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    Ghana, Kenya, South Africa, Tanzania, Uganda - Epidemiology and Treatment of Epilepsy in sub-Saharan Africa

    Epidemiology
    Reference ID INDEPTH.GH002.SEEDS.v1
    Year 2007 - 2008
    Country Ghana, Kenya, South Africa, Tanzania, Uganda
    Producer(s) Prof C R Newton - Dept of Psychiatry, University of Oxford, UK and KEMRI/Wellcome Trust Research Programme, Centre for Geographic Medicine Research–Coast, Kilifi , Kenya.
    Anthony K Ngugi - Dept
    Sponsor(s) Wellcome Trust Senior Fellowship in Clinical Tropical Medicine - WT - Funder
    Wellcome Trust Research Programme - WT - Funder
    University of the Witwatersrand - Wits - Partial support at Agincourt
    South African Medical Research Council - MRC
    Collection(s)
    Epidemiology and Treatment of Epilepsy in sub-Saharan Africa
    Created on
    Aug 29, 2013
    Last modified
    Dec 29, 2013
    Page views
    291629
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    Overview
    Identification
    Countries
    Ghana, Kenya, South Africa, Tanzania, Uganda
    Title
    Epidemiology and Treatment of Epilepsy in sub-Saharan Africa

    Study Type
    Cross-sectional
    Series Information
    The study was conducted in five HDSS which are part of the International Network for the Demographic Evaluation of Populations and Their Health in Low- and Middle-Income Countries (INDEPTH). The centres were Agincourt, South Africa (August 2008-February 2009); Ifakara, Tanzania (May 2009-December 2009); Iganga/Mayuge, Uganda (February 2009-October 2009); Kilifi, Kenya (conducted between December 2007-July 2008); Kintampo, Ghana (August 2010-April 2011).

    ID Number
    INDEPTH.GH002.SEEDS.v1
    Version
    Version Description
    1.0

    Production Date
    2013-02-11
    Overview
    Abstract
    Background

    The prevalence of epilepsy in sub-Saharan Africa appear to be higher than in other parts of the world, but estimates vary substantially for unknown reasons. We assessed the prevalence and risk factors of active convulsive epilepsy across five centres in this region.

    Methods

    We conducted large population-based cross-sectional and case-control studies in five Health and Demographic Surveillance System (HDSS) centres: Kilifi , Kenya (Dec 3, 2007–July 31, 2008); Agincourt, South Africa (Aug 4, 2008–Feb 27, 2009); Iganga-Mayuge, Uganda (Feb 2, 2009–Oct 30, 2009); Ifakara, Tanzania (May 4, 2009–Dec 31, 2009); and Kintampo, Ghana (Aug 2, 2010–April 29, 2011). We used a three-stage screening process to identify people with active convulsive epilepsy. Prevalence was estimated as the ratio of confirmed cases to the population screened and was adjusted for sensitivity and attrition between stages. For each case, an age-matched control individual was randomly selected from the relevant centre’s census database. Fieldworkers masked to the status of the person they were interviewing administered questionnaires to individuals with active convulsive epilepsy and control individuals to assess sociodemographic variables and historical risk factors (perinatal events, head injuries, and diet). Blood samples were taken from a randomly selected subgroup of 300 participants with epilepsy and 300 control individuals from each centre and were screened for antibodies to Toxocara canis, Toxoplasma gondii, Onchocerca volvulus, Plasmodium falciparum, Taenia solium, and HIV. 586 607 residents in the study areas were screened in stage one, of whom 1711 were diagnosed as having active convulsive epilepsy. The 1711 individuals with active convulsive epilepsy and 2032 control individuals were interviewed with questionnaires, to determine demographic, socio-economic and medical risk factors.

    Kind of Data
    Sample survey data

    Units of Analysis
    Individual

    Scope
    Notes
    We used a three-stage screening process to identify cases of active convulsive epilepsy. In the first stage, two screening questions were asked during a routine, door-to-door census organised by each HDSS centre. Heads of households were interviewed about whether any residents had had convulsions. In the second stage, trained lay fieldworkers administered a detailed questionnaire to individuals identified as having a history of convulsions in stage one. Individuals whose responses to the questionnaire suggested they might have epilepsy were examined during stage three by clinicians who made a final diagnosis.

