China is facing the rapid ageing of its population: the total number of older people reached ~176 million (~13 % of the entire population) in 2019(Reference Yang, Wu and Tan1). ‘Biological ageing’ is the gradual loss of physiological integrity. Almost every organ in the human body is affected by the detrimental effects of ageing, including skeletal muscle(Reference Nelke, Dziewas and Minnerup2). The mass and function of skeletal muscle decline with ageing(Reference Dodds, Syddall and Cooper3). Age-related decrease of the mass and function of skeletal muscle(Reference McGregor, Cameron-Smith and Poppitt4) leads to physical fitness decline in older people. This phenomenon is manifested as an increase in the prevalence of osteoporosis, sarcopenia and frailty(Reference Yoo and Park5–Reference Pan, Li and Wang7) and can be followed by falls, delirium, fractures and increased medical burden(Reference Clegg, Young and Iliffe8,Reference Xia, Cooper and Li9) . Therefore, maintenance of good physical fitness for older people can aid avoidance of adverse outcomes. Early detection and treatment of physical decline has a crucial role in preventing or delaying the onset of physical disability(Reference Rikli and Jones10).
A balanced diet and good physical fitness are the keys to healthy ageing, and they are closely related. Studies have suggested that diet is a major factor affecting muscle mass(Reference Jang and Bu11) and muscle function(Reference Granic, Sayer and Robinson12). Healthy eating habits may contribute to increased skeletal muscle mass and help maintain good function(Reference Jang and Bu11,Reference Granic, Sayer and Robinson12) .
Tests of physical fitness can be used to evaluate several abilities (e.g., lower and upper body strength, aerobic endurance and motor agility/dynamic balance) objectively, which support the behaviours necessary to undertake everyday activities. Several studies have explored the association between food nutrients and physical fitness(Reference Aparicio-Ugarriza, Luzardo-Socorro and Palacios13), including protein, dietary fibre, vitamin D and some antioxidants(Reference Fanelli Kuczmarski, Pohlig and Stave Shupe14–Reference Passerieux, Hayot and Jaussent17). The daily diet is often a combination of various foods, and there are often complex interactions between foods and nutrients(Reference Hu18). Therefore, a food-based dietary pattern is better than nutrients in analysing the association between overall diet and physical fitness. Some studies have also explored this association. Close adherence to the ‘Mediterranean diet’ is associated with better physical fitness, whereas a Western dietary pattern may contribute to frailty(Reference Fougere, Mazzuco and Spagnolo19,Reference Bibiloni, Julibert and Argelich20) . One study based on an Asian population showed that a better overall quality of the diet may be associated with improved physical fitness(Reference Jeong, Kim and Park21). However, dietary structures among countries are quite different, and few studies have demonstrated this association among older people in China.
We analysed the dietary patterns and tested the physical fitness of older people residing in Liaocheng City (Shandong Province, China). In particular, we investigated the association between dietary patterns and physical fitness to explore a practicable dietary pattern to maintain better physical fitness and improve health and well-being in older Chinese people.
Methods
Study population
The individuals in the current study were from Shandong Province and part of the Formative Health Assessment Instrument and Parameters for the Elderly project. This is a cross-sectional study carried out across China since 2015. It includes assessment instruments and parameters for physical fitness, mental health, social health, diet and nutrition health, and chronic diseases in older people. The goal of this project is to create a national ‘healthy ageing’ strategy that helps to decrease the prevalence of chronic non-communicable diseases and slows down the loss of skeletal muscle function.
Using cluster sampling, six communities were selected from the urban, suburban and rural areas in Liaocheng City from April to May 2017. The exclusion criteria were age <60 years, suffering from severe mental illness, chronic disease or limitation of daily activities which would restrict responses to questionnaires or completion of physical fitness tests. Finally, 596 participants were recruited: 214 men (36 %) and 382 women (64 %) aged 60–93 years.
Covariate assessment and anthropometric measurement
Participants were required to complete a questionnaire during a face-to-face interview. The questionnaire contained information on age, sex, residential area, occupation, marital status, education level, income and medical history of 28 diseases (e.g., high blood pressure, CHD and diabetes mellitus). Height measurement was corrected to 0·1 cm and weight measurement was corrected to 0·1 kg. We used the International Physical Activity Questionnaire Short Form to evaluate physical activity, and its reliability and validity have been evaluated in the Chinese population(Reference Macfarlane, Lee and Ho22). According to Gao and colleagues, the question of frequency and duration of low physical activity were supplemented(Reference Gao23).
