Differences in the Prevalence of Non-Communicable Disease between Slum Dwellers and the General Population in a Large Urban Area in Brazil.

Residents of urban slums are at greater risk for disease than their non-slum dwelling urban counterparts. We sought to contrast the prevalences of selected non-communicable diseases (NCDs) between Brazilian adults living in a slum and the general population of the same city, by comparing the age and sex-standardized prevalences of selected NCDs from a 2010 survey in Pau da Lima, Salvador Brazil, with a 2010 national population-based telephone survey. NCD prevalences in both populations were similar for hypertension (23.6% (95% CI 20.9⁻26.4) and 22.9% (21.2⁻24.6), respectively) and for dyslipidemia (22.7% (19.8⁻25.5) and 21.5% (19.7⁻23.4)). Slum residents had higher prevalences of diabetes mellitus (10.1% (7.9⁻12.3)) and of overweight/obesity (46.5% (43.1⁻49.9)), compared to 5.2% (4.2⁻6.1) and 40.6% (38.5⁻42.8) of the general population in Salvador. Fourteen percent (14.5% (12.1⁻17.0)) of slum residents smoked cigarettes compared to 8.3% (7.1⁻9.5) of the general population in Salvador. The national telephone survey underestimated the prevalence of diabetes mellitus, overweight/obesity, and smoking in the slum population, likely in part due to differential sampling inside and outside of slums. Further research and targeted policies are needed to mitigate these inequalities, which could have significant economic and social impacts on slum residents and their communities.

Influenza-like illness in an urban community of Salvador, Brazil: incidence, seasonality and risk factors.

BACKGROUND: Our understanding of the epidemiology of influenza is limited in tropical regions, which in turn has hampered identifying optimal region-specific policy to diminish disease burden. Influenza-like illness (ILI) is a clinical diagnosis that can be used as a surrogate for influenza. This study aimed to define the incidence and seasonality of ILI and to assess its association with climatic variables and school calendar in an urban community in the tropical region of Salvador, Brazil. METHODS: Between 2009 and 2013, we conducted enhanced community-based surveillance for acute febrile illnesses (AFI) among patients ≥ 5 years of age in a slum community emergency unit in Salvador, Brazil. ILI was defined as a measured temperature of ≥ 37.8 °C or reported fever in a patient with cough or sore throat for ≤ 7 days, and negative test results for dengue and leptospirosis. Seasonality was analyzed with a harmonic regression model. Negative binomial regression models were used to correlate ILI incidence with rainfall, temperature, relative humidity and the number of days per month that schools were in session while controlling for seasonality. RESULTS: There were 2,651 (45.6% of 5,817 AFI patients) ILI cases with a mean annual incidence of 60 cases/1,000 population (95% CI 58-62). Risk of ILI was highest among 5-9 year olds with an annual incidence of 105 cases/1,000 population in 2009. ILI had a clear seasonal pattern with peaks between the 35-40th week of the year. ILI peaks were higher and earlier in 5-9 year olds compared with > 19 year olds. No association was seen between ILI and precipitation, relative humidity or temperature. There was a significant association between the incidence of ILI in children 5-9 years of age and number of scheduled school days per month. CONCLUSIONS: We identified a significant burden of ILI with distinct seasonality in the Brazilian tropics and highest rates among young school-age children. Seasonal peaks of ILI in children 5-9 years of age were positively associated with the number of school days, indicating that children may play a role in the timing of seasonal influenza transmission.

Spatial Distribution of Dengue in a Brazilian Urban Slum Setting: Role of Socioeconomic Gradient in Disease Risk.

BACKGROUND: Few studies of dengue have shown group-level associations between demographic, socioeconomic, or geographic characteristics and the spatial distribution of dengue within small urban areas. This study aimed to examine whether specific characteristics of an urban slum community were associated with the risk of dengue disease. METHODOLOGY/PRINCIPAL FINDINGS: From 01/2009 to 12/2010, we conducted enhanced, community-based surveillance in the only public emergency unit in a slum in Salvador, Brazil to identify acute febrile illness (AFI) patients with laboratory evidence of dengue infection. Patient households were geocoded within census tracts (CTs). Demographic, socioeconomic, and geographical data were obtained from the 2010 national census. Associations between CTs characteristics and the spatial risk of both dengue and non-dengue AFI were assessed by Poisson log-normal and conditional auto-regressive models (CAR). We identified 651 (22.0%) dengue cases among 2,962 AFI patients. Estimated risk of symptomatic dengue was 21.3 and 70.2 cases per 10,000 inhabitants in 2009 and 2010, respectively. All the four dengue serotypes were identified, but DENV2 predominated (DENV1: 8.1%; DENV2: 90.7%; DENV3: 0.4%; DENV4: 0.8%). Multivariable CAR regression analysis showed increased dengue risk in CTs with poorer inhabitants (RR: 1.02 for each percent increase in the frequency of families earning ≤1 times the minimum wage; 95% CI: 1.01-1.04), and decreased risk in CTs located farther from the health unit (RR: 0.87 for each 100 meter increase; 95% CI: 0.80-0.94). The same CTs characteristics were also associated with non-dengue AFI risk. CONCLUSIONS/SIGNIFICANCE: This study highlights the large burden of symptomatic dengue on individuals living in urban slums in Brazil. Lower neighborhood socioeconomic status was independently associated with increased risk of dengue, indicating that within slum communities with high levels of absolute poverty, factors associated with the social gradient influence dengue transmission. In addition, poor geographic access to health services may be a barrier to identifying both dengue and non-dengue AFI cases. Therefore, further spatial studies should account for this potential source of bias.