An estimate of asthma prevalence in Africa: a systematic analysis
Identifieur interne : 002330 ( Pmc/Corpus ); précédent : 002329; suivant : 002331An estimate of asthma prevalence in Africa: a systematic analysis
Auteurs : Davies Adeloye ; Kit Yee Chan ; Igor Rudan ; Harry CampbellSource :
- Croatian Medical Journal [ 0353-9504 ] ; 2013.
Abstract
To estimate and compare asthma prevalence in Africa in 1990, 2000, and 2010 in order to provide information that will help inform the planning of the public health response to the disease.
We conducted a systematic search of Medline, EMBASE, and Global Health for studies on asthma published between 1990 and 2012. We included cross-sectional population based studies providing numerical estimates on the prevalence of asthma. We calculated weighted mean prevalence and applied an epidemiological model linking age with the prevalence of asthma. The UN population figures for Africa for 1990, 2000, and 2010 were used to estimate the cases of asthma, each for the respective year.
Our search returned 790 studies. We retained 45 studies that met our selection criteria. In Africa in 1990, we estimated 34.1 million asthma cases (12.1%; 95% confidence interval [CI] 7.2-16.9) among children <15 years, 64.9 million (11.8%; 95% CI 7.9-15.8) among people aged <45 years, and 74.4 million (11.7%; 95% CI 8.2-15.3) in the total population. In 2000, we estimated 41.3 million cases (12.9%; 95% CI 8.7-17.0) among children <15 years, 82.4 million (12.5%; 95% CI 5.9-19.1) among people aged <45 years, and 94.8 million (12.0%; 95% CI 5.0-18.8) in the total population. This increased to 49.7 million (13.9%; 95% CI 9.6-18.3) among children <15 years, 102.9 million (13.8%; 95% CI 6.2-21.4) among people aged <45 years, and 119.3 million (12.8%; 95% CI 8.2-17.1) in the total population in 2010. There were no significant differences between asthma prevalence in studies which ascertained cases by written and video questionnaires. Crude prevalences of asthma were, however, consistently higher among urban than rural dwellers.
Our findings suggest an increasing prevalence of asthma in Africa over the past two decades. Due to the paucity of data, we believe that the true prevalence of asthma may still be under-estimated. There is a need for national governments in Africa to consider the implications of this increasing disease burden and to investigate the relative importance of underlying risk factors such as rising urbanization and population aging in their policy and health planning responses to this challenge.
Url:
DOI: 10.3325/cmj.2013.54.519
PubMed: 24382846
PubMed Central: 3893990
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PMC:3893990Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">An estimate of asthma prevalence in Africa: a systematic analysis</title><author><name sortKey="Adeloye, Davies" sort="Adeloye, Davies" uniqKey="Adeloye D" first="Davies" last="Adeloye">Davies Adeloye</name></author><author><name sortKey="Chan, Kit Yee" sort="Chan, Kit Yee" uniqKey="Chan K" first="Kit Yee" last="Chan">Kit Yee Chan</name></author><author><name sortKey="Rudan, Igor" sort="Rudan, Igor" uniqKey="Rudan I" first="Igor" last="Rudan">Igor Rudan</name></author><author><name sortKey="Campbell, Harry" sort="Campbell, Harry" uniqKey="Campbell H" first="Harry" last="Campbell">Harry Campbell</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">24382846</idno><idno type="pmc">3893990</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3893990</idno><idno type="RBID">PMC:3893990</idno><idno type="doi">10.3325/cmj.2013.54.519</idno><date when="2013">2013</date><idno type="wicri:Area/Pmc/Corpus">002330</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">002330</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">An estimate of asthma prevalence in Africa: a systematic analysis</title><author><name sortKey="Adeloye, Davies" sort="Adeloye, Davies" uniqKey="Adeloye D" first="Davies" last="Adeloye">Davies Adeloye</name></author><author><name sortKey="Chan, Kit Yee" sort="Chan, Kit Yee" uniqKey="Chan K" first="Kit Yee" last="Chan">Kit Yee Chan</name></author><author><name sortKey="Rudan, Igor" sort="Rudan, Igor" uniqKey="Rudan I" first="Igor" last="Rudan">Igor Rudan</name></author><author><name sortKey="Campbell, Harry" sort="Campbell, Harry" uniqKey="Campbell H" first="Harry" last="Campbell">Harry Campbell</name></author></analytic><series><title level="j">Croatian Medical Journal</title><idno type="ISSN">0353-9504</idno><idno type="eISSN">1332-8166</idno><imprint><date when="2013">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Aim</title><p>To estimate and compare asthma prevalence in Africa in 1990, 2000, and 2010 in order to provide information that will help inform the planning of the public health response to the disease.</p></sec><sec><title>Methods</title><p>We conducted a systematic search of Medline, EMBASE, and Global Health for studies on asthma published between 1990 and 2012. We included cross-sectional population based studies providing numerical estimates on the prevalence of asthma. We calculated weighted mean prevalence and applied an epidemiological model linking age with the prevalence of asthma. The UN population figures for Africa for 1990, 2000, and 2010 were used to estimate the cases of asthma, each for the respective year.</p></sec><sec><title>Results</title><p>Our search returned 790 studies. We retained 45 studies that met our selection criteria. In Africa in 1990, we estimated 34.1 million asthma cases (12.1%; 95% confidence interval [CI] 7.2-16.9) among children <15 years, 64.9 million (11.8%; 95% CI 7.9-15.8) among people aged <45 years, and 74.4 million (11.7%; 95% CI 8.2-15.3) in the total population. In 2000, we estimated 41.3 million cases (12.9%; 95% CI 8.7-17.0) among children <15 years, 82.4 million (12.5%; 95% CI 5.9-19.1) among people aged <45 years, and 94.8 million (12.0%; 95% CI 5.0-18.8) in the total population. This increased to 49.7 million (13.9%; 95% CI 9.6-18.3) among children <15 years, 102.9 million (13.8%; 95% CI 6.2-21.4) among people aged <45 years, and 119.3 million (12.8%; 95% CI 8.2-17.1) in the total population in 2010. There were no significant differences between asthma prevalence in studies which ascertained cases by written and video questionnaires. Crude prevalences of asthma were, however, consistently higher among urban than rural dwellers.</p></sec><sec><title>Conclusion</title><p>Our findings suggest an increasing prevalence of asthma in Africa over the past two decades. Due to the paucity of data, we believe that the true prevalence of asthma may still be under-estimated. There is a need for national governments in Africa to consider the implications of this increasing disease burden and to investigate the relative importance of underlying risk factors such as rising urbanization and population aging in their policy and health planning responses to this challenge.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Anandan, C" uniqKey="Anandan C">C Anandan</name></author><author><name sortKey="Nurmatov, U" uniqKey="Nurmatov U">U Nurmatov</name></author><author><name sortKey="Van Schayck, Oc" uniqKey="Van Schayck O">OC van Schayck</name></author><author><name sortKey="Sheikh, A" uniqKey="Sheikh A">A Sheikh</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bousquet, J" uniqKey="Bousquet J">J Bousquet</name></author><author><name sortKey="Mantzouranis, E" uniqKey="Mantzouranis E">E Mantzouranis</name></author><author><name sortKey="Cruz, Aa" 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Croat Med J</journal-id><journal-id journal-id-type="iso-abbrev">Croat. Med. J</journal-id><journal-id journal-id-type="publisher-id">CMJ</journal-id><journal-title-group><journal-title>Croatian Medical Journal</journal-title></journal-title-group><issn pub-type="ppub">0353-9504</issn><issn pub-type="epub">1332-8166</issn><publisher><publisher-name>Croatian Medical Schools</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">24382846</article-id><article-id pub-id-type="pmc">3893990</article-id><article-id pub-id-type="publisher-id">CroatMedJ_54_0519</article-id><article-id pub-id-type="doi">10.3325/cmj.2013.54.519</article-id><article-categories><subj-group subj-group-type="heading"><subject>Diseases in Low and Middle Income Countries</subject></subj-group></article-categories><title-group><article-title>An estimate of asthma prevalence in Africa: a systematic analysis</article-title><alt-title alt-title-type="running-head">Adeloye et al: An estimate of asthma prevalence in Africa: a systematic analysis</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Adeloye</surname><given-names>Davies</given-names></name></contrib><contrib contrib-type="author"><name><surname>Chan</surname><given-names>Kit Yee</given-names></name></contrib><contrib contrib-type="author"><name><surname>Rudan</surname><given-names>Igor</given-names></name></contrib><contrib contrib-type="author"><name><surname>Campbell</surname><given-names>Harry</given-names></name></contrib><aff id="aff1">Centre for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, UK</aff></contrib-group><author-notes><corresp id="cor1">Correspondence to:
Davies Adeloye
WHO Collaborative Centre for Population Health Research and Training, Centre for Population Health Sciences
University of Edinburgh Medical School
Edinburgh, EH8 9AG, UK
