Fitness Change Effects on Midlife Metabolic Outcomes LISA CHOW 1, LYNN E. EBERLY1, ERIN AUSTIN1, MERCEDES CARNETHON2, CLAUDE BOUCHARD3, BARBARA STERNFELD4, NA ZH U 1, STEVE SIDNEY4, and PAMELA SCHREINER1
'University o f Minnesota, Minneapolis, MN; 2Northwestern University, Evanston, IL; 3Pennington Biomedical Research Center, Baton Rouge, LA; and 4Kaiser Permanente Division o f Research, Oakland, CA
ABSTRACT CHOW, L., L. E, EBERLY, E. AUSTIN, M. CARNETHON, C. BOUCHARD, B. STERNFELD, N. ZHU, S. SIDNEY, and P. SCHREINER. Fitness Change Effects on Midlife Metabolic Outcomes. Med. Sci. Sports Exerc., Vol. 47, No. 5, pp. 967-973, 2015. Purpose: Fitness decline, high body mass index (BMI), and insulin resistance (IR) are associated with worsening cardiometabolic risk factors prospectively; modification of the fitness change effect by BMI and IR remains unknown. Methods: Participants from the Coronary Artery Risk Development in Young Adults study without diabetes at year 0 (Y0) (n = 2048, 43.4% men; mean age, 25 yr) had fitness quantified by treadmill at Y0 and Y20. Y0 BMI was normal (nBMI 25 kg-nT 2). Y0 IR status was insulin sensitive (IS) (homeostatic model assessment IR 1.84). Four groups were established: nBMI/IS, hBMI/IS, nBMI/IR, and hBMI/IR. Y0 fitness was low (33rd percentile for sex). Fitness change (treadmill time: Y20-Y0) was maintained (increase or decline 20th percentile for sex). The outcomes were incident diabetes and percentage change over 25 yr in weight, waist girth, blood pressure, and lipid profile. Analysis was by multiple linear regression and proportional hazards regression with adjustment for individual characteristics. Results: Maintained fitness after 20 yr was associated with greater increase in HDL cholesterol and less increase in weight, waist girth, blood pressure, and triglycerides than decreased fitness, similarly for the groups defined by BMI and IR. Maintained fitness reduced the rate of incident diabetes in IS but not IR participants. Conclusions: Maintained fitness after 20 yr was associated with more favorable middle-age cardiometabolic risk factors than decreased fitness; this benefit might be blunted by baseline IR. Key Words: BODY MASS INDEX, INSULIN RESISTANCE, CARDIOMETABOLIC RISK FACTORS, CARDIORESPIRATORY FITNESS
Compared with peers with longitudinal CRF decrease, indi viduals with longitudinal CRF improvement or maintenance over time had lower risk o f hypertension (26), metabolic syndrome (8,26), hyperlipidemia (26), diabetes (9), cardio vascular mortality (3), and total mortality (3). Several factors, however, limit our understanding o f CRF change and health outcomes. Most (3,26) but not all (9) o f the current literature has focused on a predominantly white male population, re ducing generalizability. The time interval for measuring CRF change has varied greatly, typically spanning 5-7 yr (3,8,26). Although it had been previously shown in the Coronary Ar tery Risk Development in Young Adults (CARDIA) cohort that participants who developed diabetes over 20 yr had larger declines in fitness after 20 yr than those who did not develop diabetes (9), whether certain subpopulations, as described by body mass index (BMI) or insulin resistance (IR), might be particularly affected remains unknown. Because improving fitness on a population level is chal lenging and expensive, identification o f populations at high risk for metabolic complications from either low baseline or decreased fitness over time would enhance the impact of fitness interventions. Antecedent obesity (21) and IR (13) in crease the risk for adverse cardiometabolic outcomes, yet the health outcomes in common subgroups such as the “metabolically obese, normal weight” (34) (-2 8 % of the US population age 20 yr and older [40]) or “obese but metabolically
A
Address for correspondence: Lisa S. Chow, M.D., M.S., University of Minnesota, MMC 101 420 Delaware St. SE, Minneapolis, MN 55455; E-mail: [email protected]. Submitted for publication February 2014. Accepted for publication August 2014. 0195-9131/15/4705-0967/0 MEDICINE & SCIENCE IN SPORTS & EXERCISE® Copyright © 2014 by the American College o f Sports Medicine DOI: 10.1249/MSS.0000000000000481
967
EPIDEMIOLOGY
mericans are becoming increasingly obese and sed entary. In 2011, the majority o f Americans reported either no or low physical activity (10). Consequently, there is growing interest in the role o f physical activity and fitness in reducing the morbidity and mortality associated with the obesity epidemic. Physical activity has an established dose-response relation with fitness (11). Moderate to high fitness level, as measured by cardiorespiratory fitness (CRF) from exercise testing, has many established benefits. In several prospective studies, higher baseline CRF was associated with lower risk o f future CHD (2), metabolic syndrome (8), diabetes (29) and total mor tality (2,4). The implications o f fitness, as described by a single measurement o f CRF (2,4,29), have been subsequently com plemented by studies examining the effects o f CRF change.
