Skip to main content
Download PDF
Download ePub

Dietary amino acids intake and all-cause and cause-specific mortality: results from the Golestan Cohort Study

Nutrition Journal volume 23, Article number: 141 (2024) Cite this article

Abstract

Background

Less is known whether the amino acid composition of dietary protein sources effects on long-term health outcomes. We aimed to evaluate the association between dietary amino acid composition and all-cause and cause-specific mortality.

Methods

This study used data from the Golestan Cohort Study, which was performed in the Golestan Province of Iran from January 2004 to June 2008. Mortality, which was the primary outcome, was ascertained through September 2022. The Cox proportional hazards regression models were used to determine the adjusted hazard ratios (HR) and 95% confidence intervals (CI) for mortality according to the quintiles of amino acid consumption, taking the third quintile as the reference.

Results

A total of 47,337 participants (27,293 [57.7%] women) with a mean (standard deviation) age of 51.9 (8.9) years were included. During a median follow-up of 15 years, 9,231 deaths were documented. Regarding essential amino acid intakes, the HRs of all-cause mortality were 1.16 (95% CI, 1.07–1.26) in the first quintile, compared with the reference group (P for non-linear trend < 0.001). Similarly, non-linear associations were observed between risk of all-cause mortality and intake of branched-chain, aromatic, sulfur-containing, or non-essential amino acids (P for non-linear trend < 0.001 for all comparisons), with higher HRs for participants in the first quintiles. There was an age interaction for the associations between dietary amino acids and mortality (P for interaction ˂0.05). While high amino acid diets were detrimental in middle-aged adults (< 65 years), increased hazards of mortality were observed among older adults (≥ 65 years) with low amino acid intake.

Conclusions

This study showed the non-linear trend between amino acids intake and risk of mortality in the middle-aged and older Iranian population. Overall, our findings suggest that diets lower in amino acids were associated with increased hazards of mortality, particularly among older adults.

Peer Review reports

Introduction

Dietary choices are important preventable risk factors for mortality [1, 2]. Several dietary recommendations and guidelines have been developed [3, 4] and commonly recommend rich dietary diversity and reduced consumption of particular components known to increase the risk of various diseases [5]. These recommendations include reducing the intake of specific types of fat and carbohydrate like trans fatty acids, saturated fatty acids, added sugars, and refined carbohydrates [5, 6]. Although it has been generally accepted that the types of dietary fat and carbohydrate are significant indicators of diet quality, protein and its constituent amino acids are often neglected and most studies on human nutrition considered protein as a single variable [7].

However, each specific amino acid has unique functions and metabolism [8]. Limited epidemiologic evidence, with inconsistent findings, has demonstrated the contribution of dietary amino acid composition to all-cause and cause-specific mortality. For instance, a cohort analysis reported that higher intakes of proline and glutamic acid are negatively associated with cardiovascular events and that amino acid intake pattern with higher loads of sulfur-containing amino acids (SAAs) is associated with decreased cardiovascular events [9]. In contrast, another study reported an increased risk of cardiometabolic diseases with high SAA dietary patterns [10].

These findings motivate and inspire an important question; whether individual amino acid or amino acid category is associated with the risk of mortality.

Given this context, we aimed to prospectively examine the associations between dietary intake of amino acids considering essential amino acids, non-essential amino acids, branched-chain amino acids (BCAAs), aromatic amino acids (AAAs), and SAAs with total and cause-specific mortality using data from a large-scale population-based cohort study in Iran.

Methods

Study population

We analyzed data from the Golestan Cohort Study, which was performed in the Golestan Province of Iran from January 2004 to June 2008. Details of the Golestan Cohort Study have been published previously [11]. The cohort recruited 50,045 individuals, aged 40–75 years, from Gonbad city and 326 nearby villages.

Participants were interviewed by trained nutritionists and general physicians in order to record data on baseline demographic characteristics and dietary intakes. Two structured questionnaires, including a lifestyle questionnaire and a semiquantitative food frequency questionnaire (FFQ), were employed. The lifestyle questionnaire contained questions on demographics, socio-economic status, education, and history of diabetes or hypertension, smoking, alcohol, and opium use. For all recruited participants, anthropometric indices were also measured at the beginning of the cohort. Participants with incomplete or missing data, extreme energy intakes (< 500 kcal/day or > 5000 kcal/day), or with an implausible body mass index (BMI) (< 15 or > 50 kg/m2) were removed from the analysis. Written informed consent was obtained from all participants. Ethical approval for the Golestan Cohort Study was obtained from the Institutional Review Boards of the Digestive Disease Research Center (DDRC) at Tehran University of Medical Sciences, the US National Cancer Institute (NCI), and the World Health Organization International Agency for Research on Cancer (IARC).

Assessment of diet

Dietary data were collected using a validated 116-item FFQ, which has been designed for the Golestan Cohort Study to indicate nutritional intakes [12]. Participants were asked to indicate the frequency and quantity of the consumed food over the last preceding year on a monthly, weekly, or daily basis and then converted into daily consumption values using household measures [13, 14]. Dietary amino acids contents were analyzed using Nutritionist IV (First Databank, Hearst Corp, San Bruno, CA, USA). The contents of amino acids were expressed as grams per day. Measured intake of amino acids were grouped as essential amino acids (tryptophan, lysine, threonine, isoleucine, leucine, methionine, histidine, phenylalanine, and valine), non-essential amino acids (cysteine, tyrosine, proline, arginine, aspartic acid, alanine, glutamic acid, glycine, and serine), BCAAs (valine, leucine, and isoleucine), AAAs (phenylalanine, tyrosine, and tryptophan), and SAAs (methionine and cysteine).

