Prescription of Step Counts for Targeted Changes in Body Composition and Cardiometabolic Risk in Overweight/Obese Adults
Prescription of Step Counts for Targeted Changes in Body Composition and Cardiometabolic Risk in Overweight/Obese Adults
The prevalence of overweight and obesity remains epidemic in the United States, with some of the highest rates seen in older adults. While this phenomenon is certainly multifactorial, a good deal of evidence suggests that insufficient physical activity (PA) contributes significantly. Pilot data recently collected in a laboratory indicates a strong, inverse relationship between daily step counts and body fatness and cardiometabolic risk (CMR) factors when step counts are expressed relative to fat mass in young adults. This expression of PA may be especially predictive of body composition because it is influenced by factors that influence appetite and energy intake, energy expenditure, and the energy "reservoir" that is represented by body fat stores, all three elements of the "settling point" model of body weight. The strength of this relationship suggests that prescription of step counts that consider current body weight and composition, and weight loss goal, may yield predictable changes in weight and CMR in adults eating ad libitum. The long-term objective of this study is to quantify the relationship between daily step counts and body composition in young, middle aged, and older adults who are overweight/obese and develop a regression model that can be used to prescribe physical activity (daily step counts) for achieving a specific target body weight and predictably improving CMR risk for young, middle-aged, and older adult men and women over eight months while eating ad libitum. To achieve this objective, investigators will undertake two specific aims: 1) quantify the relationship between average steps·kg fat mass-1·day-1 and body composition/CMR profiles in healthy, overweight, and obese adults 20-39 years, 40-59 years, 60-79 years, and 80-plus years old, using inexpensive, widely available triaxial pedometers while eating ad libitum, and 2) quantify the efficacy of employing targeted step counts expressed as steps·kg fat mass-1·day-1 using the model developed in Aim 1 for producing predictable improvements in body composition and CMR factors in overweight and obese adults 20-39, 40-59, 60-79, and 80-plus years old, over 8 months while eating ad libitum. This study will result in a regression model that may significantly improve the way that PA is prescribed for weight management, with vast clinical and public health implications.
Aim 1: Quantify the relationship between average steps·kg fat mass-1·day-1 and body composition/CMR profiles in healthy normal, overweight, and obese adults 20-39 years, 40-59 years, 60-79 years, and 80-plus years old, using inexpensive, widely available triaxial pedometers while eating ad libitum.
Introduction. Quantifying the relationship between PA and body composition/CMR factors will result in a model for prescribing PA for weight management in overweight and obese adults eating ad libitum. The objective for this aim is to quantify the relationship between average steps·kg fat mass-1·day-1 and body composition/CMR profiles in healthy overweight and obese adults in four age groups: 20-39 years, 40-59 years, 60-79 years, and 80-plus years old, using inexpensive, widely available triaxial pedometers. The working hypotheses are that i) steps·kg fat mass-1·day-1 will be strongly associated with body composition/CMR profiles in men and women in each age group, and ii) the relationship between steps·kg fat mass-1·day-1 and body composition/CMR profile will be affected by age and sex of participants, due in part to the influence of fat-free mass on energy intake, and age-related changes in body composition and the regulation of EBAL. The approach to test these hypotheses will be to measure body composition and key CMR markers, and quantify step counts over four weeks in young, middle-aged, and older adults who are overweight or obese. In pilot studies, accelerometers were worn for 3-4 weeks, a duration that was effective for characterizing average daily step counts. The rationale for Aim 1 is that, because this unit is influenced by all of the elements of the "settling point" model of body weight (energy inputs, energy outflow, and the energy reservoir), PA expressed as steps·kg fat mass-1·day-1 is strongly associated with body composition/CMR factors, and may be used to develop a model for prescribing PA that will produce predictable improvements in body composition/CMR profiles in overweight/obese adults eating ad libitum. The expected outcome for Aim 1 is the development of a regression model that may be used for prescribing PA in young, middle-age, and older overweight/obese adults that, if adhered to, will lead to predictable changes in body composition/CMR factors while eating ad libitum.
Research Design. A total of 200 adults, 50 in each age group and equally divided between men and women, will be recruited into the first phase of this study. Measures. The primary outcome measures will be body composition [determined using 4-compartment modeling] and step counts collected for four weeks using triaxial pedometers. CMR factors will be secondary outcome measures. CMR factors will include fasting plasma glucose and insulin, and glycosylated hemoglobin (A1c). In addition, blood lipids (cholesterol, HDL, LDL, VLDL, and triglycerides) will be measured, and a common indicator of whole-body inflammatory status (hsCRP) will be assessed.
Inclusion criteria.