    To enable comparison between our three-stage method and the two-stage surveys used in other population-based studies in Africa, we selected a random population sample from each centre’s census database with the RAND() command in MySQL (Oracle, Redwood Shores, CA, USA). The questionnaire used in the second stage of the study was administered to this randomly sampled population; individuals identified as possibly having epilepsy after the questionnaire results were assessed clinically in stage three.

    For each epilepsy case, an age-matched control individual was randomly selected from the relevant centre’s census database with the RAND() command. The control individuals were frequency matched by age groups: 0–5 years, 6–12 years, 13–18 years, 19–28 years, 29–49 years, and 50 years or older. In the case-control study, two or three control individuals were selected to compensate for non-response and ensure balance in the number of cases and control individuals at each centre. All control individuals were assessed by a clinician to confirm that they did not have epilepsy. Fieldworkers then administered questionnaires based on those used in previous studies to individuals identifi ed as having epilepsy and control individuals. Fieldworkers, who were masked to the status (case or control) of the person they were interviewing, gathered data on sociodemographic variables and historical risk factors (perinatal events, head injuries, and diet). Clinical history was also obtained by masked, trained clinicians (the same clinicians who made initial diagnoses) and they made a diagnosis of active convulsive epilepsy. When the study participants were younger than 18 years or had cognitive impairment, the mother or caregiver was interviewed. The questionnaires administered to mothers or caregivers included questions about antenatal (eg, severe abdominal pain, vaginal bleeding, or infection during pregnancy) and perinatal events (difficulties breathing, feeding, or crying after birth, as recalled by the mother or caregiver). Questions about consumption of alcohol and use of recreational drugs were administered to adult participants only.

    Blood samples were taken from a subgroup of 300 participants with epilepsy and 300 control individuals from each centre who were randomly selected with the RAND() command. This sample size would allow detection of an odds ratio (OR) greater than 2.4, with 80% power and the assumption that 5% of control individuals had epilepsy. The samples were screened for antibodies to Toxocara canis, Toxoplasma gondii, Onchocerca volvulus, Plasmodium falciparum, Taenia solium, and HIV. Exposure was established by detection of IgG antibodies to the parasitic antigens. IgG antibodies against T canis were detected with a commercial kit (Toxocara IgG-ELISA, Cypress Diagnostics, Belgium; sensitivity 97%; specificity 78%). Anti-Toxocara IgG4 antibodies with an optical density greater than the cutoff (mean plus three standard deviations of 30 IgG-negative serum samples) were interpreted as positive. IgG antibodies against T gondii were detected with a commercial kit (Toxoplasma IgGELISA, Genesis Diagnostics, Ely, UK; 100% agreement with test samples) and were judged positive when optical density was greater than that of the positive 8 IU/mL sample in the kit. Exposure to O volvulus was established with a modification of an ELISA that detects IgG4 to the recombinant antigen Ov-16GST (sensitivity 90%; specificity 98%). A sample with an optical density greater than the cutoff (mean plus three standard deviations of 30 serum samples from the Agincourt HDSS, where onchocerciasis is not prevalent) were interpreted as positive. Exposure to malaria was established with an in-house ELISA30 that tests for IgG antibodies to crude schizont extract from a P falciparum A4 clone line, which is derived from a laboratory strain. Exposure to the larval stage (cysticercosis) and adult stage (taeniasis) of the parasite T solium was established with a Western blot (sensitivity 97%; specifi city 99%; detection of cases with two or more viable cysts in the brain) and antibodies to taeniasis (RES33 antigen; sensitivity 99%; specifi city 93%). IgG antibodies to HIV

    type 1 or type 2, or both, were detected with the fourth generation screening test Vironostika HIV Uniform II Ag/Ab (BioMerieux, France) according to the manufacturer’s instructions.

