Measuring the Burden of Infodemics: Summary of the Methods and Results of the Fifth WHO Infodemic Management Conference.

Background: An infodemic is excess information, including false or misleading information, that spreads in digital and physical environments during a public health emergency. The COVID-19 pandemic has been accompanied by an unprecedented global infodemic that has led to confusion about the benefits of medical and public health interventions, with substantial impact on risk-taking and health-seeking behaviors, eroding trust in health authorities and compromising the effectiveness of public health responses and policies. Standardized measures are needed to quantify the harmful impacts of the infodemic in a systematic and methodologically robust manner, as well as harmonizing highly divergent approaches currently explored for this purpose.

Leptin, acylcarnitine metabolites and development of adiposity in the Rhea mother-child cohort in Crete, Greece.

Objective: This study aims to investigate relations of serum leptin at age 4 with development of adiposity and linear growth during 3 years of follow-up among 75 Greek children and to identify serum metabolites associated with leptin at age 4 and to characterize their associations with adiposity gain and linear growth.

Methods: Linear regression models that accounted for maternal age, education and gestational weight gain and child's age and sex were used to examine associations of leptin and leptin-associated metabolites measured at age 4 with indicators of adiposity and linear growth at age 7.

Results: Each 1-unit increment in natural log-(ln)-transformed leptin corresponded with 0.