Internalized and Externalized Mental Health Symptoms among Latinx Children:A Comparison between Rural Latinx Farmworker and Urban Latinx Low-Income Families Living in North Carolina

Internalized and Externalized Mental Health Symptoms among Latinx Children:A Comparison between Rural Latinx Farmworker and Urban Latinx Low-Income Families Living in North Carolina | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Internalized and Externalized Mental Health Symptoms among Latinx Children:A Comparison between Rural Latinx Farmworker and Urban Latinx Low-Income Families Living in North Carolina Lesley Berenson, William Nugent, Elizabeth Strand, Lisa Zottarelli, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4631688/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study examined mental health symptoms among 8-11-year-old children of Latinx farmworkers in rural North Carolina (N = 76) and urban children of Latinx parents (N = 65). All had household incomes of 200% below the poverty line. A Spanish version of the Child Behavioral Checklist (CBCL) for children aged 6–18 assessed internalized (anxious/depression) and externalized (aggression) mental health symptoms. CBCL scores obtained at baseline and subsequent follow-up evaluations approximately one year and two years after the first evaluation were analyzed with multi-level regression to determine if the CBCL outcomes changed over time. Children from farmworker families showed lower levels of anxious/depressive symptoms at baseline (mean = 50.59) than urban children (mean = 54.74), but these differences diminished with age. The mean depression score for the urban sample decreased by -1.17 points each year after the initial assessment. Both rural (mean = 44.15) and urban Latinx children (mean = 49.92) developed increased externalized aggressive symptoms over time, and rural children's aggression increased faster than urban children. The rural children showed a statistically significant increase with a mean linear rate of change of + 3.63 over time. This study contributes to the current research on how community settings may affect children's socio-emotional development, and suggests further examination into the impact of social, physical, and economic disadvantages on children's mental health. Latinx children mental health Child Behavioral Checklist (CBCL) Figures Figure 1 Figure 2 Background In the United States (US), Latinx is the largest ethnic minority group, with a population of 62.1 million in 2020, increasing from 50.5 million in 2010 [ 1 ]. One in four children in this country is Latinx [ 2 ], and fifty percent of US-born Latinx children have at least one parent living abroad in their country of origin [ 3 ]. As Latinx populations continue to grow, mental and emotional health is a pressing concern, especially since the prevalence of depressive symptoms and suicidal ideation among Latinx youth is higher than among other racial and ethnic groups [ 4 ]. Nearly seven percent of first-generation Latinx adolescents endorse depressive symptoms, and twenty-nine percent are symptomatic of anxiety [ 5 ]. Historically, Latinx have moved to the US Border States and regions with an established Latinx community and social support network. Over the past few decades, the Latinx population has expanded into non-traditional areas like North Carolina in the Southeast US and rural agricultural areas [ 6 ]. The Latinx gateway communities of the South were less prepared and receptive to welcoming immigrants than traditional gateway states, such as California and New York, where migrants integrate more easily into well-established Latinx communities [ 7 ]. Due to infrastructure limitations, low wages, discrimination, and high levels of segregation, Latinx and their children have found it challenging to integrate into emerging southeastern gateway communities within North Carolina [ 8 ]. According to the US Census Bureau, the Latinx population in North Carolina grew by 28.3% between 2010 and 2019, exceeding the national growth rate (19.6%) [ 9 ]. Among the cities in North Carolina, Winston-Salem has a 14.7% Latinx population, while Charlotte, Raleigh, and Durham, with 13%, 11.4%, and 14.2%, respectively, have similar numbers [ 10 ]. Rural areas of North Carolina have also seen a substantial increase in Latinx populations. Approximately 16–23% of the people in these rural counties are Latinx, and 56% of Latinx rural residents in North Carolina identified themselves as Mexican, and 12% as Puerto Rican. Another 21% reported being of Salvadoran, Honduran, or Guatemalan descent [ 9 ]. Latinx in North Carolina have found employment in agricultural and manufacturing jobs, such as poultry processing, and later found available work in the construction and service industries, which paid higher salaries and offered better working conditions [ 11 ]. Because of better employment opportunities in textile manufacturing, furniture manufacturing, and construction, Latinx workers moved to cities and suburbs within the Charlotte metropolitan area, Winston-Salem and the surrounding Piedmont Triad area, and the Raleigh/Durham Research Triangle [ 12 ]. Latinx children represent one-third of all children living in poverty in the US, more than double that of their non-Latinx white counterparts. Poverty impacts various factors, such as limited access to mental health and medical care, food insecurity, insufficient resources, unhealthy living conditions, overcrowded housing, and racism on an individual and community level [ 13 – 14 ]. Economic deprivation and poor living conditions adversely affect children's socioemotional functioning, diminishing parents' coping behaviors, causing emotional distress, and leading to interpersonal conflicts [ 15 ]. Socioeconomic status is a primary vulnerability for Latinx immigrant communities in the US. Ethnic minority families disproportionately represent low socioeconomic neighborhoods and communities [ 16 ]. A first-generation Latinx child's probability of suffering from poverty and having parents with low education is twice as great as second- and third-generation Latinx children [ 17 ]. Stress resulting from impoverished, disadvantaged communities contributes to mental health problems, including symptoms of depression, anxiety, aggression, and poor educational performance [ 14 , 18 – 19 ]. Understanding geographical and physical environment contexts provides better insight into children's development of mental illness. Identifying socioeconomic and external factors among racial minorities is necessary to eliminate mental health disparities [ 20 ]. Those who live in neighborhoods known for high levels of violence have lower self-esteem due to internalized negative self-perceptions [ 21 ]. Contrary to this, youth from areas with high community resources will project a positive self-image [ 22 ]. Preliminary Studies Dobbins et al. [ 23 ] present evidence of Adverse Childhood Experiences (ACEs) among rural and urban North Carolina Latinx children. Seventy-five (75) Latinx low-income rural farmworker mothers and sixty-three (63) Latinx urban mothers completed a standardized ACEs inventory by Felitti et al. [ 24 ] for their 8-year-old children. The analysis used a dichotomous measure of the absence of ACEs compared to endorsing the existence of ACEs. The results also included an itemized listing of the specific items in the inventory of ACEs for children with three or more ACEs. According to the data, 47.1% of the mothers did not report the presence of ACEs, 33.3% reported at least one ACE, 8.7% reported two ACEs, and 10.9% reported three or more. Children from urban communities were twice as likely as other immigrant families to experience ACEs. Using a logistic regression model, urban children had an increased risk of experiencing at least one adverse childhood experience (OR = 2.35, 95% CI = 1.01, 5.48) compared to rural children, indicating that ACEs were twice as prevalent among children from urban communities. Rural and urban Latinx populations in North Carolina are particularly vulnerable to mental health issues, especially since Latinx youth suffer from mental health problems at higher rates than non-Latinx youth [ 25 ]. Geographic and physical contexts may contribute to understanding mental illness in children. This study aims to identify measurable differences between Latinx children aged 8–11 from rural farmworker families and urban families working in different North Carolina settings regarding their anxiety/depression (internalized symptoms) and aggression (externalized symptoms). A second objective is to compare initial and follow-up CBCL results, at one year and again at two years, assessing whether there were changes in mental health outcomes over time. In earlier studies of this sample of children, urban children experienced more adverse childhood experiences [ 23 ] and scored lower on the WISC-V and tests of cognitive function [ 26 ] than rural children, suggesting that urban children may experience developmental delays and behavioral challenges compared to rural children. Specifically, the research questions were whether there are differences in anxious/depression symptoms and aggression symptoms between rural and urban children at the initial screening and how these symptoms change over time. Methods This analysis used data collected from Preventing Agricultural Chemical Exposure 5 (PACE 5), a community-based participatory research project in collaboration with the North Carolina Farmworkers Project (Benson, NC; https://ncfwp.org/ ) and the Wake Forest University School of Medicine, which analyzed the association between pesticide exposure and brain development among Latinx children from rural farmworker families and those from similar urban families. The Wake Forest University School of Medicine Institutional Review Board (IRB) approved the PACE 5 protocol and procedure. Participants One hundred forty-one (141) mother-child pairs participated in the PACE 5 study, including 76 children from rural families and 65 from urban families. This research examined Latinx rural farmworker families residing in eastern North Carolina, while the urban families lived near Winston-Salem in central North Carolina. Baseline data required that the children came from families with income below 200% of the federal poverty level and who self-identified as Latinx or Hispanic. The parents who lived in rural areas worked on farms with pesticide exposure. Children residing in urban areas neither had a parent who frequently used pesticides in their occupation (such as farming, landscaping, and pest control) nor had they lived near agricultural fields with pesticides in the previous three years. The study excluded children with life-threatening illnesses, neurological conditions, physical conditions, developmental disorders, or whose primary language was not English or Spanish from participation. Recruitment In collaboration with community members, the NC Farmworkers Project developed a list of Latinx families with 8-year-old children in rural counties near Benson, North Carolina. Winston-Salem recruiters and community members compiled a list of Latinx families with an 8-year-old child to collect data from an urban sample. Bilingual staff explained overall study procedures, responded to inquiries, and obtained signed informed consent from the parent and assent from the child. Mothers living with their child and familiar with the child's daily functioning completed the CBCL. Trained bilingual, native Spanish-speaking interviewers assisted parents with completing these questionnaires to reduce difficulties or frustrations and answer questions. Data Collection, Study Timing, and COVID Impact The study design initially specified administering the Child Behavioral Checklist (CBCL) assessments three times: at the beginning, one year in, and the end of the two years. Two bilingual, native-Spanish-speaking research psychologists with master’s and doctor’s level qualifications conducted these assessments in person. Recruitment and the administration of the initial CBCL pre-test occurred from March 2018 to December 2018, and the CBCL one-year post-tests took place during the one-year interval in 2019 for participants. COVID-19 restrictions delayed the administration of some post-tests, so second-year evaluations occurred from 2020–2021. During this time, all testing with participants transpired via phone calls with the bilingual research psychologist while participants received the CBCL materials left on their front porch. Research staff later retrieved the completed tests from the participants’ porches. Final testing occurred from March 2020 through December 2021. The study concluded in more than the planned timeframe of 2 years, with the timescale ranging between 2 and 3 years due to delays. Some participants had no timing delay, and the data included and accounted for those with a delay. Instrument The CBCL is the most used parental-reported instrument for assessing child and adolescent psychopathology [ 27 ]. The CBCL has well-established reliability and validity across cultures and racial and ethnic groups. The Spanish version of the CBCL demonstrates strong test-retest alpha reliabilities for the internalizing, externalizing, and total problems scales [ 28 ]. The CBCL Spanish version for children 6–18 has 112 questions that comprise seven subscales classified into three domains: externalizing, internalizing, and total problems [ 29 ]. The CBCL uses a response format based on a 3-point Likert-type scale with choices of 0 = Not true, 1 = Somewhat or Sometimes true, 2 = Very true