Long-Term Resistance Training and Risk of Type 2 Diabetes

Tianyue Zhang; Yiwen Zhang; Dong Hoon Lee; Leandro F M Rezende; Xinyu Wang; Chao Zheng; Edward Giovannucci

doi:10.1001/jamanetworkopen.2026.19420

. 2026 Jun 22;9(6):e2619420. doi: 10.1001/jamanetworkopen.2026.19420

Long-Term Resistance Training and Risk of Type 2 Diabetes

Tianyue Zhang ^1,², Yiwen Zhang ^2,³, Dong Hoon Lee ^2,⁴, Leandro F M Rezende ^5,⁶, Xinyu Wang ^2,³, Chao Zheng ^1,^✉, Edward Giovannucci ^2,^3,^✉

¹Department of Endocrinology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China

²Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts

³Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts

⁴Department of Sport Industry Studies, Yonsei University, Seoul, Republic of Korea

⁵Chronic Disease Epidemiology Research Center, Department of Preventive Medicine, Universidade Federal de São Paulo, Sao Paulo, Brazil

⁶Faculty of Health Sciences, Universidad Autónoma de Chile, Providencia, Chile

Accepted for Publication: April 29, 2026.

Published: June 22, 2026. doi:10.1001/jamanetworkopen.2026.19420

Open Access: This is an open access article distributed under the terms of the CC-BY-NC-ND License, which does not permit alteration or commercial use, including those for text and data mining, AI training, and similar technologies. © 2026 Zhang T et al. JAMA Network Open.

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Corresponding Authors: Chao Zheng, MD, Zhejiang University School of Medicine, The Second Affiliated Hospital, Shangcheng District, Hangzhou 310000, China (chao_zheng@zju.edu.cn); Edward Giovannucci, MD, ScD, Department of Nutrition, Harvard T. H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115 (egiovann@hsph.harvard.edu).

Author Contributions: Drs T. Zhang and Y. Zhang had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs T. Zhang and Y. Zhang contributed equally to this work as co–first authors.

Concept and design: Y. Zhang, Zheng, Giovannucci.

Acquisition, analysis, or interpretation of data: T. Zhang, Y. Zhang, Lee, Rezende, Wang, Giovannucci.

Drafting of the manuscript: T. Zhang.

Critical review of the manuscript for important intellectual content: Y. Zhang, Lee, Rezende, Wang, Zheng, Giovannucci.

Statistical analysis: T. Zhang, Y. Zhang, Lee, Wang.

Obtained funding: Giovannucci.

Administrative, technical, or material support: Rezende, Zheng.

Supervision: Y. Zhang, Zheng, Giovannucci.

Conflict of Interest Disclosures: None reported.

Funding/Support: The Nurses’ Health Study (NHS) is supported by grant NCI UM1 CA186107 from the National Institutes of Health (NIH); the Nurses’ Health Study II (NHS II), by grant NCI U01 CA176726 from the NIH; and the Health Professionals Follow-up Study (HPFS), by grant U01 CA167552 from the NIH. Additional support came from grant 311109/2023-3 from the National Council for Scientific and Technological Development (Dr Rezende).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Data Sharing Statement: See Supplement 2.

Additional Contributions: We thank the Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, home of the NHS and NHS II cohorts, and the Harvard T. H. Chan School of Public Health, home of the HPFS cohort, and the staff and participants of the 3 cohorts. Additionally, the authors acknowledge the contributions of the central cancer registries supported through the Centers for Disease Control and Prevention’s National Program of Cancer Registries and/or the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) Program. Central registries may also be supported by state agencies, universities, and cancer centers. Participating central cancer registries include the following: Alabama, Alaska, Arizona, Arkansas, California, Delaware, Colorado, Connecticut, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Mississippi, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Puerto Rico, Rhode Island, Seattle SEER Registry, South Carolina, Tennessee, Texas, Utah, Virginia, West Virginia, and Wyoming.

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Corresponding author.

PMCID: PMC13288573 PMID: 42329652

Key Points

Question

Is long-term resistance training, including volume and consistency, associated with reduced type 2 diabetes (T2D) risk, and how are combinations with aerobic activity and sedentary behavior additionally associated with T2D risk?

Findings

In this cohort study of 143 715 adults followed up for 19.2 years, consistently high levels of resistance training were associated with the greatest reduction in T2D risk. In analyses of lifestyle combinations, meeting both aerobic and resistance training recommendations and limiting television viewing was associated with the lowest risk.

Meaning

These findings suggest that consistent resistance training, particularly when combined with adequate aerobic activity and limited sedentary behavior, may be an important component of recommendations for T2D prevention.

This cohort study examines the association of long-term resistance training with risk of incident type 2 diabetes and assesses the joint associations with aerobic physical activity and sedentary behavior among adult health care professionals in the US.

Abstract

Importance

The optimal long-term patterns of resistance training, including volume, consistency, and integration with other lifestyle behaviors, remain unclear.

Objective

To examine the association of long-term resistance training with risk of incident type 2 diabetes (T2D) and to assess joint associations with aerobic physical activity and sedentary behavior.

Design, Setting, and Participants

This prospective cohort study assessed the data from 3 ongoing US studies: the Nurses’ Health Study (June 30, 2002, to June 30, 2021), the Nurses’ Health Study II (June 30, 2003, to June 30, 2021), and the Health Professionals Follow-up Study (June 30, 1992, to June 30, 2021). Follow-up was completed June 30, 2021. Participants included adult health care professionals who had undergone at least 3 assessments of resistance training between 40 and 60 years of age for trajectory analysis. Data were analyzed from April 30 to September 30, 2025.

