Soc Psychiatry Psychiatr Epidemiol DOI 10.1007/s00127-013-0782-z
ORIGINAL PAPER
School effects on risk of non-fatal suicidal behaviour: a national multilevel cohort study ¨ stberg • Anders Hjern Beata Jablonska • Viveca O Lene Lindberg • Finn Rasmussen • Bitte Modin
•
Received: 2 January 2012 / Accepted: 14 October 2013 Ó Springer-Verlag Berlin Heidelberg 2013
Abstract Objective Research has demonstrated school effects on health, over and above the effects of students’ individual characteristics. This approach has however been uncommon in mental health research. The aim of the study was to assess whether there are any school-contextual effects related to socioeconomic characteristics and academic performance, on the risk of hospitalization from non-fatal suicidal behaviour (NFSB). Methods A Swedish national cohort of 447,929 subjects was followed prospectively in the National Patient Discharge Register from the completion of compulsory school in 1989–93 (&16 years) until 2001. Multilevel logistic regression was used to assess the association between school-level characteristics and NFSB. Results A small but significant share of variation in NFSB was accounted for by the school context (variance partition coefficient \1 %, median odds ratio = 1.26). The risk of NFSB was positively associated with the school’s proportion of students from low socioeconomic status (SES), single parent household, and the school’s average academic performance. School effects varied, in part, by school location.
B. Jablonska (&) L. Lindberg F. Rasmussen Centre for Epidemiology and Community Medicine, Stockholm County Council, 1497, 17129 Stockholm, Sweden e-mail: [email protected] B. Jablonska L. Lindberg F. Rasmussen Department of Public Health Sciences, Karolinska Institutet, 17177 Stockholm, Sweden ¨ stberg A. Hjern B. Modin V. O Centre for Health Equity Studies (CHESS), Stockholm University, Karolinska Institutet, 10691 Stockholm, Sweden
Conclusion NFSB seems to be explained mainly by individual-level characteristics. Nevertheless, a concentration of children from disadvantaged backgrounds in schools appears to negatively affect mental health, regardless of whether or not they are exposed to such problems themselves. Thus, school SES should be considered when planning prevention of mental health problems in children and adolescents. Keywords Sweden Contextual effect School Multilevel model Non-fatal suicidal behaviour
Introduction School plays an important role in a child’s academic, social and emotional well-being [1]. Despite this, little attention has been paid to school as a potentially significant unit for assessing contextual effects on young people’s mental health [2]. One of the most serious consequences of mental health problems is non-fatal suicidal behaviour (NFSB). NFSB is a matter of concern both in its own right and as significant predictor of future suicidal behaviours and completed suicides [3]. Particularly worrisome is the national and international statistics pointing to a growing prevalence of NFSB in young people [4, 5]. The understanding of pathways through which the school context influences mental health is crucial for identifying potential avenues for intervention. Multilevel studies using neighbourhood as the level of analysis have shown a negative association between children’s mental health and environmental characteristics such as low average socioeconomic status (SES), high concentration of unemployed people, single parents and immigrants [6–8].
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However, little is known whether these characteristics play an independent role also within the smaller contextual unit that the school constitutes. Previous research has provided some evidence in support of the idea that mental health may vary as a function of the school’s academic context [9–11]. At an individual level, poor school performance is an important predictor of mental health problems [11–13]. Furthermore, a high proportion of poor performers is known to co-occur with a school climate characterized by low sense of connectedness, inclusion, and social support [14]. These features could also be assumed to have an overall negative effect on the mental health of students attending such a school, independently of their individual academic achievements [15]. A contrasting assumption would be that students at a certain performance level may assess themselves higher in a low-performing than in a high-performing context, thus leading to an overall positive effect on mental health of attending poor-performing schools. The school context fosters social comparison and it is well documented that students’ academic self-concept, which is a predictor of mental health and suicidal behaviours [16], is inversely related to the achievement level of other students in the same school [17]. There is also a lack of knowledge as to how any such school effects may vary according to the specific type of school setting. Urban, suburban and rural schools each function within a unique demographic, cultural and social context that may exacerbate the positive or negative impact of school effect [18]. In summary, the evidence demonstrating school effects on health, in addition to individual risk factors, is beginning to mount. This approach however has not been widely adopted in mental health research. The aim of this study is to assess whether there are any school-contextual effects on mental health, measured as hospitalization due to NFSB, and to what extent any such effect can be explained by individual- and school-level socioeconomic characteristics and academic performance. Since the communities where the schools are located differ in their level of urbanization and socio-economic composition, we also investigate whether the influences of individual- and school-level characteristics on mental health vary by school location.
Methods This study was based on data from national registers held by the Swedish National Board of Health and Welfare and Statistics Sweden. The key to these registers is the unique personal identification number, which was used to link data from the registers to each participant. The study was
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approved by the regional ethics committee at Karolinska Institutet, Stockholm, Sweden. Study population The study population consisted of individuals born between 1973 and 1977 (n = 491,258) who were registered as residents in the Swedish Population and Housing Census of 1985 and who attended the ninth grade of compulsory school in 1989–93. These are the first five birth cohorts in the National School Register—the Swedish national data source for information about school performance. Individuals were followed up in the National Hospital Discharge Register from the time of graduation until the end of 2001. Subjects were censored at the date of death (retrieved from the National Cause of Death Register), date of emigration (retrieved from the Register of the Total Population) or at the end of follow-up. Individuals who had been admitted to a hospital due to a psychiatric disorder and/or NFSB before the completion of ninth grade (n = 1,670) were excluded. Excluded subjects had a similar grade point average as included subjects with a corresponding hospital admission (2.84 versus 2.87 on the scale ranging from a minimum of 1.0 to a maximum of 5.0). Grade point average was calculated on the basis of the 17 existing school subjects in Sweden at the time. Individuals who lacked marks in three or more subjects (n = 7,062) were excluded because of their unreliable grade point average, as were foreign-born children (n = 34,597) because of the negative influence of migration on school performance [19]. Schools in which the total number of 9th grade students in the years studied was B10 (n = 213) were also excluded. The largest school, in terms of 9th grade enrolment between 1989 and 1993, had 1,121 students and the smallest had 11 students. Cases with missing data were excluded, yielding a study population of 444,769 persons. Outcome variable The outcome variable—first-time hospital admission due to ‘‘self-inflicted poisoning or injury/suicide (attempted)’’ [tenth revision of the International Classification of Diseases (ICD-10)]—was obtained through individual record linkage to the National Hospital Discharge Register from 1989 to 2001. Hospital admission involves staying at a hospital for at least one night. NFSB was defined according to the World Health Organization (WHO) ICD-9 (intentional self-harm E950–959 and event of undetermined intent E980–989) during 1989–96 and ICD-10 (intentional self-harm X60–84 and event of undetermined intent Y10–34) during 1997–2001.
Soc Psychiatry Psychiatr Epidemiol
Individual-level variables
School-level variables
School performance
School-level variables included grade point average, percentage of girls, students with a foreign background, students with low parental SES, students living with a single parent, and students having a mother with low education. These variables were constructed by aggregating data from the student level to the school level. For example, individual-level grade point averages were aggregated so that each student was attributed the grade point average at their respective school.
Data were retrieved from the National School Register on grade point averages at the time when Swedish students leave compulsory school (usually at 16 years of age). This register encompasses data from all public schools since 1988, and also data from all non-public ([5 %) schools since 1993. Until 1996, a five-graded relative scale was used in the Swedish school system, supervised by the Swedish School Authority through national tests in core subjects. The quality of the data in the National School Register is high and summary statistics are published regularly. Grade point average for the sample ranged from a minimum of 1.0 to a maximum of 5.0, Mean = 3.2, SD = 0.7. For descriptive purpose only, a dichotomous variable was also created that classified participants as ‘‘low performers’’ (i.e. grade point average below the mean) versus ‘‘high performers’’ (i.e. grade point average at or above the mean).
