Abstract
BACKGROUND/OBJECTIVES
Although dietary protein intake has received significant attention recently, research on dietary amino acid (AA) intake remains limited. Thus, this study aimed to estimate AA intake and food sources among Korean adults between 2010 and 2022.
SUBJECTS/METHODS
Based on the Korea National Health and Nutrition Examination Survey data, 69,664 adults aged 19 yrs or older were included. Essential AA (EAA), branched-chain AA (BCAA), and nonessential AA (NEAA) intakes were estimated.
RESULTS
The average total AA intake over the past 13 yrs was 62.1 g/day, consisting of 24.8 g/day of EAAs (11.8 g/day of BCAAs) and 37.3 g/day of NEAAs. Leucine was the most commonly consumed EAA, while glutamic acid was the most consumed NEAA. Over the study period, total AA intake remained stable. However, total AA intake relative to body weight significantly decreased, whereas intake relative to total energy and protein intake significantly increased. Similar trends were observed for EAAs, BCAAs, and NEAAs (P for trend < 0.0001 for all). Meat and grains were the primary food sources of AAs, and the contribution of meat consistently increased (P for trend < 0.0001).
CONCLUSION
While the total absolute AA intake has remained stable over the past 13 yrs, AA density relative to protein and energy intake has increased, accompanied by changes in individual AA intake over the past decade. These findings may inform future revisions of AA intake recommendations for Koreans and facilitate further research on the association between dietary AAs and various diseases.
Keywords: Amino acids, protein, dietary intake, food, Korea
INTRODUCTION
Proteins, composed of amino acid (AA) peptide bonds, are vital nutrients that regulate various physiological processes, such as signaling molecules, hormones, and precursors for low-molecular-weight nitrogen-containing compound synthesis [1,2,3]. The nutritional value of protein is largely determined by the type and amount of constituent AAs; thus ensuring sufficient AA intake and maintaining a balanced composition relative to protein intake are both essential for optimal health [4].
Among AAs, essential AAs (EAAs) cannot be synthesized endogenously and must be obtained through diet [5]. EAAs delay fatigue, promote muscle protein synthesis, regulate immune function, and facilitate ammonia detoxification. Branched-chain AAs (BCAAs), including valine, leucine, and isoleucine, play crucial roles in hormone secretion, hormonal action, and intracellular signaling pathways [6,7,8,9]. Conditional EAAs (CEAAs) are obtained through diets when endogenous synthesis is insufficient to meet metabolic demands [10]. In contrast, nonessential AAs (NEAAs) are readily synthesized in the body and are necessary for cognitive function and normal neuronal growth [6,10,11,12].
However, elevated levels of total AAs and their derivatives, such as ammonia, homocysteine, and asymmetric dimethylarginine, can contribute to neurological disorders, oxidative stress, and cardiovascular diseases [3]. A cohort study of Iran adults aged 35–65 yrs found that individuals with higher intakes of BCAAs and EAAs had a greater risk of developing type 2 diabetes than those with lower intakes [13]. Additionally, excessive NEAA intake is associated with an increased risk of cardiovascular diseases [14]. Previous studies have shown that excessive AA intake poses health risks, whereas insufficient intake may limit protein synthesis [4]. Moreover, an imbalance in AAs can impair protein utilization in the body, potentially leading to anemia and weakened immune function [4]. These findings indicate the need to monitor the quantity and composition of AA intake.
Most existing studies have focused primarily on total protein intake, potentially overlooking the distinct health effects of different AA profiles, with limited evidence on AA profiles among Koreans. Protein quality is often assessed using indices such as the Protein Digestibility-Corrected Amino Acid Score and the Digestible Indispensable Amino Acid Score. However, these indices require detailed information on AA digestibility and food matrices, which are generally unavailable in large-scale dietary surveys [15]. Therefore, the evaluation of dietary intake at the individual AA level is crucial for a more comprehensive understanding of the relationship between protein quality and health outcomes.
From 2010 to 2019, protein intake in Korea has increased in parallel with greater consumption of animal-based foods, reflecting the ongoing westernization of the Korean diet [15]. Additionally, public interest in high-protein diets and protein/AA supplementation has grown [16,17,18], primarily to enhance muscle mass, strength, and immune function [10]. Although some dietary recommendations for AAs have been established [10], limited data on AA intake among Koreans hinders the accurate assessment of individual AA consumption and evaluation of adequacy. The increasing use of AA supplements and functional foods underscores the need for robust evidence to ensure their safety [10]. Identifying major food sources and understanding the differences in AA composition across foods can assist dietary and health professionals in assessing diet quality and developing strategies to meet nutrient recommendations [19]. Therefore, this study aimed to evaluate AA intake levels and major food sources among Korean adults over the past 13 yrs using an AA composition database of commonly consumed foods in Korea.
