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Atopic eczema is a common health problem in children. The prevalence has increased in the past decades. Besides a genetic predisposition, lifestyle factors, dietary habits and indoor environments are thought to be related to its high prevalence. A cross-sectional questionnaire study was carried out in 2011 in the Wuhan area to study associations between home environments and children’s health. The questionnaires were replied to by parents of 2193 children 1–8 years old and the response rate was 91.4% (2193/2400). The results show: (1) The prevalence of “eczema symptom ever that lasted for 6 months” was 23.2%; “eczema symptom in the last 12 months” 7.4% and “awake at night due to itchy rash” 3.4%. (2) Risk factors: Closer to business area (AOR 1.4), moisture related problems (AOR 1.3–2.2), moldy and stuffy odor perception (AOR 1.5), mice observed (AOR 1.8), pet keeping (AOR 1.3), exposure to environmental tobacco smoke (AOR 1.3) and incense (AOR 1.8) were significant risk factors for atopic eczema symptoms ever. Living in an apartment, compared to single family house, was related to more eczema symptom in the last 12 months. Damp clothing/bed sheets and perception of stuffy odor were risk factors for both “eczema symptom in the last 12 months” and “awake due to itchy rash (severe eczema)”. The odds ratio of mice observed for severe eczema was 3.1 (95% CI: 1.4–6.7). It suggests that urbanization, life style and dampness problems at home were significant risk factors for eczema symptoms among children in Wuhan, China.

The understanding and analysis of video content are fundamentally important for numerous applications, including video summarization, retrieval, navigation, and editing. An important part of this process is to detect salient (which usually means important and interesting) objects in video segments. Unlike existing approaches, we propose a method that combines the saliency measurement with spatial and temporal coherence. The integration of spatial and temporal coherence is inspired by the focused attention in human vision. In the proposed method, the spatial coherence of low-level visual grouping cues (e.g. appearance and motion) helps per-frame object-background separation, while the temporal coherence of the object properties (e.g. shape and appearance) ensures consistent object localization over time, and thus the method is robust to unexpected environment changes and camera vibrations. Having developed an efficient optimization strategy based on coarse-to-fine multi-scale dynamic programming, we evaluate our method using a challenging dataset that is freely available together with this paper. We show the effectiveness and complementariness of the two types of coherence, and demonstrate that they can significantly improve the performance of salient object detection in videos.