Abstract
BACKGROUND/OBJECTIVES
Our study aimed to investigate the association of food group intake and the quality of diet with the risk of loss of muscle mass in Korean baby boomers using a large-scale national cohort data.
SUBJECTS/METHODS
The study included 1,280 Korean baby boomers (609 men and 671 women) who were born between 1955 and 1963 and who participated in the Korean Genome and Epidemiology Study from 2001 to 2018. A validated semi-quantitative food frequency questionnaire was used to assess dietary intake. The Korean Healthy Eating Index (K-HEI) and the Mediterranean-Type Diet scores helped to evaluate the quality of the diet. Bioelectrical impedance analysis at baseline and during follow-up visits was used to measure the total muscle mass. Muscle loss was defined as a ≥ 5% decrease in total muscle mass over 2 yrs. This prospective cohort study had a mean follow-up duration of 12.7 yrs. Cox proportional hazards model was used to estimate the hazard ratio for muscle loss on the basis of the levels of dietary variables.
RESULTS
In men, high grain intake was significantly associated with an increased risk of muscle loss (P for trend = 0.023). In women, a high intake of dairy products was associated with a reduced risk of muscle loss (P for trend = 0.021). Additionally, higher fruit intake and K-HEI scores were inversely associated with muscle loss when adjusted only for age and total energy intake.
CONCLUSION
Our study demonstrates gender-specific associations of diet with the loss of muscle mass in the Korean baby boomers. Although high grain intake may increase the risk of loss of muscle mass in men, high dairy intake may provide protective effects in women. These findings emphasize the need for targeted dietary strategies to prevent age-related muscle loss.
Keywords: Diet, sarcopenia, baby boom, cohort studies
INTRODUCTION
In South Korea, there is a rapid demographic shift toward an aging society. The proportion of the population aged 65 and over is expected to increase from 17.4% in 2022 to over 20% in 2025, classified as a super-aged society [1]. Baby boomers, the generation born between 1955 and 1963, constitute 15% of Korea’s total population [2]. With a substantial proportion of baby boomers entering old age, a major public health priority has been to prevent and to manage age-related health conditions. This requires a tailored approach that takes into account their lifestyles and health behaviors.
Due to their exposure to rapid industrialization and urbanization, baby boomers are distinguishable from previous generations by the distinct characteristics of a high prevalence of chronic diseases, such as hypertension and obesity [3,4]. In addition, the baby boomers in South Korea experienced a period of dietary transition, which was characterized by a shift from traditional to processed and convenience foods [5]. Recent studies have reported a decline in carbohydrate intake and an increase in fat and protein intake across various age groups in South Korea [6]. The findings indicate a shift from traditional to Western diets that contain limited essential nutrients and possibly increase age-related disease risk. However, there has been limited research that examines the dietary habits and nutrient intake of Korean baby boomers.
Sarcopenia is the loss of muscle mass with aging, which is now widely recognized as a major geriatric syndrome. Sarcopenia is an important public health concern that is receiving increasing attention. According to the latest consensus definitions from the European Working Group on Sarcopenia in Older People 2019 and the Asian Working Group for Sarcopenia, sarcopenia is diagnosed based on low muscle mass, reduced strength, and impaired physical functioning [7,8]. Prior research has demonstrated that the management of sarcopenia is a crucial aspect not only for older adults but also for middle-aged individuals. Nearly 9% of middle-aged women experience significant lean mass loss over a 3-yr period, which is associated with compromised physical functioning [9]. Early interventions and lifestyle modifications throughout the lifespan may significantly contribute to prevent sarcopenia and improve physical ability in old age [10]. Without timely intervention, sarcopenia predisposes individuals to an increased risk of impaired mobility, metabolic disorders, and chronic diseases, thereby amplifying the burden on global healthcare systems [11,12]. South Korea’s baby boomers, most of whom are now in their 60s, are at a critical stage where there is accelerated age-related physiological and functional decline.
Among the modifiable risk factors, nutritional factors are recognized as critical contributors to the loss of muscle mass. Previous studies have shown that a high intake of protein, vitamin D, omega-3 fatty acids, and antioxidant-rich foods are inversely associated with the risk of sarcopenia [7,13,14]. In addition, diets that focus on healthy eating patterns, such as the Mediterranean diet, the Dietary Approaches to Stop Hypertension diet, and diet with a high Healthy Eating Index scores, have been shown to be effective to maintain muscle health [15]. These dietary patterns are characterized by a high intake of fruits, vegetables, whole grains, legumes, nuts, and healthy fats, along with a low consumption of processed foods and added sugars. As a result, dietary strategies that focus on the overall quality of diets have gained increasing attention as a non-pharmacological, population-level approach to mitigate age-related muscle loss.
Despite these observations, there has been limited research that has assessed the dietary patterns of Korean baby boomers using nationally representative data and even fewer studies that have explored the longitudinal association between diet and muscle mass. Our study aims to examine the association between food group intake, diet quality scores, and the progressive risk of loss of muscle mass in the baby boomers of the 2001–2018 Korean Genome and Epidemiology Survey (KoGES). In addition, this study has the advantage of analyzing the impact of dietary factors in middle age on muscle mass decline in older adults based on a prospective design that tracked baby boomers in their early 40s registered in the KoGES cohort. It provides important evidence on how dietary habits in middle age influence the risk of age-related muscle loss.