SUBJECTS AND METHODS
Study data and participants
This study used data from the 2010–2022 Korea National Health and Nutrition Examination Survey (KNHANES), conducted annually under the National Health Promotion Act, to provide national-level statistics for approximately 10,000 Korean individuals. The KNHANES comprises 3 main components: health examinations, health interviews, and nutrition surveys. Further details on the KNHANES can be found elsewhere [20]. Initial study participants were adults aged 19 yrs and older (n = 70,815) who participated in a 1-day 24-h recall survey. Individuals with daily energy intake below 500 kcal or above 5,000 kcal (n = 1,150), and those with a protein intake of 0 g (n = 1), were excluded, resulting in a final sample size of 69,664 individuals. The KNHANES was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Korea Disease Control and Prevention Agency (KCDC) (approval numbers: 2010-02CON-21-C, 2011-02CON-06-C, 2012-01EXP-01-2C, 2013-07CON-03-4C, 2013-12EXP-03-5C, 2018-01-03-P-A, 2018-01-03-C-A 2018-01-03-2C-A, 2013-01-03-5C-A, and 2018-01-03-4C-A). Written informed consent was obtained from all subjects. This study received Institutional Review Board exemption from Jeju University in Republic of Korea (approval number: JJNU-IRB-2024-078).
Estimation of AA intake
Dietary intake was assessed using the 1-day 24-h recall data which was administered by a trained-staff through face-to-face interview. As the KNHANES does not provide data on AA consumption, AA intake was estimated by linking food items consumed by individuals to an AA composition database. This database was constructed primarily from AA composition data in the Korean Food Composition Table developed by the Rural Development Administration [21,22], supplemented with information from the Food and Nutrition Composition Database of the Ministry of Food and Drug Safety [23], and research reports from the Korea Health Industry Development Institute [24]. For food items without AA content in these databases, values were imputed either by using moisture conversion factors for items with varying moisture content but similar nutrient composition (e.g., fresh vs. dried fish) or by substituting values from similar items (e.g., domestic vs. imported products). When items shared identical ingredients but differed only in moisture content, substitution values were calculated using moisture conversion factors assigned to third-level food codes. These factors were originally developed by the KCDC [25], and approximately 1.4% of the final database food codes were imputed using this method. Substitution with similar foods was applied when using moisture conversion factors that were either infeasible or less appropriate than when using a comparable food. For example, substitutions were made between wild and farmed types or between specific branded processed foods (e.g., generic butter vs. commercial butter). Approximately 40% of the final food codes in the database were imputed using similar food substitutions. Among the 5,448 food items reported in the 2010–2022 KNHANES, 3,977 had AA content values and were included in the final database. The database includes 18 AAs categorized into EAAs and NEAAs according to the 2020 Dietary Reference Intakes for Koreans [10]. EAAs included BCAAs (valine, leucine, and isoleucine), methionine, lysine, phenylalanine, histidine, threonine, and tryptophan. NEAAs included CEAAs, such as arginine, cysteine, tyrosine, glycine, and proline, as well as alanine, aspartic acid, glutamic acid, and serine. Individual AA intake (g/day) from each food item was calculated by multiplying the AA content by the total grams of food consumed. Additionally, AA intake was estimated in terms of g/kg of body weight, g per 1,000 kcal of total energy intake, and g per gram of total protein intake, to account for variations in body size, energy intake, and protein intake. The AA intake was evaluated according to body weight, which is an important factor for estimating AA requirements [26,27]. To evaluate the contribution of food groups to AAs, food items were categorized as grains (white rice, mixed grains, and flour), potatoes and starches, sugars, beans, seeds and nuts, vegetables, mushrooms, fruits, seaweeds, seasonings, fats and oils, meat (red meat, processed meat, and poultry), eggs, seafood, dairy, and beverages
Other variables
Trends in AA intake were evaluated across the survey periods: 2010–2012, 2013–2015, 2016–2018, 2019–2021, and 2022. Socioeconomic characteristics included education level, household income level, and region. Education levels were categorized as elementary school or lower, middle school, high school, and college or higher. Household income levels were categorized into low, lower-middle, upper-middle, and high based on quartiles of monthly average household income. Regions were categorized as metropolitan, urban, and rural areas. Metropolitan areas include Seoul and other metropolitan cities. Urban areas include “Dong” whereas “eup” or “myeon” are categorized as rural areas, including those in metropolitan cities.
Statistical analysis
All statistical analyses were performed using SAS 9.4 (SAS Institute, Cary, NC, USA). The complex sampling design parameters of the KNHANES, including strata and clusters, and sampling weights, were applied using the PROC SURVEY procedure. Continuous variables are presented as mean ± SE, and categorical variables are presented as frequency (%). Differences in AA and protein intake across the survey period were tested using an analysis of variance (ANOVA), and Scheffe’s post hoc comparisons were conducted to examine the differences in AA and protein intake between the 2010–2012 and 2022 survey periods. Differences in the mean AA intake over 13 yrs according to sociodemographic characteristics were assessed using t-test or ANOVA. Linear trends in AA and protein intake, as well as the contribution of food groups, were assessed by modeling the median year of each survey period as a continuous variable to obtain P for trend. All statistical tests were 2-sided, with a significance level set at α = 0.05.
RESULTS
Trends in AA intake over the past 13 yrs
Protein and AA intake, relative to energy, protein (only for AA), and body weight across the survey periods, are shown in Table 1. While total protein intake (g/day) and protein intake relative to body weight (g/kg/day) decreased, protein density relative to total energy intake (g/1,000 kcal/day) increased (all P for trend < 0.0001). The average total AA intake over the past 13 yrs was 62.1 ± 0.20 g/day with 24.8 ± 0.08 g/day of EAAs, 11.8 ± 0.04 g/day of BCAAs, and 37.3 ± 0.12 g/day of NEAAs. The total AA intake (g/day) remained relatively stable throughout the survey periods, with no significant trend observed (P for trend = 0.904). However, total AA intake relative to body weight significantly decreased, whereas total AA intake, relative to total energy and protein intake, significantly increased (all P for trend < 0.0001). Similar trends were observed for EAAs, BCAAs, and NEAAs (all P for trend < 0.0001).
