key: cord-1009436-9w8jgiev authors: Lee, Dohyun; Paul, Christopher; Pilkington, William; Mulrooney, Timothy; Diggs, Nicole; Kumar, Deepak title: Examining the Effects of Social Determinants of Health on COVID-19 Related Stress, Family's Stress and Discord, and Personal Diagnosis of COVID-19 date: 2021-06-16 journal: J Affect Disord Rep DOI: 10.1016/j.jadr.2021.100183 sha: 18ff2f50a28fc586f0fc8295ba280cd58e215592 doc_id: 1009436 cord_uid: 9w8jgiev BACKGROUND: COVID-19 is a significant threat to people's mental health and social well-being. The research examined the effects of social determinants of health on COVID-19 related stress, family's stress and discord, and personal diagnosis of COVID-19. METHODS: In November 2020, the data collection was conducted from 97 counties in North Carolina (N = 1500). Adult residents in North Carolina completed an online COVID-19 impact survey conducted using quota-based sampling on race, income, and county to provide a rapid quasi-representative assessment of COVID impact. The study investigated the variables in a structural model through structural equation modeling. For data analysis, IBM SPSS and AMOS were deployed. RESULTS: Social determinants of health had direct effects on COVID-19 related stress (β = .66, p < .001, r2 = .43), family's stress and discord (β = .73, p < .001, r2 = .53), and personal diagnosis of COVID-19 (β = .52, p < .001, r2 = .27). These findings indicate that underserved populations experienced higher stress and discord at both individual and family levels and more severe COVID-19 symptoms. Moreover, black participants, whose family income and food access declined significantly more, had worse stress, discord, and COVID-19 symptoms than white participants. CONCLUSIONS: The study suggests that the government and health professionals enhance mental health and family support service accessibility for underprivileged populations through telehealth and community health programs to prevent associated social and health issues such as suicide, violence, and cancer. The COVID-19 pandemic impacted the United States of America epidemiologically and socially, with about 29 million coronavirus-positive cases and 522,000 deaths (Centers for Disease Control and Prevention -CDC, 2021b). North Carolina had the top-ten highest total number of COVID-19 positive cases in the United States (CDC, 2021a) . The pandemic is a critical threat to public health and restricts food accessibility, health service access, educational opportunities, health equality, and local business chances (Gao et al., 2020) , which can increase people's stress and discord (Cullen et al., 2020; Pfefferbaum & North, 2020) . The COVID-19 pandemic has an extensive impact on people socially and mentally, and the investigation of COVID-19 and mental health variables with a socialecological model (CDC, 2020a) is necessary. Responding to the COVID-19 crisis, the present study investigated symptoms, stress, and discord with a social-ecological model, the social determinants of health approach (CDC, 2020a; CDC, 2020b) . The benefits of researching COVID-19 with social determinants of health were thoroughly discussed regarding health disparities in academia (Singu et al., 2020) . Many researchers claimed that scientific studies of health disparities with social determinants of health in are in demand (Burström & Tao, 2020; Gray et al., 2020) . Social determinants of health are conditions that individuals operate their daily lives and affect health outcomes and risks (CDC, 2020a; CDC, 2020b; Marmot, 2005 ; Office of Disease Prevention and Health Promotion, 2020; WHO, 2020). Social determinants of health include the areas of healthcare access & quality, social & community context (e.g., social support, civic participation, incarceration), neighborhood & built environment (e.g., food availability), economic stability, and education access & quality. More specifically, the present research investigated the effects of social determinants of health on COVID-19 related stress, family's stress and discord, and personal diagnosis of COVID-19 under the coronavirus pandemic to evaluate the pandemic's mental and social impact. As social determinants of health are defined as social factors affecting health outcomes and risks as mentioned above, the current study set directional paths from social determinants of health to the other health outcome variables, which are COVID-19 related stress, family's stress and discord, and personal diagnosis of COVID-19 (i.e., the severity of COVID-19 symptoms). Moreover, the study compared the results in different races to see how the results varied based on race. To examine the relationships, the study developed three research hypotheses below. An online survey was conducted using quota-based sampling on race, income, and county in November 2020 to provide a rapid quasi-representative assessment of COVID impact (Ahn, & Norwood, 2020) . In November 2020, study participants were recruited through opt-in panels developed by the Qualtrics corporation, which recruits subjects utilizing various methods and third-party validation to confirm individuals' identity. A crosssectional study design was selected to investigate correlations among the variables of Personal Diagnosis of Family's Stress and Discord, and Social Determinants of Health. Surveys were received from 1500 respondents in 97 counties out of 100 counties in North Carolina. The sample size was sufficient for the data analysis as literature determined the minimum sample size of 100 for the chosen data analysis method, structural equation modeling (Anderson & Gerbing, 1988; Ding et al., 1995; Lee & Lim, 2013; Moon, 2013; Tabachnick et al., 2001; Tinsley & Tinsley, 1987) . Moreover, a power analysis determined the minimum sample sizes of 87 to detect effects and 700 for model structure (Free Statistics Calculator Version. 