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Activity and Sedentary Time 10 Years After a Successful Lifestyle Intervention: The Diabetes Prevention Program

Published:November 21, 2016DOI:https://doi.org/10.1016/j.amepre.2016.10.007

      Introduction

      This study aims to determine if evidence exists for a lasting effect of the Diabetes Prevention Program (DPP) lifestyle intervention on activity levels by comparing objectively collected activity data between the DPP Outcome Study (DPPOS) cohort and adults from the National Health and Nutrition Examination Survey (NHANES; 2003–2006).

      Methods

      Average minutes/day of light and moderate to vigorous physical activity (MVPA) and sedentary behavior from ActiGraph accelerometers (collected 2010–2012) were examined (2013–2014) for comparable DPPOS and NHANES subgroups by age, sex, and diabetes status. Longitudinal questionnaire data on leisure activity, collected yearly from DPP baseline to the time of accelerometer measurement (1996–2010; 11.9-year mean follow-up), were also examined to provide support for a long-term intervention effect.

      Results

      Average minutes/day of accelerometer-derived MVPA was higher in all DPPOS subgroups versus NHANES subgroups of similar age/sex/diabetes status; with values as much as twice as high in some DPPOS subgroups. Longitudinal questionnaire data from DPP/DPPOS showed a maintained increase of 1.24 MET hours/week (p=0.026) of leisure activity in DPPOS participants from all original study arms between DPP baseline and accelerometer recording. There were no consistent differences between comparable DPPOS and NHANES subgroups for accelerometer-derived sedentary or light-intensity activity minutes/day.

      Conclusions

      More than 10 years after the start of DPP, DPPOS participants performed more accelerometer-measured MVPA than similar adults from NHANES. Longitudinal questionnaire data support the accelerometer-based findings by suggesting that leisure activity levels at the time of accelerometer recording remained higher than DPP baseline levels.

      Introduction

      The Diabetes Prevention Program (DPP) and other large randomized trials have shown that lifestyle interventions including physical activity (PA) and weight loss can delay or prevent Type 2 diabetes in high-risk individuals.
      • Knowler W.C.
      • Barrett-Connor E.
      • Fowler S.E.
      • et al.
      Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.
      • Davey Smith G.
      • Bracha Y.
      • Svendsen K.H.
      • et al.
      Incidence of type 2 diabetes in the randomized multiple risk factor intervention trial.
      • Lindstrom J.
      • Louheranta A.
      • Mannelin M.
      • et al.
      The Finnish Diabetes Prevention Study (DPS): Lifestyle intervention and 3-year results on diet and physical activity.
      • Ramachandran A.
      • Snehalatha C.
      • Mary S.
      • Mukesh B.
      • Bhaskar A.D.
      • Vijay V.
      Indian Diabetes Prevention Programme (IDPP). The Indian Diabetes Prevention Programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1).
      • Roumen C.
      • Blaak E.E.
      • Corpeleijn E.
      Lifestyle intervention for prevention of diabetes: determinants of success for future implementation.
      • Lindahl B.
      • Nilsson T.K.
      • Borch-Johnsen K.
      • et al.
      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
      • Kosaka K.
      • Noda M.
      • Kuzuya T.
      Prevention of type 2 diabetes by lifestyle intervention: a Japanese trial in IGT males.
      • Pan X.R.
      • Li G.W.
      • Hu Y.H.
      • et al.
      Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study.
      The DPP lifestyle intervention PA goal was to achieve and maintain 150 minutes/week of moderate to vigorous intensity PA (MVPA)
      • Knowler W.C.
      • Barrett-Connor E.
      • Fowler S.E.
      • et al.
      Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.
      The Diabetes Prevention Program (DPP) Research Group
      The Diabetes Prevention Program (DPP): description of lifestyle intervention.
      and was aligned with nationally recommended PA goals for adults.

      U.S. DHHS. Physical activity and health: a report of the Surgeon General. CDC National Center for Chronic Disease Prevention and Health Promotion; 1996

