Structural equation modeling of the medical outcome study: Short Form 36 (SF-36)

The factorial validity of the SF-36 was evaluated using confirmatory factor analysis (CFA) methods, structural equation modeling (SEM), and multigroup structural equation modeling (MSEM). First, the measurement and structural model of the hypothesized SF-36 was explicated. Second, the model was tested for the validity of a second-order factorial structure, upon evidence of model misfit, determined the best-fitting model, and tested the validity of the best-fitting model on a second random sample from the same population. Third, the best-fitting model was tested for invariance of the factorial structure across race, age, and educational subgroups using MSEM.^ The findings support the second-order factorial structure of the SF-36 as proposed by Ware and Sherbourne (1992). However, the results suggest that: (a) Mental Health and Physical Health covary; (b) general mental health cross-loads onto Physical Health; (c) general health perception loads onto Mental Health instead of Physical Health; (d) many of the error terms are correlated; and (e) the physical function scale is not reliable across these two samples. This hierarchical factor pattern was replicated across both samples of health care workers, suggesting that the post hoc model fitting was not data specific. Subgroup analysis suggests that the physical function scale is not reliable across the "age" or "education" subgroups and that the general mental health scale path from Mental Health is not reliable across the "white/nonwhite" or "education" subgroups.^ The importance of this study is in the use of SEM and MSEM in evaluating sample data from the use of the SF-36. These methods are uniquely suited to the analysis of latent variable structures and are widely used in other fields. The use of latent variable models for self reported outcome measures has become widespread, and should now be applied to medical outcomes research. Invariance testing is superior to mean scores or summary scores when evaluating differences between groups. From a practical, as well as, psychometric perspective, it seems imperative that construct validity research related to the SF-36 establish whether this same hierarchical structure and invariance holds for other populations.^ This project is presented as three articles to be submitted for publication. ^

A nested case-control study of radiation exposure and brain cancer incidence in the United States Air Force

A nested case-control study design was used to investigate the relationship between radiation exposure and brain cancer risk in the United States Air Force (USAF). The cohort consisted of approximately 880,000 men with at least 1 year of service between 1970 and 1989. Two hundred and thirty cases were identified from hospital discharge records with a diagnosis of primary malignant brain tumor (International Classification of Diseases, 9th revision, code 191). Four controls were exactly matched with each case on year of age and race using incidence density sampling. Potential career summary extremely low frequency (ELF) and microwave-radiofrequency (MWRF) radiation exposures were based upon the duration in each occupation and an intensity score assigned by an expert panel. Ionizing radiation (IR) exposures were obtained from personal dosimetry records.^ Relative to the unexposed, the overall age-race adjusted odds ratio (OR) for ELF exposure was 1.39, 95 percent confidence interval (CI) 1.03-1.88. A dose-response was not evident. The same was true for MWRF, although the OR = 1.59, with 95 percent CI 1.18-2.16. Excess risk was not found for IR exposure (OR = 0.66, 45 percent CI 0.26-1.72).^ Increasing socioeconomic status (SES), as identified by military pay grade, was associated with elevated brain tumor risk (officer vs. enlisted personnel age-race adjusted OR = 2.11, 95 percent CI 1.98-3.01, and senior officers vs. all others age-race adjusted OR = 3.30, 95 percent CI 2.0-5.46). SES proved to be an important confounder of the brain tumor risk associated with ELF and MWRF exposure. For ELF, the age-race-SES adjusted OR = 1.28, 95 percent CI 0.94-1.74, and for MWRF, the age-race-SES adjusted OR = 1.39, 95 percent CI 1.01-1.90.^ These results indicate that employment in Air Force occupations with potential electromagnetic field exposures is weakly, though not significantly, associated with increased risk for brain tumors. SES appeared to be the most consistent brain tumor risk factor in the USAF cohort. Other investigators have suggested that an association between brain tumor risk and SES may arise from differential access to medical care. However, in the USAF cohort health care is universally available. This study suggests that some factor other than access to medical care must underlie the association between SES and brain tumor risk. ^