Exposure

Time spent in resistance training was assessed every 2 to 4 years and categorized into 5 groups: consistently low, high to low, low to high, fluctuating, and consistently high. Long-term resistance training was characterized using cumulative means and trajectory patterns between ages 40 and 60 years in the Nurses’ Health Study II.

Main Outcomes and Measures

The main outcome was incident T2D. Multivariable-adjusted hazard ratios (HRs) and 95% CIs were estimated using Cox proportional hazards regression models with time-varying resistance training.

Results

Among 143 715 adults included in the analysis (mean [SD] age, 56.0 [10.5] years; 78.3% women), 10 038 incident T2D cases occurred during a mean (SD) follow-up of 19.2 (5.0) years. Compared with no resistance training, engaging in 2 or more hours per week of resistance training was associated with a lower T2D risk (HR, 0.73; 95% CI, 0.66-0.81). In trajectory analyses, participants with consistently high levels of resistance training (≥0.5 h/wk across midlife) had a 42% lower T2D risk (HR, 0.58; 95% CI, 0.45-0.74), and a low to high pattern was associated with a 21% lower risk (HR, 0.79; 95% CI, 0.66-0.94), compared with consistently low levels of resistance training. Participants who met recommendations for both aerobic activity (≥15 total metabolic equivalent h/wk) and resistance training (≥1 h/wk) and limited television viewing (<2 h/d) had the lowest T2D risk (HR, 0.38; 95% CI, 0.34-0.42) compared with those meeting none of the recommendations.

Conclusions and Relevance

In this prospective cohort study, resistance training among US adult health care professionals was associated with substantially lower T2D risk, particularly when performed consistently over midlife and combined with adequate aerobic activity and limited sedentary television viewing. These findings support the inclusion of resistance training as a key component of lifestyle recommendations for diabetes prevention.

Introduction

Type 2 diabetes (T2D) is a major global health challenge, and physical activity is a cornerstone of its prevention and management.^1,2 Current US guidelines recommend performing resistance training at least twice per week alongside aerobic activity.³ However, evidence on how resistance training should be optimally performed to maximize long-term T2D prevention remains limited.

Prospective studies of resistance training and T2D are relatively sparse but generally support an inverse association between resistance training and T2D risk.^4,5,6,7 Important gaps remain. First, few studies have simultaneously evaluated resistance training together with aerobic activity and sedentary behavior. Second, it also remains uncertain whether the associations vary according to adiposity, the distribution of muscle groups trained, or the degree of consistency. Third, most prior investigations have relied on a single baseline measure, which is vulnerable to regression dilution bias and cannot fully capture behavioral changes, thus underestimating long-term associations.^8,9 By contrast, repeated assessments and trajectory analysis can address these limitations, allowing dynamic patterns of resistance training across midlife to be modeled. To address these gaps, we analyzed 3 large US prospective cohorts with as many as 14 repeated assessments of resistance training to examine its long-term associations with incident T2D, to evaluate joint associations with adiposity and other activity and sedentary behaviors, and to characterize midlife resistance training trajectories in association with T2D risk.

Methods

Study Population

We conducted a prospective analysis of 3 ongoing studies including adult health care professionals in the US: the Nurses’ Health Study (NHS; June 30, 2002, to June 30, 2021), the Nurses’ Health Study II (NHS II; June 30, 2003, to June 30, 2021), and the Health Professionals Follow-up Study (HPFS; June 30, 1992, to June 30, 2021). Participants have been followed up biennially via mailed questionnaires assessing lifestyle factors and health status, with cumulative follow-up rates exceeding 90%¹⁰; follow-up for this study was completed June 30, 2021. Details of the 3 cohorts are described in the eMethods in Supplement 1. The study protocol was approved by the institutional review boards of the Brigham and Women’s Hospital and Harvard T. H. Chan School of Public Health, who allowed participants’ completion of questionnaires to be considered as implied consent. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.

Assessment of Physical Activity and Sedentary Behavior

Resistance training was assessed at regular intervals (approximately every 2 years in HPFS and every 4 years in NHS and NHS II). For aerobic activities, total metabolic equivalent (MET)–hours per week were calculated by summing the MET-hours per week for all reported activities. Resistance training and aerobic activity were treated as time-varying exposures and calculated as cumulative means across follow-up.

Television (TV) viewing time, a major sedentary behavior, has been strongly associated with T2D in prior investigations and was therefore assessed as our primary measure of sedentary behavior.¹¹ Consistent with US guidelines, we defined 1 or more hours per week (two 30-minute sessions) as the recommended threshold for resistance training.³ For aerobic activities, we defined 15 or more MET-hours per week, and for sedentary TV viewing time, less than 2 hours per day, as the recommended thresholds.^3,12,13 Beyond guideline adherence, we also applied a lower cutoff of 0.5 hours or more per week (one 30-minute session) to capture minimal but sustained participation, which was specifically used in the analyses of long-term consistency and resistance training trajectories. Further details on the assessment, validity, and reproducibility are provided in the eMethods in Supplement 1.

Ascertainment of T2D

The disease outcome of this study was incident T2D. Participants who reported a diagnosis of T2D on biennial questionnaires received a supplementary questionnaire. T2D was defined according to contemporaneous national and international criteria. The validity of the supplementary questionnaire for the diagnosis of diabetes was high, with 97% in men and 98% in women.^14,15,16 Further details are provided in the eMethods in Supplement 1.

