Prevalence of pediatric epilepsy in low-income rural Midwestern counties

Epilepsy & Behavior 53 (2015) 190–196

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Prevalence of pediatric epilepsy in low-income rural Midwestern counties Suzanne R. Hawley a, Elizabeth Ablah b, Dale Hesdorffer c, John M. Pellock d, David P. Lindeman e, Angelia M. Paschal f, David J. Thurman g, Yi Liu c,1, Mary Beth Warren h, Terri Schmitz h, Austin Rogers b,2, Theresa St. Romain i, W. Allen Hauser c,⁎, the Prevalence of Epilepsy in Rural Kansas Study Group a

Wichita State University, Department of Public Health Sciences, 1845 Fairmount Box 43, Wichita, KS 67260-0043, USA University of Kansas School of Medicine—Wichita, Department of Preventive Medicine and Public Health, 1010 N. Kansas, Wichita, KS 67214, USA c Columbia University, 680 West 168 Street, New York, NY 10032, USA d Virginia Commonwealth University, Department of Neurology, P.O. Box 980599, Richmond, VA 23298, USA e University of Kansas Life Span Institute at Parsons, 2601 Gabriel, Parsons, KS 67357, USA f The University of Alabama, Department of Health Science, Box 870311, Tuscaloosa, AL 35487-0311, USA g Emory University, School of Medicine 201 Dowman Dr. Mailstop 1930-001-1AN, Atlanta, GA 30322, USA h University of Kansas Area Health Education Center, 1501 S. Joplin, Pittsburg, KS 66762, USA i P.O. Box 21322, Wichita, KS 67208, USA b

a r t i c l e

i n f o

Article history: Received 11 September 2015 Accepted 13 September 2015 Available online xxxx Keywords: Pediatric epilepsy Epilepsy prevalence Rural populations Low-income populations

a b s t r a c t Epilepsy is one of the most common disabling neurological disorders, but significant gaps exist in our knowledge about childhood epilepsy in rural populations. The present study assessed the prevalence of pediatric epilepsy in nine low-income rural counties in the Midwestern United States overall and by gender, age, etiology, seizure type, and syndrome. Multiple sources of case identification were used, including medical records, schools, community agencies, and family interviews. The prevalence of active epilepsy was 5.0/1000. Prevalence was 5.1/1000 in males and 5.0/1000 in females. Differences by age group and gender were not statistically significant. Future research should focus on methods of increasing study participation in rural communities, particularly those in which research studies are rare. © 2015 Elsevier Inc. All rights reserved.

Prevalence of epilepsy in rural Kansas study group. Participating institutions

Location

Ashley Clinic Coffeyville Regional Medical Center Labette Health Mercy Hospital Mercy Clinic Mt. Carmel Hospital St. John's Regional Medical Center University of Kansas Medical Center (KUMC) KUMC—Area Health Education Center (AHEC) Parsons State Hospital Community Health Center of Southeast Kansas Via Christi Health

Chanute, KS Coffeyville, KS Parsons, KS Independence, KS Independence, KS Pittsburg, KS Joplin, MO Kansas City, KS Pittsburg, KS Parsons, KS Pittsburg, KS Wichita, KS

⁎ Corresponding author at: Department of Epidemiology and GH Sergievsky Center, Columbia University, 680 West 168 Street, New York, NY 10032, USA. Tel.: +1 914 760 3144; fax: +1 212 305 2426. E-mail address: [email protected] (W.A. Hauser). 1 Yi Liu is now a graduate student at the University of Pittsburgh. Her work on this project was completed while employed at Columbia University. 2 Austin Rogers is now a Business Technical Analyst with WellCare.

http://dx.doi.org/10.1016/j.yebeh.2015.09.014 1525-5050/© 2015 Elsevier Inc. All rights reserved.