<email xlink:href="Davies.Adeloye@ed.ac.uk">Davies.Adeloye@ed.ac.uk</email></corresp></author-notes><pub-date pub-type="ppub"><month>12</month><year>2013</year></pub-date><volume>54</volume><issue>6</issue><fpage>519</fpage><lpage>531</lpage><history><date date-type="received"><day>15</day><month>8</month><year>2013</year></date><date date-type="accepted"><day>15</day><month>12</month><year>2013</year></date></history><permissions><copyright-statement>Copyright © 2013 by the Croatian Medical Journal. All rights reserved.</copyright-statement><copyright-year>2013</copyright-year><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.5/"><license-p>This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions><abstract><sec><title>Aim</title><p>To estimate and compare asthma prevalence in Africa in 1990, 2000, and 2010 in order to provide information that will help inform the planning of the public health response to the disease.</p></sec><sec><title>Methods</title><p>We conducted a systematic search of Medline, EMBASE, and Global Health for studies on asthma published between 1990 and 2012. We included cross-sectional population based studies providing numerical estimates on the prevalence of asthma. We calculated weighted mean prevalence and applied an epidemiological model linking age with the prevalence of asthma. The UN population figures for Africa for 1990, 2000, and 2010 were used to estimate the cases of asthma, each for the respective year.</p></sec><sec><title>Results</title><p>Our search returned 790 studies. We retained 45 studies that met our selection criteria. In Africa in 1990, we estimated 34.1 million asthma cases (12.1%; 95% confidence interval [CI] 7.2-16.9) among children <15 years, 64.9 million (11.8%; 95% CI 7.9-15.8) among people aged <45 years, and 74.4 million (11.7%; 95% CI 8.2-15.3) in the total population. In 2000, we estimated 41.3 million cases (12.9%; 95% CI 8.7-17.0) among children <15 years, 82.4 million (12.5%; 95% CI 5.9-19.1) among people aged <45 years, and 94.8 million (12.0%; 95% CI 5.0-18.8) in the total population. This increased to 49.7 million (13.9%; 95% CI 9.6-18.3) among children <15 years, 102.9 million (13.8%; 95% CI 6.2-21.4) among people aged <45 years, and 119.3 million (12.8%; 95% CI 8.2-17.1) in the total population in 2010. There were no significant differences between asthma prevalence in studies which ascertained cases by written and video questionnaires. Crude prevalences of asthma were, however, consistently higher among urban than rural dwellers.</p></sec><sec><title>Conclusion</title><p>Our findings suggest an increasing prevalence of asthma in Africa over the past two decades. Due to the paucity of data, we believe that the true prevalence of asthma may still be under-estimated. There is a need for national governments in Africa to consider the implications of this increasing disease burden and to investigate the relative importance of underlying risk factors such as rising urbanization and population aging in their policy and health planning responses to this challenge.</p></sec></abstract></article-meta></front><body><p>Chronic respiratory diseases (CRDs) are among the leading causes of death worldwide, with asthma rated the most common chronic disease affecting children (<xref rid="R1" ref-type="bibr">1</xref>). Globally, about 300 million people have asthma, and current trends suggest that an additional 100 million people may be living with asthma by 2025 (<xref rid="R1" ref-type="bibr">1</xref>,<xref rid="R2" ref-type="bibr">2</xref>). The World Health Organization (WHO) estimates about 250 000 deaths from asthma every year, mainly in low- and middle-income countries (LMIC) (<xref rid="R3" ref-type="bibr">3</xref>,<xref rid="R4" ref-type="bibr">4</xref>). Just like with many other chronic diseases in Africa, the fast rate of urbanization has been linked to the increase in the burden of asthma and other allergic diseases (<xref rid="R3" ref-type="bibr">3</xref>,<xref rid="R5" ref-type="bibr">5</xref>,<xref rid="R6" ref-type="bibr">6</xref>). The prevalence of these conditions may, in theory, have the potential to reach levels higher than those observed in high-income countries (HIC) due to priming effects of parasitic helminthic infections on the immune system, as these infections are common in many African settings (<xref rid="R5" ref-type="bibr">5</xref>). The International Study of Asthma and Allergies (ISAAC) reported that asthma prevalence among children was increasing in Africa and has contributed most to the burden of disease through its effects on quality of life (<xref rid="R3" ref-type="bibr">3</xref>). In-patient admissions and purchase of medications account for most of the direct costs on government, while loss of productivity, due to absenteeism from work and school, are responsible for most of the indirect costs (<xref rid="R7" ref-type="bibr">7</xref>,<xref rid="R8" ref-type="bibr">8</xref>).</p><p>Asthma is widely known as a multifactorial respiratory disorder with both genetic and environmental underlying risk factors (<xref rid="R3" ref-type="bibr">3</xref>). Exposure to common allergens (including pollens, dust mites, and animal furs) and indoor and outdoor air pollution from various sources (eg, traffic pollution, combustion of fossils and biomass fuels, workplace dust) have all been implicated as triggers of the disease (<xref rid="R9" ref-type="bibr">9</xref>). Second hand tobacco smoking is a confirmed risk factor in pediatric patients (<xref rid="R5" ref-type="bibr">5</xref>,<xref rid="R10" ref-type="bibr">10</xref>). Viral infections, a major cause of upper respiratory tract infections and “common cold,” are also a common risk factor in children (<xref rid="R11" ref-type="bibr">11</xref>,<xref rid="R12" ref-type="bibr">12</xref>). As noted, helminthic infections are relatively common in Africa and are associated with bronchial hyper-responsiveness and asthma (<xref rid="R5" ref-type="bibr">5</xref>,<xref rid="R13" ref-type="bibr">13</xref>); this is perhaps due to the presence of related raised immunoglobulin E (IgE) and a prominent Th2 immune response (<xref rid="R5" ref-type="bibr">5</xref>,<xref rid="R14" ref-type="bibr">14</xref>).</p><p>Studies on asthma are few in Africa, with most publications mainly from South African and Nigerian populations (<xref rid="R14" ref-type="bibr">14</xref>). One main factor affecting research output is the diagnosis of asthma, which still remains a challenging issue (<xref rid="R15" ref-type="bibr">15</xref>,<xref rid="R16" ref-type="bibr">16</xref>). The WHO has emphasized that this has limited on-going research efforts globally (<xref rid="R4" ref-type="bibr">4</xref>,<xref rid="R16" ref-type="bibr">16</xref>). The International Union against Tuberculosis and Lung Diseases (IUATLD) published one of the first diagnostic and survey guidelines for asthma in 1984, but experts subsequently reported concerns about its precision and reliability (<xref rid="R17" ref-type="bibr">17</xref>). According to the Global Initiative for Asthma (GINA), detailed history, physical examination and spirometric lung function tests are vital to the diagnosis and management of asthma (<xref rid="R10" ref-type="bibr">10</xref>,<xref rid="R18" ref-type="bibr">18</xref>). Generally, a reduction in forced expiratory volume in one second (FEV<sub>1</sub>) and peak expiratory flow (PEF) may be indicative of asthma, with the amount of reduction proportional to the severity of asthma (<xref rid="R4" ref-type="bibr">4</xref>). GINA proposed that an increase in FEV<sub>1</sub> of >12% and 200 mL in about 15-20 minutes following the inhalation of 200-400 μg of salbutamol or a 20% increase in PEF from baseline can be employed as standardized criteria in diagnosis of asthma (<xref rid="R10" ref-type="bibr">10</xref>). This, however, lacks sensitivity, as many asthmatics, especially those on treatment, may not exhibit an increase in FEV<sub>1</sub> and PEF when assessed (<xref rid="R16" ref-type="bibr">16</xref>,<xref rid="R20" ref-type="bibr">19</xref>). Thus, although asthma is characterized by significant reversibility of airway obstruction, an absence of reversibility may not always exclude the presence of asthma (<xref rid="R19" ref-type="bibr">20</xref>). The ISAAC established in 1991, remains the largest epidemiological study among children globally (<xref rid="R1" ref-type="bibr">1</xref>). ISAAC methodologies and scoring are currently the most widely employed by researchers in Africa (<xref rid="R1" ref-type="bibr">1</xref>,<xref rid="R4" ref-type="bibr">4</xref>). This involves both video and written questionnaires, as there were reports that video and pictorial representations of asthma symptoms may contribute to improved case recognition in younger children (<xref rid="R1" ref-type="bibr">1</xref>). However, this is still a subject of debate among experts (<xref rid="R21" ref-type="bibr">21</xref>). The European Community Respiratory Health Survey (ECRHS), which assessed the prevalence of atopy and symptoms of airway disease among older age groups in Western Europe, has been widely implemented and has reported significant geographic variations in the prevalence of asthma and atopy (<xref rid="R9" ref-type="bibr">9</xref>). Despite these revised guidelines, both ISAAC and ECRHS research groups have reported challenges in achieving high sensitivity and specificity in case ascertainment with the symptom “wheeze at rest in the last 12 months” (also regarded as current wheeze, or active wheeze), yielding the highest sensitivity and specificity (<xref rid="R1" ref-type="bibr">1</xref>).