Background: Digital health literacy has emerged as a critical skill set to navigate the digital age. Objective: This review sought to broadly summarize the literature on associations between digital health literacy and (1) sociodemographic characteristics, (2) health resource use, and (3) health outcomes in the general population, patient groups, or parent or caregiver groups. Methods: A rapid review of literature published between January 2016 and May 2022 was conducted through a search of 4 web-based databases. Articles were included on the basis of the following keywords: “measured digital health literacy,” “digital literacy,” “ehealth literacy,” “e-health literacy,” “electronic health literacy,” or “internet health literacy” in adult populations; participants were from countries where English was the primary language; studies had to be cross-sectional, longitudinal, prospective, or retrospective, and published in English. Results: Thirty-six articles met the inclusion criteria. Evidence on the associations between digital health literacy and sociodemographic characteristics varied (27/36, 75% included studies), with higher education (16/21, 76.2% studies that examined the association) and younger age (12/21, 57.1% studies) tending to predict higher digital health literacy; however, other studies found no associations. No differences between genders were found across the majority of studies. Evidence across ethnic groups was too limited to draw conclusions; some studies showed that those from racial and ethnic minority groups had higher digital health literacy than White individuals, while other studies showed no associations. Higher digital health literacy was associated with digital health resource use in the majority of studies (20/36, 55.6%) that examined this relationship. In addition, higher digital health literacy was also associated with health outcomes across 3 areas (psychosocial outcomes; chronic disease and health management behaviors; and physical outcomes) across 17 included studies (17/36, 47.2%) that explored these relationships. However, not all studies on the relationship among digital health literacy and health resource use and health outcomes were in the expected direction. Conclusions: The review presents mixed results regarding the relationship between digital health literacy and sociodemographic characteristics, although studies broadly found that increased digital health literacy was positively associated with improved health outcomes and behaviors. Further investigations of digital health literacy on chronic disease outcomes are needed, particularly across diverse groups. Empowering individuals with the skills to critically access and appraise reliable health information on digital platforms and devices is critical, given emerging evidence that suggests that those with low digital health literacy seek health information from unreliable sources. Identifying cost-effective strategies to rapidly assess and enhance digital health literacy capacities across community settings thus warrants continued investigation.

Shift work is associated with diet-related chronic conditions such as obesity and cardiovascular disease. This study aimed to explore factors influencing food choice and dietary intake in shift workers. A fixed mixed method study design was undertaken on a convenience sample of firefighters who continually work a rotating roster. Six focus groups (n = 41) were conducted to establish factors affecting dietary intake whilst at work. Dietary intake was assessed using repeated 24 h dietary recalls (n = 19). Interviews were audio recorded, transcribed verbatim, and interpreted using thematic analysis. Dietary data were entered into FoodWorks and analysed using Wilcoxon signed-rank test; p < 0.05 was considered significant. Thematic analysis highlighted four key themes influencing dietary intake: shift schedule; attitudes and decisions of co-workers; time and accessibility; and knowledge of the relationship between food and health. Participants reported consuming more discretionary foods and limited availability of healthy food choices on night shift. Energy intakes (kJ/day) did not differ between days that included a day or night shift but greater energy density (ED_energy, kJ/g/day) of the diet was observed on night shift compared with day shift. This study has identified a number of dietary-specific shift-related factors that may contribute to an increase in unhealthy behaviours in a shift-working population. Given the increased risk of developing chronic diseases, organisational change to support workers in this environment is warranted.

