Asthma is a chronic disease of the airways that leads to breathing difficulty and sometimes death: the condition affects about 235 million people worldwide, especially children. Scientists still do not know exactly what causes asthma, but studies in Europe and North America suggest that individuals born or raised in rural areas are less likely to be affected. However, few studies have examined asthma in African countries, where urbanization is often quickly increasing. Examining the factors associated with the disease as more people move to cities may provide new clues about how asthma emerges, and how to prevent it.

To this end, Mpairwe et al. conducted a study with over 1,670 schoolchildren in Uganda. Those born or raised in rural areas were least likely to have asthma, but the risk doubled among children from small towns, and tripled in those born or who grew up in the city. Children whose parents had a higher education and socioeconomic status had the highest asthma risk, but more work is required to understand why this is the case.

The study by Mpairwe et al. is the first step towards identifying environmental and lifestyle factors associated with increased asthma risk in Africa. Further studies may help scientists to understand how beginning life in a more urban area plays a role in the development of the disease.

Asthma is estimated to affect more than 235 million people globally, and is the most common non-communicable condition among children (World Health Organisation, 2017). In Africa, the prevalence of asthma appears to be increasing (Asher et al., 2006; Addo-Yobo et al., 2007; van Gemert et al., 2011; Zar et al., 2007; Lawson et al., 2017), particularly in urban areas (Addo-Yobo et al., 2007; Morgan et al., 2018), but the causes of this increase are not fully understood. Moreover, asthma has various phenotypes which may have different aetiologies (Lötvall et al., 2011). Asthma risk factors appear to vary internationally, and to differ between high-income countries (HICs) and low-and-middle income countries (LMICs) (Douwes and Pearce, 2002).

There is little previously published data on asthma risk factors from Africa. The few studies reported have suggested that current residence in urban areas is associated with a higher risk of asthma than rural residence in Africa (Botha et al., 2019; Addo-Yobo et al., 2001) and other LMICs (Robinson et al., 2011; Gaviola et al., 2016). The association between helminth infections and asthma has been investigated in Africa and other LMICs, but the findings have been inconsistent across studies (Leonardi-Bee et al., 2006; Mpairwe and Amoah, 2019). Other risk factors for asthma in Africa and other LMICs, similar to those in HICs, include maternal smoking (Ayuk et al., 2018; Arrais et al., 2019), maternal history of asthma (Nantanda et al., 2013), childhood atopic sensitisation (Addo-Yobo et al., 2001; Nyembue et al., 2012) and history of allergy (Nantanda et al., 2013; Mehanna et al., 2018). Previous reports suggest no association between biomass fuels and asthma risk (Thacher et al., 2013; Oluwole et al., 2017a), but increased asthma symptoms (Oluwole et al., 2017a; Oluwole et al., 2017b). Unlike in HICs, higher parental education and socioeconomic status has been associated with asthma among children in Africa (Addo-Yobo et al., 2007; Nantanda et al., 2013; Wolff et al., 2012).

We undertook a case-control study among schoolchildren in an urban area in Uganda, to investigate the main risk factors for asthma and the patterns of allergic sensitisation.

We found a step-wise increase in asthma risk according to the child’s area of residence at the time of birth and in their first five years of life. Children born and raised in rural areas had the lowest risk, children born and raised in small towns had a 2-fold increase in risk, while children born and raised in the city had a 3-fold increase in asthma risk. This is the first study in Africa to show such a strong gradient in asthma risk by place of birth. Previous studies have been mostly cross-sectional and conducted in either rural or urban settings, and therefore focusing on current residence; these have shown that the prevalence of asthma is lower among rural residents compared to urban residents (Lawson et al., 2017; Morgan et al., 2018; Botha et al., 2019).

Our findings confirm that the area where a child is born (usually the same as the area where the mother was resident during pregnancy) is important for asthma risk. Indeed, we found that when children moved to other environments, they carried with them the asthma risk related to their area of residence in pregnancy: children born in urban areas who were subsequently raised in rural areas still had a 2-fold increase in asthma risk, similar to their counterparts born and raised in urban areas. These findings are comparable to observations from Europe showing that children born on a farm (usually in rural areas) have a lower risk of asthma in later life, even when they subsequently moved to urban areas (Leynaert et al., 2001), and that children who migrated to Europe after age five had a lower prevalence of asthma, similar to their country of origin, than children who were either born in Europe or migrated before the age of five (Migliore et al., 2007; Kuehni et al., 2007). However, there are also studies that show increased risk of wheezing and allergy among children following migration (Rodriguez et al., 2017; Stein et al., 2016). Unlike studies from Europe and North America which have reported a lower risk of asthma for children born or raised on farms (Genuneit, 2012; Timm et al., 2015), our study found no association between asthma risk and exposure to farm animals either during pregnancy or in early life. We hypothesise that this may be due to ubiquitous farm animal exposure due to subsistence farming, a widespread practice in Uganda, even in towns.

