Introduction
Sarcopenia is a progressive skeletal muscle disorder affecting muscle strength and function [
1,
2]. This disorder is often linked to aging, however, in some cases it occurs at earlier age [
1]. In addition to muscle strength, sarcopenia affects muscle quantity/quality and physical performance [
1]. It is associated with fall, fracture and mortality [
3,
4]. The prevalence of sarcopenia in western societies [
5] and Asian countries [
3] is estimated at 1 to 29% and 2 to 46%, respectively. Overall prevalence among Iranians is 16.5 to 32.5% [
6].
Along with several non-dietary contributors including telomere length, dietary intake of macro- and micro-nutrients [
1,
7,
8] and several food groups including fruits [
9] and nuts [
10] has been linked with this condition. However, earlier studies have mostly focused on individual nutrients or foods and limited attention has been given to the whole diet approach. To examine adherence of people to whole dietary recommendations, several indicators, including Healthy Eating Index (HEI), have been developed. The Alternative Healthy Eating Index-2010 (AHEI-2010) is an amended version of the Healthy Eating Index (HEI), which measures dietary compliance with suggested healthy eating habits [
11‐
13]. AHEI is different from HEI in terms of components. The AHEI-2010 focuses on fat quality (i.e., omega-3 and polyunsaturated fat intake), highlights nuts and legumes intake, and considers moderate alcohol consumption as being healthful regardless of disease status (i.e., diabetes). Furthermore, it recommends restricting the intake of red and processed meats and added sugars (i.e., sugar-sweetened beverages and fruit juice) [
14]. The majority of earlier studies on chronic conditions have revealed that healthy eating, as measured by HEI and AHEI, were protectively associated with risk of these conditions [
15,
16]. In addition, in a nationally representative elderly cohort of US population, greater HEI score was associated with longevity [
17]. Furthermore, in a cross-sectional study, HEI scores were associated with handgrip strength (HGS) [
18]. Several components of AHEI-2010 has been assessed in relation to sarcopenia [
9,
19,
20], but the holistic approach of total diet was rarely examined. In particular, we are aware of no study examining the relationship between AHEI and risk of sarcopenia.
This is particularly important in the Middle East, where the application of other dietary patterns, like Mediterranean diet, might be less relevant. In addition, the growing number of elderly people in this region highlights the need for finding preventive measures, including dietary measures, for sarcopenia [
21,
22]. Given the lack of evidence on the association between AHEI and sarcopenia in this region, we conducted this observational study to investigate the association between adherence to AHEI-2010 and prevalence of sarcopenia among Iranian elderly people.
Results
General characteristics of study participants across tertile categories of AHEI-2010 are presented in Table
1. People with EWGSOP2-sarcopenia were less likely to be obese and diabetic and more likely to be sexual hormone and corticosteroids user. The mean ± SD of AHEI-2010 in our study was 49.5 ± 9.9. When we examined across tertiles of AHEI-2010 score, individuals in the highest tertile were more likely to be smoker. No other significant differences were seen.
