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Research Article                                                                                                                                        Open Access

## Immigrant Preadolescents and Risk of Emotional Distress

Daniele E. Alves 1* , Heather L. Corliss 2,3 , Espen Roysamb 1,4 , Henrik D. Zachrisson 1,5 , Brit Oppedal 1 , Kristin Gustavson 1

1 Division of Mental Health, Norwegian Institute of Public Health, Oslo, Norway 2 Department of Pediatrics, Harvard Medical School, Boston, MA, USA 3 Division of Health Promotion and Behavioral Science, San Diego University, San Diego, CA, USA 4 Department of Psychology, University of Oslo, Oslo, Norway

5 Norwegian Center for Child Behavioral Development, Oslo, Norway

*Corresponding author: Daniele.Evelin.Alves@fhi.no; alves.integra@gmail.com

## Abstract

Background: The  question  of  whether  immigrants  have  more  emotional  problems  than  their  non-immigrant  peers  has yielded mixed results. In Norway, there has been a tendency toward immigrant youth reporting higher rates of emotional problems. In addition to studying levels of emotional problems across those with immigrant backgrounds, there is a need to investigate whether the phenomenology of these problems is comparable across ethnic groups.

Objectives :  We used latent class analysis (LCA) to identify subgroups of preadolescents with distinct types of emotional problems in a multiethnic sample in Norway and to investigate associations with immigrant status after controlling for other demographic and risk factors related to emotional problems.

Methods: Preadolescents between the ages of 10 and 12 years (n = 1042) completed a questionnaire that assessed emotional problems and sociodemographic factors such as gender, grade level, city, economic hardship, school hassles, and parental achievement values. LCA was used to identify subgroups of preadolescent emotional problems. Multinomial logistic regressions were conducted to assess the relationships between these subgroups and the presence of an immigrant background with four immigrant groups (all backgrounds, Pakistan, Turkey, and Sri Lanka). The reference group was the ethnic Norwegians.

Results : LCA identified three classes according to the severity of the problems; these were labeled healthy, borderline, and distressed.  Multinomial  logistic  regression  analyses  found  the  presence  of  an  immigrant  background  as  compared  with  a non-immigrant background to increase the odds of a person belonging to the distressed class by an approximate factor of 2, depending on the immigrant group. This finding remained consistent after controlling for risk factors.

Conclusions: These findings suggest that, even as early as preadolescence, the presence of an immigrant background may significantly increase the odds of an individual belonging to a subgroup characterized by emotional distress (as compared with belonging to a healthy class). These findings also suggest similarity across ethnic backgrounds with regard to the expression  of  emotional  problems  during  preadolescence.  This  is  the  first  study  to  identify  classes  of  emotional  problems among specific preadolescent immigrant groups.

Keywords: internalizing symptoms, ethnic minority, latent class, gender

## Background

Configurations of Emotional Symptoms across Ethnic Groups

Emotional  problems  can  be  expressed  differently across cultures. It is well known that some types of diagnoses  and  symptom  configurations  are  seemingly more abundant in specific ethno-cultural groups (1;2). An example is the 'nerve attack' ( ata- que de nervios in Spanish), which is found in Spanish and Hispanic communities but not in other populations (2). Although studies investigating group variations in the factor structure of mental health screening instruments are increasing (3), only a few studies have investigated whether certain ethnic groups are more likely to suffer from specific configurations of emotional  symptoms,  including  related  disorders such as depression, anxiety, and somatization (4-6). It is important to address this research gap, because identifying which symptoms characterize depressive distress in different cultural groups may potentially aid diagnosis. In addition, it may also help with the identification of risk and protective factors for distinct symptom configurations.

Configurations can be studied by identifying distinct  subgroups  of  people  with  characteristic  patterns  of  emotional  symptoms.  For  instance,  Carragher  and  colleagues  (4)  found  four  subgroups based on reported depression in a nationally representative adult population in the United States: severely depressed, psychosomatic, cognitiveemotional,  and  non-depressed.  Hispanics  were  significantly less likely to report psychosomatic symptoms  as  compared  with  their  white  counterparts, and  Native  Americans  had  a  decreased  risk  of  reporting  depressive  symptomatology.  The  researchers'  interpretation  was  that  these  minority  groups may embed protective aspects, because they report lower  levels  of  depression  despite  more  social  adversity  (4).  Studies  comparing  immigrant  and  nonimmigrant children and adolescents in terms of levels of emotional problems have yielded inconsistent findings  (7;8).  For  example,  adolescents  from  minority groups with physical appearances that generally differ from that of the dominant ethnic majority have  been  found  to  be  more  vulnerable  to  emotional  problems  in  some  studies  (9-11)  but  not  in others (12-14). Moreover, findings vary according to several factors, such as the specific ethnic minority group being studied, the country in which the group lives,  and  the  group's  age  range  (7).  The  reasons why  an  immigrant  background  may  be  related  to more  emotional  problems  have  been  attributed  to minority-related  stigma  (15;16),  characteristics  of the  family  (e.g.,  low  socioeconomic  status,  strong collectivistic  values,  more  acculturative  stress)  (7), the  presence  of  war  in  the  environment  (13;17), characteristics  of  the  majority  society  (e.g.,  social education, integration policies, discrimination) (18;19).