      Although reducing sedentary time was encouraged, there was no explicit sedentary behavior reduction goal.
      The Diabetes Prevention Program (DPP) Research Group
      The Diabetes Prevention Program (DPP): description of lifestyle intervention.
      • Wing R.R.
      • Hamman R.F.
      • Bray G.A.
      • et al.
      Achieving weight and activity goals among Diabetes Prevention Program lifestyle participants.
      The DPP lifestyle intervention succeeded at increasing MVPA and reducing sedentary time, as assessed by questionnaire, in the lifestyle participants (3.2-year mean follow-up).
      • Wing R.R.
      • Hamman R.F.
      • Bray G.A.
      • et al.
      Achieving weight and activity goals among Diabetes Prevention Program lifestyle participants.
      • Rockette-Wagner B.
      • Edelstein S.
      • Venditti E.M.
      • et al.
      The impact of lifestyle intervention on sedentary time in individuals at high risk of diabetes.
      After the DPP ended, participants from all study arms were offered a group-implemented version of the lifestyle intervention and have been followed as part of the DPP Outcomes Study (DPPOS) for more than 10 years since DPP baseline.
      • Knowler W.C.
      • Fowler S.E.
      • Hamman R.F.
      • et al.
      10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study.
      This extensive follow-up period made it possible to examine whether activity levels over the DPPOS follow-up increased from baseline and were greater than what would be expected in the general population.
      The follow-up time in other diabetes prevention trials examining the impact of lifestyle interventions on improving activity is typically shorter than 10 years.
      • Ramachandran A.
      • Snehalatha C.
      • Mary S.
      • Mukesh B.
      • Bhaskar A.D.
      • Vijay V.
      Indian Diabetes Prevention Programme (IDPP). The Indian Diabetes Prevention Programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1).
      • Lindahl B.
      • Nilsson T.K.
      • Borch-Johnsen K.
      • et al.
      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
      • Pan X.R.
      • Li G.W.
      • Hu Y.H.
      • et al.
      Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study.
      • Wing R.R.
      • Hamman R.F.
      • Bray G.A.
      • et al.
      Achieving weight and activity goals among Diabetes Prevention Program lifestyle participants.
      • Rockette-Wagner B.
      • Edelstein S.
      • Venditti E.M.
      • et al.
      The impact of lifestyle intervention on sedentary time in individuals at high risk of diabetes.
      • Eriksson K.F.
      • Lindgarde F.
      Prevention of type 2 (non-insulin-dependent) diabetes mellitus by diet and physical exercise. The 6-year Malmo feasibility study.
      Additionally, the majority of published studies rely solely on self-reported measures of PA.
      • Ramachandran A.
      • Snehalatha C.
      • Mary S.
      • Mukesh B.
      • Bhaskar A.D.
      • Vijay V.
      Indian Diabetes Prevention Programme (IDPP). The Indian Diabetes Prevention Programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1).
      • Lindahl B.
      • Nilsson T.K.
      • Borch-Johnsen K.
      • et al.
      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
      • Pan X.R.
      • Li G.W.
      • Hu Y.H.
      • et al.
      Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study.
      • Wing R.R.
      • Hamman R.F.
      • Bray G.A.
      • et al.
      Achieving weight and activity goals among Diabetes Prevention Program lifestyle participants.
      • Rockette-Wagner B.
      • Edelstein S.
      • Venditti E.M.
      • et al.
      The impact of lifestyle intervention on sedentary time in individuals at high risk of diabetes.
      • Eriksson K.F.
      • Lindgarde F.
      Prevention of type 2 (non-insulin-dependent) diabetes mellitus by diet and physical exercise. The 6-year Malmo feasibility study.
      Self-reported PA, using recall questionnaires, has been shown to be a reasonably valid and reliable method of assessing MVPA and domain-specific sedentary behaviors in adults. However, self-report has been shown to be less valid and reliable for measuring unplanned activities, light-intensity activity (LPA), and total accumulated sedentary behavior.
      • Kriska A.
      • Caspersen C.J.
      Introduction to a collection of Physical Activity Questionnaires.
      • Jacobs Jr., D.R.
      • Ainsworth B.E.
      • Hartman T.J.
      • Leon A.S.
      A simultaneous evaluation of 10 commonly used physical activity questionnaires.
      Objective methods of measuring PA are arguably a more valid method of recording across all intensities of PA and sedentary behavior.
      • Jacobs Jr., D.R.
      • Ainsworth B.E.
      • Hartman T.J.
      • Leon A.S.
      A simultaneous evaluation of 10 commonly used physical activity questionnaires.
      • Marshall A.L.
      • Miller Y.D.
      • Burton N.W.
      • Brown W.J.
      Measuring total and domain-specific sitting: a study of reliability and validity.
      • Hart T.L.
      • Ainsworth B.E.
      • Tudor-Locke C.
      Objective and subjective measures of sedentary behavior and physical activity.
      • Pettee K.K.
      • Storti K.L.
      • Ainsworth B.E.
      • Kriska A.M.
      Measurement of physical activity and inactivity in epidemiologic studies.
      This current effort presents objectively collected activity data from accelerometers, measured more than 10 years after DPP baseline. Comparisons to similar accelerometer data from a national sample of adults participating in the National Health and Nutrition Examination Survey (NHANES) was undertaken to provide context for these data. If a long-term intervention effect existed in DPP, then activity levels in the DPPOS cohort as a whole would be expected to be higher and sedentary behavior would be expected to be lower than those for people of the same sex and of similar age and diabetes status in a population-representative cohort. Additionally, the longitudinal changes in questionnaire-based leisure activity (collected yearly from baseline) in the DPPOS cohort was examined to determine whether observed differences in activity between the DPPOS cohort and NHANES participants could be the result of a successful long-term intervention effect or simply represent baseline differences in activity patterns between the two populations.
      • Kriska A.M.
      • Edelstein S.L.
      • Hamman R.F.
      • et al.
      Physical activity in individuals at risk for diabetes: Diabetes Prevention Program.

