Major dietary patterns in relation to muscle strength status among middle‐aged people: A cross‐sectional study within the RaNCD cohort

Abstract Grip strength in midlife can predict physical disability in senior years. Recent evidence shows the critical role of nutritional status on muscle function. We aimed to elucidate whether adherence to a particular dietary pattern would be associated with abnormal muscle strength among middle‐aged people. In this cross‐sectional study, a semiquantitative Food Frequency Questionnaire was used to assess the dietary intake of 2781 participants in the Ravansar Non‐Communicable Chronic Disease (RaNCD) cohort. Major dietary patterns from 28 main food groups were extracted using principal component analysis. Binary logistic regression was used to determine the association between the tertiles of the major dietary patterns and muscle strength status. Two major dietary patterns were identified: the “mixed dietary pattern” that heavily loaded with fruits, vegetables, nuts, dairies, sweets, legumes, dried fruits, fish, red meat, butter, whole grains, natural juices, poultry, pickles, olive, industrial juice, egg, processed meat, and snacks and “unhealthy dietary pattern” that heavily loaded by fats, sugar, refined grains, soft drink, salt, organ meat, tea, and coffee. Adherence to the mixed dietary pattern (OR = 1.03, 95% CI = 0.8–1.33, P for trend = 0.77) and the unhealthy dietary pattern (OR = 1.01, 95% CI = 0.79–0.13, P for trend = 0.89) did not associate with abnormal muscle strength. This study suggests that the dietary pattern involving the consumption of healthy and unhealthy food does not have an effect on muscle strength in middle‐aged adults.


| INTRODUC TI ON
Handgrip strength (HGS) is a good predictor of general health, nutritional status, physical disability, muscle loss, and morbidity (Gallup et al., 2007); thus, a strong HGS in midlife can indicate the capacity to prevent illness and reduce physical disability and aging-related outcomes in future (Rantanen et al., 2000). HGS has shown prognostic utility in the assessment of aging-related outcomes (Lawman et al., 2016). After 30, aging leads to an approximately 1% decline in muscle mass for each year (Kim & Choi, 2013). Aging after middle age causes a change in the body composition, which involves reducing muscle mass and increasing body fat mass. The main concern about aging is loss of muscle mass that leads to physical inability and mortality (Houston et al., 2008). Sarcopenia is a syndrome characterized by the progressive loss of the entire muscle and muscle strength with complications of physical inability, poor quality of life and death. The reasons for the onset and progression of sarcopenia are the inadequate food intake, inhibition of absorption, inactivity and endocrine disorders such as insulin resistance (Baumgartner et al., 1998;Cruz-Jentoft et al., 2010;Morley et al., 2001).
Nutritional status is an important factor in body's health and its role as a determinative factor for chronic diseases has been proven (Organization, 2002). Nutrition plays an important role in maintaining muscle performance, muscle strength and decreasing rate of age-related skeletal muscle mass loss, so that optimizing diet and nutrition throughout life can be a key for preventing sarcopenia and enhancing physical fitness (Robinson et al., 2012). Robert et al. in the Framingham Offspring Cohort study indicated that higher consumption of protein can play a protective role in reducing grip strength (McLean et al., 2015). Sian et al. showed that high consumption of fatty fish can improve grip strength in older men and women (Robinson et al., 2008). A prospective study revealed that vitamin D can play an important role in preserving muscle mass and performance (Scott et al., 2010). Richard et al. in their cross-sectional study indicated that high levels of beta-carotene and vitamin E can help increase muscle strength (Semba et al., 2003). The result of InCHIANTI study showed that high level concentration of magnesium influence on muscle performance such as grip strength in older adult (Dominguez et al., 2006a).
Since consumed foods are a combination of nutrients and nonnutrients, it is better to investigate the dietary patterns individually rather than nutrients alone for identification of diet-disease relationships (Esmaillzadeh et al., 2007b). Some studies showed that healthy or prudent dietary patterns were positively associated with muscle strength (Lee, 2020;Zhang et al., 2020). However, other study indicated that subjects with unhealthy dietary patterns had a significantly lower muscle strength (Granic et al., 2016;Kang et al., 2020).
Due to no studies conducted on Iranian population, we examined the association between adherence to each dietary pattern and odds of abnormal muscle strength.

| Study population
The current cross-sectional study was carried on data from participants in Ravansar Non-Communicable Chronic Disease (RaNCD) study. We use from following formula for estimation of the sample size in cross-sectional study.
According to Hashemi, R study, Z 1α/2 = 1.96 for 95% standard, Z 1-B = 1.28, µ 1 = 76.6 ± 2.7, µ 2 = 73.9 ± 2.5. N = 20 is the minimum number of sample size for each dietary pattern, we estimated at least 3 dietary pattern to result in this population, since the current crosssectional study was carried on data from participants in Ravansar

| Assessment of dietary intake
A semiquantitative 125-item Food Frequency Questionnaire (FFQ) was used to assess dietary intake over a year. The FFQ includes a list of food with standard service sizes consumed by Iranian population (Esmaillzadeh et al., 2007c;Mirmiran et al., 2009 (Azar & Sarkisian, 1980).

