June 13, 2024

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Dietary niacin intake in relation to depression among adults: a population-based study | BMC Psychiatry

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Study population

This cross-sectional study analyzed data from the NHANES 2007–2016, performed by the Centers for Disease Control and Prevention. The NHANES is a series of cross-sectional, stratified, multi-stage probability surveys for the representative non-institutionalized US civilians to evaluate the health and nutritional status of children and adults. NHANES collects a variety of health-related data, including demographics, diet, physical examination, and laboratory tests. All NHANES study protocols were approved by the ethical review committee of the National Centre for Health Statistics. Also, NHANES obtained the written informed consent of all participants. Methodological details and survey design of the NHANES are publicly available at https://www.cdc.gov/nchs/nhanes/index.htm.

To ensure a high degree of consistency across survey variables and to ensure adequate study power, we combined data from NHANES 2007–2016 into our analyses, which obtained 50,588 participants, and we restricted our analyses to adults aged 20 years and older. Pregnant women and participants who lacked data on depression, dietary niacin intake, covariates, or weight were excluded (Fig. 1).

Fig. 1
figure 1

Inclusion and exclusion flow chart

Depression classification

In NHANES, the DSM-V-based nine-item Patient Health Questionnaire (PHQ-9) was used to assess depression, a reliable and valid diagnostic tool for examining depression in clinical work and related research settings [13, 14]. DSM-IV based symptom criteria for the nine-item instrument “not at all,“ “several days,“ “more than half the days,“ and “nearly every day” were given a score from 0 to 3, respectively. The scores of each participant were summed to obtain a total score ranging from 0 to 27. Consistent with previous studies, this study defined depression as a PHQ-9 total score ≥ 10, a threshold that has been clinically verified with a sensitivity of 88% and specificity of 88% and was commonly used to define depression in clinical and epidemiological studies [15,16,17].

Dietary niacin assessment

Data on dietary niacin intake were collected through 24-hour recall survey. The survey is a retrospective dietary assessment method that provided detailed information on all dietary and beverage consumption in 24-hour period. For each individual, the intake of nutrients from each food or beverage, including niacin intake, were calculated via the US Department of Agriculture’s Food and Nutrient Database for Dietary Studies [18]. Detailed dietary interview methods can be found in the NHANES dietary interview procedure manual [19]. In keeping with previous literature, we used the dietary day-one sample weight for weighting, so the first 24-hour dietary data was included in this study for analysis [20,21,22].

Potential covariates

Various potential covariates were included based on the published literature [23,24,25,26]. The present study included the following demographic covariates: age (20–44, 45–59, or ≥ 60 years), sex, race, education level (< high school, high school, >high school), marital status (married, living alone, never married) and family income. The poverty income ratio (PIR) divided family income into three categories: low (PIR ≤ 1.3), medium (PIR > 1.3 ~ 3.5) and high (PIR > 3.5). Data on total energy intake were obtained from 24-hour dietary recall. Body mass index (BMI) was categorized as less than 25, 25 to 30, and more than 30 kg/m2. According to previous descriptions in the literature, drinking status was classified as never, current and former. And smoking status was categorized as “never” (lifetime < 100 cigarettes), “former” (previous history of smoking but no longer smoking at the time of the interview), or “now” (lifetime cigarette use). Physical activity (PA) can be calculated based on the metabolic equivalent (MET) value, activity type, weekly frequency, and duration [27]. We calculated the value of PA according to the following formula: PA (MET-h/wk) = MET × weekly frequency × duration of each physical activity. PA was divided into three categories: no (MET ≤ 1), low (MET > 1 ~ 48), high (MET ≥ 48). History of hypertension or diabetes was evaluated as self-reported physician diagnosis of hypertension or diabetes.

Statistical analysis

In accordance with the requirements of the National Centre for Health Statistics, we weighted the data in our analysis. In this study, we combined five 2-year survey cycles of the consecutive NHANES (2007–2016). A specific 10-year dietary weight was created by taking one-fifth of the 2-year dietary weights according to the analytical guidelines available on the NHANES website [28]. Continuous variables were reported by sample-weighted means (standard error, SE), while categorical variables were described as sample-weighted percentages and frequencies. To compare the differences between depression group and no depression group, t-tests (continuous variables) and Chi square tests (categorical variables) were performed. Multiple logistic regression models were used to estimate odd ratios (ORs) with 95% confidence intervals (CIs) of depression at different quartile of dietary niacin. Model 1 was adjusted for total energy intake. Model 2 was additionally adjusted for age and sex. Model 3 was adjusted for age, sex, race, marital status, education, family income, smoking, drinking, physical activity, BMI, hypertension, diabetes, energy, n-3 fatty acids, n-6 fatty acids, folate and zinc.

. We also conducted subgroup analyses to explore whether there were other confounding factors that might influence the association between niacin intake and depression. To assess the robustness of the results of our analysis, we excluded participants with extreme energy intake (consuming < 500 or > 5000 kcal per day) for the sensitivity analysis. Furthermore, restricted cubic spline (RCS) regression was used to investigate the nonlinear relationship between dietary niacin intake and depression. After adjusting for all potential confounding variables, we used a two-piece-wise logistic regression model with smoothing to explore the threshold for the association between dietary niacin intake and depression. Inflection points were identified by using likelihood-ratio test and the bootstrap resampling method. All statistical analysis was conducted by using R software (version 4.2.1). Two-sided p values < 0.05 was considered statistically significant difference.


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