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Cited by 72Physical Activity and HealthDiabetes, Cardiovascular Risks, and LipoproteinsDiabetes Management and Research

The impact of physical activity on the prevention of type 2 diabetes: Evidence and lessons learned from the Diabetes Prevention Program, a long-standing clinical trial incorporating subjective and objective activity measures

Open access
Kriska, Andrea M., Rockette-Wagner, Bonny, Edelstein, Sharon L., Bray, George A., Delahanty, Linda M., Hoskin, Mary A., Horton, Edward S., Venditti, Elizabeth M. +586 more·2021·Diabetes Care
DOI 10.2337/dc20-1129PMC PMC7783946
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Abstract

OBJECTIVE: Across the Diabetes Prevention Program (DPP) follow-up, cumulative diabetes incidence remained lower in the lifestyle compared with the placebo and metformin randomized groups and could not be explained by weight. Collection of self-reported physical activity (PA) (yearly) with cross-sectional objective PA (in follow-up) allowed for examination of PA and its long-term impact on diabetes prevention. RESEARCH DESIGN AND METHODS: Yearly self-reported PA and diabetes assessment and oral glucose tolerance test results (fasting glucose semiannually) were collected for 3,232 participants with one accelerometry assessment 11–13 years after randomization (n = 1,793). Mixed models determined PA differences across treatment groups. The association between PA and diabetes incidence was examined using Cox proportional hazards models. RESULTS: There was a 6% decrease (Cox proportional hazard ratio 0.94 [95% CI 0.92, 0.96]; P < 0.001) in diabetes incidence per 6 MET-h/week increase in time-dependent PA for the entire cohort over an average of 12 years (controlled for age, sex, baseline PA, and weight). The effect of PA was greater (12% decrease) among participants less active at baseline (<7.5 MET-h/week) (n = 1,338) (0.88 [0.83, 0.93]; P < 0.0001), with stronger findings for lifestyle participants. Lifestyle had higher cumulative PA compared with metformin or placebo (P < 0.0001) and higher accelerometry total minutes per day measured during follow-up (P = 0.001 and 0.047). All associations remained significant with the addition of weight in the models. CONCLUSIONS: PA was inversely related to incident diabetes in the entire cohort across the study, with cross-sectional accelerometry results supporting these findings. This highlights the importance of PA within lifestyle intervention efforts designed to prevent diabetes and urges health care providers to consider both PA and weight when counseling high-risk patients.

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Crossref · 10.2337/dc20-1129

Cites

25 of 25 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

12 of 28 cited sources checked · 3 supported · 1 flagged · accuracy not yet measured

  • Premisecitation
    § Correlation of Accelerometer and MAQ Activity Levels

    In a previous study, moderate/vigorous-intensity leisure activity from a past-week version of the MAQ was more strongly correlated with accelerometer-recorded bouts of moderate/vigorous-intensity physical activity over the same week (r = 0.69-0.76, P < 0.0001).

    “In a previous study in which the two instruments were examined over similar time frames, moderate/ vigorous-intensity leisure activity from a past week version of the MAQ was more strongly correlated with bouts of moderate/vigorous-intensity PA recorded by accelerometers collected over the same week (r 5 0.69-0.76,P , 0.0001) (16).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [16] Pettee Gabriel, 2011, Reliability and convergent validity of the past-week Modifiable Activity Questionnaire, Public Health Nutr source

      The Validity section reports significant correlations between past-week MAQ leisure activity and accelerometer-recorded bouts of moderate-to-vigorous activity, including time-matched data. However, the available passages do not establish the claimed r = 0.69–0.76 or P < 0.0001 for those same-week bouts; the Validity text states P < 0.001 for bouts. (LLM, conf=0.78)

      Experimental — accuracy not yet measured
  • Premisecitation
    § PA

    Only objective measures, such as the accelerometer, can validly measure activities of light intensity.