Low skeletal muscle mass is known to be associated with poor morbidity and mortality outcomes in cancer, but evidence of its impact on health‐related quality of life (HRQOL) is less established. This systematic review and meta‐analysis was performed to investigate the relationship between skeletal muscle mass and HRQOL in adults with cancer. Five databases (Ovid MEDLINE, Embase via Ovid, CINAHL plus, Scopus, and PsycInfo) were systematically searched from 1 January 2007 until 2 September 2020. Studies reporting on the association between measures of skeletal muscle (mass and/or radiodensity) derived from analysis of computed tomography imaging, and a validated measure of HRQOL in adults with cancer, were considered for inclusion. Studies classifying skeletal muscle mass as a categorical variable (low or normal) were combined in a meta‐analysis to investigate cross‐sectional association with HRQOL. Studies reporting skeletal muscle as a continuous variable were qualitatively synthesized. A total of 14 studies involving 2776 participants were eligible for inclusion. Skeletal muscle mass classified as low or normal was used to dichotomize participants in 10 studies (n = 1375). Five different cut points were used for classification across the 10 studies, with low muscle mass attributed to 58% of participants. Low muscle mass was associated with poorer global HRQOL scores [n = 985 from seven studies, standardized mean difference −0.27, 95% confidence interval (CI) −0.40 to −0.14,P < 0.0001], and poorer physical functioning domain HRQOL scores (n = 507 from five studies, standardized mean difference −0.40, 95% CI −0.74 to −0.05,P = 0.02), but not social, role, emotional, or cognitive functioning domain scores (allP > 0.05). Five studies examined the cross‐sectional relationship between HRQOL and skeletal muscle mass as a continuous variable and found little evidence of an association unless non‐linear analysis was used. Two studies investigated the relationship between longitudinal changes in both skeletal muscle and HRQOL, reporting that an association exists across several HRQOL domains. Low muscle mass may be associated with lower global and physical functioning HRQOL scores in adults with cancer. The interpretation of this relationship is limited by the varied classification of low muscle mass between studies. There is a need for prospective, longitudinal studies examining the interplay between skeletal muscle mass and HRQOL over time, and data should be made accessible to enable reanalysis according to different cut points. Further research is needed to elucidate the causal pathways between these outcomes.

Current dietary trends show that humans consume up to 40% of their energy intake during the night. Those who habitually eat during the night are observed to have an increased risk of metabolic conditions such as type-2 diabetes and cardiovascular disease. Increasing evidence suggest that a biological consequence of eating during the night is a larger postprandial glucose response, compared to meals eaten earlier in the day. However, findings from individual acute postprandial studies have been inconsistent, due to variations in protocols. Therefore, this review aimed to systematically summarize findings from acute postprandial studies and investigate whether postprandial glucose and insulin response at night differs to during the day in healthy adults. This would indicate a possible physiological mechanism linking habitual nighttime eating and increased risk of metabolic conditions. Seven electronic databases were searched in February 2018. Included studies met the following criteria: had a day-time test between 0700 – 1600h, a nighttime test between 2000 and 0400h, the test meals were identical and consumed by the same participant at both day and night time points, preceded by a 3-h fast (minimum). Primary outcome measures were postprandial glucose and insulin incremental area under the curve (iAUC) or area under the curve (AUC). Studies that reported numerical data were included in the meta-analyses, conducted using Stata statistical software (version 13.0, StataCorp, College Station, TX, USA). For eligible studies that did not report numerical data, their authors’ conclusions on the effect of time of day on the primary outcome measures were summarized qualitatively. Full text of 172 articles were assessed for eligibility. Fifteen studies met the eligibility criteria, ten of which were included in the meta-analyses. Meta-analysis for glucose showed a lower postprandial glucose response in the day compared to during the night, after an identical meal (SMD = −1.66; 95% CI, −1.97 to −1.36; p < .001). This was supported by the findings from included studies ineligible for meta-analysis. Meta-analysis also showed a lower postprandial insulin response in the day compared to during the night (SMD = −0.35; 95% CI, −0.63 to −0.06; p = .016). However, findings from included studies ineligible for meta-analysis were inconsistent. Our results suggest poor glucose tolerance at night compared to the day. This may be a contributing factor to the increased risk of metabolic diseases observed in those who habitually eat during the night, such as shift workers.