Our observation that children with asthma were more likely to have parents with tertiary education and to use gas or electricity for indoor cooking (as opposed to charcoal stoves) has been made by an earlier study in Uganda (Nantanda et al., 2013). Similarly, our finding that children with asthma reported the highest frequency of ‘trucks passing on the street near their home’ has been reported elsewhere (Sharma and Banga, 2007; Shirinde et al., 2014; Venn et al., 2005). We suggest that these factors are proxy measures of a higher socio-economic status of asthma cases and of urbanicity, consistent with findings from other LMICs that have found a higher prevalence of asthma among children (and adults) in urban than rural areas (Morgan et al., 2018; Robinson et al., 2011; Gaviola et al., 2016). However, our findings contradict those from HICs in which asthma is associated with lower parental education (Lewis et al., 2017) and socio-economic status (Akinbami et al., 2011). This suggests that there may be similarities in lifestyle and environmental factors between the highly educated and high socio-economic status families in LMICs with the low educated and low socio-economic status families in HICs, which increase asthma risk, and therefore require further investigation.

Although children with asthma were more likely to be sensitised to allergens than controls, the pattern of allergic sensitisation was similar among cases and controls; majorly sensitised to house-dust mites and cockroach, and least sensitised to peanut, cat, pollen and mould. This SPT response pattern was similar to other studies from Africa (Nyembue et al., 2012; Mbatchou Ngahane et al., 2016), but different from Europe where the main allergens are dust mite, cat and pollen (Bousquet et al., 2007).

Although maternal smoking is a known risk factor for childhood asthma (Silvestri et al., 2015), our study found no association between maternal smoking and asthma. We attribute this to the low prevalence of smoking in this population, by the mothers during pregnancy (2.5%) and by any household members currently (11%). The lack of association between asthma and indoor cooking with biomass fuels in this study is consistent with other studies from Africa (Thacher et al., 2013; Oluwole et al., 2017a). Indeed, this is consistent with the general pattern of lower risk of asthma in rural areas (where biomass fuel use is highest) than urban areas.

We found an inverse association between asthma and current infection with any helminths, particularly T. trichuria. However, the association between asthma and current infections in Africa has been inconsistent across studies (Mpairwe and Amoah, 2019). What was novel in this study is that we also collected data on history of using de-worming medication in the last 12 months. We found that children with asthma were more likely to have used de-worming medication more than twice in the last 12 months compared to controls, and this was de-worming with albendazole (for geo-helminths) not with praziquantel (for schistosomiasis). This implies that the inverse association we noted between asthma and helminths may be partly explained by increased de-worming among children with asthma. The current de-worming schedule in this age-group in Uganda includes mass-deworming in schools, bi-annually for albendazole and once a year for praziquantel. We did not establish whether the additional de-worming was self-medicated or prescribed by medical workers.

We found that children with asthma were less likely to have a BCG scar, but there was no association with tuberculin skin test at enrolment. In Uganda, BCG vaccination is routinely given at birth. A lack of BCG scar does not mean the vaccine was not administered, but may indicate differences in immune responses among children who will eventually develop asthma. Alternatively, BCG vaccination may be protective against asthma, as suggested by previous studies (El-Zein et al., 2010).

The other important risk factors for asthma, that have been previously described, included parental history of allergic disease (Lim et al., 2010), a child’s atopy status and concomitant other allergic disease (Bao et al., 2017). The strength of this study was to demonstrate that having a combination of any two of these known risk factors for asthma had an additive effect on asthma risk, and that this risk also increased in relation to area of residence in early life, with an increasing rural-town-city gradient. This gradient and independent effects of parental education provide strong evidence for the role of environmental and lifestyle factors associated with urbanisation that are responsible for the increasing asthma risk in urban areas. More investigations are required to identify the specific factors, in order to design interventions to modify them so as to prevent the establishment of asthma risk in early life.