Table 1
General characteristics of study participants across tertiles of Alternative Healthy Eating Index and individuals with and without sarcopenia a
Age (year) | 66.79 ± 7.70 | 64.5 ± 6.3 | 67.0 ± 7.8 | 0.08 | 66.1 ± 7.4 | 67.7 ± 7.5 | 67.2 ± 8.0 | 0.51 |
BMI (kg/m2) d | 27.38 ± 4.20 | 23.4 ± 2.7 | 27.8 ± 4.1 | < 0.001 | 27.0 ± 3.9 | 27.7 ± 4.4 | 27.3 ± 4.2 | 0.55 |
Physical activity (MET-h/wk) e | 1294.52 ± 1429.57 | 1223.4 ± 1122.3 | 1302.7 ± 1462.3 | 0.77 | 1286.8 ± 1563.3 | 1076.0 ± 1013.6 | 1508.0 ± 1588.5 | 0.10 |
Female (%) | 51 | 64.5 | 49.4 | 0.11 | 44.3 | 58.5 | 51.0 | 0.13 |
Alcohol use (%) f | 13.3 | 9.7 | 13.8 | 0.52 | 15.1 | 16.0 | 9.0 | 0.29 |
Smoking (%) | 12.7 | 12.9 | 12.6 | 0.96 | 19.8 | 7.4 | 10.0 | 0.02 |
Medical history | |
Diabetes (%) | 20.7 | 6.5 | 22.3 | 0.03 | 17.9 | 20.2 | 24.0 | 0.55 |
MI (%) g | 12 | 6.5 | 12.6 | 0.31 | 13.2 | 9.6 | 13.0 | 0.68 |
CVA (%) h | 2.7 | 6.5 | 2.2 | 0.16 | 1.9 | 5.3 | 1.0 | 0.14 |
Arthritis (%) | 1.7 | 3.2 | 1.5 | 0.47 | 0.9 | 4.3 | 0 | 0.05 |
Asthma (%) | 2 | 3.2 | 1.9 | 0.60 | 2.8 | 3.2 | 2.0 | 0.21 |
Drug history | |
Sexual hormone use (%) | 3 | 9.7 | 2.2 | 0.02 | 2.8 | 4.3 | 2.0 | 0.64 |
Statin use (%) | 36.7 | 35.5 | 36.8 | 0.88 | 31.1 | 40.4 | 39.0 | 0.33 |
ACEI use (%) i | 7.7 | 3.2 | 8.2 | 0.32 | 6.6 | 9.6 | 7.0 | 0.69 |
Corticosteroid use (%) | 2.7 | 12.9 | 1.5 | < 0.001 | 1.9 | 5.3 | 1.0 | 0.14 |
Table
2 provides the multivariate-adjusted dietary intakes of study population across tertiles of AHEI-2010. Compared to the bottom tertile, individuals in the top tertile of AHEI-2010 had higher intakes of fruits, vegetables, nuts, legumes and soy, dairy products, grains, fiber, calcium, pyridoxine and folate and lower intake of energy, sugar-sweetened beverages and sweets, red and processed meats and sodium.
Table 2
Dietary intakes of participants by tertiles of Alternative Healthy Eating Index a
Food groups (g/day) |
Fruits | 527.3 ± 23.9 | 657.8 ± 25.3 | 776.1 ± 24.7 | < 0.001 |
Vegetables | 431.5 ± 21.7 | 514.9 ± 23.0 | 717.5 ± 22.4 | < 0.001 |
Nuts, legumes and soy | 49.2 ± 3.4 | 56.1 ± 3.6 | 72.2 ± 3.5 | < 0.001 |
Dairy products | 342.2 ± 29.3 | 627.4 ± 31.1 | 513.3 ± 30.3 | 0.027 |
Grains | 387.1 ± 17.4 | 331.0 ± 18.5 | 307.2 ± 18.0 | 0.005 |
Sugar-sweetened beverages and sweets | 128.2 ± 11.1 | 84.9 ± 11.8 | 53.0 ± 11.5 | < 0.001 |
Red and processed meats | 50.7 ± 2.7 | 33.8 ± 2.9 | 27.3 ± 2.8 | < 0.001 |
Nutrients |
Sodium | 3856.1 ± 124.0 | 3296.8 ± 131.8 | 3148.5 ± 128.4 | < 0.001 |
Energy (kcal/d) | 2156.6 ± 88.1 | 2119.2 ± 93.5 | 2510.7 ± 90.3 | 0.004 |
Carbohydrate (g/day) | 373.3 ± 5.3 | 364.4 ± 5.6 | 359.7 ± 5.5 | 0.200 |
Protein (g/day) | 84.7 ± 1.7 | 85.4 ± 1.8 | 88.0 ± 1.8 | 0.411 |
Fat (g/day) | 55.9 ± 1.8 | 60.4 ± 1.9 | 61.7 ± 1.8 | 0.074 |
Fiber (g/day) | 27.0 ± 0.7 | 29.6 ± 0.8 | 33.3 ± 0.8 | < 0.001 |
Calcium (mg/d) | 1287.7 ± 42.0 | 1433.3 ± 44.6 | 1304.7 ± 43.5 | 0.039 |
Pyridoxine (mg/d) | 2.3 ± 0.1 | 2.8 ± 0.1 | 2.6 ± 0.1 | 0.023 |
Folate (mcg/d) | 499.4 ± 10.6 | 537.9 ± 11.2 | 595.5 ± 10.9 | < 0.001 |
Means of sarcopenia components as well as the prevalence of EWGSOP2-sarcopenia and its components across different AHEI-2010 categories are shown in Table
3. In the general population, mean gait speed and hand grip strength were significantly lower among cases in the highest tertile of AHEI-2010 compared with those in the lowest tertile. Stratified analysis by gender revealed no significant difference in means of muscle mass, hand grip strength and gait speed across different AHEI-2010 categories. Examining the prevalence of EWGSOP2-sarcopenia across categories of AHEI-2010, we found a high prevalence of slower gait speed among those in the highest category of AHEI-2010 compared with those in the lowest tertile (36% vs. 34%,
P < 0.05). In terms of other components, we did not find a significant difference across tertiles of AHEI-2010 score. This was the case when we assessed by gender.