(continued) Participating institutions

Location

Children's Mercy Hospital University of Oklahoma Medical Center

Kansas City, MO Oklahoma City, OK

Participating practitioners

Location

Dr. Harold Goldman Dr. Devendra Jain Dr. Kore Liow Dr. Subhash Shah Dr. Dwight Lindholm Dr. Modesto Gometz Dr. Manish Dixit Dr. Ivan Osorio Toni Sadler, PA-C Dr. Enrique Chaves Dr. Husam Kayyali Dr. Ahmed Abdelmoity Dr. Britton Zuccarelli Connie Haney, RN Dr. Jeanne King Dr. David Siegler Dr. Walter Lajara-Nanson

Independence, KS Parsons, KS Wichita, KS Wichita, KS Wichita, KS Pittsburg, KS Parsons, KS Kansas City, KS Wichita, KS Kansas City, KS Kansas City, MO Kansas City, MO Kansas City, MO Kansas City, MO Oklahoma City, OK Tulsa, OK Bartlesville, OK

S.R. Hawley et al. / Epilepsy & Behavior 53 (2015) 190–196

1. Introduction Epilepsy, a neurological condition characterized by recurrent unprovoked seizures, affects an estimated 2.2 million people in the United States and 65 million worldwide and is most often manifest in childhood and older adults [1]. At present, information is lacking about prevalence and etiology of epilepsy in pediatric rural populations in the United States [1]. Different methodologies and sources of cases can affect the measured prevalence of active epilepsy [2]. Past studies of pediatric epilepsy prevalence have involved the collection of cases from retrospective chart reviews [3–5], door to door surveys [6–8], questionnaires administered through primary care offices [9], and random samples of a community [10]. The latter method identified a very high prevalence, especially for children aged 0–4 years (65.4/1000) [10], whereas studies using door to door surveys [8] and hospital chart abstraction [11] have identified pediatric epilepsy prevalence to be as low as 3.8/1000 and 3.4/1000, respectively. Epilepsy prevalence might be affected by population demographics as well as by methodology. Past prevalence studies conducted in rural areas of the United States have generally reported higher prevalence than studies using similar definitions performed in urban populations [12–14]. However, race and SES may be confounding factors. While epilepsy prevalence has generally been shown to be higher in minority communities when compared with Caucasian communities, the separate impact of socioeconomic status (SES) has seldom been assessed, particularly in a pediatric population. In studies not specific to pediatric populations, low SES has long been associated with increased prevalence of epilepsy [15,16]. This phenomenon was first observed in cross-sectional studies, where it was impossible to determine whether low SES was a risk factor or a consequence of the disorder. More recently, two population-based studies have shown that low SES is associated with an increased incidence of epilepsy [17,18]. This may be partially related to the increased prevalence of risk factors for epilepsy in those of lower SES, but associations held even in those for whom etiology was unknown [18]. We undertook a study of the prevalence of active epilepsy in children in a rural, predominantly Caucasian, low SES population in southeastern Kansas. The population was selected to determine prevalence in a low SES rural community while limiting confounding by race and ethnicity.

2. Material and methods 2.1. Definitions and factors examined Epilepsy was defined according to the guidelines of the Commission on Epidemiology and Prognosis, International League Against Epilepsy [ILAE], as a condition characterized by two or more unprovoked seizures at least 24 h apart [19–21]. Active epilepsy was defined as having a diagnosis of epilepsy and having at least one seizure or taking antiepileptic drugs (AEDs) in the past five years through 2009.

2.1.1. Etiology of epilepsy Etiology of epilepsy was classified as idiopathic/cryptogenic, remote symptomatic, progressive symptomatic, other rare categories that did not fit the prior three etiologies, or unknown [19–22]. Etiology was classified as unknown when etiology information was not present in the medical record.

2.1.2. Seizure type Seizure type was classified as primary generalized, partial with secondary generalization, partial without generalization, both partial and generalized, unclassifiable whether partial or generalized, or unknown [23].