    “Only objective measures, such as the accelerometer, can validly measure activities of light intensity (9,10).”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [9] Shephard, 2003, Limits to the measurement of habitual physical activity by questionnaires, Br J Sports Med source

      The “Types of activity” section says many questionnaires have floor effects and may omit activities less intense than brisk walking. The “Sensitivity” section says accelerometers are generally more sensitive than questionnaires, but the paper does not establish that only objective measures can validly measure light-intensity activity; its “Reliability” section also describes limitations of motion sensors. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [10] Haskell, 2012, Physical activity by self-report: a brief history and future issues, J Phys Act Health source

      The ‘Looking Ahead—Measurement of Sitting or Light-Intensity Activity’ section says existing self-report tools are very poor at estimating time spent in low-intensity activity. But the paper does not support ‘only’: ‘The Limited Evolution of Physical Activity Self-Report’ says some self-report instruments reasonably classify light-intensity activity, while ‘Looking Ahead’ notes that accelerometers also have difficulty distinguishing sitting from other light-intensity activity. Page numbers are unavailable in our copy. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
  • Premisecitation
    § Abstract

    During an average 10 years of follow-up since DPP randomization, between-group differences in cumulative diabetes incidence persisted, although to a lesser degree than at DPP end.

    “During an average 10 years of follow-up since DPP randomization, the between-group differences in cumulative diabetes incidence persisted, although to a lesser degree than at DPP end (2).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [2] Knowler, 2009, 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study, Lancet source
  • Findingown data
    § Abstract

    Across all treatment arms combined, there was a 6% reduction in diabetes incidence for each 6 MET-h/week increase in reported leisure physical activity over an average 12-year follow-up, adjusted for age, sex, baseline physical activity, and baseline weight (HR 0.94 [95% CI 0.92, 0.96]; P < 0.001).

    “There was a 6% decrease (Cox proportional hazard ratio 0.94 [95% CI 0.92, 0.96]; P < 0.001) in diabetes incidence per 6 MET-h/week increase in time-dependent PA for the entire cohort over an average of 12 years (controlled for age, sex, baseline PA, and weight).”
    • Also stated in: § PA Levels and Diabetes Incidence: MAQ · plain
      “Across all treatment arms combined, there was a 6% reduction (HR 0.94 [95% CI 0.92, 0.96]; P , 0.001) in diabetes incidence for each 6 MET-h/week (;17 min of brisk walking per day) of reported leisure activity over the 12-year follow-up period (Fig. 2).”
    Quote in the paperSubstantial claim
  • Findingown data
    § PA Levels and Diabetes Incidence: MAQ

    Among lifestyle participants not meeting the leisure activity goal at baseline (n = 451), the relationship was strongest, with a 20% reduction (HR 0.80 [95% CI 0.72, 0.89]; P < 0.0001).

    “Similar to the analyses in all treatment arms combined, the relationship was strongest (20% reduction) in those lifestyle participants who reported not meeting the leisure activity goal at baseline (n 5 451, 0.80 [0.72, 0.89]; P , 0.0001).”
    Quote in the paperNot a substantial claim
  • May combine two claims. 15
  • Classified as probably not a substantial claim. 12

  • May combine two claims.

    Study design and conductcitation
    § Statistical Analysis

    Diet differences across intervention groups were negligible 9 years after randomization, so diet was not included in the model.

    “Although diet was assessed by food frequency questionnaire intermittently throughout DPP and DPPOS, there were negligible differences across intervention groups 9 years after randomization and, therefore, was not included in the model (15).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [15] Jaacks, 2014, Long-term changes in dietary and food intake behaviour in the Diabetes Prevention Program Outcomes Study, Diabet Med source

      The Results (page not provided) report that lifestyle participants had lower total and saturated fat intake and higher fiber intake than the other groups up to nine years after randomization, contrary to the claim that dietary differences were negligible. The Methods (page not provided) describe models used to analyze dietary intake; the paper does not give the claimed rationale for excluding diet from the citing authors’ model. (LLM, conf=0.86)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured

  • May combine two claims.

    Study design and conductcitation
    § CONCLUSIONS

    The longitudinal measure of activity was subjective, although the MAQ has been widely used and validated against several objective measures, including accelerometry.

