Studies of outpatient department patients indicate that somatic discomforts such as headache, neck pain, chest pain, low back pain, and gastrointestinal discomfort are commonly found in patients with multiple complaints. Clustering of some symptoms has been found in common somatic symptom analyses. Because of the complexity involved in the diagnosis of patients with multiple complaints, the aim of this study is to identify and classify patterns of somatic symptoms in individuals assessed during a health examination.

The accuracy and precision of the Friedewald formula for estimating low-density lipoprotein cholesterol (LDL-C) is questionable. Although other formulae have been developed, only a few studies compare them. Thus, we compared the efficiencies of various formulae, based on the age and gender of adults, to determine which ones yield more accurate estimations in terms of mean squared error, and which formulae underestimated and overestimated LDL-C performance. This study compares various formulae in terms of mean squared error (MSE), as well as underestimation and overestimation of LDL-C concentrations, using subjects of various ages and both genders. Six groups were examined in this study based on age and gender: males 20–44 years old, 45–64, and 65 and above, and females in the same three age ranges. The results show that the Friedewald formula has relatively low accuracy, and while its performance among older (aged 45 and above) women with triglyceride concentrations ≤ 400 mg/dL is better than that with other groups, it is still more inaccurate than the other formulae. In terms of prediction errors and mean squared errors, Tsai’s formula (TF) and a calibrated TF provide the most accurate results with regard to the LDL-C concentration. Moreover, based on a cross-validation of age and gender, these two formulae provide highly accurate results for the LDL-C concentrations of all the studied groups, except for women aged 20–44 years. Based on the experimental results, this study provides a set of benchmarks for the formulae used in LDL-C tests when considering the factors of age and gender. Therefore, it is a valuable method for providing formula benchmarking.