191

2.1.3. Syndrome Syndrome was classified according to the 1989 ILAE Commission on Classification and Terminology as idiopathic generalized epilepsy, cryptogenic or symptomatic generalized epilepsies, localization-related epilepsy, epilepsy with both generalized and localization-related features, no definitive features of partial or generalized epilepsies, or unknown when insufficient information was available to allow classification [22]. 2.2. Participants and site participation for data collection 2.2.1. Ethical approval The study protocol was approved by the University of Kansas and University of Kansas School of Medicine—Wichita Human Subjects Committees, Columbia University Institutional Review Board, and institutional review boards at all participating sites. Table 1 Prevalence of active epilepsy in nine rural Kansas counties by demographics and epilepsy features.

Total Sexb Male Female Age groups 0–4 5–9 10–14 15–18 Countyc Allen Bourbon Cherokee Crawford Labette Montgomery Neosho Wilson Woodson Etiology Idiopathic/cryptogenic Remote symptomatic Progressive symptomatic Other Unknown Seizure type Primary generalized seizures Partial with secondary generalization Partial without generalization Both partial and generalized Unclassifiable, whether partial or generalized Unknown Syndrome Idiopathic generalized Cryptogenic or symptomatic generalized epilepsies Localization-related epilepsiesd Both partial and generalized epilepsies No definitive features of partial or generalized epilepsy Unknown a

N (%)

Base population N (%)

Prevalence per 1000 (95% C.I.)a

216 (100%)

42,897 (100%)

5.0 (4.4, 5.7)

112 (51.9%) 104 (48.1%)

22,002 (51.3%) 20,895 (48.7%)

5.1 (4.6, 5.6) 5.0 (4.5, 5.5)

40 (18.5%) 62 (28.7%) 68 (31.4%) 46 (21.3%)

11,500 (25.0%) 11,030 (24.0%) 10,920 (23.8%) 9447 (20.5%)

3.5 (2.4, 4.6) 5.6 (4.2, 7.0) 6.2 (4.7, 7.7) 4.9 (3.5, 6.3)

12 (5.6%) 14 (6.5%) 14 (6.5%) 48 (22.2%) 40 (18.5%) 43 (19.9%) 26 (12.0%) 11 (5.1%) 4 (1.9%)

3193 (7.4%) 3953 (9.2%) 5356 (12.5%) 9164 (21.4%) 5527 (12.9%) 8631 (20.1%) 4100 (9.6%) 2363 (5.5%) 610 (1.4%)

114 (52.8%) 50 (23.2%) 3 (1.4%) 15 (6.9%) 34 (15.7%)

42,897 (100%) 42,897 (100%) 42,897 (100%) 42,897 (100%) 42,897 (100%)

2.7 (2.2, 3.1) 1.2 (0.8, 1.5) 0.1 (0.0, 0.1) 0.3 (0.2, 0.5) 0.8 (0.5, 1.1)

25 (11.6%) 47 (21.8%)

42,897 (100%) 42,897 (100%)

0.6 (0.4, 0.8) 1.1 (0.8, 1.4)

22 (10.2%) 3 (1.4%) 49 (22.7%)

42,897 (100%) 42,897 (100%) 42,897 (100%)

0.5 (0.3, 0.7) 0.1 (0.0, 0.1) 1.1 (0.8, 1.5)

70 (32.4%)

42,897 (100%)

1.6 (1.2, 2.0)

24 (11.1%) 14 (6.5%)

42,897 (100%) 42,897 (100%)

0.6 (0.3, 0.8) 0.3 (0.2, 0.5)

84 (38.9%)

42,897 (100%)

2.0 (1.5, 2.4)

9 (4.2%)

42,897 (100%)

0.2 (0.1, 0.3)

56 (25.9%)

42,897 (100%)

1.3 (1.0, 1.6)

29 (13.4%)

42,897 (100%)

0.7 (0.4, 0.9)

3.8 (1.6, 5.9) 3.5 (1.7, 5.4) 2.6 (1.2, 4.0) 5.2 (3.8, 6.7) 7.2 (5.0, 9.5) 5.0 (3.5, 6.5) 6.3 (3.9, 8.8) 4.7 (1.9, 7.4) 6.6 (0.1, 13.0)

For calculation of confidence interval of county, etiology, seizure type, and syndrome specific prevalence, Poisson distribution on count was assumed. b For gender specific confidence interval, assumed binomial distribution with expected mean calculated from census data. c Two cases missing county information. d Idiopathic localization-related epilepsy, cryptogenic localization-related epilepsies, symptomatic localization-related epilepsies, and localization-related epilepsies with uncertainty about whether they are cryptogenic or symptomatic.

