This article briefly summarizes the “Pre-Diabetes Detection and Intervention Symposium” that described ongoing and past pre-diabetes interventions, and outlined some considerations when deciding to target specific populations with pre-diabetes. The success of type 2 diabetes (T2D) prevention clinical trials provides clear evidence that healthy lifestyle change can prevent the development of T2D in a cost effective manner in high risk individuals. However, who to target and what cut-points should be used to identify individuals who would qualify for these T2D prevention programs are not simple questions. More stringent cut-offs are more efficient in preventing T2D, but less equitable. Interventions will likely need to be adapted and made more economical for local communities and health care centers if they are to be adopted universally. Further, they may need to be adapted to meet the specific needs of certain high-risk populations such as ethnic minorities. The Chronic Disease Management & Prevention Program for Diverse Populations in Alberta and the Pre-diabetes Detection and Physical Activity Intervention Delivery project in Toronto represent 2 examples of specialized interventions that are targeted at certain high risk populations. To reverse the current T2D trends will require continued efforts to develop and refine T2D prevention interventions.
Jennifer L Kuk, Shahnaz Davachi, Andrea M. Kriska, Michael C. Riddell and Edward W. Gregg
Saowaluck Suntraluck, Hirofumi Tanaka and Daroonwan Suksom
Diabetes mellitus is recognized as one of the leading causes of disability, morbidity, and premature mortality and has become an epidemic in many countries. Patients with type 2 diabetes demonstrate four times greater mortality from cardiovascular disease ( Almdal, Scharling, Jensen, & Vestergaard
Janelle M. Wagnild and Tessa M. Pollard
Television (TV) time is consistently linked with poor health outcomes, including all-cause mortality and incident type 2 diabetes. 1 Within epidemiological studies, the associations between TV time and cardiometabolic health outcomes are generally interpreted to be effects of sitting. However, the
Marjan Mosalman Haghighi, Yorgi Mavros and Maria A. Fiatarone Singh
Low levels of physical activity (PA) and high levels of sedentary behavior are independent, modifiable risk factors for the progression of insulin resistance, and poor health outcomes in adults with type 2 diabetes. 1 , 2 However, this cohort is substantially less likely to meet PA guidelines
Susumu S. Sawada, I-Min Lee, Hisashi Naito, Koji Tsukamoto, Takashi Muto and Steven N. Blair
Limited data are available on the relationship between muscular and performance fitness (MPF) and the incidence of type 2 diabetes.
A cohort of 3792 Japanese men completed a medical examination that included MPF and cardiorespiratory fitness tests. MPF index composite score was calculated using Z-scores from vertical jump, sit-ups, side step, and functional reach tests.
The mean follow-up period was 187 months (15.6 years). There were 240 patients who developed type 2 diabetes during follow-up. Relative risks and 95% confidence intervals (CI) for incidence of diabetes across baseline quartiles of MPF index composite score were obtained using the Cox proportional hazards model while adjusting for age, BMI, diastolic blood pressure, cigarette smoking, alcohol intake, and family history of diabetes. The relative risks for developing diabetes across quartiles of MPF index composite scores (lowest to highest) were 1.0 (referent), 1.15 (95% CI 0.83−1.60), 1.10 (0.78−1.55), and 0.57 (0.37−0.90) (P for trend = .061). These results were attenuated after adjustment for cardiorespiratory fitness (P for trend = .125).
This prospective study suggests that MPF is a predictor of type 2 diabetes, although its predictive ability was attenuated after adjusting for cardiorespiratory fitness.
James Dziura, Stanislav V. Kasl and Loretta Di Pietro
It is not clear whether physical activity can exert a protective role on diabetes risk in older people that is independent of the changes in body weight that occur with both aging and disuse. The purpose of this analysis was to determine the relation between current physical activity, 3-year change in body weight, and the subsequent risk of type 2 diabetes in an older cohort.
We studied prospectively 2,135 older (≥65 years) persons living in New Haven, CT, between 1982 and 1994. Physical activity was self-reported in 1982 and again in 1985; body weight and diabetes were self-reported annually over 12 years. Data were analyzed using multivariable Cox Proportional Hazards modeling with adjustments for age, sex, race, education, body mass index (BMI), smoking, chronic conditions, physical function, and alcohol intake.
Although an inverse graded relation was observed between level of activity and rate of diabetes, this dose–response relation did not reach statistical significance. However, older people who reported at least some activity at baseline experienced a significantly lower rate of diabetes between 1983 and 1994 compared to those reporting no activity (RR = 0.55; 95%CI = 0.35, 0.87). When 3-year changes in physical activity and body weight between 1982 and 1985 were added to the model, the relation between physical activity and reduced diabetes risk was unchanged (RR = 0.49; 95%CI = 0.24, 0.99).
Even in advanced age, physical activity exerts an important and independent role in the prevention of type 2 diabetes. Continued physician counseling on the health effects of physical activity and referrals to community-based exercise programs should be encouraged among older people.