Statistical Analysis

Data were analyzed from April 30 to September 30, 2025. To reduce potential reverse causation, we defined baseline as 2002 in the NHS, 2003 in the NHS II, and 1992 in the HPFS, corresponding to 2 years after the initial assessment of resistance training in each cohort. We excluded participants who had missing information on physical activity at baseline, had died before baseline or were missing a date of birth, and had a history of major chronic diseases at baseline, including diabetes, major cardiovascular disease, or cancer, as the diagnoses of these conditions might have influenced subsequent physical activity (eFigure 1 in Supplement 1). Participants in the cohort were categorized as White or other race or ethnicity (including African American, American Indian or Alaska Native, Asian, Hispanic, or other race or ethnicity not captured by the listed categories). These data were included because they were used as covariates and are reported in only 2 categories because the numbers of participants in each minority racial or ethnic group were small. After exclusions, the final analytic sample included 42 891 participants from the NHS, 69 576 from the NHS II, and 31 248 from the HPFS. Person-years were accrued from baseline until the first diagnosis of T2D, death, or the end of follow-up (June 30, 2021), whichever occurred first. We further applied a 2-year lag between exposure and outcome (eMethods in Supplement 1).

Resistance training was categorized as 0, greater than 0 to less than 0.5, 0.5 to less than 1.0, 1.0 to less than 2.0, and 2.0 or more hours per week, consistent with prior studies.⁶ We assessed the proportional hazards assumption using Schoenfeld residuals and found no meaningful violations for resistance training categories or key covariates. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) and 95% CIs for incident T2D. Age in months was used as the underlying time scale, and models were stratified by calendar year and cohort. Potential confounders were selected a priori based on existing literature^17,18 and a framework specifying factors that are associated with both resistance training and T2D but are not considered mediators. These included sociodemographic characteristics, lifestyle factors, diet quality, and total aerobic physical activity; assessment of these variables is described in the eMethods in Supplement 1.

Within our framework, adiposity-related factors were considered potential mediators as well as markers of residual confounding and were therefore not included in the primary multivariable model. In supplementary Cox proportional hazards regression models, we additionally adjusted for time-updated body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) and, in separate models, baseline waist circumference and intentional weight loss to account for overall and central adiposity and weight loss intention at baseline (eMethods in Supplement 1).

To flexibly examine the dose-response association between resistance training and T2D risk, we used restricted cubic spline models with knots at the 50th, 75th, and 90th percentiles of cumulative resistance training exposure.¹⁹ We additionally conducted joint analyses of resistance training with BMI, walking (duration and pace), total aerobic activity, and sedentary behaviors using cross-classified exposure categories (eMethods in Supplement 1).

Because most NHS participants were 60 years or older after 2002, making evaluation of ages 40 to 60 years infeasible, and because the resistance training questions in the HPFS changed across questionnaire cycles, we restricted trajectory analyses to the NHS II cohort. We included participants who had at least 3 assessments of resistance training between 40 and 60 years of age and were free of diabetes, major cardiovascular disease, or cancer at 60 years of age and classified long-term resistance training patterns between 40 and 60 years of age into 5 trajectory groups using a threshold of 0.5 hours per week. We then used Cox proportional hazards regression models to examine associations of these trajectory groups with incident T2D after 60 years of age, with the consistently low group as the reference. Detailed definitions of the trajectory groups were provided in eMethods in Supplement 1.

Sensitivity analyses included models using simple-updated resistance training values, models without a 2-year lag, and models excluding participants with very high aerobic activity or baseline chronic obstructive pulmonary disease or arthritic disease. We also used marginal structural models with inverse probability weighting to address potential time-varying confounding (details in eMethods in Supplement 1). All analyses were conducted in SAS, version 9.4 (SAS Institute Inc), and 2-sided P < .05 was considered statistically significant.

Results

Baseline Characteristics

A total of 143 715 participants were included in the analysis (mean [SD] age, 56.0 [10.5] years; 78.3% women and 21.7% men). Of these, 96.7% participants were White and 3.3% were of other race or ethnicity. At baseline, participants who engaged in greater amounts of resistance training tended to have lower BMI, higher levels of aerobic physical activity, less sedentary time for TV, better dietary quality, and lower prevalence of hypertension and hypercholesterolemia (Table 1). Baseline characteristics by nonresponse before the end of the study are presented in eTable 1 in Supplement 1. Baseline characteristics according to resistance training information missing are presented in eTable 2 in Supplement 1.

Table 1. Baseline Cohort Characteristics by Resistance Training Category.

