Article

Efficacy of a pedometer-based physical activity program on parameters of diabetes control in type 2 diabetes mellitus

School of Medicine, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA.
Metabolism (Impact Factor: 3.89). 11/2006; 55(10):1382-7. DOI: 10.1016/j.metabol.2006.06.009
Source: PubMed

ABSTRACT

The aim of the study was to determine whether a recommendation to walk 10000 steps per day would result in significant improvements in glycemic control, insulin sensitivity, and cardiovascular risk in patients with type 2 diabetes mellitus. The study was a 6-week randomized controlled trial that included 30 patients with type 2 diabetes mellitus. After 10 days of baseline activity, patients were randomized into 2 groups: control and active. The control group (n = 15) was instructed to continue with their baseline activity for 6 weeks. The active group (n = 15) was instructed to walk at least 10000 steps per day 5 or more days per week, for 6 weeks. Data relevant to glycemic control and other parameters of health were collected at study weeks 0 and 6. There were no differences in the baseline activity between groups (P = .36). Subjects in the active group significantly increased physical activity by 69% during the intervention phase of the study (P = .002), whereas there was no change in the physical activity of the control group (P > .05). High-density lipoprotein cholesterol and resting energy expenditure significantly increased in the active group (P < .05). Finally, plasminogen activator inhibitor 1 (PAI-1) activity was reduced by exercise relative to the control group (P = .03). There were no differences in any other study parameters during the 6-week study. In conclusion, short-term intervention with a pedometer increased physical activity and positively affected plasminogen activator inhibitor 1 activity in previously inactive patients with type 2 diabetes mellitus. The use of a pedometer may prove to be an effective tool for promoting healthy lifestyle changes that include daily physical activity and self-monitoring of therapeutic goals.

Full-text

Available from: Chantal Vella, Sep 03, 2014
Efficacy of a pedometer-based physical activity program on parameters
of diabetes control in type 2 diabetes mellitus
Paul Araiza, Hilary Hewes, Carrie Gashetewa, Chantal A. Vella, Mark R. Burge
4
School of Medicine, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA
Received 8 June 2005; accepted 7 June 2006
Abstract
The aim of the study was to determine whether a recommendation to walk 10 000 steps per day would result in significant improvements
in glycemic control, insulin sensitivity, and cardiovascular risk in patients with type 2 diabetes mellitus. The study was a 6-week randomized
controlled trial that included 30 patients with type 2 diabetes mellitus. After 10 days of baseline activity, patients were randomized into
2 groups: control and active. The control group (n = 15) was instructed to continue with their baseline activity for 6 weeks. The active group
(n = 15) was instructed to walk at least 10 000 steps per day 5 or more days per week, for 6 weeks. Data relevant to glycemic control and
other parameters of health were collected at study weeks 0 and 6. There were no differences in the baseline activity between groups ( P = .36).
Subjects in the active group significantly increased physical activity by 69% during the intervention phase of the study ( P = .002), whereas
there was no change in the physical activity of the control group ( P N .05). High-density lipoprotein cholesterol and resting energy
expenditure significantly increased in the active group ( P b .05). Finally, plasminogen activator inhibitor 1 (PAI-1) activity was reduced by
exercise relative to the control group ( P = .03). There were no differences in any other study parameters during the 6-week study. In
conclusion, short-term intervention with a pedometer increased physical activity and positively affected plasminogen activator inhibitor
1 activity in previously inactive patients with type 2 diabetes mellitus. The use of a pedometer may prove to be an effective tool for
promoting healthy lifestyle changes that include daily physical activity and self-monitoring of therapeutic goals.
D 2006 Elsevier Inc. All rights reserved.
1. Introduction
Regular physical activity is an important component in
the prevention and management of type 2 diabetes mellitus.
