scholarly journals A standardisation approach to the control of socioeconomic confounding in small area studies of environment and health.

1995 ◽  
Vol 49 (Suppl 2) ◽  
pp. S9-14 ◽  
Author(s):  
H Dolk ◽  
B Mertens ◽  
I Kleinschmidt ◽  
P Walls ◽  
G Shaddick ◽  
...  
Keyword(s):  
Small Area ◽  
Area Studies ◽  
Environment And Health

scholarly journals Small-area methods for investigation of environment and health

2020 ◽  
Vol 49 (2) ◽  
pp. 686-699 ◽  
Author(s):  
Frédéric B Piel ◽  
Daniela Fecht ◽  
Susan Hodgson ◽  
Marta Blangiardo ◽  
M Toledano ◽  
...  
Keyword(s):  
Small Area ◽  
Environmental Pollutants ◽  
Population Level ◽  
Data Availability ◽  
Area Studies ◽  
Individual Level ◽  
Environment And Health ◽  
Disease Patterns ◽  
Geographical Scale ◽  
Study Designs

Abstract Small-area studies offer a powerful epidemiological approach to study disease patterns at the population level and assess health risks posed by environmental pollutants. They involve a public health investigation on a geographical scale (e.g. neighbourhood) with overlay of health, environmental, demographic and potential confounder data. Recent methodological advances, including Bayesian approaches, combined with fast-growing computational capabilities, permit more informative analyses than previously possible, including the incorporation of data at different scales, from satellites to individual-level survey information. Better data availability has widened the scope and utility of small-area studies, but has also led to greater complexity, including choice of optimal study area size and extent, duration of study periods, range of covariates and confounders to be considered and dealing with uncertainty. The availability of data from large, well-phenotyped cohorts such as UK Biobank enables the use of mixed-level study designs and the triangulation of evidence on environmental risks from small-area and individual-level studies, therefore improving causal inference, including use of linked biomarker and -omics data. As a result, there are now improved opportunities to investigate the impacts of environmental risk factors on human health, particularly for the surveillance and prevention of non-communicable diseases.

scholarly journals Design Issues in Small-Area Studies of Environment and Health

2008 ◽  
Vol 116 (8) ◽  
pp. 1098-1104 ◽  
Author(s):  
Paul Elliott ◽  
David A. Savitz
Keyword(s):  
Small Area ◽  
Design Issues ◽  
Area Studies ◽  
Environment And Health

Uncontrolled Migrations as a Cause of Inequality in Health and Mortality in Small-area Studies

Epidemiology ◽  
2009 ◽  
Vol 20 (3) ◽  
pp. 411-418 ◽  
Author(s):  
Ricardo Ocaña-Riola ◽  
Alberto Fernández-Ajuria ◽  
José María Mayoral-Cortés ◽  
Silvia Toro-Cárdenas ◽  
Carmen Sánchez-Cantalejo
Keyword(s):  
Small Area ◽  
Area Studies ◽  
Inequality In Health ◽  
Health And Mortality

scholarly journals Using ecological propensity score to adjust for missing confounders in small area studies

Biostatistics ◽  
2017 ◽  
Vol 20 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Yingbo Wang ◽  
Monica Pirani ◽  
Anna L Hansell ◽  
Sylvia Richardson ◽  
Marta Blangiardo
Keyword(s):  
Propensity Score ◽  
Small Area ◽  
Area Studies

scholarly journals Availability, access, analysis and dissemination of small-area data

2020 ◽  
Vol 49 (Supplement_1) ◽  
pp. i4-i14 ◽  
Author(s):  
Susan Hodgson ◽  
Daniela Fecht ◽  
John Gulliver ◽  
Hima Iyathooray Daby ◽  
Frédéric B Piel ◽  
...  
Keyword(s):  
Small Area ◽  
Demographic Data ◽  
Open Data ◽  
Remote Sensing Data ◽  
Environmental Research ◽  
Middle Income ◽  
Environment And Health ◽  
Open Government Data ◽  
Environmental Public Health Tracking ◽  
Area Data

AbstractIn this era of ‘big data’, there is growing recognition of the value of environmental, health, social and demographic data for research. Open government data initiatives are growing in number and in terms of content. Remote sensing data are finding widespread use in environmental research, including in low- and middle-income settings. While our ability to study environment and health associations across countries and continents grows, data protection rules and greater patient control over the use of their data present new challenges to using health data in research. Innovative tools that circumvent the need for the physical sharing of data by supporting non-disclosive sharing of information, or that permit spatial analysis without researchers needing access to underlying patient data can be used to support analyses while protecting data confidentiality. User-friendly visualizations, allowing small-area data to be seen and understood by non-expert audiences, are revolutionizing public and researcher interactions with data. The UK Small Area Health Statistics Unit’s Environment and Health Atlas for England and Wales, and the US National Environmental Public Health Tracking Network offer good examples. Open data facilitates user-generated outputs, and ‘mash-ups’, and user-generated inputs from social media, mobile devices and wearable tech are new data streams that will find utility in future studies, and bring novel dimensions with respect to ethical use of small-area data.

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