- Research article
- Open Access
- Open Peer Review
Prevalence and risk factors of neurological impairment among children aged 6–9 years: from population based cross sectional study in western Kenya
© Kawakatsu et al.; licensee BioMed Central Ltd. 2012
- Received: 17 May 2012
- Accepted: 28 November 2012
- Published: 3 December 2012
The burden of disability is more severe among children in low income countries. Moreover, the number of children with disabilities (CWDs) in sub-Saharan Africa is predicted to increase with reduction in child mortality. Although the issue on CWDs is important in sub-Saharan Africa, there are few researches on risk factors of disabilities. The purpose of this study was to evaluate the risk factors of neurological impairment (NI) among children in western Kenya.
The present study was conducted in Mbita district (which has high HIV infectious prevalence), Kenya from April 2009 to December 2010. The study consisted of two phases. In phase 1, the Ten Question Questionnaire (TQQ) was administered to all 6362 caregivers of children aged 6–9 years. In phase two, all 413 children with TQQ positive and a similar number of controls (n=420) which were randomly selected from children with TQQ negative were examined for physical and cognitive status. In addition, a structured questionnaire was also conducted to their caregivers.
The prevalence was estimated to be 29/1000. Among the types of impairments, cognitive impairment was the most common (24/1000), followed by physical impairment (5/1000). In multivariate analysis, having more than five children [adjusted odds ratio (AOR): 2.85; 95%IC: 1.25 – 6.49; p=0.013], maternal age older than 35 years old [AOR: 2.31; 95%IC: 1.05 – 5.07; p=0.036] were significant factors associated with NI. In addition, monthly income under 3000 ksh [AOR: 2.79; 95%IC: 1.28 – 6.08; p=0.010] and no maternal tetanus shot during antenatal care [AOR: 5.17; 95%IC: 1.56 – 17.14; p=0.007] were also significantly related with having moderate/severe neurological impairment.
It was indicated that increasing coverage of antenatal care including maternal tetanus shot and education of how to take care of neonatal children to prevent neurological impairment are important.
- Risk factor
The average global prevalence of moderate and severe disability is estimated to be 5% in children aged 0–14 years. Disability among children in low-income countries is more common than high-income countries . The number of children with disabilities (CWDs) in Sub-Sahara Africa is estimated to increase with the reduction in child mortality . Furthermore, neurological impairment such as epilepsy, hearing impairment, vision impairment, physical impairment and cognitive impairments is one of the important causes of disability and death. It estimated to account for >28% of years lived with disability and to be responsible for at least one in every nine deaths .
Main risk factors of severe and moderate disabilities in low-income countries were generally considered genetic factors [4, 5], nutritional deficiencies [6–9], infections , prenatal and neonatal factors [11, 12] and socio-economic factors [13, 14]. However, most of the studies focused on one impairment/disability [15–18] and some researches didn’t conduct physical assessment to diagnose child’s disability [9, 19]. In addition, there are few researches on causes and risk factors of NI in sub-Saharan Africa, especially high prevalence area of malaria and HIV infection.
This research aimed to assess prevalence of NI and evaluate risk factors of NI among children aged 6–9 years by conducting structured questionnaire and physical assessments at the area of high malaria and HIV prevalence in Kenya.
This study was conducted in Gembe West, Gembe East, Rusinga West and Rusinga East, Mbita district, Nyanza province, Kenya, located on the lakeside of Lake Victoria. This is one of the poorest areas in Kenya  and the residents are primarily, subsistence farmers or fishermen. Moreover, this area has one of the highest prevalence rates of malaria and HIV infection . Health and Demographic Surveillance System (HDSS) project in this area is being conducted by Kenya Medical Research Institute (KEMRI) - Nagasaki University Institute of Tropical Medicine (NUITM) project.
The research population consisted of the all 6263 children, aged 6–9 years, and their caregivers in research site. Their main tribe is the Luo tribe and their main languages are Luo language, followed by Swahili and English. The age group of 6–9 years was selected because of difficulties in identifying impairments in children younger than 6 years old and the lack of cross-cultural assessment tools for cognitive impairment in young children.
In phase one, we targeted all 6263 caregivers of children aged 6–9 years in the research area. The sample size for phase two was calculated according to L.Naing . With estimated prevalence of CWDs in Kenya (10%), confidence level of 95% and with a relative precision of 2.5% points on each side, a sample of 813 children was needed.