Table 3
Means of sarcopenia components and their prevalence across categories of Alternative Healthy Eating Index
Whole population |
n | 106 | 94 | 100 | |
Muscle mass [ASM/h2] (kg) b | 6.6 ± 1.0 | 6.5 ± 0.9 | 6.6 ± 1.0 | 0.701 |
Hand grip strength (psi) | 11.5 ± 3.9 | 10.2 ± 3.4 | 11.3 ± 3.2 | 0.026 |
Gait speed (m/s) | 0.8 ± 0.2 | 0.7 ± 0.2 | 0.8 ± 0.2 | 0.019 |
Lower muscle mass, n (%) c | 48 (45.3) | 34 (36.2) | 35 (35) | 0.253 |
Lower hand grip strength, n (%) d | 31 (29.2) | 38 (40.4) | 27 (27) | 0.101 |
Slower gait speed (m/s), n (%) e | 36 (34) | 50 (53.2) | 36 (36) | 0.011 |
Sarcopenia, n (%) f | 11 (10.4) | 14 (14.9) | 6 (6) | 0.126 |
Men |
n | 59 | 39 | 49 | |
Muscle mass [ASM/h2] (kg) | 7.2 ± 0.7 | 7.1 ± 0.7 | 7.2 ± 0.7 | 0.814 |
Hand grip strength (psi) | 14.0 ± 3.0 | 12.8 ± 3.1 | 13.6 ± 2.6 | 0.153 |
Gait speed (m/s) | 0.9 ± 0.2 | 0.8 ± 0.2 | 0.8 ± 0.2 | 0.067 |
Lower muscle mass, n (%) c | 33 (55.9) | 22 (56.4) | 25 (51) | 0.842 |
Lower hand grip strength, n (%) d | 9 (15.3) | 10 (25.6) | 6 (12.2) | 0.226 |
Slower gait speed (m/s), n (%) e | 15 (25.4) | 18 (46.2) | 13 (26.5) | 0.065 |
Sarcopenia, n (%) f | 4 (6.8) | 6 (15.4) | 1 (2) | 0.059 |
Women |
n | 47 | 55 | 51 | |
Muscle mass [ASM/h2] (kg) | 5.8 ± 0.8 | 6.1 ± 0.8 | 6.1 ± 0.9 | 0.305 |
Hand grip strength (psi) | 8.3 ± 2.1 | 8.3 ± 2.1 | 9.0 ± 2.0 | 0.156 |
Gait speed (m/s) | 0.8 ± 0.2 | 0.7 ± 0.1 | 0.8 ± 0.2 | 0.449 |
Lower muscle mass, n (%) c | 15 (31.9) | 12 (21.8) | 10 (19.6) | 0.319 |
Lower hand grip strength, n (%) d | 22 (46.8) | 28 (50.9) | 21 (41.2) | 0.603 |
Slower gait speed (m/s), n (%) e | 21 (44.7) | 32 (58.2) | 23 (45.1) | 0.288 |
Sarcopenia, n (%) f | 7 (14.9) | 8 (14.5) | 5 (9.8) | 0.697 |
Crude and multivariable-adjusted ORs for sarcopenia across tertiles of AHEI-2010 score are provided in Table
4. In the crude model, AHEI-2010 was not significantly associated with the risk of EWGSOP2-sarcopenia [OR: 0.55; 95% confidence interval (CI): 0.19, 1.55]. When the analysis was controlled for potential confounders, this association remained non-significant (OR: 0.44; 95% CI: 0.14, 1.34). Even further adjustment for BMI did not alter the associations (OR: 0.39; 95% CI: 0.10, 1.51). The same findings were observed in the sex-stratified analyses either before (men: OR: 0.30; 95% CI: 0.03, 3.14 and women: 0.37; 95% CI: 0.09, 1.52) or after controlling for BMI (men: OR: 0.35; 95% CI: 0.02, 4.82 and women: 0.52; 95% CI: 0.10, 2.53). The same findings were seen when we applied EWGSOP-sarcopenia definition, either before (OR: 0.58; 95% CI: 0.27, 1.27) or after adjusting for potential confounders (OR: 0.58; 95% CI: 0.26, 1.31) or BMI (OR: 0.55; 