This study had limitations inherent to all case-control studies, such as potential recall bias, selection bias and confounding. We minimised recall bias by focusing on major early life events that a parent was likely to remember. It was re-assuring to note a strong correlation between the recalled events and objective measures such as SPT. We minimised the selection bias for controls by randomly selecting controls from the same class register where the cases were obtained, and by randomly selecting the 400 participants for the asIgE assay. We minimised confounding by adjusting for measured confounders in all our analyses, but cannot rule out the possible role of unmeasured confounders. Finally, a large number of potential participants were not included in this study, mostly because they were in the boarding school section and were unable to contact their parents/guardians in time to attend the parents’ meeting (to provide consent). We do not have information on whether these parents were more likely to reside in rural areas or the city, where the asthma risk is either lower or higher than the town where this study was conducted, respectively. Our results may or may not be generalisable to similar urban areas in Uganda and Sub-sahara Africa.

Our findings support the concept that environmental factors during early life may influence the risk of development of NCDs in later life (Fleming et al., 2018). However, our study does not involve information sufficiently detailed to identify whether exposures in utero or in early life are most relevant. Further research in this setting is required to investigate these hypotheses, and this would have important implications for the life course approach in the prevention of asthma globally.

Data is available on request via https://datacompass.lshtm.ac.uk/1369/. To gain access to the data please complete the application process via the website. Requests will be reviewed and assessed by the corresponding author, in consultation with the LSHTM's Research Data Manager and relevant LSHTM staff members responsible for research governance and data protection. Applications will be evaluated on the basis of their compatibility with the study's research objectives and the ability to provide de-identified data sufficient to meet the intended purpose, without breaching participant confidentiality or the study's ethical and legal commitments. Successful applicants will be asked to sign a Data Transfer Agreement prior to being provided with the data.

1. 1. Webb E
   2. Mpairwe H

   (2019) London School of Hygiene & Tropical Medicine (LSHTM) Data Compass

   SONA project - Asthma risk factors data.

   https://doi.org/10.17037/DATA.00001369

1. 1. Aarø LE
   2. Flisher AJ
   3. Kaaya S
   4. Onya H
   5. Namisi FS
   6. Wubs A

   (2009) Parental education as an Indicator of socioeconomic status: improving quality of data by requiring consistency across measurement occasions

   Scandinavian Journal of Public Health 37:16–27.

   https://doi.org/10.1177/1403494808086917

   • PubMed
   • Google Scholar
2. 1. Addo-Yobo EO
   2. Custovic A
   3. Taggart SC
   4. Craven M
   5. Bonnie B
   6. Woodcock A

   (2001) Risk factors for asthma in urban Ghana

   Journal of Allergy and Clinical Immunology 108:363–368.

   https://doi.org/10.1067/mai.2001.117464

   • PubMed
   • Google Scholar
3. 1. Addo-Yobo EO
   2. Woodcock A
   3. Allotey A
   4. Baffoe-Bonnie B
   5. Strachan D
   6. Custovic A

   (2007) Exercise-induced bronchospasm and atopy in Ghana: two surveys ten years apart

   PLOS Medicine 4:e70.

   https://doi.org/10.1371/journal.pmed.0040070

   • PubMed
   • Google Scholar
4. 1. Akinbami LJ
   2. Moorman JE
   3. Liu X

   (2011)

   Asthma prevalence, health care use, and mortality: united states, 2005-2009

   National Health Statistics Reports 32:1–14.

   • Google Scholar
5. 1. Arrais M
   2. Lulua O
   3. Quifica F
   4. Rosado-Pinto J
   5. Gama JMR
   6. Taborda-Barata L

   (2019) Prevalence of asthma, allergic rhinitis and eczema in 6-7-year-old schoolchildren from Luanda, Angola

   Allergologia Et Immunopathologia 47:523–534.

   https://doi.org/10.1016/j.aller.2018.12.002

   • PubMed
   • Google Scholar
6. 1. Asher MI
   2. Keil U
   3. Anderson HR
   4. Beasley R
   5. Crane J
   6. Martinez F
   7. Mitchell EA
   8. Pearce N
   9. Sibbald B
   10. Stewart AW

   (1995) International study of asthma and allergies in childhood (ISAAC): rationale and methods

   European Respiratory Journal 8:483–491.

   https://doi.org/10.1183/09031936.95.08030483

   • PubMed
   • Google Scholar
7. 1. Asher MI
   2. Montefort S
   3. Björkstén B
   4. Lai CKW
   5. Strachan DP
   6. Weiland SK
   7. Williams H

