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Abstract

Background

Physical activity becomes increasingly fragmented with age, which may be an early marker of functional decline. Energetic cost of walking and energy capacity are also linked with functional decline, but their associations with activity fragmentation, and the potential modifying roles of total daily physical activity and age, remains unclear.

Method

A total of 493 participants (50–93 years) from the Baltimore Longitudinal Study of Aging underwent measures of energetic cost of usual-paced overground walking (mL/kg/m), energy demand during slow walking (mL/kg/min) on a treadmill (0.67 m/s, 0% grade), and average peak walking energy expenditure (mL/kg/min) during a fast-paced 400-m walk. A ratio of slow walking to peak walking energy expenditure (“cost-to-capacity ratio”) was calculated. Activity fragmentation was quantified as an active-to-sedentary transition probability (ASTP) using Actiheart accelerometer data. Linear regression models with ASTP as the dependent variable were used to test whether poorer energy cost and capacity were associated with higher ASTP and whether the associations differed by daily physical activity or age.

Results

After adjusting for demographics, body composition, comorbidities, and daily physical activity, every 10% higher cost-to-capacity ratio was associated with 0.4% greater ASTP (p = .005). This association was primarily driven by the least active participants (pinteraction = .023). Peak walking energy expenditure was only associated with ASTP among participants aged ≥70 years.

Conclusions

Higher cost-to-capacity ratio and lower energy capacity may manifest as more fragmented physical activity, especially among those less active or aged ≥70 years. Future studies should examine whether an increasing cost-to-capacity ratio or declining energy capacity predicts subsequent activity fragmentation.

Activity fragmentation, Energy capacity, Energy cost, Energy utilization, Walking efficiency

Historically, the majority of physical activity research in older adults has focused on total daily or weekly summary measures, or compliance with public health guidelines (1,2). More recently, studies on periodicity and time patterns of daily physical activity have gained interest (3–7). Such studies include diurnal patterns (8,9), active and sedentary bouts (10–13), and activity fragmentation (14–16), which have emerged as earlier markers of health and function status in older adults.

Activity fragmentation is typically quantified by the probability of transitioning from an active to a sedentary state using minute-by-minute accelerometer data collected across multiple days. A higher transition probability means more frequent switching to a sedentary state, and hence shorter duration of active bouts on average (14,17). Activity fragmentation has been shown to be more strongly associated with physical functioning (14), higher perceived fatigability (14,16), cancer history (18), and mortality risk (15,17,19) than traditional measures of physical activity volume.

Energy availability for essential and desired activity, which has been proposed as a domain of phenotypic aging (20), depends on 2 components—energy capacity, the maximum amount of energy available to sustain life and support various daily activities, and energy cost, the energy consumed for daily activities (21). Both components and their combination have been associated with many of the same outcomes as activity fragmentation, including slow and declining gait speed (22–25), and higher perceived fatigability (26,27). Therefore, it has been postulated that decline in energy availability with age is one of the possible physiologic mechanisms underlying more fragmented physical activity among older adults (14,27–29). However, to our knowledge, no studies have explored the association between energetics and activity fragmentation.

The present cross-sectional study investigates the associations between energetic measures: (i) energy capacity during peak sustained walking, (ii) energy demand during slow walking, (iii) energy cost during customary walking, and (iv) energy utilization, a combination of energy capacity and cost, quantified as a ratio of energy demand (a measure of energy cost) to energy capacity (“cost-to-capacity ratio”), and activity fragmentation. Illuminating which aspect of energetics—lower energy capacity, higher energy cost, or a combination thereof—is most strongly associated with activity fragmentation may provide more novel, sensitive targets for intervention and treatment than traditional rehabilitative efforts. We hypothesized that a higher energetic cost of walking, lower peak walking energy expenditure, and a higher cost-to-capacity ratio would be associated with higher activity fragmentation. Since activity fragmentation was low among participants with high level of physical activity and the interindividual difference may not be meaningful, we further tested whether the associations between the energetic measures and activity fragmentation differed by total volume of daily physical activity, specifically, whether the activity patterns of more active participants were less affected by energetics than less active participants. Two other potential effect modifiers, age and sex, were also explored.

Method

Study Population

The study sample consisted of 493 participants aged 50–93 years from the Baltimore Longitudinal Study of Aging (BLSA) who underwent energy expenditure testing and wore an Actiheart physical activity monitor between December 2007 and March 2015. The BLSA is a community-based cohort study of normative human aging established in 1958. A general description of the population and enrollment criteria and procedures have been reported elsewhere (20). Briefly, the BLSA is a continuously enrolled cohort of community-dwelling volunteers who pass comprehensive health and functional screening evaluations and are free of major chronic conditions and cognitive and functional impairment at the time of enrollment. Once enrolled, participants are followed for life and undergo extensive testing every 1–4 years depending on age (<60 every 4 years, 60–79 every 2 years, ≥80 every year).

Physical Activity

Physical activity was measured using the Actiheart accelerometer (CamNtech, Cambridge, UK), a unidirectional device that monitors heart rate and physical activity. The device was fitted on participants’ chests at the third intercostal space using 2 standard electrocardiogram electrodes. Acceleration was measured in 32 Hz for the following 7 days in the free-living environment. Data were downloaded using commercial software (ActiLife, version 4.0.32) to derive activity counts in 1-minute epochs. Days with less than 5%, or 72 minutes, of data missing were counted as valid days (30). To be included in the analysis, participants were required to have at least 3 valid days of wear. Missing data for each valid day were imputed by minute as the average activity counts from the same minute across other valid days for each participant (30). Among the 2 545 valid days contributed by the 493 participants in our sample, 1 361 valid days (53.5%) from 445 participants had 26 694 minutes imputed (7.3% of the total minutes). The 445 participants had an average of 60.0 ± 42.8 minutes imputed. Minute-level mean activity counts for each minute of the day (12:00 am to 11:59 pm) were derived by averaging the activity counts in that minute across all valid days. Total daily physical activity was extracted as the sum of the log transformed minute-level activity counts (ie, total log activity count) due to the skewed distribution (31).

To calculate activity fragmentation, each participant’s active and sedentary states on a minute-by-minute basis (12:00 am to 11:59 pm) were determined for each valid day. An active state was indicated when activity counts were ≥10 counts/min and a sedentary/sleep state was indicated when activity counts were <10 counts/min (14,15,32). Bout length was defined as the number of consecutive minutes spent in either an active or sedentary state and a daily activity profile was created for each participant to detect alternating bouts of sedentary and active states. An active-to-sedentary transition probability (ASTP) was defined as the probability of transitioning from an active to a sedentary state, and calculated for each participant as the reciprocal of the average active bout duration (14).

Walking Energy Expenditure

Average peak walking energy expenditure (mL/kg/min) was assessed using a Cosmed K4b2 portable metabolic analyzer (Cosmed, Rome, Italy) during a fast 400-m walk, one of the 2 components of the long-distance corridor walk, a validated measure of cardiorespiratory fitness in older adults (33,34). The test was performed on a 20-m course in an uncarpeted corridor marked by cones at both ends. The participants were asked to walk as fast as possible at a pace they could sustain for 400 m. Standard encouragement was given with each lap along with the number of laps remaining. VO2 readings from the first 1.5 minutes were discarded, as the participants adjusted to the workload during the period. Readings after the first 1.5 minutes were used to calculate the volume of oxygen consumed per kilogram of body weight per minute (VO2 mL/kg/min) (29).

The energetic cost of customary walking (mL/kg/m) was measured using the same Cosmed K4b2 portable metabolic analyzer during a 2.5-minute walking test. Participants were asked to walk at their usual pace on a 20-m course. Readings from the first 1.5 minutes were discarded, and the remaining values were averaged and then divided by the distance (m) covered during the 2.5 minutes to provide a standardized measure of expenditure per meter (mL/kg/m) (23).

