Association of dietary niacin intake with all-cause and cardiovascular mortality in the general population

Association of dietary niacin intake with all-cause and cardiovascular mortality in the general population | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Association of dietary niacin intake with all-cause and cardiovascular mortality in the general population Zikai Song, Dayong Deng, Haidi Wu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4536509/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Dietary niacin, a vital nutrient needed for the metabolism of mitochondrial energy, has been linked to nonalcoholic fatty liver disease and cancer mortality. There is, however, little information available about how dietary niacin intake affects mortality risk in the general population. Therefore, our aim was to investigate the relationship between dietary niacin consumption and all-cause and cardiovascular mortality in the general population. 39428 participants from the National Health and Nutrition Examination Survey (NHANES) 1999-2008 were analyzed. Multivariate Cox proportional hazards regression models, restricted cubic splines (RCS), trend tests, subgroup analysis and inflection point analysis were employed. Over a median follow-up period of 110 months, all-cause mortality accounted for 15.1% of cases, and cardiovascular mortality accounted for 3.387%. During Cox proportional hazards regression analysis, no linear trend was observed between dietary niacin intake and all-cause (P for trend = 0.001) or cardiovascular mortality (P for trend = 0.008) after adjusting for confounding factors. RCS revealed a non-linear association between dietary niacin intake and all-cause mortality (Non-linear P=0.001), but linear association between dietary niacin intake and cardiovascular mortality (Non-linear P = 0.384) when 99.9% of the data was shown. In the inflection point analysis, the HR of all-cause mortality was 0.995 (95% CI:0.991–0.995, P = 0.039) in general population with dietary niacin intake of <54.6 mg/day and 1.007 (95% CI:0.993–1.020, P = 0.296) in general population with dietary niacin intake of ≥54.6 mg/day. The effect of dietary niacin intake was consistent across most subgroups in terms of all-cause and cardiovascular mortality, with no significant interaction with randomized factors (all-cause mortality: P for interaction = 0.047–0.719, cardiovascular mortality: P for interaction = 0.257–0.784). Dietary niacin intake was nonlinearly associated with all-cause mortality but linearly associated with cardiovascluar mortality in general population of United States. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research dietary niacin mortality general population Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Niacin, also known as nicotinic acid or vitamin B3, serves as a precursor in the synthesis of the pyridine coenzymes nicotinamide adenine dinucleotide (NAD) and nicotinamide adenine dinucleotide phosphate (NADP). These coenzymes play pivotal roles in numerous cellular metabolic reactions, energy metabolism, and redox processes 1,2 . Niacin facilitates the conversion of nutrients into energy, the synthesis of cholesterol and fats, DNA creation and repair, and antioxidant effects 1 . Dietary sources of niacin include a variety of whole and processed foods, with enriched packaged foods, meat, poultry, and fatty fish like tuna and salmon being the richest sources, followed by nuts, legumes, and seeds. A prospective population-based study suggests that dietary niacin intake could potentially offer protection against Alzheimer’s disease and age-related cognitive decline 3 . Insufficient dietary niacin levels may impair oxidative phosphorylation and disrupt mitochondrial respiration 4 . Physiological supplementation of nicotinic acid (15–20 mg/day) and nicotinamide (300 mg/day) has been found effective in the treatment of classic pellagra 5,6 . However, when administered at higher doses, these forms of niacin exhibit diverse additional pharmacological effects, ranging from anti-dyslipidemic properties to anti-inflammatory actions 7,8 . Several trials have demonstrated the anti-inflammatory potential of niacin, particularly in conditions like acute coronary syndrome, sepsis, and lung fibrosis 9 . Cardiovascular disease (CVD), type 2 diabetes, and cancer collectively contribute to nearly half of all global deaths, as documented by the World Health Organization 10–12 . These diseases garner significant attention due to their detrimental impact on health, leading to considerable suffering, disability, and substantial economic burdens 13 , ultimately resulting in increased mortality rates. Prior studies have revealed that a mere 1 mg/d escalation in dietary niacin intake correlates with a 2% decrease in the incidence of new-onset hypertension among individuals with daily niacin consumption below 15.6 mg 14 . Elevated dietary niacin levels have shown a positive association with type 2 diabetes in the United States adult population (Ke等 2022), while increased dietary niacin intake has been linked to reduced mortality among cancer patients 15 . However, there are rare studies examining the association between dietary niacin intake and all-cause and cardiovascular mortality in the general population. Therefore, the relationship between dietary niacin intake and all-cause and cardiovascular mortality in adults was assessed with data from the NHANES to refine this study in the general population. Based on the nutritional patterns found in this population, we hypothesized that there was negative correlation between dietary consumption of niacin and mortality. We also conducted subgroup analyses to assess possible effect modification of the association between dietary niacin intake and mortality. Furthermore, the dose–response correlation between dietary niacin intake and mortality was also described. Limited research has explored the link between dietary niacin intake and overall mortality, including deaths related to cardiovascular causes, within the general population. To address this gap, the present study aimed to investigate the potential connection between dietary niacin intake and both all-cause and cardiovascular mortality among adults, utilizing data from the National Health and Nutrition Examination Survey (NHANES) to enhance the scope of investigation. In light of the dietary habits observed in this sample, our hypothesis suggested a negative correlation between niacin consumption and mortality risks. Subgroup analyses were additionally performed to evaluate any potential modifications to this association. Moreover, the study sought to establish a dose-response relationship between dietary niacin intake levels and mortality outcomes. Materials and methods Study population This study utilized data from NHANES, a comprehensive survey representing nutrition and health status across the United States (https://wwwn.cdc.gov/nchs/nhanes/Default.aspx) and adhered to The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.. NHANES received approval from the NCHS Research Ethics Review Board. Our investigation into the relationship between dietary niacin intake and all-cause, as well as cardiovascular mortality, was based on NHANES data spanning from 1999 to 2018. All participants provided written informed consent, and the research protocol received approval from the NCHS Research Ethics Review Board. Exclusions from the study comprised the following patient groups: (1) individuals under 20 years of age, (2) pregnant individuals, (3) individuals with missing data on dietary niacin intake, (4) individuals with missing death data, and (5) individuals with missing covariates information. The final study population included 39,428 participants, and the selection process is depicted in Figure 1. Data collection The analysis incorporated the following covariates based on existing literature: age, gender, race and ethnicity, educational attainment, marital status, household income, body mass index (BMI), vigorous physical activity, diabetes status, smoking habits, alcohol consumption patterns, presence of hypertension, CVDs, daily calorie intake, protein intake, carbohydrate intake, fat intake, and use of dietary supplements 16,17 . Within the NHANES dataset, self-reported race and ethnicity information was obtained through responses to survey queries on racial background and Hispanic ethnicity. Participant classification aligned with NHANES conventions, encompassing four racial and ethnic groupings: Non-Hispanic Asian, Non-Hispanic Black, Mexican American, and Others (incorporating multiracial individuals). Educational attainment was stratified into three categories: below 9th grade, 9th-12th grade, and beyond 12th grade. Marital status was delineated into two groups: Married or cohabiting, and Independent living (comprising widowed, divorced, separated, or never married individuals). Following the criteria utilized by U.S. government entities for reporting NHANES data on dietary and health metrics, family income was classified into three tiers utilizing the family poverty income ratio: low income (≤1.3), medium income (>1.3 to 3.5), and high income (>3.5). Physical activity levels (PA) were determined using the formula: PA (MET-h/wk) = MET × weekly frequency × activity duration, categorizing physical activity into two groups: vigorous activity (MET ≥ 48) and non-vigorous activity (MET < 48). The smoking status was classified into three distinct groups: Never smoked (or smoked <100 cigarettes), Current smoker (currently smoking and having consumed a minimum of 100 cigarettes), and Former smoker (previously smoked at least 100 cigarettes but has since ceased). Alcohol consumption status was characterized by individuals consuming a minimum of 12 alcoholic drinks annually. Hypertension was diagnosed based on a history of physician-diagnosed hypertension, an average systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg, or the current utilization of antihypertensive medication. Diabetes was diagnosed based on a history of physician-diagnosed diabetes, a hemoglobin A1c level ≥6.5%, fasting glucose level ≥7.0 mmol/l, two-hour oral glucose tolerance tests (OGTT) blood glucose ≥11.1 mmol/l, or current utilization of diabetes medication or insulin. The presence of cardiovascular disease was identified through participants’ self-reported history of congestive heart failure, angina, heart attack, coronary heart disease, or stroke. Prior to the interview at the Mobile Examination Center (MEC), participants underwent a dietary recall interview to provide details on their 24-hour nutritional intake, encompassing total dietary calories, protein, carbohydrates, and fats. The use of dietary supplements was ascertained through inquiries regarding nutritional supplements and medications taken in the preceding month. Clinical outcomes The primary outcome assessed in this study encompassed all-cause and cardiovascular mortality. The follow-up period initiated on the examination date and continued until either the individual’s date of death or the termination of the mortality surveillance period (December 31, 2019). Statistical analysis The collected data from all patients underwent descriptive statistical analysis. Categorical variables are presented as counts and percentages, while normally distributed continuous variables are expressed as means with standard deviation (SD) or as medians with inter quartile range. Statistical comparisons for categorical, normally distributed, and non-normally distributed continuous variables were conducted using the χ² test, one-way ANOVA, and the Kruskal-Wallis test, respectively. An exploratory analysis was carried out, designating Quintile 1 (≤14.79 mg/day) as the reference group due to exhibiting the lowest mortality risk. Through Cox proportional hazards regression, we conducted three distinct multivariate models. The Crude model solely comprised niacin intake. Adjustments were made for variables that, upon inclusion, altered the matched odds ratio by a minimum of 10 percent. The Adjust I model integrated age, gender, race, and education, while the Adjust II model further incorporated adjustments for vigorous activity, calorie intake, protein, carbohydrate, and fat consumption. Initial analysis