In recent decades, the prevalence of obesity has reached epidemic proportions in the United States and is especially pronounced in certain subgroups. The 2007–2008 National Health and Nutrition Examination Survey showed that African-American (AA) women have considerably higher body mass index (BMI) values compared with women of other races and ethnicities. A staggering 78% of non-Hispanic black females in the United States are overweight or obese (BMI ≥ 25 kg·m−2) and 50% are obese (BMI ≥ 30 kg·m−2) (16). These statistics are worrisome because they place AA women at a higher risk for obesity-related comorbidities, particularly those related to cardiovascular disease (CVD).
It has been established that obesity is associated with an increased risk of CVD and metabolic syndrome (MetS). MetS includes a collection of abnormalities, associated with insulin resistance, that increase the risk of CVD. The Third Report of the National Cholesterol Education Program Adult Treatment Panel specifies MetS as the presence of at least three of five abnormalities including waist circumference >88 cm in women or >102 cm in men, blood pressure ≥130/≥85 mm Hg, triglycerides (TG) ≥150 mg·dL−1, HDL cholesterol <50 mg·dL−1 in women or <40 mg·dL−1 in men, and fasting glucose ≥100 mg·dL−1 (17). Proinflammatory and prothrombotic states are also associated with MetS and can be identified by C-reactive protein (CRP) >3.0 mg·L−1 (27) and fibrinogen ≥350 mg·dL−1 (21), respectively. With such high prevalences of overweight and obesity (16) and 39% of adult AA women in the United States having MetS (14), it is important to uncover new and diverse ways to treat and prevent multiple CVD risk factors in this population.
Weight reduction and increasing physical activity are well-established strategies for CVD risk factor improvement. AA women are currently understudied in regard to the effects of physical activity on these risk factors. This is problematic because AA women are a population in which overweight and obesity are highly prevalent, leaving them more vulnerable to the development of CVD. It has even been shown that AA women, when compared with Caucasian, Asian, and Hispanic women, are more likely to have elevated levels of most of the CVD risk factors related to MetS including waist circumference (28), hypertension (28), fasting glucose (31), CRP (3,24), and fibrinogen (4,20). In addition, several studies assessing physical activity using surveys (2,13) and pedometers (12,18) have shown that AA women are sedentary or acquire minimal amounts of daily physical activity and that they are consistently less active than their Caucasian (13,18) and Native American (2) counterparts.
The few studies that have examined the effects of aerobic exercise and ambulation-based interventions on CVD risk factors in AA women have shown improvements in waist circumference (23,45), abdominal visceral fat (5), fasting glucose (23), blood pressure (23,39,45), HDL cholesterol (5,23), and TG (5,23). Although not specific to AA women, recent studies have also shown that resistance training (RT) improves the CVD risk factors associated with MetS (7,30,42) and that improvements in several CVD risk factors were similar when comparing the effects of RT with those of aerobic training (9,15). In addition, studies have shown an inverse relationship between muscular strength and the prevalence of MetS that is independent of cardiorespiratory fitness (22,44).
There are currently few studies that have examined the benefits of RT specifically in AA women (1,34,35,38), and to our knowledge, no study has evaluated the effects of a progressive RT program on CVD risk factors in this population. The purpose of this study was to evaluate the effects of a lifestyle walking intervention (W) and lifestyle walking combined with RT (WRT) on the CVD risk factors associated with MetS in inactive middle-age AA women. We hypothesized that an intervention that combined lifestyle walking with RT would facilitate greater reductions in the CVD risk factors associated with MetS compared with the lifestyle walking intervention alone.
Subjects included 44 self-identified AA women, age 39–61 yr, who were not currently participating in any RT and not categorized as “active” (averaging <10,000 steps per day) (43). Subjects were excluded for uncontrolled hypertension, uncontrolled diabetes, active heart disease, endocrine disease, anticoagulant therapy, bleeding disorders, history of stroke, thyroid disease, being pregnant or planning to become pregnant, smoking during the past 6 months, or any physical illness/orthopedic disability that would limit ambulation or the ability to complete RT exercises. Subjects were also excluded if they were currently participating in any type of physical activity program, special diet, or weight loss program and were asked not to begin any programs of this nature for the duration of the 12-wk intervention. Interested women were prescreened via telephone for age, current physical activity level, physical limitations, and smoking status. Those who successfully completed prescreening were scheduled for their first laboratory visit where they would undergo additional screening for study inclusion.