Laboratory Session One - Consent, Screening, Body Composition. Participants will arrive at the Exercise Physiology lab between 6:00 am and 9:00 am following a 10-12 hour fast. After providing informed consent, contact information and communication preferences, participants will complete a brief health-history form to confirm that they are eligible to participate, prescribed medications will be recorded. Thereafter, a Short Blessed Test will be administered to older adults (60-79 years) to screen for geriatric cognitive impairment. Participants who are eligible will then have height and weight measured using a stadiometer and medical-grade scale (Tanita Corporation of America, Arlington Heights, IL). Young women will be asked the number of days since the beginning of their last menstrual period, so that all body composition assessments can be conducted at approximately the same stage of the menstrual cycle. Bioelectric impedance analysis will be performed using an InBody 770 analyzer (InBody USA, Cerritos, CA), and total body water will be determined. Body composition measurement will conclude with the performance of a dual-energy x-ray absorptiometry (DEXA) scan (General Electric, Inc., Waukesha, WI). DEXA will allow for fat mass, fat-free mass, and bone mineral mass to be quantified. These measures will be used to determine body volume. Body volume, total body water, body mass, and bone mineral mass, will be used to determine 4-compartment body composition.
Daily Step Counts. Participants will be provided with a pedometer (Realalt, London, UK), and will be trained in its operation. They will be instructed to wear it every day during all waking hours (except for when swimming, bathing, or showering) while continuing with normal daily behaviors. For this phase of the study, pedometers will be modified in such a way that step counts are not visible so that participants are not influenced by reported step counts and will be carried daily for four weeks. To ensure and optimize pedometer-carrying compliance, participants will be called, text-messaged, or emailed (based on their stated preferences) at least twice weekly to encourage and remind them to carry their pedometers while otherwise continuing with normal behaviors, and to address any concerns that are raised. Participants will exchange their pedometers after two weeks of carrying. During this exchange, participants will also be asked to confirm that pedometers were carried each day, and days on which participants indicate not carrying the pedometer will be noted, and challenges/concerns will be recorded and addressed.
Laboratory Session Two - Body Composition and Cardiometabolic Risk Factors. After four weeks of carrying pedometers, participants will return to the lab and undergo an assessment of body composition identical to that completed during the first lab session. In young women, the assessment will be scheduled to align with the phase of the menstrual cycle in which the first assessment was conducted. In addition, during this lab visit, participants will provide a finger-stick blood sample to allow for measuring CMR factors. Approximately 80 µL will be collected on a protein saver card, and allowed to dry at room temperature overnight before being sealed in a plastic bag containing a desiccant packet and stored in a freezer (-20° C) until being delivered to ZRT laboratory (Beaverton, OR) for analysis (cholesterol, HDL, LDL, VLDL, triglycerides, insulin, HbA1c, and hsCRP). In addition, 5 µL blood will be deposited onto two glucose strips to allow for the measurement of fasting glucose using a Medtronic Contour glucometer (Bayer, Pittsburgh, PA). Glucose measurements will be performed in duplicate, and the mean of the two measurements will be recorded.
Data Exclusion - Energy Imbalance. The objective of Aim 1 is to determine the relationship between daily step counts and body composition in people in a state of energy balance while eating ad libitum. Therefore, participants who demonstrate a significant positive or negative energy balance (> 500 kcal·day-1, determined by measuring changes in weight, fat mass, and fat-free mass) will be considered to be in an energy imbalance, and their data will be excluded from the analysis. In addition, data from those who failed to carry pedometers at least five days per week will be excluded from the analysis.
Aim 2: Quantify the efficacy of employing targeted step counts expressed as steps·kg fat mass-1·day-1 using models developed in Aim 1 for producing predictable improvements in body composition and CMR factors in overweight and obese adults 20-39, 40-59, 60-79, and 80-plus years old, over 8 months while eating ad libitum.
Introduction. Recommendations for PA for weight management in adults often produce disappointing results, indicating that the dose of PA is often insufficient to result in a sustained energy deficit in people eating ad libitum. A key reason for this may be that these guidelines do not account for key influences of appetite and energy intake, nor the effects of changes in body weight on energy expenditure. However, results of previous studies suggest that the models developed in Aim 1 of this study are better able to do so, and therefore, may produce better weight/CMR management outcomes in overweight/obese adults eating ad libitum. The objective of Aim 2 is to determine the efficacy of the regression model developed in Aim 1 for providing step count targets expressed as steps·kg fat mass-1·day-1 in producing predictable changes in body weight and composition in overweight and obese adults 20-39, 40-59, 60-79, and 80-plus years old, over eight months while eating ad libitum. The working hypothesis is that the strong relationship between steps·kg fat mass-1·day-1 and body composition/CMR can be applied to prescribe step count targets that, if adhered to, yield predictable changes in body weight and composition in adults eating ad libitum. The approach to testing this hypothesis is to compare the actual vs predicted change in body weight and composition realized across eight months of adherence to step count prescriptions that will target a 7% weight loss while participants are eating ad libitum. The rationale for this aim is that PA targets determined using the model developed in Aim 1 will result in predictable weight loss because steps·kg fat mass-1·day-1 is affected by all three elements of the "settling point" model of body weight regulation: appetite and energy intake, energy expenditure, and the size of the energy reservoir (fat stores). The expected outcome of Aim 2 is that adherence to step count targets using the model developed in Aim 1 will result in predictable improvements in weight and body composition in adults eating ad libitum.