   (2006) Worldwide time trends in the prevalence of symptoms of asthma, allergic rhinoconjunctivitis, and eczema in childhood: isaac phases one and three repeat multicountry cross-sectional surveys

   The Lancet 368:733–743.

   https://doi.org/10.1016/S0140-6736(06)69283-0

   • Google Scholar
8. 1. Ayuk AC
   2. Ramjith J
   3. Zar HJ

   (2018) Environmental risk factors for asthma in 13-14 year old african children

   Pediatric Pulmonology 53:1475–1484.

   https://doi.org/10.1002/ppul.24162

   • PubMed
   • Google Scholar
9. 1. Bao Y
   2. Chen Z
   3. Liu E
   4. Xiang L
   5. Zhao D
   6. Hong J

   (2017) Risk factors in preschool children for predicting asthma during the preschool age and the early school age: a systematic review and Meta-Analysis

   Current Allergy and Asthma Reports 17:85.

   https://doi.org/10.1007/s11882-017-0753-7

   • PubMed
   • Google Scholar
10. 1. Botha M
    2. Basera W
    3. Facey-Thomas HE
    4. Gaunt B
    5. Genuneit J
    6. Gray CL
    7. Kiragu W
    8. Ramjith J
    9. Watkins A
    10. Levin ME

    (2019) Nutrition and allergic diseases in urban and rural communities from the south african food allergy cohort

    Pediatric Allergy and Immunology : Official Publication of the European Society of Pediatric Allergy and Immunology 30:511–521.

    https://doi.org/10.1111/pai.13058

    • PubMed
    • Google Scholar
11. 1. Bousquet PJ
    2. Chinn S
    3. Janson C
    4. Kogevinas M
    5. Burney P
    6. Jarvis D
    7. European Community Respiratory Health Survey I

    (2007) Geographical variation in the prevalence of positive skin tests to environmental aeroallergens in the european community respiratory health survey I

    Allergy 62:301–309.

    https://doi.org/10.1111/j.1398-9995.2006.01293.x

    • PubMed
    • Google Scholar
12. 1. Douwes J
    2. Pearce N

    (2002) Asthma and the westernization 'package'

    International Journal of Epidemiology 31:1098–1102.

    https://doi.org/10.1093/ije/31.6.1098

    • PubMed
    • Google Scholar
13. 1. Eifan AO
    2. Akkoc T
    3. Ozdemir C
    4. Bahceciler NN
    5. Barlan IB

    (2009) No association between tuberculin skin test and atopy in a Bacillus Calmette-Guérin vaccinated birth cohort

    Pediatric Allergy and Immunology 20:545–550.

    https://doi.org/10.1111/j.1399-3038.2008.00846.x

    • Google Scholar
14. 1. El-Zein M
    2. Parent ME
    3. Benedetti A
    4. Rousseau MC

    (2010) Does BCG vaccination protect against the development of childhood asthma? A systematic review and meta-analysis of epidemiological studies

    International Journal of Epidemiology 39:469–486.

    https://doi.org/10.1093/ije/dyp307

    • PubMed
    • Google Scholar
15. 1. Fleming TP
    2. Watkins AJ
    3. Velazquez MA
    4. Mathers JC
    5. Prentice AM
    6. Stephenson J
    7. Barker M
    8. Saffery R
    9. Yajnik CS
    10. Eckert JJ
    11. Hanson MA
    12. Forrester T
    13. Gluckman PD
    14. Godfrey KM

    (2018) Origins of lifetime health around the time of conception: causes and consequences

    The Lancet 391:1842–1852.

    https://doi.org/10.1016/S0140-6736(18)30312-X

    • Google Scholar
16. 1. Gaviola C
    2. Miele CH
    3. Wise RA
    4. Gilman RH
    5. Jaganath D
    6. Miranda JJ
    7. Bernabe-Ortiz A
    8. Hansel NN
    9. Checkley W
    10. CRONICAS Cohort Study Group

    (2016) Urbanisation but not biomass fuel smoke exposure is associated with asthma prevalence in four resource-limited settings

    Thorax 71:154–160.

    https://doi.org/10.1136/thoraxjnl-2015-207584

    • PubMed
    • Google Scholar
17. 1. Genuneit J

    (2012) Exposure to farming environments in childhood and asthma and wheeze in rural populations: a systematic review with meta-analysis

    Pediatric Allergy and Immunology 23:509–518.

    https://doi.org/10.1111/j.1399-3038.2012.01312.x

    • PubMed
    • Google Scholar
18. 1. Greenland S
    2. Daniel R
    3. Pearce N

    (2016) Outcome modelling strategies in epidemiology: traditional methods and basic alternatives