Baseline data collection occurred during a 2-wk period. All testing procedures were reviewed and approved by the institutional review board at The Florida State University. On their initial visit, subjects reported to the laboratory in the morning after a 12-h fast. Subjects reviewed and signed an informed consent form and a medical history questionnaire. An indirect digital blood pressure measurement (Omron Healthcare, Inc., Bannockburn, IL) was taken in duplicate according to the standard guidelines outlined by the American Heart Association (32) after 5–10 min of seated rest. Height without shoes was measured by a wall-mounted stadiometer, and weight was measured using a digital scale (Seca Corporation, Hanover, MD). Waist and hip circumferences were measured using a Gulick fiberglass measuring tape with a tension handle (Creative Health Products, Inc., Ann Arbor, MI) using the American College of Sports Medicine guidelines (41).
Subjects then had finger stick blood samples collected into a heparin-treated microcapillary tube to screen for blood glucose, TG, and HDL cholesterol using a Cholestech LDX® analyzer (Cholestech Corporation, Hayward, CA). Individuals were only eligible to participate in the study if they had at least two of the following CVD risk factors associated with MetS: waist circumference > 88 cm, blood glucose ≥ 100 mg·dL−1, blood pressure ≥ 130/≥85 mm Hg, TG ≥ 150 mg·dL−1, and HDL cholesterol < 50 mg·dL−1. Venous blood samples were then collected to be used as dependent variables in data analyses. Blood samples were collected into Vacutainer® (BD, Franklin Lakes, NJ) tubes treated with sodium citrate for fibrinogen, sodium heparin for HDL cholesterol, and EDTA for glycosylated hemoglobin (HbA1c), total cholesterol, TG, and high-sensitivity CRP. Whole blood was centrifuged for 15 min at 3200 rpm, and aliquots of plasma were separated and then stored at −80°C until further analyses. Total cholesterol, HDL cholesterol, TG, and high-sensitivity CRP were quantified using colorimetric reagents and standards in a Sirrus Clinical Chemistry Analyzer (Stanbio Laboratory, Boerne, TX). HbA1c was analyzed using an A1CNow+® kit (Bayer HealthCare, Sunnyvale, CA). Fibrinogen was determined using a BBL® Fibrometer coagulation analyzer (BD Diagnostic Systems, Franklin Lakes, NJ). Blood variables were measured in duplicate after both pre- and postintervention samples were collected from all subjects.
Body composition was measured by a dual-energy x-ray absorptiometry scanner (iDXA®; GE Healthcare, Inc., Madison, WI) and analyzed using enCORE 2006 software, version 12.10 (GE Healthcare, Inc., Madison, WI). Testing was completed by a certified x-ray technician according to the manufacturer’s instructions and specifications. The areas of interest for fat distribution (android and gynoid regions) were obtained via total body scan. The lower boundary for the android obesity measurement was the top of the iliac crest, whereas the upper boundary was located at 20% of the distance between the iliac crest and the clavicle. For the gynoid obesity measurement, the upper boundary was located at the femoral neck, and the lower boundary was marked at the point allowing the height of the gynoid region to equal two times the height of the android region. All subjects reported to the laboratory no later than 10:00 a.m. in an effort to control for physical activity before body composition measurements. Upper and lower body strength was assessed using chest press and leg extension machine exercises (MedX™, Ocala, FL), respectively. After a warm-up, subjects were progressed toward the maximum weight that they could lift one time through a full range of motion or a one-repetition maximum (1-RM) (41). All measurements were recorded within approximately five attempts.
At the end of the first visit, subjects received a New Lifestyles Digi-Walker SW-200 pedometer (New Lifestyles, Inc., Lee’s Summit, MO) (37) and were instructed to record the total number of steps taken each day for 7 d on a provided activity log. For this baseline assessment, subjects were instructed not to make any changes to their typical daily routine of work and leisure activity. Subjects were also given a food log and instructed by a registered dietitian on how to record their complete dietary consumption for three consecutive days, including two weekdays and one weekend day. Subjects were strongly encouraged to remain consistent with their typical dietary habits and record each item and its amount as accurately and specifically as possible. The subjects’ diet for each day was analyzed using the Nutritionist Pro™ nutrition analysis computer software (Axxya Systems, Stafford, TX). Average caloric intake for the 3 d was calculated to provide an estimate of each subject’s typical daily consumption. Upon entering the intervention, all subjects were asked to make no changes to their typical dietary habits during the 12-wk intervention period to better isolate the influence of the exercise interventions on CVD risk factors.