    “Another limitation involves the subjective nature of the longitudinal measure of activity, although the MAQ has been widely used and validated against several objective measures, including accelerometry (16,22,23).”
    Quote in the paperNot a substantial claim1 of 3 sources checked
    • cites [16] Pettee Gabriel, 2011, Reliability and convergent validity of the past-week Modifiable Activity Questionnaire, Public Health Nutr source
    • cites [22] Momenan, 2012, Reliability and validity of the Modifiable Activity Questionnaire (MAQ) in an Iranian urban adult population, Arch Iran Med
    • cites [23] Jacobi, 2009, Relationships of self-reported physical activity domains with accelerometry recordings in French adults, Eur J Epidemiol source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § PA

    The MAQ was not designed to measure light-intensity activity because of concerns regarding the accuracy of recall of light-intensity activity.

    “Although light-intensity activity comprises the largest percentage of the average adults' day, the MAQ was not designed to measure activities that comprise that level of intensity because of concerns regarding the accuracy of recall of light-intensity activity.”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [9] Shephard, 2003, Limits to the measurement of habitual physical activity by questionnaires, Br J Sports Med source

      The Reliability section says recall problems are particularly acute when activity intensity is low, and Types of activity says some questionnaires omit low-intensity activities. Neither passage identifies the MAQ or says why it was designed to omit them; the paper’s general concern does not establish that specific design rationale. Page numbers are unavailable in our copy. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
    • cites [10] Haskell, 2012, Physical activity by self-report: a brief history and future issues, J Phys Act Health source

      In “Looking Ahead—Measurement of Sitting or Light-Intensity Activity” (page unavailable), the paper says adults recalled light-intensity activity poorly and that developers of the Stanford 7-day physical activity recall chose not to ask about it directly. This supports the stated concern about recall accuracy, but the passage does not establish that the MAQ was designed to omit light-intensity activity for that reason. (LLM, conf=0.86)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation
    § RESEARCH DESIGN AND METHODS

    The incidence of diabetes was reduced in the lifestyle intervention and metformin arms compared with placebo by 58% and 31%, respectively, after a mean of 2.8 years of follow-up during the masked treatment phase.

    “The incidence of diabetes was reduced in the lifestyle intervention and metformin arms compared with placebo by 58% and 31%, respectively, after a mean of 2.8 years of follow-up during the masked treatment phase.”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites [1] Knowler, 2002, Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin, N Engl J Med source
    • cites [2] Knowler, 2009, 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study, Lancet source
    • cites [4] Rockette-Wagner, 2017, Activity and sedentary time 10 years after a successful lifestyle intervention: the Diabetes Prevention Program, Am J Prev Med source

      The Methods (Study Sample) report 58% lower diabetes incidence in the lifestyle arm and 31% lower incidence in the metformin arm versus placebo. However, they say the DPP ended after an average follow-up of 3.2 years, with results published after 2.8 years; they do not describe 2.8 years as the mean follow-up during a masked treatment phase. (LLM, conf=0.88)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation
    § RESEARCH DESIGN AND METHODS

    The DPP was a multicenter (27 centers), randomized controlled clinical trial designed to determine whether treatment with lifestyle intervention or metformin could prevent or delay type 2 diabetes in high-risk adults.

    “The DPP (1996-2001) was a multicenter (27 centers), randomized controlled clinical trial designed to determine whether treatment with lifestyle intervention or metformin could prevent or delay type 2 diabetes in high-risk adults.”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites [1] Knowler, 2002, Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin, N Engl J Med source
    • cites [2] Knowler, 2009, 10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study, Lancet source

      The Introduction describes the DPP as a US multicentre randomised clinical trial testing whether lifestyle intervention or metformin prevented or delayed type 2 diabetes in high-risk adults. Methods > Participants reports enrolment beginning in 1996 and masked treatment ending in 2001. Our copy does not specify 27 centres, so that detail is unsupported. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
    • cites [4] Rockette-Wagner, 2017, Activity and sedentary time 10 years after a successful lifestyle intervention: the Diabetes Prevention Program, Am J Prev Med source

