AFR_2007-2008_INDEPTH_v01_M
Epidemiology and Treatment of Epilepsy in Sub-Saharan Countries 2007-2008
Name | Country code |
---|---|
Africa | AFR |
Cross-sectional
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).
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.
Sample survey data
Individual
Version 01
2013-02-11
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.
Topic | Vocabulary | URI |
---|---|---|
Public Health [N01.400.550] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Rural Population [N01.600.725] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Mass Screening [N06.850.780.500] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Epilepsy, Generalized [C10.228.140.490.375] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Cross-Sectional Studies [N05.715.360.775.175.275] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Case-Control Studies [N05.715.360.775.175.200] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Age Distribution [N01.224.033] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Censuses [N01.224.175] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Ethnic Groups [N01.224.317] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Career Mobility [N01.824.175] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Employment, Supported [N01.824.245.350] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Educational Status [N01.824.196] | MeSH | http://www.ncbi.nlm.nih.gov/mesh |
Demographic Surveillance Areas of participating HDSS's
The following sub-saharan countries were covered: Ghana, Kenya, South Africa, Tanzania, and Uganda.
Stage One : All individuals resident in the demographic surveillance area
Stage Two: All individuals identified in Stage One as having a history of convulsions
Stage Three: Individuals whose responses in Stage Two suggested they might have epilepsy
Randomly selected sample of resident individuals in each participating HDSS
Individuals with a diagnosis of active convulsive epilepsy following Stage Three
Name | Affiliation |
---|---|
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 |
Name | Affiliation | Role |
---|---|---|
Kobus Herbst | INDEPTH Networ, Accra | Data harmonisation and documentation |
Name | Role |
---|---|
Wellcome Trust Senior Fellowship in Clinical Tropical Medicine | Funder |
Wellcome Trust Research Programme | Funder |
University of the Witwatersrand | Partial support at Agincourt |
South African Medical Research Council | Partial support at Agincourt |
National Institutes of Health, USA | Provided OV-16GST |
Centers for Disease Control and Prevention | Provided Nitrocellulose strips |
Name | Affiliation | Role |
---|---|---|
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, Ghana | Data manager |
Dorean Nakamya | Iganga-Mayuge Surveillance System, Iganga, Uganda | Data manager |
Jackson Francis Malugala | Ifakara Health Institute, Ifakara, Tanzania | Data manager |
Rachael Odhiambo | KEMRI/Wellcome Trust Research Programme, Centre for Geographic Medicine Research–Coast, Kilifi , Kenya | Data manager |
Sample size calculations. With an anticipated prevalence of at least 4/1,00016,20,159,160, in a DSS of at least 60,000 subjects, the 95% limits will be 3.5-4.5/1,000 at each site, or 3.8-4.2/1000 for the sites combined. For age-specific prevalences, confidence limits will be 2.3-5.7/1,000 in the smallest age stratum (>50 years) in the smallest site.
A random population sample from each centre's census database with the RAND() command in MySQL (Oracle, Redwood Shores, CA, USA).
For each 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.
None reported
Stage One:
Kilifi , Kenya 99.3%
Agincourt, South Africa 99.6%
Iganga-Mayuge, Uganda 92.8%
Ifakara, Tazania 89.3%
Kintampo, Ghana 87.7%
Overall 94.5%
Stage Two
Kilifi , Kenya 94.8%
Agincourt, South Africa 94.3%
Iganga-Mayuge, Uganda 64.0%
Ifakara, Tazania 95.1%
Kintampo, Ghana 91.1%
Overall 84.1%
Stage Three
Kilifi , Kenya 84.4%
Agincourt, South Africa 92.7%
Iganga-Mayuge, Uganda 64.2%
Ifakara, Tazania 91.1%
Kintampo, Ghana 77.7%
Overall 82.0%
Socio-demographic - sociodemographic information, past medical history and social history.
Clinical history - clinical history information such as epilepsy record, information on epileptic drug, description of seizures and the summary.
Clinical examination - clinical examination information.
Examination summary - a summary of the clinical examination and history defining the seizures and the syndromes.
Seizure classification - classification of the seizures as described in the clinical history.
EEG - electroencephalogram read information.
The questionnaires were developed in English and were translated to the local languages as per the sites where they were administered.
Start | End | Cycle |
---|---|---|
2007-12-03 | 2008-07-31 | Kilifi, Kenya |
2008-08-04 | 2009-02-27 | Agincourt, South Africa |
2009-05-04 | 2009-10-30 | Ifakara, Tanzania |
2009-12-31 | 2009-12-31 | Ifakara, Tanzania |
2010-08-02 | 2011-04-29 | Kintampo, Ghana |
The survey at each site will take less than 6 months since it is anticipated that each fieldworker will visit 6-10 households per day (median size of household is 10 individuals) and the required number of fieldworkers will be employed to finish the survey within 5 months. About 6-8 subjects will be assessed each day by the clinician per day. Follow-up period for the mortality is at least 3 years. Time period is between 2008 - 2013.
