Both sedentary time and physical activity are associated with cardiometabolic health in overweight adults in a 1-month accelerometer measurement

The study addresses whether device-measured sedentary behavior and different intensities of physical activity are associated with cardiometabolic health markers in overweight, working-age adults who report low physical activity. Background evidence indicates that insufficient MVPA and prolonged sedentary time predict metabolic disorders, type 2 diabetes, cardiovascular disease, and premature mortality. A substantial proportion of adults are inactive, and global obesity rates add to cardiometabolic risk. Prior work using objective measures links higher SB to adverse glucose, insulin, lipid profiles, and increased risk of metabolic syndrome and type 2 diabetes, although some findings are mixed, particularly regarding the benefits of breaking up sedentary time. Most device-based studies have short monitoring periods (typically ≤7 days), which may not capture habitual behavior accurately and may be influenced by device wear. This study extends monitoring to 4 weeks with high-resolution hip-worn triaxial accelerometry to more precisely quantify SB, standing, LPA, MVPA, and breaks, and tests associations with fasting glucose, insulin, HbA1c, lipids, and HOMA-IR, adjusting for key confounders (age, sex, BMI).

- Objectively measured sedentary time has been associated cross-sectionally with higher plasma glucose, insulin, triglycerides, lower HDL-cholesterol, larger waist circumference, glucose intolerance, and increased risk of metabolic syndrome and type 2 diabetes in several cohorts. Some studies in population samples show stronger associations for MVPA with BMI, waist, HbA1c, and HDL than for sedentary status, which sometimes associates only with HDL. - Breaking up sitting with activity breaks has attenuated postprandial glucose and insulin responses in short-term crossover trials, and sit-to-stand transitions correlate with smaller waist circumference, but evidence is mixed and not consistently observed across studies. - Device-based measurement limitations include short wear periods and reliance on counts rather than posture classification; extended monitoring improves reliability. At least 14–30 days may be needed to achieve high reliability of habitual activity/sedentary estimates when compared to 365-day monitoring. - LPA has shown beneficial associations with aspects of lipid metabolism (e.g., HDL particle profile), while MVPA is often linked to VLDL-related lipids; compositional analyses suggest LPA may have strong associations with triglycerides. Vigorous activity may mitigate harms of sedentary time. Total PA volume is associated with lower premature mortality risk.

