Reduced dietary omega-3 fatty acids intake is associated with sarcopenia in elderly patients with type 2 diabetes: a cross-sectional study of KAMOGAWA-DM cohort study

Abstract

Omega-3 fatty acids intake is important to maintain muscle mass. However, the relationship between omega-3 fatty acids intake and sarcopenia in elderly patients with type 2 diabetes has been unclear. We used the brief-type self-administered diet history questionnaire for the assessment of habitual food and nutrient intake. Body composition of patients was evaluated using bioimpedance analysis. To investigate the effect of energy intake on the presence of sarcopenia, we performed logistic regression analyses. Among the patients, 45 patients (13.2%) were diagnosed as sarcopenia. Patients with sarcopenia were aged [74.2 (5.7) vs 71.4 (5.9) years, p = 0.003] and lower body mass index [21.2 (3.5) vs 24.3 (4.6) kg/m², p<0.001] than those without. In addition, omega-3 fatty acids intake of patients with sarcopenia was lower than that without [2.6 (1.0) vs 3.0 (1.2) kcal/day, p = 0.046]. Omega-3 fatty acids intake was negatively associated with the presence of sarcopenia (odds ratio: 0.29, 95% confidence interval: 0.14–0.60, p<0.001) after adjusting for age, sex, exercise, smoking status, diabetes duration, hemoglobin A1c, energy intake, protein intake, fat intake and omega-3 fatty acids intake. Omega-3 fatty acids intake was negatively associated with the presence of sarcopenia in elderly patients with type 2 diabetes.

Introduction

Number of elderly patients with type 2 diabetes is rapidly increasing, and they often have geriatric syndrome such as sarcopenia and frailty.⁽¹⁾ Loss of muscle mass and degradation of muscle with aging is called sarcopenia, which leads to motor function disorder, falls, fractures and difficulty in sending daily life.^(2,3) It has also been reported that sarcopenia increases the risk of death.⁽⁴⁾ To maintain the muscle mass, it is necessary to take sufficient protein,⁽⁵⁾ and there is a report that healthy elderly people should take 1 g of protein per body weight (kg) to promote muscle protein anabolism and increase muscle mass.⁽⁶⁾ In fact, we previously reported that protein intake is associated with muscle mass.⁽⁷⁾

On the other hand, some previous studies reported that polyunsaturated fatty acids such as omega-3 and omega-6 fatty acids might play a role in not only prevention of cardiovascular disease and cancer⁽⁸⁾ but also muscle hypertrophy.⁽⁹⁾ Especially, omega-3 fatty acids was reported to decrease inflammation through interference with arachidonic acid metabolism and preserve skeletal muscle mass in elderly people.^(10,11) Omega-3 fatty acids supplementation increased muscle mass and strength in elderly healthy individuals.^(12,13) While several previous reports demonstrated that dietary omega-3 fatty acids intake was associated with muscle strength,^(10,14,15) few studies reported the association between dietary omega-3 fatty acids intake and muscle mass.⁽⁹⁾ Thus, we aimed to investigate the association between dietary omega-3 fatty acids intake and sarcopenia diagnosed by both muscle strength and mass in elderly patients with type 2 diabetes.

Materials and Methods

Study patients

KAMOGAWA-DM cohort study is an ongoing prospective cohort study from 2014.⁽¹⁶⁾ We extracted the elderly type 2 diabetes patients, age ≥65 years and without physical inactivity, who were recruited from the outpatient clinics at the Kyoto Prefectural University of Medicine and Kameoka Municipal Hospital from August 2015 to September 2017 in this cross-sectional study. We excluded patients with diabetic nephropathy stage 3 or more,⁽¹⁷⁾ inflammatory disease, malignancy, and endocrine disease.⁽⁴⁾ In addition, we also excluded patients with class NYHA II–IV cardiac insufficiency⁽¹⁸⁾ and severe chronic obstructive pulmonary disease⁽¹⁹⁾ because these conditions would influence in appetite and physical activity. Approval for the study was obtained from the local research ethics committee, and written informed consent was obtained from all patients.