The energetic demand during slow walking (mL/kg/min) was assessed via indirect calorimetry (Medical Graphics Corp, St Paul, MN) during a 5-min walk on treadmill at 0.67 m/s (1.5 mph) and 0% grade. A single speed was used for all participants, providing a standardized measure of walking energy expenditure (eg, walking efficiency) during a low-demand task. To calculate the average volume of oxygen consumption per kilogram of body weight during the task, energy expenditure readings from the first 2 minutes of testing were discarded. The final 3 minutes were averaged to derive a single measure of the average VO2 (mL/kg/min) consumed, or the average energetic demand of a slow standardized walking task (24,35).

The cost-to-capacity ratio was quantified by the ratio of the energetic demand, or cost, of slow walking to peak walking energy expenditure, and represented the percentage of peak walking capacity utilized for mobility (22):

Energy expenditure during slow walking was used in the calculation of cost-to-capacity ratio to allow calculation of a unitless ratio.

Covariates

Fat mass and lean mass were obtained from dual energy x-ray absorptiometry (DEXA—GE). Age (in years), sex, race, and the history of cardiovascular disease (including myocardial infarction, congestive heart failure, angina pectoris, bypass surgery or angioplasty, and peripheral arterial disease), hypertension (diagnosis of hypertension and taking antihypertensive medications), high cholesterol, stroke or transient ischemic attack, pulmonary disease (chronic bronchitis, emphysema, chronic obstructive pulmonary disease, or asthma), diabetes (diagnosis of diabetes and current medication for diabetes), cancer (non-skin [squamous or basal cell] cancer), and osteoarthritis were self-reported by participants in a medical history interview.

Statistical Analysis

ASTP, energetic measures and participant characteristics were summarized by median (interquartile range [IQR]) and frequency (%) for the overall sample. ASTP, energetic measures, and continuous participant characteristics, including age, fat mass, lean mass, and total daily physical activity, were compared between 2 levels of each energetic measure using the Wilcoxon rank-sum test, because their distributions were right skewed. Categorical characteristics such as sex, race, and each comorbidity were compared using Fisher’s exact test. Energetic cost of customary walking, peak walking energy expenditure, and cost-ratio were dichotomized into 2 categories at 0.17 mL/kg/m, 18.3 mL/kg/min, and 0.5, respectively, based on previous literature (22,24,36), and the energetic demand during slow walking was categorized at the median.

Linear regression models were used to model the associations between the continuous energetic measures and ASTP. As unadjusted scatterplots did not suggest considerable deviations from linear relationships between energetics and ASTP, no nonlinear terms were included in the models. Four sets of models were fitted, each of which has one energetic measure as the main independent variable and ASTP as the dependent variable. Each set included an unadjusted model, an adjusted model accounting for age, sex, race (White vs non-White), body composition (DEXA-measured fat mass and lean mass), and history of cardiovascular disease, hypertension, high cholesterol, stroke, pulmonary disease, diabetes, cancer, and osteoarthritis, and a final model where total daily physical activity was included in addition to all the above-mentioned covariates. To allow comparison of the strength of association across energetic measures, standardized β coefficients were also calculated. A sensitivity analysis was performed on final model using ASTP calculated from minute-level data with activity during typically sleep period (11:00 pm to 4:59 am) removed.

Effect modification by total physical activity was tested using interactions between energetics measures and quartiles of total daily physical activity. The energetics–ASTP associations and their significance were estimated from these models at each quartile, and were visualized using margins plots. Interactions with age groups (50–59 years, 60–69 years, 70–79 years, and 80 years and above) and with sex were explored in separate models.

The energetic cost of customary walking and cost-to-capacity ratio were scaled by factors of 100 and 10, respectively, in all models to improve the interpretability of the regression coefficients. Statistical significance was determined by an alpha level of .05. Analyses were performed using Stata IC 15.1 (StataCorp, College Station, TX).

Results

Participant characteristics are summarized in Table 1. The overall median age of the participants was 70 years (IQR 63–77 years), and 52% were men. Participants who were more energetically efficient, with lower energetic costs associated with slow and customary walking, higher peak walking energy expenditure, or a lower cost-to-capacity ratio, tended to be younger. Participants with higher peak waking energy expenditure also had lower fat mass and higher lean mass. Participants with low peak walking energy expenditure or a high cost-to-capacity ratio had more comorbidities (p < .001 for both). These participants also tended to be less active (p < .001 for both).

Table 1.
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Participant Characteristics