Assessment of dietary intake
Information on dietary intake was measured using a simplified semi-quantitative FFQ, which has been tested for reliability and validity in a population of older Chinese people(Reference Gao, Fei and Jiang24). Participants were asked by trained investigators to recall average consumption per serving for each food item and eating times over the previous year. The frequency of consumption was divided into five categories: ‘never or seldom’, ‘per day’, ‘per week’, ‘per month’ or ‘per year’. According to the Chinese Food Composition Table(Reference Yang, Wang and Pan25), the food items in the questionnaire were divided into 14 groups (refined cereals, coarse cereals, potatoes, mixed beans, vegetables, fruits, red meat, poultry, fish/sea food, eggs, dairy products, soyabeans, nuts and alcoholic beverages). We calculated the amount consumed (g/d) of each group and energy intake. We excluded people whose energy intake <2510·4 KJ or >16 736·0 KJ or individuals whose food intake exceeded the mean plus 6 sd. The final number of participants evaluated was 556.
Test of physical fitness
Assessment of physical fitness was based on four tests: 30-s Chair Stand test (30sCST), 30-s Arm Curl test (30sACT), 8-foot Time Up-and-Go test (8fTUAGT) and 6-min Walking test (6mWT)(Reference Rikli and Jones26).
The 30sCST assesses lower body strength. Each participant sat in the middle of a chair with his/her feet separated, and arms folded cross the chest. The investigator recorded the number of times the participant stood up and then sat down within 30 s.
The 30sACT assesses upper body strength. The participant sat on a chair holding a hand weight (women, 2·3 kg; men, 3·6 kg), with the other arm close to the body. The investigator recorded the number of bicep curls within 30 s. Both arms were tested, and the one with the higher number of bicep curls was documented.
The 8fTUAGT assesses agility/dynamic balance. Each participant was required to arise from a seated position without the use of arms, walk around a landmark placed 2·45 m from the chair and then return to the original sitting position. The investigator recorded the time spent on the 8fTUAGT.
The 6mWT assesses aerobic endurance. Each participant was in the standing posture and walked at his/her usual pace along a prescribed route. The investigator recorded the walking distance within 6 min.
Test results were divided into four quartiles according to sex or age (<70 or ≥70 years). The fourth quartile (Q4) was defined as the ‘high-level group’, and the other three quartiles were defined as the ‘low-level group’(Reference Rikli and Jones10).
Statistical analyses
Continuous variables are presented as the mean and sd. Categorical variables are expressed as sums and percentages. According to the classification of variables, the differences between men and women were compared using the Student’s t-test or χ 2 test, and the differences among quartile categories of dietary patterns were compared using ANOVA or χ 2 test. Principal component analysis was employed to identify dietary patterns and determine factor loadings for consumed amounts (g/d) of the 14 food groups. The Kaiser–Meyer–Olkin test and Bartlett’s test of sphericity were used to evaluate whether the correlation matrix was suitable for factor analysis. The varimax rotation function was used to obtain a simple correlation matrix. The factor score coefficients were estimated by the regression method. Factor scores were used to represent the dietary pattern for each participant, and a higher factor score indicated higher adherence to a dietary pattern. Scores for dietary patterns were categorised into quantiles. Q1 was considered as the reference (‘low adherence’) and Q4 denoted ‘high adherence’. OR and 95 % CI were calculated. Multiple logistic regression was used to examine the possible association between physical fitness and adherence to each dietary pattern after adjustment for potential confounders (age, sex, BMI, physical activity, energy intake, total number of diseases, residential area, occupation, marital status, education level and income). Analyses were undertaken using SPSS v21·0 (IBM). P < 0·05 was considered significant.
Results
Among 556 participants, 196 (35 %) were men and the mean age was 69·3 ± 6·4 years; 360 (65 %) were women and the mean age was 69·5 ± 6·2 years. The energy intake of men was higher than that of women, and men had fewer diseases than women. Marital status (P < 0·001) and education level (P < 0·001) between sexes were significantly different. 6mWT results showed that men walked further than women in 6 min (P < 0·001) (Table 1). Characteristics of participants by quartile categories of three dietary patterns are shown in online supplementary material, Supplemental Table 1.