or Often true, and fill-in-the-blank [ 28 – 29 ]. The CBCL uses a hierarchical model of two broad categories, internalizing and externalizing domains, to describe various psychological disorders. The internalizing measure includes a range of anxiety and depression symptoms categorized into three more specific scales: Anxious/Depressed, Withdrawn/Depressed, and Somatic Complaints. The externalizing measure includes two scales for Rule-breaking Behavior and Aggressive Behavior. Social difficulties, thought disturbances, and attention problems contribute to the total score [ 30 ]. Based on CBCL normative data, t-scores less than 59 indicate non-clinical symptoms, t-scores 60–64 suggest an increased risk of clinical symptoms, and t-scores 65 and above represent clinically relevant symptoms [ 31 ]. This study focused on two CBCL scales: externalized aggressive behavior and internalized anxious/depressive symptoms. Statistical analysis The child's categorical independent variable was a rural or urban residence. The dependent variables represented the internal (anxious/depressed) and external (aggression) CBCL mental health symptoms. The study examined whether there was a relationship between mental health symptoms and children's residential areas and whether urban and rural children differed in their initial CBCL scores or their rates of change in CBCL scores over time. Results The study analyzed the data using a hierarchical linear model (HLM) [ 32 ] with IBM SPSS Statistics software [ 33 ]. This study used multi-level regression to evaluate the relationships between psychological symptoms measured by the CBCL and children's residential location (urban versus rural). A multi-level regression analysis can determine whether the CBCL results between the initial assessment and follow-up evaluations changed approximately one and two years later. Given the repeated measures of the same individual, a multi-level regression analysis controls for clustering. Multi-level regression models also clarify the hierarchical data and account for variance within and between subjects. Through this method, analysis distinguishes cluster differences and enables effective observational and cluster-level data modeling [ 34 ]. Fully Unconditional Model The fully unconditional model for CBCL anxiety/depression scores, with time as an independent variable, indicated significant clustering, χ 2 (111) = 148.00, p = .011, confirming the need for a multi-level model [ 32 ]. The results also suggested heterogeneity of variance of CBCL scores over time, χ2 (110) = 404.8, p < .001. Hypothesized Model This model utilized data analysis to fit the hypothesized model as well as a level-1 model for the level-1 heterogeneous variance: Var (R) = σ 2 and log (σ 2 ) = α 0 + α 1 (TIME). The model comparison test between the hypothesized and the fully unconditional, or null, model was statistically significant, χ 2 (6) = 65.4, p < .001. These results suggest that the hypothesized model significantly reduced error relative to the null model [ 26 ]. The model for the heterogeneous variance across time was statistically significant, χ2 (1) = 9.92, p = 0.002. Table 1 shows the parameters for modeling the heterogeneous variance. Table 1 indicates that both the α0 and α1 terms were statistically significant. Comparisons of Sample Demographics of North Carolina Rural and Urban Latinx Mothers and their Children Table 2 shows the baseline family characteristics of the rural and urban Latinx populations for this study sample. Among the 76 Latinx rural children in farm-working families in PACE5, 47.4% of the mothers were married, 36.8% had a partner, 0% had never been married, and 15.8% were widowed, separated, or divorced. In the PACE5 urban sample of immigrant families, 60.0% of children lived in married families, 30.8% of mothers lived with their partners as married, 3.1% were never married, and 6.2% of mothers were widowed, separated, or divorced. Most mothers in this study were born in Mexico (78.9% rural and 72.3% urban). The difference between the rural mothers (1.3%) and the urban mothers (9.2%) from Honduras were statistically significant (p = 0.56). While all the households in rural farming communities had a family member working in agriculture, some mothers worked non-agricultural jobs. Mothers who worked in fishing, farming, or forestry constituted 48.7% of the sample. Many rural and urban mothers worked in building, grounds, and maintenance (7.9% and 9.2%), food preparation and serving (3.9% and 3.1%), personal care services (3.9% and 3.1%), production (14.5% and 13.8%, and sales and other occupations (0% and 6%) respectively. 0% of the rural mothers and 10.8% of the urban mothers identified themselves as housewives. Analysis of all the data for mothers' occupations discovered a significant difference between rural mothers and urban mothers. The most notable difference was that 18.4% of rural mothers did not work, compared to 40% of urban mothers (χ2(10) = 56.6, p < 0.001) . All the children were 8 years old at the start of this study. Rural and urban samples had similar gender distributions, with 52.6% and 52.3% male and 47.45% and 47.7% female participants for rural versus urban, respectively. An equivalent proportion of rural and urban child participants were born in the US (89.5% rural and 95.4% urban). 11.84% of the rural children were in 1st grade at the beginning of the study; 63.16% were in 2nd grade, 23.65% were in 3rd grade, and 1.32% were in 4th grade. Comparatively, 41.54% of urban children were in 2nd grade, 55.28% were in 3rd grade, and 3.08% were in 4th grade. The differences between the two groups of children attending 3rd grade (23.65% and 55.28%) were statistically significant ( p = .098) (Table 2 ). Results for CBCL Anxious/Depressed Baseline Data A final two-level HLM model describes CBCL data depression/anxiety symptoms as follows: ANX_DEP0 ti = β 00 + β 01 * URBRUR i + β 10 * TIME ti + β 11 * URBRUR i * TIME ti + r 0i + r 1i * TIME , ti + e ti These results appear in Table 2 . The mean anxious/depressed symptom score at baseline for rural children was 50.59 and 54.74 for children in urban settings, a statistically significant difference, t (110) = 18.57, p < 0.001. The CBCL does not identify clinical symptoms for t -scores less than 59. Results for CBCL Aggression Baseline Data An equivalent analysis to that described above investigated the CBCL aggression data. A final two-level HLM model describes aggressive behavior CBCL data as follows: AGGRESS0 ti = β 00 + β 01 * URBRURAL i + β 10 * TIME ti + β 11 * URBRURAL i * TIME ti + r 0i + r 1i * TIME ti + e ti The CBCL aggression baseline scores (AGGRESS) results appear in Table 3 . The mean aggression symptom score at baseline for children from rural farmworker families was 44.15, and for urban children, 49.92, a statistically significant difference, t (115) = 7.40, p < 0.001. Results for CBCL Rates of Change in Anxious/Depressed Scores over Time The mean linear rate of change per year in CBCL anxiety and depression scores for rural children (time slope in Fig. 1 ) was − .060, t (110) = -0.20, p = 0.844, resulting in a value not statistically different from 0, suggesting no change over time. The rate of decline across time was − 1.23 for urban children, which was statistically significantly faster than for rural children, t (110) = -2.27, p = 0.025. The decline of internalized symptoms for urban children also differed from that of rural children by -1.17. Figure 1 depicts a comparison between urban and rural children's anxious/depressed CBCL scores at baseline and across time. The steeper slope for urban children shows a decrease in CBCL scores across time compared to the essentially stable CBCL scores for rural children. Results for CBCL Rates of Change in Aggression Scores over Time The mean linear rate of change per year in CBCL aggression scores for rural children (time slope in Fig. 2 ) was + 3.63, t (115) = 7.40, p < .001, indicating a statistically significant increase in CBCL scores across time. The mean linear change rate per year for urban children (time slope in Table 2 ) was + 1.92, a statistically significantly lower rate of change. The difference in the rate of change in aggression scores between urban and rural children was − 1.71, t (115) = -3.50, p < .001. Thus, both groups showed significant increases in CBCL aggression scores across time, but the rural children's progression sequentially was significantly more rapid than that for urban children. Figure 2 shows the rates of change in CBCL aggression scores for urban and rural children. Discussion There is an increasing body of literature exploring the mental health of Latinx youth. However, the extent to which geographic contexts affect internalizing and externalizing symptoms has received little attention. Understanding Latinx youth's mental health needs will enable services and interventions appropriate to multiple contexts and tailored to their community's needs. This study assessed whether Latinx children aged 8–11 from rural farmworker families and urban non-farmworker families in North Carolina had measurable differences in anxious/depression (internalized symptoms) and aggression (externalized symptoms) across time. These findings suggest that urban children were more likely to experience internalized emotional problems than those from rural farmworker families. Internalized results for the rural sample remained unchanged and were not statistically significantly different. Other PACE 5 studies with a similar population of Latinx urban children reported more adverse childhood experiences [ 23 ] and lower WISC-V scores [ 26 ]. Adolescents with depression have lower full-scale, verbal, and performance IQs, lower working memory, organization ability, verbal fluency, and concentration than non-depressed adolescents [ 35 ]. Dobbins et al. (2021) found urban children are twice as likely as rural children to have at least one adverse childhood experience (ACE). Stresses from disadvantages may explain why urban children had higher baseline scores on anxious/depression CBCL scores than rural children. In addition, the results compared the initial and follow-up evaluations approximately one and two years after the first initial assessment to determine whether CBCL outcomes changed over time. The externalized, aggressive symptoms of Latinx children in rural and urban environments increased over time. Urban children's baseline aggression scores were higher than the rural children's initially. Still, the rural children's aggression scores increased more rapidly, resulting in diminished differences between the two groups two years later. Externalizing aggressive behaviors contributes to the risk of adolescent deviant behaviors like delinquency, substance use, parent-child conflict, and negative peer relationships [ 35 ]. Additionally, longitudinal studies have shown a reciprocal relationship between internalized emotional problems and externalized aggression among youth, in which aggressive behavior is likely to be accompanied by depression and anxiety and vice versa [ 35 – 37 ]. Although the results of this study cannot explain why Latinx children who live in rural and urban areas experience different ranges of mental health symptoms, evidence suggests that different environmental contexts may play a role. Poor and marginalized communities often experience differences ranging from targeted prejudice to structural racism. According to Cano et al. [ 38 ], discrimination or racism, which is uniquely experienced by minority groups, can contribute to Latinx youths' externalizing aggressive behavior. Latinx face discrimination, limiting their access to opportunities and resources. This study consists of Latinx children whose families earn less than 200% of the federal poverty level. Growing up in oppressive, impoverished, unstable, or dire living conditions can cause any child, regardless of age, to exhibit aggression. Identifying contextual factors may help inform prevention and intervention strategies for Latinx youth. Understanding the specific factors contributing to mental health issues among Latinx youth is vital to developing and implementing evidence-based and culturally appropriate mental health services [ 39 ]. To provide culturally competent care, mental health providers and healthcare workers must recognize how relationships, circumstances, stress, culture, and transitions affect Latinx children. Furthermore, public policy must consider how exposure to risk affects Latinx psychological well-being [ 40 ]. Understanding the specific factors contributing to mental health issues among Latinx youth is vital to developing and implementing evidence-based and culturally appropriate mental health services [ 41 ]. Sociopolitical history, ethnic density, public policies, and resource inaccessibility also contribute to mental illness [ 42 ]. Specifically, Latinx youth living in urban areas receive less mental health care than their peers from other ethnic and racial backgrounds and suffer from more mental health disparities as a result of low academic performance, physical and sexual abuse, adjustment difficulties, relocation due to temporary/seasonal migration, and deportation fears [ 43 ]. Despite meaningful, statistically significant changes in mental health symptoms over time, t-score thresholds for this population of children did not reach clinically significant levels. According to the immigrant paradox, even when children of immigrants face adverse conditions due to socioeconomic conditions and discrimination, they continue to