      The Methods (Study Sample; page not provided) describes the DPP as a multicenter randomized controlled trial testing whether metformin or lifestyle intervention could prevent or delay type 2 diabetes in high-risk adults, and places the DPP cohort in 1996–2001. It does not substantiate the claimed 27 centers; it instead refers to 26 DPP clinical centers in the later accelerometer study. (LLM, conf=0.86)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Findingown data
    § PA Levels and Diabetes Incidence: MAQ

    Treatment arm or race/ethnicity in the model did not affect the results.

    “Treatment arm or race/ethnicity in the model did not affect the results.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § PA Levels by Treatment Arm: MAQ

    Adjusted mean activity peaked in the lifestyle arm after 1 year of intervention but remained relatively unchanged from baseline in the metformin and placebo groups at that time.

    “Adjusted mean values for activity peaked in the lifestyle arm after 1 year of intervention (Fig. 1) but remained relatively unchanged from baseline in the metformin and placebo groups at that time.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data
    § DPPOS Accelerometer Validation Substudy

    At the time of ancillary study data collection, ancillary participants with valid accelerometer data (n = 1,622) had a mean age of 63.7 years (SD = 9.8), 70% were female, and 47.1% had self-reported race/ethnicity other than White, non-Hispanic.

    “At the time of ancillary study data collection, ancillary participants with valid data (n 5 1,622) had a mean age of 63.7 (SD 5 9.8) years, 70% were female, and 47.1% had self-reported race/ethnicity other than White, non-Hispanic.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § PA Levels by Treatment Arm: MAQ

    When examined separately for DPP and DPPOS, differences in leisure activity across treatment groups were significant during the DPP and during DPPOS follow-up, with activity slightly higher in the lifestyle group during DPPOS follow-up.

    “When examined separately for DPP and DPPOS, the differences in leisure activity across treatment groups were significant during the DPP (P-dif , 0.0001), with activity slightly higher in the lifestyle group during DPPOS follow-up (P-dif , 0.0001).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data
    § DPPOS Accelerometry Validation Substudy

    The mean follow-up from DPP randomization to the DPPOS accelerometry study was 12 years (SD = 1.0).

    “The mean follow-up from DPP randomization to the DPPOS accelerometry study was 12 (SD 5 1.0) years.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § Participants

    The DPP cohort comprised 3,234 adults (68% women, 45% from ethnic/racial minority groups, age 25 years or older) at high risk because of elevated fasting plasma glucose, impaired glucose tolerance, and BMI at least 24 kg/m2.

    “The diverse DPP cohort comprised 3,234 adults (68% women, 45% from ethnic/racial minority groups, age $25 years) (Table 1) at high risk because of an elevated fasting plasma glucose (5.3-6.9 mmol/L), impaired glucose tolerance (2-h postload glucose 7.8-11.0mmol/L), and BMI $24 kg/m 2 .”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § DPPOS Accelerometer Validation Substudy

    The lifestyle participants had slightly higher values for both light- and moderate/vigorous-intensity leisure activity compared with metformin and placebo participants.

    “The lifestyle participants had slightly higher values for both light-and moderate/vigorous-intensity leisure activity compared with metformin and placebo participants (Table 2).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § PA

    The MAQ assesses past-year moderate/vigorous-intensity leisure physical activities common to the population in question.

    “The MAQ assesses past year, moderate/vigorous-intensity leisure PAs common to the population in question (7,8).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [7] Kriska, 1997, Modifiable Activity Questionnaire, Med Sci Sports Exerc source
    • cites [8] Kriska, 1990, Development of questionnaire to examine relationship of physical activity and diabetes in Pima Indians, Diabetes Care source

  • May combine two claims.

    Study design and conductreasoning
    § CONCLUSIONS

    The DPP lifestyle intervention comprises weight and activity goals and was not designed to test the individual contribution of either goal alone.