involved survival assessment using standardized Kaplan-Meier curves. Subsequently, the association between dietary niacin intake and both all-cause and cardiovascular mortality was investigated through multivariate-adjusted Cox restricted cubic spline regression models and a generalized additive model to explore potential nonlinear relationships. In instances where non-linear relationships were detected, we applied two-piece wise linear regression models to elucidate variations in associations around the inflection point. The inflection point value was determined by assessing all potential values and selecting the inflection point with the highest likelihood. Subgroup analyses were performed based on age (<60 or ≥60 years), gender (male or female), coronary heart disease (absent or present), angina (absent or present), heart attack (absent or present), stroke (absent or present), and heart failure (absent or present). Statistical significance was established at a P-value of < 0.05. To assess the reliability of our findings, participants with extreme energy intake (5000 kcal per day) were excluded for sensitivity analyses. All Statistical analyses were conducted using R version 4.0.5 (R Project for Statistical Computing) with the survey package version 4.1-1 and Free Software Foundation statistics software version 1.3. A significance level of P < 0.05 (two-sided) was adopted for all tests to indicate statistical significance. Results Baseline characteristics of study population Over a median follow-up duration of 110 months, there were a total of 5955 deaths attributed to all causes, representing 15.1% of the cases. Among these fatalities, 1860 were related to cardiovascular mortality, encompassing cardiac and cerebrovascular diseases, accounting for 3.387% of cases (see Table 1 ). Baseline patient characteristics, categorized by quartiles of dietary niacin intake (Q), are outlined in Table 1 as follows: Q1: ≤14.79; Q2: 14.80–21.53; Q3: 21.54–30.38; Q4: ≥30.9. Compared to individuals with lower dietary niacin intake, those in the higher niacin intake group were typically younger, male, Non-Hispanic White, had higher educational levels, were married or cohabiting, had higher family incomes, engaged in vigorous physical activity, were former smokers and alcohol consumers, and showed a lower prevalence of comorbidities such as coronary heart disease, angina, heart attack, stroke, and heart failure. Furthermore, the higher niacin intake group demonstrated increased calorie, protein, carbohydrate, and fat intake, along with reduced dietary supplement usage. As dietary niacin intake levels rose, a gradual decrease in both all-cause mortality (20.1% vs. 16.8% vs. 13.8% vs. 9.7%, P < 0.001) and cardiovascular mortality (6.4% vs. 5.4% vs. 4.5% vs. 2.7%, P < 0.001) was observed. Table 1 Characteristics of participants in the NHANES (1999-2018) by categories of dietary niacin intake. Characteristic Niacin Intake, mg/d Total Q1 Q2 Q3 Q4 p - Value ≤14.79 (14.80-21.53) (21.54-30.38) (≥30.9) NO. 39428 9857 9855 9859 9857 < 0.001 Age(year),Mean(SD) 49.9(17.9) 53.2(18.3) 51.6(17.9) 49.6(17.6) 45.1(16.6) < 0.001 Gender,n(%) < 0.001 Male 19783 (50.2) 3040 (30.8) 4200 (42.6) 5330 (54.1) 7213 (73.2) Female 19645 (49.8) 6817 (69.2) 5655 (57.4) 4529 (45.9) 2644 (26.8) Race,n(%) < 0.001 Non-Hispanic White 18486 (46.9) 4200 (42.6) 4628 (47) 4861 (49.3) 4797 (48.7) Non-Hispanic Black 8138 (20.6) 2300 (23.3) 1993 (20.2) 1840 (18.7) 2005 (20.3) Mexican American 6506 (16.5) 1785 (18.1) 1594 (16.2) 1605 (16.3) 1522 (15.4) Others 6298 (16.0) 1572 (15.9) 1640 (16.6) 1553 (15.8) 1533 (15.6) Education level(year),n(%) < 0.001 12 20355 (51.6) 4413 (44.8) 4981 (50.5) 5421 (55) 5540 (56.2) Marital status,n(%) < 0.001 Married or living with a partner 23829 (60.4) 5414 (54.9) 6041 (61.3) 6251 (63.4) 6123 (62.1) Living alone 15599 (39.6) 4443 (45.1) 3814 (38.7) 3608 (36.6) 3734 (37.9) Family income, n (%) < 0.001 Low 11770 (29.9) 3541 (35.9) 2925 (29.7) 2631 (26.7) 2673 (27.1) Medium 15092 (38.3) 3829 (38.8) 3860 (39.2) 3762 (38.2) 3641 (36.9) High 12566 (31.9) 2487 (25.2) 3070 (31.2) 3466 (35.2) 3543 (35.9) Body mass index(kg/m 2 ),Mean(SD) 29.1(6.8) 29.3(7.0) 29.0(6.8) 29.1(6.8) 28.8(6.8) < 0.001 Vigorous activity,n(%) 27854 (70.6) 6228 (63.2) 6799 (69) 7106 (72.1) 7721 (78.3) < 0.001 Smoking status,n(%) < 0.001 Never 21013 (53.3) 5478 (55.6) 5376 (54.6) 5244 (53.2) 4915 (49.9) Current 10040 (25.5) 2333 (23.7) 2549 (25.9) 2643 (26.8) 2515 (25.5) Former 8375 (21.2) 2046 (20.8) 1930 (19.6) 1972 (20) 2427 (24.6) Alcohol drinking status,n(%) < 0.001 Non-drinkers 10533 (26.7) 3602 (36.5) 2838 (28.8) 2378 (24.1) 1715 (17.4) Drinkers 28895 (73.3) 6255 (63.5) 7017 (71.2) 7481 (75.9) 8142 (82.6) Hypertension,n(%) 11437 (29.0) 3259 (33.1) 3050 (30.9) 2797 (28.4) 2331 (23.6) < 0.001 Diabetes,n(%) 4781 (12.1) 1370 (13.9) 1303 (13.2) 1187 (12) 921 (9.3) < 0.001 Coronary heart disease,n(%) 1656 ( 4.2) 478 (4.8) 432 (4.4) 422 (4.3) 324 (3.3) < 0.001 Angina,n(%) 1143 ( 2.9) 358 (3.6) 306 (3.1) 282 (2.9) 197 (2) < 0.001 Heart attack,n(%) 1658 ( 4.2) 509 (5.2) 441 (4.5) 394 (4) 314 (3.2) < 0.001 Stroke,n(%) 1436 ( 3.6) 519 (5.3) 388 (3.9) 310 (3.1) 219 (2.2) < 0.001 Heart failure,n(%) 1238 ( 3.1) 414 (4.2) 360 (3.7) 264 (2.7) 200 (2) < 0.001 Calorie consumption, Median(IQR) 1941.0 (1429.0, 2610.2) 1279.0 (962.3, 1622.0) 1763.0 (1425.2, 2166.0) 2160.0 (1754.0, 2659.8) 2864.0 (2280.0, 3607.0) < 0.001 Protein consumption, Median(IQR) 73.3 (52.0, 100.6) 42.8 (31.6, 54.9) 64.4 (52.8, 77.9) 83.9 (69.6, 100.6) 117.6 (94.9, 147.2) < 0.001 Carbohydrate consumption, Median(IQR) 234.2 (168.5, 317.9) 163.5 (118.7, 215.9) 216.3 (166.6, 275.9) 257.0 (198.0, 326.3) 327.2 (250.5, 424.2) < 0.001 Fat consumption, Median(IQR) 71.8 (47.9, 102.8) 46.0 (30.4, 63.9) 66.4 (47.9, 88.2) 81.7 (58.9, 108.4) 106.0 (76.2, 143.2) < 0.001 Dietary supplements,n(%) 19951 (50.6) 4977 (50.5) 5108 (51.8) 5096 (51.7) 4770 (48.4) < 0.001 Outcomes All-cause mortality, n (%) 5955 (15.1) 1977 (20.1) 1660 (16.8) 1360 (13.8) 958 (9.7) < 0.001 Cardiovascular mortality, n (%) 1860 ( 4.7) 628 (6.4) 529 (5.4) 441 (4.5) 262 (2.7) < 0.001 Kaplan–Meier survival analysis curves for all‑cause and cardiovascular mortality according to dietary niacin intake Over a median follow-up of 110 months, there were 5955 cases of all-cause mortality and 1860 cases of cardiovascular mortality. The mortality rates among different dietary niacin intake groups are depicted in Fig. 2 . Significant disparity in mortality was evident within these groups (All-cause mortality: P < 0.0001 for the log-rank test; cardiovascular mortality: P < 0.0001 for the log-rank test) across the entire study population (Figs. 2 A, 2 B). Associations of dietary niacin intake with all‑cause and cardiovascular mortality The Cox proportional hazard analysis indicated a notable correlation between dietary niacin intake and both all-cause and cardiovascular mortality in the unadjusted model [All-cause mortality: HR (95% CI) 0.98 (0.98, 0.98), P < 0.001; cardiovascular mortality: HR (95% CI) 0.98 (0.97, 0.98), P < 0.001], and the adjusted models [Adjusted I: All-cause mortality: HR (95% CI) 0.99 (0.99, 1.00), P < 0.001; cardiovascular mortality: HR (95% CI) 0.99 (0.99, 1.00), P < 0.001; Adjusted II: All-cause mortality: HR (95% CI) 1.00 (0.99, 1.00), P = 0.076; cardiovascular mortality: HR (95% CI) 0.99 (0.99, 1.00), P = 0.047], treating dietary niacin intake as a continuous variable(Table 2 ). In the unadjusted and Adjust I models, positive trends were noted between dietary niacin intake and both all-cause and cardiovascular mortality (Table 2 , both P for trend < 0.05). These findings were consistently observed in the multivariate Cox proportional hazard analysis of dietary niacin intake concerning all-cause and cardiovascular mortality in Model I (Table 2 , all-cause mortality: P for trend < 0.001; cardiovascular mortality: P for trend < 0.001) and Model II (Table 2 , all-cause mortality: P for trend = 0.001; cardiovascular mortality: P for trend = 0.008). As the multivariate Cox proportional hazard analysis indicated a non-linear relationship between baseline dietary niacin intake and both all-cause and cardiovascular mortality, restricted cubic splines analysis was utilized for more in-depth exploration. The adjusted restricted cubic spline plots revealed non-linear relationships between dietary niacin intake and both all-cause and cardiovascular mortality (both Non-linear P < 0.05). Notably, the relationship between dietary niacin intake and cardiovascular mortality lost its non-linear nature when only 99.9% of the data was considered (Non-linear P = 0.384)(Fig. 3 ). Table 2 HR(95% CI) for outcomes across groups of dietary niacin intake. Crude Model I Model II HR(95%CI) p -Value HR(95%CI) p -Value HR(95%CI) p -Value All-cause mortality Niacin intake Continuous 0.98(0.98, 0.98) < 0.001 0.99 (0.99,1.00) < 0.001 1.00(0.99,1.00) 0.076 Quartiles Q1 1 1 1 Q2 0.86(0.80,0.91) < 0.001 0.90(0.84,0.96) 0.002 0.92(0.86,0.99) 0.019 Q3 0.70(0.66,0.75) < 0.001 0.86(0.80,0.92) < 0.001 0.88 (0.81,0.96) 0.002 Q4 0.50(0.47,0.54) < 0.001 0.81 (0.75,0.88) < 0.001 0.83(0.75,0.93) 0.001 P for trend < 0.001 < 0.001 0.001 Cardiovascular mortality Niacin intake Continuous 0.98(0.97, 0.98) < 0.001 0.99(0.99−1.00) 0.001 0.99(0.99−1.00) 0.047 Quartiles Q1 1 1 1 Q2 0.86 (0.76,0.96) 0.010 0.91(0.81,1.02) 0.104 0.91(0.81,1.04) 0.161 Q3 0.72 (0.64,0.81) < 0.001 0.89(0.78,1.01) 0.066 0.90(0.78,1.04) 0.162 Q4 0.43(0.38,0.50) < 0.001 0.73(0.63,0.85) < 0.001 0.73(0.60,0.90) 0.003 P for trend < 0.001 < 0.001 0.008 Crude: Unadjusted; Model 1: Age, gender, race,education were adjusted; Model 2: Model 1 + Vigorous activity, hypertension, calorie consumption, protein consumption, carbohydrate consumption and fat consumption were adjusted. The inflection point analysis In the inflection point analysis, the hazard ratio (HR) for all-cause mortality was 0.995 (95% CI: 0.991–0.995, p = 0.039) within the general population with a dietary niacin intake of < 54.6 mg/day (Table 3 ). A 0.5% reduction in the risk of all-cause mortality was observed with each 1 mg/kg rise in daily dietary niacin consumption. No significant association was found between dietary niacin intake and all-cause mortality when the daily intake exceeded 54.6 mg/kg (Table 3 ). The risk of all-cause mortality did not exhibit a further decrease with increased dietary niacin intake. Table 3 Inflection point analysis of the relationship of serum 25(OH)D with TyG. Serum 25(OH)D (nmol/L) Adjusted Model β (95%CI) p -value <59.17 0.995 (0.991,0.999) 0.0397 ≥ 59.17 1.007(0.993,1.020) 0.296 Likelihood Ratio test - 0.001 Subgroup analysis of the association between dietary niacin intake and all‑cause and cardiovascular mortality To evaluate the influence of dietary niacin intake on the primary outcomes, stratification was performed based on age, gender, coronary artery disease, angina, myocardial infarction, stroke, and heart failure (see Fig. 4 and Fig. 5 ). With the exception of the heart failure subgroup (heart failure subgroup: all-cause mortality: P for interaction = 0.047), no significant interactions were observed in most subgroups (other subgroups: all-cause mortality: P for interaction = 0.325–0.719, cardiovascular mortality: P for interaction = 0.257–0.784). Sensitivity Analysis After excluding individuals with extreme energy intake, 38,350 participants remained, and the relationship between dietary niacin intake and all-cause and cardiovascular mortality remained consistent. A significant correlation was found between dietary niacin intake and both all-cause and cardiovascular mortality in the unadjusted model [All-cause mortality: HR (95% CI) 0.98 (0.98, 0.98), P < 0.001; cardiovascular mortality: HR (95% CI) 0.97 (0.97, 0.98), P < 0.001] and the adjusted models [Adjusted I: All-cause mortality: HR (95% CI) 0.99 (0.99, 1.00), P < 0.001; cardiovascular mortality: HR (95% CI) 0.99 (0.98, 0.99), P < 0.001; Adjusted II: all-cause mortality: HR (95% CI) 1.00 (0.99, 1.00), P = 0.044; cardiovascular mortality: HR (95% CI) 0.99 (0.98, 1.00), P = 0.006] when dietary niacin intake was considered as a continuous variable (refer to Table 4 ). In comparison to individuals with lower dietary niacin intake in Q1 (≤ 14.79 mg/day), the adjusted hazard ratio (HR) values for