succeed, remain resilient, and have protective health indicators. Nevertheless, because Latinx populations suffer from lower rates of psychiatric disorders, research and treatment interventions often overlook Latinx mental health concerns [ 44 ]. It is essential to investigate subclinical symptoms since they may develop into clinically significant symptoms over time. Future Research This descriptive analysis aims to present geographical influences on Latinx children's mental health; however, it does not distinguish the other factors that may cause or contribute to symptoms. Trauma and discrimination can also play an essential role in affecting their emotional well-being. The challenges associated with adjusting to a new country, when combined with previous stressful experiences, can lead to anxiety symptoms and other mental illnesses [ 40 – 42 ]. Migrants often experience trauma due to political unrest, forced disappearances, sexual abuse, and being witnesses to violence in their countries of origin [ 39 ]. In Latinx communities, immigration remains a particularly prominent issue because many Latinx know undocumented immigrants, and a substantial percentage know someone incarcerated or deported personally. It is important to note that children with US citizenship may lose a parent or caregiver, experience environmental or community changes, and cope with stress and trauma without adequate mental health services [ 45 ]. The risks associated with undocumented and illegal status can lead to anxiety, insecurity, trauma, and exploitation [ 46 ]. Mixed-status families with native and foreign-born family members and migration-related discrimination can also suffer from emotional distress, depression, anxiety, panic attacks, attention deficit hyperactivity disorder, conduct problems, and post-traumatic stress disorder [ 2 ]. According to recent data on healthcare disparities, where people live affect their health. Some communities have a shorter average life expectancy than those mere miles away. Generally, health disparities reflect a complex interaction between racial, economic, educational, and other factors [ 47 ]. A separate inquiry found that lower externalizing problems among youth were associated with different neighborhood SES and immigrant concentrations. Latinx children living in neighborhoods with high concentrations had a lower risk of externalizing problems, while non-Latinx youth in these neighborhoods had the opposite effect [ 46 ]. Most of the urban children in this study lived near Winston-Salem, North Carolina, in Forsyth County. Based on census data, the United Way of Forsyth County [ 48 ] found that the average household income of a child of low-income parents residing in the 27104-zip code, now in their mid-30s, is $ 45,000 per year. The average income of children in their mid-thirties who grew up in the 27105-zip code is $ 17,000. The distance between these two zip codes is just five miles. Mortality and morbidity disparities exist throughout the country, even within small areas near each other [ 49 ]. Comparing zip codes with various social determinants of health datasets could help identify whether children living in specific areas are more susceptible to disparities such as economic stability, environmental injustice, and neighborhood safety than other children within the comparison groups [ 50 ]. While the study did not examine gender differences, its evaluation could provide gender-informed cultural information. Traditional Latinx gender roles involve different social expectations for males and females and adhere to a patriarchal order [ 39 ]. Gender-specific cultural norms and behaviors influence the development of a Latinx child. In addition, gender plays a vital role in how children interact socially [ 51 ]. As a result of gender roles conflicting with mainstream American cultural norms, Latinx females may be more likely to develop depression symptoms during adolescence. Latinx cultures place importance on the family, and females must behave passively, give precedence to family needs, and sacrifice their own well-being for family unity. Latinx males traditionally adhere to strict, masculinized roles and attitudes associated with aggressive behavior and male honor [ 52 ]. Differentiating gender-cultural outcomes between rural and urban comparison groups could provide a means to moderate and define significance levels in outcomes between this study's rural and urban comparison groups. Although this longitudinal study followed this group of children for two years during middle childhood, longitudinal data through adolescence may help identify crucial times during a child's life when intervention is needed or to maximize protective safeguards. Adolescence is a pivotal developmental period marked by profound physical, cognitive, and social adjustment. Therefore, analyzing the socio-emotional factors influencing childhood development provides insight into future mental health outcomes. Limitations The current study is not without limits. Specifically, the study evaluated the mental health of Latinx youth in rural and urban environments without comparing them to the youth of other races in similar residential settings. Since only Latinx children living in specific rural and urban areas in North Carolina participated in the study, the findings might not generalize to other regions across the country. Reporting bias may have affected the results as parents may not have been aware of experiences outside their homes, such as discrimination in schools or communities. Social desirability may also be a factor, especially among rural mothers who reported sub-clinical mental health symptoms affecting their children. It is imperative to consider the unique protective and risk factors of Latinx subgroups when understanding and treating psychological distress [ 53 ]. Barragán et al. (2020) found that the Spanish language buffered psychological distress in Mexican Americans; however, this resulted in higher rates of psychological distress among Latinx people of Central and South America, Puerto Rico, and Cuba. Understanding cultural differences among Latinx subgroups, like the urban and rural comparison groups, may be helpful and contribute to understanding intragroup differences. Conclusion These findings illustrate the importance of differentiating specific mental health symptoms when studying the relationship between urban or rural influences among Latinx children. Both internalized and externalized mental health symptoms varied between these groups. Latinx children living in urban areas are more likely to suffer from internalized mental health concerns. Rural children initially presented with more externalized aggressive behavior, but both groups showed increased aggressive behavior as time progressed. Mental health care for these children must also consider challenges such as discrimination, neighborhood environments, poverty, and trauma. To fully understand possible factors affecting Latinx children's mental health, it is necessary to control for confounding factors such as age, gender, race, regional differences, and ethnicity. Further longitudinal studies of Latinx communities may provide insight into how social, physical, and economic disadvantages affect children's mental health [ 55 ]. Declarations Author Contribution We further confirm that the order of authors listed in the manuscript has been approved by all of us. We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property. We further confirm that any aspect of the work covered in this manuscript that has involved either experimental animals or human patients has been conducted with the ethical approval of all relevant bodies and that such approvals are acknowledged within the manuscript. We understand that the Corresponding Author (LB) is the sole contact for the Editorial process (including Editorial Manager and direct communications with the office). She is responsible for communicating with the other authors about progress, submissions of revisions and final approval of proofs. The authors all provided substantial contributions to the conception, design of this work, analysis, interpretation of data, drafting or critical for important intellectual content, and final approval of the version to be published. We all agreed upon accountability for all aspects of the work to ensure that questions related to the accuracy or integrity of the manuscript are appropriately investigated and resolved.LB wrote the abstract, background, methods, discussion, conclusion, and references. She also helped with revisions in the results section, Table 2, Figure 1 and Figure 2.WN wrote most of the results sections, compiled analysis, and prepared Table 1, Table 2, Table 3, Table 4, Figure 1 and Figure 2.ES provided guidance regarding how to design this study, organize the paper, proofing and editing.LZ provided guidance regarding conceptualization, design and methods, proofing and editing.The corresponding author is most appreciative to PL for his mentorship and allowing her to be a part of the PACE 5 project. He helped with analysis, multiple revisions, as well as support and guidance throughout the submission process. Acknowledgement The authors appreciate the support of their community partners, the North Carolina Farmworkers Project, and Student Action with Farmworkers. They also appreciate our community field interviewers' valuable contributions to recruiting participants and collecting data. We sincerely thank the children and parents who participated in this study. Data Availability The data sets generated during and/or analyzed during this current study are not publicly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at Wake Forest University School of Medicine (Winston-Salem, North Carolina, USA). References Krogstad JM, Noe-Bustamante L. Key facts about U.S. Latinos for National Hispanic Heritage Month. https://policycommons.net/artifacts/1426132/key-facts-about-us/2040514/ . Caballero TM, DeCamp LR, Platt RE, Shah H, Johnson SB, Sibinga EMS, et al. Addressing the mental health needs of Latino children in immigrant families. Clin Pediatr. 2017;56:648–58. Budiman A, Tamir C, Mora L, Noe-Bustamante L. Facts on U.S. immigrants, 2018 [Internet]. Pew Research Center’s Hispanic Trends Project. 2020 [cited 2023 Jan 27]. Available from: https://www.pewresearch.org/hispanic/2020/08/20/facts-on-u-s-immigrants/ . Stein GL, Gonzalez LM, Huq N. Cultural stressors and the hopelessness model of depressive symptoms in Latino adolescents. J Youth Adolesc. 2012;41:1339–49. Potochnick SR, Perreira KM. Depression and anxiety among first-generation immigrant Latino youth: key correlates and implications for future research. J Nerv Ment Dis. 2010;198:470–7. Bucay-Harari L, Page KR, Krawczyk N, Robles YP, Castillo-Salgado C. Mental health needs of an emerging Latino community. J Behav Health Serv Res. 2020;47:388–98. Kochhar R, Suro R, Tafoya S. The new Latino South: The context and consequences of rapid population growth [Internet]. Pew Research Center’s Hispanic Trends Project. 2005 [cited 2023 Feb 9]. Available from: https://www.pewresearch.org/hispanic/2005/07/26/the-new-latino-south/ . Brietzke M, Perreira K. Stress and coping: Latino youth coming of age in a new Latino destination. J Adolesc Res. 2017;32:407–32. Ordoñez E. North Carolina’s Hispanic community: 2020 snapshot [Internet]. Carolina Demography. 2021 [cited 2022 Apr 16]. Available from: https://www.ncdemography.org/2021/02/05/north-carolinas-hispanic-community-2020-snapshot/ . Chesser J. Hispanics in NC: Big numbers in small towns. Welcome to the UNC Charlotte Urban Institute. 2012. Available from: https://ui.charlotte.edu/story/hispanics-nc-big-numbers-small-towns/ . Johnson–Webb KD. Employer recruitment and Hispanic labor migration: North Carolina urban areas at the end of the millennium. Prof Geogr. 2002;54:406–21. Perreira KM. The Socio-historical contexts of exit and settlement. Southeast Geogr. 2011; 51:260–86. Crain R, Grzywacz JG, Schwantes M, Isom S, Quandt SA, Arcury TA. Correlates of mental health among Latino farmworkers in North Carolina. J Rural Health. 2012;28:277–85. Hodgkinson S, Godoy L, Beers LS, Lewin A. Improving mental health access for low-income children and families in the primary care setting. Pediatrics [Internet]. 2017;139. Available from: http://dx.doi.org/10.1542/peds.2015-1175 . Eamon MK. The effects of poverty on children’s socioemotional development: An ecological systems analysis. Soc Work. 2001; 46:256–66. Bamaca MY, Umana-Taylor AJ, Shin N, Alfaro EC. Latino adolescents’ perception of parenting behaviors and self-esteem: Examining the role of neighborhood risk. Fam Relat. 2005; 54:621–32. Ceballos PL, Bratton SC. Empowering Latino families: Effects of a culturally responsive intervention for low-income immigrant Latino parents on children’s behaviors and parental stress. Psychol Sch. 2010; 47:761–75. Santiago CD, Wadsworth ME. Family and cultural influences on low-income Latino children’s adjustment. J Clin Child Adolesc Psychol. 2011; 40:332–7. Arcury TA, Chen H, Quandt SA, Talton JW, Anderson KA, Scott RP, et al. Pesticide exposure among Latinx children: Comparison of children in rural, farmworker and urban, non-farmworker communities. Sci Total Environ. 2021; 763:144233. Singh GK, Yu SM, Kogan MD. Health, chronic conditions, and behavioral risk disparities among U.S. immigrant children and adolescents. Public Health Rep. 2013; 128:463–79. Vega WA, Ang A, Rodriguez MA, Finch BK. Neighborhood protective effects on depression in Latinos. Am J Community Psychol. 