SUBJECTS AND METHODS
Data and subjects
Our study analyzed data from a national cohort study (KoGES), which was published according to the STROBE guidelines, to examine the relationship between diet and the risk of loss of muscle mass in baby boomers [16]. The community-based cohort data from Ansan and Anseong of the 2001–2018 KoGES were used to analyze the association between dietary pattern and muscle mass. Baby boomers were defined as individuals born between 1955 and 1963. The exclusion criteria for our study were as follows: 1) subjects with a daily food intake of less than 500 kcal or more than 5,000 kcal; 2) subjects who did not participate in muscle mass measurements; and 3) subjects with a physician diagnosis of hypertension, cardiovascular disease, cerebrovascular disease, or diabetes mellitus at baseline. A total of 1,280 individuals (men: 609, women: 671) were included in the final analysis after applying the exclusion criteria on the 3,710 subjects of baby boomers in KoGES (Fig. 1). This prospective cohort study had a mean follow-up duration of 12.7 yrs. This study was exempted from the Institutional Review Board (IRB) of Sungshin Women’s University (IRB No. SSWUIRB-2021-032).
Fig. 1. Flow diagram for the selection of study subjects.
KoGES, Korean Genome and Epidemiology Study.
Definition and measurement of diet (intake and quality) and muscle loss
The food group intake and the quality of the diet were analyzed using dietary data from the validated semi-quantitative food frequency questionnaire (SQFFQ) that assesses the frequency and quantity of 103 food items consumed over the past year. Intake frequency was categorized into nine levels (from rarely to 3 times per day) and serving size into 3 levels (below, at, and above the reference value). Daily food intake was calculated based on the reported frequency and the quantity of food consumed. The primary food groups were divided into 6 categories: 1) grains, 2) meat/fish/eggs/legumes, 3) vegetables, 4) fruits, 5) milk and dairy products, and 6) oils and sugars. To assess the quality of the diet, we utilized the Korean Healthy Eating Index (K-HEI) and the Mediterranean-Type Diet (MTD) scores. The 2 quality of diet scores were defined as follows: 1) The K-HEI is a comprehensive tool used to assess the quality of meals by assigning a score to various dietary components, such as fruits including juice (0–5 points), fruits excluding juice (0–5 points), vegetables including Kimchi or pickles (0–5 points), vegetables excluding Kimchi or pickles (0–5 points), milk and dairy product (0–10 points), protein foods (0–10 points), ratio of white meat to red meat (0–5 points), whole grains (0–5 points), breakfast consumption (0–10 points), sodium (0–10 points), energy percentage calculated from empty calorie foods (0–10 points), energy percentage calculated from fat (0–10 points), refined grains (0–5 points), and energy percentage calculated from carbohydrate (0–5 points) [17]. 2) The MTD score was calculated based on dietary components that include whole grains (0–5 points), fruits (0–5 points), vegetables (0–5 points), legumes (0–5 points), fish (0–5 points), red meat (0–5 points), poultry (0–5 points), dairy products (0–5 points), use of olive oil during cooking (0 or 5 points), and alcohol intake (0–5 points) [18]. Table 1 presents the components and scoring criteria of K-HEI and MTD used in our study.
Table 1. Components and scoring criteria of the K-HEI and the MTD scores.
| Component | Scoring criteria | |
|---|---|---|
| K-HEI | ||
| Fruits including juice | 5 points if men: ≥ 3 servings/day, women: ≥ 2 servings/day | |
| 0 points if 0 serving/day | ||
| Fruits excluding juice | 5 points if men: ≥ 1.5 servings/day, women: ≥ 1 serving/day | |
| 0 points if 0 serving/day | ||
| Vegetables including Kimchi or pickles | 5 points if ≥ 7 servings/day | |
| 0 points if 0 serving/day | ||
| Vegetables excluding Kimchi or pickles | 5 points if ≥ 4 servings/day | |
| 0 points if 0 serving/day | ||
| Milk and dairy products | 10 points if ≥ 1 serving/day | |
| 0 points if 0 serving/day | ||
| Protein foods | 10 points if men: ≥ 5 servings/day, women: ≥ 4 servings/day | |
| 0 points if 0 serving/day | ||
| Ratio of white meat to red meat | 5 points if ≥ 4 servings/day | |
| 0 points if 0 serving/day (red meat only) | ||
| Whole grains | 5 points if ≥ 1 serving/day | |
| 0 points if 0 serving/day | ||
| Breakfast consumption | 10 points if yes | |
| 0 points if no | ||
| Sodium | 10 points if ≤ 2,000 mg/day | |
| 0 points if > 85 percentile value | ||
| Percentages of energy from empty calorie foods | 10 points if ≤ 5% | |
| 0 points if ≥ 10% | ||
| Percentages of energy from fat | 10 points if 15–25% | |
| 0 points if < 15 percentile value or > 85 percentile value | ||
| Refined grains | 5 points if men: ≤ 4 servings/day, women: ≤ 3 servings/day | |
| 0 points if men: ≥ 5 servings/day, women: ≥ 4 servings/day | ||
| Percentages of energy from carbohydrate | 5 points if 55–70% | |
| MTD score | 0 points if < 15 percentile value or > 85 percentile value | |
| Whole grains | 5 points if ≥ 4.6 servings/week | |
| 0 points if 0 serving/day | ||
| Fruits | 5 points if ≥ 4.6 servings/week | |
| 0 points if 0 serving/day | ||
| Vegetables | 5 points if ≥ 4.6 servings/week | |
| 0 points if 0 serving/day | ||
| Legumes | 5 points if ≥ 4.6 servings/week | |
| 0 points if 0 serving/day | ||
| Fish | 5 points if ≥ 4.6 servings/week | |
| 0 points if 0 serving/day | ||
| Red meat | 5 points if 0 serving/day | |
| 0 points if ≥ 4.6 servings/week | ||
| Poultry | 5 points if 0 serving/day | |
| 0 points if ≥ 4.6 servings/week | ||
| Dairy products | 5 points if 0 serving/day | |
| 0 points if ≥ 4.6 servings/week | ||
| Alcohol | 5 points if 0 ≤ to < 300 mL/day | |
| 0 points if ≥ 700 mL/day | ||
| Olive oil use | 5 points if used | |
| 0 points if never used | ||
K-HEI, Korean Healthy Eating Index; MTD, Mediterranean-Type Diet.