In  the  research  of  the  mental  health  of  children and adolescents, studies investigating different configurations  of  emotional  or  underlying  symptoms and diagnoses (including anxiety, mood, and somatoform disorders) are rare. As compared with adults,  the  comorbidity  of  emotional  problems  is higher among children and adolescents, both within emotional  problems  as  well  as  between  emotional problems and behavioral problems (20). The literature includes one study that identified different configurations  of  combined  emotional  and  behavior symptoms and their risk factors (21), but no studies were found that identified subgroup configurations of isolated emotional  symptoms  (or underlying symptoms  or  diagnoses)  in  a  multi-ethnic  young population. Subgroup-specific configurations of emotional  problems  should  be  investigated;  they may be associated with potential risk and protective factors, and they may demonstrate whether specific ethnic  groups  are  overrepresented  in  any  type  of configuration.

## Different Ethnic Groups of Preadolescents in Norway

The main body of Scandinavian research  concerning emotional problems among immigrant children and adolescents has been conducted in Norway and Sweden (7;8). This study focuses on the Norwegian context.  Although  the  size  of  indigenous  minority groups has been quite stable during the last 40 years in  Norway,  the  size  of  immigrant  minority  groups has increased markedly during this period (22). Today, the largest groups of children of immigrants are from  Pakistan  (13%),  Somalia  (8%),  and  Vietnam (7%) (22). There has been particular concern about the  mental  health  of  non-Western  immigrant  students (23;24). These preadolescents are more likely to  live  in  poorer  neighborhoods,  to  attend schools that  are  more  socioeconomically  disadvantaged,  to achieve lower grades on national examinations (25), and, for minority boys, to drop out of high school (26). By contrast, immigrant girls appear to be more likely to finish high school than their ethnic Norwegian peers (27).

Although  the  evidence  involving  emotional  distress  among  immigrant  adolescents  in  Norway  is mixed,  most  studies  suggest  that  immigrant  youth are more likely to report higher levels of emotional problems  than  their  ethnic  Norwegian  peers,  although  the  magnitude  of  the  difference  in  some studies is small (28). Other studies have stressed the differences  in  levels  of  emotional  problems  across ethnic  minority  groups  (12;29;30).  In  a  large-scale comparative  study  involving  immigrant  and  nonimmigrant  youth  in  thirteen  countries,  immigrant youth in Norway scored around the grand mean for the  total  international  sample  and  lower  than  the ethnic Norwegian reference sample (18). Still other investigators  have  focused  on  possible  contextual factors in different societies (e.g., Norway and Sweden), which may have differing effects on emotional problems  in  immigrants  from  the  same  national background  (19).  The  included  studies  have  used mean symptom scores to assess the level of mental health problems; this may potentially hide variations in the structuring of symptoms. Identifying different configurations of  emotional  problem  symptoms across different ethnic groups of youth in Norway may provide additional  information  about  the  heterogeneity of emotional problems in this group.

Theory-Driven Versus Data-Driven Configurations of Emotional Problems .

The common approach to studying configurations of emotional problems is theory driven. According to the theory, the types of symptoms and configurations of emotional problems (including emotional disorders) are already established before data analysis takes place. For instance, a researcher who is studying emotional disorders may wish to identify whether a specific ethnic group is more likely to endorse depressive versus anxious symptoms. However, the 'subgroups' (e.g., anxious, depressed, somatizing) are established a priori and beforehand, in this case (31). By contrast, latent class analysis (LCA) is a data-driven approach in which configurations of emotional problems emerge from the available data. LCA identifies subgroups of people (also known as classes ) that distinguish themselves in terms of symptom combinations (also called configurations ), as well as subgroup-specific risk and protective factors. Among young populations, there is also the tendency to analyze emotional problems as one homogeneous phenomenon. LCA allows researchers to test this one-phenomenon assumption by allowing emotional symptoms to cluster into subgroups according to patterns of associations among variables that evolve from the sample (31).

In  adults,  all  LCA  studies  involving  emotional problems have found classes that are, to some degree,  based  on  the  severity  of  emotional  problems (e.g., a 'low levels of symptoms' class) (4-6;32). In addition,  some  LCA  studies  also  define  classes  on the basis of the type of emotional problems (4;6;32). Copeland  and  colleagues  (32)  identified  five  subgroups  with  distinct  configurations  of  common childhood  psychosocial  risks:  two  were  low-risk subgroups  (the  no-risk  class  and  the  inter-parental problems class), two were moderate-risk subgroups (the uneducated/poor class, and the stepparent/crime  class),  and  one  was  a  high-risk  group. High-risk youth had the highest levels of both emotional and behavioral disorders (32).

The aim of this study is to identify subgroups of children on the threshold of adolescence on the basis  of  their  configuration  of  emotional  problems. When  focusing  on  immigrant-specific  configurations, it is important to include variables that could confound  the  relationship  between  the  emotional symptom  classes  and  the  immigrant  groups.  As such, it has been found that girls are more likely to report  emotional  problems,  at  least  from  puberty onward (7;38). Age is another implicated factor, because emotional problems increase from childhood to  adolescence  (7;34).  Although  some  studies  have shown that children who live in rural settings have lower levels of emotional problems than those who live  in  urban areas, overall findings are mixed (15).

