Habibollah Esmaeily - , Mashhad University of Medical Sciences, Mashhad, Iran.
Elham Dolat - , Mashhad University of Medical Sciences, Mashhad, Iran.
Hamid Heidarian Miri - , Mashhad University of Medical Sciences, Mashhad, Iran.
Ala Taji-Heravi - Islamic Azad University, Tehran North Branch, Tehran, Iran.
Omid Kiani - , Mashhad University of Medical Sciences, Mashhad, Iran.

Background and Purpose: Serum total cholesterol (TC) concentrations are affected by several factors including ethnicity, diet, geographic, and environmental determinants, and are related to another disease, including hypothyroidism, and renal and liver disease. It is associated with an increased risk of cardiovascular disease, particularly if associated with high levels of serum low-density lipoprotein (LDL). The distribution of TC levels within populations may be useful, and the current study aimed to determine the reference values and specific cut points in a population sample from Mashhad, Iran. Methods: A cross-sectional study was conducted, and data was collected from ۶۵۱۸ individuals (۲۴۸۳ men and ۴۰۳۵ women) aged ۲۵–۶۴ year-old living in Mashhad city using a stratified cluster random sampling design. Reference values for borderline and high TC levels in three age groups were obtained using a percentile regression model. Data were analyzed using Quantreg Software Package and R Ver. ۳.۱.۲ Software. Results: Within the population sample, ۳۸% of the subjects were male and ۶۲% of them were female. The mean and standard deviation for age were found to be ۴۷.۰۷±۹ years and ۴۵.۲۸±۹ years for men and women, respectively. Percentile regression showed that borderline TC levels for men and women aged ۲۵-۶۴ years were ۱۹۸-۲۱۶ mg/dl and ۱۷۶-۲۴۳mg/dl, respectively. The values for defining high TC levels were also ۲۲۶-۲۳۹ mg/dl in men and ۲۰۲ - ۲۷۱ mg/dl in women. Conclusion: Our study estimated reference values and cut points for borderline and high TC separately in both men and women, and age-related sub-groups for a population derived from Mashhad. These findings could be used in local policy plans to allocate health resources.

Reference value, Total cholesterol, Percentile regression, Population