Assessment of covariates

Information on age, sex, education level, cigarette smoking, alcohol and opium consumption, socio-economic status, physical activity, and history of hypertension or diabetes mellitus were collected using lifestyle questionnaires. Education level was categorized into five groups including illiterate, ≤ 5 years, 6–8 years, 9–12 years, and college or university level. If someone smoked cigarettes, used opiates, or drank alcohol at least once a week for a period of six months or more defined as ever in the corresponding variable, otherwise, defined as never. Physical activity was defined by calculating the metabolic equivalent of task per minute per week considering the duration, intensity, and frequency of the physical activity and then grouped into low, medium, and high according to tertiles [15]. Wealth index was defined based on house and appliance ownership as described previously [16], and categorized as low, medium, and high according to the tertiles. Measurements of weight and height were performed following a standardized protocol. BMI was calculated by dividing weight in kilograms by height in meters square. Total energy, lipid, and protein intake were calculated using data from FFQ.

Follow-up and outcomes

Follow-up phone calls or home visits were made annually. During each phone call/home visit a case review questionnaire was completed and vital status of participants was recorded. Additionally, monthly inquiries were made on the vital status of participants by local healthcare providers in rural areas. At the time of analysis, participants were followed-up for a median of 15 years. Each participant’s person-years were calculated from the recruitment date to either the end of follow-up or the date of death, whatever occurred first. The primary outcome of the present study was mortality from all causes, cardiovascular disease (CVD), cancer, or other causes, during the first visit until September 2022. In the case of death, two internists completed a verbal autopsy questionnaire [17] and independently investigated all relevant medical records to determine the cause of death. In case of different results, a third, more experienced internist studied the records to make the final diagnosis.

Statistical analysis

All participants were categorized according to dietary quintiles of essential amino acids, non-essential amino acids, BCAAs, AAAs, and SAAs. Baseline data were compared between the lowest (quintile 1) and highest (quintile 5) consumption by using the chi-squared or linear regression test, as appropriate. The Cox proportional hazards regression model was used to determine the adjusted hazard ratio (HRs) with 95% confidence intervals (CIs) for all-cause, CVD, cancer, or other causes of mortality during the follow-up period according to the quintiles of amino acid consumption, taking the third quintile as the reference group. The reference value for estimating HRs and 95% CIs was chosen as 1.

Model 1 (minimally adjusted model) was adjusted for age, sex, and energy intake. Model 2 (fully adjusted model) was additionally adjusted for BMI, cigarette smoking, opium use, diabetes, hypertension, alcohol use, wealth index, education, physical activity, total lipids intake, and total protein intake. The non-linear associations of amino acid intake and cause-specific or all-cause mortality were all plotted and investigated by the restricted cubic spline function using four knots.

To avoid potential surveillance bias, the analyses were also repeated after excluding patients who died, lost to follow-up, or were diagnosed with cancer within the first two years of follow-up (i.e. 2-year lag analysis).

We further stratified our analyses by baseline characteristics of the participants including sex (male or female), age (< 65 or ≥ 65 years), BMI (15-24.9, 25-29.9, 30–50), smoking status (never, ever), history of diabetes (yes or no), and hypertension (yes or no) for potential effect modification. The interaction was tested using multivariate Cox regression models and adjusted for all Model 2 variables, except for the respective stratifying factor. All statistical analyses were performed in STATA software (version 12; StataCorp, College Station, TX) and R software. P-values < 0.05 were considered significant.

Results

Participant’s characteristics

This cohort study included data from 47,337 individuals (Fig. 1), including 27,293 (57.7%) women and 20,044 (42.3%) men. Their overall mean (standard deviation) age was 51.9 (8.9) years. During a median follow-up of 15 years, 9,231 deaths were recorded, including 4,215 deaths from CVD, 1,887 deaths from cancer, and 3,373 deaths from other causes. The baseline characteristics of participants, stratified by extreme quintiles of different categories of amino acid consumption, are shown in Table 1.

Fig. 1
figure 1

Flowchart illustrating the selection process of participants

Full size image
Table 1 Characteristics of the study population, according to the extreme quintiles of amino acid intake
Full size table

Compared to individuals in the lowest quintile, those in the highest quintile of all categories of amino acids consumption were more likely to be male, have a higher BMI, and more likely to be alcohol drinkers or cigarette smokers. They were more often highly educated, physically active, and had a higher wealth index. Those with higher dietary amino acid consumption were more likely to have diabetes mellitus, have higher energy intake, total lipid and protein intakes, and were less likely to have hypertension.

Essential amino acids and mortality

In the age-, sex-, and calorie intake-adjusted model (minimally adjusted model), a non-linear association was observed between dietary intake of essential amino acids and hazard of all-cause mortality (P for non-linear trend < 0.001) (Table 2). After fully adjusted model (model 2) was applied, the HRs of all-cause mortality were 1.16 (95%CI, 1.07–1.26) in the first quintile, and 1.08 (95%CI, 1.00-1.16) in the second quintile (P for non-linear trend < 0.001), when compared with the reference group (the third quintile). Figure 2A shows dose-response associations between essential amino acid consumption and all-cause mortality in the fully adjusted model, which is slightly U-shaped.

Fig. 2
figure 2

Multivariable adjusted cubic spline models for the association between essential amino acids intake and HRs for all-cause mortality (A) and CVD mortality (B); and for the association between non-essential amino acids intake and hazard ratios for all-cause mortality (C), CVD mortality (D), and other cause of mortality (D). Solid lines demonstrate estimates of HRs, while dashed lines demonstrate 95% confidence intervals. Abbreviations: CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio

Full size image
Table 2 Multivariate Cox regression derived HRs and 95% CIs for all-cause mortality and cause-specific mortality by essential amino acid intakes
Full size table

Participants in the first, fourth, and fifth quintiles of essential amino acid intake were at about 11–32% higher risk of CVD mortality, in the minimally adjusted model (P for non-linear trend < 0.001). In the fully adjusted model, compared with the reference group, the HR of CVD mortality was 1.23 (95% CI, 1.09–1.38) in the first quintile (P for non-linear trend = 0.003) (Fig. 2B).

After multivariable adjustment, no significant associations were observed between essential amino acid intake and cancer-related or other causes of mortality.