      Methods

      Study Sample

      Participants for this effort were recruited from the DPPOS (2002–present) of the DPP follow-up study (1996–2001) cohort. DPP was a multi-center RCT designed to determine if metformin or lifestyle intervention could prevent or delay Type 2 diabetes in adults at high risk for the disease.
      The Diabetes Prevention Program
      Design and methods for a clinical trial in the prevention of type 2 diabetes.
      The DPP study design, methods, and primary results have been published.
      • Knowler W.C.
      • Barrett-Connor E.
      • Fowler S.E.
      • et al.
      Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.
      The Diabetes Prevention Program
      Design and methods for a clinical trial in the prevention of type 2 diabetes.
      DPP enrolled 3,234 overweight U.S. adults aged ≥25 years (1996–1999) and ended after an average follow-up of 3.2 years (results published after 2.8 years). Diabetes incidence was reduced in the metformin and lifestyle intervention arms compared with placebo by 31% and 58%, respectively.
      • Knowler W.C.
      • Barrett-Connor E.
      • Fowler S.E.
      • et al.
      Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.
      After DPP ended, all remaining participants were offered a modified group version of the lifestyle intervention (previously described).
      • Wing R.R.
      • Hamman R.F.
      • Bray G.A.
      • et al.
      Achieving weight and activity goals among Diabetes Prevention Program lifestyle participants.
      The goals of the DPP/DPPOS original and group version interventions were to achieve a 7% weight loss and at least 150 minutes/week of moderate-intensity activity (e.g., brisk walking). This PA goal was aligned with the Surgeon General’s recommended PA goal for adults.

      U.S. DHHS. Physical activity and health: a report of the Surgeon General. CDC National Center for Chronic Disease Prevention and Health Promotion; 1996

      A total of 2,766 of the remaining 3,150 (88%) participants consented to participate in DPPOS.
      • Knowler W.C.
      • Fowler S.E.
      • Hamman R.F.
      • et al.
      10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study.
      The DPPOS Accelerometer Ancillary Study (data collected 2010–2012) was a cross-sectional study conducted in DPPOS participants to obtain objectively measured total time spent in PA and sedentary behaviors using a validated accelerometer (ActiGraph GT3X, Pensacola, FL).
      • Wetten A.A.
      • Batterham M.
      • Tan S.Y.
      • Tapsell L.
      Relative validity of 3 accelerometer models for estimating energy expenditure during light activity.
      • Hendelman D.
      • Miller K.
      • Baggett C.
      • Debold E.
      • Freedson P.
      Validity of accelerometry for the assessment of moderate intensity physical activity in the field.
      • Skotte J.
      • Korshoj M.
      • Kristiansen J.
      • Hanisch C.
      • Holtermann A.
      Detection of physical activity types using triaxial accelerometers.
      • Kozey-Keadle S.
      • Libertine A.
      • Lyden K.
      • Staudenmayer J.
      • Freedson P.S.
      Validation of wearable monitors for assessing sedentary behavior.
      Twenty-three of the 26 DPP clinical centers (1,932 active participants, all aged ≥39 years) took part. Participants not confined to a wheelchair and able to walk were eligible for inclusion. Informed consent was obtained from all participants and the study was approved by the IRBs of each institution.
      Conducted by the National Center for Health Statistics, NHANES is a cross-sectional observational study of the U.S. population. During NHANES 2003–2004 and 2005–2006, measures of PA were collected in a U.S. representative sample using an ActiGraph accelerometer.
      • Troiano R.P.
      • Berrigan D.
      • Dodd K.W.
      • Masse L.C.
      • Tilert T.
      • McDowell M.
      Physical activity in the United States measured by accelerometer.
      For comparability to the DPPOS cohort, only participants aged ≥40 years with valid accelerometer data and fasting blood glucose measurements were included in this report.