Every 2 yrs, the total muscle mass was measured using bioelectrical impedance analysis (BIA) to calculate the percentage change from baseline. Loss of muscle mass was defined as a reduction of ≥ 5% of total muscle mass over a 2-yr period. The same definition was applied in previous analyses based on the dataset used in our study [19].
Covariates
We assessed demographic, socioeconomic, and lifestyle characteristics as covariates. Age, as a continuous variable, was included as a demographic factor. The total daily energy intake (kcal/day) was also included as a continuous variable and was calculated from dietary data using a validated SQFFQ. Alcohol consumption was categorized as a binary variable (yes or no) based on the self-reported drinking status. Smoking status was categorized into three groups: never, former, and current smokers. The physical activity of subjects was categorized into three levels based on metabolic equivalent of tasks (METs) per day: light (METs < 20), moderate (20 ≤ METs < 40), and vigorous (40 ≤ METs). Socioeconomic factors include monthly household income and educational levels. Monthly household income was divided into 4 groups: 1) < 1,000,000 won (Korean currency 1 million won ≍ 735 USD), 2) 1,000,000 to < 2,000,000 won, 3) 2,000,000 to < 4,000,000 won, and 4) ≥ 4,000,000 won. Educational levels were grouped into 4 categories: 1) elementary school or less, 2) middle school graduate, 3) high school graduate, and 4) college graduate or higher.
Statistical analysis
Categorical data were summarized as frequencies and percentages, while continuous data were summarized as means and SDs. Demographic characteristics, as well as food group intakes and dietary quality scores assessed at baseline, were compared between men and women. Gender differences in baseline characteristics were statistically analyzed using the χ2 test and Student’s t-test. To compare the energy-adjusted mean intakes of food groups and diet quality scores between genders, analysis of covariance was performed with total energy intake as a covariate. The consumption of each food group and the quality of diet score were categorized into 4 quartiles.
The data were analyzed using a Cox proportional hazards regression model to calculate the hazard ratio (HR) and the 95% confidence interval (CI) to identify the level of association between the quality of the diet and the progressive risk of muscle loss. To test for linear trends across quartiles of food group intake and diet quality scores, the median value of each quartile was assigned to participants in that quartile and modeled as a continuous variable in the Cox regression models. P for trend values were derived from these models. Model 1 was adjusted for age and total energy intake. In addition to the adjusted covariates in Model 1, Model 2 was adjusted for alcohol intake, smoking experience, physical activity, monthly household income, and educational level. All the analyses were conducted using the SAS 9.4 software (SAS Institute, Cary, NC, USA).
RESULTS
Baseline characteristics of subjects
Table 2 presents gender-specific analysis of the general characteristics of the subjects in our study. Our study includes a total of 1,280 participants (609 men and 671 women). The mean age is 43.2 ± 0.1 yrs with a slightly higher value observed in men than that in women (43.4 ± 0.1 vs. 43.1 ± 0.1 yrs, P = 0.016). Men had a significantly higher body mass index (24.6 ± 0.1 vs. 24.2 ± 0.1 kg/m2, P = 0.013) and significantly higher energy intake (2,026.7 ± 21.9 vs. 1,889.2 ± 23.5 kcal/day, P < 0.001) than those observed in women. The proportion of never smokers was significantly higher in women (96.4%) than in men (22.7%) (P < 0.001), but 47.2% of men were current smokers when compared to only 2.7% of women. Alcohol consumption was also significantly higher in men (82.9%) than in women (37.5%) (P < 0.001). There was no significant gender-specific difference in the physical activity levels that ranged from light (70.6%), followed by moderate (17.7%), to high (11.7%) in all the subjects (P = 0.176). However, the distribution of monthly household income and educational level was significantly different between men and women (P < 0.001). The percentage of the highest income group (> 4,000,000 won) was higher in men (15.0%) than in women (9.6%), while the percentage of the lowest income group (< 1,000,000 won) was higher in women (15.0%) than in men (8.4%). In terms of educational level, 32.1% of men had a college degree or higher when compared to only 11.2% of women.