dietary niacin intake and all-cause mortality in Q2 (14.80–21.53 mg/day), Q3 (21.54–30.38 mg/day), and Q4 (≥ 30.9 mg/day) were 0.94 (95% CI: 0.88–1.01, p = 0.113), 0.92 (95% CI: 0.84–1.00, p = 0.045), and 0.88 (95% CI: 0.79–0.99, p = 0.029) (refer to Table 4 ). Likewise, when compared to individuals with lower dietary niacin intake in Q1 (≤ 14.79 mg/day), the adjusted HR values for dietary niacin intake and cardiovascular mortality in Q2 (14.80–21.53 mg/day), Q3 (21.54–30.38 mg/day), and Q4 (≥ 30.9 mg/day) were 0.94 (95% CI: 0.88–1.01, p = 0.113), 0.92 (95% CI: 0.84–1.00, p = 0.045), and 0.88 (95% CI: 0.79–0.99, p = 0.029) (refer to Table 4 ), respectively. Table 4 Sensitivity analysis excluding total calorie consumption 5000 kcal. Crude Adjust I Adjust II HR(95%CI) p -Value HR(95%CI) p -Value HR(95%CI) p -Value All-cause mortality Niacin intake Continuous 0.98(0.98, 0.98) < 0.001 0.99(0.99,1.00) < 0.001 1.0(0.99−1.00) 0.044 Quartiles Q1 1 1 1 Q2 0.86(0.81,0.92) < 0.001 0.91(0.85,0.97) 0.005 0.94 (0.88,1.01) 0.113 Q3 0.71(0.66,0.76) < 0.001 0.86(0.80,0.93) < 0.001 0.92 (0.84,1.00) 0.045 Q4 0.52(0.48,0.56) < 0.001 0.80(0.74,0.87) < 0.001 0.88 (0.79,0.99) 0.029 P for trend < 0.001 < 0.001 0.022 Cardiovascular mortality Niacin intake Continuous 0.97(0.97,0.98) < 0.001 0.99(0.98,0.99) < 0.001 0.99(0.98,1.00) 0.006 Quartiles Q1 1 1 1 Q2 0.86(0.77,0.97) 0.014 0.91(0.81,1.03) 0.132 0.94(0.83,1.07) 0.334 Q3 0.73(0.64,0.82) < 0.001 0.89(0.79,1.02) 0.087 0.94(0.81,1.10) 0.454 Q4 0.45(0.39,0.52) < 0.001 0.73(0.62,0.85) < 0.001 0.78(0.63,0.96) 0.018 P for trend < 0.001 < 0.001 0.054 Crude: Unadjusted; Model 1: Age, gender, race,education were adjusted; Model 2: Model 1 + Vigorous activity, hypertension, calorie consumption, protein consumption, carbohydrate consumption and fat consumption were adjusted. Discussion Our study revealed that a higher intake of dietary niacin is linked to a reduced risk of mortality caused by all reasons and cardiovascular issues. The relationship between niacin consumption and mortality demonstrated a non-linear dose-effect pattern for overall mortality, with a notable inflection point at approximately 54.6 mg per day, while a linear dose-effect pattern was observed for cardiovascular mortality. Both subgroup and sensitivity analyses confirmed the strong association between dietary niacin intake and decreased risks of all-cause and cardiovascular mortality. Our findings indicate that, within an appropriate range, increased niacin consumption is connected to a lower likelihood of mortality from all reasons and cardiovascular causes in the general population. These results support the notion that dietary niacin intake may act as a protective factor against mortality. Recent studies have explored the correlation between dietary niacin intake and disease-related mortality. Wei et al. demonstrated a significant link between adequate niacin intake from food and decreased mortality rates among U.S. adults with diabetes 18 . Jie et al. proposed that a higher dietary niacin intake could be connected to a reduced risk of all-cause mortality in individuals with nonalcoholic fatty liver disease (NAFLD). They observed a 30% decrease in the risk of all-cause mortality for NAFLD participants for every 1 mg/kg increase in daily dietary niacin consumption, particularly for those with a niacin intake of 26.7 mg or higher. Additionally, Hongan et al. discovered a positive association between higher dietary niacin intake and reduced mortality among cancer patients, noting that niacin supplementation contributed to improved cancer mortality outcomes 15 . Nevertheless, few studies have investigated the link between dietary niacin intake and all-cause as well as cardiovascular mortality in the general population. Our study offers a distinctive opportunity to assess the potential relationship between dietary niacin intake and both all-cause and cardiovascular mortality in the general population. This assessment could establish a foundation for further investigations into the effectiveness of niacin in reducing mortality risks. The relationship between dietary niacin consumption and all-cause mortality exhibited a non-linear pattern, specifically L-shaped. The beneficial impact of higher dietary niacin intake on all-cause mortality appeared to plateau among individuals with sufficient niacin levels. More precisely, the risk of all-cause mortality decreased as dietary niacin consumption increased for those with a dietary intake of < 54.67 mg/day, while the reduction in the risk of all-cause mortality ceased in individuals with a dietary niacin intake of ≥ 54.67 mg/day. Sources rich in niacin encompass fish, meat, milk, peanuts, and fortified flour products 19 . Based on the present statistical data analysis, a high-niacin diet appears to play a role in reducing all-cause mortality. Subgroup analysis revealed no significant interactions in various subgroups based on age, gender, coronary artery disease, angina, heart attack, and stroke, except for the heart failure subgroup. Nonetheless, the P-value for interaction was 0.047, approaching the conventional threshold of 0.05. Further investigation is warranted to elucidate the impact of dietary niacin intake on heart failure. The correlation between dietary niacin consumption and cardiovascular mortality followed a linear pattern. The positive impact of higher dietary niacin intake on cardiovascular mortality appeared to diminish with sufficient niacin levels. Analysis of the current statistical data suggests that a high-niacin diet contributes to the prevention of cardiovascular mortality. Subgroup analysis indicated no significant interactions among age, gender, coronary artery disease, angina, heart attack, stroke, and heart failure subgroups. Limited knowledge currently exists regarding the mechanism underlying the association between dietary niacin intake and mortality. We believe that this correlation can be attributed to the capacity of dietary niacin to reduce mortality related to various diseases, including nonalcoholic fatty liver disease, cancer, and diabetes 15,18,20 . Additionally, dietary niacin intake can decrease the risk factors associated with cardiovascular disease. Zhuxian et al. noted that maintaining optimal dietary niacin intake levels could lower the occurrence of new-onset hypertension 14 . Yuong et al. demonstrated that each unit increase in niacin intake was linked to a 3.5% reduction in the risk of diabetes 21 . Furthermore, several trials have highlighted the anti-inflammatory effects of niacin, particularly in acute coronary syndrome 22–24 . Our study has several limitations. Firstly, the dietary information was gathered from one-time recall surveys, potentially inadequately representing an individual’s typical diet and overall niacin intake. Nonetheless, research suggests that 24-hour dietary recalls are a reliable method for evaluation 25,26 . Secondly, the conclusions were drawn from a U.S. adult sample, and generalizing these findings to other populations necessitates further scrutiny. Third, despite the implementation of regression models, stratified analyses, and sensitivity analysis, residual confounding effects stemming from unmeasured or unknown variables could not be entirely eliminated. Lastly, as our study was cross-sectional, causal relationships cannot be inferred. Therefore, these limitations should be taken into account in future research endeavors. Conclusions In conclusion, dietary niacin intake showed a substantial correlation with all-cause and cardiovascular mortality in the general population. Particularly, a non-linear association was evident between dietary niacin intake and all-cause mortality, pinpointing an inflection point at approximately 54.67 mg/day. Furthermore, a linear relationship was identified between dietary niacin intake and cardiovascular mortality. Declarations Author Contribution Zikai Song and Haidi Wu wrote the main manuscript text and Dayong Deng prepared figures and table. All authors reviewed the manuscript. Acknowledgements We gratefully thank Jie Liu of the Department of Vascular and Endovascualr Surgery, Chinese PLA General Hospital for his contribution to the statistical support, study design consultations, and comments regarding the manuscript. This work was supported by the central government of China, Fundamental Research Funds for the Central Universities of China, and the Science and Technology Project of the Education Department of Jilin Province (JJKH20201078KJ). Data Availability The datasets generated and analyzed for the current study are available in the NHANES database (https://www.cdc.gov/nchs/nhanes/index.htm). References Kirkland, J. B. & Meyer-Ficca, M. L. Chapter Three - Niacin. in Advances in Food and Nutrition Research (ed. Eskin, N. A. M.) vol. 83 83–149 (Academic Press, 2018). Tek, C. & Bhalla, S. Vitamin B3, Niacin. in Industrial Biotechnology of Vitamins, Biopigments, and Antioxidants. (Wiley-VCH Verlag GmbH & Co. KGaA, 2016). Morris, M. C. et al. Dietary niacin and the risk of incident Alzheimer’s disease and of cognitive decline. J Neurol Neurosurg Psychiatry 75 , 1093–1099 (2004). Pirinen, E. et al. Niacin Cures Systemic NAD+ Deficiency and Improves Muscle Performance in Adult-Onset Mitochondrial Myopathy. Cell Metab 31 , 1078-1090.e5 (2020). Cao, S., Wang, X. & Cestodio, K. Pellagra, an Almost-Forgotten Differential Diagnosis of Chronic Diarrhea: More Prevalent Than We Think. Nutr Clin Pract 35 , 860–863 (2020). Prakash, R., Gandotra, S., Singh, L. K., Das, B. & Lakra, A. Rapid resolution of delusional parasitosis in pellagra with niacin augmentation therapy. General Hospital Psychiatry 30 , 581–584 (2008). AIM-HIGH Investigators et al. Niacin in patients with low HDL cholesterol levels receiving intensive statin therapy. N Engl J Med 365 , 2255–2267 (2011). Boden, W. E., Sidhu, M. S. & Toth, P. P. The therapeutic role of niacin in dyslipidemia management. J Cardiovasc Pharmacol Ther 19 , 141–158 (2014). Kwon, W. Y. et al. Niacin and Selenium Attenuate Sepsis-Induced Lung Injury by Up-Regulating Nuclear Factor Erythroid 2-Related Factor 2 Signaling. Crit Care Med 44 , e370-382 (2016). World Health Organization. Diabetes. [Internet]. (2021) doi:https://www.who.int/news-room/fact-sheets/detail/diabetes. World Health Organization. Cardiovascular diseases (CVDs). [Internet]. (2021). World Health Organization. Cancer. [Internet]. (2022). Eyre, H. et al. Preventing cancer, cardiovascular disease, and diabetes: a common agenda for the American Cancer Society, the American Diabetes Association, and the American Heart Association. Circulation 109 , 3244–3255 (2004). Zhang, Z. et al. Evaluation of Dietary Niacin and New-Onset Hypertension Among Chinese Adults. JAMA Netw Open 4 , e2031669 (2021). Ying, H. et al. Association between niacin and mortality among patients with cancer in the NHANES retrospective cohort. BMC Cancer 22 , 1173 (2022). Liu, H., Wang, L., Chen, C., Dong, Z. & Yu, S. Association between Dietary Niacin Intake and Migraine among American Adults: National Health and Nutrition Examination Survey. Nutrients 14 , 3052 (2022). Ruan, Z. et al. Association Between Psoriasis and Nonalcoholic Fatty Liver Disease Among Outpatient US Adults. JAMA Dermatol 158 , 745 (2022). Liu, W. et al. Association between dietary vitamin intake and mortality in US adults with diabetes: A prospective cohort study. Diabetes Metab Res Rev 40 , e3729 (2024). Kirkland, J. B. & Meyer-Ficca, M. L. Niacin. Adv Food Nutr Res 83 , 83–149 (2018). Pan, J., Zhou, Y., Pang, N. & Yang, L. Dietary Niacin Intake and Mortality Among Individuals With Nonalcoholic Fatty Liver Disease. JAMA Netw Open 7 , e2354277 (2024). Jiang, Y., Zhang, Z., Zhu, Y., Chai, Y. & Xie, H. Dose-response association between dietary folate and niacin intakes with diabetes among Chinese adults: a cross-sectional study. J Health Popul Nutr 42 , 31 (2023). Benjó, A. M. et al. Accumulation of chylomicron remnants and impaired vascular reactivity occur in subjects with isolated low HDL cholesterol: effects of niacin treatment. Atherosclerosis 187 , 116–122 (2006). Karacaglar, E. et al. The Effects of Niacin on Inflammation in Patients with Non-ST Elevated Acute Coronary Syndrome. Acta Cardiol Sin 31 , 120–126 (2015). Kuvin, J. T. et al. Effects of extended-release niacin on lipoprotein particle size, distribution, and inflammatory markers in patients with coronary artery disease. Am J Cardiol 98 , 743–745 (2006). Knüppel, S., Norman, K. & Boeing, H. Is a Single 24-hour Dietary Recall per Person Sufficient to Estimate the Population Distribution of Usual Dietary Intake? J Nutr 149 , 1491–1492 (2019). Huang, L. et al. U-shaped association of serum uric acid with all-cause mortality in patients with hyperlipidemia in the United States: a cohort study. Front. Cardiovasc. Med. 10 , 1165338 (2023). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4536509","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":319933188,"identity":"3aef0e7a-ef44-4876-bd7f-d8004b51158b","order_by":0,"name":"Zikai Song","email":"","orcid":"","institution":"The First Hospital of Jilin University","correspondingAuthor":false,"prefix":"","firstName":"Zikai","middleName":"","lastName":"Song","suffix":""},{"id":319933189,"identity":"ddee9d52-7974-4bad-8203-42d80e3d0bd0","order_by":1,"name":"Dayong Deng","email":"","orcid":"","institution":"Jilin Provincial Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Dayong","middleName":"","lastName":"Deng","suffix":""},{"id":319933191,"identity":"f58d2fcb-978f-4b9c-a9a6-0dae54b3effa","order_by":2,"name":"Haidi Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIie3RMUvEMBTA8VcKvaXQTSLidwgURGjBr5IsyVKOA0E6CAaEON6qHOhXuOPAOeWBU9VV6HL3DermdJjmcMudNwrmP4XwfjxCAEKhP5pZATCIgRpWlzdTQGUv4/2E/ZBVK6IH1fxOwBEAGq01RnMT7SfZEa4N1zjO7uKFPYg4bxpNoC64Gr0aHzmeCTqQS4LJxLC3MjkzA2klV+mY+QjtmCXPyBWm9vlXInUk0vaGpNRHLjrZO/LkSIIkVwPZ7Cb0pNpumTuikVIYiNpNSFdNDN9IvnBvaQUjprk9Zy8y12nlJdlMLvu+LfjjOy4/v+qSZffYfPTXxel01HqJb7HZflNy4PywWB0+GwqFQv+ib+83dY3ZFbOAAAAAAElFTkSuQmCC","orcid":"","institution":"The First Hospital of Jilin University","correspondingAuthor":true,"prefix":"","firstName":"Haidi","middleName":"","lastName":"Wu","suffix":""}],"badges":[],"createdAt":"2024-06-06 00:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4536509/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4536509/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59965291,"identity":"c8f9edb1-8e87-4716-88b1-c0d534c8c727","added_by":"auto","created_at":"2024-07-10 01:58:13","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":564046,"visible":true,"origin":"","legend":"\u003cp\u003eThe flow diagram of the study.\u003c/p\u003e","description":"","filename":"floatimage1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4536509/v1/37915748c3fcce3cbe838f1e.jpg"},{"id":59966334,"identity":"edaa2b32-599c-4540-97d1-c7024b1103e0","added_by":"auto","created_at":"2024-07-10 02:06:14","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":346179,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival analysis curves for all-cause and cardiovascular mortality. Niacin quartile (Q): Q1:≤14.79; Q2:14.80-21.53; Q3:21.54-30.38; Q4:≥30.9. A Kaplan-Meier analysis for mortality among dietary niacin intake groups in \u003cstrong\u003eA\u003c/strong\u003eall-cause mortality, \u003cstrong\u003eB\u003c/strong\u003e cardiovascular mortality.\u003c/p\u003e","description":"","filename":"floatimage2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4536509/v1/10bfd90047cd0c3e2ae96e97.jpg"},{"id":59965293,"identity":"6bc2b56e-6a5e-4987-b963-0c2d2ef0713b","added_by":"auto","created_at":"2024-07-10 01:58:13","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":304046,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between dietary niacin intake and all-cause and cardiovascular mortality in the general population. \u003cstrong\u003eA\u003c/strong\u003eall-cause mortality, \u003cstrong\u003eB\u003c/strong\u003e cardiovascular mortality. Solid and dashed lines represent the predicted value and 95% confidence intervals. Adjusted for age, gender, race,education, vigorous activity, hypertension, calorie consumption, protein consumption, carbohydrate consumption and fat consumption. Only 99.9% of the data is shown.\u003c/p\u003e","description":"","filename":"floatimage3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4536509/v1/4b780c2e58ca15d55be4e040.jpg"},{"id":59965292,"identity":"c713cf4e-90db-4047-9109-da97dbaca88d","added_by":"auto","created_at":"2024-07-10 01:58:13","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":567884,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis of the association between dietary niacin intake and all-cause mortality in the general population. Adjusted for age, gender, race,education, vigorous activity, hypertension, calorie consumption, protein consumption, carbohydrate consumption and fat consumption.\u003c/p\u003e","description":"","filename":"floatimage4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4536509/v1/62374c0a27d3e0fbd817e5de.jpg"},{"id":59965295,"identity":"db21646a-8e53-4349-84e0-812c46319ae2","added_by":"auto","created_at":"2024-07-10 01:58:14","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":565105,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analysis of the association between dietary niacin intake and cardiovascular mortality in the general population. Adjusted for age, gender, race,education, vigorous activity, hypertension, calorie consumption, protein consumption, carbohydrate consumption and fat consumption.\u003c/p\u003e","description":"","filename":"floatimage5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4536509/v1/c6b96ebcf054de3d4e1cb5c8.jpg"},{"id":76274277,"identity":"fe162854-075a-4525-9347-c61382eed88f","added_by":"auto","created_at":"2025-02-14 09:32:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3450889,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4536509/v1/7f57e1a2-3ba4-40cb-b818-e378c16a36bb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of dietary niacin intake with all-cause and cardiovascular mortality in the general population","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNiacin, also known as nicotinic acid or vitamin B3, serves as a precursor in the synthesis of the pyridine coenzymes nicotinamide adenine dinucleotide (NAD) and nicotinamide adenine dinucleotide phosphate (NADP). These coenzymes play pivotal roles in numerous cellular metabolic reactions, energy metabolism, and redox processes\u0026nbsp;\u003csup\u003e1,2\u003c/sup\u003e.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eNiacin facilitates the conversion of nutrients into energy, the synthesis of cholesterol and fats, DNA creation and repair, and antioxidant effects\u0026nbsp;\u003csup\u003e1\u003c/sup\u003e.\u0026nbsp;Dietary sources of niacin include a variety of whole and processed foods, with enriched packaged foods, meat, poultry, and fatty fish like tuna and salmon being the richest sources, followed by nuts, legumes, and seeds. A prospective population-based study suggests that dietary niacin intake could potentially offer protection against Alzheimer\u0026rsquo;s disease and age-related cognitive decline\u0026nbsp;\u003csup\u003e3\u003c/sup\u003e.\u0026nbsp;Insufficient dietary niacin levels may impair oxidative phosphorylation and disrupt mitochondrial respiration\u0026nbsp;\u003csup\u003e4\u003c/sup\u003e. Physiological supplementation of nicotinic acid (15\u0026ndash;20 mg/day) and nicotinamide (300 mg/day) has been found effective in the treatment of classic pellagra\u0026nbsp;\u003csup\u003e5,6\u003c/sup\u003e. However, when administered at higher doses, these forms of niacin exhibit diverse additional pharmacological effects, ranging from anti-dyslipidemic properties to anti-inflammatory actions\u0026nbsp;\u003csup\u003e7,8\u003c/sup\u003e.\u0026nbsp;Several trials have demonstrated the anti-inflammatory potential of niacin, particularly in conditions like acute coronary syndrome, sepsis, and lung fibrosis\u0026nbsp;\u003csup\u003e9\u003c/sup\u003e.\u0026nbsp;Cardiovascular disease (CVD), type 2 diabetes, and cancer collectively contribute to nearly half of all global deaths, as documented by the World Health Organization\u0026nbsp;\u003csup\u003e10\u0026ndash;12\u003c/sup\u003e. These diseases garner significant attention due to their detrimental impact on health, leading to considerable suffering, disability, and substantial economic burdens\u0026nbsp;\u003csup\u003e13\u003c/sup\u003e,\u0026nbsp;ultimately resulting in increased mortality rates. Prior studies have revealed that a mere 1 mg/d escalation in dietary niacin intake correlates with a 2% decrease in the incidence of new-onset hypertension among individuals with daily niacin consumption below 15.6 mg\u0026nbsp;\u003csup\u003e14\u003c/sup\u003e. Elevated dietary niacin levels have shown a positive association with type 2 diabetes in the United States adult population\u0026nbsp;(Ke等\u0026nbsp;2022), while increased dietary niacin intake has been linked to reduced mortality among cancer patients\u0026nbsp;\u003csup\u003e15\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eHowever, there are rare studies examining the association between dietary niacin intake and all-cause and cardiovascular mortality in the general population. Therefore, the relationship between dietary niacin intake and all-cause and cardiovascular mortality in adults was assessed with data from the NHANES to refine this study in the general population. Based on the nutritional patterns found in this population, we hypothesized that there was negative correlation between dietary consumption of niacin and mortality. We also conducted subgroup analyses to assess possible effect modification of the association between dietary niacin intake and mortality. Furthermore, the dose\u0026ndash;response correlation between dietary niacin intake and mortality was also described. Limited research has explored the link between dietary niacin intake and overall mortality, including deaths related to cardiovascular causes, within the general population. To address this gap, the present study aimed to investigate the potential connection between dietary niacin intake and both all-cause and cardiovascular mortality among adults, utilizing data from the National Health and Nutrition Examination Survey (NHANES) to enhance the scope of investigation. In light of the dietary habits observed in this sample, our hypothesis suggested a negative correlation between niacin consumption and mortality risks. Subgroup analyses were additionally performed to evaluate any potential modifications to this association. Moreover, the study sought to establish a dose-response relationship between dietary niacin intake levels and mortality outcomes.