Characteristic	Resistance training, h/wk^a
Characteristic	0	>0 to <0.5	0.5 to <1.0	1.0 to <2.0	≥2.0
Nurses’ Health Study cohort
No. of participants	32 499	3671	2226	2563	1932
Age, mean (SD), y	67.1 (7.1)	66.4 (7)	66.7 (6.8)	65.4 (6.6)	65.4 (6.5)
Race and ethnicity, No. (%)
White	31 784 (97.8)	3561 (97.0)	2166 (97.3)	2512 (98.0)	1888 (97.7)
Other^b	715 (2.2)	110 (3.0)	60 (2.7)	51 (2.0)	44 (2.3)
BMI, mean (SD)	25.5 (4.3)	24.3 (3.8)	24.0 (3.5)	24.0 (3.6)	23.7 (3.5)
Resistance training time, mean (SD), h/wk	0	0.2 (0.1)	0.8 (0.2)	1.5 (0.3)	4.0 (2.6)
Aerobic activity, mean (SD), MET-h/wk	14.0 (18.4)	17.9 (18.7)	26.5 (21.5)	27.0 (22.4)	38.6 (38.8)
Sedentary TV viewing, mean (SD), h/wk	13.0 (10.1)	11.7 (9.3)	11.9 (9.3)	11.6 (9.1)	10.6 (8.9)
Smoking status, No. (%)
Never	15 080 (46.4)	1637 (44.6)	1019 (45.8)	1095 (42.7)	780 (40.4)
Quit >10 y ago	11 765 (36.2)	1593 (43.4)	962 (43.2)	1199 (46.8)	916 (47.4)
Quit ≤10 y ago	2437 (7.5)	257 (7.0)	138 (6.2)	174 (6.8)	139 (7.2)
Current	3217 (9.9)	184 (5.0)	107 (4.8)	95 (3.7)	97 (5.0)
Alcohol intake, mean (SD), g/d	5.6 (8.5)	6.3 (8.1)	6.5 (8.5)	7.0 (8.3)	7.2 (8.6)
Total energy intake, mean (SD), kcal/d	1743 (443)	1761 (432)	1761 (429)	1763 (418)	1738 (432)
AHEI-2010 score, mean (SD)	51.1 (8.9)	54.6 (9.1)	55.9 (9.1)	57.0 (9.2)	57.9 (9.3)
Baseline hypertension, No. (%)	14 365 (44.2)	1435 (39.1)	846 (38.0)	935 (36.5)	761 (39.4)
Baseline high cholesterol level, No. (%)	18 622 (57.3)	2052 (55.9)	1242 (55.8)	1387 (54.1)	1018 (52.7)
Current multivitamin use, No. (%)	21 092 (64.9)	2728 (74.3)	1710 (76.8)	2007 (78.3)	1455 (75.3)
Current aspirin use, No. (%)	13 195 (40.6)	1571 (42.8)	986 (44.3)	1135 (44.3)	790 (40.9)
Family history of diabetes, No. (%)	8775 (27.0)	929 (25.3)	568 (25.5)	630 (24.6)	450 (23.3)
Family history of myocardial infarction, No. (%)	11 505 (35.4)	1281 (34.9)	790 (35.5)	933 (36.4)	682 (35.3)
Nurses’ Health Study II cohort
No. of participants	45 135	8445	3404	7179	5413
Age, mean (SD), y	48.2 (4.7)	47.9 (4.6)	48.3 (4.6)	47.9 (4.7)	47.8 (4.7)
Race and ethnicity, No. (%)
White	43 600 (96.6)	8107 (96.0)	3292 (96.7)	6964 (97.0)	5251 (97.0)
Other^b	1535 (3.4)	338 (4.0)	112 (3.3)	215 (3.0)	162 (3.0)
BMI, mean (SD)	26.1 (5.7)	24.6 (4.5)	24.1 (4.3)	24.1 (4.1)	23.9 (4.1)
Resistance training time, mean (SD), h/wk	0	0.2 (0.1)	0.8 (0.2)	1.6 (0.3)	4.2 (3.1)
Aerobic activity, mean (SD), MET-h/wk	13.6 (18.5)	17.6 (18.7)	29.0 (22.9)	29.3 (25.2)	45.5 (43.4)
Sedentary TV viewing, mean (SD), h/wk	9.0 (7.0)	8.1 (6.3)	8.1 (6)	7.9 (6.1)	7.5 (5.9)
Smoking status, No. (%)
Never	30 161 (66.8)	5650 (66.9)	2291 (67.3)	4652 (64.8)	3345 (61.8)
Quit >10 y ago	8226 (18.2)	1816 (21.5)	735 (21.6)	1694 (23.6)	1292 (23.9)
Quit ≤10 y ago	2584 (5.7)	481 (5.7)	184 (5.4)	445 (6.2)	404 (7.5)
Current	4164 (9.2)	498 (5.9)	194 (5.7)	388 (5.4)	372 (6.9)
Alcohol intake, mean (SD), g/d	3.6 (6.2)	4.5 (6.5)	4.7 (6.3)	4.9 (6.6)	5.0 (6.9)
Total energy intake, mean (SD), kcal/d	1821 (483)	1829 (467)	1839 (473)	1824 (455)	1810 (469)
AHEI-2010 score, mean (SD)	49.3 (9.5)	52.9 (9.5)	54.4 (9.7)	54.8 (9.7)	56.0 (10.0)
Baseline hypertension, No. (%)	8079 (17.9)	1132 (13.4)	453 (13.3)	948 (13.2)	650 (12.0)
Baseline high cholesterol level, No. (%)	14 127 (31.3)	2424 (28.7)	882 (25.9)	1917 (26.7)	1402 (25.9)
Current multivitamin use, No. (%)	26 133 (57.9)	5667 (67.1)	2369 (69.6)	5061 (70.5)	3740 (69.1)
Current aspirin use, No. (%)	10 291 (22.8)	2077 (24.6)	844 (24.8)	1694 (23.6)	1305 (24.1)
Family history of diabetes, No. (%)	14 128 (31.3)	2449 (29.0)	909 (26.7)	2032 (28.3)	1564 (28.9)
Family history of myocardial infarction, No. (%)	21 349 (47.3)	3741 (44.3)	1498 (44.0)	3209 (44.7)	2409 (44.5)
Health Professionals Follow-Up Study cohort
No. of participants	25 690	2080	1139	931	1408
Age, mean (SD), y	58.9 (9.3)	54.8 (8.3)	54.6 (8.1)	54.8 (8.1)	54.0 (7.9)
Race and ethnicity, No. (%)
White	24 508 (95.4)	1949 (93.7)	1105 (97.0)	886 (95.2)	1362 (96.7)
Other^b	1182 (4.6)	131 (6.3)	34 (3.0)	45 (4.8)	46 (3.3)
BMI, mean (SD)	25.6 (3.2)	25.1 (2.7)	24.9 (2.6)	25.0 (2.6)	25.0 (2.9)
Resistance training time, mean (SD), h/wk	0	0.3 (0.2)	1.0 (0)	1.5 (0)	3.6 (2.1)
Aerobic activity, mean (SD), MET-h/wk	28.8 (27.7)	35.5 (31)	40.0 (28.4)	46.4 (33.3)	50.6 (40.8)
Sedentary TV viewing, mean (SD), h/wk	9.6 (8.2)	9.0 (7.6)	8.8 (7.7)	8.7 (7.7)	8.6 (7.5)
Smoking status, No. (%)
Never	13 035 (50.7)	1115 (53.6)	574 (50.4)	473 (50.8)	724 (51.4)
Quit >10 y ago	8101 (31.5)	707 (34.0)	410 (36.0)	319 (34.3)	479 (34.0)
Quit ≤10 y ago	2576 (10.0)	185 (8.9)	106 (9.3)	87 (9.3)	128 (9.1)
Current	1978 (7.7)	73 (3.5)	49 (4.3)	52 (5.6)	77 (5.5)
Alcohol intake, mean (SD), g/d	10.7 (14.1)	11 (13.3)	11.1 (12.7)	11.3 (12.5)	10.3 (12.4)
Total energy intake, mean (SD), kcal/d	1968 (559)	1983 (558)	1968 (555)	1970 (555)	1988 (564)
AHEI-2010 score, mean (SD)	52.4 (10.7)	55.1 (10.4)	56.3 (10.8)	56.5 (10.3)	57.2 (10.8)
Baseline hypertension, No. (%)	6063 (23.6)	451 (21.7)	222 (19.5)	180 (19.3)	279 (19.8)
Baseline high cholesterol level, No. (%)	7142 (27.8)	624 (30.0)	298 (26.2)	281 (30.2)	346 (24.6)
Current multivitamin use, No. (%)	13 693 (53.3)	957 (46.0)	528 (46.4)	409 (43.9)	566 (40.2)
Current aspirin use, No. (%)	7141 (27.8)	591 (28.4)	335 (29.4)	273 (29.3)	387 (27.5)
Family history of diabetes, No. (%)	5986 (23.3)	468 (22.5)	249 (21.9)	228 (24.5)	307 (21.8)
Family history of myocardial infarction, No. (%)	8041 (31.3)	647 (31.1)	355 (31.2)	317 (34.0)	470 (33.4)