Non-essential amino acids and mortality

As shown in Table 3, a non-linear trend was found between non-essential amino acid intake and hazard of all-cause, CVD, and other mortality in minimally and fully adjusted models (P for non-linear trend < 0.05) (Fig. 2C-E). Higher HRs of all-cause (Q5 vs. Q3, 1.20; 95% CI, 1.12–1.30), CVD (Q5 vs. Q3, 1.34; 95% CI, 1.20–1.50), and other mortality (Q5 vs. Q3, 1.27; 95% CI, 1.12–1.45) were found in the upper quintile of non-essential amino acid intake in the minimally adjusted model. These associations were attenuated in the fully adjusted model. Moreover, in the fully adjusted model, participants in the lowest quintile of non-essential amino acid intake (median intake of 29.07 g/day) were at higher risk of all-cause mortality (Q1 vs. Q3, 1.16; 95% CI, 1.06–1.26), CVD mortality (Q1 vs. Q3, 1.14; 95% CI, 1.01–1.29), and other mortality (Q1 vs. Q3, 1.16; 95% CI, 1.01–1.33). No significant association was observed between hazard of cancer-related mortality and non-essential amino acid intake.

Table 3 Multivariate Cox regression derived HRs and 95% CIs for all-cause mortality and cause specific mortality by non-essential amino acids intake
Full size table

Branched-chain amino acids and mortality

In the minimally adjusted model, participants in the highest quintile of BCAAs intake were at higher risks of all-cause (HR for Q5 vs. Q3, 1.17; 95%CI, 1.08–1.26), CVD (HR for Q5 vs. Q3, 1.30; 95%CI, 1.17–1.45), and other mortality (HR for Q5 vs. Q3, 1.17; 95%CI, 1.03–1.32). However, when the fully adjusted model was applied, the significance of the associations was lost (Table 4).

Table 4 Multivariate Cox regression derived HRs and 95% CIs for all-cause mortality and cause specific mortality by BCAAs intake
Full size table

In the fully adjusted model, the first quintile was associated with all-cause mortality risk (P for non-linear trend < 0.001). Participants with a median BCAAs intake of 7.87 g/day were at about 15% higher risk of all-cause mortality in the fully adjusted model (HR for Q1 vs. Q3, 1.5; 95%CI, 1.06–1.25) (Fig. 3A).

Fig. 3
figure 3

Multivariable adjusted cubic spline models for the association between BCAAs intake and HRs for all-cause mortality (A) and CVD mortality (B); and for the association between AAAs intake and hazard ratios for all-cause mortality (C) and CVD mortality (D). Solid lines demonstrate estimates of HRs, while dashed lines demonstrate 95% confidence intervals. Abbreviations: AAAs, aromatic amino acids; BCAAs, branched chain amino acids; CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio

Full size image

Furthermore, a non-linear association was noted between BCAAs intake and the risk of CVD mortality, as shown in Fig. 3B. BCAAs intakes within the first quintile were associated with about 19% higher risk of CVD mortality in the fully adjusted model (HR for Q1 vs. Q3, 1.19; 95%CI, 1.05–1.34; P for non-linear trend = 0.005).

Aromatic amino acids and mortality

As shown in Fig. 3C, a non-linear association was observed between dietary aromatic amino acids intake and risk of all-cause mortality (P for non-linear trend < 0.001), with the highest HRs for participants in the first quintile (fully adjusted HR for Q1 vs. Q3, 1.19; 95% CI, 1.09–1.29). A similar trend was found for HRs of mortality from CVD (P for non-linear trend = 0.004) (Fig. 3D). Aromatic amino acids intake within the first quintile (median intake of 4.24 g/day), was significantly associated with increased hazards of CVD mortality (HR for Q1 vs. Q3, 1.21; 95% CI, 1.07–1.36) and cancer mortality (HR for Q1 vs. Q3, 1.28; 95% CI, 1.07–1.54) in the fully adjusted model (Table 5).

Table 5 Multivariate Cox regression derived HRs and 95% CIs for all-cause mortality and cause specific mortality by AAAs intake
Full size table

Sulfur-containing amino acids and mortality

SAAs intake appeared to be associated with all-cause, CVD, cancer, and other mortality in both minimally and fully adjusted models (P for non-linear trend < 0.05), as demonstrated in Fig. 4A-D.

Fig. 4
figure 4

Multivariable adjusted cubic spline models for the association between SAAs intake and HRs for all-cause mortality (A), CVD mortality (B), cancer mortality (C) and other causes of mortality (D). Solid lines demonstrate estimates of HRs, while dashed lines demonstrate 95% confidence intervals. Abbreviations: CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio; SAAs, sulfur-containing amino acids

Full size image

Those who were in the highest quintile of SAAs intake (3.96 g/day) had increased hazards of all-cause, CVD, and other mortality in the minimally adjusted models (P for non-linear trend < 0.001). However, this trend did not remain significant in the fully adjusted model.

Compared with those in the reference group, higher HRs for all-cause (HR for Q1 vs. Q3, 1.18; 95% CI, 1.09–1.28), CVD (HR for Q1 vs. Q3, 1.17; 95% CI, 1.03–1.32), cancer (HR for Q1 vs. Q3, 1.21; 95% CI, 1.01–1.45), and other (HR for Q1 vs. Q3, 1.18; 95% CI, 1.03–1.35) mortality were observed in the fully adjusted model for participants in the first quintile, with a median SAAs intake of 1.75 g/day (Table 6).

Table 6 Multivariate Cox regression derived HRs and 95% CIs for all-cause mortality and cause specific mortality by SAAs intake
Full size table

Each specific amino acids and mortality

We further investigated the associations between dietary intake of each amino acid and all-cause and cause-specific mortality. Minimally and fully adjusted HRs are presented in Supplementary Tables 1–18.

In the fully adjusted model, lower intakes of amino acids (first quintile) compared with third quintile were associated with about 12–18% increased hazards of all-cause mortality, for all amino acids except lysine (P for non-linear trend < 0.05 for all comparisons). Furthermore, high intake of proline was associated with significantly increased hazards of all-cause mortality (HR for Q5 vs. Q3, 1.11; 95% CI, 1.01–1.22).

