The 45-year sample remains broadly representative of the surviving cohort, but specific biases may need to be taken into account in future research. Renewed efforts to re-engage all cohort members will improve the representativeness and value of the study.

Northern Ireland. In contrast to previous surveys, Scotland did not participate meaning that UK wide comparisons are not possible. The first paper in this series 1 describes in more detail the sampling and analytic methods. This paper, the second in the series, summarises the main findings of the 2009 Adult Dental Health Survey (ADHS) with respect to the state of teeth and periodontal tissues and how these impact on the quality of life of people. It is based on data from both the questionnaire and the clinical examination. For the dental examination, teeth were examined and data recorded at tooth surface level for caries and restoration status. Periodontal examination was undertaken at two sites on each tooth and data were also recorded for plaque, tooth wear and occlusal contacts. The questionnaire included information on oral-health-related quality of life, by focusing on the impact of oral conditions on the daily life of participants. We employed two indicators (OHIP-14 2 and

Adverse SEP in childhood is associated with a poorer health profile in mid-adulthood, independently of adult social position, and across diverse measures of disease risk and physical and mental functioning.

This meta-analysis examined the effects of early interventions on social communication outcomes for young children with autism spectrum disorder. A systematic review of the literature included 1442 children (mean age 3.55 years) across 29 studies. The overall effect size of intervention on social communication outcomes was significant (g = 0.36). The age of the participants was related to the treatment effect size on social communication outcomes, with maximum benefits occurring at age 3.81 years. Results did not differ significantly depending on the person implementing the intervention. However, significantly larger effect sizes were observed in studies with contextbound outcome measures. The findings of this meta-analysis highlight the need for further research examining specific components of interventions associated with greater and more generalized gains.

Oral health inequalities associated with socioeconomic status are widely observed but may depend on the way that both oral health and socioeconomic status are measured. Our aim was to investigate inequalities using diverse indicators of oral health and 4 socioeconomic determinants, in the context of age and cohort. Multiple linear or logistic regressions were estimated for 7 oral health measures representing very different outcomes (2 caries prevalence measures, decayed/missing/filled teeth, 6-mm pockets, number of teeth, anterior spaces, and excellent oral health) against 4 socioeconomic measures (income, education, Index of Multiple Deprivation, and occupational social class) for adults aged ≥21 y in the 2009 UK Adult Dental Health Survey data set. Confounders were adjusted and marginal effects calculated. The results showed highly variable relationships for the different combinations of variables and that age group was critical, with different relationships at different ages. There were significant income inequalities in caries prevalence in the youngest age group, marginal effects of 0.10 to 0.18, representing a 10- to 18-percentage point increase in the probability of caries between the wealthiest and every other quintile, but there was not a clear gradient across the quintiles. With number of teeth as an outcome, there were significant income gradients after adjustment in older groups, up to 4.5 teeth (95% confidence interval, 2.2-6.8) between richest and poorest but none for the younger groups. For periodontal disease, income inequalities were mediated by other socioeconomic variables and smoking, while for anterior spaces, the relationships were age dependent and complex. In conclusion, oral health inequalities manifest in different ways in different age groups, representing age and cohort effects. Income sometimes has an independent relationship, but education and area of residence are also contributory. Appropriate choices of measures in relation to age are fundamental if we are to understand and address inequalities.