Design: One-arm explorative observational cross-sectional analysis (screening phase of an intervention) conducted at Turku PET Centre, Turku, Finland (April 2017–May 2019). Ethics approval obtained; informed consent provided; registered at ClinicalTrials.gov (NCT03101228). Participants: Recruited via community advertisements. Inclusion: age 40–65 years, BMI 25–40 kg/m², self-reported not meeting PA recommendations and predominantly sitting. Exclusion: history of cardiac event, insulin or medically treated diabetes, high alcohol use, narcotics, tobacco/snus use, inability to understand written Finnish, or conditions compromising safety/procedures. Procedures: Screening interview with measurements of BMI, waist circumference, blood pressure. Participants wore a hip-worn tri-axial accelerometer (UKK AM30; ADXL345 sensor; 100 Hz; ±16 g; 4 mg resolution) on the right hip during waking hours for 4 consecutive weeks (avoid water exposure). They were advised to maintain habitual lifestyle. During the 4-week period, fasting venous blood samples were collected at a convenient time. Accelerometry and derived measures: Raw acceleration analyzed in 6-second epochs using validated mean amplitude deviation (MAD) and converted to METs. Intensity thresholds: LPA ≥1.5 and <3.0 METs (MAD 22.5–91.5 mg), MVPA ≥3.0 METs (MAD >91.5 mg); vigorous PA (≥6.0 METs) was combined with MVPA due to non-normality. Epoch-wise METs smoothed with 1-min exponential moving average; daily peak 1-min EMA MET and daily mean MET computed. Posture classification: For epochs with MAD <22.5 mg, body posture determined by angle for posture estimation (APE) method. APE <11.6° classified as standing; ≥11.6° as sedentary behavior. In standardized conditions, SB vs standing accuracy ~95%; agreement with thigh-worn data in free-living ~90%. Breaks in sedentary time: Number of SB periods (1-min EMA MET <1.5) ending with a clear vertical acceleration and subsequent standing or movement. Step detection: Vertical acceleration component (1–4 Hz band-pass) integrated; steps detected when integral exceeded a threshold; requires ~3 km/h to detect every step. Wear-time criteria: Non-wear defined as acceleration within 187.5 mg range on all axes for ≥30 min. Valid day: 10–19 h wear; ≥4 valid days required. Time >19 h/day considered sleep and subtracted from SB time. Activity intensities also expressed as percentage of wear time per day. Clinical measures: Fasting plasma insulin (ECLIA), glucose (hexokinase), triglycerides and total/LDL/HDL cholesterol (enzymatic colorimetric tests), HbA1c (turbidimetric inhibition immunoassay). HOMA-IR calculated as glucose × insulin/22.5. Blood pressure measured seated after ≥10 min rest; heart rate recorded. Anthropometrics: body mass, height, waist circumference (measured twice until repeatable). Statistical analysis: Due to sex differences in fasting insulin, sex included in all models. Linear models tested associations between accelerometer measures and outcomes (BMI, waist, glucose, HbA1c, insulin, HOMA-IR), adjusting for age and sex; lipid models additionally adjusted for statin use; blood pressure models for antihypertensive treatment. Further models added BMI to adjust for adiposity confounding. Log10 transformations applied when needed. Residuals inspected for normality; sensitivity analyses via leave-one-out. Missing data handled by pairwise deletion and maximum likelihood. Significance set at 5%. Analyses performed with JMP Pro 13.1 (SAS). Additional analyses repeated using only first week of accelerometry (4–7 valid days) to compare with 4-week monitoring.

Sample and monitoring: 144 adults (42 men); mean age 57 (SD 6.5) years; mean BMI 31.7 (SD 4.0) kg/m². Mean accelerometer wear time 14.37 (SD 1.04) h/day over 25 (SD 4) days; 67.0% (SD 8.3) of wear time sedentary; average 5,265 (SD 2,113) steps/day. Men had higher sedentary proportion and lower standing time compared to women. Anthropometrics: BMI associated negatively with MVPA, daily steps, breaks in sedentary time, and MET peak, and positively with sedentary proportion (sex- and age-adjusted). Waist circumference associated with fewer breaks, fewer steps, lower MET peak, higher sedentary proportion, and lower standing time. Insulin and insulin resistance: Adjusted for age and sex, fasting insulin (log10) and HOMA-IR were: - Positively associated with sedentary proportion (e.g., insulin vs sedentary % p=0.0011). - Negatively associated with standing time (% and h/day), LPA (time and %), MVPA (time and %), total PA (time and %), steps/day (p<0.0001), breaks in sedentary time (p=0.0005), MET mean (p=0.0001), and MET peak (p=0.0003). Strongest associations were with steps/day and MET mean. Glucose and HbA1c: Adjusted for age and sex, fasting glucose was positively associated with sedentary proportion (p=0.017) and negatively with standing time (p=0.022), MVPA time (p=0.0072), PA time (p=0.038), steps/day (p=0.0024), breaks (p=0.027), MET mean (p=0.020), and MET peak (p=0.035). In sensitivity analysis excluding one glucose outlier, only standing, MVPA, and steps remained significant. HbA1c associated negatively with breaks in sedentary time but became non-significant after excluding one outlier (p=0.089). Lipids: Adjusted for age, sex, and statins: - Triglycerides (log10) positively associated with sedentary proportion (p=0.0011) and negatively with LPA (time p=0.0029; % p=0.0059), MVPA (time p=0.0080; % p=0.015), total PA (time p=0.0011; % p=0.0022), steps/day (p=0.0076), breaks (p=0.0080), and MET mean (p=0.0033). Associations were stronger for LPA and total PA than MVPA. - HDL-cholesterol negatively associated with sedentary time and sedentary proportion, and positively with LPA, MVPA, total PA (all p≤0.048). No association with standing. - No significant associations for total cholesterol or LDL-cholesterol. Blood pressure and heart rate: No associations between accelerometer measures and systolic/diastolic blood pressure. Lower resting heart rate associated with more breaks in sedentary time (p=0.018). BMI-adjusted models: After adding BMI, associations of breaks with metabolic markers became non-significant. However, insulin and HOMA-IR remained negatively associated with PA, steps, and MET mean/peak and positively with sedentary proportion. Triglycerides and HDL remained associated with sedentary proportion, PA, steps, and MET mean. Associations for glucose, HbA1c, and resting heart rate with activity measures became non-significant. One-week vs four-week accelerometry: Using only the first week of data, several associations (especially those involving insulin/glucose and some BMI/waist relations) were no longer significant compared with 4-week analyses, indicating improved detection and stability of associations with longer monitoring. Lipid-related associations were more consistent across durations.