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2.2.2. Study area Cases were identified in nine rural counties of southeast Kansas (Table 1). In all nine study counties, the percentage of the population identified as Caucasian was above the US average of 75%, ranging from 85.8% in Montgomery County to 97.0% in Woodson County [24]. The percentage of children in poverty ranged from 19.7% in Neosho County to 25.8% in Cherokee County, with most counties having at least 23% of children in poverty compared with the US average of 13.5% [24]. 2.2.3. Medical facilities Children aged 1 month to 17 years of age who had active epilepsy in 2009 were identified at 18 partnering hospitals, clinics, or doctor's offices serving nine contiguous rural Kansas counties (Woodson, Allen, Bourbon, Wilson, Neosho, Crawford, Montgomery, Labette, and Cherokee; Fig. 1). Medical records were abstracted for ZIP code of residence, seizure information, date of birth, gender, comorbidities, medications, parental contact information, and EEG or imaging findings. Participant information was cross-checked with the Kansas Department of Health and Environment Office of Vital Statistics to verify living status. Regional Kansas pediatric neurologists and epilepsy referral centers for the nine-county study area were identified for participation (Fig. 2). Epilepsy referral/surgery centers providing cases included Children's Mercy Hospital in Kansas City, MO; Via Christi Comprehensive Epilepsy Center in Wichita, KS; and University of Kansas Medical Center in Kansas City, KS. The University of Oklahoma also participated, though no cases were identified through that facility. St. John's Regional Medical Center in Joplin, MO, provided some cases, although due to a natural disaster during the study period, the facility was unable to update its review fully. Three local hospitals in the nine-county area declined participation: one each in Allen, Neosho, and Wilson counties. No community hospitals were identified in Cherokee and Woodson counties. A pediatrician in Crawford County and four neurologists outside the nine counties were contacted and also declined participation.

2.2.4. School districts Identification of participants was also facilitated by 33 of the 34 school nurses representing the study area's 28 school districts. Seventeen of the nurses assisted in recruitment by sending information to the parents of children who were thought to have epilepsy. These parents were sent a letter and consent form to return. Upon receiving the signed informed consent form, study personnel contacted the parents to schedule an interview.

2.3. Other recruitment methods Additional prevalent cases were identified through local newspaper advertisements, as well as recruitment postcards that were distributed through schools and community organizations. These instructed parents who thought their child qualified for the study to call a toll-free line and answer a series of screening questions to determine eligibility prior to scheduling an interview.

2.4. Team review of abstracted records A medical record abstraction form was used to ascertain information on seizures from medical records and emergency department visit records. Following abstraction of records, data were transferred to a subject tracking form. This and the final diagnosis form were entered into an electronic database for analysis. Once data were collected from the medical record, consensus conferences were convened to identify and classify active prevalent cases of epilepsy. Two epileptologists and one epidemiologist served on each consensus review. Classification of the cases was considered to be final unless additional information was later retrieved from additional medical records at the original site or from another site, or an interview was conducted.

Fig. 1. Nine-county (study area) map by medical facility participation. Gray = participating. Black = declined participation. Dot = community hospital. Triangle = clinic/physician's office.

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Fig. 2. Participating regional referral centers and pediatric neurologists. Gray = cases identified. Black = no cases identified.

