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Department of Frailty Research, Center for Gerontology and Social Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
Address correspondence to Rei Otsuka, PhD, Department of Epidemiology of Aging, Center for Gerontology and Social Science, Research Institute, National Center for Geriatrics and Gerontology, 7-430 Morioka, Obu, Aichi 474-8511, Japan.
Department of Epidemiology of Aging, Center for Gerontology and Social Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
Department of Epidemiology of Aging, Center for Gerontology and Social Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
Department of Epidemiology of Aging, Center for Gerontology and Social Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
Department of Epidemiology of Aging, Center for Gerontology and Social Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
Department of Epidemiology of Aging, Center for Gerontology and Social Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
Department of Epidemiology of Aging, Center for Gerontology and Social Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, JapanFaculty of Health and Medical Sciences, Aichi Shukutoku University, Nagakute, Aichi, Japan
Department of Epidemiology of Aging, Center for Gerontology and Social Science, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, JapanGraduate School of Nutritional Sciences, Nagoya University of Arts and Sciences, Nissin, Aichi, Japan
The amount of breakfast protein intake is important for maintaining muscle strength. However, the effect of breakfast protein quality (ie, bioavailability) remains unclear. We investigated the association between breakfast protein quality and the incidence of muscle weakness.
Design
Longitudinal study.
Setting and Participants
Healthy older adults age 60–83 years without stroke, arthritis, Parkinson disease, or muscle weakness at baseline (maximum follow-up period and participations were 9.2 years and 5 times, respectively).
Methods
Weakness was defined by the Asian Working Group for Sarcopenia 2019 criteria, using grip strength. Breakfast protein quality was evaluated using the protein digestibility–corrected amino acid score (PDCAAS), where higher scores represent higher quality, calculated from 3-day dietary records. Participants were classified according to sex-stratified tertiles of breakfast PDCAAS (ie, low to high groups). The association between PDCAAS and incident weakness was analyzed using the generalized estimating equation, after adjusting for sex, age, follow-up time, grip strength, body mass index, physical activity, cognition, education, smoking, economics, medical history, lunch and dinner PDCAASs, and energy and protein intake during 3 regular meals at baseline.
Results
Overall, 14.4% of the initial sample was excluded owing to a diagnosis of weakness-related diseases, and 58.3% (n = 701) had at least 1 follow-up measurement for inclusion in the analysis. The mean ± SD follow-up period was 6.9 ± 2.1 years; the cumulative number of participants was 3019, and 282 developed weakness. Using the low PDCAAS group as the reference, the adjusted odds ratios (95% CIs) for incident weakness in the middle and high PDCAAS groups were 0.71 (0.43–1.18) and 0.50 (0.29–0.86), respectively.
Conclusions and Implications
Higher breakfast protein quality was associated with a reduction in incident weakness in older adults, independent of protein intake. These findings may highlight the role of protein quality for muscle health in older adults.
Maintaining functional ability is important for healthy aging; maintaining muscle strength is, therefore, essential. Grip strength is used worldwide as a measure of muscle strength.
Assessment of muscle function and physical performance in daily clinical practice: a position paper endorsed by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO).
It is a predictor of adverse health outcomes such as fractures, extended hospital stays, mobility limitation, disability, and mortality in older people,
Association of grip strength with risk of all-cause mortality, cardiovascular diseases, and cancer in community-dwelling populations: a meta-analysis of prospective cohort studies.
it may be important to consume proteins with higher bioavailability (ie, higher quality proteins). However, the quality of protein varies depending on the food; while egg has a bioavailability of 118%, that of wheat is 42%.
, The amount of protein intake at breakfast should be similar to that at lunch and dinner to promote optimal stimulation of muscle protein synthesis after all meals.
considering quality is important for older people, especially at breakfast. We hypothesized that breakfast with a higher quality of protein could prevent muscle strength decline. To our knowledge, no study has investigated the association between breakfast protein quality and muscle strength in community-dwelling older adults. We, therefore, aimed to investigate the longitudinal association between breakfast protein quality and incidence of low grip strength among older people.
