The association between adolescents' health and disparities in school career: a longitudinal cohort study

Health and health behaviours in adolescence as predictors of education and socioeconomic status in adulthood - a longitudinal study

BACKGROUND

The positive association of health with education level and socioeconomic status (SES) is well-established. Two theoretical frameworks have been delineated to understand main mechanisms leading to socioeconomic health inequalities: social causation and health selection but how these work in adolescence is poorly known. We studied if adolescent health and health behaviours predict higher education and higher SES in adulthood and if family background and school performance in adolescence explain these associations.

METHODS

Surveys on health and health behaviours were sent to representative samples of 12-18-year-old Finns in 1981-1997 every second year (response rate 77.8%, N = 55,682). The survey data were linked with the respondents' and their parents' socioeconomic data from the Finnish national registries. Both latent variables, namely, health (perceived health, health complaints, chronic disease), health-compromising behaviours (smoking status, drunkenness frequency), and family background (parents' occupation-based SES, education, family type) and variables directly measuring health-enhancing behaviours (toothbrushing, physical activity) and school performance were used to predict higher education and higher occupation-based SES at age 34. Logistic regression analysis and structural equation models (SEM) were used.

RESULTS

In logistic regression analyses, good health, health-enhancing behaviours, and lack of health-compromising behaviours were related to higher education and SES, also after controlling for family background and school performance. In the SEM analyses, good health, health-enhancing behaviours, and lack of health-compromising behaviours directly predicted higher SES and higher education, although the standardised coefficients were low (from 0.034 to 0.12). In all models, health, lack of health-compromising behaviours, and health-enhancing behaviours predicted school performance, which in turn, predicted the outcomes, suggesting indirect routes to these. Good socioeconomic prospects in terms of family background predicted good health, healthy behaviours, and good school performance in adolescence and higher SES and higher education in adulthood.

CONCLUSION

Health and health behaviours in adolescence predicted education and SES in adulthood. Even though the relationships were modest, they support the health selection hypotheses and emphasise the importance of adolescence for health inequalities during the life-course. Health and health behaviours were strongly associated with school performance and family background which together modified the paths from health and health behaviours to the outcomes.

Evaluating the Role of Parental Education and Adolescent Health Problems in Educational Attainment

This article reconsiders the role of social origin in health selection by examining whether parental education moderates the association between early health and educational attainment and whether health problems mediate the intergenerational transmission of education. We used longitudinal register data on Finns born in 1986–1991 (n = 352,899). We measured the completion of secondary and tertiary education until age 27 and used data on hospital care and medication reimbursements to assess chronic somatic conditions, frequent infections, and mental disorders at ages 10–16. We employed linear probability models to estimate the associations between different types of health problems and educational outcomes and to examine moderation by parental education, both overall in the population and comparing siblings with and without health problems. Finally, we performed a mediation analysis with g-computation to simulate whether a hypothetical eradication of health problems would weaken the association between parental and offspring education. All types of health problems reduced the likelihood of secondary education, but mental disorders were associated with the largest reductions. Among those with secondary education, there was further evidence of selection to tertiary education. High parental education buffered against the negative impact of mental disorders on completing secondary education but exacerbated it in the case of tertiary education. The simulated eradication of health problems slightly reduced disparities by parental education in secondary education (up to 10%) but increased disparities in tertiary education (up to 2%). Adolescent health problems and parental education are strong but chiefly independent predictors of educational attainment.

Trajectories of care for children and adolescents with psychosocial problems: a 3-year prospective cohort study

BACKGROUND

Care for children and adolescents with psychosocial problems is aimed at reducing problems. There may be a relationship between the intensity and duration of care provision and improvement of these outcomes, but evidence on this issue is lacking. We therefore examined the association between care trajectories based on duration and intensity of care for children, and the reduction in psychosocial problems after 3 years.

METHODS

We obtained a cohort of all children entering psychosocial care in one region (n = 1,378), the TAKECARE cohort, and followed it for 3 years, with five assessment rounds. Retention in the final round was 85.8%. Psychosocial problems were measured using the parent report of the Total Difficulty Score of the Strength and Difficulties Questionnaire (SDQ-TDS). We constructed trajectories for intensity of care using growth mixture modelling and assessed the association between duration and intensity of care trajectories and SDQ-TDS after 3 years.

RESULTS

After 3 months 60.6% of children and adolescents were receiving care, after 1 year 38.7% were receiving care and after 3 years 26.0%. Regarding intensity of care, three trajectories were found: one with minimal intensity during all 3 years, a second with initially medium intensity and strong reduction within 1 year, and a third with high intensity and a reduction after 1 year. Although the psychosocial problems of children and adolescents were reduced during the 3-year period, the rate of decline was relatively less marked for children and adolescents with longer care trajectories.

CONCLUSION

Overall, children and adolescents with psychosocial problems who received care had improved outcomes at follow-up. However, increased provision of care does not automatically lead to reduction of problems, and although overall psychosocial problems are reduced, a substantial subgroup has longer lasting problems.

