Risk of bias from the six articles selected for the qualitative analysis.

<p>Risk of bias: 0 = low; 1 = moderate; 2 = high.</p><p>Risk of bias from the six articles selected for the qualitative analysis.</p

Reliability of Nationwide Prevalence Estimates of Dementia: A Critical Appraisal Based on Brazilian Surveys

<div><p>Background</p><p>The nationwide dementia prevalence is usually calculated by applying the results of local surveys to countries’ populations. To evaluate the reliability of such estimations in developing countries, we chose Brazil as an example. We carried out a systematic review of dementia surveys, ascertained their risk of bias, and present the best estimate of occurrence of dementia in Brazil.</p><p>Methods and Findings</p><p>We carried out an electronic search of PubMed, Latin-American databases, and a Brazilian thesis database for surveys focusing on dementia prevalence in Brazil. The systematic review was registered at PROSPERO (CRD42014008815). Among the 35 studies found, 15 analyzed population-based random samples. However, most of them utilized inadequate criteria for diagnostics. Six studies without these limitations were further analyzed to assess the risk of selection, attrition, outcome and population bias as well as several statistical issues. All the studies presented moderate or high risk of bias in at least two domains due to the following features: high non-response, inaccurate cut-offs, and doubtful accuracy of the examiners. Two studies had limited external validity due to high rates of illiteracy or low income. The three studies with adequate generalizability and the lowest risk of bias presented a prevalence of dementia between 7.1% and 8.3% among subjects aged 65 years and older. However, after adjustment for accuracy of screening, the best available evidence points towards a figure between 15.2% and 16.3%.</p><p>Conclusions</p><p>The risk of bias may strongly limit the generalizability of dementia prevalence estimates in developing countries. Extrapolations that have already been made for Brazil and Latin America were based on a prevalence that should have been adjusted for screening accuracy or not used at all due to severe bias. Similar evaluations regarding other developing countries are needed in order to verify the scope of these limitations.</p></div

Characteristics of the studies selected for the qualitative analysis.

<p>MMSE: Mini-Mental State Examination; PFAQ: Pfeffer Functional Activities Questionnaire; DSM-IV: Diagnostic and Statistical Manual of Mental Disorders, 4th edition; CAMDEX: Cambridge Examination for Mental Disorders; FOME: Fuld Object Memory Evaluation, IQCODE Informant Questionnaire on Cognitive Decline in the Elderly, B-ADL: Bayer-Activities of Daily Living Scale.</p><p>Characteristics of the studies selected for the qualitative analysis.</p

Overall crude and adjusted prevalences of dementia and 95% CIs among subjects aged 65 years* and older.

<p>* Magalhães: subjects aged 60 years and older.</p

Additional file 1: of The effect of industry-related air pollution on lung function and respiratory symptoms in school children

Figure S1. Modelled NOX isoconcentration contours (μg/m3), five years average exposure (2008–2012) without background concentration. Map reprinted from Kadaster [28] in the Netherlands under a CC-BY-4.0 license, 2017″. (JPEG 1976 kb

The mediating role of risk perception in the association between industry-related air pollution and health

<div><p>Background</p><p>Heavy industry emits many potentially hazardous pollutants into the air which can affect health. Awareness about the potential health impacts of air pollution from industry can influence people’s risk perception. This in turn can affect (self-reported) symptoms. Our aims were to investigate the associations of air pollution from heavy industry with health symptoms and to evaluate whether these associations are mediated by people’s risk perception about local industry.</p><p>Methods</p><p>A cross-sectional questionnaire study was conducted among children (2–18 years) and adults (19 years and above) living in the direct vicinity of an area with heavy industry. A dispersion model was used to characterize individual-level exposures to air pollution emitted from the industry in the area. Associations between PM_2.5 and NO_X with presence of chronic diseases (adults) and respiratory symptoms (adults and children) were investigated by logistic regression analysis. Risk perception was indirectly measured by worries about local industry (0–10 scale). Mediation analyses were performed to investigate the role of mediation by these worries.</p><p>Results</p><p>The response was 54% (2,627/4,877). In adults exposure to modelled PM_2.5 from industry (per μg/m³) was related with reported high blood pressure (OR 1.56, 95% CI 1.13–2.15) and exposure to modelled NO_X (per μg/m³) was inversely related with cardiovascular diseases (OR 0.91, 95% CI 0.84–0.98). In children higher PM_2.5 and NO_X concentrations (per μg/m³) were related with wheezing (OR 2.00, 95% CI 1.24–3.24 and OR 1.13, 95% CI 1.06–1.21 respectively) and dry cough (OR 2.33, 95% CI 1.55–3.52 and OR 1.16, 95% CI 1.10–1.22 respectively). Parental worry about local industry was an important mediator in exposure–health relations in children (indirect effect between 19–28%).</p><p>Conclusion</p><p>Exposure from industry was associated with self-reported reported high blood pressure among adults and respiratory symptoms among their children. Risk perception was found to mediate these associations for children.</p></div

Characteristics of adult respondents (19 years and more) and their children (2–18 years).

<p>Characteristics of adult respondents (19 years and more) and their children (2–18 years).</p

Modelled PM_2.5 isoconcentration contours (μg/m³), mean annual exposure without background concentration.

<p><b>Map reprinted from Kadaster in the Netherlands</b> [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0196783#pone.0196783.ref025" target="_blank">25</a>] <b>under a CC-BY-4.0 license, 2017</b>.</p

Associations between the exposure and worry with measures of health by children (2 to 18 years) from logistic regression.

<p>Associations between the exposure and worry with measures of health by children (2 to 18 years) from logistic regression.</p

Associations between the exposure and worry with measures of health by adults (19 years and more) from logistic regression.

<p>Associations between the exposure and worry with measures of health by adults (19 years and more) from logistic regression.</p