Socio-demographic variables Socio-demographic indicators were created through linkage to the Swedish Population and Housing Census of 1985: year of birth, sex, ethnicity, SES of the household, single parent household, and geographical location of the school attended. Information about parental country of birth was used to create a three-category proxy for ethnicity: Swedish (both parents born in Sweden), nonSwedish (neither parent born in Sweden) and mixed (one parent born in Sweden and one parent born in another country). SES was defined according to the classification used by Statistics Sweden, which is based on occupation and considers the occupation’s required level of qualification, type of production and position of work of the head of the household. Six categories of SES were created: unskilled workers, skilled workers, lower-level nonmanual, middle-level non-manuals, higher-level nonmanuals and others (i.e. the self-employed, farmers, students, housewives, old age/sickness disability pensioners, long-term unemployed). The highly heterogeneous composition of the SES category ‘‘other’’ was due to the relatively small numbers of individuals belonging to each subcategory. Data on maternal education were obtained from the Swedish Educational Register (if available from the register of 2001, otherwise from the registers of 1995 or 1990) categorized as short (B11 years), medium (12–13 years), long (14–15 years) and very long (C16 years).
Statistical methods In this study, two-level logistic regression models (random intercept) with students at level one and schools at level two were used, and computations were carried out using MLwiN 2.10 [20]. Random intercepts models provide estimates of the fixed effects of the predictor variables (i.e. the effects of explanatory variables are assumed to be constant across schools upon the outcome variable). The fixed effects are expressed as odds ratios (OR). The first step of the analyses was to run a so-called empty model with no exposure variable to obtain the unexplained variance in NFSB between schools. Three additional models were fitted. The first model included all the individual-level characteristics, and in the second model school-level variables were also added to the model, enabling us to assess the effects of school-level characteristics after the influence of individual-level characteristics had been accounted for. The second model also contained interactions between school region and individual-level/school-level grade point average as well as interaction tests for individual- and school-level grade point average. Tests for cross-level interactions were carried out to explore whether the effect of individual grade point average on the risk of NFSB varied across schools depending upon their overall grade point average. Twolevel logistic regression models were also run separately for three types of school regions (big cities, smaller cities and rural areas) (Model 3a, b, and c). We calculated the variance partition coefficient (VPC) to estimate the proportion of total variance in the outcome attributable to the school level and the proportional change in variance (PCV) comparing the empty model with the models including the selected individual- and school-level variables. The simulation method provided by MLwiN was used to calculate VPC. According to the recommendation of Larsen and Merlo [21], we also used the median odds ratio (MOR), as an alternative measure of the school variance, which unlike VPC is not dependent of the prevalence of the outcome. The MOR method translates the area
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level variance in an odds ratio scale and measures the school variance as an OR. In this study, MOR estimates the individual risk of NFSB (in median) that can be attributed to the school context. MOR equal to one indicates no school variance. The higher the MOR, the more important are the school effects for understanding the individual probability of risk of NFSB.
Results Information on percentage or means of the variables included in the study is presented in Table 1. The first group of variables was assessed at the individual level. The next group of variables addresses the same aspects as those accounted for at the individual level, but on the school level, with each student given the mean value of their respective school. The study population was 48.6 % female and the majority was Swedes and lived with two parents. More than 50 % came from non-manual backgrounds and mothers of onethirds of the students had short education. Slightly more than 50 % of the study population lived in smaller city areas and around one-fourth in big city or rural areas. Schools ranged from being completely homogenous concerning ethnic composition and family structure to being very mixed. Table 1 also shows individual- and school-level characteristics stratified by NFSB. A total of 4,740 individuals were hospitalized due to NFSB at least once during the study period. Hospital admission due to NFSB was more common among females than among males. It was also more frequent among students with a non-Swedish background, low parental SES, maternal education B13 years, and among students living in single parent households. Furthermore, self-injurious persons had a lower grade point average than the population as a whole. Hospital admission because of NFSB was slightly more common in schools with higher than average proportions of students with a foreign background, low parental SES and single parents. Table 2 shows the results of the multilevel analyses. The empty model with no predictors indicates that the risk of NFSB varies significantly between schools (p \ 0.001) with a variance of 0.061 and a VPC of 0.0007. The latter number is very low, suggesting little school-contextual variation in NFSB. Median odds ratio for empty model was 1.26. Thus, if randomly picked student moved from one school to another with higher prevalence of NFSB, then his/her odds of NFSB would, in median, increase with 1.26. The individual-level model for NFSB (Model 1) points to an increased risk among females, individuals with a nonSwedish background and those from single parent households. Students from lower non-manual background run a
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lower risk of NFSB in relation to those with highest nonmanual social class background, whereas no significant excess risk was found for the skilled/unskilled worker background. Maternal education\16 years was related to a decreased risk of NFSB compared to the reference category. The positive associations between maternal education and NFSB appeared only after the inclusion of grade point average in the model. Grade point average and the risk of NFSB were inversely associated: a one-unit increase in grade point average was associated with a considerable decrease in NFSB corresponding to an odds ratio of 0.4. The inclusion of these individual-level predictors reduced the between-school-level variance by 40 %, but significant variation in NFSB between schools still remained. The corresponding school-aggregated information for the individual-level variables is presented in Model 2. Thus, school-level predictors included proportion of students with a foreign background, low parental SES, living with a single parent, having a mother with low education and school grade point average. The findings indicate that, regardless of their individual social characteristics, students who attend schools with a high proportion of pupils from lower social classes (OR = 1.01) and from single parents households (OR = 1.02) are more likely to self-injure themselves than those who attend schools with a lower proportion of such students. In all analyses, including those performed separately for the three school regions (Table 3), attending a school with a high concentration of pupils from single parent household consistently emerged as a significant predictor of NFSB. Contrary to what one might expect, the higher the grade point average of the school attended, the higher the odds risk of NFSB (OR = 1.39) when individual-level grade point average had been taken into consideration in the analysis. A significant interaction between school region and individual grade point average as well as between school region and school-level grade point average was also found. These results indicated that the higher the individual grade point average and the lower the urbanization level of the school region, the lower was the risk of NFSB, whereas the opposite appeared to be true for the school-level grade point average. With the additional inclusion of these interactions in the model, the variance between schools was further reduced but remained significantly different from zero. The interactions were further examined by regressing NFSB on student and school GPA within each school region (Table 3). The empty models for all three school regions revealed that, in the absence of any predictor variables, variation in the risk of NFSB differed significantly between schools. The amount of clustering of NFSB within schools appeared to be higher in big cities than in small cities and rural regions. However, with the inclusion
Soc Psychiatry Psychiatr Epidemiol Table 1 Individual- and school-level characteristics and their distribution by hospital admission due to NFSB from graduation in 1989–93 to 2001 Student level
Number of participants
(%)
Hospitalization due to NFSB (%)
Man
228,636
51.4
0.7
Women
216,133
48.6
1.4
388,425
87.3
1.0
25,273
5.7
1.4
31,071
7.0
1.8
Higher-level non-manuals
86,733
19.5
0.8
Middle-level non-manuals
102,843
21.1
0.9
Lower-level non-manuals
56,736
12.8
1.0
Skilled workers
72,051
16.2
1.2
Unskilled workers
63,640
14.3
1.5
Other
62,766
14.1
1.3
No
371,008
83.4
0.9
Yes
73,761
16.6
1.9
53,825
12.1
0.8
Sex
Ethnicity Swedish Non-Swedish Mixed Parental SES
Single parent household
Mother’s education Very long Long
95,091
21.4
0.8
138,493
31.1
1.2
Short School region
157,360
35.4
1.2
Big city area
113,422
25.2
1.1
Smaller city area
231,733
52.1
1.1
99,614
22.4
1.0
Medium
Rural area
3.24a
Grade point average
2.87a
Low grade (below the mean)
220,333
49.5
1.5
High grade (at or above the mean)
224,436
50.5
0.7
School level
Range
Mean
Mean for schools with students hospitalized for NFSB
% Of girls at the school
12–69
48.6
48.6
% With a foreign background
0–94
12.7
13.9
% With low parental SES
14–92
44.6
45.3
% Living with a single parent
0–72
16.6
17.9
% Having a mother with low education
0–72
35.4
35.9
Grade point average
2.36–3.93
3.24
3.23
Low (below the mean)
2.36–3.23
3.16
3.16
High (at or above the mean)
3.24–3.93
3.34
Number of students
444,769
4,740
Number of schools
1,121
995
a
3.33
Mean
of explanatory variables, the between-school variance in NFSB decreased to an insignificant level in all of the three studied regions.