Research Design. A total of 120 adults, 30 in each age group, will be recruited Phase Two of the study. Each age group will be comprised of an equal number of men and women. Participants will be provided step-count targets determined using the model developed in Aim 1 to achieve a 7% reduction in body weight.
Measures. The primary outcome measure is body weight and composition, which will be determined using 4-compartment modeling. Changes in CMR factors, identical to those assessed in Aim 1, will be secondary outcome measures. Blood collection and assessment of CMR factors will be performed in a manner identical to that utilized in Aim 1 of the study. Step counts of all participants will be collected every day for eight months and average daily step counts will be calculated. Changes realized in body weight and composition, and changes in CMR factors after eight months will be compared with predicted changes using the model produced in Aim 1 of the study.
Inclusion and Exclusion criteria are identical to those in Aim 1, except that only those will a BMI between 25-32 kg·m-2 (overweight or obese) will be enrolled in Phase Two of the study.
Recruitment. Interested and eligible participants from Phase One of the study will be invited to continue to participate in phase two, and additional participants will be recruited as described in Aim 1 to achieve targeted enrollment. Participants in each age group will be equally divided between men and women.
Laboratory Session One: Consent, Screening, Body Composition, CMR Factors, and Step Count Prescription. Participants will arrive at the Exercise Physiology laboratory at Kennesaw State University between 6:00 am and 9:00 am in a fasted (10-12 hours) state. Consent, screening, assessment of body composition, collection of blood for the determination of CMR factors, determination of stage of menstrual cycle, and recording of prescribed medications will be done exactly as done in Aim 1. All participants will be provided step-count targets determined from 4-compartment body composition using the regression model developed in Aim 1 of the study. Step-count targets will be calculated to achieve a body composition change consistent with a 7% weight loss, a target that was chosen because the lifestyle intervention group in the Diabetes Prevention Program study reported improvements in clinical status in participants that were pre-diabetic at baseline who were able to achieve this level of weight loss (see "STEP Prescription Example" below).
Participants will be provided with a triaxial pedometer (Realalt, London, UK), and will be instructed in its use. Pedometers will be exchanged every two weeks so that 1) step counts can be downloaded regularly and data files kept current, and participants can be kept apprised of how well t hey are adhering to targeted step counts and be encouraged in doing so, and 2) to ensure that pedometers are provided with fresh batteries on a regular basis. In addition, weekly phone calls or emails (based on participant preference) will be used to encourage and discuss pedometer wear and address concerns that are expressed. All participants will be instructed not to alter their diets, and other than the step count objectives, to continue with normal daily activity. All participants will record dietary intake for 3 days, and dietary analysis will be completed to determine energy intake. To facilitate reaching step-count goals, participants will be provided memberships to a fitness facility of their choice (e.g., Planet Fitness, Anytime Fitness, etc.) to allow access to treadmills, and will be instructed not to engage in other forms of exercise during their involvement in the study. Pedometers will be carried daily for all waking hours except for when bathing, showering, or swimming.
STEP Prescription Example. Step count targets will be determined using the relationship between body composition and steps·kg fat mass-1·day-1. For example, consider a hypothetical 35-year-old male participant weighing 100 kg with 30% body fat. This individual currently possesses 30 kg of fat, and a recent pilot investigation yielded the power regression model: body fat percentage = 2679.5x-0.746, where x = steps·kg of fat mass-1·day-1. (This model will be revised in Aim 1 of this study using step counts derived from triaxial pedometers, instead of the wrist-worn accelerometers utilized in a pilot study.) The model predicts that this individual currently accumulates an average of 412.3 steps·kg of fat mass-1·day-1, or a total of 12,368 steps·day-1. A 7% weight loss target would require a 7 kg weight loss, so his target body weight would be 93 kg. Assuming that the entire weight loss is fat weight, his target body composition would be 23kg ÷ 93kg = 24.7% body fat. The model above estimates that men exhibiting that body composition accumulate an average of 535 steps·kg of fat mass-1·day-1. Therefore, as this participant currently has 30 kg of fat, his target would be 16,050 steps·day-1, or an increase in approximately 3,700 steps·day-1 from his current predicted level of activity. After four months, participants will undergo an intermediate body composition assessment, and step count targets will be revised given body composition at that time.
Intermediate Body Composition Assessment. After four months, all participants will be asked to again record all dietary intake for 3 days for the determination of energy intake. Participants will then return to the lab for an assessment of body composition identical to that performed during the initial lab session. Results of this assessment will be used to revise the step count targets based on body fat and composition at that time.
Post-Intervention Assessment. After the 2nd four-month period, participants will again record all dietary intake for 3 days for the determination of energy intake, to be compared with those values collected upon enrollment into phase two of the study. All participants will then be scheduled for a laboratory assessment identical to the first assessment. Changes in body composition and CMR factors will be quantified, and average daily step counts will be collected and analyzed.
Inclusion Criteria:
Exclusion Criteria:
any diagnosed cardiovascular, metabolic, renal, or pulmonary disease, or any diagnosed cognitive dysfunction
rburesh@kennesaw.edu470-578-6488
bkliszcz@kennesaw.edu