BackgroundExcess screen media use is a robust predictor of childhood obesity. Understanding how household factors may affect children’s screen use is needed to tailor effective intervention efforts. The preschool years are a critical time for obesity prevention, and while it is likely that greater household disorder influences preschool-aged children’s screen use, data on that relationship are absent. In this study, our goal was to quantify the relationships between household chaos and screen use in preschool-aged children.MethodsA cross-sectional, online survey was administered to 385 parents of 2–5 year-olds recruited in 2017. Household chaos was measured with the Confusion, Hubbub and Order Scale (i.e., the chaos scale), a validated, parent-reported scale. The scale consists of 15 items, each scored on a 4-point Likert scale. Final scores were the sum across the 15 items and modeled as quartiles for analyses. Parents reported their children’s screen use for nine electronic media activities. Adjusted linear and Poisson regression were used to model associations between household chaos and children’s total weekly screen use, screen use within one hour of bedtime and screen use in the bedroom.ResultsChildren averaged 31.0 (SD = 23.8) hours per week with screens, 49.6% used screens within one hour of bedtime and 41.0% used screens in their bedrooms. In adjusted regression models, greater household chaos was positively associated with weekly screen use (P = 0.03) and use of screens within one hour of bedtime (P < 0.01) in a dose-dependent manner. Children in the fourth versus the first quartile of household chaos were more likely to use screens in their bedroom (P = 0.03).ConclusionsGreater household chaos was associated with increased total screen use as well as screen use behaviors that are related to disrupted nighttime sleep. Findings suggest that household chaos may be an obesity risk factor during the preschool years because of such effects on screen use, and highlight the need to consider household chaos when implementing home-based obesity prevention programs for young children.Electronic supplementary materialThe online version of this article (10.1186/s12889-018-6113-2) contains supplementary material, which is available to authorized users.
BackgroundPhysical activity after cancer diagnosis improves quality of life and may lengthen survival. However, objective data in cancer survivors are limited and no physical activity tracker has been validated for use in this population.ObjectiveThe aim of this study was to validate the Fitbit One’s measures of physical activity over 7 days in free-living men with localized prostate cancer.MethodsWe validated the Fitbit One against the gold-standard ActiGraph GT3X+ accelerometer in 22 prostate cancer survivors under free-living conditions for 7 days. We also compared these devices with the HJ-322U Tri-axis USB Omron pedometer and a physical activity diary. We used descriptive statistics (eg, mean, standard deviation, median, interquartile range) and boxplots to examine the distribution of average daily light, moderate, and vigorous physical activity and steps measured by each device and the diary. We used Pearson and Spearman rank correlation coefficients to compare measures of physical activity and steps between the devices and the diary.ResultsOn average, the men wore the devices for 5.8 days. The mean (SD) moderate-to-vigorous physical activity (MVPA; minutes/day) measured was 100 (48) via Fitbit, 51 (29) via ActiGraph, and 110 (78) via diary. The mean (SD) steps/day was 8724 (3535) via Fitbit, 8024 (3231) via ActiGraph, and 6399 (3476) via pedometer. Activity measures were well correlated between the Fitbit and ActiGraph: 0.85 for MPVA and 0.94 for steps (all P<.001). The Fitbit’s step measurements were well correlated with the pedometer (0.67, P=.001), and the Fitbit’s measure of MVPA was well correlated with self-reported activity in the diary (0.84; P<.001).ConclusionsAmong prostate cancer survivors, the Fitbit One’s activity and step measurements were well correlated with the ActiGraph GT3X+ and Omron pedometer. However, the Fitbit One measured two times more MVPA on average compared with the ActiGraph.
The West African Ebola Virus Disease epidemic of 2014-16 cost more than 11,000 lives. Interventions targeting key behaviors to curb transmission, such as safe funeral practices and reporting and isolating the ill, were initially unsuccessful in a climate of fear, mistrust, and denial. Building trust was eventually recognized as essential to epidemic response and prioritized, and trust was seen to improve toward the end of the epidemic as incidence fell. However, little is understood about how and why trust changed during Ebola, what factors were most influential to community trust, and how different institutions might have been perceived under different levels of exposure to the outbreak. In this large-N household survey conducted in Liberia in 2018, we measured self-reported trust over time retrospectively in three different communities with different exposures to Ebola. We found trust was consistently higher for non-governmental organizations than for the government of Liberia across all time periods. Trust reportedly decreased significantly from the start to the peak of the epidemic in the study site of highest Ebola incidence. This finding, in combination with a negative association found between knowing someone infected and trust of both iNGOs and the government, indicates the experience of Ebola may have itself caused a decline of trust in the community. These results suggest that national governments should aim to establish trust when engaging communities to change behavior during epidemics. Further research on the relationship between trust and epidemics may serve to improve epidemic response efficacy and behavior uptake.
Hand hygiene is central to hospital infection control. During the 2014–2016 West Africa Ebola virus disease epidemic in Liberia, gaps in hand hygiene infrastructure and health worker training contributed to hospital-based Ebola transmission. Hand hygiene interventions were undertaken post-Ebola, but many improvements were not sustainable. This study characterizes barriers to, and facilitators of, hand hygiene in rural Liberian hospitals and evaluates readiness for sustainable, locally derived interventions to improve hand hygiene. Research enumerators collected data at all hospitals in Bong and Lofa counties, Liberia, in the period March–May 2020. Enumerators performed standardized spot checks of hand hygiene infrastructure and supplies, structured observations of hand hygiene behavior, and semi-structured key informant interviews for thematic analysis. During spot checks, hospital staff reported that handwashing container water was always available in 89% (n = 42) of hospital wards, piped running water in 23% (n = 11), and soap in 62% (n = 29). Enumerators observed 5% of wall-mounted hand sanitizer dispensers (n = 8) and 95% of pocket-size dispensers (n = 53) to be working. In interviews, hospital staff described willingness to purchase personal hand sanitizer dispensers when hospital-provided supplies were unavailable. Low-cost, sustainable interventions should address supply and infrastructure-related obstacles to hospital hand hygiene improvement.
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