At least 1 wk later, subjects returned for their second laboratory visit to find out if they were eligible for the study on the basis of the presence of risk factors from the finger stick blood samples and their physical activity classification. Resting blood pressure measurements were repeated during this visit, and the average measurement from the first and second visits was used for the dependent variable in data analyses. Strength 1-RM measurements were also repeated. The highest measurement for the upper and lower body of the two visits was considered the 1-RM. Subjects also submitted their physical activity log and 3-d diet record from the previous week during this visit. If eligible to enter the intervention, subjects were randomized, by picking a number out of a bag, into either the W group or the WRT group.
Both groups were asked to increase their daily ambulation to ≥10,000 steps per day during the 12-wk intervention. In addition, the WRT group underwent a supervised progressive RT program 2 d·wk−1. Throughout the study, all subjects were asked to wear a pedometer to monitor daily ambulatory activity. Subjects were instructed on appropriate pedometer placement on the waistband at the hip level, while its precise alignment was individually determined on the basis of a 20-step walking test for accuracy. Before putting the monitor on each morning, subjects were instructed to make sure it was set to zero and to record the time at which it was placed on the waistband. Each night before retiring, subjects recorded the number of steps on the pedometer for that day, noted the time at which the pedometer was taken off, and briefly reported the specific activities engaged in during that day. Subjects recorded data daily on a provided activity log and were asked to submit them weekly.
If randomly selected for WRT, subjects added progressive RT to their walking prescription on two nonconsecutive days each week for the entire 12 wk. All RT took place at The Florida State University Strength Laboratory. Subjects performed three sets of 8–12 repetitions of 10 resistance exercises for the lower and upper body, and all training sessions were supervised by trained exercise science students. Machine exercises (MedX™) included the chest press, seated row, overhead press, biceps curl, triceps extension, leg press, leg extension, leg curl, and abdominal crunch. Low back extensions were performed using body weight or dumbbells on a 45° Roman chair. A rest period of approximately 1 min was given between each exercise set. Training load was progressed throughout the 12 wk to keep the number of repetitions between 10 and 12. The intensity goal was to get subjects to train at approximately 60%–70% of their. 1-RM Before and after the RT sessions, subjects performed 5 min of warm-up and stretching, respectively. The strength tests described above were repeated in this group after the completion of weeks 4 and 8 and in both groups at the end of the 12-wk intervention. Strength gains were monitored to prescribe the appropriate intensity progression and provide motivation.
No less than 72 h after the completion of the intervention, all subjects returned to the laboratory to repeat all testing procedures. These included anthropometric measurements, resting blood pressure, venous blood sample collection, a body composition scan, and strength testing. Subjects also submitted another 3-d diet record that had been given to them at a previous visit or sent via e-mail.
A one-way ANOVA was used to analyze baseline measures between the two groups. A two-way repeated-measures ANOVA (group × time) was used to analyze dependent variables with repeated measures on the last factor. An intention-to-treat analysis was used to evaluate dependent measures to address the effects of the intervention on the subjects regardless of whether or not they completed the study. Using the principle of last observation carried forward, missing data points were filled using the test scores that were collected closest to the time of dropout. Secondary analyses were done on just the subjects who completed the study. One-way ANOVA analyses were used to determine the location of significant findings. Pearson product moment correlations were used to determine whether the 12 wk of W or WRT influenced blood pressure, HDL cholesterol, TG, HbA1c, mean glucose, CRP, and fibrinogen. Significance was accepted at P ≤ 0.05. All statistical analyses were performed using the SPSS software, version 18.0 (SPSS, Inc., Chicago, IL). Data are presented as means ± SD.