2011; 47:114–26. Behnke AO, Plunkett SW, Sands T, Bámaca-Colbert MY. The Relationship between Latino adolescents’ perceptions of discrimination, neighborhood risk, and parenting on self-esteem and depressive symptoms. J Cross Cult Psychol. 2011;42:1179–97. Dobbins DL, Berenson LM, Chen H, Quandt SA, Laurienti PJ, Arcury TA. Adverse childhood experiences among low-income, Latinx children in immigrant families: Comparison of children in rural farmworker and urban non-farmworker communities. J Immigr Minor Health. 2022;24:977–86. Felitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. Am J Prev Med. 1998;14:245–58. Ramirez AG, Gallion KJ, Aguilar R, Dembeck ES. Mental health and Latino kids: A research review. State Coverage Initiat Issue Brief. 2017. Dobbins DL, Chen H, Cepeda MJ, Berenson L, Talton JW, Anderson KA, et al. Comparing impact of pesticide exposure on cognitive abilities of Latinx children from rural farmworker and urban non-farmworker families in North Carolina. Neurotoxicol Teratol. 2022;92:107106. Achenbach TM, Rescorla LA. Manual for the ASEBA school-age forms & profiles: an integrated system of multi-informant assessment Burlington, VT: University of Vermont. Research Center for Children, Youth, & Families. Albores-Gallo L, Lara-Muñoz C, Esperón-Vargas C, Zetina JAC, Soriano AMP, Colin GV. Validity and reliability of the CBCL/6–18. Includes DSM scales. Actas Españolas de Psiquiatría. 2007;35:393–9. Haack LM, Gerdes AC, Schneider BW, Hurtado GD. Advancing our knowledge of ADHD in Latino children: psychometric and cultural properties of Spanish-versions of parental/family functioning measures. J Abnorm Child Psychol. 2011;39:33–43. Magyar CI, Pandolfi V. Utility of the CBCL DSM-oriented scales in assessing emotional disorders in youth with autism. Res Autism Spectr Disord. 2017;37:11–20. Guerrera S, Menghini D, Napoli E, Di Vara S, Valeri G, Vicari S. Assessment of psychopathological comorbidities in children and adolescents with autism spectrum disorder using the Child Behavior Checklist. Front Psychiatry. 2019;10:535. Kim TK, Solomon P, Zurlo KA. Applying Hierarchical Linear Modeling (HLM) to social work administration research. Adm Soc Work. 2009;33:262–77. IBM Corp. IBM SPSS statistics software for Windows [Internet]. Armonk, NY: IBM Corp; 2021 [cited 2024 May 18]. Available from: https://www.ibm.com/products/spss-statistics . David Garson G. Multilevel modeling: Applications in STATA®, IBM® SPSS®, SAS®, R, & HLMTM. SAGE Publications; 2019. Smokowski PR, Guo S, Evans CBR, Wu Q, Rose RA, Bacallao M, et al. Risk and protective factors across multiple microsystems associated with internalizing symptoms and aggressive behavior in rural adolescents: Modeling longitudinal trajectories from the Rural Adaptation Project. Am J Orthopsychiatry. 2017;87:94–108. McLaughlin KA, Aldao A, Wisco BE, Hilt LM. Rumination as a transdiagnostic factor underlying transitions between internalizing symptoms and aggressive behavior in early adolescents. J Abnorm Psychol. 2014;123:13–23. Zeman J, Shipman K, Suveg C. Anger and sadness regulation: Predictions to internalizing and externalizing symptoms in children. J Clin Child Adolesc Psychol. 2002;31:393–8. Cano MÁ, Schwartz SJ, Castillo LG, Romero AJ, Huang S, Lorenzo-Blanco EI, et al. Depressive symptoms and externalizing behaviors among Hispanic immigrant adolescents: Examining longitudinal effects of cultural stress. J Adolesc. 2015;42:31–9. Lawton KE, Gerdes AC. Acculturation and Latino adolescent mental health: integration of individual, environmental, and family influences. Clin Child Fam Psychol Rev. 2014;17:385–98. Chapman MV, Perreira KM. The well-being of immigrant Latino youth: A framework to inform practice. Fam Soc. 2005;86:104–11. Ko LK, Perreira KM. “It turned my world upside down”: Latino youths’ perspectives on immigration. J Adolesc Res. 2010;25:465–93. Das-Munshi J, Becares L, Dewey ME, Stansfeld SA, Prince MJ. Understanding the effect of ethnic density on mental health: multi-level investigation of survey data from England. BMJ. 2010;341:c5367. Villalba JA. Health disparities among Latina/o adolescents in urban and rural schools: educators’ perspectives. J Cult Divers. 2007;14:169–75. Alegría M, Canino G, Shrout PE, Woo M, Duan N, Vila D, et al. Prevalence of mental illness in immigrant and non-immigrant U.S. Latino groups. Am J Psychiatry. 2008;165:359–69. Vargas ED, Juárez M, Sanchez GR, Livaudais M. Latinos’ connections to immigrants: How knowing a deportee impacts Latino health. J Ethn Migr Stud. 2019;45:2971–88. Ornelas IJ, Yamanis TJ, Ruiz RA. The health of undocumented Latinx immigrants: What we know and future directions. Annu Rev Public Health. 2020;41:289–308. Graham GN. Why your ZIP Code matters more than your genetic code: Promoting healthy outcomes from mother to child. Breastfeed Med. 2016;11:396–7. Our initiatives [Internet]. United Way Forsyth. 2022. [cited 2023 Jan 30]. Available from: https://www.forsythunitedway.org/our-initiatives/ . National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Population Health and Public Health Practice, Committee on Community-Based Solutions to Promote Health Equity, Baciu A, Negussie Y, et al. The root causes of health inequity. National Academies Press (US); 2017. Social Determinants of Health (SDOH) and PLACES data. 2022 [Internet]. 2023 [cited 2023 Jan 31]. Available from: https://www.cdc.gov/places/social-determinants-of-health-and-places-data/index.html . Perreira K, Smith LO. A cultural-ecological model of migration and development: Focusing on Latino immigrant youth. Prev Res. 2007;14:6–9. McLaughlin KA, Hilt LM, Nolen-Hoeksema S. Racial/ethnic differences in internalizing and externalizing symptoms in adolescents. J Abnorm Child Psychol. 2007;35:801–16. Kim SY, Schwartz SJ, Perreira KM, Juang LP. Culture’s influence on stressors, parental socialization, and developmental processes in the mental health of children of immigrants. Annu Rev Clin Psychol. 2018;14:343–70. Barragán A, Yamada A-M, Gilreath TD, Lizano EL. Protective and risk factors associated with comorbid mental health disorders and psychological distress among Latinx subgroups. J Hum Behav Soc Environ. 2020;30:635–48. Rosen LD, Imus D. Environmental injustice: Children’s health disparities and the role of the environment. EXPLORE. 2007;3:524–8. Tables Table 1 Model for Level 1 Variance over Time Parameter Coefficient Standard Error Z -ratio p -value INTRCPT1, α 0 2.88 0.197459 14.59 < 0.000 TIME, α 1 -0.34 0.163490 -2.09 0.036 *These findings show that both the α0 and α1 terms were statistically significant. Table 2 Comparison of Rural and Urban North Carolina Latinx Mothers and their Children Demographics Variable Rural Urban Chi-square p-value χ 2 (3) = 6.64 p = 0.08 Marital status Living as married 36.8% 30.8% Married 47.4% 60.0% Never married 0% 3.1% Widowed/separated/divorced 15.8% 6.2% χ 2 (1) = 0.34 p = 0.56 Sex of child Male 52.6% 52.3% Female 47.4% 47.7% Child’s grade level χ 2 (6) = 10.702 p = .098 1st grade 11.84% 0% 2nd grade 63.16% 41.54% 3rd grade 23.68% * 55.38% * 4th grade 1.32% 3.08% Child's birth country χ 2 (3) = 2.05 p = 0.56 Guatemala 1.3% 0% Mexico 6.6% 3.1% Other 2.6% 1.5% United States 89.5% 95.4% Mother's birth country χ 2 (4) = 5.4 p = 0.25 Guatemala 5.3% 4.6% Honduras 1.3% * 9.2% * Mexico 78.9% 72.3% Other 9.2% 6.2% United States 5.3% 7.7% Mother's occupation χ 2 (10) = 56.6 p < 0.001 Building, grounds, or maintenance 7.9% 9.2% Construction & Extraction 0% 1.5% Does not work 18.4% * 40.0% * Fishing, farming, and/or forestry 48.7% 0% Food preparation and serving 3.9% 3.1% Healthcare support 1.3% 3.1% Housewife 0% * 10.8% * Office & Administration 1.3% 9.2% Personal care and services 3.9% 3.1% Production 14.5% 13.8% Sales & Related 0% * 6.2% * *Column differences are statistically significant Table 3 HLM Results for CBCL Anxious/Depression (ANX-DEPO) final estimation of fixed effects. Coefficient Standard Error t -ratio Approximate d. f. p-value For INTERCEPT Rural children 50.59 0.43 18.57 110 < 0.001 Urban children 4.15 0.75 5.52 110 < 0.001 For TIME slope Rural children -0.06 0.29 0.197 110 0.844 Urban children -1.17 0.52 -2.27 110 0.025 Table 4 HLM Results for CBCL Aggression (AGGRESS) final estimation of fixed effects. Fixed Effect Coefficient Standard Error t -ratio Approximate d. f. p -value For INTERCEPT Rural children 44.14 0.65 7.40 115 < 0.001 Urban children 5.76 1.04 5.52 115 < 0.001 For TIME slope Rural children 3.63 0.30 1.79 115 < 0.001 Urban children -1.71 0.49 -3.50 115 < 0.001 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4631688","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":331392936,"identity":"0be65bd9-6e9e-465d-af50-a58f305c1681","order_by":0,"name":"Lesley Berenson","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIie3NvQrCMBDA8YRAJrVrpaKv0BJw8etVLAFdCg6CYxGEmyyuFl9CEMSxEqhLcRYcFFwdFBc7FC2ii9iim0P+0+W4H0FIJvvDcupzUBAiCPfjDcrET5pM6Ivk+09C6bdE974m2sA/nRd2kW34QT8vqiVacjx06olkUvC56waClTctZrpBywCaa+LxOoWoFiNZ8Mz5tslEFgQGmtHjTRrpXEgEtjmbtC8iglvjQaJUYhGCgZhTzWIcx989CE4jBZ9hBwRTd8eu4QDnQC19OVy3E4miDQ4oBLuoDFczNYR6bUQCY3/tVRLJ57wf72UymUz21h3KtlDcHkW1RwAAAABJRU5ErkJggg==","orcid":"","institution":"Wake Forest University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Lesley","middleName":"","lastName":"Berenson","suffix":""},{"id":331392937,"identity":"e0878df8-4fec-4f77-8ef7-553f226bfcba","order_by":1,"name":"William Nugent","email":"","orcid":"","institution":"University of Tennessee at Knoxville","correspondingAuthor":false,"prefix":"","firstName":"William","middleName":"","lastName":"Nugent","suffix":""},{"id":331392938,"identity":"9756c98d-161c-4d9a-a9b3-856c537f2694","order_by":2,"name":"Elizabeth Strand","email":"","orcid":"","institution":"University of Tennessee at Knoxville","correspondingAuthor":false,"prefix":"","firstName":"Elizabeth","middleName":"","lastName":"Strand","suffix":""},{"id":331392939,"identity":"55f41094-b9f0-4189-a0e9-3fd066fcf119","order_by":3,"name":"Lisa Zottarelli","email":"","orcid":"","institution":"University of Tennessee at Knoxville","correspondingAuthor":false,"prefix":"","firstName":"Lisa","middleName":"","lastName":"Zottarelli","suffix":""},{"id":331392940,"identity":"de3d3c75-b1ff-4e84-bb8b-d7642c81f5bf","order_by":4,"name":"Paul Laurienti","email":"","orcid":"","institution":"Wake Forest University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"","lastName":"Laurienti","suffix":""}],"badges":[],"createdAt":"2024-06-24 17:14:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4631688/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4631688/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61178998,"identity":"88cd9e6b-9c15-49e4-8e6e-3c5f839ebf3a","added_by":"auto","created_at":"2024-07-26 16:06:05","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":24087,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eResults of CBCL Anxious/Depressed Scores over Time\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis figure shows the differences in anxious/depressed CBCL scores for rural (dashed line) and urban (solid line) at baseline (year 1) and how their scores changed over time. This difference in slopes between the urban and rural samples was statistically significant. The slope of anxious/depressed symptoms for the rural sample was statistically non-significant and remained essentially unchanged.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4631688/v1/059b2de54fd667c35dba13c4.png"},{"id":61178304,"identity":"621c6c9f-5228-4ff2-b538-58b9bb67ee76","added_by":"auto","created_at":"2024-07-26 15:58:05","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":32683,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eResults for CBCL Aggression Scores over Time\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis figure shows the differences in CBCL aggression scores for rural children (dashed line) and urban children (solid line) at baseline (year 1) and across time. The difference between slopes in this figure was statistically significant. The urban children's CBCL scores increased statistically significantly more than rural children's, with differences between the two groups diminishing as time progressed.