2.5. Statistical methods The prevalence of active epilepsy was calculated per 1000 children according to age, etiology, seizure type, and syndrome using extrapolated US Census Bureau estimates for the nine counties [24]. Active prevalence cases included children with a diagnosis of epilepsy, residing in one of the study counties in 2009, and known to have taken AEDs or to have had a seizure in the preceding five years. The 95% confidence interval for the prevalence was calculated using the Poisson distribution. For gender-specific confidence intervals, we assumed a binomial distribution with the expected calculation from Census data. 3. Results Across the 18 medical facilities, 28 school districts, and one special education cooperative at which potential cases were identified, 382 unique individuals were screened, and 366 with unprovoked nonfebrile seizures during the prevalence period were identified. Of these, 70% (n = 258) of the children were living in one of the study counties in 2009; 84% (n = 216) were classified as having active prevalent epilepsy. The most common diagnoses resulting in exclusion were undefined seizure(s) among children not taking AEDs (n = 14), children with single unprovoked seizures not taking AEDs (n = 10), and children with a history of epilepsy who did not have a seizure in the past five years or were not on AEDs (n = 7). Prevalent epilepsy was identified at medical facilities outside the county of residence in 20% to 100% of the cases in the different counties. All cases were identified at medical facilities outside the county of residence for residents of Allen, Cherokee, Wilson, and Woodson counties.

Prevalence was higher among males than females, but this difference was not statistically significant. Among children aged 0–4 years, the prevalence was lower, but not significantly so when compared with all other age groups. When prevalence was examined by age and gender, there was an increased prevalence in males among children age 0–4 years, 10–14 years, and 15–18 years, while prevalence was higher in females 5–9 years old (Fig. 3), though neither of these comparisons were statistically significant. 3.2. Etiology Etiology of epilepsy was idiopathic/cryptogenic among 53% of prevalent active epilepsy. Prenatal and perinatal etiologies accounted for a further 18% of the total. “Other” etiologies—a mixture of different rare etiologies—accounted for 7% of prevalent cases. Among the active

3.1. Prevalence of epilepsy The prevalence of active epilepsy among children in rural Kansas was 5.0/1000 (Table 1). Prevalence differed across the nine counties. The lowest prevalence was in Cherokee County (2.6/1000), and the highest was in Labette County (7.2/1000); this difference was statistically significant (p b .05).

Fig. 3. Prevalence by age and gender (n = 216).

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Fig. 4. Etiology (n = 216).

prevalence cases, the etiology of 16% of the cases could not be classified because information was unavailable, so classification was listed as “unknown” (Fig. 4). The prevalence of epilepsy was higher for idiopathic/cryptogenic etiology than for each of the other etiologies (Table 1). 3.3. Seizure type For almost one-third of cases (n = 70, 32.4%), only a diagnosis of “epilepsy” was provided, and seizure type was classified as “unknown.” For a further 22.7% (n = 49), information was unavailable to distinguish whether the seizures were partial or generalized, and the type was considered “unclassifiable.” In those with sufficient information to allow classification, the predominant seizure type was partial with secondary generalization (n = 47, 21.8%) (Table 1). 3.4. Syndrome The most prevalent syndromes were localization-related epilepsies (2.0/1000) and cases with “no definitive features of partial or generalized epilepsies” (1.3/1000). Prevalence was 0.6/1000 for idiopathic generalized epilepsy. Prevalence was 0.7/1000 where the syndrome was unknown (Table 1). 4. Discussion The prevalence of epilepsy in our study was 5.0/1000. This is generally consistent with other population-based pediatric US studies, though lower than the prevalence identified in some non-US studies (Table 2). As in several other studies [5,6,25], we found an increasing prevalence throughout early and middle childhood, with a drop in prevalence among the oldest pediatric age group (Table 2), though in the present study these differences were nonsignificant. Other studies found higher prevalence among older children, aged 10–19 years [9,26,27]. Still, other studies found the highest prevalence in children younger than five years, with declining prevalence in older age groups [28,29]. These inconsistent age-specific patterns may reflect different distributions of epilepsy risk factors and differential mortality in children with epilepsy across diverse communities. While epilepsy tends to be more prevalent among males, pediatric studies have found inconsistent results by gender. Cossu et al. [3] identified a higher prevalence among young girls (0–9 years) and older boys (10–19 years), whereas other researchers found higher prevalence in