    International Journal of Epidemiology 45:565–575.

    https://doi.org/10.1093/ije/dyw040

    • PubMed
    • Google Scholar
19. 1. Greenland S
    2. Pearce N

    (2015) Statistical foundations for model-based adjustments

    Annual Review of Public Health 36:89–108.

    https://doi.org/10.1146/annurev-publhealth-031914-122559

    • PubMed
    • Google Scholar
20. 1. Heinzerling L
    2. Mari A
    3. Bergmann KC
    4. Bresciani M
    5. Burbach G
    6. Darsow U
    7. Durham S
    8. Fokkens W
    9. Gjomarkaj M
    10. Haahtela T
    11. Bom AT
    12. Wöhrl S
    13. Maibach H
    14. Lockey R

    (2013) The skin prick test - European standards

    Clinical and Translational Allergy 3:3.

    https://doi.org/10.1186/2045-7022-3-3

    • PubMed
    • Google Scholar
21. 1. Hoyte FCL
    2. Gross LM
    3. Katial RK

    (2018) Exhaled nitric oxide: an update

    Immunology and Allergy Clinics of North America 38:573–585.

    https://doi.org/10.1016/j.iac.2018.06.001

    • PubMed
    • Google Scholar
22. 1. Katz N
    2. Chaves A
    3. Pellegrino J

    (1972)

    A simple device for quantitative stool thick-smear technique in schistosomiasis mansoni

    Revista Do Instituto De Medicina Tropical De Sao Paulo 14:397–400.

    • PubMed
    • Google Scholar
23. 1. Kuehni CE
    2. Strippoli MP
    3. Low N
    4. Silverman M

    (2007) Asthma in young south Asian women living in the United Kingdom: the importance of early life

    Clinical & Experimental Allergy 37:47–53.

    https://doi.org/10.1111/j.1365-2222.2006.02627.x

    • PubMed
    • Google Scholar
24. 1. Lawson JA
    2. Rennie DC
    3. Cockcroft DW
    4. Dyck R
    5. Afanasieva A
    6. Oluwole O
    7. Afsana J

    (2017) Childhood asthma, asthma severity indicators, and related conditions along an urban-rural gradient: a cross-sectional study

    BMC Pulmonary Medicine 17:4.

    https://doi.org/10.1186/s12890-016-0355-5

    • PubMed
    • Google Scholar
25. 1. Leonardi-Bee J
    2. Pritchard D
    3. Britton J

    (2006) Asthma and current intestinal parasite infection: systematic review and meta-analysis

    American Journal of Respiratory and Critical Care Medicine 174:514–523.

    https://doi.org/10.1164/rccm.200603-331OC

    • PubMed
    • Google Scholar
26. 1. Lewis KM
    2. Ruiz M
    3. Goldblatt P
    4. Morrison J
    5. Porta D
    6. Forastiere F
    7. Hryhorczuk D
    8. Zvinchuk O
    9. Saurel-Cubizolles MJ
    10. Lioret S
    11. Annesi-Maesano I
    12. Vrijheid M
    13. Torrent M
    14. Iniguez C
    15. Larranaga I
    16. Harskamp-van Ginkel MW
    17. Vrijkotte TGM
    18. Klanova J
    19. Svancara J
    20. Barross H
    21. Correia S
    22. Jarvelin MR
    23. Taanila A
    24. Ludvigsson J
    25. Faresjo T
    26. Marmot M
    27. Pikhart H
    28. European Community Respiratory Health Survey

    (2017) Mother's education and offspring asthma risk in 10 European cohort studies

    European Journal of Epidemiology 32:797–805.

    https://doi.org/10.1007/s10654-017-0309-0

    • PubMed
    • Google Scholar
27. 1. Leynaert B
    2. Neukirch C
    3. Jarvis D
    4. Chinn S
    5. Burney P
    6. Neukirch F

    (2001) Does living on a farm during childhood protect against asthma, allergic rhinitis, and atopy in adulthood?