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4631688/v1/90fe02b41d59abb49f964f96.png"},{"id":64405602,"identity":"e209d7bc-5f54-46a8-8a9d-6a41505421a5","added_by":"auto","created_at":"2024-09-12 17:16:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":855976,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4631688/v1/08695ecc-e732-4314-bac5-75cfe7fbc5e0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Internalized and Externalized Mental Health Symptoms among Latinx Children:A Comparison between Rural Latinx Farmworker and Urban Latinx Low-Income Families Living in North Carolina","fulltext":[{"header":"Background","content":"\u003cp\u003eIn the United States (US), Latinx is the largest ethnic minority group, with a population of 62.1\u0026nbsp;million in 2020, increasing from 50.5\u0026nbsp;million in 2010 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. One in four children in this country is Latinx [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], and fifty percent of US-born Latinx children have at least one parent living abroad in their country of origin [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. As Latinx populations continue to grow, mental and emotional health is a pressing concern, especially since the prevalence of depressive symptoms and suicidal ideation among Latinx youth is higher than among other racial and ethnic groups [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Nearly seven percent of first-generation Latinx adolescents endorse depressive symptoms, and twenty-nine percent are symptomatic of anxiety [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHistorically, Latinx have moved to the US Border States and regions with an established Latinx community and social support network. Over the past few decades, the Latinx population has expanded into non-traditional areas like North Carolina in the Southeast US and rural agricultural areas [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The Latinx gateway communities of the South were less prepared and receptive to welcoming immigrants than traditional gateway states, such as California and New York, where migrants integrate more easily into well-established Latinx communities [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Due to infrastructure limitations, low wages, discrimination, and high levels of segregation, Latinx and their children have found it challenging to integrate into emerging southeastern gateway communities within North Carolina [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to the US Census Bureau, the Latinx population in North Carolina grew by 28.3% between 2010 and 2019, exceeding the national growth rate (19.6%) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Among the cities in North Carolina, Winston-Salem has a 14.7% Latinx population, while Charlotte, Raleigh, and Durham, with 13%, 11.4%, and 14.2%, respectively, have similar numbers [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Rural areas of North Carolina have also seen a substantial increase in Latinx populations. Approximately 16\u0026ndash;23% of the people in these rural counties are Latinx, and 56% of Latinx rural residents in North Carolina identified themselves as Mexican, and 12% as Puerto Rican. Another 21% reported being of Salvadoran, Honduran, or Guatemalan descent [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Latinx in North Carolina have found employment in agricultural and manufacturing jobs, such as poultry processing, and later found available work in the construction and service industries, which paid higher salaries and offered better working conditions [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Because of better employment opportunities in textile manufacturing, furniture manufacturing, and construction, Latinx workers moved to cities and suburbs within the Charlotte metropolitan area, Winston-Salem and the surrounding Piedmont Triad area, and the Raleigh/Durham Research Triangle [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLatinx children represent one-third of all children living in poverty in the US, more than double that of their non-Latinx white counterparts. Poverty impacts various factors, such as limited access to mental health and medical care, food insecurity, insufficient resources, unhealthy living conditions, overcrowded housing, and racism on an individual and community level [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Economic deprivation and poor living conditions adversely affect children's socioemotional functioning, diminishing parents' coping behaviors, causing emotional distress, and leading to interpersonal conflicts [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Socioeconomic status is a primary vulnerability for Latinx immigrant communities in the US. Ethnic minority families disproportionately represent low socioeconomic neighborhoods and communities [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A first-generation Latinx child's probability of suffering from poverty and having parents with low education is twice as great as second- and third-generation Latinx children [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Stress resulting from impoverished, disadvantaged communities contributes to mental health problems, including symptoms of depression, anxiety, aggression, and poor educational performance [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUnderstanding geographical and physical environment contexts provides better insight into children's development of mental illness. Identifying socioeconomic and external factors among racial minorities is necessary to eliminate mental health disparities [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Those who live in neighborhoods known for high levels of violence have lower self-esteem due to internalized negative self-perceptions [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Contrary to this, youth from areas with high community resources will project a positive self-image [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003ePreliminary Studies\u003c/h3\u003e\n\u003cp\u003eDobbins et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] present evidence of Adverse Childhood Experiences (ACEs) among rural and urban North Carolina Latinx children. Seventy-five (75) Latinx low-income rural farmworker mothers and sixty-three (63) Latinx urban mothers completed a standardized ACEs inventory by Felitti et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] for their 8-year-old children. The analysis used a dichotomous measure of the absence of ACEs compared to endorsing the existence of ACEs. The results also included an itemized listing of the specific items in the inventory of ACEs for children with three or more ACEs. According to the data, 47.1% of the mothers did not report the presence of ACEs, 33.3% reported at least one ACE, 8.7% reported two ACEs, and 10.9% reported three or more. Children from urban communities were twice as likely as other immigrant families to experience ACEs. Using a logistic regression model, urban children had an increased risk of experiencing at least one adverse childhood experience (OR\u0026thinsp;=\u0026thinsp;2.35, 95% CI\u0026thinsp;=\u0026thinsp;1.01, 5.48) compared to rural children, indicating that ACEs were twice as prevalent among children from urban communities.\u003c/p\u003e \u003cp\u003eRural and urban Latinx populations in North Carolina are particularly vulnerable to mental health issues, especially since Latinx youth suffer from mental health problems at higher rates than non-Latinx youth [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGeographic and physical contexts may contribute to understanding mental illness in children. This study aims to identify measurable differences between Latinx children aged 8\u0026ndash;11 from rural farmworker families and urban families working in different North Carolina settings regarding their anxiety/depression (internalized symptoms) and aggression (externalized symptoms). A second objective is to compare initial and follow-up CBCL results, at one year and again at two years, assessing whether there were changes in mental health outcomes over time. In earlier studies of this sample of children, urban children experienced more adverse childhood experiences [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and scored lower on the WISC-V and tests of cognitive function [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] than rural children, suggesting that urban children may experience developmental delays and behavioral challenges compared to rural children. Specifically, the research questions were whether there are differences in anxious/depression symptoms and aggression symptoms between rural and urban children at the initial screening and how these symptoms change over time.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis analysis used data collected from Preventing Agricultural Chemical Exposure 5 (PACE 5), a community-based participatory research project in collaboration with the North Carolina Farmworkers Project (Benson, NC; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ncfwp.org/\u003c/span\u003e\u003cspan address=\"https://ncfwp.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e and the Wake Forest University School of Medicine, which analyzed the association between pesticide exposure and brain development among Latinx children from rural farmworker families and those from similar urban families. The Wake Forest University School of Medicine Institutional Review Board (IRB) approved the PACE 5 protocol and procedure.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eOne hundred forty-one (141) mother-child pairs participated in the PACE 5 study, including 76 children from rural families and 65 from urban families. This research examined Latinx rural farmworker families residing in eastern North Carolina, while the urban families lived near Winston-Salem in central North Carolina. Baseline data required that the children came from families with income below 200% of the federal poverty level and who self-identified as Latinx or Hispanic. The parents who lived in rural areas worked on farms with pesticide exposure. Children residing in urban areas neither had a parent who frequently used pesticides in their occupation (such as farming, landscaping, and pest control) nor had they lived near agricultural fields with pesticides in the previous three years. The study excluded children with life-threatening illnesses, neurological conditions, physical conditions, developmental disorders, or whose primary language was not English or Spanish from participation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eRecruitment\u003c/h2\u003e \u003cp\u003eIn collaboration with community members, the NC Farmworkers Project developed a list of Latinx families with 8-year-old children in rural counties near Benson, North Carolina. Winston-Salem recruiters and community members compiled a list of Latinx families with an 8-year-old child to collect data from an urban sample. Bilingual staff explained overall study procedures, responded to inquiries, and obtained signed informed consent from the parent and assent from the child. Mothers living with their child and familiar with the child's daily functioning completed the CBCL. Trained bilingual, native Spanish-speaking interviewers assisted parents with completing these questionnaires to reduce difficulties or frustrations and answer questions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Collection, Study Timing, and COVID Impact\u003c/h2\u003e \u003cp\u003eThe study design initially specified administering the Child Behavioral Checklist (CBCL) assessments three times: at the beginning, one year in, and the end of the two years. Two bilingual, native-Spanish-speaking research psychologists with master\u0026rsquo;s and doctor\u0026rsquo;s level qualifications conducted these assessments in person. Recruitment and the administration of the initial CBCL pre-test occurred from March 2018 to December 2018, and the CBCL one-year post-tests took place during the one-year interval in 2019 for participants. COVID-19 restrictions delayed the administration of some post-tests, so second-year evaluations occurred from 2020\u0026ndash;2021. During this time, all testing with participants transpired via phone calls with the bilingual research psychologist while participants received the CBCL materials left on their front porch. Research staff later retrieved the completed tests from the participants\u0026rsquo; porches. Final testing occurred from March 2020 through December 2021. The study concluded in more than the planned timeframe of 2 years, with the timescale ranging between 2 and 3 years due to delays. Some participants had no timing delay, and the data included and accounted for those with a delay.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eInstrument\u003c/h2\u003e \u003cp\u003eThe CBCL is the most used parental-reported instrument for assessing child and adolescent psychopathology [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The CBCL has well-established reliability and validity across cultures and racial and ethnic groups. The Spanish version of the CBCL demonstrates strong test-retest alpha reliabilities for the internalizing, externalizing, and total problems scales [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The CBCL Spanish version for children 6\u0026ndash;18 has 112 questions that comprise seven subscales classified into three domains: externalizing, internalizing, and total problems [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The CBCL uses a response format based on a 3-point Likert-type scale with choices of 0\u0026thinsp;=\u0026thinsp;Not true, 1\u0026thinsp;=\u0026thinsp;Somewhat or Sometimes true, 2\u0026thinsp;=\u0026thinsp;Very true or Often true, and fill-in-the-blank [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe CBCL uses a hierarchical model of two broad categories, internalizing and externalizing domains, to describe various psychological disorders. The internalizing measure includes a range of anxiety and depression symptoms categorized into three more specific scales: Anxious/Depressed, Withdrawn/Depressed, and Somatic Complaints. The externalizing measure includes two scales for Rule-breaking Behavior and Aggressive Behavior. Social difficulties, thought disturbances, and attention problems contribute to the total score [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Based on CBCL normative data, t-scores less than 59 indicate non-clinical symptoms, t-scores 60\u0026ndash;64 suggest an increased risk of clinical symptoms, and t-scores 65 and above represent clinically relevant symptoms [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This study focused on two CBCL scales: externalized aggressive behavior and internalized anxious/depressive symptoms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe child's categorical independent variable was a rural or urban residence. The dependent variables represented the internal (anxious/depressed) and external (aggression) CBCL mental health symptoms. The study examined whether there was a relationship between mental health symptoms and children's residential areas and whether urban and rural children differed in their initial CBCL scores or their rates of change in CBCL scores over time.