Methods
Study Design and Participants
This study was derived from the National Institute for Longevity Sciences–Longitudinal Study of Aging (NILS-LSA), which was conducted using stratified random sampling by age and sex among community dwellers from Obu City and Higashiura Town in Aichi Prefecture, Japan.
The NILS-LSA has been conducted every 2 years since 1997; participants were 40–79 years old at their first participation. Herein, the third survey of the NILS-LSA (between May 2002 and May 2004, n = 2378) was set as the baseline, because of the British bovine spongiform encephalopathy outbreak that occurred worldwide (including Japan) during the second NILS-LSA survey (between April 2000 and May 2002).
The bovine spongiform encephalopathy outbreak led to decreased meat consumption, the main source of amino acids.
In this study, participants age ≥60 years were considered older adults. At baseline, there were 1202 participants age ≥60 years; 1006 participated in the follow-up survey (4th to 7th survey, up to July 2012) at least once. We excluded those with diseases influencing grip strength (ie, stroke, arthritis, and Parkinson disease, n = 173), without grip strength assessment (n = 9), with low grip strength (as defined later, n = 53), without dietary records (n = 35), who skipped at least 1 of the 3 regular meals (ie, 0 kcal/meal, n = 4), and who had missing covariate data (n = 31); data from 701 participants were finally analyzed (age range, 60-83 years; male, n = 375, 53.5%).
This study was conducted according to the guidelines of the Declaration of Helsinki, and all procedures were approved by the relevant Ethics Committee of Human Research of the National Center for Geriatrics and Gerontology, Japan (No. 1377). Written informed consent was obtained from all the NILS-LSA participants.
Muscle Strength Assessment
To assess muscle strength, hand grip strength (kg) was measured using a handgrip dynamometer (Takei Scientific Instruments) at baseline, and during each follow-up survey.
Grip strength was measured twice for each hand in the standing position; the highest measurement was used for analysis. Low grip strength was defined based on the Asian Working Group for Sarcopenia 2019 criteria, as follows: <28 kg for male and <18 kg for female individuals.
Breakfast intake was assessed at baseline using a 3-day dietary record, including intake data from 2 weekdays and 1 weekend day; sheets for breakfast intake were separate sheets from those used for lunch and dinner. Participants weighed each food item using a kitchen scale before cooking (Sekisui Jushi) and photographed their meals using a disposable camera before and after eating (Fuji Film). Dietitians used these photographs to estimate complete food consumption for missing data from the dietary records and telephoned the participants to resolve any discrepancies or obtain further information. The average dietary intake for breakfast, lunch, and dinner over 3 days was calculated by the dietitians based on the Japanese Standard Tables of Food Composition.
Protein Quality Assessment—Calculation of the PDCAAS
Dietary protein quality (ie, the nutritional value of the amino acids) was evaluated using the protein digestibility–corrected amino acid score (PDCAAS),
The PDCAAS was calculated for each meal (ie, breakfast, lunch, and dinner) and total intake, based on the guidelines of the Food and Agriculture Organization of the United Nations (FAO)/World Health Organization (WHO)/United Nations University (UNU) expert consultation, as follows: PDCAAS = digestibility × amino acid score.
The ratios of these 9 amino acids in the meal are calculated by comparing their requirement patterns; the lowest ratio is defined as the amino acid score.
As diets generally comprise various foods, the WHO/FAO/UNU report indicates the true protein digestibility of some mixed diets for calculating the PDCAAS; it was 96%, 88%, and 96% for the American, Filipino, and Chinese diets, respectively.
The body mass index (kg/m2) was calculated using anthropometric data. The trained staff measured height and weight. Daily total physical activity, measured in metabolic equivalent of tasks (MET-min/d), was assessed during interviews by the staff, using questionnaires regarding activity intensity and frequency over the year.