Study design and data collection
Ten Questions Questionnaire (TQQ)
The Ten Questions Questionnaire (TQQ) developed by WHO is a convenient questionnaire focusing on the child’s functional abilities and is used to detect NI among children aged 2–9 years in community settings . TQQ has been used widely to screen for childhood impairment in low- and middle-income counties [9, 12, 14]. The validity of the TQQ has been reported in some countries such as Bangladesh , Jamaica , Pakistan , India  and Kenya . We conducted one day training to research assistants to improve their understanding on this question. Although most of the participants could understand English in this area, the questionnaire was translated into Luo language in case that they could not understand English.
Physical, neurological and cognitive assessments
The word of NI mentioned in this research belongs to body functions & structures part in the International Classification of Functioning, Disability, and Health (ICF) and contained cognitive impairment, physical impairment, epilepsy, hearing impairment and visual impairment. The assessments to diagnose NI included physical examination  including measurement of height and weight to assess motor impairment and a vision test (Landolt Chart) . Hearing test by three screening tests (Behavioral Observation Audiometry (BOA): bell-tone, paper crash test, small voice) was also performed. Almost quarter subjects in phase 2 were re-checked by using an audiometer  (KS8: PC Werth Ltd) . In addition, the diagnosis of epilepsy was based on the history gathered from their caregivers about the child’s epilepsy-like symptoms.
Cross-cultural cognitive assessment was also used . This cognitive assessment included seven batteries which tested verbal and non-verbal skills, namely, “Digit span (phonological loop component of working memory)”, “Corsi Block ( operational skill of the visuospatial sketch-pad component of working memory)”, “Verbal fluency (retrieval function from long term memory)”, “Silly sentence (general intelligence and speed of access to semantic memory)”,”Visual search (speed of visual information processing)”, “Free recall (Long term memory) ”, and ”Vocabulary learning (prose learning) ”. These seven cognitive assessments were performed for the target children. These seven cognitive assessments were analyzed by using factor analysis and summarized as factor 1 and 2. Factor one significantly correlated with Digit span, Visual search, Silly sentence, and Free recall, while factor two significantly correlated with Corsi block, Verbal fluency. Finally, all suspected cases by using above assessments were re-evaluated by a physical therapist.
Definitions of moderate and severe impairment
Under 1% of factor 1 OR factor 2 in 296 children with negative response of TQQ
Inability to successfully complete even one cognitive test item
Difficulty in grip, dressing and sitting. Ability to move around with help.
Inability to walk and absence of functional use of hands
More than one non-febrile seizure per month
More than one non-febrile seizure per week.
At least one positive response in screening tests and 41–70 dB loss in the best ear.
More than 70 dB loss in the best ear
Visual acuity less than 6/18 or better than 6/60
Visual acuity worse than 6/60 meters or better than 3/60
Data storage and analysis
Data from all phases were double-entered after the verification of the data had been performed and stored using Epi info version 3.5. Statistical analysis was performed by using STATA version 10 (STATA Corporation, TX, USA).
Factor analysis was used to refine factor structure in seven cognitive assessments. Thirteen variables were considered as the potential risk factors. The potential risk factors were dichotomized and coded. Moreover, these potential risk factors in children aged 6–9 years were analyzed using univariate analysis and linear logistic models with 13 potential factors as covariates. Starting with a logistic model including all of these covariates, we selected the most appropriate model on the basis of Akaike’s information criterion (AIC) . Once the most appropriate model was selected, maximum likelihood estimation of the model parameters was conducted and then the odds ratio and the 95% confidence interval were calculated for each covariate in the model.
Informed consents from all guardians of target children were obtained after fully explanation of the study purpose and possible consequences. This study was approved by the Ethical Review Committee of Kenya Medical Research Institute (KEMRI SSC No. 1088) and National Council for Science and Technology in Kenya (Approval number: NCST/RR1/12/1/SS/150/5). In addition, the ethical committee of the Institute of Tropical Medicine, Nagasaki University (Approval number: 06060604) and the ethics committee of International Health Development, Graduate School of Nagasaki University (Approval number: 0012) were approved this study.