      Measures

      DPPOS participants wore an ActiGraph GT3X triaxial accelerometer on their waist for 7 days, during waking hours, following their annual or midyear clinic visit (one time from 2010 to 2012). NHANES study participants received an ActiGraph (AM7164 uniaxial) monitor at their examination visit to wear on their waist for the 7 days following the visit.
      • Troiano R.P.
      • Berrigan D.
      • Dodd K.W.
      • Masse L.C.
      • Tilert T.
      • McDowell M.
      Physical activity in the United States measured by accelerometer.
      Only counts from the vertical axis were used from the DPPOS accelerometers, as this is the only axis measured by both the uniaxial and triaxial monitors used in NHANES and DPPOS, respectively. This method of comparison between ActiGraph uniaxial and triaxial models has been previously validated.
      • Robusto K.M.
      • Trost S.G.
      Comparison of three generations of ActiGraph activity monitors in children and adolescents.
      • Sasaki J.E.
      • John D.
      • Freedson P.S.
      Validation and comparison of ActiGraph activity monitors.
      Monitor data from DPPOS and NHANES was screened for wear time using 1-minute epochs, with non-wear (monitor removal) identified as ≥60 consecutive minutes of zero counts with an allowance for up to 2 minutes of non-zero counts. At least 10 hours of wear time was required for a valid day and ≥4 valid days were required for inclusion in the analyses.
      • Trost S.G.
      • McIver K.L.
      • Pate R.R.
      Conducting accelerometer-based activity assessments in field-based research.
      Validated Freedson activity intensity cut-points were used to classify sedentary behavior (0–99 counts/minute); LPA (100–1,751 counts/minute); and MVPA (≥1,952 counts/minute).
      • Freedson P.S.
      • Melanson E.
      • Sirard J.
      Calibration of the Computer Science and Applications, Inc. accelerometer.
      Data were examined as total minutes/day in each PA intensity.
      In DPP and DPPOS, activity data were collected annually (1996–2010 presented) via the Modifiable Activity Questionnaire (MAQ). MAQ assesses past-year leisure PA (primarily MVPA bouts ≥10 minutes). Results are coded as MET hours/week. MAQ has been shown to be valid and reliable, with strong correlations reported between leisure PA from MAQ and time spent in comparable bouts of MVPA from accelerometers (ρ=0.69–0.76, all p<0.0001).
      • Rockette-Wagner B.
      • Edelstein S.
      • Venditti E.M.
      • et al.
      The impact of lifestyle intervention on sedentary time in individuals at high risk of diabetes.
      • Kriska A.
      • Caspersen C.J.
      Introduction to a collection of Physical Activity Questionnaires.
      • Momenan A.A.
      • Delshad M.
      • Sarbazi N.
      • Rezaei Ghaleh N.
      • Ghanbarian A.
      • Azizi F.
      Reliability and validity of the Modifiable Activity Questionnaire (MAQ) in an Iranian urban adult population.
      • Pettee Gabriel K.
      • McClain J.J.
      • Schmid K.K.
      • Storti K.L.
      • Ainsworth B.E.
      Reliability and convergent validity of the past-week Modifiable Activity Questionnaire.
      • Jacobi D.
      • Charles M.A.
      • Tafflet M.
      • Lommez A.
      • Borys J.M.
      • Oppert J.M.
      Relationships of self-reported physical activity domains with accelerometry recordings in French adults.
      Unreasonably high leisure PA values (>150 MET hours/week; <0.01% of all individual recordings) were truncated to 150 MET hours/week (450 minutes/week moderate activity).
      Demographic information was collected before DPP randomization.
      The Diabetes Prevention Program
      Design and methods for a clinical trial in the prevention of type 2 diabetes.
      Incident diabetes was identified annually (75-g oral glucose tolerance test [OGTT]) and semi-annually (fasting glucose levels), with values confirmed within 6 weeks.
      The Diabetes Prevention Program
      Design and methods for a clinical trial in the prevention of type 2 diabetes.
      At DPP enrollment, all participants had elevated fasting glucose. At the time of the accelerometer study, there were no differences in activity and sedentary behavior levels (p>0.05) between subgroups of individuals without diabetes but at high risk for the disease (currently normal glucose tolerance, isolated impaired fasting glucose, or impaired glucose tolerance). Therefore, in this study, DPPOS participants without confirmed diabetes during accelerometer wear were considered to be one subgroup, identified as high risk for diabetes.
      In NHANES, demographic variables, age, and fasting plasma glucose were collected during household interviews or examination visits. Diabetes status was determined by self-reported diabetes medication usage (non-insulin) and fasting plasma glucose test results using American Diabetes Association guidelines.
      American Diabetes Association
      Diagnosis and classification of diabetes mellitus.
      The possibility of using the OGTT instead of the fasting plasma glucose test to identify diabetes status was also examined in the much smaller OGTT subsample (n=654, also given an OGTT). The overall results of the comparisons between the DPPOS and NHANES participants were unchanged using this method. Therefore, the larger fasting sample was used for this report.