Cognitive function was assessed by a trained psychologist or psychology graduate students, using the Japanese version of the Mini-Mental State Examination.
Educational years, smoking status, household annual income, and medical history (ie, hypertension, dyslipidemia, diabetes mellitus, and ischemic heart disease) were assessed using self-reported questionnaires. The responses in self-reported questionnaires were confirmed by medical doctors and trained staff. These data were assessed at baseline and used as covariates.
Statistical Analyses
All statistical analyses were performed using the Statistical Analysis System v 9.3 (SAS Institute, Inc). A 2-sided P value of <.05 was considered statistically significant. Continuous variables are presented as means ± SD, and categorical variables are presented as numbers and percentages (%). To analyze the association between breakfast PDCAAS and incidence of low grip strength, we classified participants according to sex-stratified tertiles (T1 to T3) of breakfast PDCAAS. Groups T1, T2, and T3 were defined as the low-, middle-, and high-PDCAAS groups, respectively; the baseline characteristics of the participants in these groups were compared using the general linear model for continuous variables and the χ2 test for categorical variables. Food consumption (g/100 kcal) at breakfast was compared between the 3 PDCAAS groups using the general linear model.
Association between PDCAAS and incident low grip strength was analyzed using the generalized estimating equation (GEE),
which assumes that data is missing completely at random, and can handle the unmeasured dependence of repeated observations within participants. It averages overall subject parameters, and provides a good estimate of within-subject covariance structure. It uses moment assumptions to iteratively select the optimal β to evaluate the relationship between explanatory variables and outcomes, instead of assumption of data generation from a certain distribution. In epidemiologic studies, repeated data is used as it controls for time-invariant unobservable differences between individuals; thus, the GEE is commonly used. Here, the GEE analysis was performed using the GENMOD procedure in SAS. The odds ratios (ORs) and 95% CIs of the middle and high PDCAAS groups for low grip strength were estimated using the GEE, considering the low PDCAAS group as reference. We adjusted for sex, age (year), follow-up time (year), and grip strength (kg) at baseline in model 1. In model 2, body mass index (kg/m2), total physical activity (MET-min/d), Mini-Mental State Examination (score), education (years), smoking status (current or not), household annual income (<3.50 million yen/year, 3.50–6.49 million yen/year, or ≥ 6.50 million yen/year), medical history (ie, hypertension, dyslipidemia, diabetes mellitus, and ischemic heart disease), and PDCAAS values for lunch and dinner (low to high at each meal) at baseline were added to model 1. In model 3, energy (kcal/meal) and protein (g/meal) intake at the 3 regular meals at baseline were added to model 2.
Four types of supplemental analyses were performed. First, to investigate the effect of total daily intake, the GEE was used to evaluate the association between the PDCAAS for total daily intake and low grip strength. Second, to clarify the impact of the PDCAAS for breakfast in participants with insufficient protein intake, its association with low grip strength was evaluated using the GEE, after excluding participants with sufficient protein intake at breakfast (sufficiency was defined as ≥25 g/meal based on recommendations).
Furthermore, to compare the incidence of low grip strength between individuals having high protein intake with low PDCAAS and low protein intake with high PDCAAS, participants were classified into 6 groups by combining median breakfast protein intake (ie, 20 g) and low-to-high PDCAAS. Using the high protein intake with low PDCAAS group as reference, the OR for the incidence of low grip strength was estimated. Third, to exclude selection bias, we compared characteristics between participants included and excluded. Fourth, to consider the effect of newly developed diseases that could influence grip strength during follow-up, we excluded participants who developed stroke, arthritis, and Parkinson disease during follow-up. The ORs and 95% CIs of the middle and high PDCAAS groups for low grip strength were estimated using the low PDCAAS group as the reference.