Moreover,  given  the  importance  of  school  hassles (8;39-42) and parental achievement values for emotional  problems  in  previous  studies  (42-44),  we chose to also include them in this study. School is a major arena in the lives of children and adolescents, and  some  researchers  point  to  minority  parents  as being highly invested in the school as a place for social mobility for their offspring in the majority society (42;45;46). As a measure of parental investment in  filial  school  performance,  parental  achievement values  have  been  associated  with  positive  consequences for child emotional health in some studies (47-49)  and  with  negative  consequences  in  others (42;45;46).

It  is  important  to  know  more  about  classes  or configurations  of  emotional  problems  in  young people,  especially  for  immigrant  groups  in  which mental  health  problems  may  be  considered  even more  taboo  than  they  are  in  the  majority  population. Emotional problems are still related to stigma in  Western  countries,  and  their  lack  of  disruptiveness that involves others (as compared with behavioral problems) may contribute to the increased difficulty of identifying these problems in daily life and prolong the suffering of those affected. This study will thus investigate the following two questions:

1.  Which  types  of  classes  of  emotional  problems emerge from a multiethnic preadolescent sample in Norway?
2. Is immigrant background (both of specific immigrant groups and in general) more likely to be represented in certain classes than in others?

## Methods

Data Collection and Sample

Data was provided by the Youth Culture and Competence (YCC) study undertaken by the Norwegian Institute of Public Health and approved by the Regional  Committee  for  Medical  Research  Ethics. During 2006 and 2007, the YCC invited preadolescents  (age  range,  10  to  12  years)  from  fourteen schools in Oslo and Bergen to participate in the first wave of the study. The proportion of immigrants in Bergen is 11%, which is equivalent to the national average; however, 27% of the population in Oslo is composed of immigrants (i.e., foreign born or Norwegian  born  with  two  foreign-born  parents).  The immigrants come from more than 200 mostly nonWestern countries (22). There are a few ethnic enclaves in Norway, and immigrants tend to settle together in areas where housing prices are reasonable. Schools in these areas were targeted during the initial  stage of recruitment for this study. In addition, children  with  Tamil  (from  Sri  Lanka)  and  Turkish origins  from  other  schools  were  recruited  through collaboration with immigrant non-governmental organizations.  Parents  were  informed  of  the  YCC

study through the preadolescents' school or a nongovernmental immigrant organization and asked to provide written informed consent.

The  YCC  questionnaire  was  completed  by  the preadolescents in their respective classrooms during two class  hours.  For  those  recruited  through  nongovernmental  immigrant  organizations,  the  questionnaire  completion  was  done  after  school  hours. Research assistants were available, if needed, during data  collection.  Of  the  children  invited,  1042  preadolescents  in  the  fifth,  sixth,  and  seventh  grades participated  in  the  YCC  for  a  participation  rate  of 65%.  Participants  with  two  foreign-born  parents and  at  least  three  grandparents  born  abroad  were classified  as  being  of  immigrant  background;  they will be referred to as the minority from now on. Similarly, participants with two Norwegian-born parents and  at  least  three  Norwegian-born  grandparents were  classified  as  ethnic  Norwegians;  they  will  be referred to as the majority from now on. All preadolescents who were not classified as belonging to the categories 'ethnic Norwegian' or 'ethnic minority' were excluded from further analyses (9). This yielded  a  sample  of  902  preadolescents  who  were evenly divided across age and gender.

## Measures

Emotional  problems  were  measured  with  the  selfreport  questionnaire  of  the  emotional  problems subscale of the Strengths and Difficulties Questionnaire, Norwegian version (50). The emotional symptoms scale consists of five items that indicate symptoms of somatization, anxiety, and depression (α = 0.68; e.g., 'I worry a lot,' 'I am often unhappy, depressed,  or  tearful').  Although,  a  sum  score  that range from 0 to 10 is typically computed (50), each item  was  kept  separate  in  our  analyses  to  identify how the different symptoms cluster. Gender (boys = 0, girls = 1), city (Bergen = 0, Oslo = 1), and ethnic status and background (majority group = 0, immigrant/specific  immigrant  group  =  1,)  were  dichotomized.  The  three  possible  grade  levels  (fifth, sixth, and seventh) that we included in the analyses due  to  their  being  a  proxy  of  age  were  used  as dummy variables. The dummy variables were coded as follows: fifth grade (0 = sixth and seventh grades, 1 = fifth grade), sixth grade (0 = fifth and seventh grades,  1  =  sixth  grade),  and  seventh  grade  (0  = fifth and sixth grades, 1 = seventh grade).