Energetic Cost of Customary WalkingdEnergetic Demand During Slow Walkinge
Characteristics Overall≤0.17 mL/kg/m>0.17 mL/kg/m≤8.7 ml/kg/min>8.7 ml/kg/min
Median (IQR)/N (%)n = 493n = 308n = 185pn = 247n = 246p
Age (y)a70 (63, 77)69 (63, 75)73 (67, 82)<.00168 (62, 75)73 (65, 80)<.001
Sex, male258 (52.3%)157 (51.0%)101 (54.6%).46117 (47.4%)141 (57.3%).031
Race, White355 (72.0%)212 (68.8%)143 (77.3%).049164 (66.4%)191 (77.6%).007
Fat mass (kg)a25 (20, 32)26 (21, 33)24 (18, 31).00127 (21, 35)24 (18, 30)<.001
Lean mass (kg)a48 (39, 56)48 (40, 56)48 (38, 56).4745 (39, 56)49 (40, 56).33
Chronic conditions 2 (1, 3)2 (2, 3)2 (1, 3).593 (2, 3)2 (1, 3).012
 CVDb63 (12.8%)37 (12.0%)26 (14.1%).5840 (16.2%)23 (9.3%).030
 Hypertension236 (47.9%)149 (48.4%)87 (47.0%).78123 (49.8%)113 (45.9%).42
 High cholesterol309 (62.7%)204 (66.2%)105 (56.8%).043165 (66.8%)144 (58.5%).063
 Stroke or TIA30 (6.1%)16 (5.2%)14 (7.6%).3310 (4.0%)20 (8.1%).062
 Pulmonary diseasec70 (14.2%)40 (13.0%)30 (16.2%).3539 (15.8%)31 (12.6%).37
 Diabetes92 (18.7%)61 (19.8%)31 (16.8%).4757 (23.1%)35 (14.2%).015
 Cancer157 (31.8%)93 (30.2%)64 (34.6%).3280 (32.4%)77 (31.3%).85
 Osteoarthritis 269 (54.6%)168 (54.5%)101 (54.6%)1.00135 (54.7%)134 (54.5%)1.00
Total daily physical activity1 822 (1 537, 2 133)1 812 (1 565, 2 070)1 826 (1 519, 2 206).961 830 (1 558, 2 154)1 778 (1 524, 2 072).31
ASTP0.26 (0.22, 0.30)0.26 (0.22, 0.30)0.26 (0.22, 0.31).470.25 (0.22, 0.27)0.27 (0.23, 0.31).096
Energetic cost of customary walking (mL/kg/m)0.17 (0.15, 0.18)0.15 (0.14, 0.16)0.19 (0.18, 0.21)<.0010.16 (0.14, 0.17)0.17 (0.16, 0.19)<.001
Energetic demand during slow walking (mL/kg/min)8.68 (7.84, 9.66)8.49 (7.68, 9.43)9.09 (8.19, 10.05)<.0017.84 (7.00, 8.34)9.66 (9.11, 10.42)<.001
Peak walking energy expenditure (mL/kg/min)17.26 (14.61, 20.41)16.16 (13.94, 19.07)18.84 (16.42, 21.91)<.00116.45 (13.89, 19.95)17.98 (15.14, 20.69).003
Cost-to-capacity ratio (%)50.05 (41.67, 60.28)51.15 (43.72, 62.16)48.65 (39.45, 58.42).01546.07 (36.49, 54.32)54.65 (46.30, 67.64)<.001
Peak Walking Energy ExpenditurefCost-to-Capacity Ratiog
Characteristics ≥18.3 mL/kg/min<18.3 mL/kg/min≤50%>50%
Median (IQR)/N (%)n = 200n = 293pn = 246n = 247p
Age (y)a67 (61, 75)72 (65, 80)<.00167 (61, 74)73 (67, 81)<.001
Sex, male117 (58.5%)141 (48.1%).027131 (53.3%)127 (51.4%).72
Race, White158 (79.0%)197 (67.2%).004185 (75.2%)170 (68.8%).13
Fat mass (kg)a23 (18, 29)28 (21, 35)<.00125 (20, 31)27 (20, 34).095
Lean mass (kg)a49 (41, 58)46 (38, 55).00848 (40, 57)48 (39, 55).27
Chronic conditions 2 (1, 3)3 (2, 4)<.0012 (1, 3)3 (2, 4)<.001
 CVDb15 (7.5%)48 (16.4%).00424 (9.8%)39 (15.8%).058
 Hypertension85 (42.5%)151 (51.5%).054106 (43.1%)130 (52.6%).038
 High cholesterol122 (61.0%)187 (63.8%).57155 (63.0%)154 (62.3%).93
 Stroke or TIA8 (4.0%)22 (7.5%).138 (3.3%)22 (8.9%).013
 Pulmonary diseasec24 (12.0%)46 (15.7%).2930 (12.2%)40 (16.2%).25
 Diabetes24 (12.0%)68 (23.2%).00238 (15.4%)54 (21.9%).083
 Cancer62 (31.0%)95 (32.4%).7776 (30.9%)81 (32.8%).70
 Osteoarthritis 99 (49.5%)170 (58.0%).066119 (48.4%)150 (60.7%).007
Total daily physical activity1 956 (1 675, 2 283)1 711 (1 467, 1 978)<.0011 889 (1 628, 2 259)1 707 (1 467, 2 005)<.001
ASTP0.24 (0.20, 0.28)0.27 (0.24, 0.32)<.0010.24 (0.21, 0.28)0.27 (0.24, 0.33)<.001
Energetic cost of customary walking (mL/kg/m)0.17 (0.16, 0.19)0.16 (0.14, 0.17)<.0010.16 (0.15, 0.18)0.16 (0.14, 0.18).006
Energetic demand during slow walking (mL/kg/min)8.93 (8.13, 9.67)8.56 (7.68, 9.61).0078.34 (7.28, 9.06)9.12 (8.33, 10.32)<.001
Peak walking energy expenditure (mL/kg/min)21.33 (19.55, 23.58)14.99 (13.41, 16.65)<.00120.21 (17.84, 22.90)14.92 (13.16, 16.74)<.001
Cost-to-capacity ratio (%)41.42 (35.41, 47.10)56.99 (49.52, 69.32)<.00141.63 (35.41, 46.24)60.29 (54.51, 71.76)<.001
Energetic Cost of Customary WalkingdEnergetic Demand During Slow Walkinge
Characteristics Overall≤0.17 mL/kg/m>0.17 mL/kg/m≤8.7 ml/kg/min>8.7 ml/kg/min
Median (IQR)/N (%)n = 493n = 308n = 185pn = 247n = 246p
Age (y)a70 (63, 77)69 (63, 75)73 (67, 82)<.00168 (62, 75)73 (65, 80)<.001
Sex, male258 (52.3%)157 (51.0%)101 (54.6%).46117 (47.4%)141 (57.3%).031
Race, White355 (72.0%)212 (68.8%)143 (77.3%).049164 (66.4%)191 (77.6%).007
Fat mass (kg)a25 (20, 32)26 (21, 33)24 (18, 31).00127 (21, 35)24 (18, 30)<.001
Lean mass (kg)a48 (39, 56)48 (40, 56)48 (38, 56).4745 (39, 56)49 (40, 56).33
Chronic conditions 2 (1, 3)2 (2, 3)2 (1, 3).593 (2, 3)2 (1, 3).012
 CVDb63 (12.8%)37 (12.0%)26 (14.1%).5840 (16.2%)23 (9.3%).030
 Hypertension236 (47.9%)149 (48.4%)87 (47.0%).78123 (49.8%)113 (45.9%).42
 High cholesterol309 (62.7%)204 (66.2%)105 (56.8%).043165 (66.8%)144 (58.5%).063
 Stroke or TIA30 (6.1%)16 (5.2%)14 (7.6%).3310 (4.0%)20 (8.1%).062
 Pulmonary diseasec70 (14.2%)40 (13.0%)30 (16.2%).3539 (15.8%)31 (12.6%).37
 Diabetes92 (18.7%)61 (19.8%)31 (16.8%).4757 (23.1%)35 (14.2%).015
 Cancer157 (31.8%)93 (30.2%)64 (34.6%).3280 (32.4%)77 (31.3%).85
 Osteoarthritis 269 (54.6%)168 (54.5%)101 (54.6%)1.00135 (54.7%)134 (54.5%)1.00
Total daily physical activity1 822 (1 537, 2 133)1 812 (1 565, 2 070)1 826 (1 519, 2 206).961 830 (1 558, 2 154)1 778 (1 524, 2 072).31
ASTP0.26 (0.22, 0.30)0.26 (0.22, 0.30)0.26 (0.22, 0.31).470.25 (0.22, 0.27)0.27 (0.23, 0.31).096
Energetic cost of customary walking (mL/kg/m)0.17 (0.15, 0.18)0.15 (0.14, 0.16)0.19 (0.18, 0.21)<.0010.16 (0.14, 0.17)0.17 (0.16, 0.19)<.001
Energetic demand during slow walking (mL/kg/min)8.68 (7.84, 9.66)8.49 (7.68, 9.43)9.09 (8.19, 10.05)<.0017.84 (7.00, 8.34)9.66 (9.11, 10.42)<.001
Peak walking energy expenditure (mL/kg/min)17.26 (14.61, 20.41)16.16 (13.94, 19.07)18.84 (16.42, 21.91)<.00116.45 (13.89, 19.95)17.98 (15.14, 20.69).003
Cost-to-capacity ratio (%)50.05 (41.67, 60.28)51.15 (43.72, 62.16)48.65 (39.45, 58.42).01546.07 (36.49, 54.32)54.65 (46.30, 67.64)<.001
Peak Walking Energy ExpenditurefCost-to-Capacity Ratiog
Characteristics ≥18.3 mL/kg/min<18.3 mL/kg/min≤50%>50%
Median (IQR)/N (%)n = 200n = 293pn = 246n = 247p
Age (y)a67 (61, 75)72 (65, 80)<.00167 (61, 74)73 (67, 81)<.001
Sex, male117 (58.5%)141 (48.1%).027131 (53.3%)127 (51.4%).72
Race, White158 (79.0%)197 (67.2%).004185 (75.2%)170 (68.8%).13
Fat mass (kg)a23 (18, 29)28 (21, 35)<.00125 (20, 31)27 (20, 34).095
Lean mass (kg)a49 (41, 58)46 (38, 55).00848 (40, 57)48 (39, 55).27
Chronic conditions 2 (1, 3)3 (2, 4)<.0012 (1, 3)3 (2, 4)<.001
 CVDb15 (7.5%)48 (16.4%).00424 (9.8%)39 (15.8%).058
 Hypertension85 (42.5%)151 (51.5%).054106 (43.1%)130 (52.6%).038
 High cholesterol122 (61.0%)187 (63.8%).57155 (63.0%)154 (62.3%).93
 Stroke or TIA8 (4.0%)22 (7.5%).138 (3.3%)22 (8.9%).013
 Pulmonary diseasec24 (12.0%)46 (15.7%).2930 (12.2%)40 (16.2%).25
 Diabetes24 (12.0%)68 (23.2%).00238 (15.4%)54 (21.9%).083
 Cancer62 (31.0%)95 (32.4%).7776 (30.9%)81 (32.8%).70
 Osteoarthritis 99 (49.5%)170 (58.0%).066119 (48.4%)150 (60.7%).007
Total daily physical activity1 956 (1 675, 2 283)1 711 (1 467, 1 978)<.0011 889 (1 628, 2 259)1 707 (1 467, 2 005)<.001
ASTP0.24 (0.20, 0.28)0.27 (0.24, 0.32)<.0010.24 (0.21, 0.28)0.27 (0.24, 0.33)<.001
Energetic cost of customary walking (mL/kg/m)0.17 (0.16, 0.19)0.16 (0.14, 0.17)<.0010.16 (0.15, 0.18)0.16 (0.14, 0.18).006
Energetic demand during slow walking (mL/kg/min)8.93 (8.13, 9.67)8.56 (7.68, 9.61).0078.34 (7.28, 9.06)9.12 (8.33, 10.32)<.001
Peak walking energy expenditure (mL/kg/min)21.33 (19.55, 23.58)14.99 (13.41, 16.65)<.00120.21 (17.84, 22.90)14.92 (13.16, 16.74)<.001
Cost-to-capacity ratio (%)41.42 (35.41, 47.10)56.99 (49.52, 69.32)<.00141.63 (35.41, 46.24)60.29 (54.51, 71.76)<.001