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Abbreviations: AHEI-2010, Alternate Healthy Eating Index 2010; BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); MET, metabolic equivalent of task; TV, television.

^{^a}

Values are standardized to the age distribution of the study population except for age. Percentages may not sum to 100 because of rounding.

^{^b}

Includes African American, American Indian or Alaska Native, Asian, Hispanic, and other race or ethnicity not captured by the listed categories.

Association Between Resistance Training and T2D Risk

During a mean (SD) follow-up of 19.2 (5.0) years, we documented 10 038 incident T2D cases across the 3 cohorts. In pooled analyses, compared with no resistance training, the multivariable-adjusted HRs for increasing categories of resistance training were 0.83 (95% CI, 0.79-0.88) for greater than 0 to less than 0.5 hours per week, 0.83 (95% CI, 0.77-0.90) for 0.5 to less than 1.0 hours per week, 0.73 (95% CI, 0.67-0.80) for 1.0 to less than 2.0 hours per week, and 0.73 (95% CI, 0.66-0.81) for 2.0 hours or greater per week in model 3 (P < .001 for trend; P < .001 for nonlinearity) (Table 2 and eFigure 2 in Supplement 1). Similar inverse associations between higher levels of resistance training and T2D risk were observed in each cohort (eTable 3 in Supplement 1). Additional adjustment for baseline waist circumference, intentional weight loss, or time-updated BMI resulted in only small to modest attenuation of the estimates, and the inverse association at higher resistance training levels remained (eTable 4 in Supplement 1).

Table 2. Association Between Resistance Training and Type 2 Diabetes in Pooled Prospective Cohorts.

Variable	Resistance training, h/wk					P value for trend	P value for nonlinearity
Variable	0	>0 to <0.5	0.5 to <1.0	1.0 to <2.0	≥2.0	P value for trend	P value for nonlinearity
No. of cases	6540	1706	727	641	424	NA	NA
Person-years	1 281 755	514 961	243 087	257 810	183 085	NA	NA
Model, HR (95% CI)^a
1^b	1 [Reference]	0.71 (0.68-0.76)	0.62 (0.58-0.67)	0.50 (0.46-0.55)	0.46 (0.42-0.51)	<.001	<.001
2^c	1 [Reference]	0.79 (0.74-0.83)	0.72 (0.67-0.78)	0.60 (0.55-0.66)	0.56 (0.51-0.62)	<.001	<.001
3^d	1 [Reference]	0.83 (0.79-0.88)	0.83 (0.77-0.90)	0.73 (0.67-0.80)	0.73 (0.66-0.81)	<.001	<.001

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Abbreviations: HR, hazard ratio; NA, not applicable.