School hassles were measured by five items from the  General  Everyday  Hassles  scale  (8,40).  Each question was rated on a scale ranging from 0 ('No, never') to 3 ('Yes, very often'), and then the sum of the rated scores was computed (α = 0.57; e.g., 'I am afraid of not doing well enough at school,' 'Big problems in understanding the teacher when he/she is  teaching').  Economic  hardship  was  used  as  a proxy  for  socioeconomic  status  and  was  measured with four items from the Adolescent Perceptions of Family  Hardship  scale  (51):  'How  often  do  your parents  argue  with  each  other  about  not  having enough  money?,'  'How  much  do  you  argue  with your  parents  about  not  having  enough  money?,' 'How  much  of  a  problem  does  your  family  have because your parents do not have enough money to buy things your family needs or wants?,' and 'How upset or worried are your parents because they do not have enough money?' (α = .65). All four economic  hardship  items  were  standardized,  and  a mean  score  was  computed.  The  un-standardized scale,  which  consisted  of  the  first  two  items,  was used  when  reporting  mean  differences  (α  =  .48); otherwise, the standardized scale was used. The first two items were rated on a scale that ranged from 1 ('Never')  to  5  ('Always'),  whereas  the  latter  two items  were  rated  on  a  scale  that  ranged  from  1 ('Never') to 4 ('Very much').

The Parental Achievement Values scale measured how preadolescents perceived parental emphasis on achievement  and  was  extracted  from  the  Parental Pressure Questionnaire (52). Four items were rated with  the  use  of  a  Likert  scale  that  ranged  from  1 ('Never') to 5 ('Always') (α = 0.70; e.g., 'My parents think that doing well in school is very important,'  'My  parents  say  that  I  should  work  hard  at everything I do'). Parental achievement values were included because immigrant parents may emphasize their  children's  academic  success  more  than  nonimmigrant parents do (25;43;45). This emphasis may in turn increase preadolescents' pressure to achieve academically and thus contribute to their emotional problems.

## Analytic Strategy

Each  emotional  symptom  indicator  was  included separately  in  the  model  to  enable  heterogeneity  in terms  of  emotional  symptoms  in  the  data-driven subgroups.  This  allowed  us  to  investigate  whether certain  subgroups  of  preadolescents  were  more likely to display distinct patterns of emotional problems  than  others.  Covariates  were  not  used  to  inform  class  enumeration,  because  research  suggests this  can  lead  to  an  overextraction  of  classes  (31). The LCA was accomplished with the use of Mplus version  5,  a  statistical  modeling  program  that  can accommodate  complex  design  methodology  (53). Models with one to four classes were estimated to determine  the  optimal  number  of  classes  that  best fit the data. With LCA, there are multiple statistical indicators  of  model  fit.  The  choice  of  best-fitting model is achieved through a combination of statistical considerations, data, and theory. Both the bootstrapped parametric likelihood ratio test and the LoMendell-Rubin  likelihood  ratio  test  assess  the  im- provement  in  fit  between  competing  models.  A non-significant  value  ( P >  .05)  suggests  that  the model with one class less provides a better fit to the data. The Bayesian information criterion (BIC) and the  sample-size  adjusted  BIC  (SSABIC)  are  goodness-of-fit  measures  that  span  competing  models: the  lowest  value  for  each  criterion  indicates  the best-fitting  model.  In  this  analysis,  we  chose  the BIC and the Lo-Mendell-Rubin likelihood ratio test as our main indicators; they have been evaluated as the  most  reliable  indicators  for  determining  the number of latent classes (54). Finally, the best number of classes in terms of statistical fit indicators was assessed in terms of theoretical soundness.

The second part of the analyses consisted of examining how immigrant background (for all immigrants  and  for  the  three  largest  specific  immigrant groups in the sample) predicted membership in the different classes. We also assessed whether gender, city, grade level, school hassles, economic hardship, and  parental  achievement  values  could  distinguish among  specific  class  memberships.  For  this  purpose, we used the latent class variable obtained with Mplus to conduct a multinomial logistic regression with  PASW  Statistics  18  software  version  18.0.0 (55).  We  conducted  separate  multinomial  logistic regressions  for  each  immigrant  group:  1)  all  immigrants;  2)  Pakistani  background;  3)  Turkish  background; and 4) Tamil/Sri Lankan background. Ethnic  Norwegians  were  the  reference  group  for  all four immigrant groups, and results were reported as odds ratios (ORs) with 95% confidence intervals.

## Missing Data

The  Mplus  software  uses  a  full  information  maximum  likelihood  estimation,  which  is  a  widely  accepted  way  of  handling  missing  data  (56;57).  The covariance  coverage  for  all  variables  ranged  from 97.2%  to  99.1%,  which  was  well  above  minimum threshold  needed  to  establish  adequate  coverage (54). Four subjects were excluded from the analyses because their answers were missing in all indicators. Missing value analysis and an expectationmaximization algorithm were used to impute missing values for covariates with the use of PASW Statistics 18 (55).

## Results

An overview of the sample is presented in Table 1, which shows that 47% of the sample had immigrant backgrounds. This means that minorities were overrepresented in line with the recruitment strategy of the  YCC.  The  largest  minority  groups  were  from Pakistan (14%), which was followed by Turkey (5%) and Sri Lanka (5%). Of those recruited through cultural centers, 18 preadolescents with Turkish backgrounds (40% of the Turkish sample) and 4 with Sri Lankan  (Tamil)  backgrounds  (9%  of  the  Tamil sample) completed the questionnaire.