Of the 56 women who underwent the initial assessment, four did not return to the laboratory for their second visit for unidentified reasons, seven did not meet the inclusion criteria, and one declined the opportunity to participate in the intervention. The remaining 44 women were randomized into one of two groups. Twenty-five women were randomly assigned to the W group, and eight of them discontinued the study (32% dropout rate). These included three women who acquired an illness, three who had time/scheduling conflicts, and two who discontinued for unidentified reasons. Nineteen women were randomly assigned to the WRT group, and four discontinued the study (21% dropout rate). Two women discontinued because of time/scheduling conflicts, one woman acquired an illness, and one woman did not enjoy strength training. Thirty-two women completed the study, for a 27% dropout rate for the entire sample. At baseline, there were no significant differences between the women who did and did not complete the intervention for any variable. However, both BMI (P = 0.08) and weight (P = 0.09) were somewhat higher in the noncompleters (n = 12) versus the completers (n = 32). The intention-to-treat analyses were completed on all subjects who were initially randomized into the W (n = 25) and WRT (n = 19) groups. There were no significant (P > 0.05) differences between the W and WRT groups for any measured variable at baseline (presented in Tables 1 and 2). Both groups met the Third Report of the National Cholesterol Education Program Adult Treatment Panel criteria for MetS (17).
Body composition variables
Table 1 presents descriptive characteristics and the effects of the two exercise interventions on body composition variables. Significant group × time interactions occurred for waist circumference (F1,42 = 5.789, P ≤ 0.05, effect size (ES) = 0.12), gynoid fat mass (F1,42 = 7.023, P ≤ 0.05, ES = 0.14), and total body fat mass (F1,42 = 4.675, P ≤ 0.05, ES = 0.10). No variables changed in the W group. Although there was no interaction, there was a significant time effect for percent total body fat (F1,42 = 8.017, P ≤ 0.05, ES = 0.16). The WRT group showed a significant decrease in percent total body fat with no change in the W group.
Physical activity, strength, and diet
Table 2 presents changes in daily physical activity, strength measures, and diet. Both groups significantly increased their steps per day (W by 1392 steps per day and WRT by 2036 steps per day); however, neither group reached the goal of ≥10,000 steps per day. There was a significant interaction effect for both upper (F1,42 = 30.496, P ≤ 0.05, ES = 0.42) and lower body (F1,42 = 14.940, P ≤ 0.05, ES = 0.26) strength between the two groups. Upper and lower body strength significantly increased in the WRT group by 13% and 14%, respectively, whereas strength did not change in the W group. We did not reach the 60%–70% of 1-RM training intensity that we anticipated at the start of the study. On average, those in the WRT group who completed the intervention completed 12 repetitions for each exercise and trained at 56.0% ± 5.7% of their initial 1-RM for upper body and 60.7% ± 8.2% of their initial 1-RM for lower body. During the 12 wk, the actual RT intensity was progressed from 50.9% ± 6.1% to 60.6% ± 5.7% of initial 1-RM in the upper body and from 51.7% ± 6.5% to 68.6% ± 10.4% of initial 1-RM in the lower body. Adherence to RT, defined as the completed percentage of the prescribed sessions per week, was 96% in women who completed the study. No individual missed more than 3 of her 24 training sessions.
Three-day diet records showed no changes in average energy intake or percentage of intake from fat or CHO for the two groups. There was a significant time effect for protein intake (F1,42 = 5.717, P ≤ 0.05, ES = 0.12). The WRT group had a significant increase in the percentage of intake from protein, and the W group had no change in protein consumption.
CVD risk factors
Table 2 also presents the effects of both interventions on CVD risk factors. There were no interactions for any of these measures. There were significant time effects for HbA1c (F1,41 = 4.663, P ≤ 0.05, ES = 0.10), mean blood glucose calculated from HbA1c (F1,41 = 4.663, P ≤ 0.05, ES = 0.10), and fibrinogen (F1,42 = 4.266, P ≤ 0.05, ES = 0.09). When the groups were analyzed separately, the WRT group significantly decreased from before to after intervention in HbA1c (5.9% ± 1.2% to 5.6% ± 1.0%) and mean blood glucose calculated from HbA1c (122 ± 39 to 114 ± 32 mg·dL−1). There were no changes in these two parameters for the W group. Fibrinogen significantly increased in the WRT group from 499 ± 123 to 538 ± 129 mg·dL−1. Neither intervention had a significant effect on systolic or diastolic blood pressure, HDL cholesterol, TG, total cholesterol, or CRP. There were no significant correlations between the changes in steps per day or changes in strength and blood pressure, HDL cholesterol, TG, HbA1c, mean glucose, CRP, or fibrinogen.