Estimation and assessment of usual food and nutrient intake

The brief-type self-administered diet history questionnaire (BDHQ) was used for the assessment of usual food and nutrient intake in this study.⁽²⁰⁾ The details of BDHQ were expressed elsewhere.⁽²⁰⁾ Briefly, BDHQ estimates the dietary intake of 58 items in the past month using five sections: (i) daily intake of rice, type of rice, and miso soup; (ii) frequency of forty-six food and nonalcoholic beverage items; (iii) usual cooking methods; (iv) frequency of drinking alcoholic beverages and amount per drink for five alcoholic beverages; and (v) general dietary behavior.⁽²⁰⁾ Estimates of the intakes of energy, carbohydrate, protein and fat or the intakes of the 58 food items were calculated by an ad hoc computer algorithm for the BDHQ based on Standard Tables of Food Composition in Japan.⁽²¹⁾ We estimated dietary total energy (kcal/day), carbohydrate (g/day), total protein (g/day), fat (g/day), alcohol (g/day), omega-3 fatty acids intake (g/day) and omega-6 fatty acids intake (g/day), using this calculation program of BDHQ. We also excluded the patient who reported extremely low (under 600 kcal) or high (over 4,000 kcal) energy intake.⁽²²⁾

Measurement of body composition determined by bioelectric impedance

We evaluated the body composition of patients using the InBody 720 (InBody Japan, Tokyo, Japan), which analyzes body composition with a multifrequency impedance.⁽²³⁾ Several previous studies demonstrated that the multifrequency impedance analyzer shows a good correlation with the dual-energy X-ray absorptiometry method and was validated.⁽²⁴⁾ We got the data of body weight (BW, kg), body fat mass (kg), skeletal muscle mass (kg) and appendicular muscle mass (kg). Additionally, we calculated skeletal muscle mass index (SMI, kg/m²) by dividing appendicular muscle mass (kg) by the square of the height (m),^(25,26) and defined body mass index (BMI) as body weight (kg) divided by the square of the height (m).

Standardized questionnaire for lifestyle factors

A standardized questionnaire was performed to all patients. We divided the patients into nonsmoker, ex-smoker and current smoker. On the questionnaire, patients reported the kind and frequency of their participation in sports or recreational activities.⁽²⁷⁾ We categorized the patients, who performed any kind of sport regularly at least once a week, as regular exercisers.⁽²⁸⁾

Data collection

The concentrations of several factors, including fasting plasma glucose, creatinine and C-peptide were measured, using venous blood, after an overnight fast. Hemoglobin A1c (HbA1c) was analyzed using high-performance liquid chromatography and was showed as a National Glycohemoglobin Standardization Program unit. We used the Japanese Society of Nephrology equation for estimated glomerular filtration rate (eGFR): eGFR (ml/min/1.73 m²) = 194 × serum creatinine^−1.094 × age^−0.287 (×0.739 for women).⁽²⁹⁾ In addition, patients reported the kind of oral hypoglycemic agent and the presence of insulin use on the questionnaire.

Definition of sarcopenia

Sarcopenia was diagnosed with grip strength and SMI based on Japan Society of Hepatology guidelines for sarcopenia.⁽³⁰⁾ We measured grip strength of patients using a Smedley grip dynamometer, and set the cut-off values to <26 kg/m² for men and 18 kg/m² for women. Moreover, we set the cut-off values of SMI to <7.0 kg/m² for men and 5.7 kg/m² for women. We diagnosed patients with both of two benchmarks as sarcopenia.

Statistical analysis

We preformed statistical analyses using JMP ver. 12.0 software (SAS Institute Inc., Cary, NC) and considered that a p value <0.05 was statistically significant. Mean or frequencies of potential confounding variables were calculated, and continuous variables were presented as the mean (SD). We divided the patients into tertile according to dietary omega-3 fatty acids intake: the lowest group (men; <2.3 g/day, women; <2.1 g/day), the middle group (men; ≥2.3, <3.3 g/day, women; ≥2.1, <3.1 g/day), and the highest group (men; ≥3.3 g/day, women; ≥3.1 g/day). Categorial variables were compared among the groups by Pearson’s chi-square test, and continuous variables were compared by one-way ANOVA and Tukey HSD test, respectively. Odds ratios (ORs) and 95% confidence intervals (CIs) of several factors on the presence of sarcopenia were calculated and we considered following factors as independent variables for multivariate logistic regression analyses: age, sex, exercise, smoking status, diabetes duration, HbA1c, energy intake, protein intake, fat intake⁽¹⁶⁾ and omega-3 fatty acids intake.

Results

In this study, 390 patients (207 men and 183 women) with type 2 diabetes received BDHQ. Among them, a total of 359 patients completed the questionnaire, yielding a collection rate of 92.1%. We excluded 6 patients with incomplete data of covariates, 3 patients with diabetic nephropathy stage 3 or more and 8 patients with hyper- and hypo-nutrition. Finally, the study population was 342 patients (180 men and 162 women) (Fig. 1). There were no patients with class NYHA II-IV cardiac insufficiency and severe chronic obstructive pulmonary disease.