Recent evidence suggests that participation in nonvigorous
physical activity significantly improves insulin sensitivity in
patients at high risk for diabetes [1]. The Diabetes
Prevention Program found that a lifestyle modification
incorporating a minimum of 150 min/wk of moderate-
intensity physical activity, such as brisk walking, was more
effective in preventing type 2 diabetes mellitus in individ-
uals with prediabetes than was either with metformin or with
placebo [2]. Furthermore, Heimrich and colleagues [3]
reported an inverse relationship between energy expenditure
in leisure-time physical activity and the development of type
2 diabetes mellitus in former college students.
Regular exercise has been demonstrated to have positive
effects on glycemic control, weight reduction, and insulin
resistance in patients with type 2 diabetes mellitus [4-7].
Regular physical activity is also correlated with decreases in
all-cause and cardiovascular disease mortality in diabetic
patients [8]. Conversely, impaired insulin action can lead to
elevated triglycerides, reduced high-density lipoprotein
cholesterol (HDL -C), increase d secretion of very low-
density lipoprotein cholesterol, and hypertension [9] .In
nondiabetic subjects, regular physical activity has been
found to raise HDL-C, reduce triglyceride levels, reduce
blood pressure, decrease body weight, and increase insulin
sensitivity [10-20].
The Centers for Disease Control and Prevention (CDC)
and the American College of Sports Medicine (ACSM)
have recommended that every adult accumulate at least
30 minutes of moderate-intensity physical activity on most
days of the week [21]. Another popular recommendation is
the accumulation of 10 000 steps per day on most days of
the week. According to Tudor-Locke and Bassett [22] and
Le Masurier and colleagues [23], the amount of physical
0026-0495/$ see front matter D 2006 Elsevier Inc. All rights reserved.
doi:10.1016/j.metabol.2006.06.009
4 Corresponding author. Department of Medicine, Endocrinology and
Metabolism, University of New Mexico Health Sciences Center, MSC10-
5500, Albuquerque, NM 87131, USA. Tel.: +1 505 272 4658; fax: +1 505
272 5155.
E-mail address: mburge@salud.unm.edu (M.R. Burge).
Metabolism Clinical and Experimental 55 (2006) 1382 1387
www.elsevier.com/locate/metabol
Page 1
activity achieved by walking 10000 steps per day is in
agreement with the recommendations of the CDC and
ACSM. However, whether the achievement of moderate-
intensity physical activity goals translate into favorable
changes in glycemic control, insulin sensitivity, and/or
cardiovascular risk in patients with type 2 diabetes mellitus
over the short-term remains to be established.
Despite the known health benefits of moderate physical
activity in patients with type 2 diabetes mellitus, compli-
ance with exercise prescriptions is notoriously poor. The
recent availability of low-cost pedometers may improve
exercise complia nc e in p at ients w ith type 2 diabet es
mellitus by providing a motivational and monitoring tool
that offers immediate feedback about physical activity
levels. The purpose of this study was therefore to determine
whether a recommendation to accumulate 10 000 steps per
day, as documented by use of a pedometer, would result in
significant improvements in parameters of glycemic con-
trol, insulin sensitivity, cardiovascular risk, lipid profile,
and oxidative stress in sedentary patients with type 2
diabetes mellitus.
2. Materials and methods
2.1. Subjects
A total of 30 subjects with type 2 diabetes mellitus
participated in the study. All study subjects were between
33 and 69 years of age, had a diagnosis of type 2 diabetes
mellitus for at least 1 year, were treated with oral therapy,
and were free from advanced secondary complications of
diabetes. Oral therapies included sulfonylureas (n = 25),
metformin (n = 14), thiazolidinediones (n = 3), and statins
(n = 4). Medications and doses were not changed during
the study period, and there were no group differences in oral
therapies ( P = .51). Study exclusion criteria included preg-
nant or lactating women, anemia (hemoglobin b 11 g/100 mL
for males, hemoglobin b 10 g/100 mL for females),
cardiovascular disease, hypertension (systolic blood pres-
sure N 180 mm Hg and/or diastolic blood pressure
N 110 mm Hg), or orthopedic limitations for walking. The
study was approved by the University of New Mexico
Human Research Review Committee, and all participants
provided verbal and written consent.
