The Relationship of Restless Legs Syndrome to History of Pregnancy-Induced Hypertension.

BACKGROUND: Restless legs syndrome (RLS), a burdensome sleep disorder, has been associated with cardiovascular disease (CVD), hypertension, diabetes, and related disorders. However, the relationship of RLS to history of pregnancy-induced hypertension (PIH), a predictor of subsequent CVD, diabetes, and associated conditions, remains little explored. In this study, we investigated the relationship of RLS to history of PIH in a sample of primary care patients. METHODS: Participants were women aged ≥40 years drawn from an anonymous survey study of West Virginia primary care patients. Data collected included detailed information on demographics, lifestyle factors, sleep patterns, and reproductive/medical history; the survey also included an RLS diagnostic questionnaire. Women who were pregnant or unsure about their pregnancy status were excluded from the analyses. RESULTS: Of the 498 participants in the final analytic sample, 24.5% met diagnostic criteria for RLS (17.9% with symptoms ≥once/week, 11.9% with symptoms ≥3 times/week); 73 (16.5% of parous women) reported a history of PIH, defined as physician-diagnosed preeclampsia or gestational hypertension. After adjustment for demographics, lifestyle characteristics, obesity, reproductive history, health conditions, and other factors, those reporting a history of PIH were approximately twice as likely to meet criteria for RLS (odds ratio [OR] = 1.9; 95% confidence interval [CI] = 1.1, 3.6). These associations increased in magnitude with increasing symptom frequency (adjusted OR for RLS with symptoms ≥3 times/week = 3.8; CI 1.9, 7.6; p for trend = 0.003). CONCLUSIONS: History of PIH was strongly and positively related to current RLS in this study of primary care patients; these findings further support a possible role for metabolic dysregulation in RLS etiology.

Restless legs syndrome in an appalachian primary care population: prevalence, demographic and lifestyle correlates, and burden.

BACKGROUND: Restless legs syndrome (RLS) is a common and distressing sensorimotor disorder of unknown etiology. While the epidemiology of RLS has been examined in several North American and European studies, research on RLS and RLS burden in poor, rural populations, including those residing in Appalachia, remains sparse. In this study, we investigated RLS prevalence in an Appalachian primary care population and examined the association of RLS to demographic factors, lifestyle characteristics, sleep quality, and mood disorders. METHODS: Participants of this anonymous survey study were community-dwelling adults aged ≥ 18 years visiting one of 4 West Virginia primary care clinics. Data gathered included detailed information on sleep patterns, demographic characteristics, lifestyle factors, and health/medical history; the survey also included questions specific to RLS diagnosis and severity. Response rates were excellent, with 68% of eligible adults contacted returning completed surveys (N = 1,424/2,087). Pregnant women (N = 65) and those with missing data on key variables (N = 142) were excluded from the analyses. RESULTS: Of the 1,217 participants included in the final analytic sample, 19.6% (18.2% with symptoms at least once/month) met the 4 IRLSSG diagnostic criteria in the absence of positional discomfort or leg cramps; 14.5% reported RLS symptoms at least once/week and 10.1% indicated symptoms ≥ 3×/week. Excluding respondents with diabetes, kidney disease, or anemia reduced these rates only slightly. Those with RLS were more likely to be older, female, lower income, unemployed, disabled, non-Hispanic white, and less likely to be college educated than those without RLS. Mood and sleep impairment were significantly elevated in those with RLS; after adjustment for demographic and lifestyle characteristics, health history, and other factors, those with RLS remained significantly more likely to indicate a history of depression (adjusted odds ratio [OR] = 1.9; 95% confidence interval [CI] = 1.4, 2.6) and anxiety (OR = 1.6, CI 1.1, 2.2), to report sleep impairment both 4 (OR = 2.4, CI 1.6, 3.7) and 7 days/week (OR = 1.8, CI 1.3, 2.4), and a mean sleep duration < 5 h/night (OR = 1.7, CI 1.2, 2.3). These associations increased in both strength and magnitude with increasing symptom frequency (p's for trend ≤ 0.01). CONCLUSIONS: Findings of this preliminary anonymous survey study suggest that RLS prevalence is high in this Appalachian primary care population and that RLS is associated with significant burden in terms of both mood and sleep impairment.

Appalachian versus non-Appalachian U.S. traffic fatalities, 2008-2010.

PURPOSE: Although myriad health disparities exist in Appalachia, limited research has examined traffic fatalities in the region. This study compared traffic fatality rates in Appalachia and the non-Appalachian United States. METHODS: Fatality Analysis Reporting System and Census data from 2008 through 2010 were used to calculate traffic fatality rates. Poisson models were used to estimate unadjusted (rate ratio [RR]) and adjusted rate ratios, controlling for age, gender, and county-specific population density levels. RESULTS: The Appalachian traffic fatality rate was 45% (95% confidence interval [CI], 1.42-1.47) higher than the non-Appalachian rate. Although only 29% of fatalities occur in rural counties in non-Appalachia versus 48% in Appalachia, rates in rural counties were similar (RR, 0.97; 95% CI, 0.95-1.00). However, the rate for urban, Appalachian counties was 42% (95% CI, 1.38-1.45) higher than among urban, non-Appalachian counties. Appalachian rates were higher for passenger vehicle drivers, motorcyclists, and all terrain vehicle riders, regardless of rurality, as well as for passenger vehicle passengers overall and for urban counties. Conversely, Appalachia experienced lower rates among pedestrians and bicyclists, regardless of rurality. CONCLUSIONS: Disparities in traffic fatality rates exist in Appalachia. Although elevated rates are partially explained by the proportion of residents living in rural settings, overall rates in urban Appalachia were consistently higher than in urban non-Appalachia.