    “Included in the limitations of this effort is the fact that the DPP lifestyle intervention, not unlike other published lifestyle investigations in the literature, comprises weight and activity goals and was not designed to test the individual contribution of either goal alone.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation
    § CONCLUSIONS

    A review of community translation studies documented that only about one-half of published studies include physical activity change in their results, making it difficult to assess the impact of activity on health outcomes in these translation efforts.

    “Although these community translation studies have adapted the same DPP lifestyle goals of weight loss and increased activity, a review of the translation literature documented that only about onehalf of these published studies include PA change in their results (24), making it difficult to assess the impact of activity on health outcomes in these translation efforts.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [24] Eaglehouse, 2015, Evaluation of physical activity reporting in community Diabetes Prevention Program lifestyle intervention efforts: a systematic review, Prev Med source

  • Classified as probably not a substantial claim.

    Study design and conductown data
    § Statistical Analysis

    Models were adjusted for age, sex, race/ethnicity, baseline activity, and baseline and, in some models, time-dependent weight.

    “Models were adjusted for age, sex, race/ethnicity, baseline activity, and baseline and, in some models, timedependent weight.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § DPPOS Accelerometer Validation Substudy

    A total of 1,622 ancillary study participants (90.4% of 1,793) had at least 4 valid days of accelerometer recording.

    “A total of 1,622 ancillary study participants (90.4% of 1,793 participants) had at least 4 valid days of accelerometer recording (on the basis of triaxial data).”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductown data
    § Statistical Analysis

    Models were adjusted for baseline leisure activity, age, and sex.

    “Models were adjusted for baseline leisure activity, age, and sex.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data
    § CONCLUSIONS

    In this cohort, physical activity was inversely related to the development of diabetes over the long term and remained significant even when adjusted for weight change.

    “In this cohort, PA was inversely related to the development of diabetes over the long term and remain significant even when adjusted for weight change.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § Participants

    The accelerometry ancillary study cohort included 1,793 individuals from the 1,932 possible active DPPOS participants (93%).

    “The resulting accelerometry ancillary study cohort included 1,793 individuals from the 1,932 possible active DPPOS participants (93%).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation
    § CONCLUSIONS

    Change in activity from baseline to DPP end, previously shown not to be significantly related to diabetes development, is significant if the analyses are limited to those less active at baseline.

    “Change in activity from baseline to DPP end (3.2 years) previously shown not to be significantly related to diabetes development (3) is significant if the analyses are limited to those less active at baseline.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [3] Hamman, 2006, Effect of weight loss with lifestyle intervention on risk of diabetes, Diabetes Care source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation
    § PA

    Four or more valid days with at least 10 hours of wear time each day were required for inclusion in the accelerometry analyses.

    “Four or more valid days with $10 h of wear time each day were required for inclusion in the analyses (11).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [11] Trost, 2005, Conducting accelerometer-based activity assessments in field-based research, Med Sci Sports Exerc source

  • May combine two claims.

    Study design and conductown data
    § CONCLUSIONS

    Unique strengths of this investigation include yearly collected subjective activity measures over a long follow-up period and support for persistent treatment group differences in activity from cross-sectional accelerometry at follow-up.

    “Among the unique strengths of this current investigation are the yearly collected subjective activity measures over a long follow-up period and the support for persistent treatment group differences in activity provided by cross-sectional results obtained from accelerometry at follow-up by this widely accepted objective measure.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § Participants

    A total of 2,776 of 3,149 (88%) surviving participants of the original DPP joined the DPPOS follow-up study.

    “A total of 2,776 of the 3,149 (88%) surviving participants of the original DPP joined the DPPOS follow-up study (Supplementary Fig. 2).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § DPPOS Follow-Up (2002-Present)

    Attendance at DPPOS lifestyle sessions averaged 20% per session for all groups.

    “Attendance varied across the study and decreased during the DPPOS follow-up period, with attendance at DPPOS classes averaging 20% per session for all groups.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data
    § DPPOS Accelerometer Validation Substudy

    There were no other significant differences in key covariates across accelerometer compliance groups.