Dietary intake was excluded in the final analysis if the energy intake
was not within the normal range (800-4200 kcal/day).

| Assessment of physical activity
Physical activity levels were evaluated by the International Physical Activity Questionnaire (IPAQ), which included questions about intense, moderate and low-level physical activity in the 7-day period.
The reliability and validity of this questionnaire was confirmed previously in the Iranian population (Vasheghani-Farahani et al., 2011).
According to the IPAQ, each person's physical activity is reported based on the metabolic equivalent (MET h/week) (Committee, 2005), each all of the questionnaires were completed by trained dietitians in face-to-face interview. Physical activity lower than 7.5 MET hours per week equals to low, physical activity ≥7.5 MET hours per week <21, equals to normal or moderate, and physical activity ≥21 MET hours per week equals to high physical activity.

| Assessment of muscle strength
The muscle strength was measured by the handgrip test with the use of a digital dynamometer (model SH5003, Seahan Co, South Korea).
The handgrip strength was taken with right/dominant hand when the participant was sitting and the elbow was at 90° of flexion. The participants were asked to squeeze the handle with maximal effort for 10 s. The measurement was repeated after 30 s and the latter was recorded as hand grip strength. We used the cut-off points for muscle strength suggested in Lauretani study (Lauretani et al., 2003) in which muscle strength lower than 20 kg for women and lower than 30 kg for men considered abnormal muscle strength.

| Statistical analysis
All data were analyzed with the use of the SPSS software version 16 (SPSS Inc., Chicago, IL, USA). Factor analysis was used to identify dietary patterns. Food items in the FFQ were categorized into 28 main food groups based on the similarity of nutrient profiles or culinary usage (Table 1). We used the Kaiser-Meyer-Olkin (KMO) and Bartlett's sphericity test to evaluate the adequacy of the intercorrelation between food groups for the factor analysis. The number of retained dietary patterns was decided by the Eigenvalue of more than 1 and the shape of the scree plot and then Varimax rotation was run to create a simple and distinct matrix for preferable explanation and uncorrelated dietary patterns. The scores of each dietary pattern was determined by summing the intake of food groups weighted by factor loading of these food groups for each pattern. The main components of each dietary pattern were determined according to the rotated factor loading (absolute) more than 0.2 ( Table 2). The positive factor loading in each pattern indicates a direct relation with pattern and a negative factor loading indicates an inverse relation with pattern.
To assess the normality assumption, the Kolmogorov-Smirnov test was used. We used the one-way analysis of variance (ANOVA) to assess the significance of difference for continuous variable and

| RE SULTS
The present study included data from 2781 healthy men and women.
Demographic characteristics, anthropometric parameters and muscle strength of the participants are shown in Table 3