In the fully adjusted model, participants with lower consumption of amino acids (first quintile) had about 13–22% higher hazards of CVD mortality, compared with the reference group (P for non-linear trend < 0.05 for all comparisons). However, such association was not evident for cysteine, glutamic acid, and glycine. Moreover, participants with high intake of glycine had significantly higher hazards of CVD mortality (HR for Q5 vs. Q3, 1.13; 95% CI, 1.00-1.29).

Increased adjusted HRs of cancer-related mortality were found among those who consumed low amount of tryptophan (Q1 vs. Q3, 1.22; 95%CIs, 1.02–1.47), threonine (Q1 vs. Q3, 1.21; 95%CIs, 1.00-1.45), phenylalanine (Q1 vs. Q3, 1.24; 95%CIs, 1.03–1.50), tyrosine (Q1 vs. Q3, 1.21; 95%CIs, 1.01–1.45), valine (Q1 vs. Q3, 1.20; 95%CIs, 1.00-1.44), arginine (Q1 vs. Q3, 1.24; 95%CIs, 1.04–1.48), glycine (Q1 vs. Q3, 1.21; 95%CIs, 1.02–1.44), and serine (Q1 vs. Q3, 1.25 (1.04–1.50).

Adjusted HRs of other causes of mortality were increased among participants within the first quintile of cysteine (Q1 vs. Q3, 1.23; 95%CIs, 1.07–1.42), arginine (Q1 vs. Q3, 1.16, 95%CIs, 1.01–1.32), glycine (Q1 vs. Q3, 1.14; 95%CIs, 1.00-1.30), and proline (Q1 vs. Q3, 1.15; 95%CIs, 1.00-1.32).

Stratified and sensitivity analyses

As a sensitivity analysis, the robustness of data was further examined by excluding individuals who lost to follow-up, died or were diagnosed with cancer within the first two years of the study. In the two-year lag analysis, the risk of all-cause and cause-specific mortality did not differ significantly among the extreme quintiles of amino acids consumption (data not shown).

We conducted stratified analyses to investigate whether the associations between categories of amino acids and mortality were modified by baseline characteristics. Stratification by age, revealed significant interactions between age and intake of essential amino acids (P for interaction = 0.025), BCAAs (P for interaction = 0.010), AAAs (P for interaction = 0.011), and SAAs (P for interaction = 0.038), in relation to hazards of all-cause mortality. Among those younger than 65 years, increased hazards of mortality in higher intakes were observed. However, in older adults (≥ 65 years), lower intakes were associated with increased hazards of mortality (Fig. 5). After stratification by smoking status, there was a significant interaction between smoking status and BCAAs and AAAs intake in relation to the risk of all-cause mortality (P for interaction ˂0.05). In general, the higher risk of all-cause mortality in lower amino acid consumption appeared to be more pronounced in ever-smoker participants in comparison to never-smoker participants. For non-essential amino acids, the associations appeared to be greater among diabetic participants (P for interaction 0.026). In SAAs, in addition to age, significant interaction with sex was also observed for all-cause mortality (P for interaction 0.027). No significant interactions have been found across the stratum for BMI and history of hypertension (Supplementary Figs. 1–5).

Fig. 5
figure 5

Multivariate Cox regression derived HRs and 95% CIs for all-cause mortality by amino acids intake which were categorized according to age. Multivariable models were adjusted for sex, intake of energy, BMI, cigarette smoking, opium use, diabetes, hypertension, alcohol use, wealth index, education, physical activity, total lipid intake, and total protein intake.*Indicate significant effect (P-value < 0.05). Abbreviations: BCAA, branched-chain amino acids; AAAs, aromatic amino acids; SAAs, sulfur-containing amino acids; AAAs aromatic amino acids; CI, confidence interval; HR, hazard ratio; Q, quintile; Ref, reference

Full size image

Discussion

In this large Iranian prospective study, we found evidence for the association of dietary patterns of amino acids with mortality from all causes, CVD, cancer, or other causes. These findings tended to follow non-linear associations. Lower amino acid intake within the first quintiles compared to the median quintile, was either associated with increased mortality risk or had no added benefit. One important finding of our study was the age interaction for the associations between dietary amino acids and mortality. While a high amino acid diet, irrespective of the amino acid group, was detrimental in middle-aged adults, the opposite effect was found in older adults and increased hazards of mortality were evident among those with low amino acid intake. Accordingly, it would be of great significance for older adults to consume sufficient dietary amino acids, from the view of longevity. Previous studies carried out in older adults also found an inverse association between protein intake and mortality [18,19,20,21]. Inadequate protein intake in older adults contributes to frailty, sarcopenia, osteoporosis, and impaired immune responses [22,23,24]. The responsiveness to the anabolic stimulus of amino acid intake decreases by the increasing age [25]. Several factors may cause decreased sensitivity of muscles in response to dietary protein intakes in older individuals including: impaired protein digestion and amino acid absorption, increased splanchnic amino acids retention and subsequent decreased circulatory amino acid levels, decreased physical activity, decreased amino acid uptake by muscles, and impaired intracellular anabolic signaling [26].

Nonetheless, this decreased sensitivity in older persons can be overcome by higher amounts of amino acids consumptions. Induction of responses similar to those in younger adults by larger dose of protein provides evidence for favorable effects of higher protein intake in older ages [27]. On the other hand, Levin et al. reported higher risks of all-cause and cancer mortality among middle-aged adults with higher protein intakes, who received 20% or more of their required calories from proteins [21], which was supported by our results.

We found that essential amino acid intakes within the first quintile (median intake of 16.9 g/day) were associated with increased risk of all-cause and CVD mortality. The association of low intake of essential amino with the increased risk of all-cause and CVD mortality in the present study among Iranians is concordant with those reported by Ha et al., in an analysis from a national cohort survey in the U.S., with a median intake of 11.7 g/day [28]. On the other hand, an association of diets with high positive loadings for essential amino acids and CVD mortality was found among adults in Canada and the U.S [29]. Given the paucity of evidence on these associations for essential amino acids, further studies are warranted to provide information on the association and its direction.