    “There were no other significant differences in key covariates across compliance groups (data not shown).”
    Quote in the paperNot a substantial claim
26 of 26

  • The paper relies on this without support.

    The impact of change in physical activity levels beyond the end of the DPP trial period has not yet been reported in long-term follow-up.

    “The impact of change in PA levels beyond the end of the DPP trial period has not yet been reported in long-term follow-up.”

  • The paper relies on this without support.

    Accelerometers capture total time spent in physical activities of all intensities, including lower-intensity and unstructured activities.

    “On the other hand, accelerometers do capture total time spent in PAs of all intensities, including lower-intensity and unstructured activities.”

  • The paper relies on this without support.

    The MAQ and accelerometer capture different intensities of physical activity, with the accelerometer measuring total physical activity and the questionnaire mainly assessing moderate and vigorous intensity.

    “As stated earlier, the MAQ and accelerometer capture different intensities of PA, with the accelerometer measuring total PA (light, moderate, and vigorous) and the questionnaire mainly assessing activities of moderate and vigorous intensity.”
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Kriska, A. M., Rockette-Wagner, B., Edelstein, S. L., Bray, G. A., Delahanty, L. M., Hoskin, M. A., Horton, E. S., Venditti, E. M., Knowler, W. C., DPP Research Group, Bray, G. A., Gadde, K., Culbert, I. W., Arceneaux, J., Chatellier, A., Dragg, A., Champagne, C. M., Duncan, C., Eberhardt, B., Greenway, F., Guillory, F. G., Herbert, A. A., Jeffirs, M. L., Kennedy, B. M., Levy, E., Lockett, M., Lovejoy, J. C., Morris, L. H., Melancon, L. E., Ryan, D. H., Sanford, D. A., Smith, K. G., Smith, L. L., St. Amant, J. A., Tulley, R. T., Vicknair, P. C., Williamson, D., Zachwieja, J. J., Polonsky, K. S., Tobian, J., Ehrmann, D. A., Matulik, M. J., Clark, B., Czech, K., DeSandre, C., Hilbrich, R., McNabb, W., Semenske, A. R., Caro, J. F., Furlong, K., Goldstein, B. J., Watson, P. G., Smith, K. A., Mendoza, J., Wildman, W., Liberoni, R., Spandorfer, J., Pepe, C., Donahue, R. P., Goldberg, R. B., Prineas, R., Calles, J., Ojito, J., Rowe, P., Cassanova-Romero, P., Castillo-Florez, S., Florez, H. J., Giannella, A., Kirby, L., Larreal, C., Lara, O., McLymont, V., Mendez, J., Perry, A., Saab, P., Veciana, B., Haffner, S. M., Hazuda, H. P., Montez, M. G., Hattaway, K., Lorenzo, C., Martinez, A., Walker, T., Dabelea, D., Hamman, R. F., Nash, P. V., Steinke, S. C., Testaverde, L., Anderson, D. R., Ballonoff, L. B., Bouffard, A., Bucca, B., Calonge, B. N., Delve, L., Farago, M., Hill, J. O., Hoyer, S. R., Jenkins, T., Jortberg, B. T., Lenz, D., Miller, M., Perreault, L., Price, D. W., Regensteiner, J. G., Seagle, H., Smith, C. M., VanDorsten, B., Horton, E. S., Lawton, K. E., Poirier, C. S., Swift, K., Arky, R. A., Bryant, M., Burke, J. P., Caballero, E., Callaphan, K. M., Fargnoli, B., Franklin, T., Ganda, O. P., Guidi, A., Guido, M., Jackson, S. D., Jacobsen, A. M., Lambert, L., Ledbury, S., Kocal, M., Kula, L. M., Malloy, M. A., Nicosia, M., Oldmixon, C. F., Pan, J., Quitingon, M., Rubtchinsky, S., Sansoucy, J., Schweizer, D., Seely, E. W., Simonson, D., Smith, F., Solomon, C. G., Spellman, J., Warram, J., Kahn, S. E., Montgomery, B. K., Fujimoto, W., Knopp, R. H., Lipkin, E. W., Marr, M., Morgan-Taggart, I., Murillo, A., Trence, D., Taylor, L., Thomas, A., Tsai, E. C., Dagogo-Jack, S., Kitabchi, A. E., Murphy, M. E., Taylor, L., Dolgoff, J., Applegate, W. B., Bryer-Ash, M., Clark, D., Frieson, S. L., Ibebuogu, U., Imseis, R., Lambeth, H., Lichtermann, L. C., Oktaei, H., Ricks, H., Rutledge, L. K., Sherman, A. R., Smith, C. M., Soberman, J. E., Williams-Cleaves, B., Metzger, B. E., Molitch, M. E., Johnson, M. K., Adelman, D. T., Behrends, C., Cook, M., Fitzgibbon, M., Giles, M. M., Heard, D., Johnson, C. H., Larsen, D., Lowe, A., Lyman, M., McPherson, D., Penn, S. C., Pitts, T., Reinhart, R., Roston, S., Schinleber, P. A., Nathan, D. M., McKitrick, C., Turgeon, H., Larkin, M., Abbott, K., Anderson, E., Bissett, L., Bondi, K., Cagliero, E., Florez, J. C., D’Anna, K., Delahanty, L., Goldman, V., Lou, P., Poulos, A., Raymond, E., Stevens, C., Tseng, B., Olefsky, J. M., Barrett-Connor, E., Carrion-Petersen, M. L., Beltran, M., Claravall, L. N., Dowden, J. M., Edelman, S. V., Henry, R. R., Horne, J., Lamkin, M., Szerdi Janesch, S., Leos, D., Mudaliar, S., Polonsky, W., Smith, J., Torio-Hurley, J., Vejvoda, K., Pi-Sunyer, F. X., Lee, J. E., Allison, D. B., Agharanya, N., Aronoff, N. J., Baldo, M., Crandall, J. P., Foo, S. T., Hagamen, S., Luchsinger, J. A., Pal, C., Parkes, K., Pena, M. B., Rooney, E. S., VanWye, G. H., Viscovich, K. A., Marrero, D. G., Mather, K. J., Prince, M. J., Kelly, S. M., Jackson, M. A., McAtee, G., Putenney, P., Ackermann, R. T., Cantrell, C. M., Dotson, Y. F., Fineberg, E. S., Fultz, M., Guare, J. C., Hadden, A., Ignaut, J. M., Kirkman, M. S., O’Kelly Phillips, E., Porter, B. D., Roach, P. J., Rowland, N. D., Wheeler, M. L., Aroda, V., Ratner, R. 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Affiliations
  • University of Pittsburgh, Pittsburgh, PA
  • Massachusetts General Hospital Diabetes Center, Boston, MA
ORCID
Venue
Diabetes Care
Publisher
American Diabetes Association
Published
2020-11-10
Volume
44
Issue
1
Pages
43-49
ISSN
  • 0149-5992 (ISSN-L)
  • 1935-5548
DOI
10.2337/dc20-1129
PMC
PMC7783946
OpenAlex
W3102761761
Cited by
70
References
24
Citations by year
2026: 5 · 2025: 11 · 2024: 11 · 2023: 18 · 2022: 19 · 2021: 6
FWCI
6.46
Type
journal article
Language
en
Open access
Licence
www.diabetesjournals.org/content/license (vor, 41 d)
Locations
  • Diabetes Care (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
National Institute of Diabetes and Digestive and Kidney Diseases
Topics
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
Keywords
physical activity, type 2 diabetes prevention, Diabetes Prevention Program, lifestyle intervention, metformin, accelerometry, self-reported physical activity, diabetes incidence, body weight, high-risk patients
MeSH terms
Cross-Sectional Studies, Diabetes Mellitus, Type 2, Humans, Hypoglycemic Agents, Life Style, Metformin, Exercise

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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