HIA.bib

@article{RN12,
   author = {Banerjee, A. and Chaudhury, S.},
   title = {Statistics without tears: Populations and samples},
   journal = {Ind Psychiatry J},
   volume = {19},
   number = {1},
   pages = {60-5},
   note = {0976-2795
Banerjee, Amitav
Chaudhury, Suprakash
Journal Article
India
2010/01/01
Ind Psychiatry J. 2010 Jan;19(1):60-5. doi: 10.4103/0972-6748.77642.},
   abstract = {Research studies are usually carried out on sample of subjects rather than whole populations. The most challenging aspect of fieldwork is drawing a random sample from the target population to which the results of the study would be generalized. In actual practice, the task is so difficult that some sampling bias occurs in almost all studies to a lesser or greater degree. In order to assess the degree of this bias, the informed reader of medical literature should have some understanding of the population from which the sample was drawn. The ultimate decision on whether the results of a particular study can be generalized to a larger population depends on this understanding. The subsequent deliberations dwell on sampling strategies for different types of research and also a brief description of different sampling methods.},
   keywords = {Methods
population
sample},
   ISSN = {0972-6748 (Print)
0972-6748},
   DOI = {10.4103/0972-6748.77642},
   year = {2010},
   type = {Journal Article}
}

@article{RN3,
   author = {Checkoway, H. and Pearce, N. and Kriebel, D.},
   title = {Selecting appropriate study designs to address specific research questions in occupational epidemiology},
   journal = {Occup Environ Med},
   volume = {64},
   number = {9},
   pages = {633-8},
   note = {1470-7926
Checkoway, Harvey
Pearce, Neil
Kriebel, David
Journal Article
Research Support, Non-U.S. Gov't
Review
2007/08/21
Occup Environ Med. 2007 Sep;64(9):633-8. doi: 10.1136/oem.2006.029967.},
   abstract = {Various epidemiological study designs are available to investigate illness and injury risks related to workplace exposures. The choice of study design to address a particular research question will be guided by the nature of the health outcome under study, its presumed relation to workplace exposures, and feasibility constraints. This review summarises the relative advantages and limitations of conventional study designs including cohort studies, cross-sectional studies, repeated measures studies, case-control (industry- and community-based) studies, and more recently developed variants of the nested case-control DESIGN: case-cohort and case-crossover studies.},
   keywords = {*Accidents, Occupational
Biomedical Research/*standards
Epidemiologic Methods
Female
Humans
Male
*Occupational Diseases
Occupational Health
Research Design/*standards},
   ISSN = {1351-0711 (Print)
1351-0711},
   DOI = {10.1136/oem.2006.029967},
   year = {2007},
   type = {Journal Article}
}

@article{RN9,
   author = {Cohen, Aaron J. and Brauer, Michael and Burnett, Richard and Anderson, H. Ross and Frostad, Joseph and Estep, Kara and Balakrishnan, Kalpana and Brunekreef, Bert and Dandona, Lalit and Dandona, Rakhi and Feigin, Valery and Freedman, Greg and Hubbell, Bryan and Jobling, Amelia and Kan, Haidong and Knibbs, Luke and Liu, Yang and Martin, Randall and Morawska, Lidia and Pope, C. Arden, III and Shin, Hwashin and Straif, Kurt and Shaddick, Gavin and Thomas, Matthew and van Dingenen, Rita and van Donkelaar, Aaron and Vos, Theo and Murray, Christopher J. L. and Forouzanfar, Mohammad H.},
   title = {Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015},
   journal = {The Lancet},
   volume = {389},
   number = {10082},
   pages = {1907-1918},
   note = {doi: 10.1016/S0140-6736(17)30505-6},
   ISSN = {0140-6736},
   DOI = {10.1016/S0140-6736(17)30505-6},
   url = {https://doi.org/10.1016/S0140-6736(17)30505-6},
   year = {2017},
   type = {Journal Article}
}