younger boys and older girls [7,27] (Table 2). We identified higher prevalence among males than females for all age groups except 5 to 9 years, though this was not statistically significant. An association between lower SES and higher epilepsy prevalence has been consistently shown in previous studies [4,25,29,30]. We chose the nine-county study area because it was rural, had a low SES when compared with other areas of the state, and had a predominantly Caucasian population. Predominantly Caucasian counties were selected by design to reduce the potential of confounding by race/ethnicity in epilepsy prevalence. None of these factors were associated with a greater epilepsy prevalence in this population. 4.1. Limitations and strengths There were several limitations to this study. We were unable to obtain demographic and clinical data from some medical records, and the comprehensiveness of the medical records differed across sites. Nonetheless, most of the children identified were classifiable into broad categories for syndrome under the 1989 guidelines of the ILAE Commission on Classification and Terminology [22]. We were able to identify children with epilepsy in the community predominantly through medical record review, although few interviews were conducted. As in all studies of prevalent epilepsy, some children might have been missed if they had no medical coverage, if they were still taking medication and had no seizures, or if they had seizures that were not severe enough to require medical attention [31]. The statistically significant difference in prevalence between two of the study counties might reflect missing cases. In the county with the lowest reported prevalence, Cherokee, no community medical facilities were present. The county with a significantly higher prevalence, Labette, had more participating facilities than any other county. Nonparticipation of some of the medical centers in the study area might also have resulted in an undercount of cases. A strength of the study included development of community support and partnerships: special education cooperatives, community mental health centers, state and local health departments, and other community resources for epilepsy (local neurologists, Epilepsy Foundation of Kansas and Western Missouri, and Epilepsy Resource Connection). However, it is important to consider the difficulty in acquiring cooperation from families, leading to limited data on many variables. In addition to incomplete data within many medical records, there were process barriers in these rural communities even when significant networks and supports were utilized. This is a fundamental methodical issue in conducting the needed research addressed in this study.

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Table 2 Recent studies of epilepsy prevalence in pediatric populations. First author

Publication date

Study location

Population

Number of cases

Age range

Prevalence (per 1000)

Gender

Type of study

Ablah

2014

Kansas, US

14,770a

114a

2012

Sardinia, Italy

60,525a

394a

Retrospective chart review, patient interviews Retrospective chart review

El-Tallawy

2013

New Valley Governorate, Egypt

24,102a

225a

Hawley

Under review

Kansas, US

42,897

216

Josipovic-Jelic Khedr

2011 2013

Sibenik-Knin, Croatia Assiut Governorate, Egypt

c

1829a

181a 49a

Larsson Lomidze

2006 2012

Uppsala county, Sweden Tbilisi, Georgia

60,192 2826a

205 29a

Moualek

2012

Algeria

2820a

35a

6.6 8.8 3.8 7.7 8.4 6.1 8.0 8.8 10.1 9.2 3.5 5.6 6.2 4.9 6.9 65.4d 42.6d 26.2d 10.3d 3.4 3.2 8.1 14.4 9.7 16.9 6.3 7.4 10.3 2.1 4.7 6.2 18.7 11.3 7.2 8.8 13.2 19.8 12.1 9.7 13.2 0.9e 3.3e 6.5e 7.2e 8.2e 5.4e 5.5e 7.1e 3.8 6.3 10.3 14.0 13.9 7.2 5.9 6.4 5.1 7.5 15.3 3.3 4.4 11.5 4.5

M b Fb

Cossu

0–9 10–19 0–4 5–9 10–14 15–19 0–1 2–5 6–11 12–17 0–4 5–9 10–14 15–18 0–19 0–4 5–9 10–14 15–19 0–16 0–5 6–10 11–20 0–9 10–19 0–5 6–12 13–18 0–5 6–12 13–18 0–5 6–12 13–18 0–5 6–12 13–18 0–5 6–12 13–18 0 1–4 5–9 10–12 0–4 5–9 10–14 15–19 0–17 0–5 6–11 12–17 0–4 5–9 10–14 15–19 0–4 5–9 10–14 15–17 0–9 10–19 0–18