We also found increased hazard of all-cause, CVD, and other causes of mortality in low intake of non-essential amino acids (median intake of 29 g/day). Previously, it was shown that diets with high loading on non-essential amino acids particularly arginine, glycine, and asparagine had negative association with risk of CVD mortality [29]. Plant-based proteins contain relatively high non-essential amino acids and low essential amino acids content, when compared with animal-based proteins [30]. Considerable evidence has been accumulated regarding the beneficial role of plant-based protein in long-term health outcomes. When animal proteins such as egg, red and processed meats were replaced by plant-based proteins, lower risk of total, cancer, and CVD mortality has been observed [31,32,33]. Our data suggest that the beneficial effects of plant-based protein might not be related to their amino acid contents and attract the attention to the other components related to protein-rich foods. Whole grain food contains high bioactive substances, including antioxidants, minerals, vitamins, phenolic compounds, and phytoestrogens [34], associated with reduced CVD risk factors [35]. Additionally, the effects of red meat on human health outcomes might be due to ingredients like sodium, nitrates, nitrites, and heme iron [36, 37].

Regarding BCAAs, our study indicated increased risks of all-cause and CVD mortality in those with lower BCAAs intake (median intake of 7.9 g/day). Previous studies on dietary BCAAs intake patterns and mortality have produced mixed results. High BCAAs intake has shown adverse associations with CVD mortality in adults living in the U.S. and Canada [29]. In our study, such association was evident in the minimally adjusted model, however, this did not remain significant after further adjustment for potential confounders. In a population from the Third National Health and Nutrition Examination Survey (NHANES III) database, BCAAs intake was inversely associated with the risk of all-cause mortality, but was not associated with cancer or CVD mortality [38]. The results from the Health Professionals Follow-up Study (HPFS) and Nurses’ Health Study (NHS) were suggestive of an adverse association between high dietary BCAAs intake (median intake of 16.14 g/day) and all-cause mortality in patients with colorectal cancer [39]. Some other studies have examined the association between serum BCAAs concentrations and mortality. Serum BCAAs concentrations were inversely associated with cardiovascular risk factors and CVD mortality in the elderly [40, 41]. With increasing serum BCAA concentration, the risk of all-cause mortality steadily decreases, whereas, the risk of CVD mortality only decreases up to a certain concentration of BCAAs [40]. In the UK Biobank cohort study, total BCAAs, isoleucine, and valine levels were shown to be independently linked to stroke [42]. Nonetheless, recent investigations found only a weak positive correlation between amino acids consumption and their corresponding serum levels [43].

Our analysis revealed a significant non-linear association between dietary aromatic amino acid and risk of all-cause and CVD mortality. In another recent analysis from NHANES III, higher aromatic amino acid intake (median intake of 6.4 g/day) was associated with decreased risk of CVD mortality [44]. However, excessive dietary aromatic amino acids (median intake of 9.29% of total daily protein intake) may increase the risk of hypertension [45] and might be harmful to human health [44]. Although we did not find decreased risk of mortality in high aromatic amino acids intakes, the increased risk of all-cause and CVD mortality was found in those with low aromatic amino acid intake (median intake of 4.24 g/day). Considering the different median values of amino acids intake across studies, comparison between study results should interpreted with caution.

Based on our results, increased hazards of all-cause, CVD, cancer, and other causes of mortality were found to be associated with low SAAs intake (median intake of 1.7 g/day). Dong et al. in NHANES III study revealed that SAAs intake close to the estimated average requirement (15 mg/kg/day), decreased the risk of cardiometabolic disease [10]. They also found increased risk of diabetes mortality [46] and cardiometabolic diseases [10] in higher SAAs intake. However, increased hazard of mortality in higher intakes was not confirmed in the present study after multivariable adjustment. Another previous epidemiological research on the Iranian population found decreased risks of CVD events in those who consume higher amounts of SAA (median intake of 3.13 g/day) [9]. Some other studies explored each of the SAAs. Decreased methionine intake by postmenopausal women was associated with a lower risk of breast cancer mortality and all-cause mortality [47]. Other studies reported no association between methionine intake and the risk of esophageal, gastric [48], and breast cancer [49]. Serum levels of methionine were also not associated with the risk of lung cancer [50].

Compatible with the results from amino acid groups, increased risks of mortality were observed in lower intakes of each amino acid, but high intakes of glycine and proline amino acids were also found to increase the risk of CVD and all-cause mortality, respectively. Keeping in mind that dietary intake of amino acids might not necessarily correlate with their circulating levels. Genome-wide association studies of glycine metabolism support potential mechanisms and causality of the association between CVD and glycine level, albeit in favor of lower CVD risk in those with higher genetically predicted plasma glycine level [51, 52]. Another epidemiological study reported increased risk of mortality from ischemic stroke in higher glycine intakes [53]. Dietary glycine may directly have an adverse effect on blood pressure [54]. Nonetheless, replication of our results is required in future epidemiological studies.

Probable explanations for discrepancy in the findings among studies noted above include differences in the important study elements like endpoint determination, dietary pattern derivation, population characteristics, adjusted confounders, sample size, and methodology employed.

The strengths of this analysis are its prospective design including a representative sample of the general population with a high length of follow-up. Another strength of our research is the adjustment for several potential confounders, including multiple dietary and lifestyle factors.

We also need to acknowledge several limitations. First, the use of self-reported FFQ is a suboptimal approach to measuring nutrient intake. Second, habitual nutrient intakes were assessed only at baseline and it may have been altered during the follow-up. Third, our data on a number of confounding factors were self-reported by study participants, which may have led to measurement error. Fourth, observed findings could be subject to unmeasured or residual confounding factors like diet quality. Finally, the study results based on an Iranian middle-aged population, cannot be generalized to other ethnicities or very old populations who may have other nutritional requirements [55].

Additional studies in other populations are required to determine optimal ranges and sources of dietary protein and refine global dietary recommendations.