4.0 -a priori sample size for structural equation modeling). In the power analysis, the selected analysis conditions were anticipated effect size = .10, desired statistical power level = .80, the number of latent variables = 1, the number of observed variables = 8, and the probability level = .50, for the structural model in the present study. The Institutional Review Board (IRB) at the institution, with which the authors were affiliated, approved the data collection protocol. The study formulated an online survey with the Coronavirus Impact Scale (CIS), extracted from the PhenX Toolkit (Hamilton et al., 2011) , officially recognized by the National Institutes of Health. CIS includes 12 questions, and the current research deployed 11 questions without an open-ended question. The first nine questions have a Likert scale of "none", "mild", "moderate", and "severe" (score zero to three) and demonstrate examples for each answer choice. The last two questions have a Likert scale of " none", "mild", "moderate", "severe", and "extreme" (score zero to four) and show examples for each answer choice. A higher score meant a more negative change in life under the coronavirus pandemic. The CIS questions are related to individuals' negative life changes in 11 life domains. The areas include daily routines, family income, food access, medical care access, mental health treatment access, access to extended family or non-family social support, stress experiences related to COVID-19, stress and discord experiences in the family, personal diagnosis of COVID-19 (i.e., the severity of COVID-19 symptoms), the number of the immediate family diagnosed with COVID-19, and the number of extended family member(s) and/or close friends diagnosed with COVID-19. The CIS item topics were aligned with the current study's interests of personal diagnosis of COVID-19, stress, discord, and social determinants of health domains (i.e., healthcare access & quality, education access & quality, social & community context, economic stability, and neighborhood & built environment). The data cleaning included removing survey responses that had missing values of the variables (i.e., Personal Diagnosis of COVID-19, COVID-19 Related Stress, Family's Stress and Discord, Family Income, Medical Health Care Access, Mental Health Treatment Access, Social Support, and Food Access). There was no other data cleaning criterion and retained the dataset as much as possible to maintain the sample's representativeness to North Carolina. In the next step, the study utilized descriptive statistical analysis on variables by producing mean, standard deviations, and standard errors. For the descriptive statistical analysis and data cleaning, IBM Statistical Package for the Social Sciences (SPSS) 26 was used. As Social Determinants of Health was employed as a latent variable, the study needed to examine its validity through confirmatory factor analysis (CFA) before using it in the hypothesis test. Based on CDC's theoretical approach, Medical Health Care Access, Education Level, Social Support, Family Income, and Food Access were chosen as indicators for Social Determinants of Health (CDC, 2020b). However, Education Level was dismissed because the indicator showed a too low factor loading value (β = .07, p < .05); the plausible reason is that the present research measured Social Determinants of Health with CIS customized to the COVID-19, and the pandemic was a sudden crisis that had no impact on people's educational level. The analysis software was IBM Analysis of Moment Structures (AMOS) 26. The CFA model fit was examined with absolute and incremental model fit indices. The absolute fit indices were x 2 statistic, goodness of fit index (GFI > .90), adjusted goodness of fit index (AGFI > .90), root mean square residual (RMSR < .10), standardized root mean square residual (SRMR < .10), root mean square error of approximation (RMSEA < .10), and . Ideally, the convergent validity coefficient was expected to be .70 or greater, and AVE was expected to be .50 or greater. The In the data cleaning, 35 responses were removed due to missing values, and 1465 subjects were retained out of 1500 total survey responses. All participants were age 18 or older. In annual household income, 18.6% (272 individuals) answered as "less than $30,000", 25.5% (373 people) responded as "$30,000 -$60,000", and 56% (820 individuals) answered as "more than $60,000". In terms of ethnicity (multiple answers available in the survey), Regarding the respondent's Education Level, about half of the participants (49.8%) answered as college-level education, and 358 individuals (24.4%) studied beyond college. The results of descriptive statistical analyses of the variables are shown in Table 1 . and Mental Health Treatment Access (mean = .59), the average scores were