^{^a}

A 2-year lag between resistance training assessment and start of follow-up was applied in all models.

^{^b}

Adjusted for age (months), calendar year, and cohort.

^{^c}

Adjusted for covariates in model 1 plus race (White or other), family history of diabetes (yes or no), smoking status (never, past, or current [1-14, 15-24, or ≥25 cigarettes per day]), alcohol consumption (none, 0.1-4.9, 5-14.9, or ≥15 g/d), total calorie intake (quintile), Alternate Healthy Eating Index 2010 score (quintile), and menopausal status (premenopausal or postmenopausal [never, past, or current postmenopausal hormone use]).

^{^d}

Adjusted for model 2 covariates plus aerobic activity (none, 0.1-7.5, 7.5-14.9, 15-29.9, or ≥30 metabolic equivalent of task–hours per week).

In stratified analyses, the inverse associations were broadly consistent across strata of age, BMI, alcohol intake, Alternate Healthy Eating Index 2010 score, family history of diabetes, menopausal status (women only), and diagnosis period (P ≥ .05 for interaction) (eTable 5 in Supplement 1). Among participants who met aerobic activity guidelines (≥15 MET-h/wk), 2 or more hours per week of resistance training was associated with lower T2D risk, and similar patterns were observed when restricting our analyses to participants who achieved 30 or more MET-hours per week, although estimates were less precise in the highest aerobic stratum (≥45 MET-h/wk) (eTables 6-8 in Supplement 1).

Joint Associations With BMI and Other Lifestyle Behaviors

Higher BMI was consistently associated with greater T2D risk, and resistance training was associated with lower risk within each BMI category but did not substantially alter the BMI-related gradient (Figure 1A and eTable 9 in Supplement 1). In joint analysis of resistance training and walking, the combination of 1 or more hours per week of resistance training and 3.5 or more hours per week of brisk walking was associated with the greatest risk reduction compared with less than 1 hour per week of resistance training and less than 3.5 hours per week of walking at a nonbrisk pace (HR, 0.42; 95% CI, 0.36-0.48) (eTable 10 in Supplement 1). In joint analyses of resistance training, aerobic activity, and sedentary behavior, meeting all 3 lifestyle recommendations—15 or more MET-hours per week of aerobic activity, 1 or more hours per week of resistance training, and less than 2 hours per day of TV viewing—was associated with the lowest risk of T2D (HR 0.38; 95% CI, 0.34-0.42) compared with meeting none of these recommendations (Figure 1B and eTables 11 and 12 in Supplement 1). Similar patterns were observed when total sedentary time, defined as less than the pooled median (23 h/wk), was used instead of TV viewing (eTable 13 in Supplement 1).

Figure 1. — Data are representative of all 3 cohorts (the Nurses’ Health Study, the Nurses’ Health Study II, and the Health Professionals Follow-Up Study). Meeting the recommendation for RT was defined as performing 1.0 or more hour per week; for aerobic activity, engaging in 15 or more metabolic equivalent of task (MET)–hours per week; and for sedentary TV viewing, less than 2 hours per day. All models were adjusted for the covariates included in multivariable model 3 in Table 2, except that the joint analysis with other behaviors including aerobic physical activity (PA) was adjusted according to multivariable model 2 in Table 2. A 2-year lag between resistance training assessment and start of follow-up was applied in all models. BMI is calculated as weight in kilograms divided by height in meters squared. HR indicates hazard ratio.

Anatomical Scope and Long-Term Consistency of Resistance Training

For anatomical scope, participants who engaged exclusively in upper limb resistance training were at lower risk of T2D (HR, 0.75; 95% CI, 0.69-0.83), and those performing both upper and lower limb training also had lower risk (HR, 0.83; 95% CI, 0.78-0.88) compared with participants with no training (Figure 2A and eTable 14 in Supplement 1). When cumulative mean resistance training was examined jointly with long-term consistency, lower T2D risk was observed primarily among participants who both accumulated higher mean weekly resistance training and maintained it consistently over time (Figure 2B and eTables 15 and 16 in Supplement 1). The lowest risk was seen among participants with consistency of 75.0% or greater and cumulative mean of 1 hour per week (HR 0.65; 95% CI, 0.60-0.72).

Figure 2. — Data are representative of 2 of the 3 cohorts (the Nurses’ Health Study and the Nurses’ Health Study II). Consistency was defined as the proportion of returned questionnaires on which participants reported engaging in RT for 0.5 or more hours per week. Cumulative mean RT was defined as the mean weekly hours of RT across all questionnaires to each follow-up cycle. The joint category consistency or 75.0% or greater and cumulative mean less than 0.5 hours per week is not shown because of the extremely small number of person-years (n = 50) and zero incident type 2 diabetes cases, which precluded reliable estimation of the hazard ratio (HR). All models were adjusted for the covariates included in multivariable model 3 in Table 2. A 2-year lag between resistance training assessment and start of follow-up was applied in all models.