Results
Table 1 shows the number of participants in each survey, from baseline to follow-up. The mean ± SD follow-up period and number of follow-up visits were 6.9 ± 2.1 years and 3.2 ± 1.1 times, respectively (Supplementary Table 1 shows a comparison of baseline characteristics between participants included in this study and those excluded). Table 2 shows the baseline characteristics of the low, middle, and high PDCAAS groups. Regarding nutritional intake at breakfast, although the protein/energy and fat/energy ratios significantly increased from the low to the high PDCAAS groups, the carbohydrate/energy ratio decreased significantly (P < .001, for both, group differences and trends). Figure 1 shows the food consumption at breakfast in the low to high PDCAAS groups. The consumption of cereal grains, sugars and sweeteners, and fats and oils was significantly higher in the low PDCAAS group; however, the consumption of beans and legumes, fish and seafood, eggs, and milk and dairy products was significantly lower in this group.
Table 1Number of Participants at Each Survey from Baseline to Follow-Up
3.50 million yen = 31804.6 US dollars at July 2021.
82 (34.5)
61 (26.1)
74 (32.3)
.133
3.50–6.49 million yen
84 (35.3)
98 (41.9)
98 (42.8)
≥6.50 million yen
72 (30.3)
75 (32.1)
57 (24.9)
Nutritional intake
Breakfast
Energy, kcal/meal
482.1 ± 151.4
521.9 ± 121.9
561.1 ± 144.1
<.001
<.001
Protein, g/meal
16.7 ± 6.4
20.6 ± 5.7
24.0 ± 7.0
<.001
<.001
Protein/energy ratio, %
13.7 ± 2.7
15.8 ± 2.6
17.1 ± 2.7
<.001
<.001
Fat, g/meal
12.2 ± 7.6
13.8 ± 6.2
16.1 ± 6.6
<.001
<.001
Fat/energy ratio, %
9.8 ± 4.5
10.5 ± 4.0
11.4 ± 3.4
<.001
<.001
Carbohydrate, g/meal
76.3 ± 24.7
78.5 ± 21.8
79.7 ± 23.0
.287
.120
Carbohydrate/energy ratio, %
64.1 ± 11.0
60.2 ± 9.6
56.9 ± 8.5
<.001
<.001
Lunch
Energy, kcal/meal
602.8 ± 154.4
573.1 ± 135.5
589.9 ± 132.0
.073
.324
Protein, g/meal
22.6 ± 7.2
21.8 ± 6.6
23.0 ± 6.7
.199
.556
Protein/energy ratio, %
15.0 ± 2.9
15.3 ± 3.1
15.6 ± 3.2
.088
.028
Fat, g/meal
14.9 ± 5.9
13.8 ± 6.2
15.1 ± 6.3
.041
.712
Fat/energy ratio, %
9.8 ± 2.8
9.4 ± 3.3
10.2 ± 3.3
.050
.252
Carbohydrate, g/meal
91.6 ± 24.7
87.4 ± 21.5
87.5 ± 21.4
.075
.056
Carbohydrate/energy ratio, %
61.1 ± 7.3
61.5 ± 8.5
59.7 ± 8.6
.040
.066
Dinner
Energy, kcal/meal
746.9 ± 211.8
738.8 ± 186.9
739.7 ± 195.4
.887
.693
Protein, g/meal
32.1 ± 9.9
32.6 ± 9.2
32.9 ± 9.4
.645
.351
Protein/energy ratio, %
17.4 ± 3.7
17.9 ± 3.6
18.0 ± 3.1
.158
.073
Fat, g/meal
19.5 ± 8.0
19.5 ± 7.3
19.7 ± 7.5
.943
.761
Fat/energy ratio, %
10.3 ± 2.9
10.6 ± 3.0
10.6 ± 2.8
.520
.304
Carbohydrate, g/meal
96.6 ± 25.8
92.9 ± 24.5
92.2 ± 23.4
.116
.053
Carbohydrate/energy ratio, %
53.0 ± 9.7
51.1 ± 9.6
51.1 ± 10.2
.042
.027
PDCAAS
Lunch
74.7 ± 16.0
75.5 ± 15.7
76.8 ± 14.4
.315
.132
Dinner
82.6 ± 11.3
83.7 ± 11.3
84.9 ± 10.4
.084
.026
BMI, body mass index; MMSE, Mini‒Mental State Examination; MET, metabolic equivalents.