Notes: ASTP = active-to-sedentary transition probability; CVD = cardiovascular disease; IQR = interquartile range; TIA = transient ischemic attack.

aMean (IQR) was reported due to nonnormal distributions of the covariates. bCVD includes myocardial infarction, congestive heart failure, angina pectoris, bypass surgery or (balloon) angioplasty, and peripheral arterial disease. cPulmonary disease includes chronic obstructive pulmonary disease and asthma. dOxygen consumption during a 2.5-min usual-paced walk standardized to distance covered (mL/kg/m). eOxygen consumption during a 5-min walk on treadmill at 0.67 m/s, 0% grade (mL/kg/min). fOxygen consumption during a 400-m walk (mL/kg/min). gThe ratio between oxygen consumption during 5-min treadmill walk at 0.67 m/s and 0% grade (mL/kg/min) and oxygen consumption during 400-m rapid-paced walk (mL/kg/min).

Table 1.
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Participant Characteristics

Energetic Cost of Customary WalkingdEnergetic Demand During Slow Walkinge
Characteristics Overall≤0.17 mL/kg/m>0.17 mL/kg/m≤8.7 ml/kg/min>8.7 ml/kg/min
Median (IQR)/N (%)n = 493n = 308n = 185pn = 247n = 246p
Age (y)a70 (63, 77)69 (63, 75)73 (67, 82)<.00168 (62, 75)73 (65, 80)<.001
Sex, male258 (52.3%)157 (51.0%)101 (54.6%).46117 (47.4%)141 (57.3%).031
Race, White355 (72.0%)212 (68.8%)143 (77.3%).049164 (66.4%)191 (77.6%).007
Fat mass (kg)a25 (20, 32)26 (21, 33)24 (18, 31).00127 (21, 35)24 (18, 30)<.001
Lean mass (kg)a48 (39, 56)48 (40, 56)48 (38, 56).4745 (39, 56)49 (40, 56).33
Chronic conditions 2 (1, 3)2 (2, 3)2 (1, 3).593 (2, 3)2 (1, 3).012
 CVDb63 (12.8%)37 (12.0%)26 (14.1%).5840 (16.2%)23 (9.3%).030
 Hypertension236 (47.9%)149 (48.4%)87 (47.0%).78123 (49.8%)113 (45.9%).42
 High cholesterol309 (62.7%)204 (66.2%)105 (56.8%).043165 (66.8%)144 (58.5%).063
 Stroke or TIA30 (6.1%)16 (5.2%)14 (7.6%).3310 (4.0%)20 (8.1%).062
 Pulmonary diseasec70 (14.2%)40 (13.0%)30 (16.2%).3539 (15.8%)31 (12.6%).37
 Diabetes92 (18.7%)61 (19.8%)31 (16.8%).4757 (23.1%)35 (14.2%).015
 Cancer157 (31.8%)93 (30.2%)64 (34.6%).3280 (32.4%)77 (31.3%).85
 Osteoarthritis 269 (54.6%)168 (54.5%)101 (54.6%)1.00135 (54.7%)134 (54.5%)1.00
Total daily physical activity1 822 (1 537, 2 133)1 812 (1 565, 2 070)1 826 (1 519, 2 206).961 830 (1 558, 2 154)1 778 (1 524, 2 072).31
ASTP0.26 (0.22, 0.30)0.26 (0.22, 0.30)0.26 (0.22, 0.31).470.25 (0.22, 0.27)0.27 (0.23, 0.31).096
Energetic cost of customary walking (mL/kg/m)0.17 (0.15, 0.18)0.15 (0.14, 0.16)0.19 (0.18, 0.21)<.0010.16 (0.14, 0.17)0.17 (0.16, 0.19)<.001
Energetic demand during slow walking (mL/kg/min)8.68 (7.84, 9.66)8.49 (7.68, 9.43)9.09 (8.19, 10.05)<.0017.84 (7.00, 8.34)9.66 (9.11, 10.42)<.001
Peak walking energy expenditure (mL/kg/min)17.26 (14.61, 20.41)16.16 (13.94, 19.07)18.84 (16.42, 21.91)<.00116.45 (13.89, 19.95)17.98 (15.14, 20.69).003
Cost-to-capacity ratio (%)50.05 (41.67, 60.28)51.15 (43.72, 62.16)48.65 (39.45, 58.42).01546.07 (36.49, 54.32)54.65 (46.30, 67.64)<.001
Peak Walking Energy ExpenditurefCost-to-Capacity Ratiog
Characteristics ≥18.3 mL/kg/min<18.3 mL/kg/min≤50%>50%
Median (IQR)/N (%)n = 200n = 293pn = 246n = 247p
Age (y)a67 (61, 75)72 (65, 80)<.00167 (61, 74)73 (67, 81)<.001
Sex, male117 (58.5%)141 (48.1%).027131 (53.3%)127 (51.4%).72
Race, White158 (79.0%)197 (67.2%).004185 (75.2%)170 (68.8%).13
Fat mass (kg)a23 (18, 29)28 (21, 35)<.00125 (20, 31)27 (20, 34).095
Lean mass (kg)a49 (41, 58)46 (38, 55).00848 (40, 57)48 (39, 55).27
Chronic conditions 2 (1, 3)3 (2, 4)<.0012 (1, 3)3 (2, 4)<.001
 CVDb15 (7.5%)48 (16.4%).00424 (9.8%)39 (15.8%).058
 Hypertension85 (42.5%)151 (51.5%).054106 (43.1%)130 (52.6%).038
 High cholesterol122 (61.0%)187 (63.8%).57155 (63.0%)154 (62.3%).93
 Stroke or TIA8 (4.0%)22 (7.5%).138 (3.3%)22 (8.9%).013
 Pulmonary diseasec24 (12.0%)46 (15.7%).2930 (12.2%)40 (16.2%).25
 Diabetes24 (12.0%)68 (23.2%).00238 (15.4%)54 (21.9%).083
 Cancer62 (31.0%)95 (32.4%).7776 (30.9%)81 (32.8%).70
 Osteoarthritis 99 (49.5%)170 (58.0%).066119 (48.4%)150 (60.7%).007
Total daily physical activity1 956 (1 675, 2 283)1 711 (1 467, 1 978)<.0011 889 (1 628, 2 259)1 707 (1 467, 2 005)<.001
ASTP0.24 (0.20, 0.28)0.27 (0.24, 0.32)<.0010.24 (0.21, 0.28)0.27 (0.24, 0.33)<.001
Energetic cost of customary walking (mL/kg/m)0.17 (0.16, 0.19)0.16 (0.14, 0.17)<.0010.16 (0.15, 0.18)0.16 (0.14, 0.18).006
Energetic demand during slow walking (mL/kg/min)8.93 (8.13, 9.67)8.56 (7.68, 9.61).0078.34 (7.28, 9.06)9.12 (8.33, 10.32)<.001
Peak walking energy expenditure (mL/kg/min)21.33 (19.55, 23.58)14.99 (13.41, 16.65)<.00120.21 (17.84, 22.90)14.92 (13.16, 16.74)<.001
Cost-to-capacity ratio (%)41.42 (35.41, 47.10)56.99 (49.52, 69.32)<.00141.63 (35.41, 46.24)60.29 (54.51, 71.76)<.001
Energetic Cost of Customary WalkingdEnergetic Demand During Slow Walkinge
Characteristics Overall≤0.17 mL/kg/m>0.17 mL/kg/m≤8.7 ml/kg/min>8.7 ml/kg/min
Median (IQR)/N (%)n = 493n = 308n = 185pn = 247n = 246p
Age (y)a70 (63, 77)69 (63, 75)73 (67, 82)<.00168 (62, 75)73 (65, 80)<.001
Sex, male258 (52.3%)157 (51.0%)101 (54.6%).46117 (47.4%)141 (57.3%).031
Race, White355 (72.0%)212 (68.8%)143 (77.3%).049164 (66.4%)191 (77.6%).007
Fat mass (kg)a25 (20, 32)26 (21, 33)24 (18, 31).00127 (21, 35)24 (18, 30)<.001
Lean mass (kg)a48 (39, 56)48 (40, 56)48 (38, 56).4745 (39, 56)49 (40, 56).33
Chronic conditions 2 (1, 3)2 (2, 3)2 (1, 3).593 (2, 3)2 (1, 3).012
 CVDb63 (12.8%)37 (12.0%)26 (14.1%).5840 (16.2%)23 (9.3%).030
 Hypertension236 (47.9%)149 (48.4%)87 (47.0%).78123 (49.8%)113 (45.9%).42
 High cholesterol309 (62.7%)204 (66.2%)105 (56.8%).043165 (66.8%)144 (58.5%).063
 Stroke or TIA30 (6.1%)16 (5.2%)14 (7.6%).3310 (4.0%)20 (8.1%).062
 Pulmonary diseasec70 (14.2%)40 (13.0%)30 (16.2%).3539 (15.8%)31 (12.6%).37
 Diabetes92 (18.7%)61 (19.8%)31 (16.8%).4757 (23.1%)35 (14.2%).015
 Cancer157 (31.8%)93 (30.2%)64 (34.6%).3280 (32.4%)77 (31.3%).85
 Osteoarthritis 269 (54.6%)168 (54.5%)101 (54.6%)1.00135 (54.7%)134 (54.5%)1.00
Total daily physical activity1 822 (1 537, 2 133)1 812 (1 565, 2 070)1 826 (1 519, 2 206).961 830 (1 558, 2 154)1 778 (1 524, 2 072).31
ASTP0.26 (0.22, 0.30)0.26 (0.22, 0.30)0.26 (0.22, 0.31).470.25 (0.22, 0.27)0.27 (0.23, 0.31).096
Energetic cost of customary walking (mL/kg/m)0.17 (0.15, 0.18)0.15 (0.14, 0.16)0.19 (0.18, 0.21)<.0010.16 (0.14, 0.17)0.17 (0.16, 0.19)<.001
Energetic demand during slow walking (mL/kg/min)8.68 (7.84, 9.66)8.49 (7.68, 9.43)9.09 (8.19, 10.05)<.0017.84 (7.00, 8.34)9.66 (9.11, 10.42)<.001
Peak walking energy expenditure (mL/kg/min)17.26 (14.61, 20.41)16.16 (13.94, 19.07)18.84 (16.42, 21.91)<.00116.45 (13.89, 19.95)17.98 (15.14, 20.69).003
Cost-to-capacity ratio (%)50.05 (41.67, 60.28)51.15 (43.72, 62.16)48.65 (39.45, 58.42).01546.07 (36.49, 54.32)54.65 (46.30, 67.64)<.001
Peak Walking Energy ExpenditurefCost-to-Capacity Ratiog
Characteristics ≥18.3 mL/kg/min<18.3 mL/kg/min≤50%>50%
Median (IQR)/N (%)n = 200n = 293pn = 246n = 247p
Age (y)a67 (61, 75)72 (65, 80)<.00167 (61, 74)73 (67, 81)<.001
Sex, male117 (58.5%)141 (48.1%).027131 (53.3%)127 (51.4%).72
Race, White158 (79.0%)197 (67.2%).004185 (75.2%)170 (68.8%).13
Fat mass (kg)a23 (18, 29)28 (21, 35)<.00125 (20, 31)27 (20, 34).095
Lean mass (kg)a49 (41, 58)46 (38, 55).00848 (40, 57)48 (39, 55).27
Chronic conditions 2 (1, 3)3 (2, 4)<.0012 (1, 3)3 (2, 4)<.001
 CVDb15 (7.5%)48 (16.4%).00424 (9.8%)39 (15.8%).058
 Hypertension85 (42.5%)151 (51.5%).054106 (43.1%)130 (52.6%).038
 High cholesterol122 (61.0%)187 (63.8%).57155 (63.0%)154 (62.3%).93
 Stroke or TIA8 (4.0%)22 (7.5%).138 (3.3%)22 (8.9%).013
 Pulmonary diseasec24 (12.0%)46 (15.7%).2930 (12.2%)40 (16.2%).25
 Diabetes24 (12.0%)68 (23.2%).00238 (15.4%)54 (21.9%).083
 Cancer62 (31.0%)95 (32.4%).7776 (30.9%)81 (32.8%).70
 Osteoarthritis 99 (49.5%)170 (58.0%).066119 (48.4%)150 (60.7%).007
Total daily physical activity1 956 (1 675, 2 283)1 711 (1 467, 1 978)<.0011 889 (1 628, 2 259)1 707 (1 467, 2 005)<.001
ASTP0.24 (0.20, 0.28)0.27 (0.24, 0.32)<.0010.24 (0.21, 0.28)0.27 (0.24, 0.33)<.001
Energetic cost of customary walking (mL/kg/m)0.17 (0.16, 0.19)0.16 (0.14, 0.17)<.0010.16 (0.15, 0.18)0.16 (0.14, 0.18).006
Energetic demand during slow walking (mL/kg/min)8.93 (8.13, 9.67)8.56 (7.68, 9.61).0078.34 (7.28, 9.06)9.12 (8.33, 10.32)<.001
Peak walking energy expenditure (mL/kg/min)21.33 (19.55, 23.58)14.99 (13.41, 16.65)<.00120.21 (17.84, 22.90)14.92 (13.16, 16.74)<.001
Cost-to-capacity ratio (%)41.42 (35.41, 47.10)56.99 (49.52, 69.32)<.00141.63 (35.41, 46.24)60.29 (54.51, 71.76)<.001

