Depression is a common psychological disorder, estimated to affect 279 million persons worldwide (3.7 % of the world's population) (Azizabadi et al., 2022). Its major features are depressed mood, lack of interest, and reduced volitional activity; other symptoms include inappropriate guilt, decreased concentration, sleep and appetite disturbances, and suicidal behavior (Grosso et al., 2014; Yang et al., 2022). Only 50 % of severe cases are effectively treated in developed countries, and <25 % in developing countries, due to the scarce professional attention to depression (Demyttenaere et al., 2004). In addition, both direct and indirect economic costs resulting from depression (i.e., treatments costs, decreased productivity, and lost workdays) are major issues that should be addressed (Sobocki et al., 2006).

Primary prevention requires the identification of modifiable lifestyle factors associated with the depressive symptoms. Epidemiological studies have shown that several factors, including lifestyle, environmental, genetic, socioeconomic, and dietary aspects, are important in the pathogenesis and progression of depression. Notably, several nutrients are reportedly associated with depression, such as vegetables (Liu et al., 2016), fruit (Liu et al., 2016), fish (Li et al., 2016), and dietary fiber (Xu et al., 2018), as well as macronutrients (proteins, carbohydrates, and fatty acids) (Oh et al., 2020), micronutrients (including vitamin B and vitamin C), and folic acid(Seppälä et al., 2012; Wu et al., 2023). Recently, several studies have focused on the relationship between the depressive symptoms and the intake of several fatty acids, including n-3, n-6 polyunsaturated fatty acids (PUFAs) and their ratio, whereas the relationship between this disorder and the intake of other fatty acid types, such as total fatty acids (TFAs), saturated fatty acids (SFAs), and monounsaturated fatty acids (MUFAs), has rarely been studied, and with inconsistent results.

Several cross-sectional, observational, and experimental studies have shown negative relationships between the risk of depressive symptoms and the intake of n-3 and n-6 PUFAs(Beydoun et al., 2015; Lucas et al., 2011; Zhang et al., 2020). In a study by Zhang et al., using the fatty acids intake per total energy intake as the independent variable (mg/kcal/day), it was found that higher intake of n-3 and n-6 PUFAs are associated with a lower risk of depressive symptoms. Additionally, the ratio of n-6 to n-3 showed a negative relationship with the risk of depressive symptoms(Zhang et al., 2020). In a study using mixed-effects models, Beydoun et al. found that the dietary ratio of n-3 to n-6 fatty acids was associated with longitudinal changes in depressive symptoms(Beydoun et al., 2015). A higher ratio was linked to a slower increase in depressive symptoms over time, especially in women. However, few studies have explored the relationship between the intake of TFAs, SFAs, MUFAs, and PUFAs with depressive symptoms, and the results are inconsistent(Sánchez-Villegas et al., 2011; Vagena et al., 2019). In a follow-up study of 12,059 Spanish university graduates over an average of 6.1 years, Sánchez-Villegas et al. found no significant association between the TFAs and SFAs intake and the risk of new-onset depression(Sánchez-Villegas et al., 2011). Another study, however, found that SFAs intake increased the risk of depression, although the dose-response relationship was not significant(Sabião et al., 2024).

Additionally, dividing fatty acid intake by energy intake has often been used as an independent variable in previous studies(Dong et al., 2020; Zhang et al., 2020). Although this method offers certain advantages in controlling energy intake variability, it also presents drawbacks. Primarily, relying solely on energy ratios can misrepresent nutrient intake, especially when energy needs significantly vary across different populations. For instance, the same ratio might mean different absolute nutrient intakes at various total energy intake levels(Willett et al., 1997). Additionally, while energy-adjustment methods take total energy intake into account, they might not fully control the impact of energy intake on health outcomes. In some scenarios, total energy intake itself is a crucial factor, and the additional introduction of total energy intake potentially influences the results(Kipnis et al., 1993; Willett et al., 1997). Therefore, this study used the nutrient residual and multi-nutrient density models to investigate the relationship between the depressive symptoms and the intake of different types of fatty acids. The nutrient residual model generates residuals of nutrient intake adjusted for energy, enabling a more accurate assessment of the relationship between specific nutrients and health outcomes. This model allows comparisons across different levels of energy intake, enhancing the universality and comparability of research findings(Hantikainen et al., 2022; Willett et al., 1997). The multi-nutrient density model, considering nutrient density and total energy intake, better accounts for individual energy needs variances, like differences in body size, weight, height, gender, and age, thus more effectively controlling for confounding effects of energy intake(Okereke et al., 2012; Willett et al., 1997).