TABLE  1. Distribution of categorical variables included  in the analyses (N = 898)

| Factor                   | Categories                   |   Frequency |   Percentage |
|--------------------------|------------------------------|-------------|--------------|
| Gender                   | Boys                         |         451 |         50.2 |
| Gender                   | Girls                        |         447 |         49.8 |
| Ethnic status            | Immigrant                    |         425 |         47.3 |
| Ethnic status            | Non-immigrant                |         473 |         52.7 |
| National                 | Norway                       |         474 |         52.7 |
| background               | Pakistan                     |         129 |         14.4 |
| background               | Turkey                       |          45 |          5.0 |
| background               | Sri Lanka                    |          43 |          4.9 |
| background               | Other (37 countries)         |         198 |         22.9 |
| Grade level (approx.     | Fifth grade (10 years old    |         269 |         30.0 |
| age)                     | Sixth grade (11 years old)   |         336 |         37.4 |
| age)                     | Seventh grade (12 years old) |         293 |         32.6 |
| City                     | Oslo                         |         713 |         79.4 |
| City                     | Bergen                       |         185 |         20.6 |
| Location of data collec- | Classroom                    |         876 |         97.6 |
| tion                     | Ethnic center                |          22 |          2.4 |
| Immigrant                | First generation             |         132 |         14.7 |
| generation               | Second generation            |         766 |         85.3 |
| Latent classes           | Healthy                      |         423 |         47.1 |
| Latent classes           | Borderline                   |         298 |         33.2 |
| Latent classes           | Distressed                   |         177 |         19.7 |

Non-immigrant and ethnic Norwegian groups are identical

Significant  immigrant  versus  non-immigrant  differences were observed for all emotional symptoms as well as for school hassles and parental achievement values  (Table  2).  These  were  not  found  for  economic hardship.

TABLE  2. Mean  scores,  standard  deviations,  and  effect  size  of  mean  group differences

| Variable                    | Immigrant ground Mean (SD)   | Ethnic Ma- jority Mean (SD)   |   Partial Eta- Squared |
|-----------------------------|------------------------------|-------------------------------|------------------------|
| Somatic                     | .69 (.73)**                  | .55 (.71)                     |                    .01 |
| Worries                     | .91 (.76)***                 | .63 (.71)                     |                    .03 |
| Unhappy                     | .50 (.66)*                   | .39 (.62)                     |                    .01 |
| Clingy                      | .87 (.72)**                  | .72 (.65)                     |                    .01 |
| Afraid                      | .61 (.73)***                 | .42 (.62)                     |                    .02 |
| School hassles              | 1.63 (.51)*                  | 1.55 (.45)                    |                    .01 |
| Parental achievement values | 4.40 (.65)***                | 3.96 (.68)                    |                    .10 |
| Economic hardship           | 1.21 (.41)                   | 1.29 (.49)                    |                   .001 |

The five emotional problem symptoms are listed first in the table. Among all listed  variables,  only  economic  hardship  showed  no  significant  group  difference. Partial eta-squared is the proportion of the variance in variables that is explained by immigrant background (as compared with ethnic majority background). * P < .05; ** P < .01; *** P < .001.

## Latent Class Analysis of Emotional Symptoms

The solutions with latent classes 1 through 4 were estimated  and  evaluated  for  fit  indices,  which  are shown  in  Table  3.  The  solution  with  three  latent classes  had  the  best  fit.  It  yielded  the  lowest  BIC, SSABIC,  Akaike  information  criterion,  and  log- likelihood  values  while  simultaneously  maintaining significant  Lo-Mendell-Rubin  likelihood  ratios  and bootstrapped  parameter  likelihood  values.  Moreover, the three-class solution was theoretically sound,  because  the  classes  clearly  indicated  symp- tom severity. The classes were accordingly denominated as 'healthy,' 'borderline,' and 'distressed.'

TABLE 3. Model fit indices for one to four class solutions of emotional symptoms (N = 889 preadolescents)

| Model         |   Log- Likelihood | Bayesian Informa- tion Criterion/ Sample-Size Ad- justed Bayesian Information Criterion   |   Akaike Informa- tion Crite- rion | Entropy   | Lo-Mendell- Rubin Likeli- hood   | Boot- strapped Parameter Likelihood   |
|---------------|-------------------|-------------------------------------------------------------------------------------------|------------------------------------|-----------|----------------------------------|---------------------------------------|
| One class     |             -4255 | 8578/8546                                                                                 |                               8530 | -         | -                                | -                                     |
| Two classes   |             -3991 | 8125/8058                                                                                 |                               8024 | 0.67      | 0.000                            | 0.00                                  |
| Three classes |             -3942 | 8102/8000                                                                                 |                               7984 | 0.62      | 0.004                            | 0.00                                  |
| Four classes  |             -3928 | 8149/8013                                                                                 |                               7942 | 0.66      | 0.110                            | 0.07                                  |

Bold text indicates the best fit. The solution with three latent classes had best fit

Although the entropy (0.62) of the three-class solution  was  modest,  the  average  diagonal  values  between  the  fitted  classes  and  the  class  assignments suggest that the classifications of healthy (0.87) and distressed  (0.90)  were  good  (53).  This  means  that those assigned to the healthy and distressed classes had a respective probability of 87% and 90% of actually  belonging  to  their  assigned  classes.  For  the borderline class, the probability of correct classification  assignment  was  lower  (73%)  than  that  of  the two other classes.

