Association between low density lipoprotein cholesterol levels and prostate cancer risk in non-hypertensive middle-aged and older American men.

Often linked with the risk of various diseases, blood low-density lipoprotein cholesterol (LDL-C) levels are typically deemed more favorable when lower. The objective of this investigation is to elucidate the link between blood LDL-C levels and the risk of prostate cancer (PCa) in middle-aged and older men without hypertension in the United States. Utilizing continuous data from the National Health and Nutrition Examination Survey (NHANES) database spanning 2003-2010, a selection of 1,223 non-hypertensive men aged ≥ 40 years was made from a pool of 41,156 participants, ensuring no missing information. Regression analyses were employed to investigate the correlation between blood LDL-C levels and the PCa risk, while identifying potential inflection points indicative of threshold effects. Additionally, we scrutinized the linkage between cholesterol-lowering prescription drug usage and PCa. In our study of 2,224 participants, we found no significant correlation between blood LDL-C levels and the PCa risk after adjusting for confounding variables (Odds Ratio = 0.99; P-value > 0.05). However, upon conducting a subgroup analysis, we discovered a meaningful correlation between lower blood LDL-C levels and an increased PCa risk in the non-hypertensive population (Odds Ratio = 0.99; P-value < 0.05). Meanwhile, we identified a threshold effect and a tipping point at an LDL-C levels of 67 mg/dl. Furthermore, a significant correlation was identified between cholesterol-lowering prescription drug usage and a heightened PCa risk in the non-hypertensive population (Odds Ratio = 18.87; P-value < 0.05; P for interaction < 0.05). Our results indicate that in non-hypertensive middle-aged and older men residing in the United States, lower blood LDL-C levels are not necessarily better and the PCa risk escalates when blood LDL-C levels drop below 67 mg/dl, which may guide early screening and prognosis of PCa in specific populations. This finding calls for further validation via larger sample sizes and a more in-depth analysis of PCa history.