EPIDEMIOLOGY
healthy” (30) (8% of the US population age 20 yr and older [40]) remain less well described. Fitness may contribute to the “obese, metabolically healthy” phenotype (30); however, the relative contribution o f fitness change remains less understood. The CARDIA cohort presents a unique opportunity to address this knowledge gap. CARDIA is a 25-yr biracial prospective cohort study that has collected both fitness and cardiometabolic data over 25 yr by standardized protocols with stringent quality control. Previously in CARDIA, it has been shown that young adults with elevated metabolic risk (as defined from a composite o f blood pressure, glucose, insulin, HDL cholesterol (HDL-C), triglycerides (TG), and waist girth) had lower baseline CRF compared with young adults with normal metabolic risk; however, the rate o f CRF decline after 20 yr was similar between the two groups (7). As this earlier CARDIA study did not describe the relation between change in long-term fitness and change in cardio metabolic risk factors (7), and another earlier CARDIA study did not subdivide by BMI and IR status (9), we will extend these previous findings by specifically examining fit ness change from year 0 (Y0) to Y20 and outcome change from Y0 to Y25 to see whether the association between young adult BMI/IR status and middle-age metabolic con sequences may be influenced by interim fitness change while controlling for baseline fitness. We hypothesize that interim fitness change alters the association between young adult BMI/IR status and middle-age cardiometabolic outcomes, with participants who maintained or increased fitness having more favorable alter ations in cardiometabolic measures than participants with de creased fitness, independent o f baseline fitness.
M ETHODS Participants. The CARDIA study is a prospective, mul ticenter, cohort study designed to investigate trends and de terminants o f CHD risk factors in young adults. Black and white women and men (age 18-30 yr at Y0) were recruited and examined in 1985-1986 from four US communities (Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA) and balanced on age, race, sex, and educational attainment as previously described (18). A total of 5115 partici pants were enrolled at baseline (Y0) with follow-up examinations at 2, 5, 7, 10, 15, 20, and 25 yr after baseline, with retention o f 91%, 86%, 81%, 79%, 74%, 72%, and 72% o f the surviv ing cohort, respectively. All participants provided written in formed consent. The study was approved by the institutional review boards from each participating institution. For this particular analysis, participants were excluded if they had elevated fasting glucose >7 m m o l - L 1 (n = 31) at baseline. O f the remaining 5084 participants, an additional 2288 participants were excluded if they were missing fitness testing at Y0 (n = 150) or Y20 (n = 2138) or if they had incomplete outcome data at Y20 (n = 23 participants not pre viously excluded) or Y25 (n = 725 participants not previously excluded). In total, 2048 participants (59% of CARDIA Y25 participants) met the study criteria for the analysis.
