With over 35 billion people affected globally, depression has emerged as a major public health concern. It is also one of the main causes of disability and low quality of life (1–3).

It’s worth noting that the frequency of adult depression in the U.S. is increasing each year, affecting about 8% of adults in the U.S., and is higher in women than in men (4). A high incidence, a high clinical cure rate but a low treatment acceptance rate and a high relapse rate are the hallmarks of depression as a mental illness. Along with cognitive abnormalities that could interfere with day-to-day learning and work, the patient may also experience hallucinations and, in extreme circumstances, suicidal thoughts (5, 6). Depressed moods may cause immune, endocrine and neurological dysfunction in the body, which can increase susceptibility to disease and lead to death (6). According to a recent meta-analysis, depression raised the probability of dying by 50% (7). In addition, depression not only reduces work efficiency and productivity, but also costs the global economy $1 trillion each year (8). Studies in the United States have found that the economic burden of depression is 1.6 percent of gross domestic product. However, current treatment regimens remain inadequate for some patients, and some may experience intolerable side effects, making the discovery of new depression-related bioindicators crucial for the prevention and treatment of depression. Many studies have shown that the pathogenesis of depression is closely associated with inflammation, neuroimmune dysfunction, and abnormalities in lipid metabolism (9–12). Previous findings on the association of biomarkers in lipid metabolism with depression have however been controversial, with some studies reporting that Triglycerides (TG) have a positive correlation with the likelihood of developing depression, while low-density lipoproteins (LDL-C), total cholesterol (TC), and high-density lipoproteins (HDL-C) have a negative correlation (13–16), In contrast, Raised HDL-C levels were substantially positively correlated with depression in both sexes, according to a cross-sectional study (17). Jane E. Persons et al. concluded from a meta-analysis that there was a U-shaped relationship between LDL and depression when LDL was used as a continuous variable (18). Non-HDL-C mainly contains cholesterol from all atherogenic lipoprotein particles, apolipoproteins, very low-density lipoprotein cholesterol (VLDL-C), and IDL-C, and relevant studies have demonstrated that the major components contained within non-HDL-C are linked to an increased risk of suffering from depression (19).

Therefore, the development of newer and more reliable lipid parameters is necessary for the prediction and management strategies of depression. The ratio of non-HDL-C to HDL-C (NHHR) is a newly discovered lipoprotein ratio that is known to assess atherosclerosis and blood predictors of cardiovascular disease risk (20). To date, Reports evaluating the connections between NHHR and depression are nonexistent.

Our investigation’s primary goal was to examine the relationship between NHHR and the prevalence of depression in participants from 2005-2018 using data from the National Health and Nutrition Examination Survey (NHANES). We postulated that elevated NHHR is connected to increased prevalence of depression.

In our cross-sectional study of 29,561 adult participants, we found that the likelihood of participants developing depression increased as the NHHR index rose. A linear relationship between NHHR index and depression was demonstrated using smooth curve fitting. In the subgroup analyses and interaction tests conducted, we hypothesized that two stratification factors, BMI <25 kg/m2 and absence of sleep disorders, may influence the relationship between NHHR and the prevalence of depression.

This is the only study that we are aware of that evaluates the relationship between NHHR and higher rates of depression. Previous studies have discussed associations between depression and other biomarkers. The association between relative adiposity, an indicator of obesity, and depression was found to be most significant in the US adult population in a cross-sectional study conducted by Xianlin Zhu et al. (23). Depression has also been reported to be associated with lymphocyte to HDL ratios, leading to the suggestion that immune dysfunction or inflammatory factors may be a key contributor to depression (24). NHHR, as an emerging biomarker, has received much attention for its regulation of diseases such as atherosclerosis, diabetes, kidney stones, and periodontitis. Despite the lack of previous studies describing the relationship between NHHR and psychiatric disorders, there have been many reports of NHHR-related markers, including non-HDL, TC, HDL, apolipoproteins, and low-density lipoproteins. Non-HDL cholesterol is the sum of all kinds of lipoprotein cholesterol in the blood except HDL cholesterol, and relevant research investigations have found that apolipoprotein (b) and HDL, the main components of non-HDL cholesterol, are the main lipid metabolism indexes constituting atherosclerosis, and that atherosclerosis is prone to cause endothelial function damage at the beginning, and increase in vascular oxidative stress, which further causes nitric oxide-dependent diminished vasodilatory function, which in turn causes major depressive disorder (25–28). Numerous investigations have revealed that lower levels of total cholesterol, LDL and non-HDL increase the risk of depression (15, 29–31). It has been suggested that low plasma cholesterol levels can reduce the synthesis of neuromodulators such as steroids, which can lead to depressed mood (32, 33). In a cross-sectional study of the relationship between lipids and depressive episodes in postmenopausal women, it was found that after quintiles of HDL-C and LDL-C were used as continuous variables, it was concluded that lower concentrations of HDL-C and LDL-C were associated with the risk of developing depression (34). Xianlin Zhu et al. analyzed the positive association between non-HDL-C and depression in 42,143 subjects in a cross-sectional study, and the relationship was more significant in men (35). In view of the above relationship between each of the lipid indicators of depression, we believe that it is necessary for the study of the association between NHHR and depression. Specifically, the results of our subgroup analyses showed that age, gender, race, smoking, alcohol consumption, PIR, coronary heart disease, hypertension, diabetes mellitus, and stroke had no dependence on the positive correlation between NHHR and depression (P for interaction > 0.05), and the baseline characterization of participants as well as the smoothed curve fitting showed that, compared with the no depression group, subjects with depression subjects had a more significant association with NHHR and that for each unit increase in NHHR, subjects were 23% more likely to have depression. Neurosteroids refer to a class of endogenous steroids synthesized from cholesterol in the brain and nervous system. They are modulators involved In emotion, cognition, etc (36–38). Ramirez et al. found that the concentration of the neurosteroid pregnenolone in the hypothalamus was negatively correlated with BMI in animal models. That is, when BMI levels are low, they promote neurosteroid production and induce psychiatric disorders (39). Interestingly, BMI level was associated with changes in brain structure, with an inverse correlation with nucleus accumbens and insula volume in obese patients (BMI > 29.9kg/m²) compared with normal or underweight individuals (40, 41). The insula has been shown to play an important role in depression and cognitive function. Lidia Łapińska et al. found a positive association with insula volume in women with BMI<25 kg/m². However, it was negatively correlated with Beck Depression Inventory (BDI) score (42). This was consistent with our observation that there was a positive association between NHHR and depression in people with BMI<25 kg/m² (OR=1.16, 95%CI: 1.07-1.26, P < 0.01).

Our study has a number of strengths; firstly, our data came from having a large, accurate and reliable NHANES database, and secondly, we adjusted for multiple confounding variables and performed smoothed curve fitting and subgroup analyses to validate the stability of our results and to more accurately analyze the effects of different single factors on the association between NHHR and depression. However, this paper also has limitations. First, because this paper is a cross-sectional study design, It is unable to elucidate the causal connection between NHHR and depression, and longitudinal studies with larger sample sizes are needed in the future. Second, even though we took some probable covariates into account, we are unable to totally rule out the impact of additional potential confounders. Finally, in the future, we need to further analyze the mechanism behind this correlation through experiments.

As a result, our initial research suggests that NHHR could be a reliable independent indicator of the risk of developing depression. Large sample sizes and more prospective research are still required to confirm our findings in the future.