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OBJECTIVES: Dietary recommendations for individuals with diabetes are easy to provide, but adherence is difficult to monitor. The objective of this study was to investigate whether there was a difference in grocery purchases between households with and without diabetes.STUDY DESIGN: Cohort study.METHODS: Consumer purchase data in 2019 was collected from 6662 households donating their supermarket receipts via a receipt collecting service. Of these households, 718 included at least one individual with diabetes. The monetary percentages spent on specific food groups were used to characterize households using all purchases in 2019. A probability index model was used to compare households with diabetes to households without diabetes.RESULTS: We included 405,264 shopping trips in 2019 attributed to 6662 households. Both households with and without diabetes spent the highest monetary percentage on sweets (with diabetes: 9.3%, without diabetes: 8.8%), with no statistically significant difference detected. However, compared to households without diabetes, households with diabetes had a significantly higher probability of spending a higher monetary percentage on butter, oil and dressings; non-sugary drinks; processed red meat and ready meals as well as a significantly lower probability of spending a higher monetary percentage on accessory compounds; alcoholic beverages; eggs; grains; rice and pasta, and raw vegetables.CONCLUSIONS: Households with diabetes spent a relatively higher monetary value on several unhealthy foods and less on several healthy groceries compared to households without diabetes. There is a need for more diabetes self-management education focused on including more healthy dietary choices in their household grocery purchases.

Background A family history of specific disorders (e.g., autism, depression, epilepsy) has been linked to risk for autism spectrum disorder (ASD). This study examines whether family history data could be used for ASD risk prediction. Methods We followed all Danish live births, from 1980 to 2012, of Denmark-born parents for an ASD diagnosis through April 10, 2017 (N = 1,697,231 births; 26,840 ASD cases). Linking each birth to three-generation family members, we identified 438 morbidity indicators, comprising 73 disorders reported prospectively for each family member. We tested various models using a machine learning approach. From the best-performing model, we calculated a family history risk score and estimated odds ratios and 95% confidence intervals for the risk of ASD. Results The best-performing model comprised 41 indicators: eight mental conditions (e.g., ASD, attention-deficit/hyperactivity disorder, neurotic/stress disorders) and nine nonmental conditions (e.g., obesity, hypertension, asthma) across six family member types; model performance was similar in training and test subsamples. The highest risk score group had 17.0% ASD prevalence and a 15.3-fold (95% confidence interval, 14.0–17.1) increased ASD risk compared with the lowest score group, which had 0.6% ASD prevalence. In contrast, individuals with a full sibling with ASD had 9.5% ASD prevalence and a 6.1-fold (95% confidence interval, 5.9–6.4) higher risk than individuals without an affected sibling. Conclusions Family history of multiple mental and nonmental conditions can identify more individuals at highest risk for ASD than only considering the immediate family history of ASD. A comprehensive family history may be critical for a clinically relevant ASD risk prediction framework in the future.

Importance: Bystander-delivered defibrillation (hereinafter referred to as bystander defibrillation) of patients with out-of-hospital cardiac arrests (OHCAs) remains limited despite the widespread dissemination of automated external defibrillators (AEDs).Objective: To examine calendar changes in bystander defibrillation and subsequent survival according to a public or a residential location of the cardiac arrest after nationwide initiatives in Denmark to facilitate bystander-mediated resuscitative efforts, including bystander defibrillation.Design, Setting, and Participants: This nationwide study identified 18 688 patients in Denmark with first-time OHCA from June 1, 2001, to December 31, 2012, using the Danish Cardiac Arrest Registry. Patients had a presumed cardiac cause of arrest that was not witnessed by emergency medical services personnel. Data were analyzed from April 1, 2015, to December 10, 2016.Exposures: Nationwide initiatives to facilitate bystander resuscitative efforts, including bystander defibrillation, consisted of resuscitation training of Danish citizens, dissemination of on-site AEDs, foundation of an AED registry linked to emergency medical dispatch centers, and dispatcher-assisted guidance of bystander resuscitation efforts.Main Outcomes and Measures: The proportion of patients who received bystander defibrillation according to the location of the cardiac arrest and their subsequent 30-day survival.Results: Of the 18 688 patients with OHCAs (67.8% men and 32.2% women; median [interquartile range] age, 72 [62-80] years), 4783 (25.6%) had a cardiac arrest in a public location and 13 905 (74.4%) in a residential location. The number of registered AEDs increased from 141 in 2007 to 7800 in 2012. The distribution of AED location was consistently skewed in favor of public locations. Bystander defibrillation increased in public locations from 3 of 245 (1.2%; 95% CI, 0.4%-3.5%) in 2001 to 78 of 510 (15.3%; 95% CI, 12.4%-18.7%) in 2012 (P Conclusions and Relevance: Initiatives to facilitate bystander defibrillation were associated with a marked increase in bystander defibrillation in public locations, whereas bystander defibrillation remained limited in residential locations. Concomitantly, survival increased after bystander defibrillation in residential and public locations.

Denne artikel demonstrerer, hvordan en analyse og formidling af resultater fra en multilevelanalyse med fordel kan suppleres med grafiske illustrationer.Ved brug af data fra European Social Survey demonstreres det, hvordan man grafisk kan forenkle både fortolkning og formidling af ellers forholdsvist komplicerede resultater som eksempelvis Random Intercept-, Random Slope- og cross-level interaktionseffekter.Demonstrationen foretages gennem en analyse af sammenhængen mellem individuel social kapital og jobtilfredshed på tværs af 23 europæiske lande. Det undersøges hertil, hvordan denne sammenhæng varierer alt efter de specifikke kulturelle forhold, der er til stede i de enkelte lande.