Table 1 Characteristics of male and female participants in the current study*
MET, metabolic equivalents.
* Continuous variables are presented as the mean and sd, and categorical variables are presented as sums and percentages.
† Student’s t-test for continuous variables and χ 2 test for categorical variables.
Statistical analyses showed that Kaiser–Meyer–Olkin = 0·65 and that P < 0·05 for Bartlett’s test(Reference Castro, Baltar and Selem27). Three factors of eigenvalue >1·0 were selected and accounted for 34·4 % of the total variance. Food groups with a factor loading ≥0·35 on a dietary pattern were considered to be substantial contributors to the dietary pattern (Table 2).
Table 2 Dietary patterns and factor loading matrix of older adults*
* Absolute values <0·20 were excluded for simplicity, absolute values ≥0·35 are emboldened.
The first pattern (named ‘Western’) was characterised by a high intake of red meat, alcoholic beverages, refined cereals, eggs, poultry and fish/sea food. The second pattern (named ‘Vegetarian’) was directly associated with consumption of coarse cereals, mixed beans, vegetables and soyabeans. The third pattern (named ‘Modern’) was associated with a high intake of dairy products, nuts and fruits.
The association between dietary patterns and physical fitness (according to quartiles of dietary pattern scores) stratified by sex is provided in online supplementary material, Supplemental Table 2. Table 3 shows the OR of Q4 v. Q1. We adjusted according to age, BMI, physical activity, energy intake and total number of diseases. For the 30sACT, logistic regression showed that participants (men) with higher adherence to a Western pattern (Q4 v. Q1) were less likely to be classified in the high-level group (OR = 0·21, 95 % CI = 0·06, 0·74), thereby reflecting worse upper body strength. Participants with higher adherence to the Vegetarian pattern (men) or Modern pattern (women) were more likely to appear in the high-level group (OR = 3·51, 95 % CI = 1·10, 11·19 and OR = 2·33, 95 % CI = 1·10, 4·93, respectively), thereby reflecting better upper body strength. For the 6mWT, participants with higher adherence to the Modern pattern (men) were more likely to be classified in the high-level group (OR = 3·02, 95 % CI = 1·09, 8·37), thereby reflecting better aerobic endurance. After further controlling for residential area, occupation, marital status, education level and income, the association remained significant in men but not in women.
Table 3 Association between physical fitness and adherence to three dietary patterns among male and female participants*
WP, Western pattern; VP, Vegetarian pattern; MP, Modern pattern.
* Factor scores of each dietary pattern were categorised into quantiles. Q1: lowest quartile of dietary patterns. Q4: highest quartile of dietary patterns. Q4 v. Q1 (reference).
† Model 1 was adjusted for age, BMI, physical activity, energy intake and total number of diseases.
‡ Model 2 was adjusted for age, BMI, physical activity, energy intake, total number of diseases, residential area, occupation, marital status, education level and income.
The results of the analysis by age group are shown in online supplementary material, Supplemental Table 3. All 556 participants were divided into two groups: group 1 (age <70 years) and group 2 (age ≥70 years). Compared with participants in Q1 of the Western pattern, participants in Q4 were less likely to be classified in the high-level group for the 30sACT (group 1) and 8fTUAGT (group 2) after adjustments for age, sex, BMI, physical activity, energy intake and total number of diseases, thereby reflecting worse upper body strength and agility/dynamic balance. However, after further controlling for confounding factors, this association ceased to be significant.
Discussion
We observed three dietary patterns: Western, Vegetarian and Modern. Adherence to the Modern pattern was associated with better aerobic endurance in men and stronger upper body strength in women. Adherence to the Vegetarian pattern was associated with stronger upper body strength in men. In contrast, adherence to the Western pattern was associated with weaker upper body strength in men and younger participants and was associated with worse agility/dynamic balance in older participants.
The Vegetarian pattern (coarse cereals, mixed beans, vegetables, soyabeans and potatoes) and the Modern pattern (dairy products, nuts, fruits, fish/sea food and soyabeans) were beneficial to the physical fitness of the older participants in the current study, and they were similar to other diets that have been reported to be healthy. Such examples include the Mediterranean diet, Nordic diet and other healthy diets of which the common characteristics are a high intake of fish/seafood, fruit, vegetables, nuts, legumes, whole grain/cereal products, dairy and low intake of red meat/meat products(Reference Bibiloni, Julibert and Argelich20,Reference Perala, von Bonsdorff and Mannisto28,Reference Granic, Jagger and Davies29) .