All 6263 children aged 6–9 years were screened in phase one. Among the screened children, 50.4% of them were male. Moreover, 26.8% were 6 years old (72–84 months), 22.6% were 7 years old (84–96 months), 25.9% were 8 years old (96–108 month), and 24.8% were 9 years old (108–120 months). Through the TQQ in phase one, 413 (6.5%) had at least one positive response on TQQ. The assessments to TQQ positive group in phase two could not be conducted for 81 children for different reasons (32 children left the study, 41 migrated, 5 under or over the age based on phase-2 results, 2 refused for consent, and 1 died). Finally, 332 (80%) out of 413 children with at least one positive response on TQQ were assessed during phase two. Similarly, 420 children out of 5850 who had a negative response on TQQ were selected using simple random-sampling. The assessments to TQQ negative group in phase two could not be conducted for 123 children for different reasons (26 children left the study, 77 migrated, 4 under or over the age based on phase-2 results, 7 refused for consent, 2 died and 7 double counted). Finally, 297 (70%) of the 420 children without a positive response were assessed.
Estimated prevalence* of moderate/severe impairment in Mbita district, [ per 1000 children (95%CI)]
Univariate analysis of risk factors for neurological impairment
CWDs (N=41) N (%)
TQQ negative(N=290) N (%)
< 32 years old
≥ 32 years old
0.827 - 3.075
Primary level or more
No formal education
0.644 – 2.401
Less than 2 times
More than 3 times
1.453 – 8.079
Tetanus shot in antenatal care
No tetanus shot
1.473 – 14.89
Sex of children
0.920 – 3.621
Over 3000 ksh per month
Under 3000 ksh per month
0.811 – 3.142
Number of household member
Less than 6 persons
More than 7 persons
0.662 – 2.457
Number of children under five
Less than 4 children
More than 5 children
0.913 – 3.400
at health facility
at own house / other
0.625 – 2.456
0.391 – 3.657
0.766 – 8.224
Less than 2 times
More than 3 times
0.130 – 2.997
1.187 – 6.003
Multivariate analysis of risk factors for Neurological Impairment
Adjusted Odds ratios
< 32 years old
≥ 32 years old
1.05 – 5.07
< 5 children
≥ 5 children
1.25 – 6.49
More than 3001ksh per month
Under 3000ksh per month
1.28 – 6.08
Tetanus shot in antenatal care
Non-tetanus shot in antenatal care
1.56 – 17.14
The prevalence of NI in the present study was 29/1000 and the most common impairment was cognitive (24/1000), followed by physical impairment (5/1000). Other comparable studies using TQQ were conducted in Kenya [12, 34], India , South Africa , Ghana , Saudi Arabia , Jamaica , Bangladesh  and Pakistan . In addition, TQQ cluster survey data was reported from 18 countries in the third round of UNICEF’s Multiple Indicator Cluster Survey 2005–2006 (MICS3) . Within studies which assessed the validity of TQQ, the prevalence of NI ranged from 16 to 61 per 1000 and cognitive impairment was the most or second most common impairment. In a study in Kilifi, the prevalence of NI was 61/1000 and the most common impairment was epilepsy with prevalence 41/1000, followed by cognitive (31/1000), hearing (14/1000), motor (5/1000) and vision (2/1000) impairments. The prevalence of cognitive impairment in the present study was analogous to that in the Kilifi study . However, the prevalence of cognitive impairment in other previous studies varies widely. The differences may be explained by the differences of definition of cognition and of age group, as children with severe disabilities will frequently die in infancy or early childhood. Moreover, the use of different assessment tools for cognitive impairment may considerably influence the prevalence of cognitive impairment. It is important to develop standardized assessment tools and definitions of cognitive impairment. However, the absence of standardized tools and lack of psychologists in our situation forced us to use a trained assessor and adapt the assessments for cognitive impairment that were culturally modified.
The prevalence of epilepsy and hearing impairment in this research was noticeably lower than in the research in Kilifi, Kenya . It is well established that central nervous system (CNS) infection such as malaria and tuberculosis can lead to epilepsy [39, 40] and the research site was one of the high malaria prevalence areas in Kenya. However, the prevalence of epilepsy was low in this study, compared with Kilifi study. It is estimated that the child who have epilepsy might be easy to die, because of stigma from community member, poor treatment and poor care from caregivers [41, 42]. The other possibility is that the method used to diagnose epilepsy. In this study, caregiver recall was used to assess epilepsy. However, in Kilifi study, a interview by clinical officer and electroencephalogram were used to diagnose epilepsy, so that more minor epilepsy might have been found. The prevalence of hearing impairment (0.8/1000) in the present study was considerably lower than that (14/1000) in the Kilifi study . Schooling rate to special school may influence the prevalence. There was one residential special school focusing on hearing impairment in Mbita district, and the phase two survey was conducted during schooling term. Some children with hearing impairment in Mbita district may have stayed in a special school.