      Statistical Analysis

      Means and SEs were calculated for DPPOS and NHANES by sex, age groups (39–49 [NHANES, 40–49], 50–59, 60–69, and ≥70 years), and diabetes status groups. Results reported in Kriska et al.
      • Kriska A.
      • Rockette-Wagner B.
      • Venditti B.
      • et al.
      Objective Physical Activity Levels Across Diabetes Prevention Program (DPP) Randomized Arms Over a Decade Later.
      suggest that individual intensities of PA (MVPA, LPA, sedentary) were not significantly different across study arms in this group when examined as separate components. However, the sum of all individual intensities (i.e., total activity) was significantly different, with higher total PA in the lifestyle arm. This study only examined the separate components of PA (MVPA, LPA, sedentary). Therefore, DPPOS participants were not further divided by original randomized group.
      Means and SEs for NHANES utilized weighting procedures based on the sampling strategy. Reweighting (using appropriate subsample weights) on age, sex, race/ethnicity, and BMI was done to adjust for unequal probabilities of selection/non-response prior to analysis.
      The mean follow-up from DPP baseline to the beginning of the accelerometer study was 11.9 (SD=1.0) years. Mixed models (autoregressive covariance matrix) were used to determine differences from baseline (to Year 8 of DPPOS) for leisure activity from the MAQ (MET hours/week); adjusted least squares means were also calculated (Tukey’s test, for multiple comparisons).
      • Tukey J.W.
      The philosophy of multiple comparisons.
      Models were adjusted for important covariates: baseline leisure activity, treatment arm, age, sex, and time-dependent diabetes status. Additionally, models were run for all treatment groups combined as well as stratified by treatment group. Because the lifestyle intervention was previously shown to affect activity levels in the lifestyle arm during the DPP follow-up of 3.2 years, the interaction between treatment arm and time was also added to the model containing all treatment arms combined. All additional covariates were significant (p<0.05) in the full model. Statistical analyses were conducted in SAS, version 9.2, between 2013 and 2014.

