J o u r n a l P r e -p r o o f first wave data, we incorporate NA in our analysis into the 'no hardship' group. As presented in Table A4 in the appendix, we find very similar results for all coefficients including overall gender differences in experiencing anxiety both in terms of effect size and significance level when compared with the results from the left panel in Table A5 in the appendix. We also see substantially similar results for gender differences by economic hardship (see Figure A1 in the appendix compared with the left panel of Figure 2 ) and the effect of gender and wealth interaction on economic hardship (see Figure A2 in the appendix compared with Figure 3 ). Additionally, we find a similar pattern when examining gender differences by urban-rural location. That is, when gender differences are significant, women's anxiety level is higher than that of men, more so in the second phase (see Figure A3 and Figure A4 in the appendix). Findings in this study suggest that women, in general, were more likely to report anxiety than men in two out of four countries between June and July 2020 but in the later phase of the COVID-19 between August and October 2020, this trend can be observed in all countries. However, we notice that women that faced economic hardship were more likely to report anxiety than their male counterparts, which was more widespread in the later phase of the pandemic. We also find that women had a higher propensity of reporting anxiety than their male counterparts in different wealth categories. These results remain similar when we add controls and in different specifications as we explain in the previous section. The results overall suggest a strong gender disparity in experiencing anxiety, particularly for young working women that faced economic hardship. The findings are J o u r n a l P r e -p r o o f alarming as the number of COVID-19 cases is sharply climbing in many LMICs, which may further worsen young women's mental health. This is because women do not get only affected by their increased financial hardship but also men's job loss. The latter in LMICs like India leads to more care burden for women, women facing job overcrowding in local areas or villages, food shortage, and domestic violence (Agarwal, 2021 education should be prioritized as part of the sustainable solution to reduce risks in similar future events. The study is not without limitations. First, the outcome variable mental health complaint or anxiety in both waves is not strictly comparable. Although the measures indicate consistency in terms of distribution across different characteristics as shown in Table A2 in the appendix, one may still argue that the state of mental health would be expected to deepen more during the second phase. In addition to data limitations, we suspect that the small difference in mental health complaints between the two waves might also be because of a limited time lapse between surveys, which is around 2-3 months. The difference could probably be bigger compared to the initial phase of the pandemic, for instance, in March 2020. Second, because of the comparability issue, we did not carry out longitudinal analysis, which future research can focus on whether continuing pandemic also prolongs anxiety and depression of young people. Third, our sample is limited to a specific age group of young people (17-29). This issue can also be addressed by investigating whether gender differences in mental health by economic hardship are also prevalent in other age groups. Fourth, our study is limited in terms of exploring mechanisms through which young women's mental health is particularly vulnerable to the pandemic. The 'why' and 'how' J o u r n a l P r e -p r o o f questions could be better addressed through a qualitative research design, which we could not incorporate in the study. The COVID-19 crisis has led to unprecedented challenges in terms of job and income loss worldwide. This has evidently led to deteriorating mental health in many countries. In this paper, we show evidence from four LMICs that anxiety and depression in terms of mental health complaints are more prevalent among women that faced economic hardship than men. Our findings contradict previous evidence from the US that men tend to suffer more from COVID-19-induced anxiety than J o u r n a l P r e -p r o o f Source. Own calculations based on Young Lives data. J o u r n a l P r e -p r o o f Livelihoods in COVID times: Gendered perils and new pathways in India Economic hardships in adulthood and mental health in Sweden. the Swedish National Public Health Survey A cross-national study of factors associated with women's perinatal mental health and wellbeing during the COVID-19 pandemic Women's empowerment and domestic abuse: Experimental evidence from Vietnam Subjective well-being in China's changing society Method matters: Underreporting of intimate partner violence in Nigeria and Rwanda The pathology of inequality: Gender and Ebola in West Africa Falling living standards during the COVID-19 crisis: Quantitative evidence from nine developing countries The impact of COVID-19 on girls and young women Impact of the COVID-19 Pandemic on anxiety and depression symptoms of young people in the Global South: evidence from a four-country cohort study The impact of COVID-19 lockdowns on physical domestic violence: Evidence from a list randomization experiment. SSM-Population Health Listening to Young Lives at Work: COVID-19 Phone Survey, First Call and Second Call Mental health outcomes of the CoViD-19 pandemic and a collapsing economy: perspectives from a developing country Constructing the "Home Environment for Protection" using Young Lives data Policy Brief: The Impact of COVID-19 on Women Gender equality in the wake of COVID-19 The impact of COVID on gender equality in the Arab region Impact of the COVID-19 Pandemic on Family Planning and Ending Gender-based Violence, Female Genital Mutilation and Child Marriage Economic hardship and mental health complaints during COVID-19 World Bank Country and Lending Groups Not being able to stop or control worrying (No, not at all / Yes Worrying too much about different things (No, not at all / Yes, even if a little bit) Trouble relaxing/ Can't relax (No, not at all / Yes, even if a little bit) Being so restless that it's hard to sit still (No, not at all / Yes Becoming easily annoyed or irritable (No, not at all / Yes, even if a little bit) Feeling afraid as if something awful might happen (No, not at all / Yes, even if a Questionnaire about anxiety in the second wave Question: In the last two weeks, have you been…?