Notes: ASTP = active-to-sedentary transition probability; CVD = cardiovascular disease; IQR = interquartile range; TIA = transient ischemic attack.

aMean (IQR) was reported due to nonnormal distributions of the covariates. bCVD includes myocardial infarction, congestive heart failure, angina pectoris, bypass surgery or (balloon) angioplasty, and peripheral arterial disease. cPulmonary disease includes chronic obstructive pulmonary disease and asthma. dOxygen consumption during a 2.5-min usual-paced walk standardized to distance covered (mL/kg/m). eOxygen consumption during a 5-min walk on treadmill at 0.67 m/s, 0% grade (mL/kg/min). fOxygen consumption during a 400-m walk (mL/kg/min). gThe ratio between oxygen consumption during 5-min treadmill walk at 0.67 m/s and 0% grade (mL/kg/min) and oxygen consumption during 400-m rapid-paced walk (mL/kg/min).

Higher energetic cost of customary walking, lower peak walking energy expenditure, and higher cost-to-capacity ratio were associated with higher ASTP in the unadjusted models (Table 2). For each 0.01 mL/kg/m higher cost of customary walking, there was an associated 0.2% higher ASTP (p = .009). Every 1 mL/kg/min lower peak walking energy expenditure was associated with a 0.5% higher ASTP (p < .001). Every 10% higher cost-to-capacity ratio was associated with 1.3% higher ASTP (p < .001). ASTP did not differ by energetic demand during slow walking in the unadjusted model. After adjustment for covariates, energetic cost of customary walking was no longer associated with ASTP (Table 2, adjusted models). Further adjustment for total daily physical activity attenuated the association for peak walking energy expenditure, but a 10% higher cost-to-capacity ratio remained significantly associated with 0.4% higher ASTP (p = .005) (Table 2, final models). The magnitudes of the standardized β coefficients were the strongest for cost-to-capacity ratio, followed by peak walking energy expenditure, in all models. Removing sleep periods from ASTP yielded similar results in the final models (Supplementary Table 1).