    American Journal of Respiratory and Critical Care Medicine 164:1829–1834.

    https://doi.org/10.1164/ajrccm.164.10.2103137

    • PubMed
    • Google Scholar
28. 1. Lim RH
    2. Kobzik L
    3. Dahl M

    (2010) Risk for asthma in offspring of asthmatic mothers versus fathers: a meta-analysis

    PLOS ONE 5:e10134.

    https://doi.org/10.1371/journal.pone.0010134

    • PubMed
    • Google Scholar
29. 1. Lötvall J
    2. Akdis CA
    3. Bacharier LB
    4. Bjermer L
    5. Casale TB
    6. Custovic A
    7. Lemanske RF
    8. Wardlaw AJ
    9. Wenzel SE
    10. Greenberger PA

    (2011) Asthma endotypes: a new approach to classification of disease entities within the asthma syndrome

    Journal of Allergy and Clinical Immunology 127:355–360.

    https://doi.org/10.1016/j.jaci.2010.11.037

    • PubMed
    • Google Scholar
30. 1. Mbatchou Ngahane BH
    2. Noah D
    3. Nganda Motto M
    4. Mapoure Njankouo Y
    5. Njock LR

    (2016) Sensitization to common aeroallergens in a population of young adults in a sub-Saharan africa setting: a cross-sectional study

    Allergy, Asthma & Clinical Immunology 12:1.

    https://doi.org/10.1186/s13223-015-0107-8

    • Google Scholar
31. 1. Mehanna N
    2. Mohamed N
    3. Wordofa M
    4. Abera D
    5. Mesfin A
    6. Wolde M
    7. Desta K
    8. Tsegaye A
    9. Taye B

    (2018) Allergy-related disorders (ARDs) among ethiopian primary school-aged children: prevalence and associated risk factors

    PLOS ONE 13:e0204521.

    https://doi.org/10.1371/journal.pone.0204521

    • PubMed
    • Google Scholar
32. 1. Migliore E
    2. Pearce N
    3. Bugiani M
    4. Galletti G
    5. Biggeri A
    6. Bisanti L
    7. Caranci N
    8. Dell'Orco V
    9. De Sario M
    10. Sestini P
    11. Piffer S
    12. Viegi G
    13. Forastiere F
    14. Galassi C
    15. Ciccone G
    16. SIDRIA-2 Collaborative Group

    (2007) Prevalence of respiratory symptoms in migrant children to Italy: the results of SIDRIA-2 study

    Allergy 62:293–300.

    https://doi.org/10.1111/j.1398-9995.2007.01238.x

    • PubMed
    • Google Scholar
33. 1. Morgan BW
    2. Siddharthan T
    3. Grigsby MR
    4. Pollard SL
    5. Kalyesubula R
    6. Wise RA
    7. Kirenga B
    8. Checkley W

    (2018) Asthma and allergic disorders in Uganda: a Population-Based study across urban and rural settings

    The Journal of Allergy and Clinical Immunology: In Practice 6:1580–1587.

    https://doi.org/10.1016/j.jaip.2017.11.032

    • Google Scholar
34. 1. Mpairwe H
    2. Muhangi L
    3. Ndibazza J
    4. Tumusiime J
    5. Muwanga M
    6. Rodrigues LC
    7. Elliott AM

    (2008) Skin prick test reactivity to common allergens among women in Entebbe, Uganda

    Transactions of the Royal Society of Tropical Medicine and Hygiene 102:367–373.

    https://doi.org/10.1016/j.trstmh.2008.01.017

    • PubMed
    • Google Scholar
35. 1. Mpairwe H
    2. Amoah AS

    (2019) Parasites and allergy: Observations from Africa

    Parasite Immunology 41:e12589.

    https://doi.org/10.1111/pim.12589

    • Google Scholar
36. 1. Nantanda R
    2. Ostergaard MS
    3. Ndeezi G
    4. Tumwine JK

    (2013) Factors associated with asthma among under-fives in Mulago hospital, Kampala Uganda: a cross sectional study

    BMC Pediatrics 13:141.

    https://doi.org/10.1186/1471-2431-13-141

    • PubMed
    • Google Scholar
37. 1. Nkurunungi G
    2. Lutangira JE
    3. Lule SA
    4. Akurut H
    5. Kizindo R
    6. Fitchett JR
    7. Kizito D
    8. Sebina I
    9. Muhangi L
    10. Webb EL
    11. Cose S
    12. Elliott AM

    (2012) Determining Mycobacterium tuberculosis infection among BCG-immunised ugandan children by T-SPOT.TB and tuberculin skin testing

    PLOS ONE 7:e47340.

    https://doi.org/10.1371/journal.pone.0047340

    • PubMed
    • Google Scholar
38. 1. Nyembue TD
    2. Jorissen M
    3. Hellings PW
    4. Muyunga C
    5. Kayembe JM

    (2012) Prevalence and determinants of allergic diseases in a congolese population