Fig. 1.

Study flow diagram for the registration of patients.

Clinical characteristics of 342 patients with type 2 diabetes are shown in Table 1. The average (SD) of age and HbA1c were 74.2 (5.7) years and 7.8 (1.3) % in patients with sarcopenia, and 71.4 (5.9) years and 7.7 (1.7) % in patients without sarcopenia, respectively. In addition, the average (SD) of omega-3 fatty acids intake in patients with sarcopenia was lower than that in patients without [2.6 (1.0) vs 3.0 (1.2) g/day, p = 0.046].

Table 1.

Clinical characteristics of study patients

	Total (n = 342)	Patients with sarcopenia (n = 45)	Patients without sarcopenia (n = 297)	p value
Sex (men/women)	180/162	21/24	159/138	0.39
Age (year)	71.8 (6.0)	74.2 (5.7)	71.4 (5.9)	0.003
Body weight (kg)	60.2 (13.0)	50.9 (9.4)	61.7 (12.9)	<0.001
Body mass index (kg/m2)	23.9 (4.5)	21.2 (3.5)	24.3 (4.6)	<0.001
Skeletal muscle mass (kg)	22.4 (4.7)	18.3 (3.1)	23.0 (4.6)	<0.001
Appendicular muscle mass (kg)	16.9 (4.1)	13.5 (2.8)	17.4 (4.0)	<0.001
Skeletal muscle mass index (kg/m2)	6.6 (1.0)	5.6 (0.6)	6.8 (1.0)	<0.001
Grip Strength (kg)	26.4 (8.1)	16.7 (5.3)	27.9 (7.4)	<0.001
Body fat mass (kg)	17.4 (7.3)	14.8 (6.0)	17.8 (7.4)	0.009
Smoking (non-/ex-/current smoker)	267/54/21	1,937/5/3	230/49/18	0.652
Regular exerciser (no/yes)	263/79	38/7	72/225	0.181
Disease duration (year)	11.2 (11.9)	13.9 (16.7)	10.9 (11.2)	0.163
Plasma glucose (mM)	8.4 (3.5)	7.8 (2.9)	8.5 (3.5)	0.195
Hemoglobin A1c (%)	7.7 (1.6)	7.8 (1.3)	7.7 (1.7)	0.68
eGFR (ml/min/1.73 m2)	67.7 (17.2)	69.6 (16.8)	67.4 (17.3)	0.417
C-peptide (nmol/L)	2.0 (1.4)	1.9 (1.6)	2.0 (1.3)	0.739
C-reactive protein (mg/dl)	0.3 (0.9)	0.1 (0.1)	0.3 (0.9)	0.201
Sulfonylureas (−/+)	265/77	33/12	232/65	0.342
Glinides (−/+)	320/22	40/5	280/17	0.148
α-Glucosidase inhibitors (−/+)	296/46	45/0	251/46	0.01
Metformin (−/+)	298/44	40/5	258/39	0.794
Thiazolidine (−/+)	326/16	45/0	281/16	0.1
Dipeptidyl peptidase-4 inhibitor (−/+)	320/122	27/18	193/104	0.661
Glucagon like peptide-1receptor agonist (−/+)	322/20	42/3	280/17	0.762
Sodium-glucose cotransporter 2 inhibitors (−/+)	337/5	45/0	292/5	0.839
Insulin treatment (−/+)	280/62	33/12	247/50	0.591
Energy intake (kcal/day)	1,774.0 (584.1)	1,645.0 (493.8)	1,792.6 (594.5)	0.052
Protein intake (g/day)	74.1 (29.1)	68.7 (21.5)	74.9 (30.0)	0.193
Fat intake (g/day)	52.1 (20.7)	46.6 (16.5)	52.9 (21.2)	0.063
Carbohydrate intake (g/day)	230.1 (85.5)	226.1 (79.5)	230.6 (86.4)	0.743
Omega-3 fatty acid (g/day)	2.9 (1.4)	2.6 (1.0)	3.0 (1.2)	0.046
Omega-6 fatty acid (g/day)	9.9 (4.0)	8.8 (3.4)	10.1 (4.0)	0.045
Omega-6 fatty acid/omega-3 fatty acid ratio	3.7 (1.2)	3.6 (1.4)	3.7 (1.1)	0.595
Alcohol intake (g/day)	9.8 (18.5)	3.8 (8.5)	10.6 (19.4)	0.026

Data was expressed as mean (SD) or number. Wilcoxon test for continuous variables or the chi-square test for categorical variables was performed to assess statistical significance of differences between groups. eGFR, estimated glomerular filtration rate.