VPC for the three school regions ranged from 1.2 % in big cities to 0.4 % in smaller ones. Although these numbers are small, the MOR estimate amounts to 2.55, indicating
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Soc Psychiatry Psychiatr Epidemiol Table 2 Random intercept model for two levels: odds ratios and confidence intervals of hospital admission due to NFSB from compulsory school graduation (1989–93) until 2001 according to individual- and school-level factors
Sex: women (versus men)
Model 1 All
Model 2 All
2.62*** [2.46–2.79]
2.62*** [2.46–2.77]
1
1
Ethnicity Swedish Non-Swedish
1.64*** [1.46–1.85]
1.54*** [1.37–1.74]
Mixed
1.39*** [1.27–1.52]
1.36*** [1.24–1.49]
Higher-level non-manuals
1
1
Middle-level non-manuals
0.98 [0.88–1.09]
0.98 [0.88–1.09]
Parental SES
Lower-level non-manuals
0.87* [0.77–0.98]
0.87* [0.77–0.98]
Skilled workers
0.94 [0.75–1.18]
0.95 [0.84–1.06
Unskilled workers Other
0.94 [0.84–1.06] 1.04 [0.92–1.16]
0.95 [0.84–1.07] 1.04 [0.93–1.17]
1.61*** [1.50–1.72]
1.53*** [1.43–1.64]
Single parent household Mother’s education Very long
1
1
Long
0.86** [0.75–0.97]
0.88** [0.77–0.99]
Short
0.94 [0.83–1.06]
0.96 [0.85–1.08]
Very short
0.87* [0.77–0.99]
0.87* [0.78–0.99]
0.40*** [0.39–0.42]
0.40*** [0.39–0.42]
Grade point average (GPA) % With a foreign background
1.00 [0.99–1.00]
% With low parental social class
1.01** [1.00–1.02]
% Living with a single parent
1.02*** [1.01–1.02]
% Having a mother with low education
1.00 [0.99–1.00]
School grade point average (SGPA)
1.39 [1.00–2.07]
School region Big city area Smaller city area
1.01 [0.92–1.20] 1.04 [0.97–1.16]
Rural area
1
Interaction terms School region*School GPA
p \ 0.001
All models are adjusted for year of birth
School region*Student GPA
p \ 0.001
* Significant at the 5 % level (p B 0.05)
Variance between schools (empty model)
0.061***
0.061***
Variance between schools (current model)
0.036***
0.023*
** Significant at the 1 % level (p B 0.01)
PCV
40.1 %
62.0 %
MOR (empty model)
1.26
1.26
*** Significant at the 0.1 % level (p B 0.001)
MOR (current model)
1.20
1.15
School GPA*Student GPA
substantial cluster heterogeneity in NFSB at the school level. The corresponding figures for small town and rural areas were 1.21 and 1.26. These effects decreased to 1.09 and 1.18, respectively, when individual- and school-level factors were added to the model. Individual-level predictors of NFSB in all three school regions were, in general, consistent with the overall results presented in Model 2. Higher school-level grade point average was associated with a higher risk of NFSB only in rural regions, as was percentage of students with foreign background and percentage of
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students with relatively well-educated mothers. The risk of NFSB was slightly increased with higher school-level grade point average in smaller cities, and slightly decreased in big cities, but neither association reached statistical significance. We also found a significant cross-level interaction between individual- and school-level grade point average in big city schools indicating that the inverse association between high individual-level grade point average and NFSB is more pronounced in schools where the grade point average is relatively high.
Soc Psychiatry Psychiatr Epidemiol Table 3 Random intercept model for two levels: odds ratios and confidence intervals of hospital admission due to NFSB from compulsory school graduation (1989–93) until 2001 according to individual-, school-level factors and school region Model 1a Big city area
Model 1b Smaller city area
Model 1c Rural area
2.68*** [2.38–3.02]
2.43*** [2.23–2.65]
3.08*** [3.56–2.63]
Swedish Non-Swedish
1 1.44*** [1.20–1.75]
1 1.54*** [1.29–1.83]
1 2.01*** [1.41–2.86]
Mixed
1.36*** [1.18–1.59]
1.42*** [1.25–1.61]
1.17 [0.92–1.48] 1
Sex: women (versus men) Ethnicity
Parental SES Higher-level non-manuals
1
1
Middle-level non-manuals
0.97 [0.81–1.16]
0.96 [0.83–1.12]
1.08 [0.83–1.40]
Lower-level non-manuals
0.90 [0.73–1.11]
0.88 [0.74–1.05]
0.77 [0.56–1.05]
Skilled workers
0.85 [0.68–1.06]
0.96 [0.81–1.13]
1.05 [0.80–1.37]
Unskilled workers
0.90 [0.72–1.12]
1.00 [0.85–1.18]
0.90 [0.68–1.19]
Other
0.92 [0.74–1.14]
1.17* [1.00–1.38]
0.97 [0.74–1.28]
1.54*** [1.36–1.75]
1.54*** [1.40–1.69]
1.47*** [1.25–1.72]
Single parent household Mother’s education Very long
1
1
1
Long
0.84* [0.68–1.00]
0.85* [0.74–1.00]
1.11 [0.79–1.55]
Short
0.97 [0.78–1.20]
0.91 [0.76–1.08]
1.08 [0.78–1.05]
0.94 [0.76–1.16] 0.44*** [0.41–0.48]
0.83* [0.70–0.99] 0.41*** [0.38–0.44]
0.91 [0.66–1.27] 0.34*** [0.31–0.38]
Very short Grade point average (GPA) % With a foreign background
1.00 [0.99–1.01]
1.00 [0.99–1.01]
1.02* [1.01–1.02]
% With low parental social class
1.01 [0.99–1.02]
1.01* [1.00–1.02]
1.01 [1.00–1.01]
% Living with a single parent
1.02*** [1.01–1.02]
1.02*** [1.01–1.03]
1.02*** [1.00–1.40]
% Having a mother with low education
1.00 [0.99–1.01]
0.99 [0.98–1.01]
0.99* [0.97–1.00]
0.96 [0.50–1.80]
1.32 [0.76–2.30]
7.79*** [3.10–19.50]
–
–
–
School grade point average (SGPA) Interaction terms School region*School GPA School region*Student GPA
–
–
–
School GPA*Student GPA
p = 0.007
ns
ns
Variance between schools (empty model)
0.097***
0.040**
0.061*
Variance between schools (current model)
0.010
0.014
0.029
PCV
89.7 %
65.0 %
52.5 %
MOR (empty model)
2.55
1.21
1.26
MOR (current model)
1.09
1.12
1.18
All models are adjusted for year of birth * Significant at the 5 % level (p B 0.05) ** Significant at the 1 % level (p B 0.01) *** Significant at the 0.1 % level (p B 0.001)
Limitations of the study This is, to our knowledge, the first study to explore the contextual effect of schools on the risk of NFSB in a large national cohort, but several limitations need to be kept in mind when interpreting these results. First, our study is restricted to the most severe cases of NFSB that required hospitalization. It cannot be taken for granted that the
school effects are similar in the—probably—less severe cases of NFSB not leading to hospitalizations. Secondly, data on hospital-based NFSC may be limited by selection bias related to socioeconomic factors and/or school performance. Hospital admissions because of NFSB, however, are predominantly medical emergencies because of poisoning (&86 % of intentional NFSB cases and &69 % of the cases categorized as ‘‘event of undetermined intent’’),
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which limits bias of this kind. Thirdly, the register-based design of this study did not allow for the control of mental health conditions that do not lead to inpatient care but that are known to increase the risk of NFSB (e.g. emotionally unstable personality disorder). Fourthly, we were not able to account for the intermediate level of nesting, i.e. classroom level, although there are some suggestions that this may be a more appropriate measure of clustering effect [15]. Finally, the measures of school effects were restricted to socioeconomic and academic characteristics. Inclusion of other dimensions of the school context, e.g. teacher support, would perhaps have resulted in a more comprehensive model of school effect on mental health.