Table 2. Baseline characteristics of participants according to gender.
| Variables | Total (n = 1,280) | Men (n = 609) | Women (n = 671) | P-value1) | |
|---|---|---|---|---|---|
| Age (yrs) | 43.24 ± 0.06 | 43.39 ± 0.08 | 43.11 ± 0.08 | 0.016 | |
| BMI (kg/m2) | 24.43 ± 0.08 | 24.64 ± 0.12 | 24.23 ± 0.12 | 0.013 | |
| Energy intake (kcal) | 1,954.64 ± 16.23 | 2,026.72 ± 21.93 | 1,889.22 ± 23.45 | < 0.001 | |
| Smoking status | < 0.001 | ||||
| Never smoker | 774 (61.04) | 138 (22.70) | 636 (96.36) | ||
| Former smoker | 189 (14.91) | 183 (30.10) | 6 (0.91) | ||
| Current smoker | 305 (24.05) | 287 (47.20) | 18 (2.73) | ||
| Alcohol consumption status | < 0.001 | ||||
| Non-drinker | 522 (40.85) | 104 (17.08) | 418 (62.48) | ||
| Drinker | 756 (59.15) | 505 (82.92) | 251 (37.52) | ||
| Physical activity (METs-hours/week) | 0.176 | ||||
| Light (METs < 20) | 884 (70.55) | 408 (68.11) | 476 (72.78) | ||
| Moderate (20 ≤ METs < 40) | 222 (17.72) | 117 (19.53) | 105 (16.06) | ||
| Vigorous (40 ≤ METs) | 147 (11.73) | 74 (12.35) | 73 (11.16) | ||
| Monthly household income (won) | < 0.001 | ||||
| < 1,000,000 | 150 (11.87) | 51 (8.43) | 99 (15.02) | ||
| 1,000,000 to < 2,000,000 | 421 (33.31) | 187 (30.91) | 234 (35.51) | ||
| 2,000,000 to < 4,000,000 | 539 (42.64) | 276 (45.62) | 263 (39.91) | ||
| ≥ 4,000,000 | 154 (12.18) | 91 (15.04) | 63 (9.56) | ||
| Education levels | < 0.001 | ||||
| Elementary school or below | 110 (8.60) | 26 (4.28) | 84 (12.52) | ||
| Middle school graduate | 285 (22.28) | 103 (16.94) | 182 (27.12) | ||
| High school graduate | 614 (48.01) | 284 (46.71) | 330 (49.18) | ||
| College graduate or above | 270 (21.11) | 195 (32.07) | 75 (11.18) | ||
Values are presented as mean ± SD or percentages in parentheses. Boldface indicates statistical significance (P < 0.05).
BMI, body mass index; MET, metabolic equivalent of task.
1)Differences between groups were tested using a Student’s t-test for continuous variables and a χ2 test for categorical variables.
Gender-specific food group intake and the quality of diet
The daily intake of food groups and the quality of diet scores differed significantly between men and women after adjusting for total energy intake (Table 3). Compared to women, men had a high intake of grains (3.73 ± 0.03 vs. 3.53 ± 0.03 servings/day, P < 0.001) as well as oils and sugars (1.47 ± 0.04 vs. 1.13 ± 0.04 servings/day, P < 0.001). In contrast, women consumed significantly more fruits (1.93 ± 0.06 vs. 1.23 ± 0.06 servings/day, P < 0.001), milk and dairy products (0.83 ± 0.03 vs. 0.60 ± 0.03 servings/day, P < 0.001), vegetables (7.77 ± 0.13 vs. 7.36 ± 0.14 servings/day, P = 0.031), and meat, fish, eggs, and legumes (3.39 ± 0.06 vs. 3.14 ± 0.06 servings/day, P = 0.004) than men. Similarly, women had significantly higher diet quality scores in both the K-HEI (57.62 ± 0.43 vs. 48.55 ± 0.45, P < 0.001) and the MTD score (28.68 ± 0.17 vs. 27.38 ± 0.18, P < 0.001) than men.
Table 3. Daily intake of food groups and quality of diet scores analyzed by gender.
| Variables | Men (n = 609) | Women (n = 671) | P-value1) | |
|---|---|---|---|---|
| Food groups (servings/day) | ||||
| Grains | 3.73 ± 0.03 | 3.53 ± 0.03 | < 0.001 | |
| Meat, fish, eggs, legumes | 3.14 ± 0.06 | 3.39 ± 0.06 | 0.004 | |
| Vegetables | 7.36 ± 0.14 | 7.77 ± 0.13 | 0.031 | |
| Fruits | 1.23 ± 0.06 | 1.93 ± 0.06 | < 0.001 | |
| Milk and dairy products | 0.60 ± 0.03 | 0.83 ± 0.03 | < 0.001 | |
| Oils and sugars | 1.47 ± 0.04 | 1.13 ± 0.04 | < 0.001 | |
| Diet quality | ||||
| K-HEI score | 48.55 ± 0.45 | 57.62 ± 0.43 | < 0.001 | |
| MTD score | 27.38 ± 0.18 | 28.68 ± 0.17 | < 0.001 | |
Values are presented as the energy-adjusted mean ± SD. Boldface indicates statistical significance (P < 0.05).
K-HEI, Korean Healthy Eating Index; MTD, Mediterranean-Type Diet.
1)Differences between groups were tested using analysis of covariance adjusted for total energy intake.