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eStudy population\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study utilized data from NHANES, a comprehensive survey representing nutrition and health status across the United States (https://wwwn.cdc.gov/nchs/nhanes/Default.aspx) and adhered to The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.. NHANES received approval from the NCHS Research Ethics Review Board. Our investigation into the relationship between dietary niacin intake and all-cause, as well as cardiovascular mortality, was based on NHANES data spanning from 1999 to 2018. All participants provided written informed consent, and the research protocol received approval from the NCHS Research Ethics Review Board. Exclusions from the study comprised the following patient groups: (1) individuals under 20 years of age, (2) pregnant individuals, (3) individuals with missing data on dietary niacin intake, (4) individuals with missing death data, and (5) individuals with missing covariates information. The final study population included 39,428 participants, and the selection process is depicted in Figure 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis incorporated the following covariates based on existing literature: age, gender, race and ethnicity, educational attainment, marital status, household income, body mass index (BMI), vigorous physical activity, diabetes status, smoking habits, alcohol consumption patterns, presence of hypertension, CVDs, daily calorie intake, protein intake, carbohydrate intake, fat intake, and use of dietary supplements\u0026nbsp;\u003csup\u003e16,17\u003c/sup\u003e. Within the NHANES dataset, self-reported race and ethnicity information was obtained through responses to survey queries on racial background and Hispanic ethnicity. Participant classification aligned with NHANES conventions, encompassing four racial and ethnic groupings: Non-Hispanic Asian, Non-Hispanic Black, Mexican American, and Others (incorporating multiracial individuals). Educational attainment was stratified into three categories: below 9th grade, 9th-12th grade, and beyond 12th grade. Marital status was delineated into two groups: Married or cohabiting, and Independent living (comprising widowed, divorced, separated, or never married individuals). Following the criteria utilized by U.S. government entities for reporting NHANES data on dietary and health metrics, family income was classified into three tiers utilizing the family poverty income ratio: low income (≤1.3), medium income (\u0026gt;1.3 to 3.5), and high income (\u0026gt;3.5). Physical activity levels (PA) were determined using the formula: PA (MET-h/wk) = MET\u0026nbsp;×\u0026nbsp;weekly frequency\u0026nbsp;×\u0026nbsp;activity duration, categorizing physical activity into two groups: vigorous activity (MET\u0026nbsp;≥\u0026nbsp;48) and non-vigorous activity (MET \u0026lt; 48). The smoking status was classified into three distinct groups: Never smoked (or smoked \u0026lt;100 cigarettes), Current smoker (currently smoking and having consumed a minimum of 100 cigarettes), and Former smoker (previously smoked at least 100 cigarettes but has since ceased). Alcohol consumption status was characterized by individuals consuming a minimum of 12 alcoholic drinks annually. Hypertension was diagnosed based on a history of physician-diagnosed hypertension, an average systolic blood pressure\u0026nbsp;≥140 mmHg or diastolic blood pressure\u0026nbsp;≥90 mmHg, or the current utilization of antihypertensive medication. Diabetes was diagnosed based on a history of physician-diagnosed diabetes, a hemoglobin A1c level\u0026nbsp;≥6.5%, fasting glucose level\u0026nbsp;≥7.0 mmol/l, two-hour oral glucose tolerance tests (OGTT) blood glucose\u0026nbsp;≥11.1 mmol/l, or current utilization of diabetes medication or insulin. The presence of cardiovascular disease was identified through participants’ self-reported history of congestive heart failure, angina, heart attack, coronary heart disease, or stroke. Prior to the interview at the Mobile Examination Center (MEC), participants underwent a dietary recall interview to provide details on their 24-hour nutritional intake, encompassing total dietary calories, protein, carbohydrates, and fats. The use of dietary supplements was ascertained through inquiries regarding nutritional supplements and medications taken in the preceding month.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical outcomes\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary outcome assessed in this study encompassed all-cause and cardiovascular mortality. The follow-up period initiated on the examination date and continued until either the individual’s date of death or the termination of the mortality surveillance period (December 31, 2019).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe collected data from all patients underwent descriptive statistical analysis. Categorical variables are presented as counts and percentages, while normally distributed continuous variables are expressed as means with standard deviation (SD) or as medians with inter quartile range. Statistical comparisons for categorical, normally distributed, and non-normally distributed continuous variables were conducted using the χ² test, one-way ANOVA, and the Kruskal-Wallis test, respectively. An exploratory analysis was carried out, designating Quintile 1 (≤14.79 mg/day) as the reference group due to exhibiting the lowest mortality risk. Through Cox proportional hazards regression, we conducted three distinct multivariate models. The Crude model solely comprised niacin intake. Adjustments were made for variables that, upon inclusion, altered the matched odds ratio by a minimum of 10 percent. The Adjust I model integrated age, gender, race, and education, while the Adjust II model further incorporated adjustments for vigorous activity, calorie intake, protein, carbohydrate, and fat consumption. Initial analysis involved survival assessment using standardized Kaplan-Meier curves. Subsequently, the association between dietary niacin intake and both all-cause and cardiovascular mortality was investigated through multivariate-adjusted Cox restricted cubic spline regression models and a generalized additive model to explore potential nonlinear relationships. In instances where non-linear relationships were detected, we applied two-piece wise linear regression models to elucidate variations in associations around the inflection point. The inflection point value was determined by assessing all potential values and selecting the inflection point with the highest likelihood. Subgroup analyses were performed based on age (\u0026lt;60 or ≥60 years), gender (male or female), coronary heart disease (absent or present), angina (absent or present), heart attack (absent or present), stroke (absent or present), and heart failure (absent or present). Statistical significance was established at a P-value of \u0026lt; 0.05. To assess the reliability of our findings, participants with extreme energy intake (\u0026lt;500 or \u0026gt;5000 kcal per day) were excluded for sensitivity analyses. All Statistical analyses were conducted using R version 4.0.5 (R Project for Statistical Computing) with the survey package version 4.1-1 and Free Software Foundation statistics software version 1.3. A significance level of P \u0026lt; 0.05 (two-sided) was adopted for all tests to indicate statistical significance.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eBaseline characteristics of study population\u003c/h2\u003e\n \u003cp\u003eOver a median follow-up duration of 110 months, there were a total of 5955 deaths attributed to all causes, representing 15.1% of the cases. Among these fatalities, 1860 were related to cardiovascular mortality, encompassing cardiac and cerebrovascular diseases, accounting for 3.387% of cases (see Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Baseline patient characteristics, categorized by quartiles of dietary niacin intake (Q), are outlined in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e as follows: Q1: \u0026le;14.79; Q2: 14.80\u0026ndash;21.53; Q3: 21.54\u0026ndash;30.38; Q4: \u0026ge;30.9. Compared to individuals with lower dietary niacin intake, those in the higher niacin intake group were typically younger, male, Non-Hispanic White, had higher educational levels, were married or cohabiting, had higher family incomes, engaged in vigorous physical activity, were former smokers and alcohol consumers, and showed a lower prevalence of comorbidities such as coronary heart disease, angina, heart attack, stroke, and heart failure. Furthermore, the higher niacin intake group demonstrated increased calorie, protein, carbohydrate, and fat intake, along with reduced dietary supplement usage. As dietary niacin intake levels rose, a gradual decrease in both all-cause mortality (20.1% vs. 16.8% vs. 13.8% vs. 9.7%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and cardiovascular mortality (6.4% vs. 5.4% vs. 4.5% vs. 2.7%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was observed.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003eCharacteristics of participants in the NHANES (1999-2018) by categories of dietary niacin intake.\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"953\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.35496957403651%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.64503042596348%\" colspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eNiacin Intake, mg/d\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.705035971223023%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.86570743405276%\"\u003e\n \u003cp\u003e\u003cstrong\u003eQ1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.705035971223023%\"\u003e\n \u003cp\u003e\u003cstrong\u003eQ2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.705035971223023%\"\u003e\n \u003cp\u003e\u003cstrong\u003eQ3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.705035971223023%\"\u003e\n \u003cp\u003e\u003cstrong\u003eQ4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.314148681055156%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-\u003cstrong\u003eValue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.14910858995138%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026le;14.79\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.283630470016206%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(14.80-21.53)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.283630470016206%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(21.54-30.38)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.283630470016206%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026ge;30.9)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eNO.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e39428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e9857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e9855\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e9859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e9857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eAge(year),Mean(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e49.9(17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e53.2(18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e51.6(17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e49.6(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e45.1(16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eGender,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e19783 (50.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e3040 (30.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e4200 (42.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e5330 (54.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e7213 (73.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e19645 (49.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e6817 (69.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e5655 (57.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e4529 (45.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2644 (26.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eRace,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eNon-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e18486 (46.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e4200 (42.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e4628 (47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e4861 (49.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e4797 (48.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e8138 (20.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e2300 (23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1993 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1840 (18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2005 (20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eMexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e6506 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e1785 (18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1594 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1605 (16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1522 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e6298 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e1572 (15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1640 (16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1553 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1533 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eEducation level(year),n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003e\u0026lt;9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e4174 (10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e1467 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1170 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e864 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e673 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003e9-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e14899 (37.