Table 1. Protein and AA intake among Korea National Health and Nutrition Examination Survey participants across survey periods.
| Variable | All periods (2010–2022) (n = 69,664) | Survey period | P-value | P for trend | |||||
|---|---|---|---|---|---|---|---|---|---|
| 2010–2012 (n = 17,130) | 2013–2015 (n = 15,771) | 2016–2018 (n = 16,550) | 2019–2021 (n = 15,312) | 2022 (n = 4,901) | |||||
| Protein | |||||||||
| g/day | 71.65 ± 0.21 | 73.68 ± 0.48 | 71.28 ± 0.44 | 71.62 ± 0.43 | 70.93 ± 0.47 | 69.50 ± 0.631) | < 0.0001 | < 0.0001 | |
| g/kg | 1.114 ± 0.003 | 1.163 ± 0.007 | 1.121 ± 0.007 | 1.110 ± 0.006 | 1.088 ± 0.007 | 1.063 ± 0.0091) | < 0.0001 | < 0.0001 | |
| g/1,000 kcal | 36.18 ± 0.06 | 35.86 ± 0.12 | 34.34 ± 0.12 | 35.93 ± 0.12 | 37.62 ± 0.14 | 38.50 ± 0.201) | < 0.0001 | < 0.0001 | |
| Total AAs | |||||||||
| g/day | 62.10 ± 0.20 | 62.02 ± 0.42 | 62.51 ± 0.39 | 61.62 ± 0.39 | 62.32 ± 0.49 | 61.90 ± 0.71 | 0.572 | 0.904 | |
| g/kg | 0.965 ± 0.003 | 0.978 ± 0.006 | 0.984 ± 0.006 | 0.953 ± 0.006 | 0.954 ± 0.007 | 0.946 ± 0.010 | 0.000 | < 0.0001 | |
| g/1,000 kcal | 31.30 ± 0.06 | 30.15 ± 0.11 | 30.06 ± 0.11 | 30.82 ± 0.11 | 33.00 ± 0.17 | 34.13 ± 0.261) | < 0.0001 | < 0.0001 | |
| g/protein g | 0.867 ± 0.001 | 0.843 ± 0.002 | 0.879 ± 0.002 | 0.859 ± 0.002 | 0.877 ± 0.003 | 0.887 ± 0.0041) | < 0.0001 | < 0.0001 | |
| EAAs | |||||||||
| g/day | 24.81 ± 0.08 | 24.86 ± 0.17 | 24.98 ± 0.17 | 24.58 ± 0.16 | 24.87 ± 0.20 | 24.71 ± 0.29 | 0.497 | 0.575 | |
| g/kg | 0.385 ± 0.001 | 0.392 ± 0.003 | 0.393 ± 0.003 | 0.380 ± 0.002 | 0.380 ± 0.003 | 0.377 ± 0.004 | < 0.0001 | < 0.0001 | |
| g/1,000 kcal | 12.49 ± 0.03 | 12.06 ± 0.05 | 11.98 ± 0.05 | 12.28 ± 0.05 | 13.15 ± 0.07 | 13.61 ± 0.111) | < 0.0001 | < 0.0001 | |
| g/protein g | 0.344 ± 0.000 | 0.335 ± 0.001 | 0.348 ± 0.001 | 0.340 ± 0.001 | 0.348 ± 0.001 | 0.352 ± 0.0021) | < 0.0001 | < 0.0001 | |
| BCAAs | |||||||||
| g/day | 11.84 ± 0.04 | 12.01 ± 0.07 | 11.95 ± 0.07 | 11.74 ± 0.07 | 11.75 ± 0.09 | 11.59 ± 0.12 | 0.006 | 0.001 | |
| g/kg | 0.184 ± 0.001 | 0.190 ± 0.001 | 0.188 ± 0.001 | 0.182 ± 0.001 | 0.180 ± 0.001 | 0.177 ± 0.0021) | < 0.0001 | < 0.0001 | |
| g/1,000 kcal | 6.00 ± 0.01 | 5.88 ± 0.02 | 5.78 ± 0.02 | 5.91 ± 0.02 | 6.26 ± 0.03 | 6.42 ± 0.041) | < 0.0001 | < 0.0001 | |
| g/protein g | 0.167 ± 0.000 | 0.166 ± 0.000 | 0.170 ± 0.000 | 0.166 ± 0.000 | 0.167 ± 0.000 | 0.167 ± 0.00 | < 0.0001 | 0.857 | |
| NEAAs | |||||||||
| g/day | 37.29 ± 0.12 | 37.16 ± 0.24 | 37.53 ± 0.23 | 37.04 ± 0.23 | 37.46 ± 0.29 | 37.18 ± 0.43 | 0.572 | 0.851 | |
| g/kg | 0.580 ± 0.002 | 0.586 ± 0.004 | 0.591 ± 0.004 | 0.573 ± 0.003 | 0.574 ± 0.004 | 0.568 ± 0.006 | 0.000 | 0.000 | |
| g/1,000 kcal | 18.82 ± 0.04 | 18.09 ± 0.07 | 18.08 ± 0.06 | 18.54 ± 0.07 | 19.85 ± 0.10 | 20.52 ± 0.161) | < 0.0001 | < 0.0001 | |
| g/protein g | 0.523 ± 0.001 | 0.508 ± 0.001 | 0.531 ± 0.001 | 0.519 ± 0.001 | 0.530 ± 0.002 | 0.535 ± 0.0031) | < 0.0001 | < 0.0001 | |
All values are presented as mean ± SE. All estimates were derived using complex sample analysis with integrated sample weights to ensure representativeness of the Korean population.