Table 2.
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Association Between Energetic Measures and Physical Activity Fragmentation in Linear Regression Models (N = 493)

Dependent Variable: ASTPaβ95% CIpStandardized β
(A) Unadjusted models
 Energetic cost of customary walkingb0.0020.0006, 0.004.0090.117
 Energetic demand during slow walkingc0.003−0.0002, 0.006.0650.083
 Peak walking energy expenditured−0.005−0.006, −0.003<.001−0.310
 Cost-to-capacity ratioe0.0130.009, 0.016<.0010.312
(B) Adjusted modelsf
 Energetic cost of customary walkingb0.001−0.001, 0.003.3770.039
 Energetic demand during slow walkingc0.002−0.001, 0.005.2240.053
 Peak walking energy expenditured−0.002−0.004, −0.001.001−0.160
 Cost-to-capacity ratioe0.0070.003, 0.010<.0010.172
(C) Final modelsg
 Energetic cost of customary walkingb0.001−0.001, 0.002.3420.029
 Energetic demand during slow walkingc0.002−0.001, 0.004.1460.043
 Peak walking energy expenditured−0.001−0.002, 0.0001.067−0.062
 Cost-to-capacity ratioe0.0040.001, 0.006.0050.088
Dependent Variable: ASTPaβ95% CIpStandardized β
(A) Unadjusted models
 Energetic cost of customary walkingb0.0020.0006, 0.004.0090.117
 Energetic demand during slow walkingc0.003−0.0002, 0.006.0650.083
 Peak walking energy expenditured−0.005−0.006, −0.003<.001−0.310
 Cost-to-capacity ratioe0.0130.009, 0.016<.0010.312
(B) Adjusted modelsf
 Energetic cost of customary walkingb0.001−0.001, 0.003.3770.039
 Energetic demand during slow walkingc0.002−0.001, 0.005.2240.053
 Peak walking energy expenditured−0.002−0.004, −0.001.001−0.160
 Cost-to-capacity ratioe0.0070.003, 0.010<.0010.172
(C) Final modelsg
 Energetic cost of customary walkingb0.001−0.001, 0.002.3420.029
 Energetic demand during slow walkingc0.002−0.001, 0.004.1460.043
 Peak walking energy expenditured−0.001−0.002, 0.0001.067−0.062
 Cost-to-capacity ratioe0.0040.001, 0.006.0050.088

Notes: ASTP = active-to-sedentary transition probability.

aASTP is a measure of activity fragmentation. bOxygen consumption during a 2.5-min usual-paced walk standardized to distance covered (mL/kg/m). cOxygen consumption during a 5-min walk on treadmill at 0.67 m/s, 0% grade (mL/kg/min). dOxygen consumption during a 400-m walk (mL/kg/min). eThe ratio between oxygen consumption during the 5-min treadmill walk at 0.67 m/s, 0% grade (mL/kg/min) and oxygen consumption during the 400-m walk (mL/kg/min). fAdjusted models include age, sex, race, fat mass, lean mass, and history of cardiovascular disease, hypertension, high cholesterol, stroke, pulmonary disease, diabetes, cancer, and osteoarthritis as covariates. gFinal models include all covariates in adjusted model and total daily physical activity.

Table 2.
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Association Between Energetic Measures and Physical Activity Fragmentation in Linear Regression Models (N = 493)

Dependent Variable: ASTPaβ95% CIpStandardized β
(A) Unadjusted models
 Energetic cost of customary walkingb0.0020.0006, 0.004.0090.117
 Energetic demand during slow walkingc0.003−0.0002, 0.006.0650.083
 Peak walking energy expenditured−0.005−0.006, −0.003<.001−0.310
 Cost-to-capacity ratioe0.0130.009, 0.016<.0010.312
(B) Adjusted modelsf
 Energetic cost of customary walkingb0.001−0.001, 0.003.3770.039
 Energetic demand during slow walkingc0.002−0.001, 0.005.2240.053
 Peak walking energy expenditured−0.002−0.004, −0.001.001−0.160
 Cost-to-capacity ratioe0.0070.003, 0.010<.0010.172
(C) Final modelsg
 Energetic cost of customary walkingb0.001−0.001, 0.002.3420.029
 Energetic demand during slow walkingc0.002−0.001, 0.004.1460.043
 Peak walking energy expenditured−0.001−0.002, 0.0001.067−0.062
 Cost-to-capacity ratioe0.0040.001, 0.006.0050.088
Dependent Variable: ASTPaβ95% CIpStandardized β
(A) Unadjusted models
 Energetic cost of customary walkingb0.0020.0006, 0.004.0090.117
 Energetic demand during slow walkingc0.003−0.0002, 0.006.0650.083
 Peak walking energy expenditured−0.005−0.006, −0.003<.001−0.310
 Cost-to-capacity ratioe0.0130.009, 0.016<.0010.312
(B) Adjusted modelsf
 Energetic cost of customary walkingb0.001−0.001, 0.003.3770.039
 Energetic demand during slow walkingc0.002−0.001, 0.005.2240.053
 Peak walking energy expenditured−0.002−0.004, −0.001.001−0.160
 Cost-to-capacity ratioe0.0070.003, 0.010<.0010.172
(C) Final modelsg
 Energetic cost of customary walkingb0.001−0.001, 0.002.3420.029
 Energetic demand during slow walkingc0.002−0.001, 0.004.1460.043
 Peak walking energy expenditured−0.001−0.002, 0.0001.067−0.062
 Cost-to-capacity ratioe0.0040.001, 0.006.0050.088

Notes: ASTP = active-to-sedentary transition probability.

aASTP is a measure of activity fragmentation. bOxygen consumption during a 2.5-min usual-paced walk standardized to distance covered (mL/kg/m). cOxygen consumption during a 5-min walk on treadmill at 0.67 m/s, 0% grade (mL/kg/min). dOxygen consumption during a 400-m walk (mL/kg/min). eThe ratio between oxygen consumption during the 5-min treadmill walk at 0.67 m/s, 0% grade (mL/kg/min) and oxygen consumption during the 400-m walk (mL/kg/min). fAdjusted models include age, sex, race, fat mass, lean mass, and history of cardiovascular disease, hypertension, high cholesterol, stroke, pulmonary disease, diabetes, cancer, and osteoarthritis as covariates. gFinal models include all covariates in adjusted model and total daily physical activity.

The total daily physical activity quartiles used to test for interaction with energetic measures averaged (min–max) 2 455 (2 139–4 020), 1 945 (1 822–2 133), 1 677 (1 537–1 822), and 1 290 (360–1 537) activity counts per day, respectively, from the most active to the least active. The interactions showed that the associations between peak walking energy expenditure and ASTP, and between cost-to-capacity ratio and ASTP were modified by levels of total daily physical activity. Compared to the most active participants, the least active participants had 0.3% higher ASTP with every 1-mL/kg/min lower peak walking energy expenditure (pinteraction = .019), and 0.8% higher ASTP with every 10% higher cost-to-capacity ratio (pinteraction = .023) (Table 3). Among the least active participants, 1-mL/kg/min lower peak walking energy expenditure was associated with 0.3% higher ASTP (p = .004), and 10% higher cost-to-capacity ratio was associated with 1.0% higher ASTP (p < .001) (Figure 1). The associations were not significant in the other 3 groups.