Association between the consumption of food groups and the risk of loss of total muscle mass
The associations between food group intake and the risk of loss of total muscle mass are shown in Tables 4 and 5. In men, a significant linear trend was observed between quartiles of grain intake after multivariate adjustment in Model 2 (P for trend = 0.023), indicating that higher grain intake was associated with an increased risk of loss of muscle mass. No significant associations were found with fruit, milk and dairy product intake (Table 4). In women, grain intake was not significantly associated with the risk of loss of total muscle mass. However, higher intake of fruits, milk and dairy products was significantly associated with a reduced risk of loss of muscle mass (Table 5). For fruit intake, the HR in the 2nd, 3rd, and 4th quartiles were consistently lower than the reference group in Model 1 (HR = 0.75, 0.72, and 0.72, respectively), and a similar pattern was observed in Model 2. However, no significant linear trend was observed between the quartiles of fruit intake and the risk of loss of total muscle mass (Model 1: P for trend = 0.106; Model 2: P for trend = 0.097). The intake of milk and dairy products showed a significant linear trend toward reduced loss of total muscle mass (Model 1: P for trend = 0.003; Model 2: P for trend = 0.021). In particular, the HR in the fourth quartile was 0.67 (95% CI, 0.50–0.89) in Model 1 and 0.68 (95% CI, 0.50–0.93) in Model 2. Our analysis shows that meat, fish, egg, legume, vegetable, oil, and sugar intake were not significantly associated with the risk of loss of muscle mass in either men or women (P for trend ≥ 0.05).
Table 4. Risk of loss of total muscle mass (≥ 5% over 2 yrs) associated with food group intake in men.
| Variables | Range (serving/days) | Number of cases | Total person-yrs | Model 11) | Model 22) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| HRs | 95% CI | P for trend3) | HRs | 95% CI | P for trend3) | |||||||
| Lower | Upper | Lower | Upper | |||||||||
| Grains | 0.113 | 0.023 | ||||||||||
| 1st quartile | < 3.31 | 65 | 656 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 3.31–3.61 | 60 | 650 | 0.90 | 0.63 | 1.28 | 0.93 | 0.65 | 1.33 | |||
| 3rd quartile | 3.61–4.09 | 54 | 556 | 0.85 | 0.58 | 1.26 | 0.89 | 0.60 | 1.32 | |||
| 4th quartile | > 4.09 | 70 | 683 | 1.32 | 0.84 | 2.07 | 1.50 | 0.94 | 2.39 | |||
| Meat, fish, eggs, legumes | 0.167 | 0.111 | ||||||||||
| 1st quartile | < 2.00 | 62 | 599 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 2.00–3.00 | 70 | 708 | 1.20 | 0.85 | 1.69 | 1.18 | 0.84 | 1.68 | |||
| 3rd quartile | 3.00–4.16 | 65 | 682 | 1.03 | 0.72 | 1.48 | 1.00 | 0.69 | 1.45 | |||
| 4th quartile | > 4.16 | 52 | 556 | 0.79 | 0.52 | 1.19 | 0.79 | 0.52 | 1.22 | |||
| Vegetables | 0.725 | 0.910 | ||||||||||
| 1st quartile | < 5.15 | 60 | 559 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 5.15–7.31 | 61 | 679 | 0.99 | 0.69 | 1.42 | 0.98 | 0.68 | 1.41 | |||
| 3rd quartile | 7.31–9.38 | 70 | 717 | 1.24 | 0.87 | 1.78 | 1.17 | 0.82 | 1.69 | |||
| 4th quartile | > 9.38 | 58 | 589 | 1.03 | 0.69 | 1.52 | 0.98 | 0.65 | 1.46 | |||
| Fruits | 0.818 | 0.869 | ||||||||||
| 1st quartile | < 0.52 | 63 | 617 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 0.52–0.89 | 57 | 581 | 0.89 | 0.62 | 1.28 | 0.92 | 0.63 | 1.32 | |||
| 3rd quartile | 0.89–1.51 | 67 | 683 | 1.09 | 0.77 | 1.55 | 1.12 | 0.78 | 1.62 | |||
| 4th quartile | > 1.51 | 62 | 664 | 1.00 | 0.68 | 1.46 | 0.99 | 0.67 | 1.46 | |||
| Milk and dairy products | 0.250 | 0.466 | ||||||||||
| 1st quartile | < 0.10 | 66 | 616 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 0.10–0.50 | 62 | 662 | 0.98 | 0.70 | 1.39 | 1.02 | 0.71 | 1.45 | |||
| 3rd quartile | 0.50–1.00 | 69 | 702 | 1.02 | 0.73 | 1.43 | 1.07 | 0.75 | 1.53 | |||
| 4th quartile | > 1.00 | 52 | 564 | 0.79 | 0.55 | 1.16 | 0.89 | 0.61 | 1.31 | |||
| Oils and sugars | 0.623 | 0.307 | ||||||||||
| 1st quartile | < 0.43 | 69 | 670 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 0.43–1.12 | 64 | 665 | 0.92 | 0.65 | 1.29 | 0.91 | 0.64 | 1.29 | |||
| 3rd quartile | 1.12–2.33 | 51 | 537 | 0.69 | 0.48 | 1.00 | 0.69 | 0.48 | 1.01 | |||
| 4th quartile | > 2.33 | 65 | 672 | 0.93 | 0.66 | 1.32 | 0.87 | 0.60 | 1.24 | |||
Values are presented as HRs with 95% CIs. Boldface indicates statistical significance (P < 0.05).
HR, hazard ratio; CI, confidence interval.
1)Model 1: Adjusted for age (yrs) and total energy intake (kcal/day).