close to one, which represented individuals were most likely to move their medical appointments to telehealth. Regarding Social Support (mean = 1.26), the mean score was close to one, and this demonstrated "Continued visits with social distancing and/or regular phone calls and/or televideo or social media contacts". In terms of Food Access, the means score was .77, which represented the majority of the subjects had sufficient food but experienced difficulties in going to stores and/or finding needed items. In the 801 participants (54.68%) who experienced negative life changes in their food access in the coronavirus crisis, 534 people (36.3%) said they could get enough food but had difficulty getting to stores and/or finding needed items. The Income (β = .64, p < .001), and Social Support (β = .53, p < .001). The study examined Social Determinants' direct effects on COVID-19 Related Stress, The results were compared in black and white participants; both structural models show the goodness of model fit ( The COVID-19 pandemic's adverse social impact exacerbated individuals' mental health. Studying the epidemiological phenomenon, the study examined social determinants' effects on COVID-19 related stress, family's stress and discord, and personal diagnosis of Additionally, the results of the hypothesis tests were compared between black and white participants. The results supported RH1, finding that the more negatively individuals' life changed in social determinants of health, the more stress they had about COVID-19 ( Figure 1) . In other words, underserved people who should have been more vulnerable to the pandemic's social impact had higher stress. This was also true in the result comparison between black and white participants. Regarding black populations that were more underserved than white people, their stress could be explained more (50%) (Figure 2 ) by social determinants of health than white participants' stress (44%) (Figure 3 ). To confirm that black participants were more underserved and socially vulnerable than white participants, the study conducted an independent samples t-test ( (Hébert et al., 2015) . Thus, the study recommends that the government enhances mental health service accessibility for minority populations marginalized from social and health benefits. One potential intervention can be the increased provision of free online mental-health services for underprivileged and uninsured populations as telemental health services have been demonstrated to be effective (Whaibeh et al., 2020) . Another result of the current study also supported this implication. It was found that mental health treatment access was significantly more important for black populations (Figure 2) than white populations ( Figure 3) ; Mental Health Treatment Access's factor loading value was β = .80 to Social Determinants of Health with the explanatory power of 64% in black people (Figure 2) , whereas those values were significantly smaller as 48% and β = .69 in white people ( Figure 3 ). Moreover, the data analysis results supported RH2, discovering that the more negatively individuals' life changed in social determinants of health, the more family stress and discord they had under the COVID-19 pandemic (Figure 1 ). This result demonstrates that underprivileged populations experienced more family stress and discord due to the pandemic. The finding is aligned with the result comparison between black and white participants; as described above, black populations were underserved compared to white participants according to the independent samples t-test conducted in the current study. Fifty eight percent of the variances of Family's Stress and Discord in black subjects could be explained with Social Determinants of Health (r 2 = 58, β = .75, p < .001) (Figure 2) , whereas only fifty one percent of the variances of Family's Stress and Discord in white subjects could be explained (r 2 = 51, β = .71, p < .001) (Figure 3) . The findings imply that socially underprivileged people are more exposed to stress and discord within families during the pandemic, which can result in serious social problems and anti-social behavior such as suicide, aggression, and violence (Ferguson et al., 2009; Rubenstein et al., 1998) . Therefore, for the prevention, health professionals should rapidly increase community-based health initiatives for underserved populations to better cope with stress and discord within families, especially in a national crisis like COVID-19. Furthermore, the research results supported RH3, finding that the more negatively individuals' life changed in social determinants of health, the more severe COVID-19 symptoms they were likely to have (Figure 1 ). The finding shows that socially marginalized populations were more frequently diagnosed with COVID-19 and experienced more severe COVID-19 symptoms. It can be empirical evidence for Burström and Tao's (2020) academic argument that inequalities in social determinants of health might result in differential exposure and vulnerability to COVID-19 infection and consequences. Also, the finding was supported by the result comparison between black and white participants in the current research. As explained above, black respondents were more underprivileged than white health problems such as cancer, suicide, aggression, and violence, as discussed in