Key developmental milestones helped to identify children with special educational needs and disabilities at an early stage

AIM

Responding to developmental delay promptly is important, as it helps children to reach their full potential. This study investigated how developmental milestones predicted primary school children with special educational needs and disabilities (SEND) at an early stage.

METHODS

We obtained data about 36 milestones between 12 and 45 months using the Dutch Development Instrument. Development, primary school classification and background characteristics were collected from the Dutch Preventive Child Healthcare system in Utrecht from 2008 to 2016. We investigated SEND classifications and the primary schools that the children attended at 4-12 years of age. The findings include area under the curve (AUC) data.

RESULTS

Data on 30 579 children in mainstream schools and 1055 children with SEND were available. Different milestones predicted SEND classifications. Fourteen milestones and parental education predicted attendance at special needs schools with smaller classes (AUC 0.913). Nine milestones, sex, migration background and parental education predicted attendance at schools for severe communication problems (AUC 0.963). Ten milestones and parental education predicted attendance at schools for severe learning difficulties (AUC 0.995). Milestones did not accurately predict attendance at schools for severe behavioural or psychiatric problems.

CONCLUSION

Milestones at 12-45 months predicted most SEND classifications at primary school age, except severe behavioural or psychiatric problems.

Differences in adults' health and health behaviour between 16 European urban areas and the associations with socio-economic status and physical and social environment

Background

With a growing proportion of the European population living in urban areas (UAs), exploring health in urban areas becomes increasingly important. The objective of this study is to assess the magnitude of differences in health and health behaviour between adults living in urban areas (UAs) across Europe. We also explored whether and to what extent such differences can be explained by socio-economic status (SES) and physical or social environment. Data were obtained from a cross-sectional questionnaire survey, performed between as part of the European Urban Health Indicator System Part 2 (EURO-URHIS 2) project. Using multi-level logistic regression analysis, UA differences in psychological distress, self-assessed health, overweight and obesity, daily smoking, binge drinking and physical exercise were assessed. Median Odds Ratios (MORs) were calculated to estimate the extent to which the observed variance is attributable to UA, individual-level SES (measured by perceived financial strains, education level and employment status) and/or characteristics of physical and social environment. The dataset included 14 022 respondents in 16 UAs within 9 countries. After correction for age and gender, all MORs, except that for daily smoking, indicated statistically significant UA health differences. SES indicators (partly) explained UA differences in psychological distress, decreasing the MOR from 1.43 [95% credible interval (Cr.I.) 1.27-1.67, baseline model], to 1.25 (95% Cr.I. 1.14-1.40, SES model): a reduction of 42%. Accounting for the quality of green areas reduced the MOR for psychological distress by an additional 40%, to 1.15 (95% Cr.I. 1.05-1.28). Our study showed large differences in health and health behaviour between European UAs. Reducing socio-economic disadvantage and improving the quality of the neighbourhood's green spaces may reduce UA differences in psychological distress.