      Results

      Approximately 93% (1,793 of 1,932) of active DPPOS participants enrolled in the accelerometer ancillary study. Nine participants were ineligible based on low cognition or lack of ambulation. The remaining 130 unenrolled participants either did not attend a clinic visit during enrollment or declined. In all, 1,574 ancillary study participants (87.8% of 1,793) had at least 4 valid days of accelerometer recording (based on uniaxial data; Table 1). The mean age of ancillary study participants with valid data was 63.7 (SD=9.6) years at the time of accelerometer wear, nearly 70% were female, and 47% self-reported a race/ethnicity other than Caucasian. Individuals with complete accelerometer data (versus without) were more likely to have confirmed diabetes (54.1% vs 46.1%, p=0.026). There were no other significant differences in key covariates across compliance groups (data not shown).
      Table 1Demographics and Randomized Arm Assignment for DPPOS Participants With ≥4 Valid Days of Accelerometry (n=1,574)
      Participant characteristicValue
      Age, years, M (SD)63.7 (9.6)
      Sex (% female)69.7
      Race (%)
       Caucasian53
       African American18
       Hispanic American17
       Asian or Pacific Islander- American5
       American Indian7
       Not given<0.05
      Weight, kg, M (SD)90.2 (22.7)
      BMI, M (SD)32.6 (6.6)
      Physical activity based on MAQ, median(IQR)
       PA total MET-hours/day12.7 (4.9, 34.9)
      Randomized arm (%)
       DPP placebo33.8
       DPP lifestyle32.8
       DPP metformin33.4
      Confirmed diabetes (%)54.1
      Note: MAQ assessed for the year containing the accelerometer visit.
      DPP, Diabetes Prevention Program; DPPOS, Diabetes Prevention Program Outcome Study; IQR, interquartile range; MAQ, Modifiable Activity Questionnaire; PA, physical activity.
      On average, DPPOS participants with ≥4 valid days of data spent 556.3 (SE=2.2) minutes/day (~9.25 hours/day) in sedentary behaviors. Additionally, an average of 270.7 (SE=2.1) and 15.3 (SE=0.5) minutes/day were spent in LPA and MVPA, respectively. There were significant differences in activity and sedentary behavior by sex, age, and diabetes status categories (Table 2). Compared with women, men performed more MVPA and less LPA (both p<0.0001, respectively). Both MVPA and LPA were significantly lower (both p<0.0001), and sedentary behavior was higher (p=0.0008) with increasing age category. Additionally, individuals with confirmed diabetes status at the time of accelerometer wear had less LPA and MVPA than individuals who had not developed diabetes (both p<0.05).
      Table 2Mean (SE) Values for Accelerometer-Measured Activity Variables in DPPOS Participants With ≥4 Days of Valid Monitoring
      ParticipantsLight intensity (L) PAModerate-vigorous (MV) PASedentary behavior
      All (n=1,574)270.7 (2.1)15.3 (0.5)556.3 (2.2)
      Sex categories
       Males (n=477)256.7 (4.0)20.6 (1.0)562.3 (4.3)
       Female (n=1,097)276.8 (2.5)13.0 (0.5)553.6 (2.5)
      p-dif<0.0001<0.00010.09
      Age categories, years
       39–59 (n=564)292.3 (3.5)18.9 (0.8)550.7 (3.7)
       60–69 (n=592)273.6 (3.4)15.7 (0.8)551.9 (3.5)
       ≥70 (n=418)237.4 (3.8)9.7 (0.8)570.0 (4.3)
      p-dif<0.0001<0.00010.0008
      Diabetes status categories
       Confirmed diabetes (n=888)266.7 (3.2)14.1 (0.73)556.0 (3.3)
       High risk for diabetes (n=686)275.8 (2.8)16.8 (0.58)551.4 (2.9)
      p-dif0.030.0040.05
      Note: p-dif based on t-test/ANOVA.
      DPPOS, Diabetes Prevention Program Outcomes Study; PA, physical activity.
      Levels of MVPA were generally higher for the DPPOS cohort (n=1,574) when compared with NHANES participants (n=1,839) of the same sex and a similar age and diabetes status (Figure 1). Point estimates for average minutes/day of MVPA were higher in all of the DPPOS high-risk and confirmed diabetes subgroups when compared with individuals from NHANES of comparable age, sex, and diabetes status—representing as much as a 100% increase in some cases. The largest incremental differences in means were for men aged 60–69 years with confirmed diabetes (NHANES 11.5 [SE=3.5] vs DPPOS 17.6 [SE=1.7]); men aged 60–69 years with impaired glucose tolerance/high-risk DPPOS (NHANES 20.2 [SE=2.0] vs DPPOS 26.3 [SE=2.4]); and women aged 60–69 years with confirmed diabetes (NHANES 5.5 [SE=1.0] vs DPPOS 11.5 [SE=1.2]). By contrast, average time spent in LPA was not higher and sedentary time was not lower for the DPPOS cohort when compared to the NHANES participants (Appendix, available online). Examining sedentary time as a percentage of monitor wear time did not change the findings, likely due to the non-significant differences in wear time (p<0.05, data not shown).
      Figure 1.
      Figure 1Accelerometer measured mean (SE) minutes/day spent in moderate-vigorous activity by diabetes status, sex, and age group for adults aged ≥39 years (≥40 years for NHANES).
      Note: Calculations for NHANES values incorporating the design effect, appropriate sample weights, stratification, and clustering of the complex sample design. DM, diabetes; DPPOS, Diabetes Prevention Program Outcomes Study; HR, high risk; IFG, impaired fasting plasma glucose, NGT, normal glucose tolerance, NHANES, National Health and Nutrition Examination Survey; PA, physical activity.
      Longitudinal questionnaire data for the DPPOS accelerometer study cohort (n=1,793) were examined to determine whether the higher levels of accelerometer-measured MVPA in DPPOS (versus NHANES) could be due to an intervention effect or whether they may be related to the fact that the DPPOS cohort was less inactive at baseline than NHANES.
      • Kriska A.M.
      • Edelstein S.L.
      • Hamman R.F.
      • et al.
      Physical activity in individuals at risk for diabetes: Diabetes Prevention Program.
      Adjusted mean values for reported leisure activity (primarily MVPA) levels in MET hours/week were not different across treatment groups at baseline (placebo, 17.7 [SE=0.7]; metformin, 17.2 [SE=0.7]; lifestyle, 16.5 [SE=0.7]; p>0.05). Adjusted mean changes in leisure activity for the lifestyle group peaked at 1 year into the DPP follow-up (+7.1 [SE=0.7] MET hours/week, p<0.0001), following their participation in the lifestyle intervention. For the metformin and placebo groups, mean changes for MET hours/week of leisure activity peaked during the DPPOS follow-up (+2.36 [SE=0.9], p<0.01 and +1.57 [SE=0.9], p=0.08, respectively) after the group-based lifestyle intervention was offered to all participants.
      Over time, the mean changes in leisure activity became similar across treatment groups and differences between groups were no longer significant at the end of follow-up (data not shown, p>0.05). For participants in all groups combined, the mean estimate for change in leisure activity from baseline to the end of follow-up (mean, 11.9 [SD=1.0] years) was +1.24 (SE=0.56) MET hours/week (p=0.026), after controlling for important covariates (including the treatment group X time interaction). Changes in MET hours/week of leisure PA from baseline were also significant over follow-up for each treatment arm individually (data not shown, p<0.05).

