The early identification of risk factors on the pathway to school dropout in the SIODO study:A sequential mixed-methods study

BACKGROUND: School dropout is a persisting problem with major socioeconomic consequences. Although poor health probably contributes to pathways leading to school dropout and health is likely negatively affected by dropout, these issues are relatively absent on the public health agenda. This emphasises the importance of integrative research aimed at identifying children at risk for school dropout at an early stage, discovering how socioeconomic status and gender affect health-related pathways that lead to dropout and developing a prevention tool that can be used in public health services for youth. METHODS/DESIGN: The SIODO study is a sequential mixed-methods study. A case–control study will be conducted among 18 to 24 year olds in the south of the Netherlands (n = 580). Data are currently being collected from compulsory education departments at municipalities (dropout data), regional public health services (developmental data from birth onwards) and an additional questionnaire has been sent to participants (e.g. personality data). Advanced analyses, including cluster and factor analyses, will be used to identify children at risk at an early stage. Using the quantitative data, we have planned individual interviews with participants and focus groups with important stakeholders such as parents, teachers and public health professionals. A thematic content analysis will be used to analyse the qualitative data. DISCUSSION: The SIODO study will use a life-course perspective, the ICF-CY model to group the determinants and a mixed-methods design. In this respect, the SIODO study is innovative because it both broadens and deepens the study of health-related determinants of school dropout. It examines how these determinants contribute to socioeconomic and gender differences in health and contributes to the development of a tool that can be used in public health practice to tackle the problem of school dropout at its roots

Fetal growth influences lymphocyte subset counts at birth: The generation R study

Background: Preterm born and low-birth-weight infants are at risk for severe infections in infancy. It has been suggested that these infants have an immature immune system. Objective:To assess the associations of gestational age, birth weight and fetal growth with absolute lymphocyte subset counts at birth. Methods: This study was conducted in 571 infants participating in the Generation R Study, a population-based prospective cohort study from fetal life onwards. Gestational age and birth weight were obtained from midwives and hospital registries. Fetal growth was defined as increase in weight between late pregnancy and birth. Lymphocytes and T lymphocyte subset counts in cord blood were determined by 6-color flow cytometry. Multivariate linear regression models with adjustment for gender, maternal education, smoking, alcohol use, fever and mode of delivery were applied. Results: Per week increase of gestational age, T, B and NK lymphocyte counts increased with 3, 5 and 6%, respectively (p < 0.05). Helper, cytotoxic and naive T lymphocyte counts increased with 3, 4 and 5%, respectively (p < 0.05), but memory T lymphocyte counts did not. Increased birth weight and fetal growth were significantly associated with higher B lymphocyte counts, independent of gestational age, but not with the other lymphocyte subset counts. Conclusions: Lymphocyte subset counts increase with prolonged gestation, suggesting an ongoing development of the immune system. Birth weight and fetal growth seem to influence only B lymphocyte counts. Copyrigh

Altered folate and vitamin B12 metabolism in families with spina bifida offspring

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