Discussion In this study, we found significant school variation in risk of NFSB among graduated students. The variation was greater between schools in big city areas than between schools in other regions. Less than 1 % of the total variation of NFSB between schools was accounted for by the particular school attended suggesting that schools are very similar with respect to the prevalence of NFSB. It should be noted, however, that it is rather the standard than the exception that the amount of variation in individual-level mental health attributable to the school context is small [2, 11, 22]. In our study, the small variance at the aggregate level may additionally be accounted for by the character of the outcome. Calculation of VPC for rarely prevalent outcomes, e.g. NFSB, results in lower VPC than for outcomes that show the wider disparity in prevalence, despite a similar group variance. In contrast to VPC, the MOR is statistically independent of the outcome prevalence [23]. Using the information provided by the MOR as a measure of school variance, we found that, when randomly selecting two students from two different schools, the OR between the student at lowest risk and the student at highest risk was above 1.26 in half of the cases. Thus, the school context constituted a source of variation in risk of NFSB. This overall effect was, however, mostly driven by the high contextual variation in NFSB found in big city schools (MOR = 2.55). School-level SES, family structure and academic performance were associated independently with the risk of NFSB and explained part of the variation at the school level. Consistent with prior research, we found that, at the individual level, females, individuals with a non-Swedish background and those from single parent households were at higher risk of NFSB than comparisons [12]. Interpretation of the protective effect of shorter maternal education for NFSB is ambiguous, though the finding is consistent with a recent study from UK [24]. It seems unlikely that
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this protective effect is an artefact caused by statistical over-adjustment for socioeconomic variables since it is only manifest when school performance is introduced into the regression model. Thus, one explanation could be that children of less-educated mothers tend to face less pressure to succeed academically than children of highly educated mothers and, in consequence, they may be less at risk of the negative consequences that high educational expectations may have on mental health [25]. School performance was negatively associated with the outcome, but the strength of this relation depended upon characteristics of the school region. The lower the urbanization grade of the school region, the more pronounced was the inverse association between school performance on the individual level and NFSB. School grades thus seem more important for rural students than for students living in big city areas. Individuals who attended schools characterized by high proportions of students with low parental SES and single parent household had statistically significant excess risk of NFSB, above and beyond individual background. In addition, the latter emerged as a significant predictor of NFSB in all three school regions and its effect was not accounted for by other socioeconomic inequalities. These findings are consistent with prior studies suggesting that clustering of these social characteristics is an important higher level dimension that contributes to poor mental health [26–28]. Several explanations are possible for the association. High concentrations of disadvantaged students may hinder schools to organize their educational and social activities in ways which promote learning outcomes and well-being [14], with negative consequences for all the students attending a particular school. It is plausible that, due to economic or health problems [29], it may be more difficult for low SES and single parents to serve as positive role models, involve in school curricular and extracurricular activities and cooperate with teachers and other parents [30]. An insufficient proportion of adult role models surrounding the school milieu may have negative consequences that extend beyond the directly affected children. Students attending socially disadvantaged schools may also more often become exposed to behaviours that put them at risk of mental health problems, e.g. bullying [31, 32]. Relations with suicidal peers seem to be another type of exposure that account for the contextual effect of schoollevel disadvantage on adolescent NFSB behaviour [8]. While individual school performance was inversely related to NFSB, a positive association was found for school-level performance. Thus, students attending highperforming schools seemed to experience higher risk of NFSB. This finding is not supported by a recent Swedish study on multilevel influences on suicide risk [11], but in line with the few other studies that exist in this area [9, 10]. The separate analyses for the school regions revealed, that
Soc Psychiatry Psychiatr Epidemiol
the overall effect of school-level performance on NFSB was largely accounted for by the excess risk found in rural areas. The above finding is in accordance with theories on compositional effects, arguing that students who attend more advantaged schools may be harmed by the lower relative position they occupy in the school hierarchy (the so-called big-fish–little-pond effect) [17]. Why such effect is detectable only in rural and big city schools in the present study is not clear. It is plausible that such an effect may be strengthened by some unique features of the rural schools but this remains to be proven.
2.
3. 4.
5.
6.
Conclusions Our findings suggest that school-level factors explain only a small percentage of student’s risk of NFSB, and that differences in NFSB, therefore, mainly seem to be due to individual characteristics. We did demonstrate in this study, however, that a concentration of children from disadvantaged backgrounds in schools appears to negatively affect mental health, regardless of whether or not they are exposed to such problems themselves. Thus, school SES should be considered when planning prevention of mental health problems in children and adolescents. The pattern of association between school-level performance on NFSB was not consistent across school regions. What our findings suggest is that both the direction of the effect and mechanisms underlying the relationship may operate differently depending on student’s individual academic achievements and geographical location of the school. Attending academically high-performing schools may be considered as a warning sign for increased risk of NFSB among young people in rural areas. However, since the present study is pioneer in examining the interrelated role of school-level performance and school region on the risk of NFSB, more research is needed to confirm this association and, in the next step, to study the mechanisms, e.g. migration, through which this connection may occur.
7.
8.
9.
10.
11.
12.
13.
14.
The study was supported by The Sven Jerring
15.
Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest.
16.
Acknowledgments Foundation.