Conclusion

This study found the suggestion of non-linear associations between amino acid intake and risk of mortality in the middle-aged and older Iranian population. Low intake of different amino acid groups was found to be associated with increased mortality. For instance, increasing amount of dietary amino acids from the ranges within the first quintile to the second quintile is accompanied to decreased HRs of CVD mortality. Accordingly, adequate intake of all categories of amino acids is critical to maintain the overall health. The significant age interaction for the association between mortality and amino acids consumption highlights the importance of individualized protein recommendations for each age group. Moreover, our findings highlight the complex and divergent associations of amino acid categories with health outcomes, indicating that it could be misleading to provide advice on protein intake without specifying the components, even though this can be challenging to measure in practice.

Data availability

Data described in the manuscript, code book, and analytic code will be made available upon reasonable request from the corresponding author.

References

  1. Clark MA, Springmann M, Hill J, Tilman D. Multiple health and environmental impacts of foods. Proceedings of the National Academy of Sciences. 2019;116(46):23357-62.

  2. Afshin A, Sur PJ, Fay KA, Cornaby L, Ferrara G, Salama JS, et al. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the global burden of Disease Study 2017. Lancet. 2019;393(10184):1958–72.

    Article  Google Scholar 

  3. You A. Dietary guidelines for americans. Volume 7. US Department of Health and Human Services and US Department of Agriculture; 2015.

  4. Yang YX, Wang XL, Leong PM, Zhang HM, Yang XG, Kong LZ, et al. New Chinese dietary guidelines: healthy eating patterns and food-based dietary recommendations. Asia Pac J Clin Nutr. 2018;27(4):908–13.

    PubMed  Google Scholar 

  5. Willett WC, Stampfer MJ. Current evidence on healthy eating. Annu Rev Public Health. 2013;34:77–95.

    Article  PubMed  Google Scholar 

  6. Mozaffarian D, Ludwig DS. Dietary guidelines in the 21st century—a time for food. JAMA. 2010;304(6):681–2.

    Article  CAS  PubMed  Google Scholar 

  7. Dai Z, Zheng W, Locasale JW. Amino acid variability, tradeoffs and optimality in human diet. Nat Commun. 2022;13(1):6683.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Bender DA. Amino acid metabolism. Wiley; 2012.

  9. Mirmiran P, Bahadoran Z, Ghasemi A, Azizi F. Contribution of dietary amino acids composition to incidence of cardiovascular outcomes: a prospective population-based study. Nutr Metabolism Cardiovasc Dis. 2017;27(7):633–41.

    Article  CAS  Google Scholar 

  10. Dong Z, Gao X, Chinchilli VM, Sinha R, Muscat J, Winkels RM et al. Association of sulfur amino acid consumption with cardiometabolic risk factors: cross-sectional findings from NHANES III. eClinicalMedicine. 2020;19.

  11. Pourshams A, Khademi H, Malekshah AF, Islami F, Nouraei M, Sadjadi AR, et al. Cohort profile: the Golestan Cohort Study—a prospective study of oesophageal cancer in northern Iran. Int J Epidemiol. 2010;39(1):52–9.

    Article  PubMed  Google Scholar 

  12. Malekshah A, Kimiagar M, Saadatian-Elahi M, Pourshams A, Nouraie M, Goglani G, et al. Validity and reliability of a new food frequency questionnaire compared to 24 h recalls and biochemical measurements: pilot phase of Golestan cohort study of esophageal cancer. Eur J Clin Nutr. 2006;60(8):971–7.

    Article  CAS  PubMed  Google Scholar 

  13. Ghafarpour M, Houshiar-Rad A, Kianfar H, Ghaffarpour M. The manual for household measures, cooking yields factors and edible portion of food. Tehran: Keshavarzi; 1999.

    Google Scholar 

  14. Hashemian M, Poustchi H, Abnet CC, Boffetta P, Dawsey SM, Brennan PJ, et al. Dietary intake of minerals and risk of esophageal squamous cell carcinoma: results from the Golestan Cohort Study123. Am J Clin Nutr. 2015;102(1):102–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Nalini M, Oranuba E, Poustchi H, Sepanlou SG, Pourshams A, Khoshnia M, et al. Causes of premature death and their associated risk factors in the Golestan Cohort Study, Iran. BMJ open. 2018;8(7):e021479.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Islami F, Kamangar F, Nasrollahzadeh D, Aghcheli K, Sotoudeh M, Abedi-Ardekani B, et al. Socio-economic status and oesophageal cancer: results from a population-based case-control study in a high-risk area. Int J Epidemiol. 2009;38(4):978–88.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Khademi H, Etemadi A, Kamangar F, Nouraie M, Shakeri R, Abaie B, et al. Verbal autopsy: reliability and validity estimates for causes of death in the Golestan Cohort Study in Iran. PLoS ONE. 2010;5(6):e11183.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Meroño T, Zamora-Ros R, Hidalgo-Liberona N, Rabassa M, Bandinelli S, Ferrucci L, et al. Animal protein intake is inversely Associated with Mortality in older adults: the InCHIANTI Study. Journals Gerontology: Ser A. 2022;77(9):1866–72.

    Google Scholar 

  19. Zaslavsky O, Zelber-Sagi S, Hebert JR, Steck SE, Shivappa N, Tabung FK, et al. Biomarker-calibrated nutrient intake and healthy diet index associations with mortality risks among older and frail women from the women’s Health Initiative. Am J Clin Nutr. 2017;105(6):1399–407.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Bates CJ, Mansoor MA, Pentieva KD, Hamer M, Mishra GD. Biochemical risk indices, including plasma homocysteine, that prospectively predict mortality in older British people: the National Diet and Nutrition Survey of people aged 65 years and over. Br J Nutr. 2010;104(6):893–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Levine ME, Suarez JA, Brandhorst S, Balasubramanian P, Cheng CW, Madia F, et al. Low protein intake is associated with a major reduction in IGF-1, cancer, and overall mortality in the 65 and younger but not older population. Cell Metab. 2014;19(3):407–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Landi F, Calvani R, Tosato M, Martone AM, Ortolani E, Savera G et al. Protein Intake and Muscle Health in Old Age: from Biological plausibility to clinical evidence. Nutrients. 2016;8(5).