| D ISCUSS I ON
This study, to the best of our knowledge, is the first study to assess the relation between adherence to the certain dietary patterns and mus-   Our findings did not show the significant association between major dietary patterns and abnormal muscle strength.
Based on the previous studies, inflammation is associated with muscle wasting and sarcopenia (Allen, 2017;Jensen, 2008;Schaap et al., 2006). Inflammation causes an imbalance between protein synthesis and catabolism (Jo et al., 2012). In this study, the mixed dietary pattern included a collection of healthy foods such as fruits, vegetables, nuts, olive, fish, natural juices, and whole grain and unhealthy foods such as red meat, processed meat, snacks, butter, high fat dairy product, and pickles. Other studies described the role of healthy foods in improving muscle strength and performance by reducing inflammation (Berendsen et al., 2013). Robinson et al. reported that fish and nut consumption can improve muscle function in older adult by possible anti-inflammatory role of n-3 fatty acid (Robinson et al., 2008). A prospective study reported that nut consumption was associated with lower risk of physical dysfunction  Abnormal muscle strength cases, n 549 Note: Muscle strength lower than 20 kg for women and lower than 30 kg for men considered abnormal muscle strength. Data are reported as mean ± standard deviation or percentage as appropriate.
*Adjusted for total energy intake. and prevent sarcopenia (Millward, 2012). Also, in line with these findings, it was reported that 5 serving/day fruits and vegetables consumption compared with 2 serving/day leads to increased grip strength in older adults (Wu et al., 2004). In a cross-sectional study, high fruit and vegetable intake was inversely associated with sarcopenia in older adults (Kim et al., 2015). Also, in the Hertfordshire cohort study, higher fruit consumption in older men and higher fruit and vegetable consumption in older women was associated with higher grip strength (Robinson et al., 2008). Fruits and vegetable are sources of antioxidants such as vitamin C and carotenoids (Wu et al., 2004). These compounds can prevent muscle catabolism by reducing oxidative stress (Doria et al., 2012). Carotenoids play a protective role in keeping the muscle strength by scavenging free radicals, suppressing singlet oxygen and preventing lipid peroxidation (Young et al., 2004). Vitamin C can play a protective role in muscle strength both directly by interacting with superoxide and hydroxylfree radical (Rose & Bode, 1993), and indirectly by reducing vitamin E radicals (Chan, 1993). Several studies indicated that high whole grain intake has been accompanied with reduced inflammation and oxidative stress (Hoffmann et al., 2004;Jang et al., 2001;Schulze et al., 2005). Whole grains contain compounds that can play an antioxidant role and reduce inflammation damage through mechanisms such as cell cycle control, protein chaperoning and repair, DNA stabilization, and elimination of reactive molecular species and induction of detoxification mechanisms (Blomhoff, 2005;Gutteridge & Halliwell, 2000). On the other hand, unhealthy foods can lead to increased inflammation (Chan, 1993). Esmaillzadeh et al. reported that the western dietary pattern characterized with high consumption of unhealthy foods is associated with inflammatory factors (Esmaillzadeh et al., 2007a). Another study by Garcia at al. indicated that there was a positive relation between western dietary pattern and inflammation (Lopez-Garcia et al., 2004). Due to high content of fat, especially saturated fatty acids in red and processed meat, their high consumption could be associated with inflammation (Meyer et al., 2011). A dietary pattern with high loading fats, oils, processed food, fried potatoes, salty snacks, and deserts play a role in inflammation etiology (Nettleton et al., 2006). Therefore, our findings might be attributable to neutralizing the anti-inflammatory effects of healthy foods by the inflammatory effects of unhealthy foods in the mixed dietary pattern.
We also did not find any association between the unhealthy dietary pattern and abnormal muscle strength. This finding is unexpected because this dietary pattern included higher level of consumption of saturated fats, sugars, refined grains, soft drink, salt, and organ meat. Several studies reported that consumption of saturated fat could induce inflammation (Fung et al., 2001;Kennedy et al., 2009;King et al., 2003). Masters et al. reported that refined grain consumption is associated with inflammation (Budui et al., 2015;Masters et al., 2010). Dietary pattern with high consumption of refined grains, sugar, and saturated and trans fatty acids may induce inflammation (Giugliano et al., 2006 Note: Data are reported as mean ± standard deviation or percentage as appropriate. p Values were calculated using ANOVA test for quantitative variables and chi-square test for qualitative variables. Abbreviations: MET, Metabolic Equivalent; PA, Physical Activity. meat could increase inflammatory markers (Schulze et al., 2005).
The possible reasons for lack of association between unhealthy pattern and abnormal muscle strength could be high consumption of tea and coffee, whose role was reported in other studies in reducing the inflammation (Andersen et al., 2006;Hamer, 2007;Kempf et al., 2010;Steptoe et al., 2007), and reducing the odds ratio of sarcopenia by muscle protection (Guo et al., 2014;Jang et al., 2018;Kim et al., 2013aKim et al., , 2013b. We also examined the association between dietary patterns and BMI, muscle mass, fat mass and muscle strength by comparing the average level of those in tertiles of each dietary pattern. Compared with those in the lowest tertile of mixed diet, those in highest tertile had lower BMI and muscle mass. This can be due to less energy and protein intake in the highest tertile compared with lowest tertile. There are several limitations in this study; first, dietary patterns were extracted based on FFQ. FFQ is considered the most appropriate collection tool for dietary data in large epidemiological studies, but estimating the food intake by FFQ might be inaccurate (Hu, 2002;Khani et al., 2004). Second, because this study uses cross-sectional design, it is not possible to infer causality. Third, the results of analyzing dietary patterns are dependent on the studied population, therefore, one may observe significant differences in dietary pattern according to geographical area, race and culture. Fourth, in the factor analysis, the researcher's theoretical or optional decisions for food grouping and their naming can affect the results (Martinez et al., 1998). Fifth, in this study, dietary pattern was assessed based on participants' dietary intake and the participants' dietary behaviors such as pattern, time and number of snack and meals were not investigated.
In conclusion, we found no association between abnormal muscle strength and dietary pattern with combined characteristics of healthy and unhealthy foods among the Iranian middle-aged men and women. It is suggested to conduct well-design cohort study to clarify the association of different dietary habits and muscle strength as well as sarcopenia.

ACK N OWLED G M ENTS
The authors of this article would like to thank the Research Council of Kermanshah University of Medical Sciences for the financial support of this research. This work was performed in partial fulfillment of the requirements for MSc in Nutrition. We also sincerely appreciate all those who have trusted us and participated in this study. Muscle mass, kg 1.1 ± 9.6 1.1 ± 9.4 1.1 ± 9.5 .01 1.1 ± 9.5 1.2 ± 9.6 1.2 ± 9.5 .08 Fat mass, kg 4 ± 9.9 3.9 ± 9.7 3.8 ± 9.5 .19 3.8 ± 9.6 3.9 ± 9.8 4 ± 9.7 .79 Hand F I G U R E 1 Odds ratios (95% CI)* for abnormal muscle strength across tertiles (T) of dietary pattern scores. Odds ratios (95% CI) were obtained using binary logistic regression. *Adjusted for sex, age, education level, economical status, physical activity, and energy intake. Hosmer-Lemeshow Χ 2 (8) = 11.70. Prob > Χ 2 = 0.1650

CO N FLI C T O F I NTE R E S T
The authors have declared no conflict of interest.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.