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Age–sex heterogeneity among Russia’s indigenous small-numbered peoples: a census-based typology and the statistical core-region condition

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TL;DR

This study analyzes Russia’s indigenous small-numbered peoples' age–sex profiles using census data, revealing a continuum from younger to older demographic poles. A two-cluster typology is supported, with core-region profiles closely matching national profiles when the core share exceeds approximately 85%, providing a practical criterion for proxy validity.

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Demographic structure does not determine intergenerational cultural continuity, but it conditions its opportunities and constraints. Using Rosstat’s 2020 All-Russian Population Census tabulations, this study assembles non-overlapping national and regional age–sex profiles for legally recognized Indigenous Small-Numbered Peoples of the Russian Federation. Three questions are addressed: which latent dimensions organize territorial variation in these profiles, whether a low-dimensional typology provides a defensible summary, and under what degree of territorial concentration a national profile can be used as a proxy for the largest regional concentration. The main specification transforms 15 age-group shares with a centered log-ratio procedure, adds overall and ages-20–39 sex ratios, and analyzes 103 ethnonym × territory profiles ( N ≥ 200 ) with principal component analysis and clustering. A separate core-region analysis compares national and core age–sex distributions with L 1 distances. PC1 is a youth-to-ageing gradient, whereas PC2 captures male-skewed working-age structure. The first two principal components explain 65.0% of total variance. Silhouette diagnostics favor k = 2 (0.457), but robustness checks show that this partition is only a pragmatic summary of a dominant continuum rather than evidence of two natural kinds. The main robust result is the continuum itself and the contrast between its younger and older poles, while intermediate cases remain soft assignments. The younger cluster ( n = 86 ) has a mean median age of 31.4 years and a mean ageing index of 26.2; the older cluster ( n = 17 ) has corresponding values of 48.1 and 231.0. National-vs.-core discrepancy declines systematically with core share. In this dataset and census framework, ethnonyms with core share around or above 0.85 have L 1 distance no greater than 0.041; this value should be treated as an empirical rule of thumb rather than a universal threshold. The study contributes a reproducible statistical typology and an operational criterion for when national demographic profiles are, and are not, adequate proxies for territorially concentrated populations.

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Sleep time and efficiency in patients undergoing laboratory-based polysomnography.
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Sleep quality in patients studied with laboratory-based polysomnography may differ from sleep quality in patients studied at home but remains clinically relevant and important to describe. We assessed objective sleep quality and explored factors associated with poor sleep in patients undergoing laboratory-based polysomnography. We reviewed diagnostic polysomnography studies from a 10-year period at a single sleep center. Total sleep time (TST) and sleep efficiency (SE) were assessed as markers of sleep quality. Poor sleep was defined as TST ≤ 4 hours or SE ≤ 50%. Multivariable analysis was performed to determine associations between objective sleep quality as an outcome and multiple candidate predictors including age, sex, race, body mass index, comorbidities, severity of obstructive sleep apnea, and central nervous system medications. Among 4957 patients (age 53 ± 15 years), average TST and median SE were 5.8 hours and 79%, respectively. There were 556 (11%) and 406 (8%) patients who had poor sleep based on TST and SE, respectively. In multivariable analysis, those who were older (per 10 years: 1.48 [1.34, 1.63]), male (1.38 [1.14,1.68]), and had severe obstructive sleep apnea (1.76 [1.28, 2.43]) were more likely to have short sleep. Antidepressant use was associated with lower odds of short sleep (0.77 [0.59,1.00]). Older age (per 10 years: 1.48 [1.34, 1.62]), male sex (1.34 [1.07,1.68]), and severe obstructive sleep apnea (2.16 [1.47, 3.21]) were associated with higher odds of poor SE. We describe TST and SE from a single sleep center cohort. Multiple demographic characteristics were associated with poor objective sleep in patients during laboratory-based polysomnography. Harrison EI, Roth RH, Lobo JM, et al. Sleep time and efficiency in patients undergoing laboratory-based polysomnography. J Clin Sleep Med. 2021;17(8):1591-1598.

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Comparative analysis of volatiles difference of Yunnan sun-dried Pu-erh green tea from different tea mountains: Jingmai and Wuliang mountain by chemical fingerprint similarity combined with principal component analysis and cluster analysis.
  • Mar 10, 2016
  • Chemistry Central Journal
  • Yuanshuang Wu + 5 more

BackgroundModern instrumental analysis technology can provide various chemical data and information on tea samples. Unfortunately, it remains difficult to extract the useful information. We describe the use of chemical fingerprint similarities, combined with principal component and cluster analyses, to distinguish and recognize Pu-erh green teas, which from two tea mountains, Wuliang and Jingmai, in the Pu-erh district of Yunnan province. The volatile components of all 20 Pu-erh green teas (10 Wuliang and 10 Jingmai teas) were extracted and identified by headspace solid-phase micro extraction (HS-SPME) combined with gas chromatography-mass spectrometry (GC-MS).ResultsSixty-three volatiles (including alcohols, hydrocarbons, ketones, and aldehydes) were identified in the 20 Pu-erh green teas, and differences in compound compositions between them were also observed. Through fingerprint similarity, combined with principal component and cluster analyses, the 20 Pu-erh green teas were differentiated successfully based on their volatile characteristics.ConclusionsThis study demonstrates that the GC-MS combined with chemical fingerprint and unsupervised pattern recognition method is suitable for the investigation of the volatile profiling and evaluating the quality and authenticity of teas related to the different origins.Graphical abstractDifferentiate Pu-erh green teas from different tea mountains by using chemical fingerprint similarity and multivariate statistical methodsElectronic supplementary materialThe online version of this article (doi:10.1186/s13065-016-0159-y) contains supplementary material, which is available to authorized users.

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