scholarly journals Prevalence of chronic disabling fatigue in children and adolescents

2004 ◽  
Vol 184 (6) ◽  
pp. 477-481 ◽  
Author(s):  
Anne Farmer ◽  
Tom Fowler ◽  
Jane Scourfield ◽  
Anita Thapar
Keyword(s):  
Young People ◽  
Response Rate ◽  
Chronic Fatigue ◽  
Population Based ◽  
Self Report ◽  
Lifetime Prevalence ◽  
Telephone Interviews ◽  
Fatigue Syndrome ◽  
Prevalence Estimates ◽  
Experienced Fatigue

BackgroundThe epidemiology of chronic fatiguing illnesses in young people is poorly understood.AimsTo estimate the lifetime prevalence of different definitions of chronic fatigue in 8-to 17-year-olds.MethodParticipants came from two population-based twin series. Parents completed self-report questionnaires that enquired whether either child had ever experienced more than a few days of disabling fatigue. Telephone interviews were undertaken for individuals who had experienced such an episode.ResultsQuestionnaires were returned by 1468 families (65% response rate) and telephone interviews were undertaken regarding 99 of the 129 subjects (77%) who had experienced fatigue. The lifetime prevalence estimates ranged from 2.34% (95% CI 1.75–2.94) for disabling fatigue lasting 3 months to 1.29% (95% CI 0.87–1.71) for a disorder resembling adult operationally defined chronic fatigue syndrome.ConclusionsFrom the age of 11 years, young people have similar rates and types of chronic fatiguing illnesses to adults.

scholarly journals Predictors of new onsets of irritable bowel syndrome, chronic fatigue syndrome and fibromyalgia: the lifelines study

2020 ◽  
pp. 1-9 ◽  
Author(s):  
Rei Monden ◽  
Judith G. M. Rosmalen ◽  
Klaas J. Wardenaar ◽  
Francis Creed
Keyword(s):  
Irritable Bowel Syndrome ◽  
Chronic Fatigue Syndrome ◽  
Chronic Fatigue ◽  
Population Based ◽  
Current Approach ◽  
Self Report ◽  
Fatigue Syndrome ◽  
Starting Point ◽  
Irritable Bowel

Abstract Background It has been claimed that functional somatic syndromes share a common etiology. This prospective population-based study assessed whether the same variables predict new onsets of irritable bowel syndrome (IBS), chronic fatigue syndrome (CFS) and fibromyalgia (FM). Methods The study included 152 180 adults in the Dutch Lifelines study who reported the presence/absence of relevant syndromes at baseline and follow-up. They were screened at baseline for physical and psychological disorders, socio-demographic, psycho-social and behavioral variables. At follow-up (mean 2.4 years) new onsets of each syndrome were identified by self-report. We performed separate analyses for the three syndromes including participants free of the relevant syndrome or its key symptom at baseline. LASSO logistic regressions were applied to identify which of the 102 baseline variables predicted new onsets of each syndrome. Results There were 1595 (1.2%), 296 (0.2%) and 692 (0.5%) new onsets of IBS, CFS, and FM, respectively. LASSO logistic regression selected 26, 7 and 19 predictors for IBS, CFS and FM, respectively. Four predictors were shared by all three syndromes, four predicted IBS and FM and two predicted IBS and CFS but 28 predictors were specific to a single syndrome. CFS was more distinct from IBS and FM, which predicted each other. Conclusions Syndrome-specific predictors were more common than shared ones and these predictors might form a better starting point to unravel the heterogeneous etiologies of these syndromes than the current approach based on symptom patterns. The close relationship between IBS and FM is striking and requires further research.

scholarly journals Structural brain changes versus self-report: machine-learning classification of chronic fatigue syndrome patients

2018 ◽  
Vol 236 (8) ◽  
pp. 2245-2253 ◽  
Author(s):  
Landrew S. Sevel ◽  
Jeff Boissoneault ◽  
Janelle E. Letzen ◽  
Michael E. Robinson ◽  
Roland Staud
Keyword(s):  
Machine Learning ◽  
Chronic Fatigue Syndrome ◽  
Chronic Fatigue ◽  
Self Report ◽  
Machine Learning Classification ◽  
Fatigue Syndrome ◽  
Brain Changes ◽  
Structural Brain

scholarly journals Use of Population-Based Surveys for Estimating the Population Size of Persons Who Inject Drugs in the United States

2020 ◽  
Vol 222 (Supplement_5) ◽  
pp. S218-S229
Author(s):  
Heather Bradley ◽  
Elizabeth M Rosenthal ◽  
Meredith A Barranco ◽  
Tomoko Udo ◽  
Patrick S Sullivan ◽  
...  
Keyword(s):  
United States ◽  
Drug Use ◽  
Population Size ◽  
Prescription Drugs ◽  
The United States ◽  
Population Based ◽  
Self Report ◽  
Persons Who Inject Drugs ◽  
Population Size Estimates ◽  
Prevalence Estimates

Abstract Background In the United States, injection is an increasingly common route of administration for opioids and other substances. Estimates of the number of persons who inject drugs (PWID) are needed for monitoring risk-specific infectious disease rates and health services coverage. Methods We reviewed design and instruments for 4 national household surveys, 2012–2016, for their ability to produce unbiased injection drug use (IDU) prevalence estimates. We explored potential analytic adjustments for reducing biases through use of external data on (1) arrest, (2) narcotic overdose mortality, and (3) biomarker-based sensitivity of self-reported illicit drug use. Results Estimated national past 12 months IDU prevalence ranged from 0.24% to 0.59% across surveys. All surveys excluded unstably housed and incarcerated persons, and estimates were based on <60 respondents reporting IDU behavior in 3 surveys. No surveys asked participants about nonmedical injection of prescription drugs. Analytic adjustments did not appreciably change IDU prevalence estimates due to suboptimal specificity of data points. Conclusions PWID population size estimates in the United States are based on small numbers and are likely biased by undercoverage of key populations and self-report. Novel methods as discussed in this article may improve our understanding of PWID population size and their health needs.

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