95% CI: 0.22, 1.37). In the gender-stratified analyses, no significant relationship was found among men, either before (OR 0.76; 95% CI: 0.26, 2.21) or after controlling for BMI (OR 0.83; 95% CI: 0.26, 2.64). However, women in the top tertile of AHEI-2010 score, were 80% less likely to have EWGSOP-sarcopenia compared to those in the bottom tertile before considering BMI (OR: 0.20; 95% CI: 0.04, 0.91). Additional adjustment for BMI made this association non-significant (OR: 0.23; 95% CI: 0.04, 1.38).
Table 4
Multivariable-adjusted odds ratios (95% CIs) for sarcopenia across tertile categories of Alternative Healthy Eating Index, stratified by gender
Sarcopenia a |
n | 106 | 94 | 100 | |
Crude | 1.00 | 1.51 (0.65–3.51) | 0.55 (0.19–1.55) | 0.318 |
Model 1b | 1.00 | 1.47 (0.61–3.49) | 0.44 (0.15–1.32) | 0.189 |
Model 2 c | 1.00 | 1.43 (0.57–3.60) | 0.44 (0.14–1.34) | 0.187 |
Model 3 f | 1.00 | 1.60 (0.54–4.75) | 0.39 (0.10–1.51) | 0.259 |
Men |
n | 59 | 39 | 49 | |
Crude | 1.00 | 2.50 (0.65–9.51) | 0.28 (0.03–2.65) | 0.413 |
Model 1 e | 1.00 | 2.75 (0.70–10.82) | 0.30 (0.03–2.79) | 0.457 |
Model 2 c | 1.00 | 2.98 (0.57–15.40) | 0.30 (0.03–3.14) | 0.461 |
Model 3 f | 1.00 | 1.10 (0.11–10.39) | 0.35 (0.02–4.82) | 0.476 |
Women |
n | 47 | 55 | 51 | |
Crude | 1.00 | 0.97 (0.32–2.91) | 0.62 (0.18–2.11) | 0.451 |
Model 1 e | 1.00 | 0.92 (0.30–2.83) | 0.42 (0.10–1.63) | 0.218 |
Model 2 c | 1.00 | 0.82 (0.24–2.78) | 0.37 (0.09–1.52) | 0.168 |
Model 3 f | 1.00 | 1.58 (0.37–6.69) | 0.52 (0.10–2.53) | 0.347 |
Sarcopenia d |
n | 106 | 94 | 100 | |
Crude | 1.00 | 1.31 (0.66–2.59) | 0.58 (0.27–1.27) | 0.211 |
Model 1 b | 1.00 | 1.39 (0.69–2.81) | 0.55 (0.25–1.22) | 0.180 |
Model 2 c | 1.00 | 1.47 (0.71–3.04) | 0.58 (0.26–1.31) | 0.236 |
Model 3 f | 1.00 | 1.74 (0.75–4.03) | 0.55 (0.22–1.37) | 0.264 |
Men |
n | 59 | 39 | 49 | |
Crude | 1.00 | 2.18 (0.85–5.55) | 0.85 (0.31–2.31) | 0.847 |
Model 1 e | 1.00 | 2.01 (0.77–5.29) | 0.58 (0.74–2.26) | 0.676 |
Model 2 c | 1.00 | 1.94 (0.69–5.42) | 0.76 (0.26–2.21) | 0.693 |
Model 3 f | 1.00 | 1.92 (0.60–6.09) | 0.83 (0.26–2.64) | 0.834 |
Women |
n | 47 | 55 | 51 | |
Crude | 1.00 | 0.82 (0.29–2.28) | 0.35 (0.10–1.25) | 0.113 |
Model 1 e | 1.00 | 0.72 (0.25–2.04) | 0.03 (0.22–0.05) | 0.037 |
Model 2 c | 1.00 | 0.78 (0.25–2.36) | 0.20 (0.04–0.91) | 0.039 |
Model 3 f | 1.00 | 1.34 (0.31–5.73) | 0.23 (0.04–1.38) | 0.552 |
Regression coefficients for the association between AHEI-2010 score and components of sarcopenia are presented in Table
5. Both in crude and in adjusted models, we failed to find a significant association between adherence to AHEI-2010 and muscle mass, hand grip strength and gait speed.