Single Cross-sectional study
Name |
---|
Agincourt |
Kilifi |
Ifakara |
Iganga |
Kintampo |
Interviewing was conducted by a team of 6 interviewers including a supervisor.The field supervisor collected and checked that all the forms were filled in appropriately at the end of each day. At the end of a field day, the study co-ordinator received the verified forms from the field supervisor.
A quality assurance manual containing introduction ot the surveys, standard operating procedures for pre-analytic processes and communication and consent materials was used.
The interviewers were trained on how to collect the information before the beginning of the study.
The were various questionnaires used and the duration varied according to the size.
There were six field worker collecting the data for stage two screening and there were five assessores who were collecting stage three data.
Interviews were conducted in the local langages in the different sites i.e in Kilifi Giriama languge was used.
Fieldworkers, were masked to the status (case or control) of the person they were interviewing
Data editing took place
INDEPTH Data Repository
INDEPTH Data Repository
http://www.indepth-ishare.org/index.php/catalog/48
Cose: None
Name | Affiliation | |
---|---|---|
Charles Newton | Dept of Psychiatry, University of Oxford, UK and KEMRI/Wellcome Trust Research Programme, Centre for Geographic Medicine Research–Coast, Kilifi , Kenya. | CNewton@kemri-wellcome.org |
Is signing of a confidentiality declaration required? | Confidentiality declaration text |
---|---|
yes | Anonymised dataset |
This data is made available for restricted licensed access under the following conditions:
Data and other material provided by INDEPTH SEEDS Group will not be redistributed or sold to other individuals, institutions or organisations without INDEPTH's written agreement.
In the case of this multi-centre datasets, data originating from a single contributing member centre may not be analysed or reported on in isolation without the express permission of the member centre concerned.
No attempt will be made to re-identify respondents, and there will be no use of the identity of any person or establishment discovered inadvertently. Any such discovery will be reported immediately to INDEPTH.
No attempt will be made to produce links between datasets provided by INDEPTH or between INDEPTH data and other datasets that could identify individuals.
Any books, articles, conference papers, theses, dissertations, reports or other publications employing data obtained from INDEPTH will cite the source, in line with the citation requirement provided with the dataset.
An electronic copy of all publications based on the requested data will be sent to INDEPTH.
The original collector of the data, INDEPTH, and the relevant funding agencies bear no responsibility for the data's use or interpretation or inferences based upon it.
The researcher's organisation must be identified, as must the principal and other researchers involved in using the data. The principal researcher must sign the license on behalf of the organization. If the principal researcher is not authorized to sign on behalf of the receiving organization, a suitable representative must be identified.
The intended use of the data, including a list of expected outputs and the organisation's data dissemination policy must be provided.
The INDEPTH SEEDS Group. Epidemiology and Treatment of Epilepsy in sub-Saharan Africa Data Set. Feb 2013. Provided by the INDEPTH Network Data Repository. www.indepth-ishare.org http://www.indepth-ishare.org. doi:10.7796/INDEPTH.GH002.SEEDS.v1
The user of the data acknowledges that the original collector of the data (the SEEDS Group), INDEPTH, and the relevant funding agencies bear no responsibility for the data's use or interpretation or inferences based upon it.
Name | Affiliation | URL | |
---|---|---|---|
Rachael Odhiambo | KEMRI/Wellcome Trust Research Programme, Centre for Geographic Medicine Research–Coast, Kilifi , Kenya | ROdhiambo@kemri-wellcome.org | http://kemri-wellcome.org/ |
Charles Newton | Dept of Psychiatry, University of Oxford, UK and KEMRI/Wellcome Trust Research Programme, Centre for Geographic Medicine Research–Coast, Kilifi , Kenya. | CNewton@kemri-wellcome.org | http://kemri-wellcome.org/ |
DDI_AFR_2007-2008_INDEPTH_v01_M
Name | Affiliation | Role |
---|---|---|
Rachael Odhiambo | INDEPTH | Documentation of the study |
Kobus Herbst | INDEPTH | Review of metadata & variable documentation |
2013-03-27
Edited version, the original DDI (DDI.INDEPTH.GH002.SEEDS.v1.3) was downloaded from INDEPTH Data Repository (http://www.indepth-ishare.org/index.php/catalog/central) on October 2014. The following DDI elements have been modified: DDI Document ID and survey ID.
Version 1.1 Additions and changes by Kobus Herbst during metadata review
Version 1.2 Further changes by Rachael Odhiambo
Version 1.3 Changes by Kobus Herbst during metadata review
version 1.4 Changes by Rachael Odhiambo, adding variable level documentation
Version 1.5 Changes by Kobus Herbst during metadata review
Version 1.6 Changes by Kobus Herbst to include variable categories and final datasets
Version 1.7 Changes by Rachael Odhiambo, adding variable level documentation
Version 1.8 Changes by Kobus Herbst to include updated clinical exam dataset