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Designation of Y0 BMI and IR. Y0 BMI was cate gorized as either normal (nBMI 25 kg-m-2). Y0 IR status was measured by the ho meostatic model assessment (HOMA-IR) (5). Participants were considered either insulin sensitive (IS) (FIOMA-IR 1.84)), similar to previous studies (1,33). We used Y0 BMI and IR status to classify participants into one o f four groups: 1) normal BMI/IS (nBMI/lS), 2) high BMI/IS (hBMI/ IS), 3) normal BMI/IR (nBMI/IR), and 4) high BMI/IR (hBMI/IR) (Table 1). Measurement of CRF. The CARDIA study measured CRF at Y0 and Y20 by symptom-limited graded treadmill exercise testing using a modified Balke protocol (35). Briefly, the exercise test protocol was designed to assess maximal symptom-limited perfonnance. After baseline measurement o f pulse, blood pressure, and EKG, the participant started the protocol. The protocol consisted o f nine stages (2 min each, maximum o f 18 min in total) o f progressively increas ing difficulty, with the first six stages generally performed by walking. Stage 1 was 3.0 mph at 2% grade (4.1 METs), prog ressing to stage 9 at 5.6 mph at 25% grade (19.0 METs). Y0 fitness was classified as either low (33rd percentile for sex), similar to previous literature (36) (Table 1). Because we were interested in the effects o f long-term fitness change, only fitness data from the Y0 and Y20 time points were used. Fitness change (Y20 treadmill time — Y0 treadmill time) was considered either maintained (increase or decline 20th percentile for sex) (Table 1). This 20th percentile cutoff was derived from the observation that the mean age-related decline in fitness (16) is approximately 10% (5% per decade) from the age o f 30 to 50 yr in men and women (16). In our statistical analysis, we adjusted for baseline fitness by incorporating the Y0 treadmill time as a covariate. Measurement of cardiometabolic risk factors. Car diometabolic risk factors were measured using standardized protocols across field centers and examinations with quality control monitoring (12,18). Briefly, body weight was mea sured in light clothing to the nearest 0.2 lb using a balance beam scale; waist girth was measured midway between the xiphoid process and the umbilicus (12). Blood pressure was
TABLE 1. Definition of terms used in this article. T e rm nBMI/IS hBMI/IS nBMI/IR hBMI/IR Low baseline fitness Average-high baseline fitness Maintained fitness
Decreased fitness
D e fin itio n BMI 1.84) Y0 treadmill time 468 s for women) Change in treadmill time (Y20-Y0): increase or decline 60 s in women)
http://www.acsm-msse.org
FITNESS CHANGE ON MIDLIFE METABOLIC OUTCOMES
S ta tis tic a l a n aly s is . All analyses were conducted by using SAS (version 9.2; SAS institute, Inc., Caiy, NC). Baseline characteristics were summarized for participants across the baseline groups using ANOVA (for continuous characteris tics) and Fisher’s exact test or Pearson’s chi-squared test as appropriate (for categorical characteristics). We used two multiple linear regression models (described below) to examine the associations of each of the fitness change and baseline BMI/IR status with percentage change from base line in cardiometabolic outcomes at Y25. Because there was no overall statistically significant interaction between fitness change and BMI/IR status on any o f the continuous cardio metabolic outcomes, the interaction term (fitness change x BMP IR status) was not included in the final models, and subgroup analysis for this interaction was not reported. Cox proportional hazards regression was used to examine the relations between incident diabetes and exposures. Time to diabetes was ap proximated as the difference between baseline and the first follow-up visit with a report o f diabetes. Because the interac tion between fitness change and BMI/IR status was statisti cally significant for incident diabetes, this interaction term was retained in the two models for this outcome only. The proportional hazards assumption was tested using Schoenfeld residuals (37). Model 1, for both continuous and incident di abetes outcomes, included Y0 BMI/IR status, age, race, sex and field center, fitness change (maintained vs decreased), and Y0 fitness (treadmill duration). Model 2 further adjusted for other relevant covariates measured at Y0: education (highest year o f school completed), cigarette smoking (current/former/ never), alcohol consumption (mL-d-1), total physical activ ity intensity score (in EU with >800 EU being very high ac tivity) (22), and energy intake (total kilocalories per day).
RESULTS B aseline c h ara c te ris tic s fo r particip an ts as s e p a rated by young ad u lt B M I, IR status. The mean age
ranged from 23 to 26 yr old at baseline (Y0) across BMI and IR groups. The sex distribution was similar across all four categories (nBMI/IS, hBMI/IS, nBMI/IR, and hBMI/IR). Table 2 reports the baseline values (mean ± SD if continuous variables, percentages if categorical). In the hBMI/IR group, there were fewer participants who had education beyond high school (62%) and who are white (37%). Caloric intake and alcohol use were similar across BMI and IR groups. The hBMI/IR participants (n = 305) had the highest mean weight (88.5 ± 16.3 kg), waist girth (91 ± 12 cm), BMI (30.4 ± 5 kg-m 2), MAP (85 ± 9 mm Hg), fasting glu cose (4.8 ± 0.4 mmol-L-1), LDL-C (3.13 + 0.78 mmol-L-1), TG (1.05 + 0.77 mmol-L-1), and HOMA-IR (2.8 + 1.1). The hBMI/IR participants had the lowest physical activity (355 + 263 EU), baseline treadmill exercise time (501 + 158 s), and HDL-C (1.22 + 0.28 mmol-L '). In terms o f baseline fitness, the hBMI/IR participants had the highest percentage o f low fit participants (71%), followed by hBMI/IS (43%), nBMI/IR (33%), and nBMI/IS (21%).