Resistance Training Trajectories and T2D Risk

In the NHS II, 5 distinct trajectories of resistance training were identified: consistently low, high to low, low to high, fluctuating, and consistently high (eFigure 3 and eTable 17 in Supplement 1). Compared with the consistently low trajectory, the consistently high trajectory had a lower risk (HR, 0.58; 95% CI, 0.45-0.74); the high to low trajectory and low to high trajectory were also associated with lower risk (HRs, 0.82 [95% CI, 0.67-0.99] and 0.79 [95% CI, 0.66-0.94], respectively), whereas the fluctuating trajectory was not (HR, 1.02; 95% CI, 0.86-1.21) (Table 3). Additional models further adjusting separately for baseline waist circumference, intentional weight loss, or baseline BMI attenuated the associations modestly but did not materially change the overall pattern (eTable 18 in Supplement 1).

Table 3. Association Between Resistance Training Trajectories and Type 2 Diabetes in the Nurses’ Health Study II^a.

Variable	Resistance training trajectory
Variable	Consistently low	High to low	Low to high	Fluctuating	Consistently high
No. of cases	1155	120	151	171	71
Person-years	301 336	52 421	71 513	64 652	60 196
Model, HR (95% CI)
1^b	1 [Reference]	0.62 (0.51-0.75)	0.59 (0.50-0.70)	0.78 (0.66-0.91)	0.32 (0.25-0.41)
2^c	1 [Reference]	0.67 (0.56-0.81)	0.64 (0.54-0.76)	0.84 (0.72-0.99)	0.40 (0.31-0.51)
3^d	1 [Reference]	0.82 (0.67-0.99)	0.79 (0.66-0.94)	1.02 (0.86-1.21)	0.58 (0.45-0.74)

Open in a new tab

Abbreviation: HR, hazard ratio.

^{^a}

For trajectory analyses, follow-up began at age 60 years in the Nurses’ Health Study II, and covariates were adjusted using their baseline values at age 60 years.

^{^b}

Adjusted for age (months).

^{^c}

Adjusted for model 1 covariates plus race (White or other), family history of diabetes (yes or no), smoking status (never, past, or current [1-14, 15-24, or ≥25 cigarettes per day]), alcohol consumption (none, 0.1-4.9, 5-14.9, or ≥15 g/d), total calorie intake (quintile), Alternate Healthy Eating Index 2010 score (quintile), and menopausal status (premenopausal or postmenopausal [never, past, or current postmenopausal hormone use]).

^{^d}

Adjusted for model 2 covariates plus aerobic activity (none, 0.1-7.5, 7.5-14.9, 15-29.9, or ≥30 metabolic equivalent of task–hours per week).

Sensitivity Analyses

Results were similar when using simple updated models, using cumulative means without a time lag, and after excluding participants with high aerobic activity (>30 MET-h/wk) or those with baseline chronic obstructive pulmonary disease or arthritic disease (eTable 19 in Supplement 1). After accounting for time-varying confounding using marginal structural models with inverse probability weighting (eTable 20 in Supplement 1), resistance training remained inversely associated with T2D; compared with no resistance training, the estimated HR was 0.56 (95% CI, 0.41-0.77) for at least 2 hours per week.

Discussion

To our knowledge, this is the first prospective study to comprehensively examine the multidimensional association between resistance training and T2D across 3 long-running cohorts with repeated exposure assessments. Using nearly 2 decades of follow-up, we examined not only overall resistance training volume and dose-response shape, but also behavioral patterns (anatomical scope, long-term consistency, and life-course trajectories) and joint associations with walking, aerobic activity, and sedentary time.

Our findings align with and extend prior evidence that resistance training is inversely associated with T2D risk.^4,5,6,7 This association is biologically plausible given the effects of resistance training on muscle mass and function, adiposity, inflammation, and insulin sensitivity, which complement the benefits of aerobic activity.^20,21,22 However, a key question is how much resistance training adds beyond aerobic activity alone. In our primary analyses, the associations of resistance training with T2D were attenuated but remained inverse even after adjustment for total aerobic activity, indicating that resistance training is associated with lower T2D risk above and beyond overall aerobic activity. Collectively, these findings suggest that within an already active population, resistance training is associated with additional reductions in T2D risk.

The joint analyses further clarify how resistance training fits within broader patterns of physical activity and sedentary behavior. Combinations of brisk walking and resistance training were associated with the lowest T2D risk, and participants who met recommendations for both aerobic activity and resistance training while also limiting sedentary TV viewing had substantially lower risk than those who met none of these recommendations. Taken together, these findings underscore the importance of integrated prevention approaches that combine structured resistance and aerobic activity with reductions in sedentary time to optimize diabetes risk.

We further add novel insights from a more comprehensive perspective incorporating consistency and long-term trajectories.^4,6,7 Although 1 or more hour per week of resistance training corresponds to public health guidelines,³ our findings suggest that sustained participation may be more critical than volume alone. Participants who maintained high consistency over time experienced substantial risk reductions, even with modest training levels, whereas those with low consistency showed little difference in T2D risk regardless of reported volume. Trajectory analyses in the NHS II similarly indicated that consistently high and generally increasing resistance training patterns were associated with lower T2D risk, whereas a fluctuating moderate pattern was not. These longitudinal patterns cannot be captured by single time point measures and highlight the importance of stable engagement across midlife. With respect to anatomical scope, both upper limb only and combined upper and lower limb resistance training were associated with lower T2D risk, although differences between them should be interpreted cautiously given subgroup sample sizes and potential differences in total volume.

Strengths and Limitations

Strengths of our study include the use of large, well-characterized cohorts of women and men with long follow-up; repeated assessments of resistance training, other physical activity domains, and covariates; the use of lagged analyses to mitigate reverse causation^9,23; a specific focus on long-term resistance training patterns across midlife (volume, consistency, and trajectories); and comprehensive joint analyses of resistance training with walking, total aerobic activity, and sedentary behaviors.

