This cross-sectional analysis used data from the CDC’s 2005 ~ 2020 National Health and Nutrition Examination Survey (NHANES) (15). NHANES is a nationally representative survey that uses a stratified, multistage probability sampling design to assess the health and nutritional status of noninstitutionalized Americans (16). Data collection includes household interviews, physical examinations, and laboratory tests at mobile examination centers (MECs), ensuring comprehensive health assessments. The survey collects data on a wide range of variables, including demographic information, health conditions, lifestyle behaviors, and dietary intake, which are crucial for understanding health trends across the population. The ethical clearance for this study follows the protocols established by the NHANES program, which is conducted by the National Center for Health Statistics (NCHS). The NHANES procedures are reviewed and approved by the Ethics Review Board of the NCHS. All participants in NHANES provide written informed consent before participation, ensuring compliance with ethical guidelines. As our study is a secondary analysis of publicly available NHANES data, further Institutional Review Board (IRB) approval is not required (17). NHANES data is freely available on the NHANES website.¹ Our study included interviewees aged 20 and over. We excluded pregnant women and individuals with missing data on the PHQ-9 questionnaire, dietary magnesium intake, and covariates.

Depression symptoms were assessed using the PHQ-9, a validated, dependable, and useful measure that combines the DSM-IV diagnostic criteria for depression and is appropriate for use in both clinical and research contexts (18). Participants rated each item based on their experiences in the 2 weeks preceding the questionnaire, with response categories scored as follows: 0 (not at all), 1 (a few days), 2 (more than half of the days), and 3 (almost every day). The total score varies between 0 and 27. In line with prior research, we classified the participants’ PHQ-9 scores as <10 (with no depression) or ≥10 (with depression) for this study (19).

Dietary data, including total energy, carbohydrate, and magnesium levels, were gathered during two 24-h dietary recalls. The first dietary recall interview was held at the Mobile Examination Center (MEC), and the second was completed over the phone after 3–10 days. Participants were asked to recall all foods and beverages ingested within the first 24 h before the interview (from midnight to midnight). Throughout both interviews, participants were given a set of measuring instructions and a food model booklet to help them report food quantities (20). The average values for total calories, carbohydrate, and dietary magnesium intake were computed using 24-h recall data. The 24-h dietary supplementation session included an interview on the use of nutritional supplements and over-the-counter antacids. The average daily consumption of dietary supplements was calculated by adding all supplemental nutrients and dividing by 30. Dietary magnesium intake was calculated using the average value, and total magnesium intake was defined as the sum of dietary magnesium intake and average daily supplement intake. Subjects were assigned to quintiles based on their dietary magnesium intake.

Based on the research (21–24), age, sex, marital status, race/ethnicity, education level, family income, smoking status, hypertension, diabetes, stroke, coronary heart disease, body mass index (BMI), caloric intake, and carbohydrate intake were all considered. Race and ethnicity were classified as White, Black, or Other. Marital status was defined as married, living with a partner, or living alone. There were two schooling levels: ≤12 years and >12 years. A US government research (25) categorized family income into three categories based on the poverty income ratio (PIR): low (PIR ≤ 1.3), intermediate (PIR > 1.3 to 3.5), and high (PIR > 3.5). According to prior research, the smoking status was classified as never smokers (fewer than 100 cigarettes smoked), current smokers, and former smokers (those who quit after smoking more than 100 cigarettes). Past ailments (hypertension, diabetes, stroke, and coronary heart disease) were determined using survey replies as to whether a doctor had ever told the participant about the condition. BMI was estimated using established methods based on weight and height.

The study was meticulously constructed in accordance with the STROBE standards (26). Categorical variables were presented as percentages (%), whereas continuous variables were presented as means (SD) or medians (IQR). To examine differences across groups, single-factor analysis of variance (for normally distributed data), Kruska-Wallis test (for skewed distributed data), and chi-square test (for categorical variables) were applied. Logistic regression models were used to calculate the odds ratios (OR) and 95% confidence intervals (95% CI) for the association between dietary magnesium consumption and depression. Model 1 accounts for sociodemographic factors such as age, gender, race/ethnicity, marital status, education level, and household income. Model 2 adjusted for covariates with p-values <0.05 in univariate analysis and sociodemographic parameters. Model 3 made a full adjustment for sociodemographic variables, smoking status, hypertension, diabetes, stroke, coronary heart disease, body mass index (BMI), calorie consumption, and carbohydrate intake.

Based on the variables adjusted in Model 3, restricted cubic spline (RCS) regression was performed with knots placed at the 5th, 35th, 65th, and 95th percentiles of dietary magnesium intake and divided into four segments to assess linearity and investigate the dose–response curve between dietary magnesium intake and depression.

We used a smooth two-piece logistic regression model to examine the threshold relationship between dietary magnesium consumption and depression after controlling for the factors in Model 3. The inflection point was determined using likelihood ratio tests and bootstrapping resampling.