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EPIDEMIOLOGY
measured three times after a 5-min rest using a Hawksley random zero sphygmomanometer (WA Baum Company, Copiague, NY) on the right arm o f the seated participant at YO and a standard automated aneroid monitor (OmROn model HEM907XL; Omron Healthcare, Inc., Lake Forest, IL) at Y20. For each visit, the average of the last two measures was used (12). Fasting plasma blood samples were sent to the Northwest Lipid Research Laboratories, University o f Washington (Seattle, WA), for lipid detennination. Total cholesterol and TG were measured enzymatically (38), HDL-C was deter mined after dextran sulfate-m agnesium chloride precipita tion (39), and LDL cholesterol (LDL-C) was calculated using the Friedewald equation (17). Serum glucose con centrations were measured using the hexokinase method at Linco Research Inc. (St. Charles, MO). Serum insulin was measured by immunoassay (12). H bA lc samples were sent to the University o f Minnesota (Minneapolis, MN) and were measured using the Tosoh G7 high-performance liquid chromatography instrument (Tosoh Bioscience, Inc.; South San Francisco, CA). Incident diabetes in nonpregnant partic ipants was determined at each follow-up visit (year 7, 10, 15, 20, or 25) if any o f the following criteria were met: fasting glucose >7 mmol-L ', use o f medications for diabetes treat ment, 2-h glucose tolerance test >11.1 mmol-L-1 (performed at Y10, Y20, or Y25), or hemoglobin H bA lc >6.5% (48 m m olm ol-1 ) (performed at Y20 or Y25). O u tc o m e s . The primaiy outcomes were percentage change (100 x [Y25 — YOj/YO) in weight and in waist girth between YO and Y25 as well as incident diabetes by Y25. The sec ondary outcomes were percentage change in cardiometabolic risk factors including mean arterial pressure (MAP) ([2 x DBP + SBPJ/3), LDL-C, TG, and HDL-C. O th e r m e a s u re m e n ts . Covariates were selected as possible confounders in our analysis because o f their clinical relevance and association with BMI, IR, or fitness (7,8,16). Relevant covariates were measured at YO and included age, sex, race (black vs white), field center, and lifestyle factors (physical activity, smoking, energy intake, alcohol intake, and education level). These covariates were measured by trained and certified staff' using standardized protocols across field centers and examinations with quality control monitoring (12,18). Age, race, and sex were confirmed during the clinic visits. Educational attainment was based on self-reported number o f years o f schooling and the highest degree earned at the last follow-up examination attended. Elapsed time be tween examinations was calculated using the baseline and follow-up examination dates. Physical activity level (reported as exercise units (EU)) was measured using the CARDIA physical activity history questionnaire, an interviewer-based self-report of duration and intensity of participation in 13 cat egories o f exercise over the previous 12 months (22). For ref erence, 300 EU approximates 150 min of moderate-intensity activity (3-5 METs) per week or 30 min of moderate-intensity activity 5 d-wk 1 (32). Diet was quantified (including total en ergy intake) using a semiquantitative, interviewer-administrated, validated diet history food frequency questionnaire (28).