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2a0ff5f12801fe5f27800010876/kunskaps%C3%B6versikt_skola. pdf Sellstro¨m E, Bremberg S (2006) Is there a ‘‘school effect’’ on pupil outcomes? A review of multilevel studies. J Epidemiol Community Health 60:149–155 Spirito A, Esposito-Smythers C (2006) Attempted and completed suicide in adolescence. Annu Rev Clin Psychol 2:237–266 Barnekow V, Currie C, Letsch C, de Looze M, Morgan A (2009) A snapshot of the health of young people in Europe. A report prepared for the European commission conference on youth health, Brussels, Belgium, 9–10 July 2009. WHO Regional Office for Europe, Copenhagen National Board of Health and Welfare (2010) Skador och fo¨rgiftningar behandlade i sluten va˚rd 2009 (Hospitalisation due to injuries and poisoning in Sweden 2009). www.socialstyrelsen.se Kalff AC, Kroes M, Vles JSH, Hendriksen JGM, Feron FJM, Steyaert J, van Zeben TMCB, Jolles J, van Os J (2001) Neighbourhood level and individual level SES effects on child problem behaviour: a multilevel analysis. J Epidemiol Community Health 55:246–250 Xue Y, Leventhal T, Brooks-Gunn J, Earls F (2005) Neighborhood residence and mental health problems of 5- to 11-year-olds. Arch Gen Psychiatry 62:554–563 Bernburg JG, Thorlindsson T, Sigfusdottir ID (2009) The spreading of suicidal behavior: the contextual effect of community household poverty on adolescent suicidal behavior and the mediating role of suicide suggestion. Soc Sci Med 68:380–389 Karvonen S, Vikat A, Rimpela M (2005) The role of school context in the increase in young people’s health complaints in Finland. J Adolescence 28:1–16 Saab H, Klinger D (2010) School differences in adolescent health and wellbeing: findings from the Canadian health behaviour in school-aged children study. Soc Sci Med 70:850–858 Zammit S, Gunnell D, Lewis G, Leckie C, Dalman C, Allebeck P (2013) Individual- and are-level influence on suicide risk: a multilevel longitudinal study of Swedish schoolchildren. Psychol Med (published online: 24 April):1–11 ¨ stberg V, Jablonska B, Lindberg L, Lindblad F, Rasmussen F, O Hjern A (2009) School performance and hospital admissions due to NFSB: a Swedish national cohort study. Int J Epidemiol 38:1334–1341 Jonsson U, Goodman A, von Knorring AL, von Knorring L, Koupil I (2012) School performance and hospital admission due to unipolar depression: a three-generational study of social causation and social selection. Soc Psychiatry Psychiatr Epidemiol 47:1695–1706 OECD (2005) School factors related to quality and equity: results from PISA 2000. Organisation for Economic Cooperation and Development, Paris. http://www.pisa.oecd.org/dataoecd/15/20/ 34668095.pdf ¨ stberg V (2009) School climate and psychosomatic Modin B, O health. A multilevel analysis of nearly 20,000 ninth grade students in the larger Stockholm area. Sch Eff Sch Improv 20:433–455 Lee MT, Wong BP, Chow BW (2006) Predictors of suicide ideation and depression in Hong Kong adolescents: perceptions of academic and family climates. Suicide Life Threat Behav 36:82–96 Marsh HW (1984) Self-concept: the application of a frame of reference model to explain paradoxical results. Aust J Educ 28:165–181 Aberg-Bengtsson L (2009) The smaller the better? A review of research on small rural schools in Sweden. Int J Educ Res 48:100–108 The Swedish National Agency for Education (2009) Vad pa˚verkar resultaten i svensk grundskola? Kunskapso¨versikt om
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ORIGINAL PAPER
School effects on risk of non-fatal suicidal behaviour: a national multilevel cohort study ¨ stberg • Anders Hjern Beata Jablonska • Viveca O Lene Lindberg • Finn Rasmussen • Bitte Modin
•
Received: 2 January 2012 / Accepted: 14 October 2013 Ó Springer-Verlag Berlin Heidelberg 2013
Abstract Objective Research has demonstrated school effects on health, over and above the effects of students’ individual characteristics. This approach has however been uncommon in mental health research. The aim of the study was to assess whether there are any school-contextual effects related to socioeconomic characteristics and academic performance, on the risk of hospitalization from non-fatal suicidal behaviour (NFSB). Methods A Swedish national cohort of 447,929 subjects was followed prospectively in the National Patient Discharge Register from the completion of compulsory school in 1989–93 (&16 years) until 2001. Multilevel logistic regression was used to assess the association between school-level characteristics and NFSB. Results A small but significant share of variation in NFSB was accounted for by the school context (variance partition coefficient \1 %, median odds ratio = 1.26). The risk of NFSB was positively associated with the school’s proportion of students from low socioeconomic status (SES), single parent household, and the school’s average academic performance. School effects varied, in part, by school location.
B. Jablonska (&) L. Lindberg F. Rasmussen Centre for Epidemiology and Community Medicine, Stockholm County Council, 1497, 17129 Stockholm, Sweden e-mail: [email protected] B. Jablonska L. Lindberg F. Rasmussen Department of Public Health Sciences, Karolinska Institutet, 17177 Stockholm, Sweden ¨ stberg A. Hjern B. Modin V. O Centre for Health Equity Studies (CHESS), Stockholm University, Karolinska Institutet, 10691 Stockholm, Sweden
Conclusion NFSB seems to be explained mainly by individual-level characteristics. Nevertheless, a concentration of children from disadvantaged backgrounds in schools appears to negatively affect mental health, regardless of whether or not they are exposed to such problems themselves. Thus, school SES should be considered when planning prevention of mental health problems in children and adolescents. Keywords Sweden Contextual effect School Multilevel model Non-fatal suicidal behaviour
Introduction School plays an important role in a child’s academic, social and emotional well-being [1]. Despite this, little attention has been paid to school as a potentially significant unit for assessing contextual effects on young people’s mental health [2]. One of the most serious consequences of mental health problems is non-fatal suicidal behaviour (NFSB). NFSB is a matter of concern both in its own right and as significant predictor of future suicidal behaviours and completed suicides [3]. Particularly worrisome is the national and international statistics pointing to a growing prevalence of NFSB in young people [4, 5]. The understanding of pathways through which the school context influences mental health is crucial for identifying potential avenues for intervention. Multilevel studies using neighbourhood as the level of analysis have shown a negative association between children’s mental health and environmental characteristics such as low average socioeconomic status (SES), high concentration of unemployed people, single parents and immigrants [6–8].
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However, little is known whether these characteristics play an independent role also within the smaller contextual unit that the school constitutes. Previous research has provided some evidence in support of the idea that mental health may vary as a function of the school’s academic context [9–11]. At an individual level, poor school performance is an important predictor of mental health problems [11–13]. Furthermore, a high proportion of poor performers is known to co-occur with a school climate characterized by low sense of connectedness, inclusion, and social support [14]. These features could also be assumed to have an overall negative effect on the mental health of students attending such a school, independently of their individual academic achievements [15]. A contrasting assumption would be that students at a certain performance level may assess themselves higher in a low-performing than in a high-performing context, thus leading to an overall positive effect on mental health of attending poor-performing schools. The school context fosters social comparison and it is well documented that students’ academic self-concept, which is a predictor of mental health and suicidal behaviours [16], is inversely related to the achievement level of other students in the same school [17]. There is also a lack of knowledge as to how any such school effects may vary according to the specific type of school setting. Urban, suburban and rural schools each function within a unique demographic, cultural and social context that may exacerbate the positive or negative impact of school effect [18]. In summary, the evidence demonstrating school effects on health, in addition to individual risk factors, is beginning to mount. This approach however has not been widely adopted in mental health research. The aim of this study is to assess whether there are any school-contextual effects on mental health, measured as hospitalization due to NFSB, and to what extent any such effect can be explained by individual- and school-level socioeconomic characteristics and academic performance. Since the communities where the schools are located differ in their level of urbanization and socio-economic composition, we also investigate whether the influences of individual- and school-level characteristics on mental health vary by school location.
Methods This study was based on data from national registers held by the Swedish National Board of Health and Welfare and Statistics Sweden. The key to these registers is the unique personal identification number, which was used to link data from the registers to each participant. The study was
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approved by the regional ethics committee at Karolinska Institutet, Stockholm, Sweden. Study population The study population consisted of individuals born between 1973 and 1977 (n = 491,258) who were registered as residents in the Swedish Population and Housing Census of 1985 and who attended the ninth grade of compulsory school in 1989–93. These are the first five birth cohorts in the National School Register—the Swedish national data source for information about school performance. Individuals were followed up in the National Hospital Discharge Register from the time of graduation until the end of 2001. Subjects were censored at the date of death (retrieved from the National Cause of Death Register), date of emigration (retrieved from the Register of the Total Population) or at the end of follow-up. Individuals who had been admitted to a hospital due to a psychiatric disorder and/or NFSB before the completion of ninth grade (n = 1,670) were excluded. Excluded subjects had a similar grade point average as included subjects with a corresponding hospital admission (2.84 versus 2.87 on the scale ranging from a minimum of 1.0 to a maximum of 5.0). Grade point average was calculated on the basis of the 17 existing school subjects in Sweden at the time. Individuals who lacked marks in three or more subjects (n = 7,062) were excluded because of their unreliable grade point average, as were foreign-born children (n = 34,597) because of the negative influence of migration on school performance [19]. Schools in which the total number of 9th grade students in the years studied was B10 (n = 213) were also excluded. The largest school, in terms of 9th grade enrolment between 1989 and 1993, had 1,121 students and the smallest had 11 students. Cases with missing data were excluded, yielding a study population of 444,769 persons. Outcome variable The outcome variable—first-time hospital admission due to ‘‘self-inflicted poisoning or injury/suicide (attempted)’’ [tenth revision of the International Classification of Diseases (ICD-10)]—was obtained through individual record linkage to the National Hospital Discharge Register from 1989 to 2001. Hospital admission involves staying at a hospital for at least one night. NFSB was defined according to the World Health Organization (WHO) ICD-9 (intentional self-harm E950–959 and event of undetermined intent E980–989) during 1989–96 and ICD-10 (intentional self-harm X60–84 and event of undetermined intent Y10–34) during 1997–2001.