Table 3.
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Interactions Between Energetic Measures and Total Volume of Physical Activity (activity counts per day)a

Dependent Variable: ASTPbEnergetic Cost of Customary WalkingdEnergetic Demand During Slow Walkinge
β95% CIpβ95% CIp
Energetics measure 0.002−0.0002, 0.005.0670.0003−0.004, 0.005.898
Total daily physical activityc
 First quartile (most active)Ref.Ref.Ref.Ref.Ref.Ref.
 Second quartile (more active)0.049−0.014, 0.112.1300.004−0.053, 0.061.890
 Third quartile (less active)0.1150.057, 0.173<.0010.037−0.018, 0.093.187
 Fourth quartile (least active)0.1320.071, 0.194<.0010.0900.032, 0.149.002
Interactions
  First quartile × Energetics Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile × Energetics0.0003−0.004, 0.003.8720.005−0.002, 0.011.162
  Third quartile × Energetics−0.003−0.006, 0.0005.0950.003−0.003, 0.009.306
  Fourth quartile × Energetics−0.001−0.004, 0.003.6620.003−0.003, 0.010.305
Dependent Variable: ASTPbPeak Walking Energy ExpenditurefCost-to-Capacity Ratiog
β95% CIpβ95% CIp
Energetics measure0.0001−0.002, 0.002.8890.001−0.004, 0.006.650
Total daily physical activityc
  First quartile (most active)Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile (more active)0.0600.011, 0.109.0160.031−0.005, 0.067.087
  Third quartile (less active)0.0680.021, 0.116.0050.0560.018, 0.095.004
  Fourth quartile (least active)0.1730.124, 0.221<.0010.0720.032, 0.112<.001
Interactions
  First quartile × Energetics Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile × Energetics−0.001−0.003, 0.002.4950.002−0.004, 0.009.492
  Third quartile × Energetics−0.0001−0.003, 0.002.9540.002−0.005, 0.010.621
  Fourth quartile × Energetics−0.003−0.006, −0.001.0190.0080.001, 0.015.023
Dependent Variable: ASTPbEnergetic Cost of Customary WalkingdEnergetic Demand During Slow Walkinge
β95% CIpβ95% CIp
Energetics measure 0.002−0.0002, 0.005.0670.0003−0.004, 0.005.898
Total daily physical activityc
 First quartile (most active)Ref.Ref.Ref.Ref.Ref.Ref.
 Second quartile (more active)0.049−0.014, 0.112.1300.004−0.053, 0.061.890
 Third quartile (less active)0.1150.057, 0.173<.0010.037−0.018, 0.093.187
 Fourth quartile (least active)0.1320.071, 0.194<.0010.0900.032, 0.149.002
Interactions
  First quartile × Energetics Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile × Energetics0.0003−0.004, 0.003.8720.005−0.002, 0.011.162
  Third quartile × Energetics−0.003−0.006, 0.0005.0950.003−0.003, 0.009.306
  Fourth quartile × Energetics−0.001−0.004, 0.003.6620.003−0.003, 0.010.305
Dependent Variable: ASTPbPeak Walking Energy ExpenditurefCost-to-Capacity Ratiog
β95% CIpβ95% CIp
Energetics measure0.0001−0.002, 0.002.8890.001−0.004, 0.006.650
Total daily physical activityc
  First quartile (most active)Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile (more active)0.0600.011, 0.109.0160.031−0.005, 0.067.087
  Third quartile (less active)0.0680.021, 0.116.0050.0560.018, 0.095.004
  Fourth quartile (least active)0.1730.124, 0.221<.0010.0720.032, 0.112<.001
Interactions
  First quartile × Energetics Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile × Energetics−0.001−0.003, 0.002.4950.002−0.004, 0.009.492
  Third quartile × Energetics−0.0001−0.003, 0.002.9540.002−0.005, 0.010.621
  Fourth quartile × Energetics−0.003−0.006, −0.001.0190.0080.001, 0.015.023

Notes: ASTP = active-to-sedentary transition probability.

aModel adjusted for age, sex, race, fat mass, lean mass, and history of cardiovascular disease, hypertension, high cholesterol, stroke, pulmonary disease, diabetes, cancer, and osteoarthritis. bASTP is a measure of physical activity fragmentation. cMeasured by mean total log activity count. dOxygen consumption during a 2.5-min usual-paced walk standardized to distance covered (mL/kg/m). eOxygen consumption during a 5-min walk on treadmill at 0.67 m/s, 0% grade (mL/kg/min). fOxygen consumption during a 400-m walk (mL/kg/min). gThe ratio between oxygen consumption during the 5-min treadmill walk at 0.67 m/s, 0% grade (mL/kg/min) and oxygen consumption during the 400-m walk (ml/kg/min).

Table 3.
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Interactions Between Energetic Measures and Total Volume of Physical Activity (activity counts per day)a

Dependent Variable: ASTPbEnergetic Cost of Customary WalkingdEnergetic Demand During Slow Walkinge
β95% CIpβ95% CIp
Energetics measure 0.002−0.0002, 0.005.0670.0003−0.004, 0.005.898
Total daily physical activityc
 First quartile (most active)Ref.Ref.Ref.Ref.Ref.Ref.
 Second quartile (more active)0.049−0.014, 0.112.1300.004−0.053, 0.061.890
 Third quartile (less active)0.1150.057, 0.173<.0010.037−0.018, 0.093.187
 Fourth quartile (least active)0.1320.071, 0.194<.0010.0900.032, 0.149.002
Interactions
  First quartile × Energetics Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile × Energetics0.0003−0.004, 0.003.8720.005−0.002, 0.011.162
  Third quartile × Energetics−0.003−0.006, 0.0005.0950.003−0.003, 0.009.306
  Fourth quartile × Energetics−0.001−0.004, 0.003.6620.003−0.003, 0.010.305
Dependent Variable: ASTPbPeak Walking Energy ExpenditurefCost-to-Capacity Ratiog
β95% CIpβ95% CIp
Energetics measure0.0001−0.002, 0.002.8890.001−0.004, 0.006.650
Total daily physical activityc
  First quartile (most active)Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile (more active)0.0600.011, 0.109.0160.031−0.005, 0.067.087
  Third quartile (less active)0.0680.021, 0.116.0050.0560.018, 0.095.004
  Fourth quartile (least active)0.1730.124, 0.221<.0010.0720.032, 0.112<.001
Interactions
  First quartile × Energetics Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile × Energetics−0.001−0.003, 0.002.4950.002−0.004, 0.009.492
  Third quartile × Energetics−0.0001−0.003, 0.002.9540.002−0.005, 0.010.621
  Fourth quartile × Energetics−0.003−0.006, −0.001.0190.0080.001, 0.015.023
Dependent Variable: ASTPbEnergetic Cost of Customary WalkingdEnergetic Demand During Slow Walkinge
β95% CIpβ95% CIp
Energetics measure 0.002−0.0002, 0.005.0670.0003−0.004, 0.005.898
Total daily physical activityc
 First quartile (most active)Ref.Ref.Ref.Ref.Ref.Ref.
 Second quartile (more active)0.049−0.014, 0.112.1300.004−0.053, 0.061.890
 Third quartile (less active)0.1150.057, 0.173<.0010.037−0.018, 0.093.187
 Fourth quartile (least active)0.1320.071, 0.194<.0010.0900.032, 0.149.002
Interactions
  First quartile × Energetics Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile × Energetics0.0003−0.004, 0.003.8720.005−0.002, 0.011.162
  Third quartile × Energetics−0.003−0.006, 0.0005.0950.003−0.003, 0.009.306
  Fourth quartile × Energetics−0.001−0.004, 0.003.6620.003−0.003, 0.010.305
Dependent Variable: ASTPbPeak Walking Energy ExpenditurefCost-to-Capacity Ratiog
β95% CIpβ95% CIp
Energetics measure0.0001−0.002, 0.002.8890.001−0.004, 0.006.650
Total daily physical activityc
  First quartile (most active)Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile (more active)0.0600.011, 0.109.0160.031−0.005, 0.067.087
  Third quartile (less active)0.0680.021, 0.116.0050.0560.018, 0.095.004
  Fourth quartile (least active)0.1730.124, 0.221<.0010.0720.032, 0.112<.001
Interactions
  First quartile × Energetics Ref.Ref.Ref.Ref.Ref.Ref.
  Second quartile × Energetics−0.001−0.003, 0.002.4950.002−0.004, 0.009.492
  Third quartile × Energetics−0.0001−0.003, 0.002.9540.002−0.005, 0.010.621
  Fourth quartile × Energetics−0.003−0.006, −0.001.0190.0080.001, 0.015.023

Notes: ASTP = active-to-sedentary transition probability.

aModel adjusted for age, sex, race, fat mass, lean mass, and history of cardiovascular disease, hypertension, high cholesterol, stroke, pulmonary disease, diabetes, cancer, and osteoarthritis. bASTP is a measure of physical activity fragmentation. cMeasured by mean total log activity count. dOxygen consumption during a 2.5-min usual-paced walk standardized to distance covered (mL/kg/m). eOxygen consumption during a 5-min walk on treadmill at 0.67 m/s, 0% grade (mL/kg/min). fOxygen consumption during a 400-m walk (mL/kg/min). gThe ratio between oxygen consumption during the 5-min treadmill walk at 0.67 m/s, 0% grade (mL/kg/min) and oxygen consumption during the 400-m walk (ml/kg/min).