Unadjusted and adjusted ORs and 95% CIs of the presence of sarcopenia are shown in Table 2. We divided the patients into tertile according to omega-3 fatty acids intake, and the lowest group showed a significant association with sarcopenia compared to the highest group in univariate logistic regression analyses (OR: 3.04, 95% CI: 1.05–8.75, p = 0.039). In addition, in the multivariate logistic regression analyses, omega-3 fatty acids intake based on continuous variables was negatively associated with the presence of sarcopenia (0.29, 0.14–0.60, p<0.001), and the lowest and the middle group of omega-3 fatty acids intake showed a significant association with the presence of sarcopenia compared to the highest group (the lowest; 9.56, 1.50–61.01, p = 0.017, the middle; 5.91, 1.16–30.08, p = 0.032).

Table 2.

Univariate and multivariate logistic regression analyses for sarcopenia

	Model 1			Model 2			Model 3			Model 4
	Odds ratio (95%CI)	p value		Odds ratio (95%CI)	p value		Odds ratio (95%CI)	p value		Odds ratio (95%CI)	p value
Age (year)	—	—		—	—		1.10 (1.02–1.19)	0.013		1.11 (1.03–1.20)	0.007
Men	—	—		—	—		3.26 (1.06–10.09)	0.034		3.76 (1.26–11.17)	0.013
Regular exerciser	—	—		—	—		0.95 (0.34–2.68)	0.921		0.90 (0.32–2.53)	0.834
Ex smoker	—	—		—	—		2.16 (0.52–8.93)	0.288		1.90 (0.47–7.68)	0.366
Current smoker	—	—		—	—		2.90 (0.51–16.63)	0.232		2.43 (0.44–13.61)	0.311
Diabetes duration (years)	—	—		—	—		1.03 (0.99–1.07)	0.059		1.04 (1.00–1.07)	0.054
Hemoglobin A1c (%)	—	—		—	—		1.30 (0.99–1.68)	0.059		1.32 (1.03–1.70)	0.046
Energy intake (kcal/kg BW/day)	—	—		—	—		0.98 (0.90–1.06)	0.602		1.01 (0.94–1.08)	0.68
Protein intake (kcal/kg BW/day)	—	—		—	—		3.34 (0.40–28.14)	0.267		0.62 (0.09–4.29)	0.971
Fat intake (kcal/kg BW/day)	—	—		—	—		5.49 (0.49–61.20)	0.164		3.65 (0.50–26.6)	0.478
Omega-3 fatty acids intake (g/day)	0.74 (0.54–1.01)	0.043					0.29 (0.14–0.60)	<0.001		—	—
Tertiles
The lowest (men; <2.3 g/day, women; <2.1 g/day)	—	—		3.04 (1.05–8.75)	0.039		—	—		9.56 (1.50–61.01)	0.017
The middle (men; ≥2.3, <3.3 g/day, women; ≥2.1, <3.1 g/day)	—	—		2.43 (0.84–7.07)	0.102		—	—		5.91 (1.16–30.08)	0.032
The highest (men; ≥3.3 g/day, women; ≥3.1 g/day)	—	—		Reference	—		—	—		Reference	—

Model 1 and 2 was unadjusted. Model 3 was adjusted for age, sex, exercise, smoking status, diabetes duration, Hemoglobin A1c, energy intake, protein intake, fat intake and omega-3 fatty acids intake. Model 4 was adjusted for age, sex, exercise, smoking status, diabetes duration, Hemoglobin A1c, energy intake, protein intake, fat intake and omega-3 fatty acids intake tertile.

Discussion

We demonstrated that reduced dietary omega-3 fatty acids intake was associated with the presence of sarcopenia in elderly patients with type 2 diabetes. Although several studies showed that some fatty acids such as omega-3 fatty acids or maslinic acid intake was associated with muscle strength and muscle mass in healthy elderly people,^{(8,9,12–15,31)} to our knowledge, the present study is the first survey to identify the association between omega-3 fatty acids intake and sarcopenia in elderly patients with type 2 diabetes.