2.2. Experimental design
The protocol consisted of a 10-day baseline period during
which the participants were asked not to change their
physical activity habits, followed by a 6-week intervention
period. Subjects were randomized into 1 of 2 groups (control
and active) that were matched with respect to age, hemog-
lobin A
1c
(HbA
1c
), body mass index (BMI), and percentage
of body fat. The control group was instructed to maintain
their normal activity habits throughout the 6-week interven-
tion. The active group was instruct ed to wal k 10 000 steps
on 5 or more days of the week for 6 weeks.
Each subject wore a Yamax Digiwalker step counter
(SW-701, New Lifestyles, Kansas City, MI) throughout the
day, except for sleeping and bathing, and was trained
regarding proper placement and use of the pedometer. The
pedometers were positioned on the waist, in-line with the
right mid-thigh. Each morning the pedometer was reset to
zero, and each evening the subject recorded the steps
accumulated during the day in an activity log.
Participants were asked to follow their usual eating
habits throughout the study. All participants completed a
24-hour dietary recall at baseline (week 0) and at week 6.
Data from t he 24-hour recall were analyzed using
NutritionistPro Nutrition Analysis Software (FirstData
Bank, San Bruno, CA).
2.3. Measurements
Screening data were collected during fasting outpatient
visits to the General Clinical Research Center (GCRC).
Week 0 and week 6 data were collected in the morning after
overnight hospitalization at the University of New Mexico
GCRC. All measurements were taken at the same time of
the morn ing.
2.4. Anthropometric measures
Body mass index, percentage of body fat, blood pressure,
waist circumference, and resting energy expenditure (REE)
were measured at study weeks 0 and 6. Body height and
weight were measured with subjects wearing light clothing
and without shoes. Body mass index was calculated as the
weight in kilograms divided by the square of height in
meters. Percentage of body fat was estimated with bioelec-
trical impedance analysis (RJL Systems, Quantum Series,
Clinton Township, MI). Blood pressure was measured with
subjects in the seated position with an automated monitor
(Critikon Vital Answers, Di namap Pro Series, Tampa, FL).
Standing waist circumference was measured in duplicate at
the narrowest part of the torso between the rib cage and the
iliac crest, after a normal expiration using a Guli ck
fiberglass measuring tape with a tension handle (Creative
Health Products, Plymouth, MI). Resting energy expendi-
ture was measured using indirect calor imetry in the morning
after overnight hospitalization and 12-hour fast (Sensor-
Medics, VMax 29, Yorba Linda, CA).
2.5. Sample analyses
Hemoglobin A
1c
, fructosamine, fasting glucose, fasting
insulin, fasting lipids, total radical antioxidant parameter
(TRAP), malondiald ehyde (MDA), plasminogen activator
inhibitor 1 (PAI-1), homocysteine, and lipoprotein(a)
[Lp(a)] were measured at study weeks 0 and 6. Insulin
resistance was calculated using the homeostasis model of
assessment (HOMA-IR) [24].
Study measurements were performed in the University of
New Mexico GCRC Core Laboratory. Plasma was separated
from blood elements by centrifugation immediately after
sampling and frozen at 708C for later determination.