Health and educational aspirations in adolescence: a longitudinal study in Finland

Background

The health selection hypothesis suggests that poor health leads to low educational attainment during the life course. Adolescence is an important period as poor health might prevent students from making the best educational choices. We test if health in adolescence is associated with educational aspirations and whether these associations persist over and above sociodemographic background and academic achievement.

Methods

Using classroom surveys, a cohort of students (n = 5.614) from the Helsinki Metropolitan Region was followed from the 7th (12–13 years,) up to the 9th grade (15–16 years) when the choice between the academic and the vocational track is made in Finland. Health factors (Strengths and Difficulties Questionnaire (SDQ), self-rated health, daily health complaints, and long-term illness and medicine prescribed) and sociodemographic background were self-reported by the students. Students’ educational aspirations (applying for academic versus vocational track, or both) and their academic achievement were obtained from the Joint Application Registry held by the Finnish National Agency for Education. We conducted multilevel multinomial logistic regression analyses, taking into account that students are clustered within schools.

Results

All studied health factors were associated with adolescents’ educational aspirations. For the SDQ, daily health complaints, and self-rated health these associations persisted over and above sociodemographic background and academic achievement. Students with better health in adolescence were more likely to apply for the academic track, and those who were less healthy were more likely to apply for the vocational track. The health in the group of those students who had applied for both educational tracks was in between. Inconsistent results were observed for long-term illness. We also found robust associations between educational aspirations and worsening health from grade 7 to grade 9.

Conclusions

Our findings show that selection by health factors to different educational trajectories takes place at early teenage much before adolescents choose their educational track, thus supporting the health selection hypothesis in the creation of socioeconomic health inequalities. Our findings also show the importance of adolescence in this process. More studies are needed to reveal which measures would be effective in helping students with poor health to achieve their full educational potential.

Possible Sources of Bias in Primary Care Electronic Health Record Data Use and Reuse

BACKGROUND

Enormous amounts of data are recorded routinely in health care as part of the care process, primarily for managing individual patient care. There are significant opportunities to use these data for other purposes, many of which would contribute to establishing a learning health system. This is particularly true for data recorded in primary care settings, as in many countries, these are the first place patients turn to for most health problems.

OBJECTIVE

In this paper, we discuss whether data that are recorded routinely as part of the health care process in primary care are actually fit to use for other purposes such as research and quality of health care indicators, how the original purpose may affect the extent to which the data are fit for another purpose, and the mechanisms behind these effects. In doing so, we want to identify possible sources of bias that are relevant for the use and reuse of these type of data.

METHODS

This paper is based on the authors' experience as users of electronic health records data, as general practitioners, health informatics experts, and health services researchers. It is a product of the discussions they had during the Translational Research and Patient Safety in Europe (TRANSFoRm) project, which was funded by the European Commission and sought to develop, pilot, and evaluate a core information architecture for the learning health system in Europe, based on primary care electronic health records.

RESULTS

We first describe the different stages in the processing of electronic health record data, as well as the different purposes for which these data are used. Given the different data processing steps and purposes, we then discuss the possible mechanisms for each individual data processing step that can generate biased outcomes. We identified 13 possible sources of bias. Four of them are related to the organization of a health care system, whereas some are of a more technical nature.

CONCLUSIONS

There are a substantial number of possible sources of bias; very little is known about the size and direction of their impact. However, anyone that uses or reuses data that were recorded as part of the health care process (such as researchers and clinicians) should be aware of the associated data collection process and environmental influences that can affect the quality of the data. Our stepwise, actor- and purpose-oriented approach may help to identify these possible sources of bias. Unless data quality issues are better understood and unless adequate controls are embedded throughout the data lifecycle, data-driven health care will not live up to its expectations. We need a data quality research agenda to devise the appropriate instruments needed to assess the magnitude of each of the possible sources of bias, and then start measuring their impact. The possible sources of bias described in this paper serve as a starting point for this research agenda.

The Population Impact of Childhood Health Conditions on Dropout from Upper-Secondary Education

OBJECTIVES

To quantify how large a part of educational dropout is due to adverse childhood health conditions and to estimate the risk of dropout across various physical and mental health conditions.

STUDY DESIGN

A registry-based cohort study was conducted on a 20% random sample of Finns born in 1988-1995 (n = 101 284) followed for school dropout at ages 17 and 21. Four broad groups of health conditions (any, somatic, mental, and injury) and 25 specific health conditions were assessed from inpatient and outpatient care records at ages 10-16 years. We estimated the immediate and more persistent risks of dropout due to health conditions and calculated population-attributable fractions to quantify the population impact of childhood health on educational dropout, while accounting for a wide array of sociodemographic confounders and comorbidity.