</p><p>In Africa, problems including those arising from the over-utilization of health services, lack of trained staff and diagnostic apparatus, and non-availability and unaffordability of inhaled medications have hindered efforts to improve the management of asthma (<xref rid="R22" ref-type="bibr">22</xref>,<xref rid="R23" ref-type="bibr">23</xref>). The lack of organized health promotion programs, such as effective control strategies for environmental triggers, air pollutants, and occupational dusts have also contributed to the growing burden (<xref rid="R24" ref-type="bibr">24</xref>). The WHO has reported that the levels of asthma control and health responses in the continent have been below recommended standards, and that these have contributed to the size of the disease burden (<xref rid="R3" ref-type="bibr">3</xref>,<xref rid="R4" ref-type="bibr">4</xref>). In addition, although many African countries have national guidelines for the management of asthma and other CRDs, these guidelines have not been implemented in most rural areas (<xref rid="R25" ref-type="bibr">25</xref>,<xref rid="R26" ref-type="bibr">26</xref>). Economic analyses in many African settings have shown that direct costs from asthma are usually greater than the indirect costs. However, indirect costs represent a relatively higher proportion of total costs among pediatric than adult patients (<xref rid="R8" ref-type="bibr">8</xref>). Moreover, the wider economic burden on individuals, families, employers, and society, due to loss of future potential source of livelihood, has also been devastating in many resource-poor settings (<xref rid="R22" ref-type="bibr">22</xref>). It is believed that many children with asthma in Africa may fail to achieve their full potential if proper management and control measures are not put in place (<xref rid="R1" ref-type="bibr">1</xref>). It has been suggested that education of health care providers and the public is a vital element of the response to the challenge posed by asthma in Africa (<xref rid="R4" ref-type="bibr">4</xref>,<xref rid="R27" ref-type="bibr">27</xref>).</p><p>By 2015, it is expected that world’s urban population will increase from 45% to 59%, with over half of this occurring in Africa (<xref rid="R8" ref-type="bibr">8</xref>). It is also expected that the prevalence of asthma and many chronic diseases in Africa will increase due to this growing population size and from effects of accompanying urbanization and adoption of western lifestyles (<xref rid="R28" ref-type="bibr">28</xref>). In light of this and of the low research output and poor availability of health services data on the burden of asthma in Africa, it is important to analyze the available data through a systematic review of the literature in order to attempt to quantify the burden, guide health priority settings, and inform the formulation of an appropriate health policy response.</p><sec sec-type="methods"><title>METHODS</title><sec><title>Search strategy and selection criteria</title><p>We conducted a systematic search of Medline, EMBASE, and Global Health. After an initial scoping exercise to identify Medical Subject Headings (MESH) and keywords, we developed a final search strategy. We further hand-searched reference lists of retained publications for more relevant studies. African countries were included as contained in the World Bank list of economies from July 2012 (<xref rid="R29" ref-type="bibr">29</xref>) (<xref ref-type="table" rid="T1">Table 1</xref><bold>)</bold>.</p><table-wrap id="T1" position="float"><label>Table 1</label><caption><p>Search terms used in the study</p></caption><table frame="hsides" rules="groups"><col width="47" span="1"></col><col width="414" span="1"></col><tbody><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">africa/ or exp africa, northern/ or exp algeria/ or exp egypt/ or exp libya/ or exp morocco/ or exp tunisia/ or exp “africa south of the sahara”/ or exp africa, central/ or exp cameroon/ or exp central african republic/ or exp chad/ or exp congo/ or exp “democratic republic of the congo”/ or exp equatorial guinea/ or exp gabon/ or exp africa, eastern/ or exp burundi/ or exp djibouti/ or exp eritrea/ or exp ethiopia/ or exp kenya/ or exp rwanda/ or exp somalia/ or exp sudan/ or exp tanzania/ or exp uganda/ or exp africa, southern/ or exp angola/ or exp botswana/ or exp lesotho/ or exp malawi/ or exp mozambique/ or exp namibia/ or exp south africa/ or exp swaziland/ or exp zambia/ or exp zimbabwe/ or exp africa, western/ or exp benin/ or exp burkina faso/ or exp cape verde/ or exp cote d'ivoire/ or exp gambia/ or exp ghana/ or exp guinea/ or exp guinea-bissau/ or exp liberia/ or exp mali/ or exp mauritania/ or exp niger/ or exp nigeria/ or exp senegal/ or exp sierra leone/ or exp togo/<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 2<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">exp vital statistics/ or exp incidence/<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 3<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">(incidence* or prevalence* or morbidity or mortality).tw.<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 4<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">(disease adj3 burden).tw.<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 5<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">exp “cost of illness”/<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 6<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">exp quality-adjusted life years/<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 7<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">QALY.tw.<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 8<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">Disability adjusted life years.mp.<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 9<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">(initial adj2 burden).tw.<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 10<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">exp risk factors/<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 11<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2 or 3 or 4 or 5 or 6 or 7 or 8 or 9 or 10<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 12<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">exp asthma/ or exp asthma, aspirin-induced/ or exp asthma, exercise-induced/ or exp asthma, occupational/ or exp status asthmaticus/<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"> 13</td><td valign="top" align="left" rowspan="1" colspan="1">1 and 11 and 12</td></tr></tbody></table></table-wrap><p>We retained cross-sectional population-based studies on asthma conducted primarily on African population groups. The date of publication was set from 1990 to June 2013. We included studies providing numerical estimates on the prevalence of asthma, including non-English publications. We excluded studies that were mainly reviews, hospital-based (without a denominator population estimate), without numerical estimates, and conducted on non-human subjects.</p><p>Studies were further checked for clear diagnostic criteria and survey methods. As noted above, asthma has been described in various ways by many researchers, we therefore allowed for these variations in our analysis (<xref ref-type="table" rid="T2">Table 2</xref> and Supplementary Table 1 <xref ref-type="supplementary-material" rid="S1">(supplementary table 1)</xref>). However, most survey methods were mainly based on written or video questionnaires, as proposed by the ISAAC study group (<xref ref-type="table" rid="T3">Table 3</xref> and Supplementary Table 1 <xref ref-type="supplementary-material" rid="S1">(supplementary table 1)</xref>).</p><table-wrap id="T2" position="float"><label>Table 2</label><caption><p>Asthma terms and definitions</p></caption><table frame="hsides" rules="groups"><col width="97" span="1"></col><col width="364" span="1"></col><thead><tr><th valign="top" align="left" scope="col" rowspan="1" colspan="1">Terms</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">Definition</th></tr></thead><tbody><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Wheeze<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">A high pitched whistling sound originating from obstructed airways (<xref rid="R1" ref-type="bibr">1</xref>). “Wheeze at rest-12 months” refers to the prevalence of wheeze in a person in the last 12 mo.<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Asthma<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">A chronic airway disease characterized by wheezing (a high pitched whistling sound originating from obstructed airways). Patient usually presents with chronic airways inflammation, bronchial hyper-responsiveness and reversible airflow obstruction, resulting in the recurrent attacks of wheeze, chest tightness, breathlessness, and occasionally cough and sputum production, all of varying severity and frequency from person to person (<xref rid="R1" ref-type="bibr">1</xref>,<xref rid="R3" ref-type="bibr">3</xref>,<xref rid="R24" ref-type="bibr">24</xref>,<xref rid="R87" ref-type="bibr">87</xref>). Asthma ever refers to cummulative prevalence of asthma in a person.<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Asthma exacerbation<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">Also known as acute asthma. A sudden progressive episodes of shortness of breath, usually characterized by chest tightness, wheezing, cough, or sputum production (<xref rid="R87" ref-type="bibr">87</xref>)<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Moderate asthma exacerbation<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">An event that, when recognized, should result in a temporary change in treatment, in an effort to prevent the exacerbation from being severe (<xref rid="R24" ref-type="bibr">24</xref>)<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Severe asthma exacerbation<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">Events that require urgent action on the part of the patient and physician to prevent a serious outcome, such as hospitalization or death (<xref rid="R24" ref-type="bibr">24</xref>)<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Severe asthma<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">Uncontrolled asthma which can result in risk of frequent severe exacerbations (or death), and/or adverse reactions to medications, and/or chronic morbidity, including impaired lung function or reduced lung growth in children (<xref rid="R24" ref-type="bibr">24</xref>)<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Asthma control<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">Extent to which the various manifestation of asthma are reduced or removed by treatment (<xref rid="R3" ref-type="bibr">3</xref>,<xref rid="R24" ref-type="bibr">24</xref>)<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Asthma diagnosis</td><td valign="top" align="left" rowspan="1" colspan="1">GINA proposed a holistic approach involving detailed history, physical examination and spirometry. An increase in FEV<sub>1</sub> of ≥12% and ≥200ml after a bronchodilator is indicative of reversible airflow limitation, which is consistent with asthma. Peak expiratory flow (PEF) with an improvement of 60l/min (or ≥20% of the pre-bronchodilator PEF) after a bronchodilator, or a diurnal variation in PEF of more than 20% (with twice daily readings more than 10%) may also be indicative of asthma. Other non-specific diagnostic tests include methacholine or histamine test, inhaled mannitol or exercise challenge, skin prick test and measurement of serum IgE (<xref rid="R10" ref-type="bibr">10</xref>,<xref rid="R18" ref-type="bibr">18</xref>)</td></tr></tbody></table><table-wrap-foot><p><sup>*Abbreviations: FEV1 – forced expiratory volume in one second; GINA – Global Initiative for Asthma; IgE – immunoglobulin E; PEF – peak expiratory flow.