P. Araiza et al. / Metabolism Clinical and Experimental 55 (2006) 1382 1387 1383
Page 2
Serum total cholesterol and HDL-C were measured by
enzymatic methods (TriCore Reference Laboratory, Albu-
querque, NM). Triglycerides were measured with an
oxidative method (TriCore Reference Laboratories). Plasma
glucose was measured with a glucose oxidase method
(Analox Microstat GM7, Analox Instruments, Lulenburg,
MA). Insulin was measured by a radioimmunoassay (Linco,
St Charles, MO). Hemoglobin A
1c
was assayed with a
spectrophotometric method (Bayer DCA 2000 Analyzer,
Kernersville, NC), as was fructosamine (Specialty Labora-
tories, Santa Monica, CA). Homocysteine concentrations
were determined using automated immunoassay (IMMU-
LITE Chemiluminescence System, Diagnostic Products,
Los Angeles, CA). Total radical antioxidant parameter was
determined using an immunoactivity assay read on a
microplate reader at 590 nm (Randox Laboratories, Ocean-
side, CA). Free MDA was determined using selected ion
monitoring gas chromatography-mass spectrometry (Agilent
Technologies, Palo Alto, CA). Plasminogen activator
inhibitor 1 was assayed with a bsandwich-typeQ enzyme
linked immunosorbent assay (BioPool US, Ventura, CA)
and read on a microplate reader at 490 nm. Lipoprotein (a)
was assayed with an enzyme-linked immunosorbent assay
(Esoterix Endocrinology, Calabasas Hills, CA).
2.6. Statistical analysis
Paired Student t tests were conducted to compare all
glycemic, anthropometric, oxidative stress, and cardiovas-
cular risk factor variables at baseline and week 6. For
baseline analysis between groups, Bonferroni corrections
for multiple tests were performed, and significance was
taken at P b .008 for body composition variables and P b
.004 for metabolic variables. All comparisons were repeated
using a nonparametric Wilcoxon-Mann-Whitney test. Re-
peated-measures analysis of variance (ANOVA) was per-
formed to compare all variables using the assigned activity
level as the grouping variable and time as the repeated
factor. Significance was taken at P b .05 for all ANOVA
analyses. All analyses were performed using SAS (SAS
Institute, Cary, NC). Data are presented as mean F SD.
2.7. Power analysis
A post hoc power analysis of HbA
1c
, based on an SD of
paired differences equal to 0.88 in our data, revealed
15 subjects per group were adequate to demonstrate a
statistically significant reduction in HbA
1c
of 0.7% within
the treatment group with 80% power and a = .05 by paired
t test.
3. Results
At baseline, there were no significant differences in BMI,
HbA
1c
, or percentage of body fat between the 2 groups
( P N .05, Table 1). Both groups were classified as
overweight or obese (BMI, N 25.0 kg/m
2
).
Changes in physical activity data from baseline to week 6
are presented in Fig. 1. Baseline activity levels (steps per
day) were similar between the control and active groups,
6239 F 2985 vs 7220 F 2792 steps per day, respectively
( P = .36). Participants in the active group increased their
total steps per day by an average of 69% to 10 410 F 4162
steps per day during the intervention period ( P = .002).
Activity levels for the control group did not change during
the intervention period (6240 F 2769 steps per day, P N .05).
Changes in anthropome tric measures, metabolic control,
lipid profiles, and cardiovascular risk factors at basel ine and
week 6 are presented in Table 2. There were no significant
changes in BMI, percentage of body fat, blood pressure, or
waist circumference after the 6-week intervention in either
group ( P N .05). There was a trend for decreasing systolic
blood pressure and waist circumference in the active group
after the 6-week intervention, but statistical significance was
not reached in either variable ( P N .05).
Measured REE significantly increased from baseline to
week 6 in the active group (6856 F 1451 vs 6996 F 1343
kJ/d, P = .014). No significant change in REE was noted
in the control group (8546 F 1928 vs 8914 F 2123 kJ/d,
P N .05).
Repeated-measures ANOVA demonstrated a signi ficant
main effect over time for HDL-C ( P = .022). Post hoc
analyses revealed HDL-C significantly increased in the
active group after the 6-w eek intervention ( P = .049) with
no change in the control group (.093).