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Individual-level variables
School-level variables
School performance
School-level variables included grade point average, percentage of girls, students with a foreign background, students with low parental SES, students living with a single parent, and students having a mother with low education. These variables were constructed by aggregating data from the student level to the school level. For example, individual-level grade point averages were aggregated so that each student was attributed the grade point average at their respective school.
Data were retrieved from the National School Register on grade point averages at the time when Swedish students leave compulsory school (usually at 16 years of age). This register encompasses data from all public schools since 1988, and also data from all non-public ([5 %) schools since 1993. Until 1996, a five-graded relative scale was used in the Swedish school system, supervised by the Swedish School Authority through national tests in core subjects. The quality of the data in the National School Register is high and summary statistics are published regularly. Grade point average for the sample ranged from a minimum of 1.0 to a maximum of 5.0, Mean = 3.2, SD = 0.7. For descriptive purpose only, a dichotomous variable was also created that classified participants as ‘‘low performers’’ (i.e. grade point average below the mean) versus ‘‘high performers’’ (i.e. grade point average at or above the mean).
Socio-demographic variables Socio-demographic indicators were created through linkage to the Swedish Population and Housing Census of 1985: year of birth, sex, ethnicity, SES of the household, single parent household, and geographical location of the school attended. Information about parental country of birth was used to create a three-category proxy for ethnicity: Swedish (both parents born in Sweden), nonSwedish (neither parent born in Sweden) and mixed (one parent born in Sweden and one parent born in another country). SES was defined according to the classification used by Statistics Sweden, which is based on occupation and considers the occupation’s required level of qualification, type of production and position of work of the head of the household. Six categories of SES were created: unskilled workers, skilled workers, lower-level nonmanual, middle-level non-manuals, higher-level nonmanuals and others (i.e. the self-employed, farmers, students, housewives, old age/sickness disability pensioners, long-term unemployed). The highly heterogeneous composition of the SES category ‘‘other’’ was due to the relatively small numbers of individuals belonging to each subcategory. Data on maternal education were obtained from the Swedish Educational Register (if available from the register of 2001, otherwise from the registers of 1995 or 1990) categorized as short (B11 years), medium (12–13 years), long (14–15 years) and very long (C16 years).
Statistical methods In this study, two-level logistic regression models (random intercept) with students at level one and schools at level two were used, and computations were carried out using MLwiN 2.10 [20]. Random intercepts models provide estimates of the fixed effects of the predictor variables (i.e. the effects of explanatory variables are assumed to be constant across schools upon the outcome variable). The fixed effects are expressed as odds ratios (OR). The first step of the analyses was to run a so-called empty model with no exposure variable to obtain the unexplained variance in NFSB between schools. Three additional models were fitted. The first model included all the individual-level characteristics, and in the second model school-level variables were also added to the model, enabling us to assess the effects of school-level characteristics after the influence of individual-level characteristics had been accounted for. The second model also contained interactions between school region and individual-level/school-level grade point average as well as interaction tests for individual- and school-level grade point average. Tests for cross-level interactions were carried out to explore whether the effect of individual grade point average on the risk of NFSB varied across schools depending upon their overall grade point average. Twolevel logistic regression models were also run separately for three types of school regions (big cities, smaller cities and rural areas) (Model 3a, b, and c). We calculated the variance partition coefficient (VPC) to estimate the proportion of total variance in the outcome attributable to the school level and the proportional change in variance (PCV) comparing the empty model with the models including the selected individual- and school-level variables. The simulation method provided by MLwiN was used to calculate VPC. According to the recommendation of Larsen and Merlo [21], we also used the median odds ratio (MOR), as an alternative measure of the school variance, which unlike VPC is not dependent of the prevalence of the outcome. The MOR method translates the area
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level variance in an odds ratio scale and measures the school variance as an OR. In this study, MOR estimates the individual risk of NFSB (in median) that can be attributed to the school context. MOR equal to one indicates no school variance. The higher the MOR, the more important are the school effects for understanding the individual probability of risk of NFSB.
Results Information on percentage or means of the variables included in the study is presented in Table 1. The first group of variables was assessed at the individual level. The next group of variables addresses the same aspects as those accounted for at the individual level, but on the school level, with each student given the mean value of their respective school. The study population was 48.6 % female and the majority was Swedes and lived with two parents. More than 50 % came from non-manual backgrounds and mothers of onethirds of the students had short education. Slightly more than 50 % of the study population lived in smaller city areas and around one-fourth in big city or rural areas. Schools ranged from being completely homogenous concerning ethnic composition and family structure to being very mixed. Table 1 also shows individual- and school-level characteristics stratified by NFSB. A total of 4,740 individuals were hospitalized due to NFSB at least once during the study period. Hospital admission due to NFSB was more common among females than among males. It was also more frequent among students with a non-Swedish background, low parental SES, maternal education B13 years, and among students living in single parent households. Furthermore, self-injurious persons had a lower grade point average than the population as a whole. Hospital admission because of NFSB was slightly more common in schools with higher than average proportions of students with a foreign background, low parental SES and single parents. Table 2 shows the results of the multilevel analyses. The empty model with no predictors indicates that the risk of NFSB varies significantly between schools (p \ 0.001) with a variance of 0.061 and a VPC of 0.0007. The latter number is very low, suggesting little school-contextual variation in NFSB. Median odds ratio for empty model was 1.26. Thus, if randomly picked student moved from one school to another with higher prevalence of NFSB, then his/her odds of NFSB would, in median, increase with 1.26. The individual-level model for NFSB (Model 1) points to an increased risk among females, individuals with a nonSwedish background and those from single parent households. Students from lower non-manual background run a
