Odor-color associations differ with verbal descriptors for odors : A comparison of three linguistically diverse groups

People appear to have systematic associations between odors and colors. Previous research has emphasized the perceptual nature of these associations, but little attention has been paid to what role language might play. It is possible odor-color associations arise through a process of labeling; that is, participants select a descriptor for an odor and then choose a color accordingly (e.g., banana odor → "banana" label → yellow). If correct, this would predict odor-color associations would differ as odor descriptions differ. We compared speakers of Dutch (who overwhelmingly describe odors by referring to the source; e.g., smells like banana) with speakers of Maniq and Thai (who also describe odors with dedicated, abstract smell vocabulary; e.g., musty), and tested whether the type of descriptor mattered for odor-color associations. Participants were asked to select a color that they associated with an odor on two separate occasions (to test for consistency), and finally to label the odors. We found the hunter-gatherer Maniq showed few, if any, consistent or accurate odor-color associations. More importantly, we found the types of descriptors used to name the smells were related to the odor-color associations. When people used abstract smell terms to describe odors, they were less likely to choose a color match, but when they described an odor with a source-based term, their color choices more accurately reflected the odor source, particularly when the odor source was named correctly (e.g., banana odor → yellow). This suggests language is an important factor in odor-color cross-modal associations

Continuous glucose monitoring during diabetic pregnancy (GlucoMOMS): A multicentre randomized controlled trial

Aim: Diabetes is associated with a high risk of adverse pregnancy outcomes. Optimal glycaemic control is fundamental and is traditionally monitored with self-measured glucose profiles and periodic HbA1c measurements. We investigated the effectiveness of additional use of retrospective continuous glucose monitoring (CGM) in diabetic pregnancies. Material and methods: We performed a nationwide multicentre, open label, randomized, controlled trial to study pregnant women with type 1 or type 2 diabetes who were undergoing insulin therapy at gestational age < 16 weeks, or women who were undergoing insulin treatment for gestational diabetes at gestational age < 30 weeks. Women were randomly allocated (1:1) to intermittent use of retrospective CGM or to standard treatment. Glycaemic control was assessed by CGM for 5-7 days every 6 weeks in the CGM group, while self-monitoring of blood glucose and HbA1c measurements were applied in both groups. Primary outcome was macrosomia, defined as birth weight above the 90th percentile. Secondary outcomes were glycaemic control and maternal and neonatal complications. Results: Between July 2011 and September 2015, we randomized 300 pregnant women with type 1 (n = 109), type 2 (n = 82) or with gestational (n = 109) diabetes to either CGM (n = 147) or standard treatment (n = 153). The incidence of macrosomia was 31.0% in the CGM group and 28.4% in the standard treatment group (relative risk [RR], 1.06; 95% CI, 0.83-1.37). HbA1c levels were similar between treatment groups. Conclusions: In diabetic pregnancy, use of intermittent retrospective CGM did not reduce the risk of macrosomia. CGM provides detailed information concerning glycaemic fluctuations but, as a treatment strategy, does not translate into improved pregnancy outcome