Repeated-measures ANOVA demonstrated a signi ficant
group-vs-time interaction in PAI-1 ( P = .03), as PAI-1
values decreased in the active group and incre ased in the
Table 1
Baseline participant characteristics
Characteristic Control group (n = 15) Active group (n = 15)
Age (y) 51 F 10 49 F 11
HbA
1c
(%) 8.4 F 1.7 8.5 F 1.9
BMI (kg/m
2
) 33.5 F 6.6 30.0 F 4.4
Body fat (%) 36.7 F 8.7 38.0 F 10.4
Data are expressed as means F SD. P N .05 for all comparisons.
Fig. 1. Average steps per day at baseline and intervention period ( P = .002).
Data are expressed as means F SD.
P. Araiza et al. / Metabolism Clinical and Experimental 55 (2006) 1382 13871384
Page 3
control group during the 6-week intervention. As shown in
Table 2, there were no significant changes in total
cholesterol, homocysteine, fasting triglycerides, low-density
lipoprotein cholesterol (LDL-C), HbA
1c
, fasting serum
glucose, insulin, fructosamine, TRAP, MDA, HOMA-IR,
or Lp(a) during the 6-week intervention ( P N .05).
4. Discussion
Only 2 studies to date have evaluated the use of a
pedometer for increasing physical activity and insulin
sensitivity in patients with type 2 diabetes mel litus [6,25].
Yamanouchi and colleagues [6] reported that walking an
average of 19 200 steps per day combined with diet therapy
increased insulin sensitivity among 24 obese, type 2 diabetic
patients who were hospitalized for the duration of the study.
The authors reported that combining walking and dietary
restriction was more effective at improving insulin sensi-
tivity and reducing body weight than diet alone. However,
this study did not address the effects of walking on glycemic
control, oxidative stress, or cardiovascular risk factors.
Furthermore, this study demonstrated changes in insulin
sensitivity and body weight with walking an average of
19 200 steps per day (approximately 8.4 m iles) while
supervised, which may be an unattainable goal for most
diabetic patients. Katsuki and colleagues [24] reported a
significant increase in physical activity after a 16-week
intervention in sedentary patients with type 2 diabetes
mellitus . However, there were no reported changes in
resting blood pressure, fasting blood glucose, insulin
sensitivity, HbA
1c
, lipids, or triglycerides after the interven-
tion. Although this study used a pedometer, a specific goal
of 10 000 steps per day of physical activity was not used.
The main finding of the current study was that a
recommendation to walk 10 000 steps per day among
sedentary patients with type 2 diabetes mellitus was
effective at improving daily physical activity by an average
of 69%. In addition, subjects assigned to the active group
experienced a beneficial decrease in PAI-1 relative to
patients in the control group. Our data also demonstrated
a significant increase in HDL-C and REE in the acti ve group
after the intervention. However, the change in these
variables was not significant when compared with the
control group by repeated-measures ANOVA. In addition,
other lipid parameters (triglycerides, total cholesterol, and
LDL-C) showed a trend to increase in both groups, making
it difficult to interpret a significant increase in HDL-C in the
active group.
The increase in HDL-C observed in the active group after
the 6-week intervention is in agreement with past studies
[10,11]. Hardman and Hudson [10] reported an increase in
HDL-C after 12 weeks of brisk walking in sedentary
women. Similarly, Huttunen and colleagues [11] reported
an increase in HDL-C after 16 weeks of mild to moderate
physical activity in middle-aged men, independent of
changes in body weight. Our data suggest some improve-
ment in HDL-C with walking 10 000 steps per day, but no
comparison can be made to the control group.