Data are presented as means ± SD or n (%). P values were obtained using the χ2 test for categorical variables and the general linear model for continuous variables.
∗ 3.50 million yen = 31804.6 US dollars at July 2021.
Fig. 1Food consumption at breakfast for the groups stratified according to breakfast PDCAAS. The graphs illustrate the mean and standard error of food consumption (g/100 kcal) at breakfast in the low, middle, and high PDCAAS groups. The differences and trends of the groups were analyzed using the general linear model. ∗∗P <.001 for both difference and trend, ∗P <.05 for both difference and trend. Abbreviation: PDCAAS, protein digestibility‒corrected amino acid score.
Table 3 shows the multivariable-adjusted association between breakfast PDCAAS and low grip strength over 8 years. In all models, the adjusted OR for low grip strength was significantly lower in the high than in the low PDCAAS group. This association remained when participants with newly developed stroke, arthritis, and Parkinson disease during follow-up were further excluded (Supplementary Table 2). On supplemental analysis, there was no significant association between the PDCAAS for lunch, dinner, and total daily intake, and low grip strength (Supplementary Table 3). In addition, the analyses aimed at clarifying the impact of the PDCAAS in participants with an insufficient protein intake; when 166 participants with sufficient protein intake at breakfast were excluded, the adjusted OR (95% CI) of the high PDCAAS group for low grip strength was 0.36 (0.19–0.70). On considering the group with high protein intake and low PDCAAS as the reference while comparing incidence of low grip strength, the OR (95% CI) of the group with low protein and high PDCAAS was estimated at 0.35 (0.14–0.91).
Table 3Multivariable-Adjusted Association between Breakfast PDCAAS and Low Grip Strength over 8 Years
PDCAAS
Model 1
Model 2
Model 3
OR
95% CI
P Value
OR
95% CI
P Value
OR
95% CI
P Value
Low
Ref
Ref
Ref
Middle
0.71
0.45–1.12
.143
0.74
0.46–1.19
.213
0.71
0.43–1.18
.182
High
0.57
0.35–0.93
.026
0.56
0.34–0.94
.028
0.50
0.29–0.86
.012
BMI, body mass index; MET, metabolic equivalents; MMSE, Mini-Mental State Examination; Ref, reference.
ORs and 95% CIs were estimated using the generalized estimating equations.
Model 1: adjusted for sex, age (y), follow-up period (y), and grip strength (kg) at baseline.
Model 2: adjusted for BMI (kg/m2), total physical activity (MET-min/d), MMSE (score), education (y), smoking status (current or not), household annual income (<3.50 million yen/3.50–6.49 million yen/≥6.50 million yen), history of hypertension, dyslipidemia, diabetes mellitus, and ischemic heart disease, and PDCAAS for lunch and dinner (low/middle/high, respectively) in addition to the variables in model 1.
Model 3: adjusted for energy (kcal/meal) and protein (g/meal) intake at 3 regular meals in addition to the variables in model 2.
The contribution of this study is that it demonstrates the importance of protein intake in muscle health; protein appears to be a key element of the contribution of breakfast toward muscular health and function, which is increasingly being recognized as an important component of healthy aging. To our knowledge, this is the first longitudinal epidemiologic study to investigate the association between the PDCAAS (ie, protein quality) for breakfast and incidence of low grip strength in community-dwelling older adults. The results of this study showed that the OR of the high-PDCAAS group for incidence of low grip strength was 50% lower than that of the low-PDCAAS group, after adjusting for covariates including baseline grip strength, energy and protein intake at 3 regular meals, and the PDCAAS for lunch and dinner. There was no significant association between grip strength and the PDCAAS for the total daily intake, lunch, or dinner. These findings suggest that a diet containing good quality, (ie, more bioavailable, protein at breakfast is important for maintaining muscle strength in older adults).
