ObjectiveTo systematically review and critically appraise prognostic models for falls in community-dwelling older adults.Eligibility criteriaProspective cohort studies with any follow-up period. Studies had to develop or validate multifactorial prognostic models for falls in community-dwelling older adults (60+ years). Models had to be applicable for screening in a general population setting.Information sourceMEDLINE, EMBASE, CINAHL, The Cochrane Library, PsycINFO and Web of Science for studies published in English, Danish, Norwegian or Swedish until January 2020. Sources also included trial registries, clinical guidelines, reference lists of included papers, along with contacting clinical experts to locate published studies.Data extraction and risk of biasTwo authors performed all review stages independently. Data extraction followed the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist. Risk of bias assessments on participants, predictors, outcomes and analysis methods followed Prediction study Risk Of Bias Assessment Tool.ResultsAfter screening 11 789 studies, 30 were eligible for inclusion (n=86 369 participants). Median age of participants ranged from 67.5 to 83.0 years. Falls incidences varied from 5.9% to 59%. Included studies reported 69 developed and three validated prediction models. Most frequent falls predictors were prior falls, age, sex, measures of gait, balance and strength, along with vision and disability. The area under the curve was available for 40 (55.6%) models, ranging from 0.49 to 0.87. Validated models’ The area under the curve ranged from 0.62 to 0.69. All models had a high risk of bias, mostly due to limitations in statistical methods, outcome assessments and restrictive eligibility criteria.ConclusionsAn abundance of prognostic models on falls risk have been developed, but with a wide range in discriminatory performance. All models exhibited a high risk of bias rendering them unreliable for prediction in clinical practice. Future prognostic prediction models should comply with recent recommendations such as Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis.PROSPERO registration numberCRD42019124021.

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Iodine intake affects the occurrence of thyroid disorders. However, the association of iodine intake with longevity remains to be described. This led us to perform a 20-year follow-up on participants from the Randers-Skagen (RaSk) study. Residents in Randers born in 1920 (n=210) and Skagen born in 1918-1923 (n=218) were included in a clinical study in 1997-1998. Mean iodine content in drinking water was 2 µg/L in Randers and 139 µg/L in Skagen. We collected baseline data through questionnaires, performed physical examinations, and measured iodine concentrations in spot urine samples. Income data were retrieved from Danish registries. We performed follow-up on mortality until 12-12-2017 using Danish registries. Complete follow-up data were available on 428 out of 430 of participants (99.5%). At baseline, the median urinary iodine concentration was 55 µg/L in Randers and 160 µg/L in Skagen residents. Participants were long-term residents with 72.8% and 92.7% residing for more than 25 years in Randers and Skagen, respectively. Cox regression showed that living in Skagen compared to Randers was associated with lower hazard ratio (HR) of death in both age- and sex-adjusted analysis (HR 0.60, 95% CI: 0.41-0.87, P = 0.006), but also after adjustment for age, sex, number of drugs, Charlson Comorbidity Index, smoking, alcohol, and income (HR 0.60, 95% CI: 0.41-0.87, P = 0.008). Residing in iodine replete Skagen was associated with increased longevity. This indicates, that long-term residency in an iodine replete environment may be associated with increased longevity compared to residency in an iodine deficient environment.