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe study analyzed the data using a hierarchical linear model (HLM) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] with IBM SPSS Statistics software [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This study used multi-level regression to evaluate the relationships between psychological symptoms measured by the CBCL and children's residential location (urban versus rural). A multi-level regression analysis can determine whether the CBCL results between the initial assessment and follow-up evaluations changed approximately one and two years later. Given the repeated measures of the same individual, a multi-level regression analysis controls for clustering. Multi-level regression models also clarify the hierarchical data and account for variance within and between subjects. Through this method, analysis distinguishes cluster differences and enables effective observational and cluster-level data modeling [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eFully Unconditional Model\u003c/h2\u003e \u003cp\u003eThe fully unconditional model for CBCL anxiety/depression scores, with time as an independent variable, indicated significant clustering, χ\u003csup\u003e2\u003c/sup\u003e (111)\u0026thinsp;=\u0026thinsp;148.00, p\u0026thinsp;=\u0026thinsp;.011, confirming the need for a multi-level model [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The results also suggested heterogeneity of variance of CBCL scores over time, χ2 (110)\u0026thinsp;=\u0026thinsp;404.8, p\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eHypothesized Model\u003c/h2\u003e \u003cp\u003eThis model utilized data analysis to fit the hypothesized model as well as a level-1 model for the level-1 heterogeneous variance:\u003c/p\u003e \u003cp\u003eVar (R) = σ\u003csup\u003e2\u003c/sup\u003e and log (σ\u003csup\u003e2\u003c/sup\u003e) = α\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;α\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e (TIME).\u003c/p\u003e \u003cp\u003eThe model comparison test between the hypothesized and the fully unconditional, or null, model was statistically significant, χ\u003csup\u003e2\u003c/sup\u003e (6)\u0026thinsp;=\u0026thinsp;65.4, p\u0026thinsp;\u0026lt;\u0026thinsp;.001. These results suggest that the hypothesized model significantly reduced error relative to the null model [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The model for the heterogeneous variance across time was statistically significant, χ2 (1)\u0026thinsp;=\u0026thinsp;9.92, p\u0026thinsp;=\u0026thinsp;0.002. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the parameters for modeling the heterogeneous variance. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e indicates that both the α0 and α1 terms were statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eComparisons of Sample Demographics of North Carolina Rural and Urban Latinx Mothers and their Children\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the baseline family characteristics of the rural and urban Latinx populations for this study sample. Among the 76 Latinx rural children in farm-working families in PACE5, 47.4% of the mothers were married, 36.8% had a partner, 0% had never been married, and 15.8% were widowed, separated, or divorced. In the PACE5 urban sample of immigrant families, 60.0% of children lived in married families, 30.8% of mothers lived with their partners as married, 3.1% were never married, and 6.2% of mothers were widowed, separated, or divorced.\u003c/p\u003e \u003cp\u003eMost mothers in this study were born in Mexico (78.9% rural and 72.3% urban). The difference between the rural mothers (1.3%) and the urban mothers (9.2%) from Honduras were statistically significant (p\u0026thinsp;=\u0026thinsp;0.56). While all the households in rural farming communities had a family member working in agriculture, some mothers worked non-agricultural jobs. Mothers who worked in fishing, farming, or forestry constituted 48.7% of the sample. Many rural and urban mothers worked in building, grounds, and maintenance (7.9% and 9.2%), food preparation and serving (3.9% and 3.1%), personal care services (3.9% and 3.1%), production (14.5% and 13.8%, and sales and other occupations (0% and 6%) respectively. 0% of the rural mothers and 10.8% of the urban mothers identified themselves as housewives. Analysis of all the data for mothers' occupations discovered a significant difference between rural mothers and urban mothers. The most notable difference was that 18.4% of rural mothers did not work, compared to 40% of urban mothers \u003cem\u003e(χ2(10)\u0026thinsp;=\u0026thinsp;56.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eAll the children were 8 years old at the start of this study. Rural and urban samples had similar gender distributions, with 52.6% and 52.3% male and 47.45% and 47.7% female participants for rural versus urban, respectively. An equivalent proportion of rural and urban child participants were born in the US (89.5% rural and 95.4% urban). 11.84% of the rural children were in 1st grade at the beginning of the study; 63.16% were in 2nd grade, 23.65% were in 3rd grade, and 1.32% were in 4th grade. Comparatively, 41.54% of urban children were in 2nd grade, 55.28% were in 3rd grade, and 3.08% were in 4th grade. The differences between the two groups of children attending 3rd grade (23.65% and 55.28%) were statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.098) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eResults for CBCL Anxious/Depressed Baseline Data\u003c/h2\u003e \u003cp\u003eA final two-level HLM model describes CBCL data depression/anxiety symptoms as follows:\u003c/p\u003e \u003cp\u003e \u003cem\u003eANX_DEP0\u003c/em\u003e \u003csub\u003e \u003cem\u003eti\u003c/em\u003e \u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003e00\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003e01\u003c/em\u003e\u003c/sub\u003e*\u003cem\u003eURBRUR\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003e10\u003c/em\u003e\u003c/sub\u003e*\u003cem\u003eTIME\u003c/em\u003e\u003csub\u003e\u003cem\u003eti\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003e11\u003c/em\u003e\u003c/sub\u003e*\u003cem\u003eURBRUR\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e*\u003cem\u003eTIME\u003c/em\u003e\u003csub\u003e\u003cem\u003eti\u003c/em\u003e\u003c/sub\u003e + \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003e0i\u003c/em\u003e\u003c/sub\u003e + \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003e1i\u003c/em\u003e\u003c/sub\u003e*\u003cem\u003eTIME\u003c/em\u003e,\u003csub\u003e\u003cem\u003eti\u003c/em\u003e\u003c/sub\u003e + \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003eti\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eThese results appear in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The mean anxious/depressed symptom score at baseline for rural children was 50.59 and 54.74 for children in urban settings, a statistically significant difference, \u003cem\u003et\u003c/em\u003e(110)\u0026thinsp;=\u0026thinsp;18.57, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001. The CBCL does not identify clinical symptoms for \u003cem\u003et\u003c/em\u003e-scores less than 59.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eResults for CBCL Aggression Baseline Data\u003c/h2\u003e \u003cp\u003eAn equivalent analysis to that described above investigated the CBCL aggression data. A final two-level HLM model describes aggressive behavior CBCL data as follows:\u003c/p\u003e \u003cp\u003e \u003cem\u003eAGGRESS0\u003c/em\u003e \u003csub\u003e \u003cem\u003eti\u003c/em\u003e \u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003e00\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003e01\u003c/em\u003e\u003c/sub\u003e*\u003cem\u003eURBRURAL\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003e10\u003c/em\u003e\u003c/sub\u003e*\u003cem\u003eTIME\u003c/em\u003e\u003csub\u003e\u003cem\u003eti\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eβ\u003c/em\u003e\u003csub\u003e\u003cem\u003e11\u003c/em\u003e\u003c/sub\u003e*\u003cem\u003eURBRURAL\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e*\u003cem\u003eTIME\u003c/em\u003e\u003csub\u003e\u003cem\u003eti\u003c/em\u003e\u003c/sub\u003e + \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003e0i\u003c/em\u003e\u003c/sub\u003e + \u003cem\u003er\u003c/em\u003e\u003csub\u003e\u003cem\u003e1i\u003c/em\u003e\u003c/sub\u003e*\u003cem\u003eTIME\u003c/em\u003e\u003csub\u003e\u003cem\u003eti\u003c/em\u003e\u003c/sub\u003e + \u003cem\u003ee\u003c/em\u003e\u003csub\u003e\u003cem\u003eti\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eThe CBCL aggression baseline scores (AGGRESS) results appear in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The mean aggression symptom score at baseline for children from rural farmworker families was 44.15, and for urban children, 49.92, a statistically significant difference, \u003cem\u003et\u003c/em\u003e(115)\u0026thinsp;=\u0026thinsp;7.40, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eResults for CBCL Rates of Change in Anxious/Depressed Scores over Time\u003c/h2\u003e \u003cp\u003eThe mean linear rate of change per year in CBCL anxiety and depression scores for rural children (time slope in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) was \u0026minus;\u0026thinsp;.060, \u003cem\u003et\u003c/em\u003e(110) = -0.20, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.844, resulting in a value not statistically different from 0, suggesting no change over time. The rate of decline across time was \u0026minus;\u0026thinsp;1.23 for urban children, which was statistically significantly faster than for rural children, \u003cem\u003et\u003c/em\u003e(110) = -2.27, p\u0026thinsp;=\u0026thinsp;0.025.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe decline of internalized symptoms for urban children also differed from that of rural children by -1.17. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e depicts a comparison between urban and rural children's anxious/depressed CBCL scores at baseline and across time. The steeper slope for urban children shows a decrease in CBCL scores across time compared to the essentially stable CBCL scores for rural children.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eResults for CBCL Rates of Change in Aggression Scores over Time\u003c/h2\u003e \u003cp\u003eThe mean linear rate of change per year in CBCL aggression scores for rural children (time slope in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e) was +\u0026thinsp;3.63, \u003cem\u003et\u003c/em\u003e(115)\u0026thinsp;=\u0026thinsp;7.40, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, indicating a statistically significant increase in CBCL scores across time. The mean linear change rate per year for urban children (time slope in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) was +\u0026thinsp;1.92, a statistically significantly lower rate of change. The difference in the rate of change in aggression scores between urban and rural children was \u0026minus;\u0026thinsp;1.71, \u003cem\u003et\u003c/em\u003e(115) = -3.50, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001. Thus, both groups showed significant increases in CBCL aggression scores across time, but the rural children's progression sequentially was significantly more rapid than that for urban children. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the rates of change in CBCL aggression scores for urban and rural children.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThere is an increasing body of literature exploring the mental health of Latinx youth. However, the extent to which geographic contexts affect internalizing and externalizing symptoms has received little attention. Understanding Latinx youth's mental health needs will enable services and interventions appropriate to multiple contexts and tailored to their community's needs. This study assessed whether Latinx children aged 8\u0026ndash;11 from rural farmworker families and urban non-farmworker families in North Carolina had measurable differences in anxious/depression (internalized symptoms) and aggression (externalized symptoms) across time. These findings suggest that urban children were more likely to experience internalized emotional problems than those from rural farmworker families. Internalized results for the rural sample remained unchanged and were not statistically significantly different. Other PACE 5 studies with a similar population of Latinx urban children reported more adverse childhood experiences [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and lower WISC-V scores [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Adolescents with depression have lower full-scale, verbal, and performance IQs, lower working memory, organization ability, verbal fluency, and concentration than non-depressed adolescents [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Dobbins et al. (2021) found urban children are twice as likely as rural children to have at least one adverse childhood experience (ACE). Stresses from disadvantages may explain why urban children had higher baseline scores on anxious/depression CBCL scores than rural children.