      Discussion

      Previously, the DPP lifestyle intervention was shown, by questionnaire, to increase leisure PA levels and decrease sedentary behaviors during the original randomized trial (follow-up, 3.2 years).
      • Wing R.R.
      • Hamman R.F.
      • Bray G.A.
      • et al.
      Achieving weight and activity goals among Diabetes Prevention Program lifestyle participants.
      • Rockette-Wagner B.
      • Edelstein S.
      • Venditti E.M.
      • et al.
      The impact of lifestyle intervention on sedentary time in individuals at high risk of diabetes.
      Questionnaires are well validated for measuring domain-specific behaviors and time spent in planned and higher-intensity activities, but not as accurate as accelerometers for assessing average time spent in all intensities of activity and sedentary behavior.
      • Jacobs Jr., D.R.
      • Ainsworth B.E.
      • Hartman T.J.
      • Leon A.S.
      A simultaneous evaluation of 10 commonly used physical activity questionnaires.
      • Marshall A.L.
      • Miller Y.D.
      • Burton N.W.
      • Brown W.J.
      Measuring total and domain-specific sitting: a study of reliability and validity.
      • Hart T.L.
      • Ainsworth B.E.
      • Tudor-Locke C.
      Objective and subjective measures of sedentary behavior and physical activity.
      • Pettee K.K.
      • Storti K.L.
      • Ainsworth B.E.
      • Kriska A.M.
      Measurement of physical activity and inactivity in epidemiologic studies.
      This new study objectively measured activity more than 10 years after DPP began in the majority of remaining DPPOS participants. The current results suggest, at that time, DPPOS participants spent more time in MVPA but not more time in LPA or less time in sedentary behaviors than similar age, sex, and diabetes status participants from a nationally representative sample (NHANES). The new finding of relatively higher minutes/day of accelerometer-measured MVPA in the DPPOS cohort (versus NHANES) coupled with longitudinal evidence (from a self-reported measure) for post-intervention leisure activity improvement and maintenance in DPP/DPPOS, suggest that the lifestyle intervention was effective at increasing MVPA levels more than 10 years into the DPP follow-up.