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lower risk of NFSB in relation to those with highest nonmanual social class background, whereas no significant excess risk was found for the skilled/unskilled worker background. Maternal education\16 years was related to a decreased risk of NFSB compared to the reference category. The positive associations between maternal education and NFSB appeared only after the inclusion of grade point average in the model. Grade point average and the risk of NFSB were inversely associated: a one-unit increase in grade point average was associated with a considerable decrease in NFSB corresponding to an odds ratio of 0.4. The inclusion of these individual-level predictors reduced the between-school-level variance by 40 %, but significant variation in NFSB between schools still remained. The corresponding school-aggregated information for the individual-level variables is presented in Model 2. Thus, school-level predictors included proportion of students with a foreign background, low parental SES, living with a single parent, having a mother with low education and school grade point average. The findings indicate that, regardless of their individual social characteristics, students who attend schools with a high proportion of pupils from lower social classes (OR = 1.01) and from single parents households (OR = 1.02) are more likely to self-injure themselves than those who attend schools with a lower proportion of such students. In all analyses, including those performed separately for the three school regions (Table 3), attending a school with a high concentration of pupils from single parent household consistently emerged as a significant predictor of NFSB. Contrary to what one might expect, the higher the grade point average of the school attended, the higher the odds risk of NFSB (OR = 1.39) when individual-level grade point average had been taken into consideration in the analysis. A significant interaction between school region and individual grade point average as well as between school region and school-level grade point average was also found. These results indicated that the higher the individual grade point average and the lower the urbanization level of the school region, the lower was the risk of NFSB, whereas the opposite appeared to be true for the school-level grade point average. With the additional inclusion of these interactions in the model, the variance between schools was further reduced but remained significantly different from zero. The interactions were further examined by regressing NFSB on student and school GPA within each school region (Table 3). The empty models for all three school regions revealed that, in the absence of any predictor variables, variation in the risk of NFSB differed significantly between schools. The amount of clustering of NFSB within schools appeared to be higher in big cities than in small cities and rural regions. However, with the inclusion
Soc Psychiatry Psychiatr Epidemiol Table 1 Individual- and school-level characteristics and their distribution by hospital admission due to NFSB from graduation in 1989–93 to 2001 Student level
Number of participants
(%)
Hospitalization due to NFSB (%)
Man
228,636
51.4
0.7
Women
216,133
48.6
1.4
388,425
87.3
1.0
25,273
5.7
1.4
31,071
7.0
1.8
Higher-level non-manuals
86,733
19.5
0.8
Middle-level non-manuals
102,843
21.1
0.9
Lower-level non-manuals
56,736
12.8
1.0
Skilled workers
72,051
16.2
1.2
Unskilled workers
63,640
14.3
1.5
Other
62,766
14.1
1.3
No
371,008
83.4
0.9
Yes
73,761
16.6
1.9
53,825
12.1
0.8
Sex
Ethnicity Swedish Non-Swedish Mixed Parental SES
Single parent household
Mother’s education Very long Long
95,091
21.4
0.8
138,493
31.1
1.2
Short School region
157,360
35.4
1.2
Big city area
113,422
25.2
1.1
Smaller city area
231,733
52.1
1.1
99,614
22.4
1.0
Medium
Rural area
3.24a
Grade point average
2.87a
Low grade (below the mean)
220,333
49.5
1.5
High grade (at or above the mean)
224,436
50.5
0.7
School level
Range
Mean
Mean for schools with students hospitalized for NFSB
% Of girls at the school
12–69
48.6
48.6
% With a foreign background
0–94
12.7
13.9
% With low parental SES
14–92
44.6
45.3
% Living with a single parent
0–72
16.6
17.9
% Having a mother with low education
0–72
35.4
35.9
Grade point average
2.36–3.93
3.24
3.23
Low (below the mean)
2.36–3.23
3.16
3.16
High (at or above the mean)
3.24–3.93
3.34
Number of students
444,769
4,740
Number of schools
1,121
995
a
3.33
Mean
of explanatory variables, the between-school variance in NFSB decreased to an insignificant level in all of the three studied regions.
VPC for the three school regions ranged from 1.2 % in big cities to 0.4 % in smaller ones. Although these numbers are small, the MOR estimate amounts to 2.55, indicating
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Soc Psychiatry Psychiatr Epidemiol Table 2 Random intercept model for two levels: odds ratios and confidence intervals of hospital admission due to NFSB from compulsory school graduation (1989–93) until 2001 according to individual- and school-level factors
Sex: women (versus men)
Model 1 All
Model 2 All
2.62*** [2.46–2.79]
2.62*** [2.46–2.77]
1
1
Ethnicity Swedish Non-Swedish
1.64*** [1.46–1.85]
1.54*** [1.37–1.74]
Mixed
1.39*** [1.27–1.52]
1.36*** [1.24–1.49]
Higher-level non-manuals
1
1
Middle-level non-manuals
0.98 [0.88–1.09]
0.98 [0.88–1.09]
Parental SES
Lower-level non-manuals
0.87* [0.77–0.98]
0.87* [0.77–0.98]
Skilled workers
0.94 [0.75–1.18]
0.95 [0.84–1.06
Unskilled workers Other
0.94 [0.84–1.06] 1.04 [0.92–1.16]
0.95 [0.84–1.07] 1.04 [0.93–1.17]
1.61*** [1.50–1.72]
1.53*** [1.43–1.64]
Single parent household Mother’s education Very long
1
1
Long
0.86** [0.75–0.97]
0.88** [0.77–0.99]
Short
0.94 [0.83–1.06]
0.96 [0.85–1.08]
Very short
0.87* [0.77–0.99]
0.87* [0.78–0.99]
0.40*** [0.39–0.42]
0.40*** [0.39–0.42]
Grade point average (GPA) % With a foreign background
1.00 [0.99–1.00]
% With low parental social class
1.01** [1.00–1.02]
% Living with a single parent
1.02*** [1.01–1.02]
% Having a mother with low education
1.00 [0.99–1.00]
School grade point average (SGPA)
1.39 [1.00–2.07]
School region Big city area Smaller city area
1.01 [0.92–1.20] 1.04 [0.97–1.16]
Rural area
1
Interaction terms School region*School GPA
p \ 0.001
All models are adjusted for year of birth
School region*Student GPA
p \ 0.001
* Significant at the 5 % level (p B 0.05)
Variance between schools (empty model)
0.061***
0.061***
Variance between schools (current model)
0.036***
0.023*
** Significant at the 1 % level (p B 0.01)
PCV
40.1 %
62.0 %
MOR (empty model)
1.26
1.26
*** Significant at the 0.1 % level (p B 0.001)
MOR (current model)
1.20
1.15
School GPA*Student GPA
substantial cluster heterogeneity in NFSB at the school level. The corresponding figures for small town and rural areas were 1.21 and 1.26. These effects decreased to 1.09 and 1.18, respectively, when individual- and school-level factors were added to the model. Individual-level predictors of NFSB in all three school regions were, in general, consistent with the overall results presented in Model 2. Higher school-level grade point average was associated with a higher risk of NFSB only in rural regions, as was percentage of students with foreign background and percentage of
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ns
students with relatively well-educated mothers. The risk of NFSB was slightly increased with higher school-level grade point average in smaller cities, and slightly decreased in big cities, but neither association reached statistical significance. We also found a significant cross-level interaction between individual- and school-level grade point average in big city schools indicating that the inverse association between high individual-level grade point average and NFSB is more pronounced in schools where the grade point average is relatively high.