When separate analyses were done for just the subjects who completed the study (W: n = 17; WRT: n = 15), there were no changes compared with the results of the intention-to-treat analyses for steps per day, strength, body composition variables, and CVD risk factors. All significant interactions and findings were consistent in both analyses for these measures.
The current study was the first to evaluate the combined effects of a lifestyle walking program and low-intensity RT on CVD risk factors in AA women. Our findings suggest that pedometer-based interventions can be a successful method for significantly improving lifestyle physical activity in this population. In addition, the WRT group was successful in significantly increasing both upper and lower body strength, despite the low-intensity nature of the protocol. The significant reductions in waist circumference, total fat mass, and gynoid fat mass in the WRT group that occurred with only moderate increases in steps per day and strength could have significant health implications if the prescribed exercise is maintained over time. Okosun et al. (29) showed that waist circumference was positively correlated with plasma glucose, fasting insulin, TG, systolic and diastolic blood pressure, total cholesterol, and total cholesterol/HDL cholesterol ratio in black and white women and men. In addition, positive health benefits have been shown when reductions in waist circumference are achieved (15,42). The small but significant pre- to postintervention improvements in percent body fat in the WRT group may also have a beneficial long-term effect on CVD risk.
The significant pre- to postintervention decreases in HbA1c and mean blood glucose calculated from HbA1c in the WRT group align with previous studies where HbA1c was improved by RT (8,9,42). In fact, upon a review of the literature, HbA1c seems to be the only CVD risk factor variable of those investigated in the current study that has been consistently shown to improve with chronic RT. A larger improvement in HbA1c may have been seen in our study if baseline values were higher. Our subjects were excluded if they had uncontrolled diabetes, so most of the subjects’ glucose levels were near normal or were being controlled. The mean blood glucose value calculated from HbA1c was used in the analyses to provide a more comprehensive indication of the subjects’ blood glucose control throughout the intervention.
Previous studies in overweight and obese subjects that evaluated steps per day and CVD risk factors found improvements in body composition and several risk factors with increases in steps per day after pedometer-based walking interventions. Improvements were shown in body weight (26,36), BMI (10,36), waist circumference (10,36), hip circumference (36), percent body fat and fat mass (36), systolic (26,40) and diastolic blood pressure (40), glucose tolerance (40), HDL cholesterol (36), and resting HR (10). Subjects in these studies increased their walking by 3451 to 5275 steps per day, resulting in average daily step counts ranging from 9213 to 10,480 steps per day. Many of these improvements were observed in as little as 8 to 12 wk.
Wilson et al. (45) found improvements in systolic blood pressure, body weight, BMI, waist and hip circumferences, and percent body fat in middle-age obese AA female breast cancer survivors after an 8-wk intervention that significantly increased walking from 4791 to 8297 steps per day. This is similar to the number of steps per day achieved in our subjects who completed the study (W = 5480 ± 2162 to 7528 ± 2046 steps per day, WRT = 4833 ± 1820 to 7412 ± 1728 steps per day); however, the subjects of Wilson et al. (45) increased their steps by a larger margin. Like the current study, Schneider et al. (36) were challenged in their effort to get obese subjects to adhere to the 10,000-steps-per-day goal but found that those who did had a more positive improvement in outcome measures, particularly in body composition variables. Their nonadherers (50% of those who completed the study) significantly increased steps from 5133 ± 1268 to 7605 ± 1290 steps per day, also similar to the completers of the current study. The above results and those of the current study suggest that in sedentary obese adults, 10,000 steps per day could be the threshold for significant CVD and body composition benefits; however, it may not be immediately feasible. Future interventions in overweight and obese AA women may be more successful in getting subjects to achieve ≥10,000 steps per day by introducing the step increases more gradually over a longer period and by incorporating more accountability into the program such as weekly laboratory check-ins or supervised group walks.