Melinda J. Craike, Kylie Mosely, Jessica L. Browne, Frans Pouwer and Jane Speight
To examine associations between physical activity (PA) and depressive symptoms among adults with type 2 diabetes mellitus (Type 2 DM), and whether associations varied according to weight status.
Diabetes MILES–Australia is a national survey of adults with diabetes, focused on behavioral and psychosocial issues. Data from 705 respondents with Type 2 DM were analyzed, including: demographic and clinical characteristics, PA (IPAQ-SF), depressive symptoms (PHQ-9), and BMI (self-reported height and weight). Data analysis was performed using ANCOVA.
Respondents were aged 59 ± 8 years; 50% women. PA was negatively associated with depressive symptoms for the overall sample (ηp 2= 0.04,P < .001) and all weight categories separately: healthy (ηp 2 0.11 P = .041,), overweight (ηp 2= 0.04, P = .025) and obese (ηp 2 = 0.03, P = .007). For people who were healthy (BMI 18.5 to 24.9) or overweight (BMI 25 to 29.9), high amounts of PA were significantly associated with fewer depressive symptoms; for adults who were obese (BMI ≥ 30) however, both moderate and high amounts were associated with fewer depressive symptoms.
PA is associated with fewer depressive symptoms among adults with Type 2DM, however the amount of PA associated with fewer depressive symptoms varies according to weight status. Lower amounts of PA might be required for people who are obese to achieve meaningful reductions in depressive symptoms compared with those who are healthy weight or overweight. Further research is needed to establish the direction of the relationship between PA and depressive symptoms.
Carolyn Jimenez, Mayra Santiago, Michael Sitler, Guenther Boden and Carol Homko
Little is known about the acute effects of resistance exercise on insulin sensitivity in people with type 1 diabetes.
Repeated-measures design with 2 independent variables: group (exercise and nonexercise control) and time (preexercise and 12 and 36 h postexercise).
General Clinical Research Center, Temple University Hospital, Philadelphia, PA.
14 physically active subjects (11 men and 3 women) with type 1 diabetes.
The exercise group completed 5 sets of 6 repetitions of strenuous (80% 1-RM) quadriceps and hamstring exercises while the control group performed only activities of daily Living.
Main Outcome Measures:
Insulin sensitivity was assessed with the euglycemic-hyperinsulinemic-clamp technique preexercise and 12 and 36 h postexercise.
Insulin-sensitivity values were not significantly different between the exercise and control groups (P = .92) or over time (P = .67).
A single bout of strenuous resistance exercise does not alter insulin sensitivity in people with type 1 diabetes.
Jennifer R. O’Neill, Angela D. Liese, Robert E. McKeown, Bo Cai, Steven P. Cuffe, Elizabeth J. Mayer-Davis, Richard F. Hamman and Dana Dabelea
In this study, the relationship between physical activity (PA) and 3 self-concept constructs (physical abilities, physical appearance, and general self-concept) was examined. Youth with type 1 diabetes (n = 304), type 2 diabetes (n = 49), and nondiabetic controls (n = 127) aged 10−20 years wore pedometers over 7 days. Youth completed the Self-Description Questionnaire and correlation coefficients were calculated. Mean steps/day were 7413 ± 3415, 4959 ± 3474 and 6870 ± 3521 for type 1, type 2 and control youth, respectively. Significant correlations were found between steps/day and perception of physical abilities (r = .29; r = .31; r = .31) for type 1, type 2, and control youth, respectively. The other correlations were not significant. Among youth with type 2 diabetes, steps/day were significantly correlated with physical appearance (r = .46). The positive correlation between PA and physical abilities suggests a reciprocal relationship between behavior and perception.
John Cooper, Barbara Stetson, Jason Bonner, Sean Spille, Sathya Krishnasamy and Sri Prakash Mokshagundam
This study assessed physical activity (PA) in community dwelling adults with Type 2 diabetes, using multiple instruments reflecting internationally normed PA and diabetes-specific self-care behaviors.
Two hundred and fifty-three Black (44.8%) and White (55.2%) Americans [mean age = 57.93; 39.5% male] recruited at low-income clinic and community health settings. Participants completed validated PA self-report measures developed for international comparisons (International Physical Activity Questionnaire Short Form), characterization of diabetes self-care (Summary of Diabetes Self-Care Activities Measure; SDSCA) and exercise-related domains including provider recommendations and PA behaviors and barriers (Personal Diabetes Questionnaire; PDQ).
Self-reported PA and PA correlates differed by instrument. BMI was negatively correlated with PA level assessed by the PDQ in both genders, and assessed with SDSCA activity items in females. PA levels were low, comparable to previous research with community and diabetes samples. Pain was the most frequently reported barrier; females reported more frequent PA barriers overall.
When using self-report PA measures for PA evaluation of adults with diabetes in clinical settings, it is critical to consider population and setting in selecting appropriate tools. PA barriers may be an important consideration when interpreting PA levels and developing interventions. Recommendations for incorporating these measures in clinical and research settings are discussed.