@article{RN2,
   author = {Faustini, A. and Davoli, M.},
   title = {Attributable Risk to Assess the Health Impact of Air Pollution: Advances, Controversies, State of the Art and Future Needs},
   journal = {Int J Environ Res Public Health},
   volume = {17},
   number = {12},
   note = {1660-4601
Faustini, Annunziata
Davoli, Marina
Journal Article
Review
2020/06/27
Int J Environ Res Public Health. 2020 Jun 23;17(12):4512. doi: 10.3390/ijerph17124512.},
   abstract = {Despite the increased attention given to the health impact assessment of air pollution and to the strategies to control it in both scientific literature and concrete interventions, the results of the implementations, especially those involving traffic, have not always been satisfactory and there is still disagreement about the most appropriate interventions and the methods to assess their effectiveness. This state-of-the-art article reviews the recent interpretation of the concepts that concern the impact assessment, and compares old and new measurements of attributable risk and attributable fraction. It also summarizes the ongoing discussion about the designs and methods for assessing the air pollution impact with particular attention to improvements due to spatio-temporal analysis and other new approaches, such as studying short term effects in cohorts, and the still discussed methods of predicting the values of attributable risk (AR). Finally, the study presents the more recent analytic perspectives and the methods for directly assessing the effects of not yet implemented interventions on air quality and health, in accordance with the suggestion in the strategic plan 2020-2025 from the Health Effect Institute.},
   keywords = {Air Pollutants/*adverse effects/analysis
Air Pollution/*adverse effects/analysis
Environmental Exposure/*adverse effects/statistics & numerical data
*Health Impact Assessment/trends
Humans
Risk Factors
air pollution
attributable fraction
attributable risk
health impact assessment},
   ISSN = {1661-7827 (Print)
1660-4601},
   DOI = {10.3390/ijerph17124512},
   year = {2020},
   type = {Journal Article}
}

@techreport{RN8,
   author = {Health, Australian Institute of and Welfare},
   title = {Australian Burden of Disease Study 2015: Interactive data on risk factor burden},
   institution = {AIHW},
   url = {https://www.aihw.gov.au/reports/burden-of-disease/interactive-data-risk-factor-burden},
   year = {2020},
   type = {Report}
}

@article{RN5,
   author = {Hoek, Gerard and Krishnan, Ranjini M. and Beelen, Rob and Peters, Annette and Ostro, Bart and Brunekreef, Bert and Kaufman, Joel D.},
   title = {Long-term air pollution exposure and cardio- respiratory mortality: a review},
   journal = {Environmental Health},
   volume = {12},
   number = {1},
   pages = {43},
   abstract = {Current day concentrations of ambient air pollution have been associated with a range of adverse health effects, particularly mortality and morbidity due to cardiovascular and respiratory diseases. In this review, we summarize the evidence from epidemiological studies on long-term exposure to fine and coarse particles, nitrogen dioxide (NO2) and elemental carbon on mortality from all-causes, cardiovascular disease and respiratory disease. We also summarize the findings on potentially susceptible subgroups across studies. We identified studies through a search in the databases Medline and Scopus and previous reviews until January 2013 and performed a meta-analysis if more than five studies were available for the same exposure metric.},
   ISSN = {1476-069X},
   DOI = {10.1186/1476-069X-12-43},
   url = {https://doi.org/10.1186/1476-069X-12-43},
   year = {2013},
   type = {Journal Article}
}