The risk factors related to moderate/severe NI were low monthly income, having more children, maternal age and no maternal antenatal tetanus shot. Poverty is regarded as both a cause and consequence of disability . Poverty and disability reinforce each other, contributing to increased vulnerability and exclusion . It was clear that low monthly income was significantly related with impairment but it is not clear whether low monthly income is a cause or a result of disability based on the results in this study, because the research design was cross-sectional. Having more children was also related with moderate and severe neurological impairments. This finding was similar to the results reported in Saudi Arabia . With an increased number of children in poor countries, quality of care for a child is likely to be worse because of competing demands on mothers, while time and resource available to provide for each child become more limited , so that severe disabilities are more likely to develop due to lack of care . In addition, older maternal age was also related to have NI among children aged 6–9 years. As reported in other research, the older the woman, the greater the likelihood of miscarriage, stillborn or underweight baby, and likelihood of impairment also rises . No maternal tetanus shot was another risk factor for NI. A study in Kenya reported that tetanus increased the risk of NI among survivors . A mother who never received a tetanus shot was also less likely to go to antenatal care in this study. Moreover, antenatal care is related with child survival in terms of child fatal malnutrition  and neonatal death . Therefore, even when the child survives, poor neonatal care , neonatal encephalopathy  and neonatal insults  increase the risk of NI among survivors.
Although neonatal insults was a risk factors of neurological impairment in other research [12, 52], it was not significantly related in NI in this research. Further research on risk factors of NI would be better to ask more detail of neonatal insults.
There are four limitations in this research. There was a 1 year time-lag between phase one and phase two, because of ethical approval for physical assessment. Some children might have acquired impairments and died in the interim. However, since the age of first recognition of the impairment was mainly before 5 years old (86%) and the number of death was very few, the possibility of developing impairments or dying during the time-lag was supposed to be low. Moreover, around 100 households migrated during that time period and the households with CWDs might be likely to migrate. Hence, the years of staying in the community for households with CWDs were not different from Non-CWDs. Second, since our study design was cross-sectional, causal relationships between risk factors and impairments were not identified. A cohort study may be needed to illustrate the causal relationships. The third limitation was lack of a gold standard and standardized tools to assess cognitive impairment. The assessment for cognition in this research was an adapted and established cross-cultural assessment and definition of cognitive impairment were similar to the study in Kilifi. However, standardized tools and a gold standard for cognitive impairment are needed. Forth, since some CWDs might have stayed in special school during this research, there is a possibility that the prevalence of NI was underestimated.
Poverty, a greater number of children, older maternal age and no maternal tetanus shot were risk factors of NI in the present study. Although further research is necessary, antenatal care services including a tetanus shot and education on how to take care of neonatal children are important to prevent neurological impairment based on the findings in this study. In addition, more attention to prevent NI should be put the family with poverty and a greater number of children.
"The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in JECH editions and any other BMJPGL products to exploit all subsidiary rights, as set out in our licence (http://group.bmj.com/products/journals/instructions-for-authors/licence-forms/)."
The Nagasaki University, KEMRI and foundation of Gushinkai supported this study. We thank people who participated in this study, including the respondents and the staffs who assisted with data collection and data entry.
This work was supported by GUSHINKAI foundation grant number .