Resting energy expenditure was significantly elevated in
the active group after the 6-week intervention. Long-term
Table 2
Change in anthropometric measures, metabolic control, lipid profiles, and cardiovascular risk factors at baseline and week 6
Parameter Control (n = 15) Active (n = 15) Wilcoxon P
Baseline Week 6 Baseline Week 6 Baseline Week 6
BMI (kg/m
2
) 33.5 F 6.6 33.2 F 6.6 30.0 F 4.4 29.3 F 4.4 .14 .10
Body fat (%) 36.7 F 8.7 36.8 F 9.1 38.0 F 10.4 37.4 F 10.2 .64 .85
SBP (mm Hg) 136.6 F 19.3 143.6 F 18.6 140.6 F 21.4 135.5 F 16.9 1.00 .20
DBP (mm Hg) 77.6 F 8.9 80.2 F 10.7 80.7 F 12.2 82.6 F 10.9 .50 .75
Waist (cm) 109.5 F 19.3 110.5 F 20.6 102.3 F 15.6 101.5 F 12.1 .29 .12
REE (kJ/d) 8546 F 1928 8914 F 2123 6856 F 1451 6996 F 13434 .03 .06
HbA
1C
(%) 8.6 F 1.7 8.7 F 1.4 8.5 F 1.6 8.7 F 1.9 .81 .65
Glucose (mg/dL) 186.3 F 57.2 184.2 F 60.9 193.6 F 60.2 192.3 F 67.0 .97 .93
Insulin (lU/mL) 14.2 F 9.9 13.9 F 8.8 14.9 F 16.0 12.9 F 8.0 .76 .84
Fructosamine (lmol/L) 337.4 F 93.2 338.3 F 96.3 327.7 F 54.4 335.3 F 63.8 .60 .72
HOMA-IR 5.9 F 4.8 5.3 F 2.6 6.7 F 3.8 6.1 F 3.3 .87 .68
Triglycerides (mg/dL) 237.1 F 137.0 246.6 F 142.4 244.7 F 141.6 268.5 F 195.6 .93 .95
Total Cholesterol (mg/dL) 200.9 F 47.4 191.5 F 28.6 189.9 F 45.9 198.0 F 48.9 .76 .73
HDL-C (mg/dL) 44.7 F 9.4 45.6 F 7.3 42.0 F 9.4 45.9 F 11.74 .37 .98
LDLC (mg/dL) 117.5 F 37.4 104.6 F 28.2 105.4 F 38.4 114.6 F 37.1 .52 .65
Lp(a) (mg/dL) 40.9 F 40.2 42.4 F 42.2 44.8 F 68.4 45.9 F 61.9 .26 .56
PAI-1 (IU/mL) 23.9 F 11.8 32.5 F 22.9 38.9
F 36.8 28.4 F 20.2y .38 .87
TRAP (mmol/L) 3.9 F 0.2 3.9 F 0.5 3.7 F 0.3 3.4 F 1.0 .04 .77
Homocysteine (lmol/L) 8.3 F 2.4 8.8 F 2.8 9.1 F 4.8 8.9 F 3.6 .82 .77
MDA (lmol/L) 0.07 F 0.05 0.09 F 0.03 0.07 F 0.03 0.11 F 0.05 .57 .23
Wilcoxon P values represent comparisons between groups at baseline to test for randomization error and week 6. SBP indicates systolic blood pressure;
DBP, diastolic blood pressure.
4 P b .05 for comparison of baseline (week 0) vs week 6 ( P b .05), within group by ANOVA.
y P b .05 for week-group interaction by ANOVA.
P. Araiza et al. / Metabolism Clinical and Experimental 55 (2006) 1382 1387 1385
Page 4
changes in REE are associated with an increase in lean body
mass after exercise training. Resting energy expenditure can
also be temporarily increased for up to 24 hours after a single
bout of exercise [26]. This increase in REE has been termed
the excess post-exercise oxygen consumption (EPOC) and
can account for a 5% to 10% incre ase in REE above normal
values [26]. Because there was no change in body compo-
sition in the present study, our data suggest that the significant
increase in REE in the active group was not a long-term
training effect of the 6-week intervention, but rather most
likely the detection of excess post-exercise oxygen consump-
tion after the last exercise event.