Marginal plots of association between (A) peak walking energy expenditure/(B) cost-to-capacity ratio and ASTPa by quartiles of total daily physical activityb,c.aActive-to-sedentary transition probability (ASTP), a measure of physical activity fragmentation. bMeasured by mean total log activity count (TLAC). cAfter adjusting for total daily physical activity, age, sex, race, fat mass, lean mass, and history of cardiovascular disease, hypertension, high cholesterol, stroke, pulmonary disease, diabetes, cancer, and osteoarthritis.
Figure 1.

Marginal plots of association between (A) peak walking energy expenditure/(B) cost-to-capacity ratio and ASTPa by quartiles of total daily physical activityb,c.aActive-to-sedentary transition probability (ASTP), a measure of physical activity fragmentation. bMeasured by mean total log activity count (TLAC). cAfter adjusting for total daily physical activity, age, sex, race, fat mass, lean mass, and history of cardiovascular disease, hypertension, high cholesterol, stroke, pulmonary disease, diabetes, cancer, and osteoarthritis.

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Interactions with age were also examined. The associations between peak walking energy expenditure and ASTP were stronger with each decade of older age (β  interaction = −0.001, pinteraction = .038; Supplementary Table 2). Estimated associations between peak walking energy expenditure and ASTP were only significant for participants 70 years and older (p < .05; Supplementary Table 3). Sex did not modify the associations between energetic measures and ASTP (all pinteraction > .05).

Discussion

Our study demonstrated that older adults aged 50–93 years with combined lower energy capacity and higher energy required for walking are more likely to have fragmented daily activities patterns, especially among those who are least active, after adjusting for demographics, body composition, comorbidities, and total daily physical activity. These results add to the previous findings on the associations of energy cost and capacity with total physical activity and physical function (22–27,29), by showing a connection with physical activity patterns.

Previously, Schrager et al. suggested that self-reported lower daily physical activity may act as a compensatory strategy to conserve energy as energy capacity diminishes with age (29). Our findings support that the same adaptive mechanism may thus underlie the relationship between energy and objectively measured physical activity patterns. As energy needed for walking accounts for a higher proportion of energy capacity with age, activity is sustained for shorter durations, and more breaks between active states are needed for rest and recovery. The significant association between cost-to-capacity ratio and activity fragmentation that persisted after adjusting for total volume of daily physical activity further suggests that activity fragmentation may also be a strategy to maintain physical activity in the face of lower energy capacity and higher energy needs for mobility. In this sense, activity fragmentation may be an earlier indicator of underlying energetic changes than total amount of physical activity, creating a novel tool to identify individuals who might benefit from interventions to improve energy utilization and prevent further reduction of physical activity level and associated adverse outcomes. Our findings were also consistent with previous findings that patterns of activity are associated with various health and function outcomes, independent of physical activity volume (8,10–16). However, our cross-sectional study could not evaluate the temporal associations among changes in energy utilization, physical activity pattern, and total physical activity amount, warranting future longitudinal studies.

Our study found that the association between cost-to-capacity ratio and physical activity fragmentation was the strongest among the least active quartile of our study population. Moreover, peak walking energy expenditure was more strongly associated with physical activity fragmentation among less active participants or participants aged 70 years and older. People with lower amounts of daily physical activity or of older age may have existing physiological and functional impairments, and may thus be the most vulnerable to combined high energy costs and low energy capacity. To this end, even a small amount of change in energy utilization and capacity may elicit considerable activity fragmentation, while more active or younger people may be more able to compensate the deleterious effects of a high cost-to-capacity ratio or lower energy capacity through other venues such as walking at a slower speed (24). These results suggest that the cost-to-capacity ratio and peak walking energy expenditure may be the most useful for identifying energetic change among older adults who are less active.

The stronger associations of cost-to-capacity ratio with activity fragmentation than independent measures of energy cost and energy capacity suggest that the construct of energy utilization, a combination of energy cost and energy capacity, may be a more comprehensive and sensitive measure than either of its components. A person with elevated energetic costs may not exhibit deterioration in physical activity patterns, because their capacity is high enough to compensate. Similarly, a person with lower capacity may also have low energy costs, and hence sufficient energy for more robust physical activity patterns. In contrast, a person with low energy capacity and high energy costs may be less able to engage in daily physical activity. Collectively, this makes the cost-to-capacity ratio a more stringent criterion for energetic health, allowing it to capture finer differences in activity fragmentation. Recently, the same order of strength in associations among cost-to-capacity ratio, peak walking energy expenditure, and energetic demand during slow walking was demonstrated with perceived fatigability (27). These findings support the hypothesis that energy utilization is a phenotypic measure of aging, manifesting as reduced physical function, increased fatigability, and unfavorable patterns of physical activity (20).

We assumed that deterioration in energetics contributes to activity fragmentation and reduced total physical activity in our regression models and throughout this discussion, but the cross-sectional design of our study cannot confirm the direction of the association. As our study is the first to examine the association between energetics and activity fragmentation, no evidence exists to suggest otherwise. However, some studies have suggested that exercise and physical training improve movement energetics (37,38). One reconciliation between our hypothesis and these findings is that the relationship is bidirectional: diminished energy restricts activity, and inactivity accelerates the deterioration of energy capacity or energy required for walking—a vicious cycle. Moreover, most of daily physical activity is performed at lower intensities than exercise. While higher-intensity exercise could improve energy availability, daily, routine physical activity may be more influenced by it.

This study has several strengths. Physical activity fragmentation was measured objectively using accelerometers, offering insights into how older adults accumulate daily physical activity in their free-living environments. It also avoids recall bias or social desirability bias usually associated with self-report. Multiple energetic measures across various levels of exertion were examined, allowing assessment of the associations of different aspects of energetics with physical activity fragmentation. This study also has limitations. First, energy expenditure was measured in a controlled, laboratory setting, and thus may differ from energy expenditure in free-living settings. Second, BLSA participants are healthier than the general population and the magnitude of the association between energy utilization and activity fragmentation may be understated. Replication in more representative populations should be explored.

In conclusion, we found a higher ratio of energy cost-to-capacity and a lower energy capacity may contribute to more fragmented patterns of daily physical activity, and activity fragmentation may be a more sensitive marker that reflects underlying energetic deficits than total daily physical activity, especially among those less active or aged ≥70 years. This adds to the growing literature showing the adverse effects of deficits in energy production and consumption with aging. With the advancement of wearable devices, continuously measuring physical activity in free-living environment becomes increasingly feasible, presenting opportunities to monitor physical activity fragmentation and identify people who may best benefit from intervention efforts.

Funding

This work was supported by grants R21AG053198 and P30AG021334 from the National Institute on Aging. F.L. is supported by U01AG057545, R01AG061786, and U01HL096812. J.A.S. is supported by U01AG0057545 and R01AG061786. A.A.W. is supported by U01AG0057545, R01AG061786, P30AG021334, and P30AG059298.

Conflict of Interest

E.M.S., L.F., and J.A.S. currently serve on the editorial board for the Journal of Gerontology: Medical Sciences. All other authors have no financial conflicts to disclose.

Acknowledgment

Data used in the analyses were obtained from the Baltimore Longitudinal Study of Aging, an Intramural Research Program of the National Institute on Aging.

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  • Supplementary data

    • Supplementary data

    glab127_suppl_Supplemental_Table_and_Figure - docx file