- WHO: The global burden of disease: 2004 update, Part3 Disease incidence,prevalence and disability. 2004, World Health Organization, [http://www.who.int/healthinfo/global_burden_disease/2004_report_update/en/index.html]Google Scholar
- Kaosar Afsana AA-s, Abbas B, et al: The state of health in Bangladesh 2006: challenges of achieving equity in health. 2007, Bangladesh: Health WatchGoogle Scholar
- Murray CJ, Lopez AD: Quantifying disability: data, methods and results. Bull World Health Organ. 1994, 72 (3): 481-494.PubMedPubMed CentralGoogle Scholar
- Obama MT, Dongmo L, Nkemayim C, Mbede J, Hagbe P: Stroke in children in Yaounde, Cameroon. Indian Pediatr. 1994, 31 (7): 791-795.PubMedGoogle Scholar
- Durkin MS, Khan NZ, Davidson LL, Huq S, Munir S, Rasul E, et al: Prenatal and postnatal risk factors for mental retardation among children in Bangladesh. Am J Epidemiol. 2000, 152 (11): 1024-1033. 10.1093/aje/152.11.1024.View ArticlePubMedGoogle Scholar
- Sommer A, West KP: The duration of the effect of vitamin A supplementation . Am J Public Health. 1997, 87 (3): 467-468. 10.2105/AJPH.87.3.467.View ArticlePubMedPubMed CentralGoogle Scholar
- Hetzel BS: Iodine deficiency disorders (IDD) and their eradication. Lancet. 1983, 2 (8359): 1126-1129.View ArticlePubMedGoogle Scholar
- Roncagliolo M, Garrido M, Walter T, Peirano P, Lozoff B: Evidence of altered central nervous system development in infants with iron deficiency anemia at 6 mo: Delayed maturation of auditory brainstem responses. Am J Clin Nutr. 1998, 68 (3): 683-690.PubMedGoogle Scholar
- Gottlieb MJM CA, Claudia C, Durkin MS: Child disability screening, nutrition, and early learning in 18 countries with low and middle incomes: data from the third round of UNICEF's Multiple Indicator Cluster Survey (2005–06). Lancet. 2009, 374: 1831-1839. 10.1016/S0140-6736(09)61871-7.View ArticleGoogle Scholar
- Durkin M: THE EPIDEMIOLOGY OF DEVELOPMENTAL DISABILITIES IN LOW-INCOME COUNTRIES. MENTAL RETARDATION AND DEVELOPMENTAL DISABILITIES. 2002, 8: 206-211. 10.1002/mrdd.10039.View ArticleGoogle Scholar
- Ellis M, Manandhar N, Shrestha PS, Shrestha L, Manandhar DS, Costello AMDL: Outcome at 1 year of neonatal encephalopathy in Kathmandu, Nepal. Dev Med Child Neurol. 1999, 41 (10): 689-695. 10.1017/S0012162299001413.View ArticlePubMedGoogle Scholar
- Mung'ala-Odera V, Meehan R, Njuguna P, Mturi N, Alcock KJ, Newton CRJC: Prevalence and risk factors of neurological disability and impairment in children living in rural Kenya. Int J Epidemiol. 2006, 35 (3): 683-688. 10.1093/ije/dyl023.View ArticlePubMedGoogle Scholar
- Durkin MS, Schupf N, Stein ZA: Epidemiology of mental retardation. Fetal and Neonatal Neurology and Neurosurgery. 2001, 799-818. ThirdGoogle Scholar
- Milaat WA, Ghabrah TM, Al-Bar HMS, Abalkhail BA, Kordy MN: Population-based survey of childhood disability in Eastern Jeddah using the ten questions tool. Disabil Rehabil. 2001, 23 (5): 199-203. 10.1080/09638280151080586.View ArticlePubMedGoogle Scholar
- Carter JA, Ross AJ, Neville BGR, Obiero E, Katana K, Mung'ala-Odera V, et al: Developmental impairments following severe falciparum malaria in children. Tropical Med Int Health. 2005, 10 (1): 3-10. 10.1111/j.1365-3156.2004.01345.x.View ArticleGoogle Scholar
- Omondi D, Ogol C, Otieno S, Macharia I: Parental awareness of hearing impairment in their school-going children and healthcare seeking behaviour in Kisumu district, Kenya. Int J Pediatr Otorhinolaryngol. 2007, 71 (3): 415-423. 10.1016/j.ijporl.2006.11.007.View ArticlePubMedGoogle Scholar
