Noniterative adjustment to regression estimators with population-based auxiliary information for semiparametric models.

Disease registries, surveillance data, and other datasets with extremely large sample sizes become increasingly available in providing population-based information on disease incidence, survival probability, or other important public health characteristics. Such information can be leveraged in studies that collect detailed measurements but with smaller sample sizes. In contrast to recent proposals that formulate additional information as constraints in optimization problems, we develop a general framework to construct simple estimators that update the usual regression estimators with some functionals of data that incorporate the additional information. We consider general settings that incorporate nuisance parameters in the auxiliary information, non-i.i.d. data such as those from case-control studies, and semiparametric models with infinite-dimensional parameters common in survival analysis. Details of several important data and sampling settings are provided with numerical examples.

Gain of employment and perceived health status among previously unemployed persons: evidence from a longitudinal study in the United States.

OBJECTIVES: Using longitudinal datasets, we investigated whether gaining employment was associated with improvements in perceived mental health and overall health among previously unemployed U.S. residents. We additionally examined whether the association varied across types of employment and socio-demographic characteristics. METHODS: We used multiple two-year panel datasets of the Medical Expenditure Panel Survey during 2004-2012. We studied two health outcomes: perceived mental health and overall health. Our independent variables were employment status: full-time, part-time, self-employment, and unemployment. To examine the association between gaining employment and perceived health, we employed population-averaged models with generalized estimating equations. We secondarily examined the association across subpopulations (gender, race/ethnicity, and education). RESULTS: Those who gained full-time, part-time, and self-employment were more likely to report good mental health than those who stayed unemployed (AOR [Adjusted Odds Ratio] = 2.90, 95% CI 2.23 to 3.78, AOR = 1.63, 95% CI 1.28 to 2.06, and AOR = 3.24, 95% CI 1.08 to 9.70, respectively). Those who became full-time and part-time employed were more likely to report good overall health relative to those who stayed unemployed (AOR = 2.28, 95% CI 1.82 to 2.86 and AOR = 1.91, 95% CI 1.52 to 2.40, respectively). For both measures of perceived health, the magnitudes of the association were larger for those who gained full-time employment than part-time employment. AORs were relatively higher for males, black persons, and people with less than a college education relative to other groups in each subpopulation. CONCLUSION: Improving employment outcomes may improve perceived health. Transiting toward full-time employment, in particular, may maximize the benefits of employment.

Regionally-specific diffusion tensor imaging in mild cognitive impairment and Alzheimer's disease.

BACKGROUND: Diffusion tensor imaging (DTI) studies have shown significant cross-sectional differences among normal controls (NC) mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients in several fiber tracts in the brain, but longitudinal assessment is needed. METHODS: We studied 75 participants (25 NC, 25 amnestic MCI, and 25 mild AD) at baseline and 3 months later, with both imaging and clinical evaluations. Fractional anisotropy (FA) was analyzed in regions of interest (ROIs) in: (1) fornix, (2) cingulum bundle, (3) splenium, and (4) cerebral peduncles. Clinical data included assessments of clinical severity and cognitive function. Cross-sectional and longitudinal differences in FA, within each ROI, were analyzed with generalized estimating equations (GEE). RESULTS: Cross-sectionally, AD patients had lower FA than NC (p<0.05) at baseline and 3 months in the fornix and anterior portion of the cingulum bundle. Compared to MCI, AD cases had lower FA (p<0.05) in these regions and the splenium at 0 and 3 months. Both the fornix and anterior cingulum correlated across all clinical cognitive scores; lower FA in these ROIs corresponded to worse performance. Over the course of 3 months, when the subjects were clinically stable, the ROIs were also largely stable. CONCLUSIONS: Using DTI, findings indicate FA is decreased in specific fiber tracts among groups of subjects that vary along the spectrum from normal to AD, and that this measure is stable over short periods of time. The fornix is a predominant outflow tract of the hippocampus and may be an important indicator of AD progression.