Ngugi

2013

a

c

Kilifi, Kenya

128,344

Agincourt, South Africa

36,916a

c

Iganga-Mayuge, Uganda

37,138a

c

Ifakara, Tanzania

48,066a

c

Kintampo, Ghana

57,564a

c

Oka

2006

Okayama Prefecture, Japan

250,997

1337d

Parko

2009

Navajo Reservation, United States

37,676e

c

Pi Russ

2012 2012

Yueyang, China United States

c

91,605

20 977

Schiariti

2009

British Columbia

1,013,816

8125

Topbas

2012

Trabzon, Turkey

4288

37

Winkler

2009

Northern Tanzania

4316a

32a

Wong

2004

Hong Kong

245,340

1103

a b c d e

Study surveyed all ages; only pediatric cases included in table. Only aggregate data available; not specific to pediatric population. Data not available. Lifetime prevalence. Modified data resulting from redefinition of study parameters.

MbF MbF MNF MNF M b Fb

Door to door survey

MNF

Retrospective chart review, patient interviews

M N Fb M N Fb

Retrospective chart review Random community sampling

MbF MNF MNF MbF MbF

Retrospective chart review Door to door survey

MNF

Door to door survey

Primary care office questionnaire

MNF

MNF

MbF

MNF

MNF MNF MNF MNF M N Fa

Retrospective chart review

M N Fb MNF

Door to door survey Random-digit telephone survey

c

Retrospective chart review

MbF

Random selection based on chart review; face to face parental interviews

MNF MbF MNF

Random door to door sampling

Retrospective chart review

Retrospective chart review

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4.2. Conclusions Our findings indicate that the prevalence of active epilepsy in children living in poor rural communities is similar to that found in urban settings. Further study of epilepsy prevalence in low-income populations in the United States is warranted, which may permit deeper investigation of the contributions of race and SES to epilepsy prevalence in these settings. Acknowledgments The study team would like to acknowledge the support and funding provided by the Association of University Centers on Disabilities (AUCD RTOI 2008-01-01) and the Centers for Disease Control and Prevention (CDC) National Center on Birth Defects and Developmental Disabilities (NCBDDD) for this cooperative agreement grant. Author contributions All authors were involved with coordination and facilitation of case identification. Hawley and Lindeman wrote the first draft of the article and edited later versions. Hauser and Hesdorffer developed the study questions and general methodology. St. Romain completed several revisions of the literature review and editing. Ablah and Liu managed and analyzed the data. Rogers and Ablah were responsible for data tracking. Warren and Schmitz managed data collection. Pellock, Paschal, Hauser, Rogers, and Lindeman completed all case reviews. Pellock and Thurman contributed to conclusions and implications of study. Conflicting interests No conflicting interests are declared. References [1] National Research Council. Epilepsy across the spectrum: promoting health and understanding. Washington, DC: National Academies Press; 2012. [2] Cowan LD, Leviton A, Bodensteiner JB, Doherty L. Problems in estimating the prevalence of epilepsy in children: the yield from different sources of information. Paediatr Perinat Epidemiol 1989;3:386–401. [3] Cossu P, Deriu MG, Casetta I, Leoni S, Daltveit A-K, Riise T, et al. Epilepsy in Sardinia, insular Italy: a population-based prevalence study. Neuroepidemiology 2012;39: 19–26. [4] Josipovic-Jelic Z, Sonicki Z, Soljan I, Demarin V. Prevalence and socioeconomic aspects of epilepsy in the Croatian county of Sibenik-Knin: community-based survey. Epilepsy Behav 2011;20:686–90. [5] Oka E, Ohtsuka Y, Yoshinaga H, Murakami N, Kobayashi K, Ogino T. Prevalence of childhood epilepsy and distribution of epileptic syndromes: a population-based survey in Okayama, Japan. Epilepsia 2006;47:626–30. [6] El-Tallawy HN, Farghaly WM, Shehata GA, Abdel-Hakeem NM, Rageh TA, Abo-Elftoh NA, et al. Epidemiology of epilepsy in New Valley Governorate, Al Kharga District, Egypt. Epilepsy Res 2013;104:167–74.

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