\u003c/p\u003e \u003cp\u003eIn addition, the results compared the initial and follow-up evaluations approximately one and two years after the first initial assessment to determine whether CBCL outcomes changed over time. The externalized, aggressive symptoms of Latinx children in rural and urban environments increased over time. Urban children's baseline aggression scores were higher than the rural children's initially. Still, the rural children's aggression scores increased more rapidly, resulting in diminished differences between the two groups two years later. Externalizing aggressive behaviors contributes to the risk of adolescent deviant behaviors like delinquency, substance use, parent-child conflict, and negative peer relationships [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Additionally, longitudinal studies have shown a reciprocal relationship between internalized emotional problems and externalized aggression among youth, in which aggressive behavior is likely to be accompanied by depression and anxiety and vice versa [\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough the results of this study cannot explain why Latinx children who live in rural and urban areas experience different ranges of mental health symptoms, evidence suggests that different environmental contexts may play a role. Poor and marginalized communities often experience differences ranging from targeted prejudice to structural racism. According to Cano et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], discrimination or racism, which is uniquely experienced by minority groups, can contribute to Latinx youths' externalizing aggressive behavior. Latinx face discrimination, limiting their access to opportunities and resources. This study consists of Latinx children whose families earn less than 200% of the federal poverty level. Growing up in oppressive, impoverished, unstable, or dire living conditions can cause any child, regardless of age, to exhibit aggression. Identifying contextual factors may help inform prevention and intervention strategies for Latinx youth. Understanding the specific factors contributing to mental health issues among Latinx youth is vital to developing and implementing evidence-based and culturally appropriate mental health services [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo provide culturally competent care, mental health providers and healthcare workers must recognize how relationships, circumstances, stress, culture, and transitions affect Latinx children. Furthermore, public policy must consider how exposure to risk affects Latinx psychological well-being [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Understanding the specific factors contributing to mental health issues among Latinx youth is vital to developing and implementing evidence-based and culturally appropriate mental health services [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Sociopolitical history, ethnic density, public policies, and resource inaccessibility also contribute to mental illness [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Specifically, Latinx youth living in urban areas receive less mental health care than their peers from other ethnic and racial backgrounds and suffer from more mental health disparities as a result of low academic performance, physical and sexual abuse, adjustment difficulties, relocation due to temporary/seasonal migration, and deportation fears [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite meaningful, statistically significant changes in mental health symptoms over time, t-score thresholds for this population of children did not reach clinically significant levels. According to the immigrant paradox, even when children of immigrants face adverse conditions due to socioeconomic conditions and discrimination, they continue to succeed, remain resilient, and have protective health indicators. Nevertheless, because Latinx populations suffer from lower rates of psychiatric disorders, research and treatment interventions often overlook Latinx mental health concerns [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. It is essential to investigate subclinical symptoms since they may develop into clinically significant symptoms over time.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eFuture Research\u003c/h2\u003e \u003cp\u003eThis descriptive analysis aims to present geographical influences on Latinx children's mental health; however, it does not distinguish the other factors that may cause or contribute to symptoms. Trauma and discrimination can also play an essential role in affecting their emotional well-being. The challenges associated with adjusting to a new country, when combined with previous stressful experiences, can lead to anxiety symptoms and other mental illnesses [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Migrants often experience trauma due to political unrest, forced disappearances, sexual abuse, and being witnesses to violence in their countries of origin [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In Latinx communities, immigration remains a particularly prominent issue because many Latinx know undocumented immigrants, and a substantial percentage know someone incarcerated or deported personally. It is important to note that children with US citizenship may lose a parent or caregiver, experience environmental or community changes, and cope with stress and trauma without adequate mental health services [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The risks associated with undocumented and illegal status can lead to anxiety, insecurity, trauma, and exploitation [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Mixed-status families with native and foreign-born family members and migration-related discrimination can also suffer from emotional distress, depression, anxiety, panic attacks, attention deficit hyperactivity disorder, conduct problems, and post-traumatic stress disorder [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to recent data on healthcare disparities, where people live affect their health. Some communities have a shorter average life expectancy than those mere miles away. Generally, health disparities reflect a complex interaction between racial, economic, educational, and other factors [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. A separate inquiry found that lower externalizing problems among youth were associated with different neighborhood SES and immigrant concentrations. Latinx children living in neighborhoods with high concentrations had a lower risk of externalizing problems, while non-Latinx youth in these neighborhoods had the opposite effect [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Most of the urban children in this study lived near Winston-Salem, North Carolina, in Forsyth County. Based on census data, the United Way of Forsyth County [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] found that the average household income of a child of low-income parents residing in the 27104-zip code, now in their mid-30s, is \u003cspan\u003e$\u003c/span\u003e45,000 per year. The average income of children in their mid-thirties who grew up in the 27105-zip code is \u003cspan\u003e$\u003c/span\u003e17,000. The distance between these two zip codes is just five miles. Mortality and morbidity disparities exist throughout the country, even within small areas near each other [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Comparing zip codes with various social determinants of health datasets could help identify whether children living in specific areas are more susceptible to disparities such as economic stability, environmental injustice, and neighborhood safety than other children within the comparison groups [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile the study did not examine gender differences, its evaluation could provide gender-informed cultural information. Traditional Latinx gender roles involve different social expectations for males and females and adhere to a patriarchal order [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Gender-specific cultural norms and behaviors influence the development of a Latinx child. In addition, gender plays a vital role in how children interact socially [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. As a result of gender roles conflicting with mainstream American cultural norms, Latinx females may be more likely to develop depression symptoms during adolescence. Latinx cultures place importance on the family, and females must behave passively, give precedence to family needs, and sacrifice their own well-being for family unity. Latinx males traditionally adhere to strict, masculinized roles and attitudes associated with aggressive behavior and male honor [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Differentiating gender-cultural outcomes between rural and urban comparison groups could provide a means to moderate and define significance levels in outcomes between this study's rural and urban comparison groups.\u003c/p\u003e \u003cp\u003eAlthough this longitudinal study followed this group of children for two years during middle childhood, longitudinal data through adolescence may help identify crucial times during a child's life when intervention is needed or to maximize protective safeguards. Adolescence is a pivotal developmental period marked by profound physical, cognitive, and social adjustment. Therefore, analyzing the socio-emotional factors influencing childhood development provides insight into future mental health outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe current study is not without limits. Specifically, the study evaluated the mental health of Latinx youth in rural and urban environments without comparing them to the youth of other races in similar residential settings. Since only Latinx children living in specific rural and urban areas in North Carolina participated in the study, the findings might not generalize to other regions across the country. Reporting bias may have affected the results as parents may not have been aware of experiences outside their homes, such as discrimination in schools or communities. Social desirability may also be a factor, especially among rural mothers who reported sub-clinical mental health symptoms affecting their children. It is imperative to consider the unique protective and risk factors of Latinx subgroups when understanding and treating psychological distress [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Barrag\u0026aacute;n et al. (2020) found that the Spanish language buffered psychological distress in Mexican Americans; however, this resulted in higher rates of psychological distress among Latinx people of Central and South America, Puerto Rico, and Cuba. Understanding cultural differences among Latinx subgroups, like the urban and rural comparison groups, may be helpful and contribute to understanding intragroup differences.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThese findings illustrate the importance of differentiating specific mental health symptoms when studying the relationship between urban or rural influences among Latinx children. Both internalized and externalized mental health symptoms varied between these groups. Latinx children living in urban areas are more likely to suffer from internalized mental health concerns. Rural children initially presented with more externalized aggressive behavior, but both groups showed increased aggressive behavior as time progressed. Mental health care for these children must also consider challenges such as discrimination, neighborhood environments, poverty, and trauma. To fully understand possible factors affecting Latinx children's mental health, it is necessary to control for confounding factors such as age, gender, race, regional differences, and ethnicity. Further longitudinal studies of Latinx communities may provide insight into how social, physical, and economic disadvantages affect children's mental health [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eWe further confirm that the order of authors listed in the manuscript has been approved by all of us. We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property. We further confirm that any aspect of the work covered in this manuscript that has involved either experimental animals or human patients has been conducted with the ethical approval of all relevant bodies and that such approvals are acknowledged within the manuscript. We understand that the Corresponding Author (LB) is the sole contact for the Editorial process (including Editorial Manager and direct communications with the office). She is responsible for communicating with the other authors about progress, submissions of revisions and final approval of proofs. The authors all provided substantial contributions to the conception, design of this work, analysis, interpretation of data, drafting or critical for important intellectual content, and final approval of the version to be published. We all agreed upon accountability for all aspects of the work to ensure that questions related to the accuracy or integrity of the manuscript are appropriately investigated and resolved.LB wrote the abstract, background, methods, discussion, conclusion, and references. She also helped with revisions in the results section, Table 2, Figure 1 and Figure 2.WN wrote most of the results sections, compiled analysis, and prepared Table 1, Table 2, Table 3, Table 4, Figure 1 and Figure 2.ES provided guidance regarding how to design this study, organize the paper, proofing and editing.LZ provided guidance regarding conceptualization, design and methods, proofing and editing.The corresponding author is most appreciative to PL for his mentorship and allowing her to be a part of the PACE 5 project. He helped with analysis, multiple revisions, as well as support and guidance throughout the submission process.