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e3977 (40.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3704 (37.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3574 (36.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3644 (37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003e\u0026gt;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e20355 (51.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e4413 (44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e4981 (50.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e5421 (55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e5540 (56.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eMarital status,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eMarried or living with a partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e23829 (60.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e5414 (54.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e6041 (61.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e6251 (63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e6123 (62.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eLiving alone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e15599 (39.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e4443 (45.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3814 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3608 (36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3734 (37.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eFamily income, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e11770 (29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e3541 (35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2925 (29.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2631 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2673 (27.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e15092 (38.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e3829 (38.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3860 (39.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3762 (38.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3641 (36.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e12566 (31.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e2487 (25.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3070 (31.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3466 (35.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3543 (35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eBody mass index(kg/m\u003csup\u003e2\u003c/sup\u003e),Mean(SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e29.1(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e29.3(7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e29.0(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e29.1(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e28.8(6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eVigorous\u0026nbsp;activity,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e27854 (70.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e6228 (63.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e6799 (69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e7106 (72.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e7721 (78.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eSmoking status,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e21013 (53.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e5478 (55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e5376 (54.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e5244 (53.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e4915 (49.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eCurrent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e10040 (25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e2333 (23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2549 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2643 (26.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2515 (25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eFormer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e8375 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e2046 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1930 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1972 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2427 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eAlcohol drinking status,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eNon-drinkers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e10533 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e3602 (36.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2838 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2378 (24.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1715 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eDrinkers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e28895 (73.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e6255 (63.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e7017 (71.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e7481 (75.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e8142 (82.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eHypertension,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e11437 (29.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e3259 (33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e3050 (30.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2797 (28.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2331 (23.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eDiabetes,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e4781 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e1370 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1303 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1187 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e921 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eCoronary heart disease,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1656 ( 4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e478 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e432 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e422 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e324 (3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eAngina,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1143 ( 2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e358 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e306 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e282 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e197 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eHeart attack,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1658 ( 4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e509 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e441 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e394 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e314 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eStroke,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1436 ( 3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e519 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e388 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e310 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e219 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eHeart failure,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1238 ( 3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e414 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e360 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e264 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e200 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eCalorie consumption, Median(IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1941.0 (1429.0, 2610.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e1279.0 (962.3, 1622.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1763.0 (1425.2, 2166.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2160.0 (1754.0, 2659.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e2864.0 (2280.0, 3607.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eProtein consumption, Median(IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e73.3 (52.0, 100.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e42.8 (31.6, 54.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e64.4 (52.8, 77.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e83.9 (69.6, 100.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e117.6 (94.9, 147.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eCarbohydrate consumption, Median(IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e234.2 (168.5, 317.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e163.5 (118.7, 215.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e216.3 (166.6, 275.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e257.0 (198.0, 326.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e327.2 (250.5, 424.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eFat consumption, Median(IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e71.8 (47.9, 102.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e46.0 (30.4, 63.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e66.4 (47.9, 88.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e81.7 (58.9, 108.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e106.0 (76.2, 143.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eDietary supplements,n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e19951 (50.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e4977 (50.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e5108 (51.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e5096 (51.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e4770 (48.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eOutcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eAll-cause mortality, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e5955 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e1977 (20.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1660 (16.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1360 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e958 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.062730627306273%\"\u003e\n \u003cp\u003eCardiovascular mortality, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e1860 ( 4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.745387453874539%\"\u003e\n \u003cp\u003e628 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e529 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e441 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.391143911439114%\"\u003e\n \u003cp\u003e262 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.627306273062731%\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eKaplan\u0026ndash;Meier survival analysis curves for all‑cause and cardiovascular mortality according to dietary niacin intake\u003c/h2\u003e\n \u003cp\u003eOver a median follow-up of 110 months, there were 5955 cases of all-cause mortality and 1860 cases of cardiovascular mortality. The mortality rates among different dietary niacin intake groups are depicted in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. Significant disparity in mortality was evident within these groups (All-cause mortality: P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 for the log-rank test; cardiovascular mortality: P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 for the log-rank test) across the entire study population (Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA, \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eAssociations of dietary niacin intake with all‑cause and cardiovascular mortality\u003c/h2\u003e\n \u003cp\u003eThe Cox proportional hazard analysis indicated a notable correlation between dietary niacin intake and both all-cause and cardiovascular mortality in the unadjusted model [All-cause mortality: HR (95% CI) 0.98 (0.98, 0.98), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; cardiovascular mortality: HR (95% CI) 0.98 (0.97, 0.98), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001], and the adjusted models [Adjusted I: All-cause mortality: HR (95% CI) 0.99 (0.99, 