RESULTS

Children with any health condition requiring inpatient or outpatient care at ages 10-16 years were more likely to be dropouts at ages 17 years (risk ratio 1.71, 95% CI 1.61-1.81) and 21 years (1.46, 1.37-1.54) following adjustment for individual and family sociodemographic factors. A total of 30% of school dropout was attributable to health conditions at age 17 years and 21% at age 21 years. Mental disorders alone had an attributable fraction of 11% at age 21 years, compared with 5% for both somatic conditions and injuries. Adjusting for the presence of mental disorders reduced the effects of somatic conditions.

CONCLUSIONS

More than one fifth of educational dropout is attributable to childhood health conditions. Early-onset mental disorders emerge as key targets in reducing dropout.

Chronic health conditions and school performance in first graders: A prospective cohort study

Objective

Children with chronic health conditions may perform poorer at school. Associations may be confounded by numerous social factors. We aimed to estimate the effects of a chronic health condition on overall school performance in first graders with an emphasis on rigorous adjustment for potential confounders.

Methods

A population-based cohort study was performed in the area of Mainz-Bingen (Germany). In 2015 all preschoolers were approached and the presence of a chronic health condition was assessed by parental questionnaires and preschool health examination data. The identification of a chronic health condition was based on special health care needs and presence of a doctor’s diagnosis out of 24 school-relevant diseases. At the end of the first school year, overall school performance was assessed by teachers and rated on a 5-item scale ranging from -10 to +10.

Results

Of 3683 children approached, 2003 were enrolled. Overall school performance was available for 1462 children (51% boys). Of these, 52% suffered from a chronic health condition. Compared to children without a chronic health condition, children with special health care needs (15%) performed worse at school (adjusted mean difference: -0.95, 95% CI: [-1.55; -0.35], P = 0.002). Children with a doctor’s diagnosis but without special health care needs (37%) did not perform worse at school. The effect was further analysed considering the extent of special health care needed.

Conclusions

Chronic health conditions affect overall school performance early in primary school. To identify academically at-risk children, a chronic health condition identification based on special health care needs may be used.

Health-Related Factors Associated with Discrepancies between Children's Potential and Attained Secondary School Level: A Longitudinal Study

Objectives

This longitudinal study examines children’s health-related characteristics in relation to discrepancies between their educational potential assessed by a cognitive test in primary school at age 11 and their attained secondary school level at age 14.

Methods

Data were used from 1510 participants of the Dutch PIAMA (Prevention and Incidence of Asthma and Mite Allergy) birth cohort. Multiple multinomial logistic regression analyses were used to estimate the associations between indicators of physical health, psychosocial health, lifestyle, sleeping patterns and stressful life events and attending a higher or lower level of secondary education than indicated by the cognitive test.

Results

We found no evidence that physical health contributes to discrepancies between the potential and attained level of secondary education, but attention disorders and stressful life events (nasty experiences and parents’ divorce) were associated with educational attainment below children’s potential level. Furthermore, substance use (alcohol, drugs and smoking) were strongly associated with attending a lower level of secondary education than expected (odds ratios from 2.2 (CI: 1.5–3.3) to 5.0 (CI: 2.8–8.7)).

Conclusion

In this general population study, attention disorders, stressful life events and especially substance use seemed to be more important than physical health for the discrepancy between expected and attained level of secondary education. The longitudinal design of the present study and the broad range of health-related factors that were studied, adds insights to the process of health-selection.

Do school teachers and primary contacts in residential youth care institutions recognize mental health problems in adolescents?

BACKGROUND

Studies show that adolescents living in residential youth care (RYC) institutions experience more mental health problems than others. This paper studies how well teachers and primary contacts in RYC institutions recognize adolescents' mental health problems as classified by The Child and Adolescent Psychiatric Assessment diagnostic interviews (CAPA).

METHODS

All residents between 12 and 23 years of age living in RYC institutions in Norway and enrolled in school at the time of data collection were invited to participate in the study. Of the 601 available children, 400 participated in the study, namely 230 girls, mean age = 16.9 years, SD = 1.2 and 170 boys, mean age = 16.5 years, SD = 1.5. The Child Behavior Checklist (CBCL) and Teacher's Report Form (TRF) were used. The sensitivity and specificity of these instruments were studied.

RESULTS

We observed a significant gap between the mental health problems diagnosed by the CAPA interviews and the problems reported by primary contacts on the CBCL and by teachers on the TRF. The CBCL showed a higher sensitivity than the TRF, whereas the TRF showed a higher specificity than the CBCL. Both primary contacts and teachers classified externalizing problems fairly well such as ADHD in both genders and conduct disorder in girls. Both teachers and primary contacts, however, had more problems detecting internalizing problems. Teachers may have a tendency to view most students as healthy and to underestimate the severity of their problems, whereas primary contacts may tend to overestimate the number of problems and view adolescents as sicker than they really are.

CONCLUSION

The Child Welfare System should revise their intake procedures to detect possible problems early on and to introduce the necessary treatment. It is important to identify factors that increase healthy school adaption in order for these adolescents to accomplish school in a proper way since education is important for a successful adult life.