Table 2

Publications comparing asthma prevalence among cities and publication comparing intraurban variation in asthma within cities

Publication	Methodology	Asthma definition	Urban indicators	Findings
Cunha et al, 2007 85	Approach: Comparing cities Region/country: Brazil Population: 6–7 and 13–14 years Unit of analyses: cities Sample: 20	Current wheezing	Socioeconomic indicators: Illiteracy rate, poverty rate, income, water supply, sanitation, GINI, HDI. Health indicators: Infant Mortality, Mortality for external Causes and Hospitals beds.	Asthma prevalence increased with poorer sanitation and with higher infant mortality, GINI index and external mortality. Poverty and inequality seems to be related with asthma prevalence in urban areas of Brazil.
Rodriguez et al, 2011 86	Approach: Comparing cities Region/country: Ecuador Population: 5–15 years Unit of analyses: Rural communities Sample: 59	Current wheezing	Infrastructure Index: Administrative grade, spatial organisation, transport access, electrical grid, pipe water system, telephone system, health centre, educational institutions. Socioeconomic Index: Parent’s education, household income, material goods, access to urban services, housing materials, motors vehicle. Lifestyles Index: Junk food consumption, physical exercise, TV viewing, farm activities, pets in house, migration and parasite infections.	Lifestyle and socioeconomic indicators had stronger overall effects on asthma prevalence than infrastructure indicators. Higher asthma prevalence was present in communities with a higher socioeconomic level and a more urbanised lifestyle.
Fattore et al, 2014 87	Approach: Comparing cities Region/country: Latin America Population: 6–7 years Unit of analyses: Cities Sample: 31	Current wheezing	Socioeconomic indicators: GINI Index and HDI. Environmental variables: Water supply, sanitation, crowding. Health indicators: Infant mortality and homicide mortality rate.	Income inequality, lack of adequate sanitation, less crowding households, greater reduction in the infant mortality rates and high homicide rates were determinants of asthma symptoms in Latin American urban children.
Tabalipa et al,2015 88	Approach: Comparing cities Region/country: Brazil Population: 6–7 and 13–14 years Unit of analyses: Municipalities Sample: 266	Hospital rate admissions (doctor diagnosis)	-Index of Youth Vulnerability to Violence: Injury from external causes, incidences of homicides, traffic accidents, education, involvement in crime, poverty and unemployment.	Direct correlation between indicators of violence and rates of admission due to asthma, and an inverse correlation with indicators of development.
Ponte et al,2016 89	Approach: Comparing cities Region/country: Brazil Population: 5–24 and 25–39 years Unit of analyses: Municipality Sample: 5505	Hospital rate admissions (doctor diagnosis)	Socioeconomic indicators: Per capita income, proportion of the population living in an urban area. Health indicators: Number of physicians, number of hospital beds, rate of hospital admission from influenza, access to inhaled corticosteroid for asthma.	An increase in urban population by municipality was associated with lower odds for reduced hospital admissions and death rates from asthma in children and young adults.
Antunes et al, 2014 90	Approach: Intraurban variation Region/country: Bahía, Brazil Population: All population Unit of analyses: Census Wards Sample: 93	Hospital rate admissions (doctor diagnosis)	Socioeconomic indicators: Income, education, household crowding, presence of slums, GINI Index, sanitation, garbage collection.	Areas of Salvador whose population had lower levels of education and income had higher risk of hospitalisation for respiratory diseases, particularly for asthma and pneumonia.
Dias et al, 2016 91	Approach: Intraurban variation Region/country: Belo Horizonte, Brazil Population: 0–14 Unit of analyses: Census Wards Sample	Hospital rate admissions (doctor diagnosis)	-Health Vulnerability Index: Inadequate water supply, sanitary sewage and inadequate garbage collection, housing, illiterate population, per capita income, race and ethnicity.	Hospital admissions for asthma were higher in areas of greater social vulnerability, suggesting that social and environmental factors may be determinants of variation in asthma prevalence in urban areas.

GINI, Measure of Inequality; HDI, Human Development Index.