AA, amino acid; EAA, essential amino acid; BCAA, branched-chain amino acid; NEAA, nonessential amino acid.
1)Significant differences between the 2010–2012 and 2022 groups, as determined by Scheffe’s post hoc test (P < 0.05).
Among EAAs, leucine intake was the highest at 5.23 ± 0.02 g/day, while glutamic acid was the most consumed NEAA (11.09 ± 0.04 g/day) (Fig. 1). During the past 13 yrs, the mean daily total AA intake did not significantly change (62.0 g in 2010–2012 and 61.9 g in 2022); however, intakes of leucine, valine, phenylalanine, tryptophan, arginine, alanine, and proline significantly decreased (all P for trend < 0.05). In contrast, lysine, methionine, threonine, cysteine, glutamic acid, glycine, and serine intake significantly increased over the 13 yrs (all P for trend < 0.05). Post hoc tests showed significant differences between 2010–2012 and 2022 for valine, lysine, tryptophan, cysteine, alanine, glycine, proline, and serine.
Fig. 1. Trends in individual essential amino acid (A) and nonessential amino acid (B) intakes across survey periods. All estimates were derived using complex sample analysis with integrated sample weights to ensure representativeness of the Korean population.
1)Significant trend across survey periods (P for trend < 0.05).
2)Significant difference by Scheffe’s post hoc test difference between 2010–2012 and 2022 (P < 0.05).
AA intake by general characteristics
Mean AA intake according to general characteristics from 2010–2012 to 2022 is shown in Tables 2 and 3. The total AA intake was higher among males, younger individuals, those with higher education and household income levels, and those living in urban areas (P < 0.0001 for all). Similarly, other AA intakes showed significant differences according to sex, age, education level, household income level, and regions (except alanine) (P < 0.05 for all).
Table 2. Mean total and EAA intakes based on general characteristics from 2010 to 2022.
| Characteristic | No. | Total AAs | Total EAAs | Total BCAAs1) | Isoleucine | Leucine | Valine | Lysine | Methionine | Phenylalanine | Threonine | Tryptophan | Histidine | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Sex | ||||||||||||||
| Male | 29,288 | 72.80 ± 0.30 | 29.18 ± 0.13 | 13.88 ± 0.05 | 3.42 ± 0.01 | 6.13 ± 0.02 | 4.33 ± 0.02 | 4.34 ± 0.02 | 1.52 ± 0.01 | 3.52 ± 0.01 | 2.96 ± 0.01 | 0.71 ± 0.00 | 2.25 ± 0.01 | |
| Female | 40,376 | 51.68 ± 0.20 | 20.56 ± 0.08 | 9.84 ± 0.03 | 2.41 ± 0.01 | 4.36 ± 0.02 | 3.07 ± 0.01 | 2.98 ± 0.02 | 1.06 ± 0.00 | 2.52 ± 0.01 | 2.09 ± 0.01 | 0.51 ± 0.00 | 1.55 ± 0.01 | |
| P-value | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | ||
| Age (yrs) | ||||||||||||||
| 19–29 | 7,985 | 69.47 ± 0.57 | 28.09 ± 0.24 | 13.05 ± 0.10 | 3.24 ± 0.03 | 5.79 ± 0.05 | 4.03 ± 0.03 | 4.37 ± 0.05 | 1.53 ± 0.01 | 3.33 ± 0.03 | 2.92 ± 0.03 | 0.66 ± 0.01 | 2.23 ± 0.02 | |
| 30–49 | 23,080 | 67.24 ± 0.31 | 26.91 ± 0.13 | 12.69 ± 0.06 | 3.13 ± 0.01 | 5.62 ± 0.03 | 3.93 ± 0.02 | 4.07 ± 0.02 | 1.42 ± 0.01 | 3.22 ± 0.01 | 2.77 ± 0.01 | 0.66 ± 0.00 | 2.08 ± 0.01 | |
| 50–64 | 19,527 | 59.62 ± 0.29 | 23.64 ± 0.12 | 11.42 ± 0.05 | 2.79 ± 0.01 | 5.05 ± 0.02 | 3.58 ± 0.02 | 3.38 ± 0.02 | 1.20 ± 0.01 | 2.91 ± 0.01 | 2.38 ± 0.01 | 0.59 ± 0.00 | 1.77 ± 0.01 | |