Table 5
Linear regression analysis of the association between Alternative Healthy Eating Index and components of sarcopenia
Muscle mass [ASM/h2] C | 0.019 | −0.118, 0.155 | 0.78 | 0.016 | | 0.069 | −0.044, 0.182 | 0.23 | 0.586 | | 0.061 | −0.053, 0.175 | 0.29 | 0.603 | | 0.050 | − 0.022, 0.123 | 0.173 | 0.862 |
Hand grip strength | −0.119 | − 0.610, 0.372 | 0.63 | 0.028 | | 0.149 | −0.180, 0.477 | 0.37 | 0.756 | | 0.174 | −0.155, 0.503 | 0.29 | 0.767 | | −0.023 | −0.085, 0.040 | 0.475 | 0.379 |
Gait speed | −0.018 | −0.048, 0.013 | 0.25 | 0.066 | | −0.011 | −0.041, 0.018 | 0.45 | 0.337 | | −0.013 | −0.042, 0.016 | 0.371 | 0.421 | | 0.001 | −0.065, 0.067 | 0.982 | 0.365 |
Table
6 shows Pearson correlation coefficients (r) AHEI score and components of sarcopenia. No significant correlation was found between AHEI and Muscle mass, Hand grip strength and Gait speed.
Table 6
Association between Alternative Healthy Eating Index and components of sarcopenia a
Muscle mass [ASM/h2] b | −0.078 | 0.17 |
Hand grip strength | 0.008 | 0.89 |
Gait speed | 0.01 | 0.86 |
Discussion
In this cross-sectional study, we failed to find a significant association between adherence to AHEI-2010 and odds of sarcopenia in older adults, even after adjustment for potential confounders. Following sex-stratified analysis, we found a significant relationship between AHEI-2010 and odds of EWGSOP-sarcopenia among women, such that; women in the top tertile of AHEI-2010 score have lower risk of EWGSOP-sarcopenia compared to those in the bottom tertile. To the best of our knowledge, this is the first study investigating the association between AHEI-2010 and sarcopenia.
Sarcopenia is linked to adverse health related outcomes, including fall, fracture and mortality [
3,
4]. Sarcopenia and its components were strongly linked to nutritional status [
32]. In addition, body composition, for instance high body fat percentage, was significantly associated with poor health-related quality of life that can in turn result in sarcopenia [
33,
34]. Based on observational studies, adhering to AHEI-2010 is associated with a lower risk of all-cause mortality, cardiovascular disease, cancer and type 2 diabetes mellitus [
15]. However, there is no evidence on the link between AHEI-2010 and risk of sarcopenia risk. A cross-sectional study on 14,585 individuals aged ≥65 years indicated that increased consumption of fruits was associated with a reduced risk of sarcopenia in women, but not in men. However, vegetables consumption was related to a lower risk in either gender [
9]. Dietary salt intake [
35] and sugar-sweetened drinks [
36] were also associated with elevated risk of sarcopenia in earlier investigations. Examining the relationship between healthy dietary patterns, similar to what AHEI-2010 reflects, and risk of sarcopenia demonstrated that such dietary patterns were associated with a lower risk of sarcopenia. For instance, Chan et al. reported that higher Diet Quality Index-International (DQI-I), “vegetables-fruits” dietary pattern score, and also greater scores of “snacks-drinks-milk products” dietary pattern [
37] and Mediterranean diet were associated with a lower risk of sarcopenia [
38]. Esmaeily et al. [
18] reported that adhering to the HEI-2015 might improve muscle strength in aging individuals. It must be taken into account that muscle strength is only one component of sarcopenia and the association with that index might not indicate the relationship of HEI with sarcopenia. In addition to having a larger sample size in the current study compared with that in Esmaeily et al. (300 vs. 201), we used DXA scanner to calculate ASM. In addition, lack of controlling for BMI in that study as one of the key variables affecting sarcopenia might further confine the interpretation of their findings. In opposite to above-mentioned studies, in the Newcastle cohort study performed on 757 individuals, a positive association was seen between a “traditional British” dietary pattern- high in butter, red meat, gravy and potato intake -and sarcopenia [
39]. In addition, no significant association was found between adherence to the DASH-style diet, a healthy dietary pattern, and odds of sarcopenia in our previous analysis on this population [