We analyzed the relationship between dietary magnesium and depression according to gender, age (20–60 years vs. ≥60 years), education level (≤12 vs. >12 years), marital status (married or cohabiting vs. living alone), family income (low vs. medium or high), race, BMI (<25 vs. ≥25 kg/m²), smoking status, hypertension, diabetes, stroke, and coronary heart disease. Heterogeneity among categories was assessed using multivariable logistic regression, and the relationships between subgroups and dietary magnesium intake were investigated using likelihood ratio tests. We conducted sensitivity analyses by removing subjects with excessive energy consumption (<500 or >5,000 kcal/day) to evaluate the robustness of our findings.

Sample size was determined solely on the provided data; therefore, no a priori statistical power estimation was performed. All analyses were conducted using R version 4.2.2² and Free Statistics software version 1.9.2. Descriptive statistics were performed for all participants. A two-tailed p-value of <0.05 was declared significant.

The interviews were completed by 86,844 individuals, 38,453 of whom were under the age of 20. Individuals who met the following criteria were excluded: pregnant women (n = 1,076); missing PHQ-9 questionnaire data (n = 6,809); missing dietary magnesium intake data (n = 1,205); and missing covariate data (n = 4,049). This cross-sectional study included 35,252 NHANES participants from 2005 to 2020. Figure 1 illustrates the detailed inclusion and exclusion processes.

Table 1 presents the baseline characteristics of all participants by quartile of dietary magnesium consumption. A total of 2,964 people (8.4%) experienced depression. The average age of the participants was 49.5 (17.6) years, with 17,589 (49.9%) women and 17,663 (50.1%) men. Those who consumed more magnesium were more likely to be male, married or living with a partner, non-Hispanic White, never smokers, more educated; had a higher family income, a lower prevalence of hypertension, diabetes, stroke, and coronary heart disease and higher energy and carbohydrate consumption.

A univariate analysis revealed significant associations between depression and age, gender, education level, marital status, family income, BMI, smoking status, hypertension, diabetes, stroke, coronary heart disease, caloric intake, and carbohydrate intake (Table 2).

When dietary magnesium consumption was separated into quartiles and potential confounders were controlled for, there was a substantial negative correlation between magnesium intake and depression. In the unadjusted model, the ORs for depression in Q2 (192.5–252.0 mg/day), Q3 (252.1–314.4 mg/day), Q4 (314.5–406.9 mg/day), and Q5 (≥407.0 mg/day) were reduced by 31% (OR = 0.69 [95% CI 0.62, 0.77]), 39% (OR = 0.61 [95% CI 0.54, 0.68]), 54% (OR = 0.46 [95% CI 0.41, 0.52]), and 51% (OR = 0.49 [95% CI 0.43, 0.55]). After adjusting for the variables described in Table 1, the adjusted ORs were 0.83 (95% CI 0.74, 0.93), 0.82 (95% CI 0.72, 0.93), 0.70 (95% CI 0.61, 0.81), and 0.80 (95% CI 0.68, 0.94; p < 0.001; Table 3). Using Q4 as the reference group, in the unadjusted model, persons with low dietary magnesium intake had a 64% higher risk of depression (OR = 1.64 [95% CI 1.48, 1.83]), whereas those with high dietary magnesium intake had a 5% higher risk. After adjusting for the variables described in Table 1, the adjusted ORs were 1.23 (95% CI 1.09, 1.38) and 1.16 (95% CI 1.01, 1.34; Table 4).

After adjusting for various covariates, Figure 2 demonstrates a nonlinear relationship between dietary magnesium intake and the risk of depression. For magnesium intake levels below 366.7 mg/day, each 1 mg increase in magnesium intake is associated with a 0.2% decrease in the risk of depression (OR = 0.998, 95% CI: 0.997–0.999). In contrast, for magnesium intake levels ≥366.7 mg/day, the risk of depression increases by 0.1% for each 1 mg increase in daily magnesium consumption (OR = 1.001, 95% CI: 1.000–1.002; Table 5).

A stratified analysis was performed across multiple subgroups to assess the potential moderating effect of dietary magnesium on the association with depression. After stratifying by age, gender, race, education level, family income, marital status, smoking status, hypertension, diabetes, stroke, coronary heart disease, and body mass index, a significant interaction was observed between dietary magnesium intake and age (p-value for the likelihood ratio test for the interaction was p = 0.002; Figure 3).

Figure 4 illustrates a nonlinear relationship between magnesium consumption and depression in individuals aged ≥60 years (p < 0.001). And the link is inverse L-shaped. For individuals with magnesium intake ≥270.7 mg/day, each 1 mg/day increase in magnesium consumption is associated with a 0.1% increase in the incidence of depression (Table 6).

After excluding 412 individuals with excessive calorie intake, the relationship between dietary magnesium intake and depression remained unchanged. When compared to the Q4 group (314.5–406.9 mg/day), the adjusted odds ratios for depression were 1.23 (95% CI: 1.09–1.38, p = 0.001) for participants in Q1–Q3 (≤314.4 mg/day) and 1.16 (95% CI: 1.00–1.33, p = 0.049) for participants in Q5 (≥407.0 mg/day; Table 7).