- V. Mung’ala-Odera SW, Meehan R, Otieno GO, Njuguna P, Mturi N, Edwards T, Neville BG, Newton CRJC: Prevalence, incidence and risk factors of epilepsy in older children in rural Kenya. Seizure. 2008, 17: 396-404. 10.1016/j.seizure.2007.11.028.View ArticleGoogle Scholar
- Kello AB, Gilbert C: Causes of severe visual impairment and blindness in children in schools for the blind in Ethiopia. Br J Ophthalmol. 2003, 87 (5): 526-530. 10.1136/bjo.87.5.526.View ArticlePubMedPubMed CentralGoogle Scholar
- Fitaw Y, Boersma MFJ: Prevalence and impact of disability in north-western Ethiopia. Disabil Rehabil. 2006, 28 (15): 949-953. 10.1080/09638280500404552.View ArticlePubMedGoogle Scholar
- Central Bureau of Statistics GoK: Geographic dimension of well being in Kenya: a constituency level profile, volume II. 2006Google Scholar
- KDHS: 2008–09 Kenya demographic and health survey. 2010Google Scholar
- Kaneko Satoshi JK, Kiche I, Wanyua S, Goto K, Tanaka J, Changoma M, Mwangangi M, Karama M, Moji K, Shimada M: Health and demoraphic surveillance system (HDSS) in the western and coastal areas of Kenya: an inflastructure for epidemiologic studies in africa. J Epidemiol. 2012, Under publishingGoogle Scholar
- Naing L, Winn T, Rusli BN: Practical issue in calculating the sample size for prevalence survey. Arch Orofac Sci. 2006, 1: 9-14.Google Scholar
- Zaman SS, Khan NZ, Islam S, Banu S, Dixit S, Shrout P, et al: Validity of the 'Ten Questions' for screening serious childhood disability: results from urban Bangladesh. Int J Epidemiol. 1990, 19 (3): 613-20. 10.1093/ije/19.3.613.View ArticlePubMedGoogle Scholar
- Durkin MS, Davidson LL, Desai P, Hasan ZM, Khan N, Shrout PE, et al: Validity of the Ten Questions screen for childhood disability: Results from population-based studies in Bangladesh, Jamaica, and Pakistan. Epidemiology. 1994, 5 (3): 283-9. 10.1097/00001648-199405000-00005.View ArticlePubMedGoogle Scholar
- Singhi P, Kumar M, Malhi P, Kumar R: Utility of the WHO ten questions screen for disability detection in a rural community - The North Indian experience. J Trop Pediatr. 2007, 53 (6): 383-7. 10.1093/tropej/fmm047.View ArticlePubMedGoogle Scholar
- Mung'ala-Odera V, Meehan R, Njuguna P, Mturi N, Alcock K, Carter JA, et al: Validity and reliability of the 'Ten Questions' Questionnaire for detecting moderate to severe neurological impairment in children aged 6–9 years in rural Kenya. Neuroepidemiology. 2004, 23 (1–2): 67-72.View ArticlePubMedGoogle Scholar
- Seidel HM, Ball J, Dains J, Benedict GW: Mosby's physical examination handbook. 2006Google Scholar
- Pointer JS: Recognition versus resolution: a comparison of visual acuity results using Two alternative test chart optotype. J Optometry. 2008, 1: 65-70. 10.3921/joptom.2008.65.View ArticleGoogle Scholar
- Survey NHaNE: AUDIOMETRY PROCEDURES MANUAL. 2003Google Scholar
- Baddeley A, Gardner JM, Graham-Mcgrgor S: Cross-cultural cognition: Developing tests for developing countries. Applied Cognitive Psychology. 1995, 9 (7): S173-S195. 10.1002/acp.2350090711.View ArticleGoogle Scholar
- Glanzer: Storage mechamsms in recall: The psychology of learning and motivation; advances in research and theory. 1972, New York Academic PressGoogle Scholar
- Akaike H: A new look at the statistical model identification. IEEE Trans Automatic Control. 1974, 19 (6): 716-23. 10.1109/TAC.1974.1100705.View ArticleGoogle Scholar
- Muga E: Screening for disability in a community: the 'ten questions' screen for children, in Bondo, Kenya. Afr Health Sci. 2003, 3 (1): 33-9.PubMedPubMed CentralGoogle Scholar
- Couper J: Prevalence of childhood disability in rural KwaZulu-Natal. South African Medical J. 2002, 92 (7): 549-52.Google Scholar