      Limitations

      Although the general findings were consistent across all population subgroups, it was not possible to perform an assessment of the statistical significance for the differences between DPPOS and NHANES subgroups owing to the complex sampling design of NHANES and the wide differences in the variances between population subgroups. Unmeasurable differences between DPPOS and NHANES participants could also not be accounted for, such that individuals in an observational study may be different from those participating in an intervention study. It should be noted that DPPOS accelerometer data were collected 4–7 years after NHANES accelerometer data. However, published NHANES results from self-reports suggest that activity levels in U.S. adults were relatively stable over that time period.
      • Carlson S.A.
      • Fulton J.E.
      • Schoenborn C.A.
      • Loustalot F.
      Trend and prevalence estimates based on the 2008 Physical Activity Guidelines for Americans.
      Because there are known strengths and limitations of both subjective and objective methods of activity measurement,
      • Hart T.L.
      • Ainsworth B.E.
      • Tudor-Locke C.
      Objective and subjective measures of sedentary behavior and physical activity.
      • Strath S.J.
      • Kaminsky L.A.
      • Ainsworth B.E.
      • et al.
      Guide to the assessment of physical activity: clinical and research applications: a scientific statement from the American Heart Association.
      a strength of this study was the ability to utilize longitudinal activity questionnaire data in conjunction with cross-sectional accelerometer data to provide stronger evidence for the findings of a lasting intervention effect on activity levels. The MAQ provided a yearly metric (MET hours/week) of leisure activity (primarily MVPA) based on frequency and duration from DPP baseline. MAQ output has previously been shown to correlate to minutes/day of MVPA from accelerometers.
      • Momenan A.A.
      • Delshad M.
      • Sarbazi N.
      • Rezaei Ghaleh N.
      • Ghanbarian A.
      • Azizi F.
      Reliability and validity of the Modifiable Activity Questionnaire (MAQ) in an Iranian urban adult population.
      • Pettee Gabriel K.
      • McClain J.J.
      • Schmid K.K.
      • Storti K.L.
      • Ainsworth B.E.
      Reliability and convergent validity of the past-week Modifiable Activity Questionnaire.
      • Jacobi D.
      • Charles M.A.
      • Tafflet M.
      • Lommez A.
      • Borys J.M.
      • Oppert J.M.
      Relationships of self-reported physical activity domains with accelerometry recordings in French adults.
      If the results from the cross-sectional comparison of DPPOS and NHANES accelerometer data were due to an intervention effect, evidence of this effect should be apparent in the longitudinal MAQ data as well.
      The longitudinal analyses supported the accelerometer findings by suggesting that there was a lasting, significant increase of 1.24 MET hours/week (approximately 25 minutes/week of brisk walking) between DPP baseline and the accelerometer study measurement. It should be noted that self-reported activity typically decreases, not increases, with increasing age.
      • DiPietro L.
      Physical activity in aging: changes in patterns and their relationship to health and function.
      The maintained increase in leisure activity seen across all three original study arms was not surprising given that participants in all arms were offered a group version of the intervention after the original DPP randomized trial ended (and before the DPPOS follow-up), and they were knowledgeable of the DPP results.
      Accelerometry made it possible to examine differences between the DPPOS cohort and NHANES participants for total minutes/day of sedentary behavior and LPA. The accelerometer results did not suggest lower time spent in sedentary behavior for the DPPOS cohort compared to NHANES participants. Therefore, it does not appear that the 37 minutes/day reduction in sedentary time reported for lifestyle participants over the DPP trial (mean, 3.2 years) was still evident more than 10 years later.
      • Rockette-Wagner B.
      • Edelstein S.
      • Venditti E.M.
      • et al.
      The impact of lifestyle intervention on sedentary time in individuals at high risk of diabetes.
      Had there been an explicit focus on reducing sedentary behavior in the DPP lifestyle intervention, the initial reductions in sedentary behavior may have been greater and perhaps lasted longer.

      Conclusions

      Based on objective activity data collected more than 10 years after the DPP started, it appears that DPPOS participants performed more MVPA than a nationally representative sample of similar adults from NHANES. However, relevant differences in LPA and conversely in sedentary time between DPPOS and NHANES participants were not noted. Longitudinal questionnaire data support the findings related to MVPA by suggesting that leisure activity levels remained significantly higher than baseline more than 10 years after the start of DPP. Results from both questionnaires and accelerometers suggest that the DPP lifestyle intervention was successful at achieving long-term improvements in MVPA levels.

      Acknowledgments

      The Research Group gratefully acknowledges the commitment and dedication of the participants of the Diabetes Prevention Program (DPP) and DPP Outcomes Study (DPPOS).
      The DPPOS Accelerometer Ancillary Study was funded by the National Institute of Diabetes and Digestive and Kidney Diseases ([NIDDK] R01 DK081345-01A1). During DPPOS, NIDDK provided funding to the clinical centers and the Coordinating Center for the design and conduct of the study, and collection, management, analysis, and interpretation of the data (U01 DK048489). The Southwestern American Indian Centers were supported directly by NIDDK, including its Intramural Research Program, and the Indian Health Service. The General Clinical Research Center Program, National Center for Research Resources, and the Department of Veterans Affairs supported data collection at many of the clinical centers. Funding was also provided by the National Institute of Child Health and Human Development, National Institute on Aging, National Eye Institute, National Heart Lung and Blood Institute, Office of Research on Women’s Health, National Institute on Minority Health and Health Disparities, Centers for Disease Control and Prevention, and American Diabetes Association. Bristol-Myers Squibb and Parke-Davis provided additional funding and material support during DPP, Lipha (Merck-Sante) provided medication, and LifeScan Inc. donated materials during DPP and DPPOS. The opinions expressed herein are those of the investigators and do not necessarily reflect the views of the funding agencies. A complete list of Centers, investigators, and staff can be found in the Appendix (available online).
      BRW helped draft the concept and design, conducted data analyses, and drafted and revised the manuscript; KLS helped draft the concept and design, assisted with data analysis, and with article revisions; DD, SE, HF, PWF, MGM, and JP assisted with design, aided in the interpretation of data, and provided feedback/assisted with article revisions; and AMK helped draft the concept and design, aided in data interpretation, and assisted with revised manuscript. All authors had final approval of the submitted manuscript. BRW is responsible for the integrity of this work as a whole.
      No financial disclosures were reported by the authors of this paper.

      SUPPLEMENTAL MATERIAL

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