Breakfast has an important role in preventing CVD and diabetes, which lead to muscle weakness or inhibition of skeletal muscle synthesis. Infrequent breakfast consumption is associated with elevated hemoglobin A1c, higher fasting plasma glucose, all-day postprandial hyperglycemia, increased serum cholesterol, and higher risks of developing type 2 diabetes mellitus and CVD.
Grain-derived protein makes a relatively large contribution to the total daily protein intake of the Japanese people. As grain protein is limited by lysine, it has a low PDCAAS.
Depending on the combination of foods in the diet, as in the case of a grain-based meal, there is a difference between the calculated total protein amount and the available protein (ie, the PDCAAS). Therefore, a diet with a high PDCAAS may be more important when dietary intake is low. Sex-stratified analysis showed significant association between high PDCAAS and the incidence of low grip strength only in female individuals (data not shown). This suggested sex-related differences; however, the power of analysis may have been small due to the small number of participants. This result may be attributed to lower protein intake in female individuals. In additional analyses that investigated the impact of the PDCAAS in participants with a low protein intake, the OR of the high PDCAAS group for low grip strength was lower than that before the exclusion of participants with sufficient protein intake at breakfast. In addition, individuals with low protein intake and high PDCAAS showed a negative association with the incidence of low grip strength, compared with those with high protein intake and low PDCAAS. This suggested the importance of protein quality over the amount of protein intake at breakfast. Food intake in older adults changes because of physical conditions or social problems/norms/trends, resulting in an unbalanced diet.
Accordingly, older people may easily have an unbalanced diet, such as a grain-based diet containing poor quality protein. Therefore, more focus should be directed to the protein quality of meals, especially breakfast, for healthy aging.
This study had several limitations. First, we only assessed the PDCAAS at baseline. Dietary intake changes with time, because it is influenced by aging, which is associated with reduced chewing function, decreased economic status, and limited food access
; thus, PDCAAS may also change with aging. However, these factors could not be considered, and we may have underestimated the PDCAAS. In addition, physical activity and cognitive function were also adjusted only at baseline; these functional changes may affect grip strength. Second, we assessed nutritional intake using a 3-day dietary record, which might not have reflected habitual intake. However, general nutritional assessments, such as the food frequency questionnaire, are unable to assess breakfast, lunch, and dinner separately. Therefore, dietary records are the best for assessing dietary intake at each meal. Epidemiologic data were used in this study, and the effect of breakfast protein intake could not be completely separated from that of total protein intake; the effect of breakfast protein quality on muscle strength therefore needs to be investigated in future intervention studies. Third, although the average grip strength in male and female individuals was close to the national average,
the enrolled participants in this study were healthier than those excluded. Although only Japanese individuals were included as participants, dietary habits may differ across races and regions; further studies including different countries, races, and regions are therefore needed.
Conclusions and Implications
Higher breakfast protein quality reduced the incidence of low muscle strength in community-dwelling older adults, independent of protein intake, suggesting that a diet with high amounts of bioavailable protein at breakfast is important for maintaining muscle strength in older people. Our findings may provide valuable insights on nutritional approaches for maintaining muscle strength and, therefore, quality of life in the older population.
Acknowledgments
We appreciate the cooperation and contributions of all participants and staff of the NILS-LSA. We thank Editage (www.editage.com) for English language editing. This study was supported in part by the Food Science Institute Foundation and Research Funding for Longevity Sciences from the National Center for Geriatrics and Gerontology, Japan (grant number 19-10, 21-18). The sponsor had no role in the preparation of this article, including the design, methods, subject recruitment, data collection, and analysis.