Studies have shown that healthy dietary patterns have positive effects on physical fitness of older people. A cross-sectional study conducted among older adults in Spain showed that the Mediterranean pattern was associated with faster gait speed in men(Reference Bibiloni, Julibert and Argelich20). Based on several cohort studies(Reference Perala, von Bonsdorff and Mannisto28–Reference Shahar, Houston and Hue30), participants with higher adherence to the Mediterranean diet at baseline have faster walking speed over 8 years(Reference Shahar, Houston and Hue30). Perala and colleagues showed that the Nordic diet helped older women perform better in the 6mWT, 30sACT and 30sCST, which reflected better aerobic endurance and upper and lower body strength(Reference Perala, von Bonsdorff and Mannisto28). Granic and coworkers showed that participants classified in a ‘Low Meat’ pattern showed overall better performance in the 8fTUAGT in the entire cohort(Reference Granic, Jagger and Davies29). Our results confirmed the findings stated above. Meanwhile, a healthy diet has also been associated with stronger grip strength,(Reference Jeong, Kim and Park21,Reference Barrea, Muscogiuri and Di Somma31–Reference Perala, von Bonsdorff and Mannisto33) which is the most frequently used indicator of muscle functional capacity for clinical purposes (though this indicator was not used in our study). In addition to the muscle strength measured by physical fitness tests, decreased muscle mass in older people (an important symptom of sarcopenia and frailty) is also closely related to skeletal muscle health. A cross-sectional study in South Korea observed that older men with a healthy dietary pattern had higher appendicular muscle mass(Reference Lee and Lee34). Similarly, the results of longitudinal studies have demonstrated that a better quality of diet or adherence to a healthy diet is associated with a lower risk of sarcopenia in older people(Reference Isanejad, Sirola and Mursu35–Reference Chan, Leung and Woo37). The findings of a meta-analysis suggested that a diet high in fruit, vegetables and whole grains may be associated with a reduced risk of frailty(Reference Rondanelli, Rigon and Perna38). Our research did not involve muscle mass but, overall, it is clear that a balanced and healthy diet is essential for the skeletal muscle health of older people. Long-term adherence to a healthy dietary pattern can prevent sarcopenia and frailty.
Several mechanisms could explain the associations observed in the present study. Studies have demonstrated that oxidative damage(Reference Cesari, Pahor and Bartali39) and inflammation(Reference Cesari, Penninx and Pahor40) can lead to poor muscle function in older adults. Appropriate intake of vegetables and fruits rich in antioxidants can maintain healthy muscle activity and have a protective effect on age-related oxidative stress. Diets rich in dietary fibre can lower levels of C-reactive protein, which is associated with inflammation(Reference King, Egan and Woolson41). n-3 PUFA, levels of which are high in some fish and nuts, exert anti-inflammatory effects on muscle function by reducing production of inflammatory mediators and expression of adhesion molecules(Reference Calder42). Furthermore, individuals who have high consumption of dairy products have stronger grip strength and lower body muscle strength(Reference Radavelli-Bagatini, Zhu and Lewis43). Studies have shown that the synthesis and metabolism of protein in muscles in older people are affected by negative changes in the homeostasis of proteins and amino acids. Also, the supply of proteins or amino acids (especially legume proteins) is beneficial to this process(Reference Timmerman and Volpi44). We postulate that Vegetarian (whole cereals, soyabeans, mixed beans and vegetables) and Modern (dairy products, nuts, fruits, soyabeans and fish/sea food) patterns may prevent oxidative damage and inflammation and have the beneficial effects of proteins and, thus, have a positive effect on physical fitness in older people.