The findings demonstrate that a higher proportion of the day spent sedentary is associated with greater insulin resistance in overweight working-age adults with low self-reported activity, while greater total physical activity—irrespective of intensity—is associated with lower fasting insulin and improved insulin sensitivity. LPA and MVPA both contributed to favorable lipid profiles, with LPA showing particularly strong associations with lower triglycerides and higher HDL, suggesting that accumulating activity at lower intensities across the day can be beneficial when MVPA recommendations are unmet. Standing time was not independently associated with insulin sensitivity after accounting for BMI, though it related to waist circumference, indicating limited metabolic stimulus from standing alone compared to ambulatory activity. Adjustment for BMI revealed that excess adiposity attenuates some associations, notably those involving glucose and HbA1c, implying that adiposity may exert a stronger influence on fasting glycemia than SB or PA in this cohort, whereas SB and PA remain robustly related to insulin dynamics and lipids. The lack of associations with blood pressure and LDL/total cholesterol aligns with prior mixed evidence for short-term cross-sectional links. Importantly, the extended 4-week accelerometry provided more reliable estimates and revealed associations that would have been missed with typical 1-week monitoring, particularly for insulin-glucose outcomes and light-intensity behaviors. This underscores the value of longer monitoring periods and high-resolution posture/activity classification for studying habitual SB/PA-health relationships.

In overweight, working-age adults with low self-reported activity, a higher sedentary proportion is associated with greater insulin resistance, while greater total physical activity—regardless of intensity—is associated with lower fasting insulin, better insulin sensitivity, and a more favorable lipid profile. LPA shows strong beneficial associations with triglycerides and HDL. After adjusting for BMI, breaks in sedentary time do not independently relate to metabolic markers, and BMI appears to have a stronger impact on fasting glucose than PA or SB. The total daily duration of activity may be more important than intensity for maintaining metabolic health when MVPA guidelines are not met. Longer accelerometer monitoring (≈4 weeks) enhances detection of these associations and is recommended for future research.

- Cross-sectional design precludes causal inference. - Diet and energy intake were not assessed; unmeasured nutritional factors could confound associations. - Accelerometers were worn only during waking hours; variable wear time may bias sedentary estimates (non-wear likely sedentary). Full 24-h monitoring could yield more robust measures. - Hip placement may misclassify some postures/activities compared to thigh placement, though validated posture algorithms were used. - Step detection underestimates steps at slow speeds (<~3 km/h). - Sample restricted to overweight adults (BMI 25–40 kg/m²) aged 40–65 years with low PA; generalizability to other populations may be limited. - Some associations (e.g., glucose, HbA1c) were sensitive to outliers and to adjustment for BMI.