</sup></p></table-wrap-foot></table-wrap><table-wrap id="T3" position="float"><label>Table 3</label><caption><p>Asthma study distribution</p></caption><table frame="hsides" rules="groups"><col width="231" span="1"></col><col width="114" span="1"></col><thead><tr><th valign="top" align="left" scope="col" rowspan="1" colspan="1">Country:</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">Number of studies</th></tr></thead><tbody><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Algeria (<xref rid="R32" ref-type="bibr">32</xref>,<xref rid="R36" ref-type="bibr">36</xref>,<xref rid="R37" ref-type="bibr">37</xref>,<xref rid="R44" ref-type="bibr">44</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">4<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Burkina Faso (<xref rid="R55" ref-type="bibr">55</xref>,<xref rid="R56" ref-type="bibr">56</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Cameroon (<xref rid="R31" ref-type="bibr">31</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Cape Verde (<xref rid="R72" ref-type="bibr">72</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Congo Brazzaville (<xref rid="R31" ref-type="bibr">31</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Cote d’Ivoire (<xref rid="R31" ref-type="bibr">31</xref>,<xref rid="R47" ref-type="bibr">47</xref>,<xref rid="R63" ref-type="bibr">63</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">DR Congo (<xref rid="R31" ref-type="bibr">31</xref>,<xref rid="R61" ref-type="bibr">61</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Egypt (<xref rid="R52" ref-type="bibr">52</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Ethiopia (<xref rid="R12" ref-type="bibr">12</xref>,<xref rid="R31" ref-type="bibr">31</xref>,<xref rid="R32" ref-type="bibr">32</xref>,<xref rid="R53" ref-type="bibr">53</xref>,<xref rid="R71" ref-type="bibr">71</xref>,<xref rid="R73" ref-type="bibr">73</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Gabon (<xref rid="R31" ref-type="bibr">31</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Gambia (<xref rid="R69" ref-type="bibr">69</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Ghana (<xref rid="R41" ref-type="bibr">41</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Guinea (<xref rid="R31" ref-type="bibr">31</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Kenya (<xref rid="R31" ref-type="bibr">31</xref>,<xref rid="R39" ref-type="bibr">39</xref>,<xref rid="R40" ref-type="bibr">40</xref>,<xref rid="R59" ref-type="bibr">59</xref>,<xref rid="R68" ref-type="bibr">68</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Madagascar (<xref rid="R66" ref-type="bibr">66</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Morocco (<xref rid="R32" ref-type="bibr">32</xref>,<xref rid="R34" ref-type="bibr">34</xref>,<xref rid="R44" ref-type="bibr">44</xref>,<xref rid="R48" ref-type="bibr">48</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">4<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Mozambique (<xref rid="R49" ref-type="bibr">49</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Nigeria (<xref rid="R31" ref-type="bibr">31</xref>-<xref rid="R33" ref-type="bibr">33</xref>,<xref rid="R38" ref-type="bibr">38</xref>,<xref rid="R45" ref-type="bibr">45</xref>,<xref rid="R50" ref-type="bibr">50</xref>,<xref rid="R51" ref-type="bibr">51</xref>,<xref rid="R58" ref-type="bibr">58</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Rwanda (<xref rid="R57" ref-type="bibr">57</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">South Africa (<xref rid="R19" ref-type="bibr">20</xref>,<xref rid="R31" ref-type="bibr">31</xref>,<xref rid="R32" ref-type="bibr">32</xref>,<xref rid="R42" ref-type="bibr">42</xref>,<xref rid="R43" ref-type="bibr">43</xref>,<xref rid="R54" ref-type="bibr">54</xref>,<xref rid="R60" ref-type="bibr">60</xref>,<xref rid="R62" ref-type="bibr">62</xref>,<xref rid="R65" ref-type="bibr">65</xref>,<xref rid="R67" ref-type="bibr">67</xref>,<xref rid="R70" ref-type="bibr">70</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">11<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Sudan (<xref rid="R31" ref-type="bibr">31</xref>,<xref rid="R32" ref-type="bibr">32</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Tanzania (<xref rid="R35" ref-type="bibr">35</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Togo (<xref rid="R31" ref-type="bibr">31</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">Tunisia (<xref rid="R32" ref-type="bibr">32</xref>,<xref rid="R44" ref-type="bibr">44</xref>,<xref rid="R46" ref-type="bibr">46</xref>,<xref rid="R64" ref-type="bibr">64</xref>)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">4<hr></hr></td></tr><tr><td valign="top" align="left" scope="col" rowspan="1" colspan="1"><bold>Duration of study:</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1"><hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"><1 y<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">23<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">1-3 y<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">16<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">>3 y<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6<hr></hr></td></tr><tr><td valign="top" align="left" scope="col" rowspan="1" colspan="1"><bold>Sample size:</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1"><hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"><1000<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">18<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">1001-3000<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">15<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">>3000<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">12<hr></hr></td></tr><tr><td valign="top" align="left" scope="col" rowspan="1" colspan="1"><bold>Study setting:</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1"><hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">rural<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">urban<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">mixed<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">30<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">occupational<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8<hr></hr></td></tr><tr><td valign="top" align="left" scope="col" rowspan="1" colspan="1"><bold>Study type:</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1"><hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">based on ISAAC guidelines*<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">14<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">non-ISAAC guidelines<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">31<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">written questionnaire<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">39<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">video questionnaire</td><td valign="top" align="left" rowspan="1" colspan="1">6</td></tr></tbody></table><table-wrap-foot><p>*ISAAC – The International Study of Asthma and Allergies.</p></table-wrap-foot></table-wrap></sec><sec><title>Data extraction and analysis</title><p>Relevant data were extracted from retained studies and saved in Microsoft Excel file-format. All data were double extracted and sorted by country, study period, age, and their respective case number, sample size, and prevalence estimate. Extracts were grouped into data from written questionnaires or video questionnaires, both including data based on asthma diagnosis, and/or its symptoms (wheeze at rest, wheeze on exercise, nocturnal wheeze, nocturnal cough, or severe wheeze). For studies conducted on the same study site, population or cohort, the first chronologically published study was selected, with all additional data from other studies added to that of the selected paper.</p><p>For our analysis, weighted means of asthma symptoms were calculated (pooled from reported crude prevalences in individual studies) and expressed in percentages. Asthma prevalence estimates based on “current wheeze” (wheeze at rest- 12 months) have high sensitivities and specificities (<xref rid="R1" ref-type="bibr">1</xref>,<xref rid="R17" ref-type="bibr">17</xref>,<xref rid="R30" ref-type="bibr">30</xref>); we therefore applied extracted values from this in our modeling. Mean age and prevalence were plotted on bubble graphs, and the fitted curve explaining the largest proportion of variance (best fit) was applied. The equation generated determined the prevalence of asthma in Africa at midpoints of the United Nation population 5-year age-groups (for Africa) for the years 1990, 2000, and 2010.