TABLE 2. Baseline variables by baseline BMI/IR status.
hBIVII
nBMI V aria b le (SD) n Age (yr) Gender (% men) Race (% white) Weight (kg) Waist girth (cm) BMI (kg-m-2) Smoking (% never smoked) Caloric intake (kcai) Alcohol consumption (milliliters of alcohol per day) Level of education (% more than high school education) Study center Birmingham Chicago Minneapolis Oakland Total activity (EU) Baseline treadmill time (s) MAP (mm Hg) Glucose (mmol-L-1) LDL (mmol-L-1 ) HDL (mmol-L-1) TG (mmol-L-1) H0MA-IR Population with low fitness at baseline (n, % of BMI/insulin sensitivity category) (
'University o f Minnesota, Minneapolis, MN; 2Northwestern University, Evanston, IL; 3Pennington Biomedical Research Center, Baton Rouge, LA; and 4Kaiser Permanente Division o f Research, Oakland, CA
ABSTRACT CHOW, L., L. E, EBERLY, E. AUSTIN, M. CARNETHON, C. BOUCHARD, B. STERNFELD, N. ZHU, S. SIDNEY, and P. SCHREINER. Fitness Change Effects on Midlife Metabolic Outcomes. Med. Sci. Sports Exerc., Vol. 47, No. 5, pp. 967-973, 2015. Purpose: Fitness decline, high body mass index (BMI), and insulin resistance (IR) are associated with worsening cardiometabolic risk factors prospectively; modification of the fitness change effect by BMI and IR remains unknown. Methods: Participants from the Coronary Artery Risk Development in Young Adults study without diabetes at year 0 (Y0) (n = 2048, 43.4% men; mean age, 25 yr) had fitness quantified by treadmill at Y0 and Y20. Y0 BMI was normal (nBMI 25 kg-nT 2). Y0 IR status was insulin sensitive (IS) (homeostatic model assessment IR 1.84). Four groups were established: nBMI/IS, hBMI/IS, nBMI/IR, and hBMI/IR. Y0 fitness was low (33rd percentile for sex). Fitness change (treadmill time: Y20-Y0) was maintained (increase or decline 20th percentile for sex). The outcomes were incident diabetes and percentage change over 25 yr in weight, waist girth, blood pressure, and lipid profile. Analysis was by multiple linear regression and proportional hazards regression with adjustment for individual characteristics. Results: Maintained fitness after 20 yr was associated with greater increase in HDL cholesterol and less increase in weight, waist girth, blood pressure, and triglycerides than decreased fitness, similarly for the groups defined by BMI and IR. Maintained fitness reduced the rate of incident diabetes in IS but not IR participants. Conclusions: Maintained fitness after 20 yr was associated with more favorable middle-age cardiometabolic risk factors than decreased fitness; this benefit might be blunted by baseline IR. Key Words: BODY MASS INDEX, INSULIN RESISTANCE, CARDIOMETABOLIC RISK FACTORS, CARDIORESPIRATORY FITNESS
Compared with peers with longitudinal CRF decrease, indi viduals with longitudinal CRF improvement or maintenance over time had lower risk o f hypertension (26), metabolic syndrome (8,26), hyperlipidemia (26), diabetes (9), cardio vascular mortality (3), and total mortality (3). Several factors, however, limit our understanding o f CRF change and health outcomes. Most (3,26) but not all (9) o f the current literature has focused on a predominantly white male population, re ducing generalizability. The time interval for measuring CRF change has varied greatly, typically spanning 5-7 yr (3,8,26). Although it had been previously shown in the Coronary Ar tery Risk Development in Young Adults (CARDIA) cohort that participants who developed diabetes over 20 yr had larger declines in fitness after 20 yr than those who did not develop diabetes (9), whether certain subpopulations, as described by body mass index (BMI) or insulin resistance (IR), might be particularly affected remains unknown. Because improving fitness on a population level is chal lenging and expensive, identification o f populations at high risk for metabolic complications from either low baseline or decreased fitness over time would enhance the impact of fitness interventions. Antecedent obesity (21) and IR (13) in crease the risk for adverse cardiometabolic outcomes, yet the health outcomes in common subgroups such as the “metabolically obese, normal weight” (34) (-2 8 % of the US population age 20 yr and older [40]) or “obese but metabolically
A
Address for correspondence: Lisa S. Chow, M.D., M.S., University of Minnesota, MMC 101 420 Delaware St. SE, Minneapolis, MN 55455; E-mail: [email protected]. Submitted for publication February 2014. Accepted for publication August 2014. 0195-9131/15/4705-0967/0 MEDICINE & SCIENCE IN SPORTS & EXERCISE® Copyright © 2014 by the American College o f Sports Medicine DOI: 10.1249/MSS.0000000000000481
967
EPIDEMIOLOGY
mericans are becoming increasingly obese and sed entary. In 2011, the majority o f Americans reported either no or low physical activity (10). Consequently, there is growing interest in the role o f physical activity and fitness in reducing the morbidity and mortality associated with the obesity epidemic. Physical activity has an established dose-response relation with fitness (11). Moderate to high fitness level, as measured by cardiorespiratory fitness (CRF) from exercise testing, has many established benefits. In several prospective studies, higher baseline CRF was associated with lower risk o f future CHD (2), metabolic syndrome (8), diabetes (29) and total mor tality (2,4). The implications o f fitness, as described by a single measurement o f CRF (2,4,29), have been subsequently com plemented by studies examining the effects o f CRF change.