Soc Psychiatry Psychiatr Epidemiol Table 3 Random intercept model for two levels: odds ratios and confidence intervals of hospital admission due to NFSB from compulsory school graduation (1989–93) until 2001 according to individual-, school-level factors and school region Model 1a Big city area
Model 1b Smaller city area
Model 1c Rural area
2.68*** [2.38–3.02]
2.43*** [2.23–2.65]
3.08*** [3.56–2.63]
Swedish Non-Swedish
1 1.44*** [1.20–1.75]
1 1.54*** [1.29–1.83]
1 2.01*** [1.41–2.86]
Mixed
1.36*** [1.18–1.59]
1.42*** [1.25–1.61]
1.17 [0.92–1.48] 1
Sex: women (versus men) Ethnicity
Parental SES Higher-level non-manuals
1
1
Middle-level non-manuals
0.97 [0.81–1.16]
0.96 [0.83–1.12]
1.08 [0.83–1.40]
Lower-level non-manuals
0.90 [0.73–1.11]
0.88 [0.74–1.05]
0.77 [0.56–1.05]
Skilled workers
0.85 [0.68–1.06]
0.96 [0.81–1.13]
1.05 [0.80–1.37]
Unskilled workers
0.90 [0.72–1.12]
1.00 [0.85–1.18]
0.90 [0.68–1.19]
Other
0.92 [0.74–1.14]
1.17* [1.00–1.38]
0.97 [0.74–1.28]
1.54*** [1.36–1.75]
1.54*** [1.40–1.69]
1.47*** [1.25–1.72]
Single parent household Mother’s education Very long
1
1
1
Long
0.84* [0.68–1.00]
0.85* [0.74–1.00]
1.11 [0.79–1.55]
Short
0.97 [0.78–1.20]
0.91 [0.76–1.08]
1.08 [0.78–1.05]
0.94 [0.76–1.16] 0.44*** [0.41–0.48]
0.83* [0.70–0.99] 0.41*** [0.38–0.44]
0.91 [0.66–1.27] 0.34*** [0.31–0.38]
Very short Grade point average (GPA) % With a foreign background
1.00 [0.99–1.01]
1.00 [0.99–1.01]
1.02* [1.01–1.02]
% With low parental social class
1.01 [0.99–1.02]
1.01* [1.00–1.02]
1.01 [1.00–1.01]
% Living with a single parent
1.02*** [1.01–1.02]
1.02*** [1.01–1.03]
1.02*** [1.00–1.40]
% Having a mother with low education
1.00 [0.99–1.01]
0.99 [0.98–1.01]
0.99* [0.97–1.00]
0.96 [0.50–1.80]
1.32 [0.76–2.30]
7.79*** [3.10–19.50]
–
–
–
School grade point average (SGPA) Interaction terms School region*School GPA School region*Student GPA
–
–
–
School GPA*Student GPA
p = 0.007
ns
ns
Variance between schools (empty model)
0.097***
0.040**
0.061*
Variance between schools (current model)
0.010
0.014
0.029
PCV
89.7 %
65.0 %
52.5 %
MOR (empty model)
2.55
1.21
1.26
MOR (current model)
1.09
1.12
1.18
All models are adjusted for year of birth * Significant at the 5 % level (p B 0.05) ** Significant at the 1 % level (p B 0.01) *** Significant at the 0.1 % level (p B 0.001)
Limitations of the study This is, to our knowledge, the first study to explore the contextual effect of schools on the risk of NFSB in a large national cohort, but several limitations need to be kept in mind when interpreting these results. First, our study is restricted to the most severe cases of NFSB that required hospitalization. It cannot be taken for granted that the
school effects are similar in the—probably—less severe cases of NFSB not leading to hospitalizations. Secondly, data on hospital-based NFSC may be limited by selection bias related to socioeconomic factors and/or school performance. Hospital admissions because of NFSB, however, are predominantly medical emergencies because of poisoning (&86 % of intentional NFSB cases and &69 % of the cases categorized as ‘‘event of undetermined intent’’),
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Soc Psychiatry Psychiatr Epidemiol
which limits bias of this kind. Thirdly, the register-based design of this study did not allow for the control of mental health conditions that do not lead to inpatient care but that are known to increase the risk of NFSB (e.g. emotionally unstable personality disorder). Fourthly, we were not able to account for the intermediate level of nesting, i.e. classroom level, although there are some suggestions that this may be a more appropriate measure of clustering effect [15]. Finally, the measures of school effects were restricted to socioeconomic and academic characteristics. Inclusion of other dimensions of the school context, e.g. teacher support, would perhaps have resulted in a more comprehensive model of school effect on mental health.
Discussion In this study, we found significant school variation in risk of NFSB among graduated students. The variation was greater between schools in big city areas than between schools in other regions. Less than 1 % of the total variation of NFSB between schools was accounted for by the particular school attended suggesting that schools are very similar with respect to the prevalence of NFSB. It should be noted, however, that it is rather the standard than the exception that the amount of variation in individual-level mental health attributable to the school context is small [2, 11, 22]. In our study, the small variance at the aggregate level may additionally be accounted for by the character of the outcome. Calculation of VPC for rarely prevalent outcomes, e.g. NFSB, results in lower VPC than for outcomes that show the wider disparity in prevalence, despite a similar group variance. In contrast to VPC, the MOR is statistically independent of the outcome prevalence [23]. Using the information provided by the MOR as a measure of school variance, we found that, when randomly selecting two students from two different schools, the OR between the student at lowest risk and the student at highest risk was above 1.26 in half of the cases. Thus, the school context constituted a source of variation in risk of NFSB. This overall effect was, however, mostly driven by the high contextual variation in NFSB found in big city schools (MOR = 2.55). School-level SES, family structure and academic performance were associated independently with the risk of NFSB and explained part of the variation at the school level. Consistent with prior research, we found that, at the individual level, females, individuals with a non-Swedish background and those from single parent households were at higher risk of NFSB than comparisons [12]. Interpretation of the protective effect of shorter maternal education for NFSB is ambiguous, though the finding is consistent with a recent study from UK [24]. It seems unlikely that
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this protective effect is an artefact caused by statistical over-adjustment for socioeconomic variables since it is only manifest when school performance is introduced into the regression model. Thus, one explanation could be that children of less-educated mothers tend to face less pressure to succeed academically than children of highly educated mothers and, in consequence, they may be less at risk of the negative consequences that high educational expectations may have on mental health [25]. School performance was negatively associated with the outcome, but the strength of this relation depended upon characteristics of the school region. The lower the urbanization grade of the school region, the more pronounced was the inverse association between school performance on the individual level and NFSB. School grades thus seem more important for rural students than for students living in big city areas. Individuals who attended schools characterized by high proportions of students with low parental SES and single parent household had statistically significant excess risk of NFSB, above and beyond individual background. In addition, the latter emerged as a significant predictor of NFSB in all three school regions and its effect was not accounted for by other socioeconomic inequalities. These findings are consistent with prior studies suggesting that clustering of these social characteristics is an important higher level dimension that contributes to poor mental health [26–28]. Several explanations are possible for the association. High concentrations of disadvantaged students may hinder schools to organize their educational and social activities in ways which promote learning outcomes and well-being [14], with negative consequences for all the students attending a particular school. It is plausible that, due to economic or health problems [29], it may be more difficult for low SES and single parents to serve as positive role models, involve in school curricular and extracurricular activities and cooperate with teachers and other parents [30]. An insufficient proportion of adult role models surrounding the school milieu may have negative consequences that extend beyond the directly affected children. Students attending socially disadvantaged schools may also more often become exposed to behaviours that put them at risk of mental health problems, e.g. bullying [31, 32]. Relations with suicidal peers seem to be another type of exposure that account for the contextual effect of schoollevel disadvantage on adolescent NFSB behaviour [8]. While individual school performance was inversely related to NFSB, a positive association was found for school-level performance. Thus, students attending highperforming schools seemed to experience higher risk of NFSB. This finding is not supported by a recent Swedish study on multilevel influences on suicide risk [11], but in line with the few other studies that exist in this area [9, 10]. The separate analyses for the school regions revealed, that
Soc Psychiatry Psychiatr Epidemiol
the overall effect of school-level performance on NFSB was largely accounted for by the excess risk found in rural areas. The above finding is in accordance with theories on compositional effects, arguing that students who attend more advantaged schools may be harmed by the lower relative position they occupy in the school hierarchy (the so-called big-fish–little-pond effect) [17]. Why such effect is detectable only in rural and big city schools in the present study is not clear. It is plausible that such an effect may be strengthened by some unique features of the rural schools but this remains to be proven.
2.
3. 4.
5.
6.
Conclusions Our findings suggest that school-level factors explain only a small percentage of student’s risk of NFSB, and that differences in NFSB, therefore, mainly seem to be due to individual characteristics. We did demonstrate in this study, however, that a concentration of children from disadvantaged backgrounds in schools appears to negatively affect mental health, regardless of whether or not they are exposed to such problems themselves. Thus, school SES should be considered when planning prevention of mental health problems in children and adolescents. The pattern of association between school-level performance on NFSB was not consistent across school regions. What our findings suggest is that both the direction of the effect and mechanisms underlying the relationship may operate differently depending on student’s individual academic achievements and geographical location of the school. Attending academically high-performing schools may be considered as a warning sign for increased risk of NFSB among young people in rural areas. However, since the present study is pioneer in examining the interrelated role of school-level performance and school region on the risk of NFSB, more research is needed to confirm this association and, in the next step, to study the mechanisms, e.g. migration, through which this connection may occur.
7.
8.
9.
10.
11.
12.
13.
14.
The study was supported by The Sven Jerring
15.
Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest.
16.
Acknowledgments Foundation.
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