    Topics
    TopicVocabularyURI
    Public Health [N01.400.550] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Rural Population [N01.600.725] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Mass Screening [N06.850.780.500] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Epilepsy, Generalized [C10.228.140.490.375] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Cross-Sectional Studies [N05.715.360.775.175.275] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Case-Control Studies [N05.715.360.775.175.200] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Age Distribution [N01.224.033] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Censuses [N01.224.175] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Ethnic Groups [N01.224.317] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Career Mobility [N01.824.175] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Employment, Supported [N01.824.245.350] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Educational Status [N01.824.196] MeSHhttp://www.ncbi.nlm.nih.gov/mesh
    Coverage
    Geographic Coverage
    Demographic Surveillance Areas of participating HDSS's

    Universe (1)
    Stage One : All individuals resident in the demographic surveillance area

    Universe (2)
    Stage Two: All individuals identified in Stage One as having a history of convulsions

    Universe (3)
    Stage Three: Individuals whose responses in Stage Two suggested they might have epilepsy

    Universe (4)
    Randomly selected sample of resident individuals in each participating HDSS

    Universe (5)
    Individuals with a diagnosis of active convulsive epilepsy following Stage Three

    Producers and Sponsors
    Primary Investigator(s)
    NameAffiliation
    Prof C R Newton Dept of Psychiatry, University of Oxford, UK and KEMRI/Wellcome Trust Research Programme, Centre for Geographic Medicine Research–Coast, Kilifi , Kenya.
    Anthony K Ngugi Dept of Psychiatry, University of Oxford, UK and KEMRI/Wellcome Trust Research Programme, Centre for Geographic Medicine Research–Coast, Kilifi , Kenya.
    Christian Bottomley London School of Hygiene and Tropical Medicine, London, UK
    Immo Kleinschmidt London School of Hygiene and Tropical Medicine, London, UK
    Ryan G Wagner MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt),School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
    Angelina Kakooza-Mwesige Iganga-Mayuge Surveillance System, Iganga, Uganda
    Kenneth Ae-Ngibise Kintampo Health Research Centre, Kintampo, Ghana
    Seth Owusu-Agyei Kintampo Health Research Centre, Kintampo, Ghana
    Honorati Masanja Ifakara Health Institute, Ifakara, Tanzania
    Gathoni Kamuyu KEMRI/Wellcome Trust Research Programme, Centre for Geographic Medicine Research–Coast, Kilifi , Kenya
    Rachael Odhiambo KEMRI/Wellcome Trust Research Programme, Centre for Geographic Medicine Research–Coast, Kilifi , Kenya
    Eddie Chengo KEMRI/Wellcome Trust Research Programme, Centre for Geographic Medicine Research–Coast, Kilifi , Kenya
    Josemir W Sander University College London, London, UK; Stichting Epilepsie Instellingen Nederland, Heemstede,Netherlands
    Other Producer(s)
    NameAffiliationRole
    Kobus Herbst INDEPTH Networ, AccraData harmonisation and documentation
    Funding
    NameAbbreviationRole
    Wellcome Trust Senior Fellowship in Clinical Tropical Medicine WTFunder
    Wellcome Trust Research Programme WTFunder
    University of the Witwatersrand WitsPartial support at Agincourt
    South African Medical Research Council MRCPartial support at Agincourt
    National Institutes of Health, USA NIHProvided OV-16GST
    Centers for Disease Control and Prevention CDCProvided Nitrocellulose strips
    Other Acknowledgements
    NameAffiliationRole
    Afolabi Sulaimon MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt),School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa Data manager
    Robert Adda Kintampo Health Research Centre, Kintampo, GhanaData manager
    Dorean Nakamya Iganga-Mayuge Surveillance System, Iganga, UgandaData manager
    Jackson Francis Malugala Ifakara Health Institute, Ifakara, TanzaniaData manager
    Rachael Odhiambo KEMRI/Wellcome Trust Research Programme, Centre for Geographic Medicine Research–Coast, Kilifi , KenyaData manager
    Metadata Production
    Metadata Produced By
    NameAbbreviationAffiliationRole
    Rachael OdhiamboRodhiamboINDEPTHDocumentation of the study
    Kobus HerbstkherbstINDEPTHReview of metadata & variable documentation
    Date of Metadata Production
    2013-03-27
    DDI Document Version
    Version 1.6

    DDI Document ID
    DDI.INDEPTH.GH002.SEEDS.v1.3

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