2)Model 2: Adjusted for age (yrs), total energy intake (kcal/day), alcohol consumption status (yes or no), smoking status (never, former, and current smoker), physical activity (light, moderate, and vigorous activity), monthly household income (< 1,000,000 won [Korean currency: 1 million won ≍ 735 USD], 1,000,000 to < 2,000,000 won, 2,000,000 to < 4,000,000 won, and 4,000,000 won or higher), and educational level (elementary school or below, middle school graduate, high school graduate, and college graduate or above).
3)P for trend were obtained from Cox regression model analysis.
Table 5. Risk of loss of total muscle mass (≥ 5% over 2 yrs) associated with food group intake in women.
| Variables | Range (serving/days) | Number of cases | Total person-yrs | Model 11) | Model 22) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| HR | 95% CI | P for trend3) | HR | 95% CI | P for trend3) | |||||||
| Lower | Upper | Lower | Upper | |||||||||
| Grains | 0.272 | 0.198 | ||||||||||
| 1st quartile | < 2.96 | 104 | 1,052 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 2.96–3.39 | 113 | 1,156 | 1.12 | 0.85 | 1.48 | 1.12 | 0.83 | 1.49 | |||
| 3rd quartile | 3.39–3.91 | 101 | 1,025 | 0.98 | 0.73 | 1.32 | 1.13 | 0.83 | 1.54 | |||
| 4th quartile | > 3.91 | 112 | 1,084 | 1.25 | 0.89 | 1.76 | 1.29 | 0.90 | 1.86 | |||
| Meat, fish, eggs, legumes | 0.688 | 0.963 | ||||||||||
| 1st quartile | < 1.93 | 108 | 1,088 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 1.93–2.85 | 108 | 1,093 | 0.99 | 0.76 | 1.30 | 1.09 | 0.82 | 1.45 | |||
| 3rd quartile | 2.85–4.07 | 113 | 1,167 | 1.06 | 0.81 | 1.40 | 1.20 | 0.90 | 1.61 | |||
| 4th quartile | > 4.07 | 101 | 969 | 0.93 | 0.67 | 1.28 | 1.02 | 0.73 | 1.42 | |||
| Vegetables | 0.879 | 0.879 | ||||||||||
| 1st quartile | < 4.79 | 108 | 1,082 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 4.79–6.85 | 105 | 1,066 | 0.94 | 0.72 | 1.23 | 0.96 | 0.73 | 1.27 | |||
| 3rd quartile | 6.85–9.51 | 114 | 1,191 | 1.05 | 0.80 | 1.38 | 1.06 | 0.80 | 1.41 | |||
| 4th quartile | > 9.51 | 103 | 978 | 0.95 | 0.70 | 1.29 | 0.91 | 0.66 | 1.25 | |||
| Fruits | 0.106 | 0.097 | ||||||||||
| 1st quartile | < 0.71 | 123 | 1,238 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 0.71–1.26 | 103 | 1,067 | 0.75 | 0.57 | 0.97 | 0.81 | 0.61 | 1.06 | |||
| 3rd quartile | 1.26–2.14 | 102 | 1,045 | 0.72 | 0.55 | 0.95 | 0.76 | 0.57 | 1.00 | |||
| 4th quartile | > 2.14 | 102 | 966 | 0.72 | 0.54 | 0.97 | 0.73 | 0.54 | 1.00 | |||
| Milk and dairy products | 0.003 | 0.021 | ||||||||||
| 1st quartile | < 0.15 | 120 | 1,176 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 0.15–0.51 | 112 | 1,139 | 0.91 | 0.70 | 1.18 | 0.86 | 0.66 | 1.14 | |||
| 3rd quartile | 0.51–1.12 | 102 | 1,015 | 0.76 | 0.58 | 1.00 | 0.81 | 0.61 | 1.08 | |||
| 4th quartile | > 1.12 | 96 | 987 | 0.67 | 0.50 | 0.89 | 0.68 | 0.50 | 0.93 | |||
| Oils and sugars | 0.564 | 0.406 | ||||||||||
| 1st quartile | < 0.26 | 112 | 1,126 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 0.26–1.00 | 105 | 1,062 | 0.83 | 0.64 | 1.09 | 0.87 | 0.66 | 1.16 | |||
| 3rd quartile | 1.00–1.58 | 103 | 1,039 | 1.00 | 0.77 | 1.31 | 1.10 | 0.83 | 1.45 | |||
| 4th quartile | > 1.58 | 110 | 1,090 | 1.01 | 0.77 | 1.32 | 1.05 | 0.79 | 1.39 | |||
Values are presented as HRs with 95% CIs. Boldface indicates statistical significance (P < 0.05).
HR, hazard ratio; CI, confidence interval.
1)Model 1: Adjusted for age (yrs) and total energy intake (kcal/day).
2)Model 2: Adjusted for age (yrs), total energy intake (kcal/day), alcohol consumption status (yes or no), smoking status (never, former, and current smoker), physical activity (light, moderate, and vigorous activity), monthly household income (< 1,000,000 won [Korean currency: 1 million won ≍ 735 USD], 1,000,000 to < 2,000,000 won, 2,000,000 to < 4,000,000 won, and 4,000,000 won or higher), and educational level (elementary school or below, middle school graduate, high school graduate, and college graduate or above).
3)P for trend were obtained from Cox regression model analysis.