  23. Bauer J, Biolo G, Cederholm T, Cesari M, Cruz-Jentoft AJ, Morley JE, et al. Evidence-based recommendations for optimal dietary protein intake in older people: a position paper from the PROT-AGE Study Group. J Am Med Dir Assoc. 2013;14(8):542–59.

    Article  PubMed  Google Scholar 

  24. Ni Lochlainn M, Bowyer RCE, Steves CJ. Dietary protein and muscle in Aging people: the potential role of the gut Microbiome. Nutrients. 2018;10(7).

  25. Traylor DA, Gorissen SHM, Phillips SM, Perspective. Protein requirements and optimal intakes in aging: are we ready to recommend more than the recommended Daily Allowance? Adv Nutr. 2018;9(3):171–82.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Burd NA, Gorissen SH, Van Loon LJ. Anabolic resistance of muscle protein synthesis with aging. Exerc Sport Sci Rev. 2013;41(3):169–73.

    Article  PubMed  Google Scholar 

  27. Baum JI, Kim I-Y, Wolfe RR. Protein consumption and the elderly: what is the optimal level of intake? Nutrients. 2016;8(6):359.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Ha K, Sakaki JR, Chun OK. Nutrient adequacy is Associated with reduced mortality in US adults. J Nutr. 2021;151(10):3214–22.

    Article  PubMed  Google Scholar 

  29. Tharrey M, Mariotti F, Mashchak A, Barbillon P, Delattre M, Huneau J-F, et al. Patterns of amino acid intake are strongly associated with cardiovascular mortality, independently of the sources of protein. Int J Epidemiol. 2020;49(1):312–21.

    Article  PubMed  Google Scholar 

  30. Gorissen SHM, Crombag JJR, Senden JMG, Waterval WAH, Bierau J, Verdijk LB, et al. Protein content and amino acid composition of commercially available plant-based protein isolates. Amino Acids. 2018;50(12):1685–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Song M, Fung TT, Hu FB, Willett WC, Longo VD, Chan AT, et al. Association of animal and plant protein intake with all-cause and cause-specific mortality. JAMA Intern Med. 2016;176(10):1453–63.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Budhathoki S, Sawada N, Iwasaki M, Yamaji T, Goto A, Kotemori A, et al. Association of animal and plant protein intake with all-cause and cause-specific mortality in a Japanese cohort. JAMA Intern Med. 2019;179(11):1509–18.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Huang J, Liao LM, Weinstein SJ, Sinha R, Graubard BI, Albanes D. Association between Plant and Animal Protein Intake and overall and cause-specific mortality. JAMA Intern Med. 2020;180(9):1173–84.

    Article  CAS  PubMed  Google Scholar 

  34. Slavin JL. Mechanisms for the impact of whole grain foods on cancer risk. J Am Coll Nutr. 2000;19(3 Suppl):s300–7.

    Article  Google Scholar 

  35. Hollænder PL, Ross AB, Kristensen M. Whole-grain and blood lipid changes in apparently healthy adults: a systematic review and meta-analysis of randomized controlled studies. Am J Clin Nutr. 2015;102(3):556–72.

    Article  PubMed  Google Scholar 

  36. Etemadi A, Sinha R, Ward MH, Graubard BI, Inoue-Choi M, Dawsey SM, et al. Mortality from different causes associated with meat, heme iron, nitrates, and nitrites in the NIH-AARP Diet and Health Study: population based cohort study. BMJ. 2017;357:j1957.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Pan A, Sun Q, Bernstein AM, Schulze MB, Manson JE, Stampfer MJ, et al. Red meat consumption and mortality: results from 2 prospective cohort studies. Arch Intern Med. 2012;172(7):555–63.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Xu B, Wang M, Pu L, Shu C, Li L, Han L. Association of dietary intake of branched-chain amino acids with long-term risks of CVD, cancer and all-cause mortality. Public Health Nutr. 2021;25(12):1–11.

    CAS  PubMed  Google Scholar 

  39. Long L, Yang W, Liu L, Tobias DK, Katagiri R, Wu K et al. Dietary intake of branched-chain amino acids and survival after colorectal cancer diagnosis. Int J Cancer. 2020.

  40. Moissl AP, Lorkowski S, Meinitzer A, Pilz S, Scharnagl H, Delgado GE, et al. Association of branched-chain amino acids with mortality-the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. iScience. 2023;26(4):106459.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Le Couteur DG, Ribeiro R, Senior A, Hsu B, Hirani V, Blyth FM, et al. Branched chain amino acids, cardiometabolic risk factors and outcomes in older men: the Concord Health and Ageing in Men Project. Journals Gerontology: Ser A. 2020;75(10):1805–10.

    Google Scholar 

  42. Xu H, Wang X, Geng G, Xu X, Liu L, Zhang Y, et al. Association of circulating branched-chain amino acids with Cardiovascular diseases: a mendelian randomization study. Nutrients. 2023;15(7):1580.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Iguacel I, Schmidt JA, Perez-Cornago A, Van Puyvelde H, Travis R, Stepien M, et al. Associations between dietary amino acid intakes and blood concentration levels. Clin Nutr. 2021;40(6):3772–9.

    Article  CAS  PubMed  Google Scholar 

  44. Xu D, Xu Y, Zhang B, Wang Y, Han L, Sun J, et al. Higher dietary intake of aromatic amino acids was associated with lower risk of cardiovascular disease mortality in adult participants in NHANES III. Nutr Res. 2023;113:39–48.

    Article  CAS  PubMed  Google Scholar 

  45. Teymoori F, Asghari G, Mirmiran P, Azizi F. High dietary intake of aromatic amino acids increases risk of hypertension. J Am Soc Hypertens. 2018;12(1):25–33.