## Characteristics of the Classes

The  healthy  class  comprised  a  group  of  children with few emotional problems and represented 47% of the sample (Figure 1). These preadolescents had the  lowest  probabilities  of  fully  endorsing  somatic complaints  or  worries  (both  7%)  and  feeling  unhappy (1%). The borderline class represented 33% of the total sample. The response patterns of these participants were  characteristic of a partial endorsement of emotional symptoms. This class  had moderate probabilities with regard to falling into the bottom  quartile  for  emotional  symptoms;  these ranged from a probability of 44% of being afraid to a probability of 18% for being clingy. On a general basis,  however, the  borderline  class  had  low  probabilities  of  fully  endorsing  emotional  symptoms, which ranged from 12% for somatic symptoms to 0% for being clingy.

The distressed class represented 20% of the total sample and had the highest probabilities for falling into  the  top  quartile  on  all  emotional  symptoms; this  ranged  from  a  probability  of  55%  for  being worried and clingy to a 29% probability of feeling unhappy. In light of these results, the main distinction of these classes was the severity rather than the type of emotional problem (i.e., depression vs. anxiety).  Because  the  contrast  between  the  distressed and healthy subgroups is both clinically relevant and statistically  robust  (due  to  the  lower  probability  of correct class assignment  in  the  borderline  subgroup), the next section focuses on the comparison between the distressed and healthy subgroups.

## Predictors Associated With Each Class

Table 4 presents the OR estimates and confidence intervals for class membership in relation to predictors as derived with latent class multinomial logistic regression models. The OR indicates the estimated odds of belonging to the distressed class relative to the healthy class (the reference class).

TABLE 4. Odd ratios and confidence intervals for predictors comparing the distressed and healthy subgroups, controlled for risk factors

|                                         | Groups                                              |                                                       | Turkish Background vs. Ethnic Norwegians 2   | Sri Lankan Background vs. Ethnic Norwegians   |
|-----------------------------------------|-----------------------------------------------------|-------------------------------------------------------|----------------------------------------------|-----------------------------------------------|
| Distressed Versus Healthy Subgroup      | All Immi- grants vs. Ethnic Nor- wegians R 2 = 0.16 | Pakistani Background vs. Ethnic Norwegians R 2 = 0.19 | R = 0.16                                     | R 2 = 0.18                                    |
| Immigrant group vs. ethnic Nor- wegians | 1.82** (1.18-2.81)                                  | 2.26* (1.18-4.34)                                     | 2.62* (1.02-6.68)                            | 3.19* (1.25-8.15)                             |
| Girls vs. boys                          | 2.22***                                             | 2.36***                                               | 2.68***                                      | 2.50**                                        |
|                                         | (1.49-3.31)                                         | (1.41-3.97)                                           | (1.53-4.70)                                  | (1.42-4.38)                                   |
| School has- sles                        | 2.54*** (2.07-3.13)                                 | 3.06***                                               | 2.51***                                      | 2.93***                                       |
| sixth grades vs. seventh                | 1.74* (1.05-2.88)                                   | (2.33-4.01) 1.50 (0.79-2.83)                          | (1.90-3.33) 1.37 (0.69-2.70)                 | (2.19-3.93) 1.65 (0.81-3.34)                  |
| Fifth and                               |                                                     |                                                       |                                              |                                               |
|                                         |                                                     | 1.20                                                  | 1.18                                         |                                               |
| Economic                                | 1.25*                                               |                                                       |                                              | 1.18                                          |
| hardship                                | (1.03-1.52)                                         | (0.94-1.53)                                           | (0.92-1.51)                                  | (0.92-1.51)                                   |

Predictors  implicated  in  distinguishing  between  the  distressed  and  healthy classes  are  similar  in  the  three  largest  immigrant  groups.  City,  parental achievement values, and the other dummy variables for grade level (fifth and seventh  grades)  did  not  reach  significance  in  any  of  the  immigrant  group comparisons  and  were  excluded  from  the  table.  Significance  was  vertically tested within groups. * P < .05; ** P < .01; *** P < 0.001

8.5

8.0

7.5

7.0

6.5

6.0

5.5

5.0

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

All immigrants

· Unadjusted

Figure 1. Class probability of endorsing each of the three alternatives ('Not true', 'Partly true, and 'Not true at all') for each of the five emotional symptoms. A, Probability of symptom absence. B, Probability of some symptom presence. C, Probability of strong symptom presence

<!-- image -->

When  collapsing  a  population  as  heterogeneous immigrants into one group, the question of whether findings are representative across immigrant groups arises.  Accordingly,  findings  were  tested  across  the three  largest  national  groups  in  the  sample  (those with Pakistani, Turkish, and Sri Lankan backgrounds), whereas ethnic Norwegians were kept as the reference group. As seen in Table 4, analyses of specific  minority  groups  are  coherent  in  terms  of OR  sizes  and  the  statistical  significance  of  values with  findings  that  apply  to  immigrant  groups  in general,  with  two  exceptions.  These  exceptions are grade level and economic hardship, which are only significant  in  the  collapsed  immigrant  group.  The reason  seems  to  be  the  small  sample  sizes  of  the separate immigrant groups. Apart from these exceptions, immigrant-group-specific findings support the results.