| ≤ 65 | 19,072 | 46.64 ± 0.26 | 18.47 ± 0.11 | 9.28 ± 0.05 | 2.24 ± 0.01 | 4.06 ± 0.02 | 2.98 ± 0.01 | 2.41 ± 0.02 | 0.90 ± 0.01 | 2.36 ± 0.01 | 1.76 ± 0.01 | 0.45 ± 0.00 | 1.32 ± 0.01 | |
| P-value | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | ||
| Education level | ||||||||||||||
| Elementary school or lower | 14,228 | 45.10 ± 0.28 | 17.89 ± 0.12 | 9.07 ± 0.05 | 2.19 ± 0.01 | 3.96 ± 0.02 | 2.93 ± 0.02 | 2.28 ± 0.02 | 0.86 ± 0.01 | 2.29 ± 0.01 | 1.67 ± 0.01 | 0.44 ± 0.00 | 1.28 ± 0.01 | |
| Middle school | 6,464 | 55.74 ± 0.53 | 22.15 ± 0.22 | 10.82 ± 0.10 | 2.64 ± 0.02 | 4.76 ± 0.04 | 3.42 ± 0.03 | 3.09 ± 0.04 | 1.11 ± 0.01 | 2.75 ± 0.02 | 2.19 ± 0.02 | 0.55 ± 0.01 | 1.65 ± 0.02 | |
| High school | 20,339 | 64.08 ± 0.34 | 25.64 ± 0.14 | 12.15 ± 0.06 | 2.99 ± 0.02 | 5.38 ± 0.03 | 3.78 ± 0.02 | 3.82 ± 0.03 | 1.35 ± 0.01 | 3.10 ± 0.02 | 2.62 ± 0.02 | 0.63 ± 0.00 | 1.97 ± 0.01 | |
| College or higher | 21,448 | 68.28 ± 0.32 | 27.30 ± 0.13 | 12.82 ± 0.06 | 3.17 ± 0.02 | 5.69 ± 0.03 | 3.96 ± 0.02 | 4.16 ± 0.03 | 1.44 ± 0.01 | 3.27 ± 0.01 | 2.83 ± 0.01 | 0.67 ± 0.00 | 2.11 ± 0.01 | |
| P-value | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | ||
| Household income | ||||||||||||||
| Low | 14,035 | 50.22 ± 0.44 | 20.01 ± 0.18 | 9.90 ± 0.08 | 2.41 ± 0.02 | 4.33 ± 0.04 | 3.16 ± 0.02 | 2.71 ± 0.04 | 1.00 ± 0.01 | 2.51 ± 0.02 | 1.94 ± 0.02 | 0.47 ± 0.00 | 1.47 ± 0.02 | |
| Lower-middle | 17,396 | 60.04 ± 0.35 | 24.00 ± 0.15 | 11.52 ± 0.06 | 2.83 ± 0.02 | 5.08 ± 0.03 | 3.61 ± 0.02 | 3.48 ± 0.03 | 1.24 ± 0.01 | 2.93 ± 0.02 | 2.42 ± 0.02 | 0.58 ± 0.00 | 1.82 ± 0.01 | |
| Upper-middle | 18,485 | 64.79 ± 0.36 | 25.90 ± 0.15 | 12.29 ± 0.07 | 3.02 ± 0.02 | 5.44 ± 0.03 | 3.82 ± 0.02 | 3.86 ± 0.03 | 1.36 ± 0.01 | 3.13 ± 0.02 | 2.64 ± 0.02 | 0.63 ± 0.00 | 1.99 ± 0.01 | |
| High | 19,304 | 67.40 ± 0.36 | 26.93 ± 0.15 | 12.67 ± 0.07 | 3.13 ± 0.02 | 5.63 ± 0.03 | 3.91 ± 0.02 | 4.08 ± 0.03 | 1.42 ± 0.01 | 3.24 ± 0.02 | 2.78 ± 0.02 | 0.67 ± 0.00 | 2.07 ± 0.01 | |
| P-value | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | ||
| Region | ||||||||||||||
| Metropolitan | 36,333 | 62.88 ± 0.26 | 25.13 ± 0.11 | 11.94 ± 0.05 | 2.93 ± 0.01 | 5.29 ± 0.02 | 3.72 ± 0.01 | 3.72 ± 0.02 | 1.31 ± 0.01 | 3.05 ± 0.01 | 2.56 ± 0.01 | 0.62 ± 0.00 | 1.93 ± 0.01 | |
| Urban | 18,926 | 62.60 ± 0.42 | 25.00 ± 0.17 | 11.88 ± 0.07 | 2.93 ± 0.02 | 5.25 ± 0.03 | 3.70 ± 0.02 | 3.72 ± 0.03 | 1.31 ± 0.01 | 3.03 ± 0.02 | 2.56 ± 0.02 | 0.60 ± 0.00 | 1.91 ± 0.01 | |
| Rural | 14,405 | 58.80 ± 0.52 | 23.50 ± 0.21 | 11.43 ± 0.09 | 2.80 ± 0.02 | 5.02 ± 0.04 | 3.61 ± 0.03 | 3.33 ± 0.04 | 1.20 ± 0.01 | 2.88 ± 0.02 | 2.32 ± 0.02 | 0.57 ± 0.01 | 1.76 ± 0.02 | |
| P-value | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | 0.001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | ||
All values are presented as mean ± SE. All estimates were derived using complex sample analysis with integrated sample weights to ensure representativeness of the Korean population. Units are expressed in g/day.
EAA, essential amino acid; BCAA, branched-chain amino acid.
1)BCAAs included isoleucine, leucine, and valine.