    Article  CAS  PubMed  Google Scholar 

  46. Dong Z, Gao X, Chinchilli VM, Sinha R, Muscat J, Winkels R, et al. Association of dietary sulfur amino acid intake with mortality from diabetes and other causes. Eur J Nutr. 2022;61(1):289–98.

    Article  CAS  PubMed  Google Scholar 

  47. Sun Y, Fowke JH, Liang X, Mozhui K, Sen S, Bao W et al. Changes in Dietary Intake of Methionine, Folate/Folic acid and vitamin B12 and survival in Postmenopausal women with breast Cancer: a prospective cohort study. Nutrients. 2022;14(22).

  48. Xiao Q, Freedman ND, Ren J, Hollenbeck AR, Abnet CC, Park Y. Intakes of folate, methionine, vitamin B6, and vitamin B12 with risk of esophageal and gastric cancer in a large cohort study. Br J Cancer. 2014;110(5):1328–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Bassett JK, Baglietto L, Hodge AM, Severi G, Hopper JL, English DR, et al. Dietary intake of B vitamins and methionine and breast cancer risk. Cancer Causes Control. 2013;24:1555–63.

    Article  PubMed  Google Scholar 

  50. Fanidi A, Muller DC, Yuan JM, Stevens VL, Weinstein SJ, Albanes D, et al. Circulating folate, vitamin B6, and methionine in relation to Lung Cancer Risk in the Lung Cancer Cohort Consortium (LC3). J Natl Cancer Inst. 2018;110(1):57–67.

    Article  CAS  PubMed  Google Scholar 

  51. Wittemans LBL, Lotta LA, Oliver-Williams C, Stewart ID, Surendran P, Karthikeyan S, et al. Assessing the causal association of glycine with risk of cardio-metabolic diseases. Nat Commun. 2019;10(1):1060.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Hartiala JA, Wilson Tang W, Wang Z, Crow AL, Stewart AF, Roberts R, et al. Genome-wide association study and targeted metabolomics identifies sex-specific association of CPS1 with coronary artery disease. Nat Commun. 2016;7(1):10558.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Nagata C, Wada K, Tamura T, Kawachi T, Konishi K, Tsuji M, et al. Dietary intakes of glutamic acid and Glycine are Associated with Stroke Mortality in Japanese Adults1,2. J Nutr. 2015;145(4):720–8.

    Article  CAS  PubMed  Google Scholar 

  54. Stamler J, Brown IJ, Daviglus ML, Chan Q, Miura K, Okuda N, et al. Dietary glycine and blood pressure: the International Study on Macro/Micronutrients and blood pressure. Am J Clin Nutr. 2013;98(1):136–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Weiler M, Hertzler SR, Dvoretskiy S. Is it time to reconsider the U.S. Recommendations for Dietary Protein and amino acid. Intake? Nutrients. 2023;15(4):838.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank the study participants and the Behvarzes for their long term cooperation. We also thank the local authorities, Golestan University of Medical Sciences officials, local physicians, elders and religious leaders as well as the general physicians, nurses and nutritionists in the enrolment teams for their collaboration.

Funding

This work was supported by Tehran University of Medical Sciences (grant number: 81/15), Cancer Research UK (grant number: C20/A5860), the National Cancer Institute/National Institutes of Health, Intramural Research Program, and various collaborative research agreements with International Agency for Research on Cancer. The funding sources had no role in study design, data collection, data analysis, data interpretation or writing of the report.

Author information

Author notes

  1. Asieh Mansour and Sayed Mahmoud Sajjadi-Jazi equally contributed as the first authors.

Authors and Affiliations

  1. Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran

    Asieh Mansour, Sayed Mahmoud Sajjadi-Jazi, Maryam Mirahmad & Pooria Asili

  2. Liver and Pancreaticobiliary Disease Research Center, Digestive Diseases Research Institute, Tehran University of Medical Sciences, Shariati Hospital, Kargar Shomali St, Tehran, 14117-13135, Iran

    Maryam Sharafkhah, Sahar Masoudi, Akram Pourshams & Reza Malekzadeh

  3. Digestive Oncology Research Center, Digestive Diseases Research Institute, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran

    Hossein Poustchi

  4. Heart Disease Phenomics Laboratory, Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA

    Maryam Hashemian

  5. Department of Clinical Nutrition and Dietetics, Faculty of Nutrition and Food Technology, National Nutrition and Food Technology Research Institute, Shahid Beheshti University of Medical Sciences, 46, West Arghavan St., Farahzadi Blvd., Shahrak Gharb, Tehran, Iran

    Azita Hekmatdoost

Authors
  1. Asieh Mansour
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Sayed Mahmoud Sajjadi-Jazi
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Maryam Mirahmad
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Pooria Asili
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Maryam Sharafkhah
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Sahar Masoudi
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Hossein Poustchi
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Akram Pourshams
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Maryam Hashemian
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Azita Hekmatdoost
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Reza Malekzadeh
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

A.M. Analysis and interpretation of data, Drafting of manuscript, Critical revision, S.M.S.J. Drafting of manuscript, Critical revision. M.M. Drafting of manuscript, Critical revision, P.A. Drafting of manuscript, M.S. Analysis and interpretation of data, S.M. Analysis and interpretation of data, H.P. Acquisition of data, A.P. Acquisition of data, M.H. Critical revision, A.H. Critical revision, R.M. Acquisition of data, Critical revision.

Corresponding authors

Correspondence to Azita Hekmatdoost or Reza Malekzadeh.

Ethics declarations

Ethical approval

Ethical approval for the Golestan Cohort Study was obtained from the Institutional Review Boards of the Digestive Disease Research Center (DDRC) at Tehran University of Medical Sciences, the US National Cancer Institute (NCI), and the World Health Organization International Agency for Research on Cancer (IARC). Written informed consent was obtained from all participants.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mansour, A., Sajjadi-Jazi, S.M., Mirahmad, M. et al. Dietary amino acids intake and all-cause and cause-specific mortality: results from the Golestan Cohort Study. Nutr J 23, 141 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12937-024-01044-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12937-024-01044-x

Keywords

Nutrition Journal

ISSN: 1475-2891

Contact us