Background Germany has a long history of migration. In 2020, more than 1 person in every 4 people had a statistically defined, so-called migration background in Germany, meaning that the person or at least one of their parents was born with a citizenship other than German citizenship. People with a history of migration are not represented proportionately to the population within public health monitoring at the Robert Koch Institute, thus impeding differentiated analyses of migration and health. To develop strategies for improving the inclusion of people with a history of migration in health surveys, we conducted a feasibility study in 2018. The lessons learned were implemented in the health interview survey German Health Update (Gesundheit in Deutschland aktuell [GEDA]) Fokus, which was conducted among people with selected citizenships representing the major migrant groups in Germany. Objective GEDA Fokus aimed to collect comprehensive data on the health status and social, migration-related, and structural factors among people with selected citizenships to enable differentiated explanations of the associations between migration-related aspects and their impact on migrant health. Methods GEDA Fokus is an interview survey among people with Croatian, Italian, Polish, Syrian, or Turkish citizenship living in Germany aged 18-79 years, with a targeted sample size of 1200 participants per group. The gross sample of 33,436 people was drawn from the residents’ registration offices of 99 German municipalities based on citizenship. Sequentially, multiple modes of administration were offered. The questionnaire was available for self-administration (web-based and paper-based); in larger municipalities, personal or phone interviews were possible later on. Study documents and the questionnaire were bilingual—in German and the respective translation language depending on the citizenship. Data were collected from November 2021 to May 2022. Results Overall, 6038 respondents participated in the survey, of whom 2983 (49.4%) were female. The median age was 39 years; the median duration of residence in Germany was 10 years, with 19.69% (1189/6038) of the sample being born in Germany. The overall response rate was 18.4% (American Association for Public Opinion Research [AAPOR] response rate 1) and was 6.8% higher in the municipalities where personal interviews were offered (19.3% vs 12.5%). Overall, 78.12% (4717/6038) of the participants self-administered the questionnaire, whereas 21.88% (1321/6038) took part in personal interviews. In total, 41.85% (2527/6038) of the participants answered the questionnaire in the German language only, 16.69% (1008/6038) exclusively used the translation. Conclusions Offering different modes of administration, as well as multiple study languages, enabled us to recruit a heterogeneous sample of people with a history of migration. The data collected will allow differentiated analyses of the role and interplay of migration-related and social determinants of health and their impact on the health status of people with selected citizenships. International Registered Report Identifier (IRRID) DERR1-10.2196/43503

Background By explaining the development of health inequalities, eco-social theories highlight the importance of social environments that children are embedded in. The most important environment during early childhood is the family, as it profoundly influences children’s health through various characteristics. These include family processes, family structure/size, and living conditions, and are closely linked to the socioeconomic position (SEP) of the family. Although it is known that the SEP contributes to health inequalities in early childhood, the effects of family characteristics on health inequalities remain unclear. The objective of this scoping review is to synthesise existing research on the mediating and moderating effects of family characteristics on socioeconomic health inequalities (HI) during early childhood in high-income countries. Methods This review followed the methodology of “Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews”. To identify German and English scientific peer-reviewed literature published from January 1st, 2000, to December 19th, 2019, the following search term blocks were linked with the logical operator “AND”: (1) family structure/size, processes, living conditions, (2) inequalities, disparities, diversities, (3) income, education, occupation, (4) health and (5) young children. The search covered the electronic databases PubMed, PsycINFO, and Scopus. Results The search yielded 7,089 records. After title/abstract and full-text screening, only ten peer-reviewed articles were included in the synthesis, which analysed the effects of family characteristics on HI in early childhood. Family processes (i.e., rules /descriptive norms, stress, parental screen time, parent–child conflicts) are identified to have mediating or moderating effects. While families’ living conditions (i.e., TVs in children’s bedrooms) are suggested as mediating factors, family structure/size (i.e., single parenthood, number of children in the household) appear to moderate health inequalities. Conclusion Family characteristics contribute to health inequalities in early childhood. The results provide overall support of models of family stress and family investment. However, knowledge gaps remain regarding the role of family health literacy, regarding a wide range of children’s health outcomes (e.g., oral health, inflammation parameters, weight, and height), and the development of health inequalities over the life course starting at birth.