The effect of immigrant background on membership  in  the  distressed  class  as  compared  with  the healthy class remained quite stable in the ORs that were not adjusted for other factors (Figure 2). The ORs adjusted for ethnic background as it relates to distressed latent class membership are presented in Table 3 after having been adjusted for gender, grade level,  economic  hardship,  school  hassles,  city,  and parental  achievement  values.  The  significance  of ORs was calculated vertically in Table 3 in four vertically adjusted models (i.e., all immigrants, Pakistani immigrants,  Turkish  immigrants,  and  Sri  Lankan immigrants).

Briefly, the main findings were as follows: 1) minority  preadolescents  are  about  twice  as  likely  as ethnic Norwegians preadolescents to belong to the distressed class as compared with the healthy class; 2) school hassles increase the odds of belonging to the distressed subgroup by about 2.5 times; and 3) these results were robust across three specific immi- grant  groups  in  the  sample:  those  from  Pakistan, those from Turkey, and those from Sri Lanka.

Figure  2. Odd  ratios  and  confidence  intervals  for  membership  in  the  distressed  class  as  compared  with  the  healthy  class  for  different  immigrant groups

<!-- image -->

## Discussion

The  identification  of  the  healthy,  borderline,  and emotionally distressed classes implies that there are primarily  quantitative  rather  than  qualitative  differences in emotional problems, at least when they are measured by the emotional symptoms scale during preadolescence.  This  finding  also  suggests  that  the expression  of  emotional  problems  may  be  similar across  ethnic  status.  However,  it  is  possible  that there would be different latent classes with an older sample, because emotional problems tend to differentiate during  adolescence  and  adulthood  from emotional problems into more specific depression, anxiety,  or  both.  Hence,  this  is  a  relevant  question to investigate in future studies.

The  classes  found  in  this  study  are  in  line  with comparable LCA studies of adults that have found classes based on the severity of the emotional symptoms or disorders being investigated (4-6). In addi- tion  to  severity,  some  of  these  studies  have  found specific  classes  on  the  basis  of  the  type  of  symptoms  (4;6).  LCA  studies  of  children's  emotional problems and disorders are scarce, although a recent study  did  investigate  depressed  mood  among  adolescent  psychiatric  outpatients  (58).  There  are  also LCA studies  related  to  children's  emotional  problems, such  as adolescent life events  and  posttraumatic stress disorder (58), as well as to psychosocial  risks  and  psychiatric disorders (32;60). Many of the identified classes in these studies were characterized  by  symptom  severity,  as  they  were  in  the present study. In addition, at least one of the classes in  these  other  studies  was  characterized  by  symptom  type;  this  did  not  occur  in  the  present  study. This contrast may be a result of the measure used to identify  emotional  problems  in  the  present  study not  being  sensitive  enough  to  distinguish  between classes,  or  it  may  be  because  the  other  LCA  child studies  were  not  truly  comparable  to  the  present study  (i.e.,  because  of  different  phenomena  being investigated or the psychiatric sample).

The effects of school hassles and economic hardship appear to be rather consistent in terms of ORs across  immigrant  groups.  This  suggests  that  children  of  immigrants  --  and  probably  those  of  nonWestern immigrants in particular -- may be prone to similar risks for emotional problems. The causes of these risks are unknown at this stage, although they may be associated with lower socioeconomic status, physical salience from the majority phenotype predisposing these individuals to discrimination, a larger  strain  on  the  family  due  to  reduced  social  network,  and  lower  parental  understanding  of  the  resources available in the society and of guiding their children  into  the  majority  institutional  system,  including schools (7;28). The factors involved in these risks raise important questions for future studies.

These  findings  suggest that during preadolescence,  ethnic  immigrant  minorities  are  about  twice as  likely  to  be  among  the  most  emotionally  distressed  preadolescents.  This  may  have  important implications, because emotional problems are often silent, non-disruptive, and likely to go unnoticed by teachers  and  parents  (61).  Even  when  parents  and teachers  do  notice  emotional  problems,  teachers may  underreport  these  problems  in  minority  children as compared  with  majority children (62). Among  traditional  non-Western  groups  with  low socioeconomic  statuses,  there  are  high  levels  of stigma concerning mental health issues (63;64). The relatively low likelihood of preadolescents with emotional  problems  getting  help,  which  is  even lower among children of immigrants, calls for special  attention  from  teachers,  parents,  and  other health care workers who are in contact with preadolescents in Norway.