Previous RT studies that had larger strength increases showed greater improvements in CVD risk factors. Cauza et al. (9) reported a 28.9% and 47.8% increase in bench press and leg press 1-RM values, respectively, and showed a significant improvement in HbA1c, blood glucose, insulin resistance, HDL cholesterol, and TG in a sample of diabetic obese women and men after a 15-wk RT program. However, baseline values for HbA1c, blood glucose, and TG were notably higher in these subjects compared with those of the current study. Fenkci et al. (15) showed significant improvements in BMI, waist circumference, fasting glucose, systolic and diastolic blood pressure, and TG in middle-age obese women after 12 wk of RT. Except for TG, which were higher in the study by Fenkci et al., all CVD risk factor variables in this population at baseline were similar to those of the current study; however, specific strength increases were not reported. Subjects in both studies trained 3 d·wk−1.
Our results and those of previous studies in obese populations (36,45) suggest that a 10,000-steps-per-day physical activity prescription may be too aggressive initially for sedentary individuals. However, the 96% adherence to the RT sessions (in the women who completed the study) suggests that RT may be an effective method to improve CVD risk factors over time. If body weight is hindering obese individuals from taking up ambulatory activities, this population may benefit from adopting an RT program first to stimulate positive body composition changes and then incorporating ambulatory activities later to maximize CVD risk factor improvements. RT may also be more appealing and promote a greater feeling of success (11) compared with cardiovascular-based training because improvements in maximal strength can occur faster than those in maximal aerobic capacity (9). Sedentary, obese, or aging individuals or those with orthopedic or other clinical limitations may also find that RT is an attractive mode of exercise to adopt in an effort to improve CVD risk because it requires little impact or ambulation and can promote self-efficacy and psychological well-being (11).
Our study adds a novel aspect by evaluating both a proinflammatory and a prothrombotic marker for CVD by measuring CRP and fibrinogen, respectively. Although baseline CRP for both groups was above normal (>3.0 mg·L−1) (27), there were no changes detected for either group at the completion of the intervention. A study by Pieroni et al. (33) stratified a sample of blood donors by BMI to examine CRP values and found significant increases in CRP as BMI increased. When comparing our sample with patients of similar age and BMI from the study by Pieroni et al. (33), mean CRP values in our sample were slightly higher (4.34 ± 2.91 vs 3.46 ± 2.76 mg·L−1). Both of our intervention groups had increases in fibrinogen; however, the increase observed in the WRT group was significant. Banz et al. (6) found similar results showing a significant increase in fibrinogen after 10 wk of RT in middle-age android-obese men. Those authors speculated that one reason for this increase may have been due to taking the measurement too soon after the last exercise session (∼72 h), eliciting an acute elevation. This was not likely a factor in the current study because all subjects underwent posttesting ≥72 h after their final RT session, with most posttests occurring within 5 to 7 d. The significant fibrinogen increase in the current study is more bothersome than that found by Banz et al. (6) because the AA women in the current study had initial values that were already above the recommended values (≥350 mg·dL−1) (21), placing them at a higher risk for CVD at baseline. The only speculation that we can offer for the fibrinogen increase in WRT subjects is the significant increase in protein consumption. There is evidence that following a vegan diet (i.e., low protein) for as little as 3 wk significantly decreases fibrinogen levels (19). Research on the effects of diet and exercise, particularly RT, on fibrinogen is lacking overall and nonexistent in AA women. More studies are needed to evaluate whether or not a fibrinogen increase occurs consistently after chronic RT exercise and should include simultaneous monitoring of diet. The lack of research on the effects of RT on inflammatory and thrombotic markers in general makes it difficult to draw a definitive conclusion as to whether or not the current findings are typical for AA women or whether or not RT of a greater intensity and/or duration of longer than 12 wk may eventually lead to improvements in either measurement. Further research is needed to identify any patterns that may exist in RT-induced changes in inflammatory and thrombotic markers.
Some limitations of this study need to be addressed. A power analysis to determine ES was calculated for fasting blood glucose (15). This variable was chosen because previous studies have shown that RT consistently improves fasting glucose. With an ES of 0.55 and α set at 0.05, this calculation predicted that 21 subjects per group were needed for a power of 70% and 26 subjects per group were needed for a power of 80% (25). Because of the smaller number of subjects in each group, the ES was not reached and may have affected the results. The results of this study were also limited because only 4 of the 32 subjects who completed either intervention actually reached the goal of 10,000 steps per day (three subjects in the W group and one subject in the WRT group). This made it difficult to clearly define the potential benefits of the intervention and likely decreased the expected CVD risk improvements. Although step goal prescriptions were progressed individually on the basis of each subject’s baseline activity, all subjects were prescribed 10,000 steps per day no later than the beginning of week 5. Therefore, subjects with lower baseline step measures may have been asked to increase their activity by as much as 8000 steps per day within 4 wk, which is an aggressive prescription. Regardless, the intervention was successful in initiating a significant physical activity behavior change in AA women.