EPIDEMIOLOGY
healthy” (30) (8% of the US population age 20 yr and older [40]) remain less well described. Fitness may contribute to the “obese, metabolically healthy” phenotype (30); however, the relative contribution o f fitness change remains less understood. The CARDIA cohort presents a unique opportunity to address this knowledge gap. CARDIA is a 25-yr biracial prospective cohort study that has collected both fitness and cardiometabolic data over 25 yr by standardized protocols with stringent quality control. Previously in CARDIA, it has been shown that young adults with elevated metabolic risk (as defined from a composite o f blood pressure, glucose, insulin, HDL cholesterol (HDL-C), triglycerides (TG), and waist girth) had lower baseline CRF compared with young adults with normal metabolic risk; however, the rate o f CRF decline after 20 yr was similar between the two groups (7). As this earlier CARDIA study did not describe the relation between change in long-term fitness and change in cardio metabolic risk factors (7), and another earlier CARDIA study did not subdivide by BMI and IR status (9), we will extend these previous findings by specifically examining fit ness change from year 0 (Y0) to Y20 and outcome change from Y0 to Y25 to see whether the association between young adult BMI/IR status and middle-age metabolic con sequences may be influenced by interim fitness change while controlling for baseline fitness. We hypothesize that interim fitness change alters the association between young adult BMI/IR status and middle-age cardiometabolic outcomes, with participants who maintained or increased fitness having more favorable alter ations in cardiometabolic measures than participants with de creased fitness, independent o f baseline fitness.
M ETHODS Participants. The CARDIA study is a prospective, mul ticenter, cohort study designed to investigate trends and de terminants o f CHD risk factors in young adults. Black and white women and men (age 18-30 yr at Y0) were recruited and examined in 1985-1986 from four US communities (Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA) and balanced on age, race, sex, and educational attainment as previously described (18). A total of 5115 partici pants were enrolled at baseline (Y0) with follow-up examinations at 2, 5, 7, 10, 15, 20, and 25 yr after baseline, with retention o f 91%, 86%, 81%, 79%, 74%, 72%, and 72% o f the surviv ing cohort, respectively. All participants provided written in formed consent. The study was approved by the institutional review boards from each participating institution. For this particular analysis, participants were excluded if they had elevated fasting glucose >7 m m o l - L 1 (n = 31) at baseline. O f the remaining 5084 participants, an additional 2288 participants were excluded if they were missing fitness testing at Y0 (n = 150) or Y20 (n = 2138) or if they had incomplete outcome data at Y20 (n = 23 participants not pre viously excluded) or Y25 (n = 725 participants not previously excluded). In total, 2048 participants (59% of CARDIA Y25 participants) met the study criteria for the analysis.