The significant group-vs-time interaction for PAI-1
indicates that the short-term exercise intervention had
positive effects on PAI-1 levels. There was a decreasing
trend in PAI-1 in the active group and an increasing trend in
PAI-1 in the control group. Interventions combining
exercise with diet modification have reported improvements
in PAI-1 [27]. Only one study to date supports a decrease in
PAI-1 after exercise [28]. In that study, Szymanski and
colleagues [28] showed a significant decrease in PAI-1 after
a single maximal exercise bout in inactive, regularly active
and highly active men. Conversely, Bodary and colleagues
[29] reported that 10 days of moderate-intensity exercise did
not change PAI-1 levels in healthy men and women. Janand-
Delenne and colleagues [30] have suggested that changes in
PAI-1 are mediated primarily through changes in visceral
fat. Interestingly, cross-sectional studies indicate that phys-
ically active individuals have lower resting PAI-1 activity
[28]. These findings suggest that regular physical activity
may be an important determinant of PAI-1 activity, but that
there may be a dose-response relationship between exercise
intensity and duration with PAI-1 activity. The current study
demonstrates that walking 10000 steps per day has
beneficial effects on PAI-1 activity in sedentary patients
with type 2 diabetes mellitus.
This study was limited by the duration of the intervention
and the relatively small number of subjects. A longer
intervention would be appropriate to determine if exerci se
compliance is maintained for greater than 6 weeks. All of
the subjects who were admitted into the current study
returned for all study visits and complied with the exercise
recommendations. A longer intervention would also provide
more information on the effects of habitual walking on
parameters of glycemic control, insulin sensi tivity, and
cardiovascular risk in type 2 diabetic patients. In a ddition,
the study entrance criteria limit the general izability of the
findings to type 2 diabetic patients receiving oral therapy
and cannot be extrapolated to type 2 diabetic patients
receiving insulin.
One might speculate that baseline differences in PAI-1
and REE reflect a chance failure of randomization and a
subsequent regression to a common mean. Unfortunately,
the curren t design does not allow us to further examine this
possibility. Although there is an appearance of randomiza-
tion failure with waist circumference, REE, and PAI-1,
Bonferroni cor recti ons fo r body comp ositi on va riables
would require P values of less than .05/6 = .008, and for
metabolic variables, .05/14 = .004. No baseline differences
rise to this level of significance. All comparisons were
repeated using a nonparametric Wilcoxon-Mann-Whitney
test (Table 2).
In summary, intervention with a simple pedometer
significantly increased physical activity, but did not improve
the metabolic or cardiovascular risk profile in previously
sedentary type 2 diabetic patients aside from a modest
reduction in PAI-1. Future research should include longer
interventions to better quantify the effects of walking on
glycemic control, insulin sensitivity, and cardiovascular risk
factors in these patients. The significant increase in daily
physical activity in the active group supports the use of
pedometer-based exercise prescriptions when working with
diabetic patients. Our data also suggest that providing
patients with a specific physical acti vity goal of 10 000 steps
per day results in a significant increase in physical activity
levels and may improve exercise compliance.
Acknowledgment
This research was supported by NIH NCRR GCRC grant
5M01-RR00997 from the University of New Mexico GCRC.