The possible explanations of the association between reduced omega-3 fatty acids intake and sarcopenia are as follows. To reduce the inflammation is important for prevention of sarcopenia.⁽³²⁾ Omega-3 fatty acids, which form a series of eicosanoids different from omega-6 fatty acids, compete with the major enzymes involved in eicosanoid formation from arachidonic acid, i.e., cyclooxygenase and lipoxygenase.^(33,34) However, these eicosanoids have lower bioactivity and less inflammation than eicosanoids formed from arachidonic acid metabolism.⁽³⁵⁾ Therefore, omega-3 fatty acids may reduce inflammation and reserve skeletal muscle mass through interference of arachidonic acid metabolism.⁽³⁶⁾

In addition, Smith et al.⁽³⁷⁾ reported that omega-3 fatty acids supplementation such as eicosapentaenoic acid and docosahexaenoic acid for 8 weeks stimulated muscle protein synthesis and be useful for both prevention and treatment of sarcopenia in elderly individuals. With the supplementation, phosphorylation of mammallian target of rapamycin (mTOR) and p70s6k, which were involved in muscle protein synthesis, was activated without activation of inflammatory cytokines. These activities were thought to occur by incorporating omega-3 fatty acids into myocyte membranes, which resulted in activating protein kinase C located upstream of mTOR and p70s6k.⁽³⁸⁾ Additionally, omega-3 fatty acids attenuate oxidative stress by suppressing forkhead box-containing protein, O1 (foxo1) pathway,⁽³⁹⁾ and suppressing foxo1 leads to suppression of muscle atrophy.⁽⁴⁰⁾ In summary, omega-3 fatty acids may stimulate protein synthesis.

Omega-3 fatty acids may also affect membrane composition of nervous tissue, which results in a favorable effect on nervous system function.⁽⁴¹⁾ Rodacki et al.⁽¹⁴⁾ reported that elderly women who were supplemented fish oil, which is rich in omega-3 fatty acids, with strength training program showed greater improvements in the neuromuscular system such as muscle strength and functional capacity than those who only performed strength training program without fish oil supplementation. Taken together, omega-3 fatty acids may work through several different mechanisms to increase muscle mass and to improve skeletal muscle strength through promoting neuromuscular function.

Our study has some limitations. First, the accuracy of diet survey depends on the memorial power of patients, because the data were based on the self-reported questionnaires. However, BDHQ was correlated with energy and protein intake evaluated by the 16-day-weighed dietary record.⁽²⁰⁾ Second, we used body composition of patients using a mulitifrequency impedance body composition analyzer, although the dual-energy X-ray absorptiometry is a gold standard test for evaluating skeletal muscle mass. However, a mulitifrequency impedance body composition analyzer has good correlation with the dual-energy X-ray absorptiometry.⁽²⁴⁾ Third, this study was a cross-sectional design; thus, this study did not permit the determination of causality. Additionally, although it has been postulated that diabetes may be an important factor in sarcopenia development, the relationship is unclear since the opposite maybe also true.⁽⁴²⁾ To clarify these causal relationships, follow up data are necessary. Fourth, we used dichotomous value for exercise, because we did not have detailed data of exercise or physical activity. Lastly, it is unclear whether this result applies to elderly patients with type 2 diabetes other than Japanese.

Conclusions

In conclusion, reduced dietary omega-3 fatty acids intake was associated with the presence of sarcopenia in patients with type 2 diabetes. Further prospective studies are needed to better asses the relationship between sarcopenia and omega-3 fatty acids intake in elderly patients with type 2 diabetes.

Abbreviations

BDHQ

brief-type self-administered diet history questionnaire

BMI

body mass index

BW

body weight

CI

confidence interval

eGFR

estimated glomerular filtration rate

foxo1

forkhead box-containing protein, O1

HbA1c

hemoglobin A1c

OR

odds ratio

SMI

skeletal muscle index

mTOR

mammallian target of rapamycin

Conflict of Interenst

YH received grants from Asahi Kasei Corporation outside the submitted work. MF received grants from AstraZeneca plc, Astellas Pharma Inc., Nippon Boehringer Ingelheim Co., Ltd., Daiichi Sankyo Co., Ltd., Eli Lilly Japan K.K., Kyowa Hakko Kirin Co., Ltd., Kissei Pharmaceutical Co., Ltd., MSD K.K., Mitsubishi Tanabe Pharma Corp., Novo Nordisk Pharma Ltd., Sanwa Kagaku Kenkyusho Co., Ltd., Sanofi K.K., Ono Pharmaceutical Co., Ltd, and Takeda Pharmaceutical Co., Ltd., outside the submitted work. The sponsors were not involved in the study design; in the collection, analysis, interpretation of data; in the writing of this manuscript; or in the decision to submit the article for publication. The authors, their immediate families, and any research foundations with which they are affiliated have not received any financial payments or other benefits from any commercial entity related to the subject of this article. The authors declare that although they are affiliated with a department that is supported financially by pharmaceutical company, the authors received no current funding for this study, and this does not alter their adherence to all the journal policies on sharing data and materials. The other authors have nothing to disclose.