968
Official Journal of the American College of Sports Medicine
Designation of Y0 BMI and IR. Y0 BMI was cate gorized as either normal (nBMI 25 kg-m-2). Y0 IR status was measured by the ho meostatic model assessment (HOMA-IR) (5). Participants were considered either insulin sensitive (IS) (FIOMA-IR 1.84)), similar to previous studies (1,33). We used Y0 BMI and IR status to classify participants into one o f four groups: 1) normal BMI/IS (nBMI/lS), 2) high BMI/IS (hBMI/ IS), 3) normal BMI/IR (nBMI/IR), and 4) high BMI/IR (hBMI/IR) (Table 1). Measurement of CRF. The CARDIA study measured CRF at Y0 and Y20 by symptom-limited graded treadmill exercise testing using a modified Balke protocol (35). Briefly, the exercise test protocol was designed to assess maximal symptom-limited perfonnance. After baseline measurement o f pulse, blood pressure, and EKG, the participant started the protocol. The protocol consisted o f nine stages (2 min each, maximum o f 18 min in total) o f progressively increas ing difficulty, with the first six stages generally performed by walking. Stage 1 was 3.0 mph at 2% grade (4.1 METs), prog ressing to stage 9 at 5.6 mph at 25% grade (19.0 METs). Y0 fitness was classified as either low (33rd percentile for sex), similar to previous literature (36) (Table 1). Because we were interested in the effects o f long-term fitness change, only fitness data from the Y0 and Y20 time points were used. Fitness change (Y20 treadmill time — Y0 treadmill time) was considered either maintained (increase or decline 20th percentile for sex) (Table 1). This 20th percentile cutoff was derived from the observation that the mean age-related decline in fitness (16) is approximately 10% (5% per decade) from the age o f 30 to 50 yr in men and women (16). In our statistical analysis, we adjusted for baseline fitness by incorporating the Y0 treadmill time as a covariate. Measurement of cardiometabolic risk factors. Car diometabolic risk factors were measured using standardized protocols across field centers and examinations with quality control monitoring (12,18). Briefly, body weight was mea sured in light clothing to the nearest 0.2 lb using a balance beam scale; waist girth was measured midway between the xiphoid process and the umbilicus (12). Blood pressure was
TABLE 1. Definition of terms used in this article. T e rm nBMI/IS hBMI/IS nBMI/IR hBMI/IR Low baseline fitness Average-high baseline fitness Maintained fitness
Decreased fitness
D e fin itio n BMI 1.84) Y0 treadmill time 468 s for women) Change in treadmill time (Y20-Y0): increase or decline 60 s in women)
http://www.acsm-msse.org
FITNESS CHANGE ON MIDLIFE METABOLIC OUTCOMES
S ta tis tic a l a n aly s is . All analyses were conducted by using SAS (version 9.2; SAS institute, Inc., Caiy, NC). Baseline characteristics were summarized for participants across the baseline groups using ANOVA (for continuous characteris tics) and Fisher’s exact test or Pearson’s chi-squared test as appropriate (for categorical characteristics). We used two multiple linear regression models (described below) to examine the associations of each of the fitness change and baseline BMI/IR status with percentage change from base line in cardiometabolic outcomes at Y25. Because there was no overall statistically significant interaction between fitness change and BMI/IR status on any o f the continuous cardio metabolic outcomes, the interaction term (fitness change x BMP IR status) was not included in the final models, and subgroup analysis for this interaction was not reported. Cox proportional hazards regression was used to examine the relations between incident diabetes and exposures. Time to diabetes was ap proximated as the difference between baseline and the first follow-up visit with a report o f diabetes. Because the interac tion between fitness change and BMI/IR status was statisti cally significant for incident diabetes, this interaction term was retained in the two models for this outcome only. The proportional hazards assumption was tested using Schoenfeld residuals (37). Model 1, for both continuous and incident di abetes outcomes, included Y0 BMI/IR status, age, race, sex and field center, fitness change (maintained vs decreased), and Y0 fitness (treadmill duration). Model 2 further adjusted for other relevant covariates measured at Y0: education (highest year o f school completed), cigarette smoking (current/former/ never), alcohol consumption (mL-d-1), total physical activ ity intensity score (in EU with >800 EU being very high ac tivity) (22), and energy intake (total kilocalories per day).
RESULTS B aseline c h ara c te ris tic s fo r particip an ts as s e p a rated by young ad u lt B M I, IR status. The mean age
ranged from 23 to 26 yr old at baseline (Y0) across BMI and IR groups. The sex distribution was similar across all four categories (nBMI/IS, hBMI/IS, nBMI/IR, and hBMI/IR). Table 2 reports the baseline values (mean ± SD if continuous variables, percentages if categorical). In the hBMI/IR group, there were fewer participants who had education beyond high school (62%) and who are white (37%). Caloric intake and alcohol use were similar across BMI and IR groups. The hBMI/IR participants (n = 305) had the highest mean weight (88.5 ± 16.3 kg), waist girth (91 ± 12 cm), BMI (30.4 ± 5 kg-m 2), MAP (85 ± 9 mm Hg), fasting glu cose (4.8 ± 0.4 mmol-L-1), LDL-C (3.13 + 0.78 mmol-L-1), TG (1.05 + 0.77 mmol-L-1), and HOMA-IR (2.8 + 1.1). The hBMI/IR participants had the lowest physical activity (355 + 263 EU), baseline treadmill exercise time (501 + 158 s), and HDL-C (1.22 + 0.28 mmol-L '). In terms o f baseline fitness, the hBMI/IR participants had the highest percentage o f low fit participants (71%), followed by hBMI/IS (43%), nBMI/IR (33%), and nBMI/IS (21%).