We examined sleep difficulties among adolescents in Germany and the association with physical activity (PA). Furthermore, we analyzed whether the association varied with the socioeconomic status (SES) among adolescent girls and boys in Germany. Using data from the German Health Interview Examination Survey for Children and Adolescents (KiGGS) study (Wave 2), 6599 adolescents aged 11 to 17 years were included in the analyses. We conducted sex-stratified logistic regression analyses. Dependent variables were unrecommended sleep duration (defined as a duration of sleep that does not meet the recommended duration), sleep-onset difficulties, trouble sleeping, and daytime sleepiness. Most adolescent girls and boys reported sleep difficulties. While no associations between PA and sleep difficulties were observed, a significant interaction between PA and SES was found for sleep duration in boys and daytime sleepiness in girls. Thus, adolescents with low SES had fewer sleep difficulties if they met the recommendation for PA, compared with those in other SES groups. In Germany, a large proportion of adolescents have sleep difficulties. We found that the experience of sleep difficulties varied according to PA, sex, and the family SES. Future sleep promotion programs should consider these differences.

This scoping review systematically mapped evidence of the mediating and moderating effects of family characteristics on health inequalities in school-aged children and adolescents (6–18 years) in countries with developed economies in Europe and North America. We conducted a systematic scoping review following the PRISMA extension for Scoping Reviews recommendations. We searched the PubMed, PsycINFO and Scopus databases. Two reviewers independently screened titles, abstracts and full texts. Evidence was synthesized narratively. Of the 12,403 records initially identified, 50 articles were included in the synthesis. The included studies were conducted in the United States (n = 27), Europe (n = 18), Canada (n = 3), or in multiple countries combined (n = 2). We found that mental health was the most frequently assessed health outcome. The included studies reported that different family characteristics mediated or moderated health inequalities. Parental mental health, parenting practices, and parent-child-relationships were most frequently examined, and were found to be important mediating or moderating factors. In addition, family conflict and distress were relevant family characteristics. Future research should integrate additional health outcomes besides mental health, and attempt to integrate the complexity of families. The family characteristics identified in this review represent potential starting points for reducing health inequalities in childhood and adolescence.

Background The number of obese children is rising worldwide. Many studies have investigated single determinants of children’s body mass index (BMI), yet studies measuring determinants at different potential levels of influence are sparse. The aim of this study is to investigate the independent role of parental socioeconomic position (SEP), additional family factors at the micro level, as well as early childhood education and care (ECEC) centre characteristics at the meso level regarding BMI. Methods Analyses used the baseline data of the PReschool INtervention Study (PRINS) including up to 1,151 children from 53 ECEC centres. Multi-level models first estimated the associations of parental SEP indicators (parental school education, vocational training, and household income) with the children’s standard deviation scores for BMI (SDS BMI, standardised for age and gender). Second, structural (number of siblings), psychosocial (strained family relationships), and nutrition behavioural (soft-drink consumption, frequency of fast-food restaurant visits) family factors at the micro level were included. Third, characteristics of the ECEC centre at the meso level in terms of average group size, the ratio of overweight children in the group, ECEC centre type (all-day care), and the location of the ECEC centre (rural vs urban) were included. All analyses were stratified by gender and adjusted for age, migration background, and parental employment status. Results Estimates for boys and girls appeared to differ. In the full model, for boys the parental SEP indicators were not related to SDS BMI. Factors related to SDS BMI in boys were: two or more siblings; B = -.55; p = 0.045 [ref.: no sibling]), the characteristics of the ECEC centre in terms of average group size (20 – 25 children; B = -.54; p = 0.022 [ref.: < 20 children]), and the ratio of overweight children (more overweight children B = -1.39; p < 0.001 [ref.: few overweight children]). For girls the number of siblings (two and more siblings; B = .67; p = 0.027 [ref.: no sibling]) and average group size (> 25 children; B = -.52; p = 0.037 [ref.: < 20 children]) were related to SDS BMI. Conclusions The BMI of preschool children appears to be associated with determinants at the micro and meso level, however with some gender differences. The identified factors at the micro and meso level appear largely modifiable and can inform about possible interventions to reduce obesity in preschool children.