- Biritwum RB, Devres JP, Ofosu-Amaah S, Marfo C, Essah ER: Prevalence of children with disabilities in central region, Ghana. West Afr J Med. 2001, 20 (3): 249-55.PubMedGoogle Scholar
- Thorburn M, Desai P, Paul TJ, Malcolm L, Durkin M, Davidson L: Identification of childhood disability in Jamaica: evaluation of the ten question screen. Int J Rehabil Res. 1992, 15 (3): 262-70. 10.1097/00004356-199209000-00013.View ArticlePubMedGoogle Scholar
- Durkin MS, Hasan ZM, Hasan KZ: The ten questions screen for childhood disabilities: Its uses and limitations in Pakistan. J Epidemiol Community Health. 1995, 49 (4): 431-6. 10.1136/jech.49.4.431.View ArticlePubMedPubMed CentralGoogle Scholar
- Annegers JF, Rocca WA: Causes of epilepsy: contributions of the rochester epidemiology project. Mayo Clin Proc. 1996, 71 (6): 570-5. 10.4065/71.6.570.View ArticlePubMedGoogle Scholar
- Carter JA, Neville BGR, White S, Ross AJ, Otieno G, Mturi N, et al: Increased prevalence of epilepsy associated with severe falciparum malaria in children. Epilepsia. 2004, 45 (8): 978-81. 10.1111/j.0013-9580.2004.65103.x.View ArticlePubMedGoogle Scholar
- Newton CR, Garcia HH: Epilepsy in poor regions of the world. Lancet. 2012, 380 (9848): 1193-201. 10.1016/S0140-6736(12)61381-6.View ArticlePubMedGoogle Scholar
- Bhalla D, Chea K, Hun C, Vannareth M, Huc P, Chan S, et al: Population-based study of epilepsy in cambodia associated factors, measures of impact, stigma, quality of life, knowledge-attitude-practice, and treatment gap. PLoS One. 2012, 7 (10): e46296-10.1371/journal.pone.0046296.View ArticlePubMedPubMed CentralGoogle Scholar
- Benedicte Ingstad LG: see me, and do not forget me people with disabilities in Kenya. 2007, Kenya: World Bank, 1-68.Google Scholar
- Sida: Children and adults with disabilities - Publications - Sida. 2009Google Scholar
- Perry H, Robison N, Chavez D, Taja O, Hilari C, Shanklin D, et al: The census-based, impact-oriented approach: Its effectiveness in promoting child health in Bolivia. Health Policy Plan. 1998, 13 (2): 140-51. 10.1093/heapol/13.2.140.View ArticlePubMedGoogle Scholar
- ADC: Focus: Persons with Disabilities in ADC. 2011, Austrian Development Agency, the operationalional unit of of the Austrian Development Cooperation Information and Communication, [http://www.entwicklung.at/uploads/media/Focus_Disabilities_May2011.pdf]Google Scholar
- Alaa Shukrallah NH, Abdel-Hamid K: Prevention, early detection and management of childhood disabilities association for health and environmental development. 2004Google Scholar
- Barlow JL, Mung'Ala-Odera V, Gona J, Newton CRJC: Brain damage after neonatal tetanus in a rural Kenyan hospital. Trop Med Int Health. 2001, 6 (4): 305-8. 10.1046/j.1365-3156.2001.00705.x.View ArticlePubMedGoogle Scholar
- OLUSEGUN J, ADEBAMI GAO, JOSHUA A, OWA , OYEKU A: OYELAMI Maternal factors in the etiology of fetal malnutrition in Nigeria. Pediatrics Int. 2007, 49: 150-5. 10.1111/j.1442-200X.2007.02328.x.View ArticleGoogle Scholar
- Rahman MM, Abidin S: Factors affecting neonatal mortality in Bangladesh. J Heal Manag. 2010, 12 (2): 137-52. 10.1177/097206341001200203.View ArticleGoogle Scholar
- FD OÂ¨zÂ¨rA, Yavuz T, Yıldız S: Antenatal and delivery risk factors and prevalence of cerebral palsy in Duzce (Turkey). Brain Dev. 2007, 29: 39-42. 10.1016/j.braindev.2006.05.011.View ArticleGoogle Scholar
- Mwaniki MK, Atieno M, Lawn JE, Newton CRJC: Long-term neurodevelopmental outcomes after intrauterine and neonatal insults: A systematic review. Lancet. 2012, 379 (9814): 445-52. 10.1016/S0140-6736(11)61577-8.View ArticlePubMedPubMed CentralGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2431/12/186/prepub
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.