1.00), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; cardiovascular mortality: HR (95% CI) 0.99 (0.99, 1.00), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Adjusted II: All-cause mortality: HR (95% CI) 1.00 (0.99, 1.00), P\u0026thinsp;=\u0026thinsp;0.076; cardiovascular mortality: HR (95% CI) 0.99 (0.99, 1.00), P\u0026thinsp;=\u0026thinsp;0.047], treating dietary niacin intake as a continuous variable(Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In the unadjusted and Adjust I models, positive trends were noted between dietary niacin intake and both all-cause and cardiovascular mortality (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, both P for trend\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These findings were consistently observed in the multivariate Cox proportional hazard analysis of dietary niacin intake concerning all-cause and cardiovascular mortality in Model I (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, all-cause mortality: P for trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001; cardiovascular mortality: P for trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and Model II (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, all-cause mortality: P for trend\u0026thinsp;=\u0026thinsp;0.001; cardiovascular mortality: P for trend\u0026thinsp;=\u0026thinsp;0.008). As the multivariate Cox proportional hazard analysis indicated a non-linear relationship between baseline dietary niacin intake and both all-cause and cardiovascular mortality, restricted cubic splines analysis was utilized for more in-depth exploration. The adjusted restricted cubic spline plots revealed non-linear relationships between dietary niacin intake and both all-cause and cardiovascular mortality (both Non-linear P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Notably, the relationship between dietary niacin intake and cardiovascular mortality lost its non-linear nature when only 99.9% of the data was considered (Non-linear P\u0026thinsp;=\u0026thinsp;0.384)(Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eHR(95% CI) for outcomes across groups of dietary niacin intake.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCrude\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel I\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eModel II\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll-cause mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNiacin intake Continuous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98(0.98, 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99 (0.99,1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00(0.99,1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuartiles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86(0.80,0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90(0.84,0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92(0.86,0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.70(0.66,0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86(0.80,0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88 (0.81,0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.50(0.47,0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81 (0.75,0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83(0.75,0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP for trend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCardiovascular mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNiacin intake Continuous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98(0.97, 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99(0.99\u0026minus;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99(0.99\u0026minus;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuartiles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86 (0.76,0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91(0.81,1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91(0.81,1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72 (0.64,0.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89(0.78,1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90(0.78,1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.162\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43(0.38,0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73(0.63,0.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73(0.60,0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP for trend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eCrude: Unadjusted;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eModel 1: Age, gender, race,education were adjusted;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eModel 2: Model 1\u0026thinsp;+\u0026thinsp;Vigorous activity, hypertension, calorie consumption, protein consumption, carbohydrate consumption and fat consumption were adjusted.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eThe inflection point analysis\u003c/h2\u003e\n \u003cp\u003eIn the inflection point analysis, the hazard ratio (HR) for all-cause mortality was 0.995 (95% CI: 0.991\u0026ndash;0.995, p\u0026thinsp;=\u0026thinsp;0.039) within the general population with a dietary niacin intake of \u0026lt;\u0026thinsp;54.6 mg/day (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). A 0.5% reduction in the risk of all-cause mortality was observed with each 1 mg/kg rise in daily dietary niacin consumption. No significant association was found between dietary niacin intake and all-cause mortality when the daily intake exceeded 54.6 mg/kg (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The risk of all-cause mortality did not exhibit a further decrease with increased dietary niacin intake.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eInflection point analysis of the relationship of serum 25(OH)D with TyG.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSerum 25(OH)D (nmol/L)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAdjusted Model\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026beta; (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;59.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.995 (0.991,0.999)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0397\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;59.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.007(0.993,1.020)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLikelihood Ratio test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eSubgroup analysis of the association between dietary niacin intake and all‑cause and cardiovascular mortality\u003c/h2\u003e\n \u003cp\u003eTo evaluate the influence of dietary niacin intake on the primary outcomes, stratification was performed based on age, gender, coronary artery disease, angina, myocardial infarction, stroke, and heart failure (see Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). With the exception of the heart failure subgroup (heart failure subgroup: all-cause mortality: P for interaction\u0026thinsp;=\u0026thinsp;0.047), no significant interactions were observed in most subgroups (other subgroups: all-cause mortality: P for interaction\u0026thinsp;=\u0026thinsp;0.325\u0026ndash;0.719, cardiovascular mortality: P for interaction\u0026thinsp;=\u0026thinsp;0.257\u0026ndash;0.784).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eSensitivity Analysis\u003c/h2\u003e\n \u003cp\u003eAfter excluding individuals with extreme energy intake, 38,350 participants remained, and the relationship between dietary niacin intake and all-cause and cardiovascular mortality remained consistent. A significant correlation was found between dietary niacin intake and both all-cause and cardiovascular mortality in the unadjusted model [All-cause mortality: HR (95% CI) 0.98 (0.98, 0.98), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; cardiovascular mortality: HR (95% CI) 0.97 (0.97, 0.98), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001] and the adjusted models [Adjusted I: All-cause mortality: HR (95% CI) 0.99 (0.99, 1.00), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; cardiovascular mortality: HR (95% CI) 0.99 (0.98, 0.99), P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Adjusted II: all-cause mortality: HR (95% CI) 1.00 (0.99, 1.00), P\u0026thinsp;=\u0026thinsp;0.044; cardiovascular mortality: HR (95% CI) 0.99 (0.98, 1.00), P\u0026thinsp;=\u0026thinsp;0.006] when dietary niacin intake was considered as a continuous variable (refer to Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). In comparison to individuals with lower dietary niacin intake in Q1 (\u0026le;\u0026thinsp;14.79 mg/day), the adjusted hazard ratio (HR) values for dietary niacin intake and all-cause mortality in Q2 (14.80\u0026ndash;21.53 mg/day), Q3 (21.54\u0026ndash;30.38 mg/day), and Q4 (\u0026ge;\u0026thinsp;30.9 mg/day) were 0.94 (95% CI: 0.88\u0026ndash;1.01, p\u0026thinsp;=\u0026thinsp;0.113), 0.92 (95% CI: 0.84\u0026ndash;1.00, p\u0026thinsp;=\u0026thinsp;0.045), and 0.88 (95% CI: 0.79\u0026ndash;0.99, p\u0026thinsp;=\u0026thinsp;0.029) (refer to Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Likewise, when compared to individuals with lower dietary niacin intake in Q1 (\u0026le;\u0026thinsp;14.79 mg/day), the adjusted HR values for dietary niacin intake and cardiovascular mortality in Q2 (14.80\u0026ndash;21.53 mg/day), Q3 (21.54\u0026ndash;30.38 mg/day), and Q4 (\u0026ge;\u0026thinsp;30.9 mg/day) were 0.94 (95% CI: 0.88\u0026ndash;1.01, p\u0026thinsp;=\u0026thinsp;0.113), 0.92 (95% CI: 0.84\u0026ndash;1.00, p\u0026thinsp;=\u0026thinsp;0.045), and 0.88 (95% CI: 0.79\u0026ndash;0.99, p\u0026thinsp;=\u0026thinsp;0.029) (refer to Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e), respectively.\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSensitivity analysis excluding total calorie consumption\u0026thinsp;\u0026lt;\u0026thinsp;500 kcal and \u0026gt;\u0026thinsp;5000 kcal.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCrude\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjust I\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjust II\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHR(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll-cause mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNiacin intake Continuous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98(0.98, 0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99(0.99,1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0(0.99\u0026minus;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuartiles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86(0.81,0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91(0.85,0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94 (0.88,1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.71(0.66,0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86(0.80,0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92 (0.84,1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52(0.48,0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.80(0.74,0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88 (0.79,0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP for trend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCardiovascular mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNiacin intake Continuous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97(0.97,0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99(0.98,0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99(0.98,1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuartiles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.86(0.77,0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.91(0.81,1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94(0.83,1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73(0.64,0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89(0.79,1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94(0.81,1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.454\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45(0.39,0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73(0.62,0.