This study also has several limitations. First, resistance training was self-reported and lacked detailed information on training modality, intensity, and supervision. However, previous validation studies in similar populations support the reliability of self-reported physical activity.^6,9,19 Moreover, capturing resistance training as it is performed in the general population may offer complementary evidence that reflects typical practice. Second, our descriptive comparisons of characteristics across resistance training categories, consistency groups, and joint behavior pattern groups indicated that participants with higher resistance training volume and consistency and multiple healthy behaviors tended to have more favorable profiles. Thus, despite extensive covariate adjustment, residual confounding cannot be ruled out (eg, health consciousness, access to care, and social support). Third, most participants were White health care professionals with specific ages, which enhances internal validity but may limit generalizability to more diverse populations. The modest differences we observed between participants with and without resistance training information, together with the proportion of missing resistance training data, also raise the possibility of selection bias. Fourth, unmeasured prediabetes at baseline could have occurred; however, this is unlikely to fully explain the observed associations, given the use of a 2-year lag between exposure assessment and case ascertainment. Moreover, individuals diagnosed with prediabetes may be more likely to initiate rather than discontinue resistance training, so any residual reverse causation would likely tend to bias the associations toward the null rather than create a spurious inverse association. Finally, our analyses of upper vs lower limb training and of training trajectories were based on relatively small numbers of T2D cases in some subgroups and should therefore be interpreted with caution. The observed differences may partly reflect differences in total resistance training volume and comorbidities, as well as patterns of resistance training in the general population in older adults.

Conclusions

In this prospective cohort study, resistance training was associated with a substantially lower risk of T2D, particularly when performed consistently over midlife and combined with adequate aerobic activity and limited sedentary TV viewing. These findings support the inclusion of resistance training as a key component of lifestyle recommendations for diabetes prevention.

Supplement 1.

eMethods. Study Population, Assessments, Ascertainment of T2D, Adiposity-Related Variables, and Analyses

eTable 1. Baseline Characteristics by Nonresponse Before the End of the Study

eTable 2. Baseline Characteristics by Availability of Resistance Training Information in Each Cohort

eTable 3. Association Between Resistance Training and Risk of Type 2 Diabetes in Each Cohort

eTable 4. Association Between Resistance Training and Type 2 Diabetes With Additional Adjustment for Baseline Waist Circumference, Intentional Weight Loss, and Time-Updated BMI in Pooled Cohorts (NHS, NHS II, and HPFS)

eTable 5. Stratified Analyses of the Association Between Resistance Training and Risk of Type 2 Diabetes in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 6. Association Between Resistance Training and Risk of Type 2 Diabetes Among Participants Meeting Aerobic Activity Guidelines (≥15 MET-h/wk) in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 7. Association Between Resistance Training and Risk of Type 2 Diabetes Among Participants Meeting at Least Twice the Aerobic Activity Guidelines (≥30 MET-h/wk) in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 8. Association Between Resistance Training and Risk of Type 2 Diabetes Among Participants Meeting at Least 3 Times the Aerobic Activity Guidelines (≥45 MET-h/wk) in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 9. Joint Association of Resistance Training and Body Mass Index Category With Risk of Type 2 Diabetes in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 10. Joint Associations of Resistance Training and Walking With Risk of Type 2 Diabetes in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 11. Time updated Characteristics During Follow-up According to Joint Categories of Aerobic Activity, Resistance Training, and Sedentary Television Viewing in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 12. Joint Associations of Meeting Recommendations for Aerobic Activity and Resistance Training and Sedentary Television Viewing Time With Risk of Type 2 Diabetes in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 13. Joint Associations of Meeting Recommendations for Aerobic Activity and Resistance Training and Categories of Total Sedentary Time With Risk of Type 2 Diabetes in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 14. Joint Association of Upper- and Lower-Limb Resistance Training and Risk of Type 2 Diabetes in Pooled Prospective Cohorts (NHS and NHS II)

eTable 15. Time Updated Characteristics During Follow-up According to Cumulative Mean and Consistency of Resistance Training in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 16. Joint Association of Cumulative Average and Consistency of Resistance Training With Risk of Type 2 Diabetes in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 17. Characteristics of Resistance Training Trajectory Groups at Ages 40, 52, and 60 Years in NHS II

eTable 18. Association Between Resistance Training Trajectories and Type 2 Diabetes With Additional Adjustment for Baseline Waist Circumference, Intentional Weight Loss, and BMI in NHS II

eTable 19. Sensitivity Analyses of Association Between Resistance Training and Type 2 Diabetes in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eTable 20. Association of Resistance Training With Risk of Type 2 Diabetes in Pooled Cohorts (NHS, NHS II, and HPFS) Estimated Using Marginal Structural Models With Inverse Probability Weighting

eFigure 1. Flow Diagram of Participant Inclusion in NHS, NHS II, and HPFS

eFigure 2. Dose-Response Relationship Between Resistance Training and Type 2 Diabetes in Pooled Prospective Cohorts (NHS, NHS II, and HPFS)

eFigure 3. Resistance Training Trajectories, Ages 40 to 60 Years, NHS II

eReferences

jamanetwopen-e2619420-s001.pdf^{(868.5KB, pdf)}

Supplement 2.

Data Sharing Statement

jamanetwopen-e2619420-s002.pdf^{(16.3KB, pdf)}

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