Association between quality of diet and the risk of loss of total muscle mass
The association between dietary quality scores and the risk of loss of total muscle mass is presented in Tables 6 and 7. There were no statistically significant associations across quartiles in men for both the K-HEI and MTD scores (Table 6). In Model 1, there was a significant linear association between K-HEI and the risk of loss of muscle mass in women, whereas this association was not significant after multivariate adjustment in Model 2. The HR in the 4th quartile compared to the 1st quartile was 0.72 (95% CI, 0.54–0.96) in Model 1 and 0.82 (95% CI, 0.60–1.11) in Model 2 (Table 7). No significant associations were observed across quartiles for the MTD scores in women.
Table 6. Risk of loss of total muscle mass (≥ 5% over 2 yrs) associated with quality of diet score in men.
| Variables | Range (score) | Number of cases | Total person-yrs | Model 11) | Model 22) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| HR | 95% CI | P for trend3) | HR | 95% CI | P for trend3) | |||||||
| Lower | Upper | Lower | Upper | |||||||||
| K-HEI | 0.730 | 0.531 | ||||||||||
| 1st quartile | < 44.99 | 81 | 755 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 44.99–53.12 | 76 | 784 | 1.12 | 0.81 | 1.54 | 1.12 | 0.81 | 1.55 | |||
| 3rd quartile | 53.12–62.05 | 67 | 721 | 1.12 | 0.80 | 1.56 | 1.21 | 0.86 | 1.71 | |||
| 4th quartile | > 62.05 | 25 | 283 | 0.99 | 0.62 | 1.58 | 1.08 | 0.67 | 1.75 | |||
| MTD score | 0.936 | 0.991 | ||||||||||
| 1st quartile | < 24.00 | 66 | 633 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 25.00–28.00 | 87 | 898 | 1.11 | 0.81 | 1.53 | 1.19 | 0.86 | 1.65 | |||
| 3rd quartile | 28.00–31.00 | 46 | 460 | 0.97 | 0.66 | 1.41 | 0.99 | 0.68 | 1.46 | |||
| 4th quartile | > 31.00 | 50 | 553 | 1.01 | 0.70 | 1.46 | 1.06 | 0.73 | 1.55 | |||
Values are presented as HRs with 95% CIs.
K-HEI, Korean Healthy Eating Index; MTD, Mediterranean-Type Diet; HR, hazard ratio; CI, confidence interval.
1)Model 1: Adjusted for age (yrs) and total energy intake (kcal/day).
2)Model 2: Adjusted for age (yrs), total energy intake (kcal/day), alcohol consumption status (yes or no), smoking status (never, former, and current smoker), physical activity (light, moderate, and vigorous activity), monthly household income (< 1,000,000 won [Korean currency; 1 million won ≍ 735 USD], 1,000,000 to < 2,000,000 won, 2,000,000 to < 4,000,000 won, and 4,000,000 won or higher), and educational level (elementary school or below, middle school graduate, high school graduate, and college graduate or above). Alcohol consumption is excluded in the MTD score.
3)P for trend were obtained from Cox regression model analysis.
Table 7. Risk of total muscle mass loss (≥ 5% over 2 yrs) associated with the diet quality score in women.
| Variables | Range (score) | Number of cases | Total person-yrs | Model 11) | Model 22) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| HR | 95% CI | P for trend3) | HR | 95% CI | P for trend3) | |||||||
| Lower | Upper | Lower | Upper | |||||||||
| K-HEI | 0.023 | 0.153 | ||||||||||
| 1st quartile | < 45.00 | 75 | 723 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 45.00–53.13 | 91 | 921 | 0.90 | 0.66 | 1.22 | 0.96 | 0.70 | 1.33 | |||
| 3rd quartile | 53.13–62.11 | 118 | 1,150 | 1.11 | 0.83 | 1.49 | 1.20 | 0.87 | 1.64 | |||
| 4th quartile | > 62.11 | 146 | 1,522 | 0.72 | 0.54 | 0.96 | 0.82 | 0.60 | 1.11 | |||
| MTD score | 0.943 | 0.730 | ||||||||||
| 1st quartile | < 25.00 | 74 | 710 | 1 (ref.) | 1 (ref.) | |||||||
| 2nd quartile | 25.00–29.00 | 124 | 1,260 | 0.91 | 0.68 | 1.21 | 0.93 | 0.69 | 1.26 | |||
| 3rd quartile | 29.00–32.00 | 125 | 1,275 | 0.98 | 0.73 | 1.31 | 1.06 | 0.78 | 1.44 | |||
| 4th quartile | 32.00–41.00 | 107 | 1,073 | 0.95 | 0.71 | 1.28 | 1.02 | 0.75 | 1.38 | |||
Values are presented as HRs with 95% CIs. Boldface indicates statistical significance (P for trend < 0.05).
K-HEI, Korean Healthy Eating Index; MTD, Mediterranean-Type Diet; HR, hazard ratio; CI, confidence interval.
1)Model 1: Adjusted for age (yrs) and total energy intake (kcal/day).
2)Model 2: Adjusted for age (yrs), total energy intake (kcal/day), alcohol consumption status (yes or no), smoking status (never, former, and current smoker), physical activity (light, moderate, and vigorous activity), monthly household income (< 1,000,000 won [Korean currency; 1 million won ≍ 735 USD], 1,000,000 to < 2,000,000 won, 2,000,000 to < 4,000,000 won, and 4,000,000 won or higher), and educational level (elementary school or below, middle school graduate, high school graduate, and college graduate or above). Alcohol consumption is excluded in the MTD score.