Table 3. Mean NEAA intakes based on general characteristics from 2010 to 2022.
| Characteristic | No. | Total NEAAs | Arginine | Tyrosine | Cysteine | Alanine | Aspartic acid | Glutamic acid | Glycine | Proline | Serine | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Sex | ||||||||||||
| Male | 29,288 | 43.62 ± 0.18 | 4.92 ± 0.02 | 2.29 ± 0.01 | 0.87 ± 0.00 | 4.46 ± 0.02 | 7.03 ± 0.03 | 12.91 ± 0.06 | 3.10 ± 0.02 | 4.88 ± 0.02 | 3.18 ± 0.01 | |
| Female | 40,376 | 31.12 ± 0.12 | 3.43 ± 0.01 | 1.62 ± 0.01 | 0.63 ± 0.00 | 3.13 ± 0.01 | 5.04 ± 0.02 | 9.31 ± 0.04 | 2.13 ± 0.01 | 3.52 ± 0.01 | 2.30 ± 0.01 | |
| P-value | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | ||
| Age (yrs) | ||||||||||||
| 19–29 | 7,985 | 41.38 ± 0.33 | 4.55 ± 0.04 | 2.24 ± 0.02 | 0.83 ± 0.01 | 4.09 ± 0.04 | 6.47 ± 0.05 | 12.59 ± 0.10 | 3.05 ± 0.03 | 4.49 ± 0.03 | 3.07 ± 0.02 | |
| 30–49 | 23,080 | 40.33 ± 0.18 | 4.49 ± 0.02 | 2.13 ± 0.01 | 0.81 ± 0.00 | 4.05 ± 0.02 | 6.47 ± 0.03 | 12.08 ± 0.06 | 2.88 ± 0.02 | 4.45 ± 0.02 | 2.97 ± 0.01 | |
| 50–64 | 19,527 | 35.98 ± 0.17 | 4.05 ± 0.02 | 1.85 ± 0.01 | 0.72 ± 0.00 | 3.68 ± 0.02 | 5.93 ± 0.03 | 10.58 ± 0.05 | 2.45 ± 0.02 | 4.08 ± 0.02 | 2.64 ± 0.01 | |
| ≤ 65 | 19,072 | 28.17 ± 0.16 | 3.22 ± 0.02 | 1.39 ± 0.01 | 0.56 ± 0.00 | 3.02 ± 0.02 | 4.68 ± 0.03 | 8.06 ± 0.05 | 1.77 ± 0.01 | 3.46 ± 0.02 | 2.01 ± 0.01 | |
| P-value | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | ||
| Education level | ||||||||||||
| Elementary school or lower | 14,228 | 27.21 ± 0.17 | 3.13 ± 0.02 | 1.33 ± 0.01 | 0.53 ± 0.00 | 2.99 ± 0.02 | 4.50 ± 0.03 | 7.71 ± 0.05 | 1.68 ± 0.02 | 3.44 ± 0.02 | 1.91 ± 0.01 | |
| Middle school | 6,464 | 33.58 ± 0.31 | 3.81 ± 0.04 | 1.70 ± 0.02 | 0.66 ± 0.01 | 3.53 ± 0.03 | 5.54 ± 0.05 | 9.74 ± 0.09 | 2.26 ± 0.03 | 3.92 ± 0.03 | 2.42 ± 0.02 | |
| High school | 20,339 | 38.44 ± 0.20 | 4.28 ± 0.02 | 2.02 ± 0.01 | 0.77 ± 0.00 | 3.88 ± 0.02 | 6.18 ± 0.03 | 11.48 ± 0.06 | 2.72 ± 0.02 | 4.28 ± 0.02 | 2.83 ± 0.02 | |
| College or higher | 21,448 | 40.98 ± 0.19 | 4.54 ± 0.02 | 2.18 ± 0.01 | 0.83 ± 0.00 | 4.05 ± 0.02 | 6.58 ± 0.03 | 12.37 ± 0.06 | 2.94 ± 0.02 | 4.45 ± 0.02 | 3.05 ± 0.01 | |
| P-value | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | ||
| Household income | ||||||||||||
| Low | 14,035 | 30.21 ± 0.26 | 3.42 ± 0.03 | 1.51 ± 0.01 | 0.60 ± 0.01 | 3.21 ± 0.03 | 4.91 ± 0.04 | 8.78 ± 0.08 | 1.95 ± 0.02 | 3.65 ± 0.02 | 2.16 ± 0.02 | |
| Lower-middle | 17,396 | 36.04 ± 0.20 | 4.03 ± 0.02 | 1.87 ± 0.01 | 0.72 ± 0.00 | 3.70 ± 0.02 | 5.82 ± 0.03 | 10.67 ± 0.06 | 2.48 ± 0.02 | 4.12 ± 0.02 | 2.63 ± 0.02 | |
| Upper-middle | 18,485 | 38.89 ± 0.21 | 4.34 ± 0.03 | 2.04 ± 0.01 | 0.78 ± 0.00 | 3.93 ± 0.02 | 6.27 ± 0.03 | 11.60 ± 0.07 | 2.75 ± 0.02 | 4.32 ± 0.02 | 2.86 ± 0.02 | |
| High | 19,304 | 40.47 ± 0.21 | 4.50 ± 0.02 | 2.14 ± 0.01 | 0.81 ± 0.00 | 4.02 ± 0.02 | 6.53 ± 0.03 | 12.14 ± 0.07 | 2.91 ± 0.02 | 4.41 ± 0.02 | 3.00 ± 0.02 | |
| P-value | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | ||
| Region | ||||||||||||
| Metropolitan | 36,333 | 37.75 ± 0.15 | 4.20 ± 0.02 | 1.98 ± 0.01 | 0.76 ± 0.00 | 3.81 ± 0.02 | 6.09 ± 0.03 | 11.26 ± 0.05 | 2.64 ± 0.01 | 4.23 ± 0.01 | 2.78 ± 0.01 | |
| Urban | 18,926 | 37.60 ± 0.25 | 4.19 ± 0.03 | 1.97 ± 0.01 | 0.75 ± 0.00 | 3.78 ± 0.02 | 6.06 ± 0.04 | 11.24 ± 0.08 | 2.67 ± 0.02 | 4.17 ± 0.02 | 2.77 ± 0.02 | |
| Rural | 14,405 | 35.30 ± 0.31 | 4.01 ± 0.03 | 1.81 ± 0.02 | 0.70 ± 0.01 | 3.73 ± 0.03 | 5.74 ± 0.05 | 10.26 ± 0.10 | 2.39 ± 0.03 | 4.13 ± 0.03 | 2.53 ± 0.02 | |
| P-value | < 0.0001 | < 0.0001 | < 0.0001 | < 0.0001 | 0.050 | < 0.0001 | < 0.0001 | < 0.0001 | 0.003 | < 0.0001 | ||
All values are presented as mean ± SE. All estimates were derived using complex sample analysis with integrated sample weights to ensure representativeness of the Korean population. Units are expressed in g/day.
