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Concerning the use of air classifiers with cut sizes in the micron range and lower, it is necessary to disperse the feed material properly in an air flow to avoid agglomerates larger than the desired cut size. Commonly used dispersing devices such as injectors use large amounts of air. To reduce the size and costs of the subsequent air classifiers, two new types of dispersing systems were developed, one design being related to a brush feeder and the other to a pin mill. Both apply mechanical rather than fluid mechanical forces in the dispersion process. The brush disperser achieves the same size distributions as the pin mill disperser with much less machinery. Its properties as a feeding and dispersing system are shown and its ability to disperse particles in the submicron range is confirmed by two independent particle size analysis systems: a new diffraction spectrometer and an impactor.

Background Health literacy (HL) has been acknowledged as a critical determinant of health. While HL and its potential determinants have been studied in adults, little research has been conducted with children. Therefore, this study investigates factors associated with children's subjective HL to explore potential entry points for the promotion of HL in childhood. Methods Cross-sectional data was collected from 4th-graders at German schools with a self-report questionnaire. Age, sex, family affluence, functional HL, self-efficacy, motivation to learn about health, and perceived parental health orientation were included as potential determinants, while the dependent variable subjective HL was assessed with a newly developed scale. We used hierarchical linear regression to explain variance in HL with different sets of predictors. Results n = 907 4th-graders (53.4% female) were surveyed. Subjective HL was high, with 82.2% reporting that it was “rather easy” or “very easy” for them to deal with health-related information. Age, sex, home language, and family affluence together were able to explain 2% of variance in subjective HL. In contrast, 19.3% of variance could be explained by all independent variables together, whereby family affluence, functional HL, self-efficacy, motivation, and perceived parental health orientation were significant predictors (p < .01). Motivation was the most potent predictor (β = .24), followed by parental health orientation (β = .18) and self-efficacy (β = .11). Conclusions This study was able to identify potential predictors of HL among children. Our data indicate that the promotion of health-related motivation and self-efficacy, but also of certain parental attitudes might be particularly fruitful in order to support the development of HL early in the life course. However, intervention research will need to provide further evidence on the extent to which these factors can be modified and actually lead to increased HL. Key messages This study was able to identify potential predictors of children’s HL which might be used to inform interventions. Further longitudinal research is necessary to verify our findings.

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