Supplementary Data
Supplementary Table 1Comparison of Baseline Characteristics between Participants Included in this Study and Those Excluded
Supplementary Table 2Multivariable-Adjusted Association of Breakfast PDCAAS for Risk of Low Grip Strength over 8 Years, when Participants with Newly Developed Stroke, Arthritis, and Parkinson Disease during Follow-Up were Further Excluded (n = 452)
Model 1
Model 2
Model 3
OR
95 % CI
P Value
OR
95 % CI
P Value
OR
95 % CI
P Value
Low
Ref
Ref
Ref
Middle
0.71
0.44–1.16
.171
0.74
0.44–1.24
.259
0.70
0.40–1.22
.208
High
0.58
0.35–0.96
.034
0.57
0.34–0.97
.038
0.50
0.28–0.88
.017
BMI, body mass index; MET, metabolic equivalents; MMSE, Mini-Mental State Examination. Ref, reference.
ORs and 95% CIs were estimated using the generalized estimating equations.
Model 1: adjusted for sex, age (y), follow-up period (y), and grip strength (kg) at baseline.
Model 2: adjusted for BMI (kg/m2), total physical activity (MET-min/d), MMSE (score), education (y), smoking status (current or not), household annual income (<3.50 million yen/3.50–6.49 million yen/≥6.50 million yen), history of hypertension, dyslipidemia, diabetes mellitus, and ischemic heart disease, and PDCAAS for lunch and dinner (low/middle/high, respectively) in addition to the variables in model 1.
Model 3: adjusted for energy (kcal/meal) and protein (g/meal) intake at 3 regular meals in addition to the variables in model 2.
Supplementary Table 3Multivariable-Adjusted Association of the PDCAAS for Lunch, Dinner, and Total Daily Intake with Low Grip Strength over 8 Years
Model 1
Model 2
Model 3
OR
95 % CI
P Value
OR
95 % CI
P Value
OR
95 % CI
P Value
Lunch PDCAAS
Low
Ref
Ref
Ref
Middle
0.96
0.60–1.64
.880
0.94
0.58–1.62
.800
0.92
0.56–1.53
.756
High
0.83
0.50–1.36
.457
0.82
0.49–1.38
.448
0.81
0.48–1.35
.419
Dinner PDCAAS
Low
Ref
Ref
Ref
Middle
1.01
0.62–1.66
.962
1.04
0.61–1.70
.891
1.07
0.64–1.79
.788
High
0.85
0.53–1.38
.510
0.86
0.53–1.37
.527
0.89
0.54–1.47
.654
Daily total PDCAAS
Low
Ref
Ref
Ref
Middle
0.70
0.41–1.12
.159
0.72
0.42–1.15
.187
0.73
0.44–1.21
.221
High
0.70
0.45–1.11
.122
0.67
0.42–1.08
.099
0.68
0.42–1.11
.121
BMI, body mass index; MET, metabolic equivalents; MMSE, Mini-Mental State Examination; Ref, reference.
ORs and 95% CIs were estimated using the generalized estimating equations.
Model 1: adjusted for sex, age (y), follow‒up period (y), and grip strength (kg) at baseline.
Model 2: adjusted for BMI (kg/m2), total physical activity (MET‒min/d), MMSE (score), education (y), smoking status (current or not), household annual income (<3.50 million yen/3.50–6.49 million yen/≥6.50 million yen), history of hypertension, dyslipidemia, diabetes mellitus, and ischemic heart disease, and PDCAAS of other meals (low/middle/high, respectively) in addition to the variables in model 1.
Model 3: adjusted for energy (kcal/meal) and protein (g/meal) intake at 3 regular meals in addition to the variables in model 2.
Assessment of muscle function and physical performance in daily clinical practice: a position paper endorsed by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO).
Association of grip strength with risk of all-cause mortality, cardiovascular diseases, and cancer in community-dwelling populations: a meta-analysis of prospective cohort studies.
This study was supported in part by the Food Science Institute Foundation and Research Funding for Longevity Sciences from the National Center for Geriatrics and Gerontology, Japan (grant number 19-10, 21-18). The authors declare no conflicts of interest.
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