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors appreciate the support of their community partners, the North Carolina Farmworkers Project, and Student Action with Farmworkers. They also appreciate our community field interviewers' valuable contributions to recruiting participants and collecting data. We sincerely thank the children and parents who participated in this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data sets generated during and/or analyzed during this current study are not publicly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Data are located in controlled access data storage at Wake Forest University School of Medicine (Winston-Salem, North Carolina, USA).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKrogstad JM, Noe-Bustamante L. 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Depressive symptoms and externalizing behaviors among Hispanic immigrant adolescents: Examining longitudinal effects of cultural stress. J Adolesc. 2015;42:31\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLawton KE, Gerdes AC. Acculturation and Latino adolescent mental health: integration of individual, environmental, and family influences. Clin Child Fam Psychol Rev. 2014;17:385\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChapman MV, Perreira KM. The well-being of immigrant Latino youth: A framework to inform practice. Fam Soc. 2005;86:104\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKo LK, Perreira KM. \u0026ldquo;It turned my world upside down\u0026rdquo;: Latino youths\u0026rsquo; perspectives on immigration. J Adolesc Res. 2010;25:465\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDas-Munshi J, Becares L, Dewey ME, Stansfeld SA, Prince MJ. Understanding the effect of ethnic density on mental health: multi-level investigation of survey data from England. BMJ. 2010;341:c5367.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVillalba JA. Health disparities among Latina/o adolescents in urban and rural schools: educators\u0026rsquo; perspectives. J Cult Divers. 2007;14:169\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlegr\u0026iacute;a M, Canino G, Shrout PE, Woo M, Duan N, Vila D, et al. Prevalence of mental illness in immigrant and non-immigrant U.S. Latino groups. Am J Psychiatry. 2008;165:359\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVargas ED, Ju\u0026aacute;rez M, Sanchez GR, Livaudais M. Latinos\u0026rsquo; connections to immigrants: How knowing a deportee impacts Latino health. J Ethn Migr Stud. 2019;45:2971\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrnelas IJ, Yamanis TJ, Ruiz RA. The health of undocumented Latinx immigrants: What we know and future directions. Annu Rev Public Health. 2020;41:289\u0026ndash;308.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraham GN. Why your ZIP Code matters more than your genetic code: Promoting healthy outcomes from mother to child. Breastfeed Med. 2016;11:396\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOur initiatives [Internet]. United Way Forsyth. 2022. [cited 2023 Jan 30]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.forsythunitedway.org/our-initiatives/\u003c/span\u003e\u003cspan address=\"https://www.forsythunitedway.org/our-initiatives/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Population Health and Public Health Practice, Committee on Community-Based Solutions to Promote Health Equity, Baciu A, Negussie Y, et al. The root causes of health inequity. National Academies Press (US); 2017.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSocial Determinants of Health (SDOH) and PLACES data. 2022 [Internet]. 2023 [cited 2023 Jan 31]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/places/social-determinants-of-health-and-places-data/index.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/places/social-determinants-of-health-and-places-data/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerreira K, Smith LO. A cultural-ecological model of migration and development: Focusing on Latino immigrant youth. Prev Res. 2007;14:6\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcLaughlin KA, Hilt LM, Nolen-Hoeksema S. Racial/ethnic differences in internalizing and externalizing symptoms in adolescents. J Abnorm Child Psychol. 2007;35:801\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim SY, Schwartz SJ, Perreira KM, Juang LP. Culture\u0026rsquo;s influence on stressors, parental socialization, and developmental processes in the mental health of children of immigrants. Annu Rev Clin Psychol. 2018;14:343\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarrag\u0026aacute;n A, Yamada A-M, Gilreath TD, Lizano EL. Protective and risk factors associated with comorbid mental health disorders and psychological distress among Latinx subgroups. J Hum Behav Soc Environ. 2020;30:635\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosen LD, Imus D. Environmental injustice: Children\u0026rsquo;s health disparities and the role of the environment. EXPLORE. 2007;3:524\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":" \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel for Level 1 Variance over Time\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard\u003c/p\u003e \u003cp\u003eError\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e-ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINTRCPT1, α\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.197459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u003c/b\u003e\u0026thinsp;0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTIME, α\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.163490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*These findings show that both the α0 and α1 terms were statistically significant.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of Rural and Urban North Carolina Latinx Mothers and their Children Demographics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eChi-square\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e(3)\u0026thinsp;=\u0026thinsp;6.64\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.08\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiving as married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidowed/separated/divorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e(1)\u0026thinsp;=\u0026thinsp;0.34\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.56\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex of child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild\u0026rsquo;s grade level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e(6)\u0026thinsp;=\u0026thinsp;10.702\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u0026thinsp;=\u0026thinsp;.098\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1st grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.84%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2nd grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.54%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3rd grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.68%\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.38%\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4th grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.08%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChild's birth country\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e(3)\u0026thinsp;=\u0026thinsp;2.05\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.56\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuatemala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMother's birth country\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e(4)\u0026thinsp;=\u0026thinsp;5.4\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.25\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuatemala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHonduras\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3%\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.2%\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexico\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMother's occupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e(10)\u0026thinsp;=\u0026thinsp;56.6\u003c/p\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBuilding, grounds, or maintenance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction \u0026amp; Extraction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDoes not work\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.4%\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.0%\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFishing, farming, and/or forestry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFood preparation and serving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthcare support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousewife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.8%\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOffice \u0026amp; Administration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePersonal care and services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSales \u0026amp; Related\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0%\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.2%\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Column differences are statistically significant\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eHLM Results for CBCL Anxious/Depression (ANX-DEPO) final estimation of fixed effects.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e-ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eApproximate \u003cem\u003ed. f.\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eFor INTERCEPT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eFor TIME slope\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.844\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHLM Results for CBCL Aggression (AGGRESS) final estimation of fixed effects.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFixed Effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e-ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eApproximate \u003cem\u003ed. f.\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eFor INTERCEPT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eFor TIME slope\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e "}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Latinx children, mental health, Child Behavioral Checklist (CBCL)","lastPublishedDoi":"10.21203/rs.3.rs-4631688/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4631688/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examined mental health symptoms among 8-11-year-old children of Latinx farmworkers in rural North Carolina (N\u0026thinsp;=\u0026thinsp;76) and urban children of Latinx parents (N\u0026thinsp;=\u0026thinsp;65). All had household incomes of 200% below the poverty line. A Spanish version of the Child Behavioral Checklist (CBCL) for children aged 6\u0026ndash;18 assessed internalized (anxious/depression) and externalized (aggression) mental health symptoms. CBCL scores obtained at baseline and subsequent follow-up evaluations approximately one year and two years after the first evaluation were analyzed with multi-level regression to determine if the CBCL outcomes changed over time. Children from farmworker families showed lower levels of anxious/depressive symptoms at baseline (mean\u0026thinsp;=\u0026thinsp;50.59) than urban children (mean\u0026thinsp;=\u0026thinsp;54.74), but these differences diminished with age. The mean depression score for the urban sample decreased by -1.17 points each year after the initial assessment. Both rural (mean\u0026thinsp;=\u0026thinsp;44.15) and urban Latinx children (mean\u0026thinsp;=\u0026thinsp;49.92) developed increased externalized aggressive symptoms over time, and rural children's aggression increased faster than urban children. The rural children showed a statistically significant increase with a mean linear rate of change of +\u0026thinsp;3.63 over time. This study contributes to the current research on how community settings may affect children's socio-emotional development, and suggests further examination into the impact of social, physical, and economic disadvantages on children's mental health.\u003c/p\u003e","manuscriptTitle":"Internalized and Externalized Mental Health Symptoms among Latinx Children:A Comparison between Rural Latinx Farmworker and Urban Latinx Low-Income Families Living in North Carolina","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-26 15:58:00","doi":"10.21203/rs.3.rs-4631688/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"047f9408-5f8d-47e0-b5c9-b5a970d3e486","owner":[],"postedDate":"July 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-12T17:08:41+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-26 15:58:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4631688","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4631688","identity":"rs-4631688","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}