3)P for trend were obtained from Cox regression model analysis.
DISCUSSION
In our present study, we analyzed the gender-associated effects of food group intake and the quality of diet scores on the loss of total muscle mass (defined as ≥ 5% muscle loss over a period of 2 yrs) among Korean baby boomers registered in the KoGES cohort from 2001 to 2018. In men, the group with the highest grain intake had a significantly higher risk of loss of muscle mass. Conversely, increased consumption of fruits and dairy products was found to be associated with a reduced risk of loss of muscle mass in women. There was a statistically significant association of K-HEI diet quality scores in women (Table 3). In particular, elevated K-HEI scores in Model 1 were associated with a reduced risk of loss of muscle mass.
The results of our study are consistent with other studies that have reported a potential negative impact of a high-carbohydrate diet on muscle health [20,21,22]. It has been established that excessive consumption of grains (especially refined grains) leads to a significant increase in postprandial blood sugar and insulin resistance. Consequently, this metabolic process may activate muscle protein breakdown. However, another study have shown a positive correlation between grain consumption and increased muscle mass in men in Korea [23]. The difference observed in our result may be attributable to physiological effects that are influenced by the methods of refining or processing grains. Refined grains lose dietary fiber, vitamins, and minerals during processing, while whole grains are enriched with these nutrients. This contributes to significant differences in blood sugar response and metabolic effects. Further research is required to distinguish between the degree of processing and refining within food groups. The muscle-protective effects of fruits and dairy products observed in women are consistent with previous studies indicating that vitamins, minerals, antioxidants, and milk proteins (casein, whey) promote muscle protein synthesis and muscle function [24,25,26]. Fruits are characterized by a high antioxidant content, including vitamins and minerals, which have been found to inhibit inflammatory mediators and to protect mitochondrial function in muscles. Dairy products are a complete source of protein and are particularly high in leucine, which activates the mTOR pathway and promotes muscle protein synthesis [27]. Calcium is also known to support the function of muscle contraction proteins [28].
The gender-specific patterns identified in this study are partially consistent with those reported in previous studies, which indicate gender differences related to dietary behavior, nutrient metabolism, and sarcopenia risk [29,30,31,32]. There are several potential causes of these gender-specific differences. Initially, the K-HEI scores of women were higher than those of men at baseline (Table 3), which may be due to the refined grain variable included in the K-HEI calculation formula with men displaying a negative trend. The evidence suggests that women generally adhere to a healthy diet that may have additional benefits, such as the protective effect of K-HEI. Furthermore, the phenomenon may be attributed to biological factors, including variations in sex hormones. A decline in testosterone levels has the potential to negate the positive effects of a healthy diet in men [31].
Our study did not observe a significant association between adherence to a Mediterranean diet and the preservation of muscle mass. In a systematic review, previous studies conducted on Mediterranean or Western populations have consistently demonstrated the protective effects of the Mediterranean diet on muscle mass and strength. However, results from studies conducted on Asian populations are inconsistent and insufficient [15]. Olive oil and seafood, which are emphasized in the traditional Mediterranean diet scoring system, are foods that are not commonly consumed in the traditional Korean diet. Although Koreans maintain a nutritionally adequate and healthy diet, the dietary scores are underestimated since there is a low consumption of culturally-specific items associated with the Mediterranean diet. Our results emphasize the importance of culturally-adapted dietary indicators when evaluating diet-disease relationships.
The current study has several strengths, including a large-scale community-based cohort study, long-term follow-up, validated dietary assessment tools, and statistical adjustments for confounding variables. However, it is important to acknowledge the limitations of our approach. First, the muscle mass of the subjects was measured using BIA. This method is generally considered to be practical for large-scale studies, but it is known to be less accurate than dual-energy X-ray absorptiometry. Second, the dietary intake data were self-reported, which is a potential factor for measurement errors. Third, we could not completely exclude the possibility of residual confounding factors. Despite these limitations, the results of our study provide valuable evidence for the development of dietary strategies that incorporate gender and cultural characteristics to prevent muscle loss of baby boomers in Korea.
In conclusion, our study provides evidence that specific dietary factors and the overall quality of the diet are significantly associated with the risk of loss of muscle mass in Korean baby boomers. There were significant differences when the results obtained for men and women were compared. The results of our study suggest an association between high grain intake in men and the potential for adverse effects, while dairy intake in women showed protective effects on muscle mass. Moreover, the gender-specific association of the quality of diet scores with the risk of loss of muscle mass highlights the necessity for personalized nutritional strategies. Future studies should include well-designed clinical trials to develop practical, evidence-based dietary strategies adapted to the lifestyle of Korean baby boomers and to evaluate their effectiveness to prevent muscle loss.
ACKNOWLEDGMENTS
This study is part of the doctoral dissertation of Eun-Hee Jang in the Department of Food and Nutrition, Sungshin Women’s University, Seoul, Korea.
Footnotes
Funding: This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2021R1F1A1061180).
Conflict of Interest: The authors declare no potential conflicts of interests.
- Conceptualization:Lee S.
- Data curation:Jang EH.
- Investigation:Jang EH.
- Methodology:Lee S, Jang EH.
- Supervision:Lee S.
- Validation:Jang EH.
- Writing - original draft:Jang EH.
- Writing - review & editing:Lee S, Jang EH.
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