NEAA, nonessential amino acid.
Food groups contributing to AA intake
Fig. 2 presents the major food groups contributing to AA intake in 2022, whereas Supplementary Tables 1, 2, 3 show the changes in major food group contributions from 2010–2012 to 2022. In 2022, EAAs were primarily derived from meat (28.8%), followed by grains (26.4%) and seafood (11.4%). Compared to 2010–2012, the contribution of meat increased (from 22.6%), whereas that of grains decreased (from 33.0%), leading to a shift in the ranking of the contributing food groups (Supplementary Table 1). The ranking of BCAAs remained unchanged, with grains (31.8%), meat (25.9%), and seafood (10.2%) being the top contributors. However, compared to 2010–2012, the contribution of grains declined (from 39.9%), whereas that of meat increased (from 19.6%) (Supplementary Table 2). Similarly, for NEAAs, the contribution of meat increased (from 20.0% in 2010–2012 to 25.6% in 2022), whereas that of grains decreased (from 33.9% in 2010–2012 to 28.3% in 2022) (Supplementary Table 3).
Fig. 2. Contribution rates (%) of major food sources to (A) EAA, (B) BCAA, and (C) NEAA intakes in 2022. All estimates were derived using complex sample analysis with integrated sample weights to ensure representativeness of the Korean population.
EAA, essential amino acid; BCAA, branched-chain amino acid; NEAA, nonessential amino acid.
1)Other included potatoes & starches, sugars, seeds and nuts, mushrooms, fruits, seasonings, fats and oils, and beverages.
DISCUSSION
In this large-scale study of a representative sample of Korean adults, the total AA intake remained consistent over the past 13 yrs, with values of 62.0 g in 2010–2012 and 61.9 g in 2022. Similarly, EAA and NEAA intakes showed no significant changes during the same period. However, AA density, relative to total energy and protein intake, increased for all types of AA. Leucine was the most consumed among the EAA, followed by valine and lysine, while glutamic acid was the most consumed among the NEAA, followed by aspartic acid, threonine, and arginine. The main food sources of AAs were grains (including white rice), and meat (including red meat); the contributions of grains continuously decreased, while those of meat increased over time.
Although this is the first study to assess the overall AA intake in the Korean population, comparisons can be made with studies conducted in other Asian populations. A recent study in the U.S reported that the total AA intake for Asian men and women was 93.8 g/day and 70.2 g/day, respectively, with their EAA intake reported as 41.6 g/day and 31.1 g/day, respectively [26]. These values were relatively higher than those observed in this study. Furthermore, when compared to a Japanese study on individuals aged 30–69 yrs, the EAA intake of Korean men in this study was lower than that of Japanese men for lysine, methionine, threonine, tryptophan, and histidine [28]. Similarly, the EAA intake of Korean women in the present study was lower than that of Japanese women [28]. In terms of NEAAs, Korean adults exhibit lower intake levels than other Asian populations. Specifically, the intake of NEAAs, such as arginine, alanine, aspartic acid, glutamic acid, glycine, proline, and serine, was lower in Korean adults than in Asian adults aged 31–50 yrs living in the US [26], which was the primary age group in this study. Additionally, Korean men consumed lower amounts of tyrosine, cysteine, aspartic acid, glutamic acid, glycine, and serine than Japanese men, and the intake of all NEAAs was lower in Korean women than in Japanese women [28].
Previous studies have shown cross-national differences in the intakes of several AAs. For example, a study examining methionine, lysine, and valine intake among Korean adults reported relatively lower AA intake than in Japanese adults [27], which may be attributed to the predominantly plant-based dietary patterns of Koreans. In contrast to American adults, in which approximately two-thirds of their total protein comes from animal-based foods, and Japanese adults, who obtain over 50% of their protein from animal-based foods [27,29], less than 50% of the total AAs, EAAs, BCAAs, and NEAAs in this study were obtained from animal-based foods. Meat products are key sources of EAAs and NEAAs [19], thus the lower contribution of meat to AA intake could explain the lower levels of AA intake observed in Korea.