the previous paragraphs (Ferguson et al., 2009; Hébert et al., 2015; Rubenstein et al., 1998) . It is a vicious cycle that is currently happening in marginalized populations under the pandemic in the U.S. To circumvent this negative cycle of social and health problems, the attenuation of socioeconomic inequality and health disparities is necessary. The government and communities should increase health equity and play essential roles in enhancing the social structure for underprivileged populations' health and safety. Additionally, comparing the results of black and white subjects, there were different patterns of correlations. In both races, COVID-19 related stress and family stress and discord were positively correlated, which means the higher level of stress regarding the pandemic an individual had, the worse stress and discord the person experienced in his or her family. However, black participants' family discord and stress were negatively correlated to personal diagnosis of COVID-19 (Figure 2 ), whereas those two variables were not significantly correlated in white participants ( Figure 3 ). Also, white subjects' COVID-19 related stress and personal diagnosis of COVID-19 were negatively correlated (Figure 3 ), while those two variables were not significantly correlated in black subjects ( Figure 2 ). In other words, underserved populations' COVID-19 symptom severity interacted more with their stress and discord at family levels than at individual levels. These differences can be another research topic for future studies in terms of why those different correlation patterns of stress and discord at family and individual levels were observed in the pandemic. The study made empirical evidence that underserved populations are more mentally vulnerable to COVID-19 related stressors, which can cause a higher risk of having severe chronic illnesses. Thus, it is recommended that the government increases mental health accessibility for underprivileged people through telemental health services. Moreover, the research found a higher level of family stress and discord in underserved populations under the pandemic. Thus, health professionals need to facilitate more community-based health programs to help underprivileged people better cope with family stress and conflict. Furthermore, the study discovered that socially marginalized populations were more often diagnosed with COVID-19 and had severe coronavirus symptoms. The research suggests that structure for underserved populations' health and safety. The study selected a cross-sectional design without investigating causal relationships. Future studies can address causality among variables in longitudinal study designs with multiple waves of data collection. Second, the research utilized self-reported survey results depending upon respondents' recalls. Lastly, there was a lack of empirical studies about stress and discord in the COVID-19 pandemic. The majority of the studies were commentary, conceptual, or theoretical without abundant data collections. 10. The oval-shaped variable is a latent variable, and the rectangle-shaped variables are measured variables. e1 to e5 are measurement errors. d1 to d3 are exogenous variables that were not measured but estimated. The two-way arrows are correlations. The one-way arrows are regression relationships. All factor loading values and correlations are significant except for the correlation between COVID-19 Related Stress and Personal Diagnosis of COVID-19. 10. The oval-shaped variable is a latent variable, and the rectangle-shaped variables are measured variables. e1 to e5 are measurement errors. d1 to d3 are exogenous variables that were not measured but estimated. The two-way arrows are correlations. The one-way arrows are regression relationships. All factor loading values and correlations are significant except for the correlation between Family's Stress and Discord and Personal Diagnosis of COVID-19. Note. b = black, w = white. See section 4. Discussion for more details. Free Statistics Calculator Version 4.0. A priori sample size for structural equation models A multivariate analysis of youth violence and aggression: The influence of family, peers, depression, and media violence Mental health problems and social media exposure during COVID-19 outbreak COVID-19 and the other pandemic: populations made vulnerable by systemic inequity The PhenX Toolkit: Get the Most From Your Measures Considering the role of stress in populations of high-risk, underserved community networks program centers Kujobangjeongshik mohyungboonsekwa AMOS 20.0 [Structural equation modeling Social determinants of health inequalities Kujobangjeongshikmodelingeui yehaewa jeokyong [Basic concepts and applications of structural equation modeling Office of Disease Prevention and Health Promotion, Department of Health and Human Services Mental health and the Covid-19 pandemic Suicidal behavior in adolescents: stress and protection in different family contexts Impact of social determinants of health on the emerging COVID-19 pandemic in the United States. Frontiers in Public Health Using multivariate statistics Uses of factor analysis in counseling psychology research Telemental health in the context of a pandemic: the COVID-19 experience Social determinants of health None. There was no conflict of interest in the present study.