</p></sec></sec><sec sec-type="results"><title>RESULTS</title><sec><title>Systematic review</title><p>Our main search returned 790 studies; Medline (n = 246), EMBASE (n = 370), and Global Health (n = 174). After screening the titles for relevance (ie, asthma studies conducted primarily in an African population setting) and excluding duplicates, 147 studies were retained. 85 abstracts satisfied our selection criteria (ie, population-based studies providing numerical prevalence estimates of asthma). Applying the quality criteria (ie, studies with clear diagnostic criteria and survey methods), 43 studies were excluded. On hand searching reference lists of selected studies, further 3 studies were included, giving a total of 45 studies retained for the review (<xref ref-type="fig" rid="F1">Figure 1</xref>).</p><fig id="F1" fig-type="figure" position="float"><label>Figure 1</label><caption><p>Search strategy.</p></caption><graphic xlink:href="CroatMedJ_54_0519-F1"></graphic></fig></sec><sec><title>Study characteristics</title><p>The 45 retained studies (<xref rid="R12" ref-type="bibr">12</xref>,<xref rid="R19" ref-type="bibr">20</xref>,<xref rid="R31" ref-type="bibr">31</xref>-<xref rid="R73" ref-type="bibr">73</xref>) covered most parts of Africa. South Africa (11 studies) and Nigeria (8 studies) had the highest publication outputs. Ethiopia and Kenya closely followed with 6 and 5 studies respectively, while Algeria, Morocco, and Tunisia in North Africa had 4 studies each. 14 studies were based on ISAAC guidelines and 31 non-ISAAC guidelines, while 39 studies employed written questionnaires and 6 used video questionnaires (<xref ref-type="table" rid="T3">Table 3</xref>).</p><p>Most studies were conducted mainly on pediatric subjects, mostly defined as less than 15 years of age. For the age determination of subjects from most studies, birth certificates were usually employed, and in the absence of valid age-verification documents, historical landmarks were employed.</p><p>Many studies were conducted within one year (23 studies), sample sizes were mostly less than 1000 (mean 3243; median 2067), and study settings were predominantly mixed (urban and rural) (36 studies) (<xref ref-type="table" rid="T3">Table 3</xref>).</p></sec><sec><title>Prevalence estimates</title><p>We observed that the prevalence of asthma in some parts of Africa was comparable with that reported from surveys in high-income settings. From studies based on written questionnaires, “asthma ever” (cumulative prevalence of asthma) was highest in South Africa (53%, 5-12 years) in 1997 (<xref rid="R19" ref-type="bibr">20</xref>), followed by Egypt (26.5%, 11-15 years) in 2005 (<xref rid="R52" ref-type="bibr">52</xref>), Nigeria (18.4%, 15-35 years) in 1995 (<xref rid="R45" ref-type="bibr">45</xref>), and Ethiopia (16.3%, >20 years) in 1997 (<xref rid="R73" ref-type="bibr">73</xref>). The lowest prevalence was recorded in Gambia (1.9%, >15 years) in 1997 (<xref rid="R69" ref-type="bibr">69</xref>). “Current wheeze” (wheeze at rest-12-months) was consistently high in South Africa, 26.8% (13-14 years) in 1994, 23.9% (5-12 years) in 1998, and 20.3% (13-14 years) in 2003 (<xref rid="R19" ref-type="bibr">20</xref>,<xref rid="R31" ref-type="bibr">31</xref>,<xref rid="R62" ref-type="bibr">62</xref>). From studies based on video questionnaires, “current wheeze” was highest in Morocco (12.9%, 6-7 years) in 2003 (<xref rid="R31" ref-type="bibr">31</xref>) and Tanzania (12.3%, 9-10 years) in 2008 (<xref rid="R35" ref-type="bibr">35</xref>), with South Africa recording the lowest prevalence (6.5%, 6-7 years) in 1995 and 2000, respectively (<xref rid="R31" ref-type="bibr">31</xref>,<xref rid="R62" ref-type="bibr">62</xref>); there was no reported prevalence of “asthma ever” from studies based on video questionnaires. However, from all studies, the pooled crude prevalences (weighted means) for “current wheeze” was 13.2% (male 10.8%, female 13.1%, mean age 18.4 years), and “asthma ever” was 6.6% (male 6.7%, female 6.3%, mean age 22.9 years) (<xref ref-type="table" rid="T4">Table 4</xref><bold>)</bold>. We observed that the pooled crude prevalences were consistently higher among urban dwellers than rural dwellers. “Current wheeze” was 9.6% (male 12.1%, female 7.0%, mean age 19.6 years) in urban settings and 7.0% (male 5.5%, female 3.8%, mean age 17.5 years) in rural settings. “Asthma ever” prevalence was 5.9% (male 5.6%, female 3.9%, mean age 22.9 years) and 5.1% (male 4.2%, female 3.1%, mean age 17.5 years) in urban and rural dwellers, respectively (<xref ref-type="table" rid="T5">Table 5</xref>).</p><table-wrap id="T4" position="float"><label>Table 4</label><caption><p>Weighted mean prevalence (pooled crude prevalences) of asthma symptoms from all studies</p></caption><table frame="hsides" rules="groups"><col width="80" span="1"></col><col width="66" span="1"></col><col width="43" span="1"></col><col width="45" span="1"></col><col width="42" span="1"></col><col width="65" span="1"></col><col width="42" span="1"></col><col width="73" span="1"></col><col width="47" span="1"></col><col width="65" span="1"></col><thead><tr><th rowspan="2" valign="top" align="left" scope="col" colspan="1">Study type</th><th rowspan="2" valign="top" align="left" scope="col" colspan="1">Asthma indices</th><th colspan="2" valign="top" align="left" scope="colgroup" rowspan="1">Overall study characteristics<hr></hr></th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">All<hr></hr></th><th valign="top" align="left" scope="col" rowspan="1" colspan="1"><hr></hr></th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">Male<hr></hr></th><th valign="top" align="left" scope="col" rowspan="1" colspan="1"><hr></hr></th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">Female<hr></hr></th><th valign="top" align="left" scope="col" rowspan="1" colspan="1"><hr></hr></th></tr><tr><th valign="top" colspan="1" align="left" scope="colgroup" rowspan="1">study period</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">mean age (years)</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">data points</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">weighted mean % (95% confidence interval)</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">data points</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">weighted mean % (95% confidence interval)</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">data points</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">weighted mean % (95% confidence interval)</th></tr></thead><tbody><tr><td rowspan="11" valign="top" align="left" scope="row" colspan="1"><bold>Written questionnaire</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">Asthma (ever)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1993-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">22.9<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">50<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6.6 (4.7-8.6)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6.7 (2.3-11.3)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6.3 (2.3-10.1)<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Wheeze at rest (12 mo)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1993-2010<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">18.4<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">46<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.2 (11.6-14.9)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">7<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">10.8 (5.9-15.8)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">7<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.1 (7.6-18.4)<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Wheeze at rest (ever)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1993-2010<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">14.7<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">12<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">17.7 (10.7-24.6)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">9.1 (8.8-9.4)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6.2 (4.8-7.5)<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Wheeze after exercise (12 mo)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2003<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">12.3<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">23.8 (15.9-31.7)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">14.7 (4.4-33.8)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">24.6 (11.0-38.2)<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Wheeze after exercise (ever)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1993-2010<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">12.0<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">11<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8.9 (5.1-12.8)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6.5<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6.5<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Nocturnal wheeze (12 mo)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2005<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">15.4<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">4.9 (2.4-7.4)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">9.1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">10.0<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Nocturnal wheeze (ever)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">-<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">-<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">-<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">-<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">-<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">-<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">-<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">-<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Nocturnal cough (12 mo)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2005<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">14.1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">7<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">24.2 (18.3-30.0)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">24.5 (11.5-37.4)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">28.1 (13.2-43.2)<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Nocturnal cough (ever)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1993<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">10.8<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">9.3<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">10.3<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8.5<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Severe wheeze (12 mo)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1993-2003<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">25<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">4.7 (3.7-5.6)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">4<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6.0 (4.6-7.4)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">4<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3.0 (0.8-5.2)<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Severe wheeze (ever)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1993-2005<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">12.2<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8.8 (5.9-11.6)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">7.2<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5.2<hr></hr></td></tr><tr><td rowspan="10" valign="top" align="left" scope="row" colspan="1"><bold>Video questionnaire</bold></td><td valign="top" align="left" rowspan="1" colspan="1">Wheeze at rest (12 mo)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.0<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">9<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">9.7 (8.9-10.5)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">11.7<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.0<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Wheeze at rest (ever)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.2 (12.4-14.0)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">16<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">18.2<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Wheeze after exercise (12 mo)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">12.9<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">15.5 (14.7-16.3)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">19.1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">11.5<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Wheeze after exercise (ever)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.0<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">7<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">20.4 (16.9-23.8)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">28.7<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">15.4<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Nocturnal wheeze (12 mo)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.0<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5.6 (4.8-6.4)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">9.6<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5.1<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Nocturnal wheeze (ever)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.0<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8.1 (7.3-8.9)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">14.9<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">19.2<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Nocturnal cough (12 mo)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">12.9<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">17.7 (16.8-18.5)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">22.3<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">20.5<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Nocturnal cough (ever)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.0<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">7<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">24.6 (20.5-28.7)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">31.9<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">34.6<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Severe wheeze (12 mo)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1995-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13.0<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">9<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6.8 (6.1-7.6)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5.3<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3.9<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Severe wheeze (ever)</td><td valign="top" align="left" rowspan="1" colspan="1">1995-2008</td><td valign="top" align="left" rowspan="1" colspan="1">13.1</td><td valign="top" align="left" rowspan="1" colspan="1">8</td><td valign="top" align="left" rowspan="1" colspan="1">9.6 (8.7-10.3)</td><td valign="top" align="left" rowspan="1" colspan="1">1</td><td valign="top" align="left" rowspan="1" colspan="1">12.8</td><td valign="top" align="left" rowspan="1" colspan="1">1</td><td valign="top" align="left" rowspan="1" colspan="1">13.0</td></tr></tbody></table></table-wrap><table-wrap id="T5" position="float"><label>Table 5</label><caption><p>Rural and urban differences in asthma prevalences</p></caption><table frame="hsides" rules="groups"><col width="46" span="1"></col><col width="41" span="1"></col><col width="41" span="1"></col><col width="36" span="1"></col><col width="38" span="1"></col><col width="59" span="1"></col><col width="38" span="1"></col><col width="59" span="1"></col><col width="38" span="1"></col><col width="59" span="1"></col><thead><tr><th rowspan="2" valign="top" align="left" scope="col" colspan="1">Asthma indices<hr></hr></th><th rowspan="2" valign="top" align="left" scope="col" colspan="1">Study setting<hr></hr></th><th colspan="2" valign="top" align="left" scope="colgroup" rowspan="1">Study characteristics</th><th colspan="2" valign="top" align="left" scope="colgroup" rowspan="1">All</th><th colspan="2" valign="top" align="left" scope="colgroup" rowspan="1">Male</th><th colspan="2" valign="top" align="left" scope="colgroup" rowspan="1">Female</th></tr></thead><tbody><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1"><bold>study period</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1"><bold>mean age</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1"><bold>data points</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1"><bold>weighted mean % (95% confidence interval)</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1"><bold>data points</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1"><bold>weighted mean % (95% confidence interval)</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1"><bold>data points</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1"><bold>weighted mean % (95% confidence interval)</bold><hr></hr></td></tr><tr><td rowspan="2" valign="top" align="left" scope="row" colspan="1">Asthma (ever)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">Rural<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1993-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">17.5<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5.1 (7.2-9.4)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">4.2 (2.1-6.3)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3.1 (0.8-6.2)<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Urban<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1993-2010<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">22.9<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">7<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5.9 (2.9-7.9)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5.6<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3.9<hr></hr></td></tr><tr><td rowspan="2" valign="top" align="left" scope="row" colspan="1">Wheeze at rest (12 mo)</td><td valign="top" align="left" rowspan="1" colspan="1">Rural<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1993-2008<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">17.5<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">7.0 (2.5-11.5)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5.5 (1.4-12.4)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3.8 (1.5-12.9)<hr></hr></td></tr><tr><td valign="top" colspan="1" align="left" scope="row" rowspan="1">Urban</td><td valign="top" align="left" rowspan="1" colspan="1">1993-2005</td><td valign="top" align="left" rowspan="1" colspan="1">19.6</td><td valign="top" align="left" rowspan="1" colspan="1">7</td><td valign="top" align="left" rowspan="1" colspan="1">9.6 (3.9-15.2)</td><td valign="top" align="left" rowspan="1" colspan="1">1</td><td valign="top" align="left" rowspan="1" colspan="1">12.1</td><td valign="top" align="left" rowspan="1" colspan="1">1</td><td valign="top" align="left" rowspan="1" colspan="1">7</td></tr></tbody></table></table-wrap><p>Our modeling revealed an increasing prevalence of asthma in Africa. We reported 34.1 million asthma cases (12.1%; 95% confidence interval [CI] 7.2-16.9) among children <15 years, 64.9 million asthma cases (11.8%; 95% CI 7.9-15.8) among people aged <45 years, and 74.4 million cases (11.7%; 95% CI 8.2-15.3) in the total population in 1990. This increased to 41.3 million (12.9%; 95% CI 8.7-17.0) among children <15 years, 82.4 million (12.5%; 95% CI 5.9-19.1) among people aged <45 years, and 94.8 million (12.0%; 95% CI 5.0-18.8) in the total population in 2000. In 2010, we estimated a total of 49.7 million asthma cases (13.9%; 95% CI 9.6-18.3) among children <15 years, 102.9 million (13.8%; 95% CI 6.2-21.4) among people aged <45 years, and 119.3 million cases (12.8%; 95% CI 8.2-17.1) in the total population. We could not model the asthma prevalences separately for men and women due to very limited data (<xref ref-type="fig" rid="F2">Figure 2</xref> and <xref ref-type="table" rid="T6">Table 6</xref>).