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    • "WFTs are becoming a major player in the consumer electronics market and many in the field are experimenting with ways of utilizing the technology's potential for patient benefit. Some studies have shown that tracking exercise with fitness trackers helps patients increase their physical activity, an observation noted in a variety of patient populations, including cardiac rehabilitation [52], chronic obstructive pulmonary disease [53] and type II diabetes [54] . A large meta-analysis of 18 randomized control and prospective trials found that tracking exercise with pedometers improved weight loss (average BMI decrease of 0.4) and systolic blood pressure (average drop of 4 mmHg) compared with no significant change in baseline groups [55]. "
    [Show abstract] [Hide abstract] ABSTRACT: Purpose of review: Frailty is the concept of accumulating physiologic declines that make people less able to deal with stressors, including surgery. Prehabilitation is intervention to enhance functional capacity before surgery. Frailty and prehabilitation among transplant populations and the role of wearable fitness tracking devices (WFTs) in delivering fitness-based interventions will be discussed. Recent findings: Frailty is associated with increased complications, longer length of hospital stay and increased mortality after surgery. Frail kidney transplant patients have increased delayed graft function, mortality and early hospital readmission. Frail lung or liver transplant patients are more likely to delist or die on the waitlist. Prehabilitation can mitigate frailty and has resulted in decreased length of hospital stay and fewer postsurgical complications among a variety of surgical populations. Increasingly, WFTs are used to monitor patient activity and improve patient health. Interventions using WFTs have resulted in improved activity, weight loss and blood pressure. Summary: Frailty is a measurable parameter that identifies patients at risk for worse health outcomes and can be mitigated through intervention. Prehabilitation to reduce frailty has been shown to improve postsurgical outcomes in a variety of populations. WFTs are being integrated in healthcare delivery for monitoring and changing health behavior with promising results.
    No preview · Article · Feb 2016 · Current opinion in organ transplantation
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    • "They revealed that body weight, BMI and the percentage of body fat were not observed in the differences between groups at 4 weeks or baseline versus 4 weeks 1 . Similarly, Araiza et al. (2006) reported that BMI and body fat showed no differences or changes either between 10,000 steps per day and the control groups both before and after study during the 6 weeks [23]. Likewise, Swartz et al. (2003) had shown that 18 overweight participants with a family history of type 2 diabetes mellitus showed no changes in BMI, body fat percentage and wrist circumference during an 8-week walking program [24]. "
    Full-text · Article · Dec 2015
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    • "Moreover, we could imagine even better results using an exercise program based on high-intensity interval training [6,8,16,17]. Also, it would have been interesting to include measurements of energy expenditure by accelerometers or podometers, since such measures were shown to improve observance to physical activity (PA) in different populations [2,15] at high risk of non-observance of regular PA [26]. Finally, it would have been useful to perform a follow-up study that examined the duration of health benefits due to this walking program. "
    [Show abstract] [Hide abstract] ABSTRACT: The aim of this study was to evaluate the impact of brisk walking on physical fitness, body composition and fasting lipid-lipoprotein profile of women 50-65 years-old, once adherence or exercise intensity is considered. A sample of 159 healthy, sedentary, obese postmenopausal women (body mass index [BMI]=29-35kg/m(2)) was subjected to 3 sessions/week of 45 min-walking, at 60% of heart rate reserve (HRR), during 16 weeks. Body composition, physical fitness and fasting lipid-lipoprotein profile were assessed before and after the intervention. Among the three tertiles of adherence to exercise sessions (<71%, 71-87%,>87%) women displaying the greatest one were characterized by the highest reduction in body weight (-1.9±2.7kg) (mean±SD), fat mass (-2.0±2.3kg) and waist girth (-4.4±3.4cm) and the best improvement in physical fitness (7.3±3.5mL O2/kg/min), (P<0.0001). A comparable analysis based on tertiles of walking intensity (<56%, 56-63%,>63% HRR) did not show between-group differences in body composition or physical fitness. Also, the fasting lipid-lipoprotein profile was improved by a reduction of cholesterol, LDL cholesterol, and triglyceride levels and by an increase in HDL cholesterol, irrespective of the participants' adherence (0.05<P<0.0001). A high practice rate seems to be the most important factor for physical fitness improvement and fat mass loss. Health benefits appear at 78minutes of brisk walk per week and increase with adherence to training, in moderately obese and initially sedentary, postmenopausal women. Copyright © 2015 Elsevier Masson SAS. All rights reserved.
    Full-text · Article · May 2015 · Annals of physical and rehabilitation medicine
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