    International Forum of Allergy & Rhinology 2:285–293.

    https://doi.org/10.1002/alr.21017

    • PubMed
    • Google Scholar
39. 1. Obihara CC
    2. Kimpen JLL
    3. Gie RP
    4. Lill SW
    5. Hoekstra MO
    6. Marais BJ
    7. Schaaf HS
    8. Lawrence K
    9. Potter PC
    10. Bateman ED
    11. Lombard CJ
    12. Beyers N

    (2006) Mycobacterium tuberculosis infection may protect against allergy in a tuberculosis endemic area

    Clinical Experimental Allergy 36:70–76.

    https://doi.org/10.1111/j.1365-2222.2005.02408.x

    • Google Scholar
40. 1. Oluwole O
    2. Arinola GO
    3. Huo D
    4. Olopade CO

    (2017a) Household biomass fuel use, asthma symptoms severity, and asthma underdiagnosis in rural schoolchildren in Nigeria: a cross-sectional observational study

    BMC Pulmonary Medicine 17:3.

    https://doi.org/10.1186/s12890-016-0352-8

    • PubMed
    • Google Scholar
41. 1. Oluwole O
    2. Arinola GO
    3. Huo D
    4. Olopade CO

    (2017b) Biomass fuel exposure and asthma symptoms among rural school children in Nigeria

    Journal of Asthma 54:347–356.

    https://doi.org/10.1080/02770903.2016.1227334

    • Google Scholar
42. 1. Robinson CL
    2. Baumann LM
    3. Romero K
    4. Combe JM
    5. Gomez A
    6. Gilman RH
    7. Cabrera L
    8. Gonzalvez G
    9. Hansel NN
    10. Wise RA
    11. Barnes KC
    12. Breysse PN
    13. Checkley W

    (2011) Effect of urbanisation on asthma, allergy and airways inflammation in a developing country setting

    Thorax 66:1051–1057.

    https://doi.org/10.1136/thx.2011.158956

    • PubMed
    • Google Scholar
43. 1. Rodriguez A
    2. Vaca MG
    3. Chico ME
    4. Rodrigues LC
    5. Barreto ML
    6. Cooper PJ

    (2017) Rural to urban migration is associated with increased prevalence of childhood wheeze in a Latin-American city

    BMJ Open Respiratory Research 4:e000205.

    https://doi.org/10.1136/bmjresp-2017-000205

    • PubMed
    • Google Scholar
44. 1. Sharma SK
    2. Banga A

    (2007) Prevalence and risk factors for wheezing in children from rural Areas of north India

    Allergy and Asthma Proceedings 28:647–653.

    https://doi.org/10.2500/aap.2007.28.3059

    • PubMed
    • Google Scholar
45. 1. Shirinde J
    2. Wichmann J
    3. Voyi K

    (2014) Association between wheeze and selected air pollution sources in an air pollution priority area in South Africa: a cross-sectional study

    Environmental Health 13:32.

    https://doi.org/10.1186/1476-069X-13-32

    • PubMed
    • Google Scholar
46. 1. Silvestri M
    2. Franchi S
    3. Pistorio A
    4. Petecchia L
    5. Rusconi F

    (2015) Smoke exposure, wheezing, and asthma development: a systematic review and meta-analysis in unselected birth cohorts

    Pediatric Pulmonology 50:353–362.

    https://doi.org/10.1002/ppul.23037

    • PubMed
    • Google Scholar
47. 1. Stein M
    2. Greenberg Z
    3. Boaz M
    4. Handzel ZT
    5. Meshesha MK
    6. Bentwich Z

    (2016) The role of helminth infection and environment in the development of allergy: a prospective study of Newly-Arrived ethiopian immigrants in israel

    PLOS Neglected Tropical Diseases 10:e0004208.

    https://doi.org/10.1371/journal.pntd.0004208

    • PubMed
    • Google Scholar
48. 1. Thacher JD
    2. Emmelin A
    3. Madaki AJ
    4. Thacher TD

    (2013) Biomass fuel use and the risk of asthma in nigerian children

    Respiratory Medicine 107:1845–1851.

    https://doi.org/10.1016/j.rmed.2013.09.009

    • PubMed
    • Google Scholar
49. 1. Timm S
    2. Frydenberg M
    3. Janson C
    4. Campbell B
    5. Forsberg B
    6. Gislason T
    7. Holm M
    8. Jogi R
    9. Omenaas E
    10. Sigsgaard T
    11. Svanes C
    12. Schlünssen V