</p><fig id="F2" fig-type="figure" position="float"><label>Figure 2</label><caption><p>Age and prevalence distribution of asthma.</p></caption><graphic xlink:href="CroatMedJ_54_0519-F2"></graphic></fig><table-wrap id="T6" position="float"><label>Table 6</label><caption><p>Estimated asthma cases and prevalences based on current wheeze “wheeze at rest- 12 months” (based on bubble graph and United Nations population estimates for Africa)</p></caption><table frame="hsides" rules="groups"><col width="75" span="1"></col><col width="77" span="1"></col><col width="78" span="1"></col><col width="77" span="1"></col><thead><tr><th valign="top" align="left" scope="col" rowspan="1" colspan="1">Age range(years)</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">1990 estimates (000)</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">2000 estimates (000)</th><th valign="top" align="left" scope="col" rowspan="1" colspan="1">2010 estimates (000)</th></tr></thead><tbody><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">0-4<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13405.19<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">15750.21<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">18946.71<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">5-9<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">11202.33<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">13526.59<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">16412.34<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">10-14<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">9461.50<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">12041.26<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">14306.87<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">15-19<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">7889.99<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">10494.98<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">12758.85<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">20-24<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6497.60<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">8806.244<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">11373.60<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">25-29<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5391.37<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">7149.79<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">9722.56<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">30-34<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">4457.30<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5804.15<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">7946.30<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">35-39<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3648.13<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">4823.34<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">6315.71<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">40-44<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2977.33<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3998.62<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">5075.31<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">45-49<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2409.99<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3260.32<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">4208.92<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">50-54<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2009.40<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2627.89<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">3490.57<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">55-59<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1637.07<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2064.60<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2801.72<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">60-64<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1282.71<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1638.11<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2172.14<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">65-69<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">919.99<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1226.50<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1581.25<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1">70+ years<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1162.36<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">1593.05<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">2201.80<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"><bold>Asthma cases (<15 y)</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">34069.02<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">41318.06<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">49665.92<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"><bold>Estimated prevalence (<15 y)</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">0.121 (95%CI: 0.072-0.169)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">0.129 (95%CI: 0.088-0.170)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">0.139 (95%CI: 0.096-0.183)<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"><bold>Asthma cases (<45 y)</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">64930.74<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">82395.18<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">102858.20<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"><bold>Estimated prevalence (<45 y)</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">0.118 (0.079- 0.158)*<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">0.125 (0.059- 0.191)<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">0.138 (0.062- 0.210)<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"><bold>Asthma cases (all)</bold><hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">74352.26<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">94805.65<hr></hr></td><td valign="top" align="left" rowspan="1" colspan="1">119314.60<hr></hr></td></tr><tr><td valign="top" align="left" scope="row" rowspan="1" colspan="1"><bold>Estimated prevalence (all)</bold></td><td valign="top" align="left" rowspan="1" colspan="1">0.117 (0.082- 0.153)</td><td valign="top" align="left" rowspan="1" colspan="1">0.119 (0.050- 0.188)</td><td valign="top" align="left" rowspan="1" colspan="1">0.128 (0.082- 0.171)</td></tr></tbody></table><table-wrap-foot><p>*CI – confidence interval.</p></table-wrap-foot></table-wrap></sec></sec><sec sec-type="discussion"><title>DISCUSSION</title><p>This study, to our knowledge, provides the first systematic, data-derived and continent-wide estimates of asthma prevalence in Africa. Our modeling was based on published epidemiological data on “current wheeze” prevalence, which has relatively higher sensitivity and specificity (<xref rid="R1" ref-type="bibr">1</xref>,<xref rid="R17" ref-type="bibr">17</xref>,<xref rid="R30" ref-type="bibr">30</xref>), and also shows a significant association between age and asthma prevalence (<xref rid="R74" ref-type="bibr">74</xref>).</p><p>From the 2010 Institute for Health Metrics and Evaluation (IHME) global burden of disease estimates, chronic respiratory diseases overall burden has been decreasing globally and was responsible for about 4.7% of global disability adjusted life years (DALYs) in 2010, with asthma accounting for about one-fifth of this (<xref rid="R75" ref-type="bibr">75</xref>). However, the IHME reported that DALYs from asthma increased by 4.6% (from 21.5 to 22.5 million) between 1990 and 2010, while deaths decreased by 9.1% (from 0.38 to 0.34 million) over the same period globally (<xref rid="R75" ref-type="bibr">75</xref>,<xref rid="R76" ref-type="bibr">76</xref>). Concerns have been raised about the application of non-user friendly analytical methods, heavy statistical modeling, and difficulties in assessing the design methodologies and metrics used (<xref rid="R77" ref-type="bibr">77</xref>,<xref rid="R78" ref-type="bibr">78</xref>). In Africa however, the ISAAC study group, which mainly conducted epidemiological studies on asthma, reported increasing prevalences of asthma across many study settings (<xref rid="R31" ref-type="bibr">31</xref>). For example, the prevalence of “current wheeze” (wheeze at rest-12 months) among children aged 13-14 years old in South Africa increased from 16.1% to 20.3% between 1995 and 2002; Nigeria (West Africa) recorded an increase from 10.9% to 13.0%, Ethiopia (Horn of Africa) reported an increase from 6.2% to 9.1%, and Kenya (East Africa) an increase from 13.9% to 18.0% (<xref rid="R31" ref-type="bibr">31</xref>,<xref rid="R32" ref-type="bibr">32</xref>). Our pooled crude prevalences (weighted means) also reflect this increase; we reported a prevalence of current wheeze (wheeze at rest- 12-months) of 13.2% for both written and video questionnaires respectively. Furthermore, in keeping with findings from many studies, our pooled crude prevalences were consistently higher in urban than rural settings, suggesting the effects of increasing urbanization on asthma prevalence in Africa (<xref rid="R68" ref-type="bibr">68</xref>,<xref rid="R69" ref-type="bibr">69</xref>,<xref rid="R71" ref-type="bibr">71</xref>).