scholarly journals Residential mobility impacts exposure assessment and community socioeconomic characteristics in longitudinal epidemiology studies

2016 ◽  
Vol 26 (4) ◽  
pp. 428-434 ◽  
Author(s):  
Cole Brokamp ◽  
Grace K LeMasters ◽  
Patrick H Ryan
Keyword(s):  
Exposure Assessment ◽  
Residential Mobility ◽  
Socioeconomic Characteristics ◽  
Epidemiology Studies ◽  
Longitudinal Epidemiology

A Two-Stage Model of Tenure Mobility

1978 ◽  
Vol 10 (1) ◽  
pp. 81-92 ◽  
Author(s):  
C Jones ◽  
S Gudjonsson ◽  
J Parry Lewis
Keyword(s):  
Discriminant Analysis ◽  
Residential Mobility ◽  
Life Style ◽  
Stage Model ◽  
Multiple Discriminant Analysis ◽  
Two Stage ◽  
Socioeconomic Characteristics ◽  
Decisionmaking Process ◽  
Two Stages ◽  
Sequential Nature

This paper examines the sequential nature of the residential-mobility decisionmaking process. Initially a model of household tenure mobility is considered, consisting of two stages, the decision to move and the choice of tenure; ultimately this assumption is relaxed. Multiple discriminant analysis is used to distinguish between the different groups of households, between movers and nonmovers, and between different tenures, on the basis of a set of variables describing the socioeconomic characteristics of the household. Life-style and demographic factors are shown to influence more the tenure moved to than the decision to move. And although various factors appear to influence the mobility decision in the different tenures, the age of the household is generally found to be the most important discriminator.

The development of a comprehensive exposure assessment strategy for polybrominated diphenyl ethers (PBDEs) for use in observational epidemiology studies.

2013 ◽  
Vol 2013 (1) ◽  
pp. 3462
Author(s):  
Shelley A Harris ◽  
Beatrice Boucher ◽  
Caryn Thompson ◽  
Cariton Kubwabo ◽  
Michelle Cotterchio ◽  
...  
Keyword(s):  
Exposure Assessment ◽  
Polybrominated Diphenyl Ethers ◽  
Assessment Strategy ◽  
Diphenyl Ethers ◽  
Epidemiology Studies

An algorithm to identify residential mobility from electronic health-record data

2021 ◽  
Author(s):  
Jessica R Meeker ◽  
Heather Burris ◽  
Mary Regina Boland
Keyword(s):  
Electronic Health Record ◽  
Exposure Assessment ◽  
Residential Mobility ◽  
Area Deprivation ◽  
Health Record ◽  
Exposure Misclassification ◽  
Electronic Health Record Data ◽  
Electronic Health ◽  
One Year ◽  
Zip Code

Abstract Background Environmental, social and economic exposures can be inferred from address information recorded in an electronic health record. However, these data often contain administrative errors and misspellings. These issues make it challenging to determine whether a patient has moved, which is integral for accurate exposure assessment. We aim to develop an algorithm to identify residential mobility events and avoid exposure misclassification. Methods At Penn Medicine, we obtained a cohort of 12 147 pregnant patients who delivered between 2013 and 2017. From this cohort, we identified 9959 pregnant patients with address information at both time of delivery and one year prior. We developed an algorithm entitled REMAP (Relocation Event Moving Algorithm for Patients) to identify residential mobility during pregnancy and compared it to using ZIP code differences alone. We assigned an area-deprivation exposure score to each address and assessed how residential mobility changed the deprivation scores. Results To assess the accuracy of our REMAP algorithm, we manually reviewed 3362 addresses and found that REMAP was 95.7% accurate. In this large urban cohort, 41% of patients moved during pregnancy. REMAP outperformed the comparison of ZIP codes alone (82.9%). If residential mobility had not been taken into account, absolute area deprivation would have misclassified 39% of the patients. When setting a threshold of one quartile for misclassification, 24.4% of patients would have been misclassified. Conclusions Our study tackles an important characterization problem for exposures that are assigned based upon residential addresses. We demonstrate that methods using ZIP code alone are not adequate. REMAP allows address information from electronic health records to be used for accurate exposure assessment and the determination of residential mobility, giving researchers and policy makers more reliable information.

A Multiple-Attribute Housing Disequilibrium Model of Residential Mobility

1983 ◽  
Vol 15 (6) ◽  
pp. 751-765 ◽  
Author(s):  
J L Onaka
Keyword(s):  
Residential Mobility ◽  
Housing Prices ◽  
Longitudinal Survey ◽  
Socioeconomic Characteristics ◽  
Interaction Terms ◽  
Proposed Model ◽  
Multiple Attribute ◽  
Residential Migration ◽  
Hedonic Theory ◽  
The Relationship

This paper presents a model of residential mobility to investigate the relationship between the socioeconomic characteristics of a household and housing dissatisfaction. The paper extends the microeconomic model of residential migration by incorporating the hedonic theory of housing prices. The proposed model is estimated by logistic regression with interaction terms, with data from a national longitudinal survey. It is shown that the model provides a statistically significant improvement in fit over existing approaches.

scholarly journals Exposure assessment issues in epidemiology studies of phthalates

2015 ◽  
Vol 85 ◽  
pp. 27-39 ◽  
Author(s):  
Lauren E. Johns ◽  
Glinda S. Cooper ◽  
Audrey Galizia ◽  
John D. Meeker
Keyword(s):  
Exposure Assessment ◽  
Epidemiology Studies

Exposure assessment for case–control and case–case epidemiology studies based in Shanghai China: Summary of methods and results

2010 ◽  
Vol 184 (1-2) ◽  
pp. 286-289 ◽  
Author(s):  
T. Armstrong ◽  
Y. Liang ◽  
Y. Zhou ◽  
S. Bowes ◽  
O. Wong ◽  
...  
Keyword(s):  
Exposure Assessment ◽  
Case Control ◽  
Epidemiology Studies

scholarly journals Impact of Residential Mobility on Exposure Assessment in Longitudinal Air Pollution Studies: A Sensitivity Analysis within the ESCAPE Project

2012 ◽  
Vol 2012 ◽  
pp. 1-5 ◽  
Author(s):  
Anna Oudin ◽  
Bertil Forsberg ◽  
Magnus Strömgren ◽  
Rob Beelen ◽  
Lars Modig
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Regression Model ◽  
Exposure Assessment ◽  
Residential Mobility ◽  
Large Population ◽  
Average Concentration ◽  
Exposure Misclassification ◽  
Land Use Regression

Exposure misclassification in longitudinal studies of air pollution exposure and health effects can occur due to residential mobility in a study population over followup. The aim of this study was to investigate to what extent residential mobility during followup can be expected to cause exposure misclassification in such studies, where exposure at the baseline address is used as the main exposure assessment. The addresses for each participant in a large population-based study (N>25,000) were obtained via national registers. We used a Land Use Regression model to estimate theNOxconcentration for each participant's all addresses during the entire follow-up period (in average 14.6 years) and calculated an average concentration during followup. The Land Use Regression model explained 83% of the variation in measured levels. In summary, theNOxconcentration at the inclusion address was similar to the average concentration over followup with a correlation coefficient of 0.80, indicating that air pollution concentration at study inclusion address could be used as indicator of average air pollution concentrations over followup. The differences between an individual's inclusion and average follow-up mean concentration were small and seemed to be nondifferential with respect to a large range of factors and disease statuses, implying that bias due to residential mobility was small.

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