    (2015) The Urban-Rural gradient in asthma: a Population-Based study in northern europe

    International Journal of Environmental Research and Public Health 13:93.

    https://doi.org/10.3390/ijerph13010093

    • Google Scholar
50. 1. van Gemert F
    2. van der Molen T
    3. Jones R
    4. Chavannes N

    (2011) The impact of asthma and COPD in sub-Saharan Africa

    Primary Care Respiratory Journal 20:240–248.

    https://doi.org/10.4104/pcrj.2011.00027

    • PubMed
    • Google Scholar
51. 1. Venn A
    2. Yemaneberhan H
    3. Lewis S
    4. Parry E
    5. Britton J

    (2005) Proximity of the home to roads and the risk of wheeze in an ethiopian population

    Occupational and Environmental Medicine 62:376–380.

    https://doi.org/10.1136/oem.2004.017228

    • PubMed
    • Google Scholar
52. 1. von Elm E
    2. Altman DG
    3. Egger M
    4. Pocock SJ
    5. Gøtzsche PC
    6. Vandenbroucke JP
    7. STROBE Initiative

    (2014) The strengthening the reporting of observational studies in epidemiology (STROBE) Statement: guidelines for reporting observational studies

    International Journal of Surgery 12:1495–1499.

    https://doi.org/10.1016/j.ijsu.2014.07.013

    • PubMed
    • Google Scholar
53. 1. Wolff PT
    2. Arison L
    3. Rahajamiakatra A
    4. Raserijaona F
    5. Niggemann B

    (2012) High asthma prevalence and associated factors in urban malagasy schoolchildren

    Journal of Asthma 49:575–580.

    https://doi.org/10.3109/02770903.2012.696170

    • PubMed
    • Google Scholar
54. Website

    1. World Health Organisation

    (2017) Asthma key facts

    Accessed August 31, 2017.

    https://www.who.int/news-room/fact-sheets/detail/asthma
55. 1. Zar HJ
    2. Ehrlich RI
    3. Workman L
    4. Weinberg EG

    (2007) The changing prevalence of asthma, allergic rhinitis and atopic eczema in African adolescents from 1995 to 2002

    Pediatric Allergy and Immunology 18:560–565.

    https://doi.org/10.1111/j.1399-3038.2007.00554.x

    • PubMed
    • Google Scholar

Author details

1. Harriet Mpairwe

   Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

   Contribution

   Conceptualization, Formal analysis, Funding acquisition, Investigation, Visualization, Writing—original draft, Project administration, Writing—review and editing

   For correspondence

   Harriet.Mpairwe@mrcuganda.org

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1199-4859

2. Milly Namutebi

   Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

   Contribution

   Investigation, Project administration, Writing—review and editing

   Competing interests

   No competing interests declared

3. Gyaviira Nkurunungi

   Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4062-9105

4. Pius Tumwesige

   Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

5. Irene Nambuya

   Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

6. Mike Mukasa

   Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

7. Caroline Onen

   Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

8. Marble Nnaluwooza

   Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

9. Barbara Apule

   Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

   Contribution

   Investigation, Writing—review and editing

   Competing interests

   No competing interests declared

10. Tonny Katongole

    Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

    Contribution

    Investigation, Writing—review and editing

    Competing interests

    No competing interests declared

11. Gloria Oduru

    Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

    Contribution

    Investigation, Writing—review and editing

    Competing interests

    No competing interests declared

12. Joseph Kahwa

    Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

    Contribution

    Data curation, Writing—review and editing

    Competing interests

    No competing interests declared

13. Emily L Webb

    London School of Hygiene and Tropical Medicine, London, United Kingdom

    Contribution

    Formal analysis, Writing—review and editing

    Competing interests

    No competing interests declared

14. Lawrence Lubyayi

    Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda

    Contribution

    Formal analysis, Writing—review and editing

    Competing interests

    No competing interests declared

15. Neil Pearce

    London School of Hygiene and Tropical Medicine, London, United Kingdom

    Contribution

    Supervision, Funding acquisition, Writing—review and editing

    Competing interests

    No competing interests declared

16. Alison M Elliott

    1. Medical Research Council/Uganda Virus Research Institute and London School of Hygiene and Tropical Medicine Uganda Research Unit, Entebbe, Uganda
    2. London School of Hygiene and Tropical Medicine, London, United Kingdom

    Contribution

    Conceptualization, Supervision, Funding acquisition, Writing—review and editing

    Competing interests

    No competing interests declared

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