Journal of epidemiology
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Journal of epidemiology · Jan 2014
Is a cutoff of 10% appropriate for the change-in-estimate criterion of confounder identification?
When using the change-in-estimate criterion, a cutoff of 10% is commonly used to identify confounders. However, the appropriateness of this cutoff has never been evaluated. This study investigated cutoffs required under different conditions. ⋯ Cutoff points for the change-in-estimate criterion varied according to the effect size of the exposure-outcome relationship, sample size, standard deviation of the regression error, and exposure-confounder correlation.
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Journal of epidemiology · Jan 2014
Relationship between physical activity and chronic musculoskeletal pain among community-dwelling Japanese adults.
Both little and excessive physical activity (PA) may relate to chronic musculoskeletal pain. The primary objective of this study was to characterize the relationship of PA levels with chronic low back pain (CLBP) and chronic knee pain (CKP). ⋯ This cross-sectional study showed that there were no significant linear or quadratic relationships of self-reported PA with CLBP and CKP. Future longitudinal study with objective measurements is needed.
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Journal of epidemiology · Jan 2014
Factors associated with delayed diagnosis of breast cancer in northeast Thailand.
We identified factors associated with delayed first consultation for breast symptoms (patient delay), delayed diagnosis after first consultation (doctor delay), and advanced pathologic stage at presentation among 180 women with breast cancer in Thailand. ⋯ Hospital referral from a health care provider was a major contributor to delayed diagnosis. Breast cancer awareness campaigns in Thailand should target individuals in low- and high-income groups, as well as practitioners.
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Journal of epidemiology · Jan 2014
The proportion of uncoded diagnoses in computerized health insurance claims in Japan in May 2010 according to ICD-10 disease categories.
Uncoded diagnoses in computerized health insurance claims are excluded from statistical summaries of health-related risks and other factors. The effects of these uncoded diagnoses, coded according to ICD-10 disease categories, have not been investigated to date in Japan. ⋯ The proportion of uncoded diagnoses differed by the type of health insurance claim and disease category. These findings indicate that Japanese health statistics computed using computerized health insurance claims might be biased by the exclusion of uncoded diagnoses.