## Limitations

This  study  provides  a  relevant  contribution  to  the research on immigrant mental health in Scandinavia, but  it  has  some  limitations.  First,  the  outcome  of emotional  problems  and  risk  factors  in  terms  of school hassles and parental achievement values were measured at the same time. This causes uncertainty regarding  whether  risk  factors  in  fact  temporally preceded emotional problems. The heightened odds of  children  of  immigrants  belonging  to  the  distressed class may be the result of unknown factors that  were  not  accounted  for  in  the  present  study. Second,  this  study  relies  only  on  self-reports  from preadolescents, whereas other sources (e.g., parents, teachers)  could  have  provided  additional  information about the latent classes of emotional problems among  preadolescents.  Third,  we  cannot  be  sure that  the same phenomena are underlying the emotional  symptoms  reported  by  both  children  of  immigrants and children of non-immigrants. Children of immigrants may report more extreme values, but this  does  not  imply  that  these  values  reflect  more severe  problems.  In  addition,  language  problems may influence  the  reports  of  immigrant  preadolescents,  because  the  questionnaire  was  administered in Norwegian. Fourth, the sample is not fully representative  of  the  population  at  either  the  national level or the municipal level. A sample size of 43 (the size  of  the  Sri  Lankan  immigrant  sample  in  this study)  is  small,  so  we  must  be  cautious  before  extrapolating  conclusions  from  the  sample.  Furthermore,  these  immigrant  populations  are  not  ethnically homogeneous. For instance, the Turkish population  in  Norway  consists  of  a  Kurdish  ethnic  minority.  These examples support the need for more knowledge of the emotional health of these groups; however, this study serves as a foundation for and contribution to such studies. It should also be noted that  the  sample  was  recruited  from  urban  settings and  thus  the  present  results  could  differ  substantially from those obtained in rural areas (37). In addition, factors such as family structure, support, and the  ethnic  composition  of  schools  and  neighborhoods may influence  mental  health  (7;8;28).  These variables are not included in the present study.

Alternatively, this study does have some noteworthy strengths.  Young  immigrants  are  rarely  addressed  in  LCA  studies  of  emotional  problems,  if they  are  represented  at  all.  By  contrast,  this  study employed  a  sample  that  included  47%  of  participants  with  immigrant  backgrounds.  Although  the size of some immigrant groups was too small to examine  separately,  conclusions  could  be  drawn  for the three largest immigrant groups in the sample. It is  important  that  mental  health  research  includes  a diversity of persons, including immigrants, who represent  a  substantial  and  growing  segment  of  the country's  population.  Researchers  who  study  minorities face additional challenges as compared with peers who do not study a specific population. These include  recruitment  issues  such  as  translation  fees, persuading  immigrant  parents  of  the  importance and  voluntary  nature  of  participating  in  mental health  surveys,  and  ethical  concerns  related  to  potentially stigmatizing findings. These challenges certainly  add  difficulty  to  the  attaining  of  knowledge about  the  mental  health  of  immigrants,  but  they surely do not alter the importance of including these groups  in  mental  health  research.  Despite  the  sole reliance  on  self-reports  being  a  limitation  of  this study,  self-reports  may  indeed  be  the  best  option for attaining information about preadolescents' emotional problems if only one source can be used (i.e.,  either  teacher  report,  parent  report,  or  selfreport  from  the  preadolescent  himself  or  herself) (61;65;66). However, there are exceptions (67).

Although it may be questioned whether the findings from the current study are nationally representative,  they  do  suggest  that  certain  immigrant  preadolescents in multi-ethnic urban neighborhoods in Norway have higher odds of being emotionally distressed. In addition, these findings are supported by other  studies  of  adolescents  in  Norway  (27),  although there are some exceptions (14;68). The participation  rate  appears  to  have  been  higher  for  the ethnic majority in this study, which indicates that a higher rate of participation among immigrants could possibly inflate the latter group's emotional problem scores. This is because non-participation tends to be more  common  among  the  most  distressed  participants, who have a higher likelihood of not attending school during data collection and of not delivering consent forms to parents and teachers (69). When comparing  the  magnitude  of  immigrant  and  nonimmigrant ORs of belonging to the distressed class as compared with the healthy class, the clinical relevance  of this study is substantial.  However,  it should be noted that there is substantial variability in the immigrant sample, because the ORs of emotional  symptoms  in  the  total  immigrant  group  are lower  than  those  of  the  three  specific  immigrant groups.  This  indicates  that,  in  the  adjusted  model, the three specific groups are among the most emotionally distressed immigrant groups in the sample. In  the  unadjusted  model,  ORs  for  the  total  immigrant  group  seem  to  reflect  the  fluctuations  in  the ORs  of  the  three  specific  immigrant  groups  (see Figure 2). In addition, this study's findings indicate that  the  silent  burden  of  emotional  problems  may already  be  more  prominent  during  preadolescence among  immigrants  and  their  children  than  among non-immigrant children in urban multi-ethnic schools.  The  present  results  and  analysis  suggest that  future  studies  should  investigate  the  possible mechanisms implicated in this overrepresentation of children of immigrants among the emotionally distressed.  Meanwhile,  parents,  teachers,  and  others who  work  with  preadolescents  should  join  forces with researchers to formulate hypotheses regarding the possible reasons that immigrant preadolescents from  as  different  backgrounds  such  as  Pakistan, Turkey,  and  Sri  Lanka  demonstrate  a  profile  of emotional  problems  and  related  factors  that  is  so similar compared to non-immigrant preadolescents. In addition, parents, teachers, and health care workers who routinely interact with preadolescents should remain attentive so that they can recognize and advocate for those children who suffer with this silent burden.

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