24]. Different findings between studies might be arisen from differences in scoring methods as well as components of dietary patterns they used. For instance, when we applied AHEI-2010, rather than DASH scoring in our previous study [
24], in the same population, we found a significant protective association among women. We believe that accurate assessment between healthy eating and risk of sarcopenia should be done by the application of locally-designed scoring methods to reflect healthy eating in each region separately. Developing such local indices based on diet-disease associations in different parts of the world should be a priority for nutrition investigators.
The gender-discrepant findings in the current study may be related to differences in physical activity levels, testosterone and body fat levels between men and women [
34,
40]. However, this finding became non-significant after additionally adjusting for BMI, which can further highlight the importance of body composition across genders in this association. Previous investigations showed that testosterone may augment the benefit of low-intensity physical training on skeletal muscle mitochondrial function in elderly male mice [
41].
Although the exact mechanisms through which healthy diets might affect the risk of sarcopenia is poorly understood, there are some hypotheses in this regard. First is lowered levels of oxidative stress through consumption of these diets [
42,
43]. Oxidative stress can in turn increase the gene expression of inflammatory cytokines such as interleukin-1 (IL-1), tumor necrosis factor (TNF), and IL-6 and consequently damaged muscle tissue [
44,
45]. Also, reduction of SFAs was associated with a lower risk of sarcopenia [
43]. Second is the low content of salt in healthy eating patterns, which is inversely associated with fat accumulation and muscle weakness and consequently sarcopenia [
35]. However, in our previous study on this population about DASH diet [
24], which is a sodium restricted diet, we did not find a significant relationship with sarcopenia. Therefore, it seems that other mechanisms might play a role in this regard. Some possible reasons might explain lack of clear association between AHEI-2010 and risk of sarcopenia in the current analysis. In addition to the cross-sectional design of the study which might help explaining this, alcohol intake and trans-fat intake as two main components of AHEI-2010 were not included in this study. These components may have concealed the protective association between AHEI-2010 and risk of sarcopenia. Furthermore, the protective association between dairy consumption and risk of sarcopenia was reported in earlier studies [
46], while dairy intake was not included in the scoring of AHEI-2010. In the current population, compared to those in the bottom tertile, individuals in the top tertile of AHEI-2010 had higher intakes of dairy products (
P = 0.02). This might also affect our findings.
This study has several major strengths. Although the links between healthy eating and sarcopenia were investigated previously, to our knowledge, this is the first study evaluating the association between AHEI-2010 and odds of sarcopenia and its components. Several potential confounders were adjusted in the current analysis. Additionally, a validated FFQ was used to evaluate dietary intakes. However, some limitations should also be considered. Causality cannot be inferred due to cross-sectional design. Some components of AHEI-2010 such as trans-fats and alcohol consumption were not included in the AHEI-2010 score due to lack of data. Also, the index does not evaluate animal protein sources (such as fish) except red meat. Furthermore, dairy consumption was not included in the scoring method of AHEI-2010, which might further affect the associations. The study was performed on a small sample from a limited area where the DEXA device was located, because of financial limitations and insufficient access to the DEXA device in Tehran (maximum 300 cases). Accordingly, the generalizability of these results should be done cautiously. It should be kept in mind that our study population were relatively young (300 subjects aged > 55 years old) which might further explain lack of finding a significant association.
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