2017
DOI: 10.1002/hec.3488
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A Dynamic Estimation of Obesity Using Nhanes Data: A Pseudo‐Panel Approach

Abstract: In this analysis, we examine the effect of wages on obesity by constructing pseudo-panels to conduct a dynamic estimation of Grossman's human capital model. The results indicate that wages have an increasing effect on obesity status. After accounting for past health status, the protective effect of wages commonly disseminated in the literature reverses on obesity status. The results may also indicate possible asymmetric consumption behavior between foods/nutrients that improve diet quality versus those that de… Show more

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Cited by 4 publications
(5 citation statements)
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“…The pseudo-panel data approach is actually a solution to transform the individual-level cross-sectional data into the group-level data (i.e., pseudo-panel data) such that the typical longitudinal models can be applied to efficiently and consistently estimate the change of the interested outcome variable over time [ 13 ]. This approach has been increasingly applied to public health [ 14 , 15 ].…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…The pseudo-panel data approach is actually a solution to transform the individual-level cross-sectional data into the group-level data (i.e., pseudo-panel data) such that the typical longitudinal models can be applied to efficiently and consistently estimate the change of the interested outcome variable over time [ 13 ]. This approach has been increasingly applied to public health [ 14 , 15 ].…”
Section: Methodsmentioning
confidence: 99%
“…Our study was actually an observational study using pseudo-panel approach to analysis the data [ 13 15 ]. Thus, we used the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) (Additional file 1 ) statement to ensure standardization and enhance the quality of the reporting [ 18 ].…”
Section: Methodsmentioning
confidence: 99%
“…The pseudo-panel data approach is actually a solution to transform the individual-level cross-sectional data into the group-level data (i.e., pseudo-panel data)such that the typical longitudinal models can be applied to e ciently and consistently estimate the change of the interested outcome variable over time. [13] This approach has been increasingly applied to public health [14,15] . According to the methods described in the literature [16,17], we constructed two pseudo-panel datasets from our discovery and replicate data by grouping three time-invariant variables -gender, birth year, and blood donation history.…”
Section: Construction Of Pseudo-panel Datasetsmentioning
confidence: 99%
“…Our study was actually an observational study using pseudo-panel approach to analysis the data [13][14][15]. Thus, we used the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement to ensure standardisation and enhance the quality of the reporting [18].…”
Section: Construction Of Pseudo-panel Datasetsmentioning
confidence: 99%
“…The key input that panel data provide for these models is a set of health and mortality transition probabilities representative of the population at large (Chen et al, 2016). Panel datasets are preferred for modeling highly complex processes in human aging (Saksena & Maldonado, 2017) because they provide data on the dynamics of individual transitions. Longitudinal datasets enable us to disentangle age, cohort, and period effects and help control for unobserved heterogeneity (Roßmann & Gummer, 2016).…”
Section: Introductionmentioning
confidence: 99%