Prevalence and determinants of periodic limb movements in the general population.

OBJECTIVE: Periodic limb movements during sleep (PLMS) are sleep phenomena characterized by periodic episodes of repetitive stereotyped limb movements. The aim of this study was to describe the prevalence and determinants of PLMS in a middle to older aged general population. METHODS: Data from 2,162 subjects (51.2% women, mean age = 58.4 ± 11.1 years) participating in a population-based study (HypnoLaus, Lausanne, Switzerland) were collected. Assessments included laboratory tests, sociodemographic data, personal and treatment history, and full polysomnography at home. PLMS index (PLMSI) was determined, and PLMSI > 15/h was considered as significant. RESULTS: Prevalence of PLMSI > 15/h was 28.6% (31.3% in men, 26% in women). Compared to subjects with PLMSI ≤ 15/h, subjects with PLMSI > 15/h were older (p < 0.001), were predominantly males (p = 0.007), had a higher proportion of restless legs syndrome (RLS; p < 0.001), had a higher body mass index (p = 0.001), and had a lower mean glomerular filtration rate (p < 0.001). Subjects with PLMSI > 15/h also had a higher prevalence of diabetes, hypertension, and beta-blocker or hypnotic treatments. The prevalence of antidepressant use was higher, but not statistically significant (p = 0.07). Single nucleotide polymorphisms (SNPs) within BTBD9 (rs3923809), TOX3 (rs3104788), and MEIS1 (rs2300478) genes were significantly associated with PLSMI > 15/h. Conversely, mean hemoglobin and ferritin levels were similar in both groups. In the multivariate analysis, age, male gender, antidepressant intake, RLS, and rs3923809, rs3104788, and rs2300478 SNPs were independently associated with PLMSI > 15/h. INTERPRETATION: PLMS are highly prevalent in our middle-aged European population. Age, male gender, RLS, antidepressant treatment, and specific BTBD9, TOX3, and MEIS1 SNP distribution are independent predictors of PLMSI > 15/h. ANN NEUROL 2016;79:464-474.

Equating accelerometer estimates among youth: The Rosetta Stone 2.

OBJECTIVES: Different accelerometer cutpoints used by different researchers often yields vastly different estimates of moderate-to-vigorous intensity physical activity (MVPA). This is recognized as cutpoint non-equivalence (CNE), which reduces the ability to accurately compare youth MVPA across studies. The objective of this research is to develop a cutpoint conversion system that standardizes minutes of MVPA for six different sets of published cutpoints. DESIGN: Secondary data analysis. METHODS: Data from the International Children's Accelerometer Database (ICAD; Spring 2014) consisting of 43,112 Actigraph accelerometer data files from 21 worldwide studies (children 3-18 years, 61.5% female) were used to develop prediction equations for six sets of published cutpoints. Linear and non-linear modeling, using a leave one out cross-validation technique, was employed to develop equations to convert MVPA from one set of cutpoints into another. Bland Altman plots illustrate the agreement between actual MVPA and predicted MVPA values. RESULTS: Across the total sample, mean MVPA ranged from 29.7MVPAmind(-1) (Puyau) to 126.1MVPAmind(-1) (Freedson 3 METs). Across conversion equations, median absolute percent error was 12.6% (range: 1.3 to 30.1) and the proportion of variance explained ranged from 66.7% to 99.8%. Mean difference for the best performing prediction equation (VC from EV) was -0.110mind(-1) (limits of agreement (LOA), -2.623 to 2.402). The mean difference for the worst performing prediction equation (FR3 from PY) was 34.76mind(-1) (LOA, -60.392 to 129.910). CONCLUSIONS: For six different sets of published cutpoints, the use of this equating system can assist individuals attempting to synthesize the growing body of literature on Actigraph, accelerometry-derived MVPA.