The current study met for RT only 2 d·wk−1 in an effort to minimize the time commitment and dropout rate because subjects were simultaneously asked to adopt a walking program into their lifestyle. Two days per week is also the minimum recommended frequency for RT prescribed by the American College of Sports Medicine (41). Postintervention analyses revealed that subjects who completed the study lifted a lower intensity (56.0% ± 5.7% and 60.7% ± 8.2% of their 1-RM for chest press and leg extension exercises, respectively) than the study goal of 60%–70% of 1-RM. The RT intensities achieved were also lower than those achieved in previous studies, which found significant improvements in several of the same CVD risk factors that were measured in the current study (9,15). Investigators and trainers found that subjects, most of whom had never trained with weights previously, felt more comfortable completing a higher number of repetitions with a lighter weight load, compared with fewer repetitions with a great amount of weight. The current study’s strength increases were not as pronounced as those achieved in other investigations, suggesting that the RT stimulus of the current study did not seem to be large enough to promote changes in many of the CVD risk factors that were measured. It seems that a threshold of strength gains or improvement of muscle quality is needed before changes in CVD risk factors are achieved. Future research on the effects of RT combined with pedometer-based ambulation on CVD risk factors in AA women should focus on the attainment of the 10,000-steps-per-day threshold and include higher intensity RT protocols for maximum benefits. Alternatively, future interventions of lower intensities, such as ours, may achieve more CVD risk factor benefits if they are longer in duration.
The nonsupervised approach in the W group compared with the twice weekly contact provided through the RT sessions in the WRT group could have affected the study outcomes; however, with the exception of an increased consumption of protein in the WRT group, there is no statistically significant data to support this assumption. Although our pedometers did not quantify walking intensity, our aim was for subjects to carry out their typical daily routine and focus on increasing overall ambulation (i.e., steps per day) through lifestyle changes, especially because the walking portion of the intervention was unsupervised. We also wanted to encourage physical activity awareness by helping subjects develop the habit of recording and interpreting their physical activity levels daily. The lower energy intake in the WRT group may raise the question of its contribution to the significant improvements in body composition and glucose control; however, results of the intention-to-treat analysis revealed no significant interaction (P = 0.230) or time effect (P = 0.230) for energy intake. Our groups were not matched for energy expenditure, so differences in the two protocols may not be directly attributed to RT. In lieu of a nonactive control group, we chose to match the walking prescription in both groups to isolate the effects of the RT. As we had hoped, both groups increased walking to the same extent essentially providing an “active” control group.
In summary, both interventions increased steps per day, but WRT was more effective in improving several body composition measures and glucose control in 12 wk. WRT may be an important addition to a lifestyle intervention aiming to facilitate reductions in CVD risk factors in overweight and obese AA women. Because there was no significant difference in steps per day between the two intervention groups at baseline and both groups increased their steps by a similar margin, these results suggest that the incorporation of RT could play a role in the reduction of abdominal obesity in AA women. Although some of the blood variables for CVD risk were not affected by the 12-wk WRT program, these results did show that improvements in body composition variables can be achieved in 12 wk. The improvement in body composition variables, particularly waist circumference, suggests that eventual improvements in CVD risk factor blood variables may occur given a longer period. AA women should be a population of priority in future intervention research because they are particularly vulnerable to the development of MetS in that they seem to be more susceptible to several of the individual CVD risk factors comprising MetS. In addition, AA women continue to be shown as a physically inactive group, a critical contributor to the development of obesity and many CVD risk factors. Because physical inactivity is modifiable, adopting an active lifestyle could prevent pharmacological intervention and protect or improve the quality of life in those at risk for CVD or other CVD-related chronic diseases.
The authors thank the American College of Sports Medicine Research Foundation and The Florida State University for the grants that supported this research study.
The authors declare no conflicts of interest.
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Keywords:©2012The American College of Sports Medicine
PEDOMETER; METABOLIC SYNDROME; WEIGHT TRAINING; OBESITY; BODY COMPOSITION; 10,000 STEPS