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78(0.63,0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP for trend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eCrude: Unadjusted;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eModel 1: Age, gender, race,education were adjusted;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003eModel 2: Model 1\u0026thinsp;+\u0026thinsp;Vigorous activity, hypertension, calorie consumption, protein consumption, carbohydrate consumption and fat consumption were adjusted.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study revealed that a higher intake of dietary niacin is linked to a reduced risk of mortality caused by all reasons and cardiovascular issues. The relationship between niacin consumption and mortality demonstrated a non-linear dose-effect pattern for overall mortality, with a notable inflection point at approximately 54.6 mg per day, while a linear dose-effect pattern was observed for cardiovascular mortality. Both subgroup and sensitivity analyses confirmed the strong association between dietary niacin intake and decreased risks of all-cause and cardiovascular mortality. Our findings indicate that, within an appropriate range, increased niacin consumption is connected to a lower likelihood of mortality from all reasons and cardiovascular causes in the general population. These results support the notion that dietary niacin intake may act as a protective factor against mortality.\u003c/p\u003e \u003cp\u003eRecent studies have explored the correlation between dietary niacin intake and disease-related mortality. Wei et al. demonstrated a significant link between adequate niacin intake from food and decreased mortality rates among U.S. adults with diabetes \u003csup\u003e18\u003c/sup\u003e. Jie et al. proposed that a higher dietary niacin intake could be connected to a reduced risk of all-cause mortality in individuals with nonalcoholic fatty liver disease (NAFLD). They observed a 30% decrease in the risk of all-cause mortality for NAFLD participants for every 1 mg/kg increase in daily dietary niacin consumption, particularly for those with a niacin intake of 26.7 mg or higher. Additionally, Hongan et al. discovered a positive association between higher dietary niacin intake and reduced mortality among cancer patients, noting that niacin supplementation contributed to improved cancer mortality outcomes \u003csup\u003e15\u003c/sup\u003e. Nevertheless, few studies have investigated the link between dietary niacin intake and all-cause as well as cardiovascular mortality in the general population. Our study offers a distinctive opportunity to assess the potential relationship between dietary niacin intake and both all-cause and cardiovascular mortality in the general population. This assessment could establish a foundation for further investigations into the effectiveness of niacin in reducing mortality risks.\u003c/p\u003e \u003cp\u003eThe relationship between dietary niacin consumption and all-cause mortality exhibited a non-linear pattern, specifically L-shaped. The beneficial impact of higher dietary niacin intake on all-cause mortality appeared to plateau among individuals with sufficient niacin levels. More precisely, the risk of all-cause mortality decreased as dietary niacin consumption increased for those with a dietary intake of \u0026lt;\u0026thinsp;54.67 mg/day, while the reduction in the risk of all-cause mortality ceased in individuals with a dietary niacin intake of \u0026ge;\u0026thinsp;54.67 mg/day. Sources rich in niacin encompass fish, meat, milk, peanuts, and fortified flour products \u003csup\u003e19\u003c/sup\u003e. Based on the present statistical data analysis, a high-niacin diet appears to play a role in reducing all-cause mortality. Subgroup analysis revealed no significant interactions in various subgroups based on age, gender, coronary artery disease, angina, heart attack, and stroke, except for the heart failure subgroup. Nonetheless, the P-value for interaction was 0.047, approaching the conventional threshold of 0.05. Further investigation is warranted to elucidate the impact of dietary niacin intake on heart failure. The correlation between dietary niacin consumption and cardiovascular mortality followed a linear pattern. The positive impact of higher dietary niacin intake on cardiovascular mortality appeared to diminish with sufficient niacin levels. Analysis of the current statistical data suggests that a high-niacin diet contributes to the prevention of cardiovascular mortality. Subgroup analysis indicated no significant interactions among age, gender, coronary artery disease, angina, heart attack, stroke, and heart failure subgroups.\u003c/p\u003e \u003cp\u003eLimited knowledge currently exists regarding the mechanism underlying the association between dietary niacin intake and mortality. We believe that this correlation can be attributed to the capacity of dietary niacin to reduce mortality related to various diseases, including nonalcoholic fatty liver disease, cancer, and diabetes \u003csup\u003e15,18,20\u003c/sup\u003e. Additionally, dietary niacin intake can decrease the risk factors associated with cardiovascular disease. Zhuxian et al. noted that maintaining optimal dietary niacin intake levels could lower the occurrence of new-onset hypertension \u003csup\u003e14\u003c/sup\u003e. Yuong et al. demonstrated that each unit increase in niacin intake was linked to a 3.5% reduction in the risk of diabetes \u003csup\u003e21\u003c/sup\u003e. Furthermore, several trials have highlighted the anti-inflammatory effects of niacin, particularly in acute coronary syndrome\u003csup\u003e22\u0026ndash;24\u003c/sup\u003e. Our study has several limitations. Firstly, the dietary information was gathered from one-time recall surveys, potentially inadequately representing an individual\u0026rsquo;s typical diet and overall niacin intake. Nonetheless, research suggests that 24-hour dietary recalls are a reliable method for evaluation \u003csup\u003e25,26\u003c/sup\u003e. Secondly, the conclusions were drawn from a U.S. adult sample, and generalizing these findings to other populations necessitates further scrutiny. Third, despite the implementation of regression models, stratified analyses, and sensitivity analysis, residual confounding effects stemming from unmeasured or unknown variables could not be entirely eliminated. Lastly, as our study was cross-sectional, causal relationships cannot be inferred. Therefore, these limitations should be taken into account in future research endeavors.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, dietary niacin intake showed a substantial correlation with all-cause and cardiovascular mortality in the general population. Particularly, a non-linear association was evident between dietary niacin intake and all-cause mortality, pinpointing an inflection point at approximately 54.67 mg/day. Furthermore, a linear relationship was identified between dietary niacin intake and cardiovascular mortality.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZikai Song and Haidi Wu wrote the main manuscript text and Dayong Deng prepared figures and table. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe gratefully thank Jie Liu of the Department of Vascular and Endovascualr Surgery, Chinese PLA General Hospital for his contribution to the statistical support, study design consultations, and comments regarding the manuscript. This work was supported by the central government of China, Fundamental Research Funds for the Central Universities of China, and the Science and Technology Project of the Education Department of Jilin Province (JJKH20201078KJ).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analyzed for the current study are available in the NHANES database (https://www.cdc.gov/nchs/nhanes/index.htm).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKirkland, J. B. \u0026amp; Meyer-Ficca, M. L. Chapter Three - Niacin. in \u003cem\u003eAdvances in Food and Nutrition Research\u003c/em\u003e (ed. Eskin, N. A. M.) vol. 83 83\u0026ndash;149 (Academic Press, 2018).\u003c/li\u003e\n\u003cli\u003eTek, C. \u0026amp; Bhalla, S. Vitamin B3, Niacin. in \u003cem\u003eIndustrial Biotechnology of Vitamins, Biopigments, and Antioxidants.\u003c/em\u003e (Wiley-VCH Verlag GmbH \u0026amp; Co. 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T. \u003cem\u003eet al.\u003c/em\u003e Effects of extended-release niacin on lipoprotein particle size, distribution, and inflammatory markers in patients with coronary artery disease. \u003cem\u003eAm J Cardiol\u003c/em\u003e \u003cstrong\u003e98\u003c/strong\u003e, 743\u0026ndash;745 (2006).\u003c/li\u003e\n\u003cli\u003eKn\u0026uuml;ppel, S., Norman, K. \u0026amp; Boeing, H. Is a Single 24-hour Dietary Recall per Person Sufficient to Estimate the Population Distribution of Usual Dietary Intake? \u003cem\u003eJ Nutr\u003c/em\u003e \u003cstrong\u003e149\u003c/strong\u003e, 1491\u0026ndash;1492 (2019).\u003c/li\u003e\n\u003cli\u003eHuang, L. \u003cem\u003eet al.\u003c/em\u003e U-shaped association of serum uric acid with all-cause mortality in patients with hyperlipidemia in the United States: a cohort study. \u003cem\u003eFront. Cardiovasc. Med.\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 1165338 (2023).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"dietary niacin, mortality, general population","lastPublishedDoi":"10.21203/rs.3.rs-4536509/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4536509/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDietary niacin, a vital nutrient needed for the metabolism of mitochondrial energy, has been linked to nonalcoholic fatty liver disease and cancer mortality. There is, however, little information available about how dietary niacin intake affects mortality risk in the general population. Therefore, our aim was to investigate the relationship between dietary niacin consumption and all-cause and cardiovascular mortality in the general population. 39428 participants from the National Health and Nutrition Examination Survey (NHANES) 1999-2008 were analyzed. Multivariate Cox proportional hazards regression models, restricted cubic splines (RCS), trend tests, subgroup analysis and inflection point analysis were employed. Over a median follow-up period of 110 months, all-cause mortality accounted for 15.1% of cases, and cardiovascular mortality accounted for 3.387%. During Cox proportional hazards regression analysis, no linear trend was observed between dietary niacin intake and all-cause (P for trend = 0.001) or cardiovascular mortality (P for trend = 0.008) after adjusting for confounding factors. RCS revealed a non-linear association between dietary niacin intake and all-cause mortality (Non-linear P=0.001), but linear association between dietary niacin intake and cardiovascular mortality (Non-linear P = 0.384) when 99.9% of the data was shown. In the inflection point analysis, the HR of all-cause mortality was 0.995 (95% CI:0.991–0.995, P = 0.039) in general population with dietary niacin intake of \u0026lt;54.6 mg/day and 1.007 (95% CI:0.993–1.020, P = 0.296) in general population with dietary niacin intake of ≥54.6 mg/day. The effect of dietary niacin intake was consistent across most subgroups in terms of all-cause and cardiovascular mortality, with no significant interaction with randomized factors (all-cause mortality: P for interaction = 0.047–0.719, cardiovascular mortality: P for interaction = 0.257–0.784). Dietary niacin intake was nonlinearly associated with all-cause mortality but linearly associated with cardiovascluar mortality in general population of United States.\u003c/p\u003e","manuscriptTitle":"Association of dietary niacin intake with all-cause and cardiovascular mortality in the general population","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-10 01:58:09","doi":"10.21203/rs.3.rs-4536509/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d4a9032b-b3b6-4031-a56d-f39a0ec0cbae","owner":[],"postedDate":"July 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":33832009,"name":"Health sciences/Diseases"},{"id":33832010,"name":"Health sciences/Health care"},{"id":33832011,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2025-02-14T09:24:28+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-10 01:58:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4536509","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4536509","identity":"rs-4536509","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}