SummaryBackgroundAntibiotic use in human medicine, veterinary medicine, and agriculture has been linked to the rise of antibiotic resistance globally. We did a systematic review and meta-analysis to summarise the effect that interventions to reduce antibiotic use in food-producing animals have on the presence of antibiotic-resistant bacteria in animals and in humans.MethodsOn July 14, 2016, we searched electronic databases (Agricola, AGRIS, BIOSIS Previews, CAB Abstracts, MEDLINE, Embase, Global Index Medicus, ProQuest Dissertations, Science Citation Index) and the grey literature. The search was updated on Jan 27, 2017. Inclusion criteria were original studies that reported on interventions to reduce antibiotic use in food-producing animals and compared presence of antibiotic-resistant bacteria between intervention and comparator groups in animals or in human beings. We extracted data from included studies and did meta-analyses using random effects models. The main outcome assessed was the risk difference in the proportion of antibiotic-resistant bacteria.FindingsA total of 181 studies met inclusion criteria. Of these, 179 (99%) described antibiotic resistance outcomes in animals, and 81 (45%) of these studies were included in the meta-analysis. 21 studies described antibiotic resistance outcomes in humans, and 13 (62%) of these studies were included in the meta-analysis. The pooled absolute risk reduction of the prevalence of antibiotic resistance in animals with interventions that restricted antibiotic use commonly ranged between 10 and 15% (total range 0–39), depending on the antibiotic class, sample type, and bacteria under assessment. Similarly, in the human studies, the pooled prevalence of antibiotic resistance reported was 24% lower in the intervention groups compared with control groups, with a stronger association seen for humans with direct contact with food-producing animals.InterpretationInterventions that restrict antibiotic use in food-producing animals are associated with a reduction in the presence of antibiotic-resistant bacteria in these animals. A smaller body of evidence suggests a similar association in the studied human populations, particularly those with direct exposure to food-producing animals. The implications for the general human population are less clear, given the low number of studies. The overall findings have directly informed the development of WHO guidelines on the use of antibiotics in food-producing animals.FundingWorld Health Organization.

The somewhat higher subscale scores than previously reported for older children appear to be consistent with more sleep problems in younger children.

ObjectiveTo determine the association between subjective social status (SSS), or the individual's perception of his or her position in the social hierarchy, and the odds of coronary artery disease (CAD), hypertension, diabetes, obesity and dyslipidaemia.Study DesignSystematic review and meta-analysis.MethodsWe searched PubMed, MEDLINE, EMBASE, CINAHL, PsycINFO, SocINDEX, Web of Science and reference lists of all included studies up to October 2014, with a verification search in July 2015. Inclusion criteria were original studies in adults that reported odds, risk or hazard ratios of at least one outcome of interest (CAD, hypertension, diabetes, obesity or dyslipidaemia), comparing ‘lower’ versus ‘higher’ SSS groups, where SSS is measured on a self-anchoring ladder. ORs were pooled using a random-effects model.Results10 studies were included in the systematic review; 9 of these were included in the meta-analysis. In analyses unadjusted for objective socioeconomic status (SES) measures such as income, education or occupation, the pooled OR comparing the bottom versus the top of the SSS ladder was 1.82 (95% CI 1.10 to 2.99) for CAD, 1.88 (95% CI 1.27 to 2.79) for hypertension, 1.90 (95% CI 1.25 to 2.87) for diabetes, 3.68 (95% CI 2.03 to 6.64) for dyslipidaemia and 1.57 (95% CI 0.95 to 2.59) for obesity. These associations were attenuated when adjusting for objective SES measures, with the only statistically significant association remaining for dyslipidaemia (OR 2.10, 95% CI 1.09 to 4.06), though all ORs remained greater than 1.ConclusionsLower SSS is associated with significantly increased odds of CAD, hypertension, diabetes and dyslipidaemia, with a trend towards increased odds of obesity. These trends are consistently present, though the effects attenuated when adjusting for SES, suggesting that perception of one's own status on a social hierarchy has health effects above and beyond one's actual income, occupation and education.

BackgroundAdministrative health data are increasingly used for research and surveillance to inform decision-making because of its large sample sizes, geographic coverage, comprehensivity, and possibility for longitudinal follow-up. Within Canadian provinces, individuals are assigned unique personal health numbers that allow for linkage of administrative health records in that jurisdiction. It is therefore necessary to ensure that these data are of high quality, and that chart information is accurately coded to meet this end. Our objective is to explore the potential barriers that exist for high quality data coding through qualitative inquiry into the roles and responsibilities of medical chart coders.MethodsWe conducted semi-structured interviews with 28 medical chart coders from Alberta, Canada. We used thematic analysis and open-coded each transcript to understand the process of administrative health data generation and identify barriers to its quality.ResultsThe process of generating administrative health data is highly complex and involves a diverse workforce. As such, there are multiple points in this process that introduce challenges for high quality data. For coders, the main barriers to data quality occurred around chart documentation, variability in the interpretation of chart information, and high quota expectations.ConclusionsThis study illustrates the complex nature of barriers to high quality coding, in the context of administrative data generation. The findings from this study may be of use to data users, researchers, and decision-makers who wish to better understand the limitations of their data or pursue interventions to improve data quality.Electronic supplementary materialThe online version of this article (10.1186/s12913-017-2697-y) contains supplementary material, which is available to authorized users.