@article{RN4,
   author = {Knibbs, L. D. and van Donkelaar, A. and Martin, R. V. and Bechle, M. J. and Brauer, M. and Cohen, D. D. and Cowie, C. T. and Dirgawati, M. and Guo, Y. and Hanigan, I. C. and Johnston, F. H. and Marks, G. B. and Marshall, J. D. and Pereira, G. and Jalaludin, B. and Heyworth, J. S. and Morgan, G. G. and Barnett, A. G.},
   title = {Satellite-Based Land-Use Regression for Continental-Scale Long-Term Ambient PM(2.5) Exposure Assessment in Australia},
   journal = {Environ Sci Technol},
   volume = {52},
   number = {21},
   pages = {12445-12455},
   note = {1520-5851
Knibbs, Luke D
Orcid: 0000-0002-0399-2370
van Donkelaar, Aaron
Martin, Randall V
Bechle, Matthew J
Orcid: 0000-0001-8076-5457
Brauer, Michael
Orcid: 0000-0002-9103-9343
Cohen, David D
Cowie, Christine T
Dirgawati, Mila
Guo, Yuming
Hanigan, Ivan C
Johnston, Fay H
Marks, Guy B
Marshall, Julian D
Pereira, Gavin
Jalaludin, Bin
Heyworth, Jane S
Morgan, Geoffrey G
Barnett, Adrian G
Journal Article
Research Support, Non-U.S. Gov't
United States
2018/10/03
Environ Sci Technol. 2018 Nov 6;52(21):12445-12455. doi: 10.1021/acs.est.8b02328. Epub 2018 Oct 15.},
   abstract = {Australia has relatively diverse sources and low concentrations of ambient fine particulate matter (<2.5 μm, PM(2.5)). Few comparable regions are available to evaluate the utility of continental-scale land-use regression (LUR) models including global geophysical estimates of PM(2.5), derived by relating satellite-observed aerosol optical depth to ground-level PM(2.5) ("SAT-PM(2.5)"). We aimed to determine the validity of such satellite-based LUR models for PM(2.5) in Australia. We used global SAT-PM(2.5) estimates (∼10 km grid) and local land-use predictors to develop four LUR models for year-2015 (two satellite-based, two nonsatellite-based). We evaluated model performance at 51 independent monitoring sites not used for model development. An LUR model that included the SAT-PM(2.5) predictor variable (and six others) explained the most spatial variability in PM(2.5) (adjusted R(2) = 0.63, RMSE (μg/m(3) [%]): 0.96 [14%]). Performance decreased modestly when evaluated (evaluation R(2) = 0.52, RMSE: 1.15 [16%]). The evaluation R(2) of the SAT-PM(2.5) estimate alone was 0.26 (RMSE: 3.97 [56%]). SAT-PM(2.5) estimates improved LUR model performance, while local land-use predictors increased the utility of global SAT-PM(2.5) estimates, including enhanced characterization of within-city gradients. Our findings support the validity of continental-scale satellite-based LUR modeling for PM(2.5) exposure assessment in Australia.},
   keywords = {*Air Pollutants
Australia
Cities
Environmental Monitoring
Particulate Matter},
   ISSN = {0013-936x},
   DOI = {10.1021/acs.est.8b02328},
   year = {2018},
   type = {Journal Article}
}

@article{RN13,
   author = {Sharma, S. K.},
   title = {Importance of case definition in epidemiological studies},
   journal = {Neuroepidemiology},
   volume = {37},
   number = {2},
   pages = {141-2},
   note = {1423-0208
Sharma, Sushil K
Comment
Journal Article
Switzerland
2011/10/12
Neuroepidemiology. 2011;37(2):141-2. doi: 10.1159/000332609. Epub 2011 Oct 7.},
   keywords = {Female
*Gulf War
Humans
Male
*Models, Statistical
Persian Gulf Syndrome/*epidemiology
Population Surveillance/*methods
Surveys and Questionnaires/*standards
*Veterans},
   ISSN = {0251-5350},
   DOI = {10.1159/000332609},
   year = {2011},
   type = {Journal Article}
}

@article{RN14,
   author = {Viera, A. J.},
   title = {Odds ratios and risk ratios: what's the difference and why does it matter?},
   journal = {South Med J},
   volume = {101},
   number = {7},
   pages = {730-4},
   note = {1541-8243
Viera, Anthony J
Journal Article
United States
2008/06/27
South Med J. 2008 Jul;101(7):730-4. doi: 10.1097/SMJ.0b013e31817a7ee4.},
   abstract = {Odds ratios (OR) are commonly reported in the medical literature as the measure of association between exposure and outcome. However, it is relative risk that people more intuitively understand as a measure of association. Relative risk can be directly determined in a cohort study by calculating a risk ratio (RR). In case-control studies, and in cohort studies in which the outcome occurs in less than 10% of the unexposed population, the OR provides a reasonable approximation of the RR. However, when an outcome is common (iY 10% in the unexposed group), the OR will exaggerate the RR. One method readers can use to estimate the RR from an OR involves using a simple formula. Readers should also look to see that a confidence interval is provided with any report of an OR or RR. A greater understanding of ORs and RRs allows readers to draw more accurate interpretations of research findings.},
   keywords = {Case-Control Studies
Cohort Studies
Humans
*Odds Ratio
*Risk},
   ISSN = {0038-4348},
   DOI = {10.1097/SMJ.0b013e31817a7ee4},
   year = {2008},
   type = {Journal Article}
}

@techreport{RN6,
   author = {WHO},
   title = {Health Risks of Air Pollution in Europe—HRAPIE Project: Recommendations for Concentration-Response Functions for Cost-Benefit Analysis of Particulate Matter, Ozone and Nitrogen Dioxide},
   year = {2013},
   type = {Report}
}

@misc{RN1,
   author = {WHO},
   title = {Health impact assessment},
   publisher = {World Health Organisation},
   url = {https://www.who.int/health-topics/health-impact-assessment#tab=tab_1},
   year = {2022},
   type = {Web Page}
}