Additionally, although animal-based foods such as meat, fish, eggs, and dairy are well-known sources of EAAs [10,30], grains have remained the primary source of EAAs among Korean adults over the last 13 yrs (Supplementary Table 2). This may be related to the traditional rice-based Korean diet. However, with westernization of the diet, the contribution of meat to AA intake has steadily increased. The intake of proline and alanine (mainly from grains) decreased, whereas that of glycine and lysine (mainly from meat) increased, suggesting a shift in protein quality. Given that protein intake is associated with various health conditions, including diabetes, cardiovascular diseases, and neurodegenerative diseases [3,13,14], future research on AA intake patterns, sources, digestibility, and bioavailability would clarify their impact on health risks.
While the absolute intake of AAs has remained stable over the past 13 yrs, except for EAAs, the protein density relative to both total protein and energy intake has increased. Similarly, although absolute protein intake decreased, protein density (g/1,000 kcal) increased. These findings suggest that, despite the decline in total protein intake, the proportion of AAs relative to total protein may have increased. Protein quality is influenced by multiple factors, including the content, absorption, digestibility, and bioavailability of EAAs [31]; therefore, the observed increase in AA density in this study does not necessarily reflect a direct improvement in protein quality. However, the intake of 4 key EAAs, lysine, methionine, cysteine, and threonine [32], increased in this study, which may have influenced protein quality.
In this study, total AA and EAA intakes relative to body weight were 0.97 and 0.39 g/kg/day, respectively. Although direct comparisons are challenging because the present analysis was based on actual body weight, both total AA and EAA intakes were lower than those reported for American adults based on ideal body weight (1.01–1.40 g/kg/day for total AAs and 0.45–0.61 g/kg/day for EAAs) [26]. Assessing AA intake relative to body weight is particularly important because requirements increase proportionally with body mass, and the intake per kilogram is used to estimate AA needs [26,27]. Therefore, continuous evaluation and monitoring are essential to ensure adequacy across different population groups, particularly when considering variations in body weight, such as obesity.
In Korea, AA intake levels differ based on sociodemographic characteristics. Older adults consumed significantly lower amounts of AAs than younger adults did. These findings were in line with previous studies, which reported that the proportion of protein intake decreased with age [15,33]. Because older adults consume more grains and less meat than younger adults in Korea [33,34,35], the absolute intake of protein and AAs is expected to be lower in this age group. A recent study conducted on Korean adults aged 50–64 yrs found that the intake of methionine, lysine, and phenylalanine was below the recommended intake, likely because grains are the primary dietary source [34]. In fact, these AAs are more commonly found in animal proteins [19]. Furthermore, the participants with lower education and household income levels consumed lower AAs than the opposite group, which was consistent with previous findings related to dietary protein [15,33,36]. Although animal products have become more accessible in recent years, they are expensive, especially meat and seafood [37,38]. These findings suggest that effective nutrition programs to improve the quantity and quality of AAs are required for older adults and populations with low socioeconomic status.
To the best of our knowledge, this is the first study to estimate all types of AA intakes and food sources among Korean adults over the past 13 yrs. These findings can facilitate further evaluation of AA intake status based on various characteristics and investigations of the health impacts of AAs. However, this study has several limitations. First, using a 1-day 24-h dietary recall may not accurately reflect usual dietary intake. Second, the AA intake estimated in this study could have been underestimated because of the limited coverage of food items in the AA database. However, the AA database constructed in this study covered 73.0% of the distinct food items and 95.7% of the total food consumption reported in the 24-h dietary recall data of the 2010–2022 KNHANES. Third, AA intake from supplements was not considered because this study focused on dietary AA intake, and there was insufficient information on protein/AA supplements in the KNHANES. Fourth, due to the lack of data on AA digestibility and bioavailability, this study did not account for these factors, which may have led to an overestimation of AA intake [39]. Finally, there was a discrepancy between the total protein intake and the sum of the total AA intake in this study. This could be attributed to differences in the methods used to measure crude protein and AA content in foods [40].
Despite the increase in animal food consumption, the dietary AA intake among Korean adults remained relatively low compared to that of other countries. While the total absolute AA intake has remained stable over the past 13 yrs, AA density relative to total protein and energy intake has increased, accompanied by changes in the intake levels of several individual AAs. These findings provide essential evidence for future revisions of AA intake recommendations for Koreans and facilitate further research on the associations between dietary AAs and various diseases.
Footnotes
Funding: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2021R1G1A1008495).
Conflict of Interest: The authors declare no potential conflicts of interests.
- Conceptualization: Ha K.
- Formal analysis: Kim S.
- Funding acquisition: Ha K.
- Investigation: Kim S, Ham H.
- Methodology: Kim S, Ha K.
- Supervision: Ha K.
- Writing - original draft: Kim S.
- Writing - review & editing: Ha K.
SUPPLEMENTARY MATERIALS
Food group contributions to essential amino acid intake, 2010–2022
Food group contributions to branched-chain amino acid intake, 2010–2022
Food group contributions to nonessential amino acid intake, 2010–2022
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Food group contributions to essential amino acid intake, 2010–2022
Food group contributions to branched-chain amino acid intake, 2010–2022
Food group contributions to nonessential amino acid intake, 2010–2022