</p><p>From our modeling, we estimated a prevalence of 11.7% for asthma, totaling over 74 million people in 1990, and our 2010 prevalence was 12.8%, about 120 million people. Public health experts have reported that increasing tobacco smoking without appropriate legislation and implementation of relevant health promotional measures in many LMIC, especially in Africa, may also be responsible for the increase in asthma and other chronic respiratory diseases’ burden in the region (<xref rid="R2" ref-type="bibr">2</xref>,<xref rid="R75" ref-type="bibr">75</xref>,<xref rid="R79" ref-type="bibr">79</xref>). In addition, the Global Burden of Asthma Report (GBAR) reported an increasing trend of asthma globally (<xref rid="R4" ref-type="bibr">4</xref>). GBAR estimated over 235 million asthma cases worldwide, and about 50 million people living with asthma in Africa in 2004, with the highest prevalence (8.1%) recorded in South Africa (<xref rid="R4" ref-type="bibr">4</xref>). The authors argue that this increasing trend is expected due to rise in atopic sensitizations, allergic conditions, and changing patterns of environmental triggers (associated with environmental smoking exposure in children, population growth, and urbanization) in Africa over the last two decades (<xref rid="R4" ref-type="bibr">4</xref>). These factors may therefore be indicative of our reported high estimates.</p><p>While we aimed to provide an improved prevalence estimate of asthma in Africa by carefully selecting high quality studies and applying simple analytical tools, there are however factors that could have affected our analysis. We thus entertain some degrees of uncertainties beyond the statistical confidence intervals generated, as variations in population settings, diagnostic criteria, sampling strategies, and effects of other health determinants (beyond age of patients) are factors that need be considered. First, the variation in diagnostic criteria was observed across many study settings, with criteria based on asthma symptoms and ISAAC scores frequently used. This could have reflected in our reported high estimates of asthma in Africa, as there is evidence suggesting the ISAAC studies could have over-estimated the prevalence of asthma in Africa, as most study centers were mainly urban (<xref rid="R1" ref-type="bibr">1</xref>); and with ISAAC studies conducted mainly in the age range 13-14 years, it may still not be representative of all age-groups and the overall population (<xref rid="R1" ref-type="bibr">1</xref>,<xref rid="R15" ref-type="bibr">15</xref>). Second, while many studies were cross-sectional population-based, we also included studies conducted in occupational settings; this is in view of reports revealing that occupational asthma contributes significantly to the global burden of chronic respiratory diseases (<xref rid="R73" ref-type="bibr">73</xref>,<xref rid="R80" ref-type="bibr">80</xref>), and as these studies reported high prevalences, we understand this could have increased our estimates, too. Third, despite included studies spreading across most parts of Africa (24 countries in total), there are still many countries in Africa that are not included in the review; this reflects data gaps in the continent, and thus the generalizability of our estimates for Africa may need to be carefully examined. In addition, our overall sample size of 187 904 (from all studies) may not be a representative sample of the general African population as there were more younger age groups. Finally, data on age- and sex-specific prevalence, including corresponding data on urban-rural settings, which are vital comparative indices in any study, were not always provided across many studies.</p><sec><title>Management of asthma and public health challenges in Africa</title><p>It is important to note that chronic respiratory disease burden, including asthma has continued to increase in Africa due to lack of appropriate response from the governments of many African countries (<xref rid="R81" ref-type="bibr">81</xref>,<xref rid="R82" ref-type="bibr">82</xref>). The national emphasis on asthma and relevant health messages have been sub-optimal, leading, in sequence, to poor awareness of the burden, low prioritization, inadequate staffing and resources, and very low budget allocation. In fact, budget allocation in many African countries mainly targets infectious diseases; funds have been greatly biased toward HIV/AIDS, malaria, and tuberculosis, as these are the main government priorities (<xref rid="R28" ref-type="bibr">28</xref>,<xref rid="R83" ref-type="bibr">83</xref>). The GBAR authors reported that poor government allocation of funds for asthma remained an important factor responsible for limited access to asthma medications, emergency health care, and other related health services in Africa (<xref rid="R4" ref-type="bibr">4</xref>). In addition, with tobacco companies still supporting many African governments, tobacco products’ sales have increased, and government funds have remained unavailable for research on asthma, as researches aimed at improving management of asthma may be against tobacco sales and consumption (<xref rid="R22" ref-type="bibr">22</xref>,<xref rid="R69" ref-type="bibr">69</xref>). This has greatly resulted in increased smoking (without a counter legislation) and a growing burden of asthma, especially among children in Africa over the last two decades (<xref rid="R5" ref-type="bibr">5</xref>,<xref rid="R10" ref-type="bibr">10</xref>). For example, Mackay et al reported that a comprehensive smoke free-legislation was important to achieving reduction in the asthma incidence among people without occupational exposure to environmental tobacco smoke; a reduction of 18.2% per year was observed in hospital admissions in Scotland among children <15 years in 2009 compared to a mean increase of admission of 5.2% per year before implementation of the legislation in 2006 (<xref rid="R84" ref-type="bibr">84</xref>)</p><p>The diagnosis and treatment of asthma still remains a major challenge in Africa (<xref rid="R16" ref-type="bibr">16</xref>). Distinguishing asthma from other obstructive airway diseases has posed a clinical challenge to clinicians (<xref rid="R3" ref-type="bibr">3</xref>,<xref rid="R5" ref-type="bibr">5</xref>). Epidemiological data have shown that while asthma presents in episodes, usually among non-smokers and onsets before 40 years, chronic obstructive pulmonary disease (COPD) is associated with smokers, people aged 40 years and above, with symptoms being persistent and progressive (<xref rid="R1" ref-type="bibr">1</xref>). In practice, asthmatics who smoke may have non-reversible airflow limitation, and some COPD patients may be non-smokers having reversible airflow limitation (<xref rid="R85" ref-type="bibr">85</xref>). In addition, many African countries have no standard protocols for the diagnosis and management of asthma (<xref rid="R22" ref-type="bibr">22</xref>); where these are available, guidelines are rarely implemented, and for the few implemented guidelines, treatment often does not reach the rural population that is mostly affected (<xref rid="R26" ref-type="bibr">26</xref>). In fact, inaccessibility of health care services in many rural and resource-poor African settings often gives traditional healers undue significance in the management of many chronic diseases (<xref rid="R22" ref-type="bibr">22</xref>). The non-availability and unaffordability of inhaled steroids, and the relative non-adherence to these medications (when available) have also had large negative impact on the response to asthma in Africa. Studies have shown that about 50% of people adhere to prescribed medications (<xref rid="R26" ref-type="bibr">26</xref>,<xref rid="R86" ref-type="bibr">86</xref>), with reasons for non-adherence including side-effects, dosing frequencies, and lack of patient education on their illness, need for treatment, and how to take medications (<xref rid="R87" ref-type="bibr">87</xref>). There are also inherent socio-cultural misconceptions and individual values that need to be understood and addressed toward improving the acceptance and use of asthma medications (<xref rid="R88" ref-type="bibr">88</xref>), with continual public awareness and education being advocated, especially among parents of children with asthma (<xref rid="R5" ref-type="bibr">5</xref>,<xref rid="R88" ref-type="bibr">88</xref>).</p><p>Asthma is an important and increasing public health problem in Africa which receives inadequate priority and attention. With increasing urbanization, population aging, and adoption of western lifestyles in many African settings, these trends are set to continue in the near future. There is a need to identify and prioritize feasible strategies that can be adopted to promote the implementation of effective interventions that will address this increasing burden in Africa. There is also a need for African national governments to also consider effects of associated risk factors in public health policy planning on this topic with a focus on reducing environmental triggers, placing restrictions on tobacco adverts, and appropriately educating health care personnel and the public on the management of the disease and the preventive measures.</p></sec></sec></body><back><ack><p><bold>Funding</bold> None.</p><p><bold>Ethical approval</bold> Not required.</p><p><bold>Authorship declaration</bold> All co-authors designed and conducted the study and contributed to the writing of the paper.</p><p><bold>Competing interests</bold> All authors have completed the Unified Competing Interest form at <italic><ext-link ext-link-type="uri" xlink:href="http://www.icmje.org/coi_disclosure.pdf">www.icmje.org/coi_disclosure.pdf</ext-link></italic> (available on request from the corresponding author) and declare: no support from any organization for the submitted work; no financial relationships with any organizations that might have an interest in the submitted work in the previous 3 years; no other relationships or activities that could appear to have influenced the submitted work.</p></ack><ref-list><title>References</title><ref id="R1"><label>1</label><mixed-citation publication-type="book">IUATLD. 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