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EPIDEMIOLOGY
measured three times after a 5-min rest using a Hawksley random zero sphygmomanometer (WA Baum Company, Copiague, NY) on the right arm o f the seated participant at YO and a standard automated aneroid monitor (OmROn model HEM907XL; Omron Healthcare, Inc., Lake Forest, IL) at Y20. For each visit, the average of the last two measures was used (12). Fasting plasma blood samples were sent to the Northwest Lipid Research Laboratories, University o f Washington (Seattle, WA), for lipid detennination. Total cholesterol and TG were measured enzymatically (38), HDL-C was deter mined after dextran sulfate-m agnesium chloride precipita tion (39), and LDL cholesterol (LDL-C) was calculated using the Friedewald equation (17). Serum glucose con centrations were measured using the hexokinase method at Linco Research Inc. (St. Charles, MO). Serum insulin was measured by immunoassay (12). H bA lc samples were sent to the University o f Minnesota (Minneapolis, MN) and were measured using the Tosoh G7 high-performance liquid chromatography instrument (Tosoh Bioscience, Inc.; South San Francisco, CA). Incident diabetes in nonpregnant partic ipants was determined at each follow-up visit (year 7, 10, 15, 20, or 25) if any o f the following criteria were met: fasting glucose >7 mmol-L ', use o f medications for diabetes treat ment, 2-h glucose tolerance test >11.1 mmol-L-1 (performed at Y10, Y20, or Y25), or hemoglobin H bA lc >6.5% (48 m m olm ol-1 ) (performed at Y20 or Y25). O u tc o m e s . The primaiy outcomes were percentage change (100 x [Y25 — YOj/YO) in weight and in waist girth between YO and Y25 as well as incident diabetes by Y25. The sec ondary outcomes were percentage change in cardiometabolic risk factors including mean arterial pressure (MAP) ([2 x DBP + SBPJ/3), LDL-C, TG, and HDL-C. O th e r m e a s u re m e n ts . Covariates were selected as possible confounders in our analysis because o f their clinical relevance and association with BMI, IR, or fitness (7,8,16). Relevant covariates were measured at YO and included age, sex, race (black vs white), field center, and lifestyle factors (physical activity, smoking, energy intake, alcohol intake, and education level). These covariates were measured by trained and certified staff' using standardized protocols across field centers and examinations with quality control monitoring (12,18). Age, race, and sex were confirmed during the clinic visits. Educational attainment was based on self-reported number o f years o f schooling and the highest degree earned at the last follow-up examination attended. Elapsed time be tween examinations was calculated using the baseline and follow-up examination dates. Physical activity level (reported as exercise units (EU)) was measured using the CARDIA physical activity history questionnaire, an interviewer-based self-report of duration and intensity of participation in 13 cat egories o f exercise over the previous 12 months (22). For ref erence, 300 EU approximates 150 min of moderate-intensity activity (3-5 METs) per week or 30 min of moderate-intensity activity 5 d-wk 1 (32). Diet was quantified (including total en ergy intake) using a semiquantitative, interviewer-administrated, validated diet history food frequency questionnaire (28).
TABLE 2. Baseline variables by baseline BMI/IR status.
hBIVII
nBMI V aria b le (SD) n Age (yr) Gender (% men) Race (% white) Weight (kg) Waist girth (cm) BMI (kg-m-2) Smoking (% never smoked) Caloric intake (kcai) Alcohol consumption (milliliters of alcohol per day) Level of education (% more than high school education) Study center Birmingham Chicago Minneapolis Oakland Total activity (EU) Baseline treadmill time (s) MAP (mm Hg) Glucose (mmol-L-1) LDL (mmol-L-1 ) HDL (mmol-L-1) TG (mmol-L-1) H0MA-IR Population with low fitness at baseline (n, % of BMI/insulin sensitivity category) (