Older individuals with high adherence to the Western pattern (as characterised by high consumption of red meat, alcoholic beverages, refined cereals, eggs, poultry and fish/sea food) showed worse upper body strength and agility/dynamic balance. Bibiloni and colleagues observed that the Western dietary pattern was associated with slower gait speed and lower body strength, agility and aerobic endurance and may be a contributor to frailty(Reference Bibiloni, Julibert and Argelich20). Intake of fat and red/processed meat has been shown to be related to increased oxidation as well as inflammation(Reference Calder, Ahluwalia and Brouns45), data which may support our findings. However, studies based on South Korean populations have drawn different conclusions from ours. They found that in metropolitan areas, the group eating more meat (high intakes of beverages and alcohol, eggs, meats, meat products and low intakes of vegetables) had better grip strength because of the adequate intake of protein(Reference Seo, Kim and Park46). In our study, most of the participants came from rural areas with low economic status and education level. Therefore, in addition to the quality of the diet, there may have been other health-related behavioural issues that affected their physical fitness. Dietary patterns are usually closely related to lifestyle, and the Western pattern is related to less healthy behaviours(Reference Leon-Munoz, Garcia-Esquinas and Lopez-Garcia47). Dietary patterns are also associated with obesity, systemic inflammation, CVD, poor cognitive function and depression, all of which may increase the risk of frailty(Reference Leon-Munoz, Garcia-Esquinas and Lopez-Garcia47), and lead to further decline in physical fitness in older people. The impact of healthy behaviours on diet and physical fitness merits further exploration.
In the present study, one of the characteristics of the Western pattern was high intake of fish/seafood, which, in general, is regarded as an optimal food for maintaining muscle mass and preventing sarcopenia(Reference Rondanelli, Rigon and Perna38) and usually denotes a healthy diet(Reference Jang and Bu11,Reference Pilleron, Ajana and Jutand48) . However, dietary pattern represents the overall diet; there may be complex interactions between food. Although the Western dietary pattern contains favourable food factors, the whole Western pattern shows an adverse effect on physical fitness.
Our study had several strengths. Similar studies have been carried out in European populations, but, to our knowledge, this is the first study to focus on the association between dietary patterns and physical fitness among an older Chinese population. In addition, dietary pattern analyses can highlight the impact of the overall diet on physical fitness rather than that of a certain food. Moreover, studies(Reference Granic, Sayer and Robinson12) have mostly used the Short Physical Performance Battery test, walking speed or grip strength to measure physical fitness. Compared with those tests, the physical fitness indicators selected in our study can reflect the overall physical fitness, including upper body strength, lower body strength, agility/dynamic balance and aerobic endurance.
Our study had four main limitations. First, due to its cross-sectional design, we could not ascertain a causal relationship between dietary patterns and physical fitness. Second, the sample size of the current study was small (especially for males). This small size hampered use of more age groups when carrying out subgroup analyses for age, but age is an important factor for the physical fitness in older individuals. Third, urban and rural samples were distributed unevenly, and all participants came from Shandong Province, so the results may not be a good representation for all older people from China. Fourth, even though we adjusted for possible confounding factors, such as physical activity, energy intake and socio-demographic characteristics, we could not control the residual confounding or effect modifications caused by other unmeasured covariates. Further studies need to be continued in other provinces in China, and more attention should be paid to the balance of sex and region of residence of participants.
Conclusions
Our study indicated that the Modern pattern was associated with better aerobic endurance and stronger upper body strength, the Vegetarian pattern was associated with stronger upper body strength and the Western pattern was associated with weaker upper body strength and worse agility/dynamic balance. Adherence to a dietary pattern characterised by high consumption of coarse cereals, mixed beans, vegetables, soyabeans, dairy products, nuts and fish/sea food may be helpful to maintenance of good physical fitness, whereas adherence to the Western dietary pattern may result in poor physical fitness among older adults. Even small improvements in physical fitness can have a considerable impact on the quality of later life, so carrying out dietary health education and physical fitness training for older individuals is needed.
Acknowledgements
Acknowledgements: The authors thank all the elderly who participated in this research for their cooperation. We also thank all the researchers and investigators for their great effort. Financial support: This research was supported by the Ministry of Science and Technology of the People’s Republic of China (2015FY111600). Conflict of interest: All authors have no conflicts of interest. Authorship: X.Y., X.L. and M.D. conceived and designed the research, X.Y., H.Y. and X.D. collected the data, Y.L. performed the statistical analyses and drafted the manuscript and B.W. and X.L. revised the manuscript. Ethics of human subject participation: The current study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving research study participants were approved by the Ethics Committee of the School of Public Health, Shandong University. Written informed consent was obtained from all subjects.
Supplementary material
For supplementary material accompanying this paper visit https://doi.org/10.1017/S136898002000333X
