Physical Activity in the Prevention of Weight Gain: the Impact of Measurement and Interpretation of Associations

Joint associations of physical activity and sedentary time with body mass index: A prospective study of mortality risk

Device-measured physical activity and sedentary time are suggested to be more important determinants of all-cause mortality compared to body mass index (BMI) in mainly older adults. However, the joint associations of physical activity and sedentary time with BMI in relation to mortality risk in relatively healthy middle-aged individuals are unclear. We followed 770 adults (56% women, mean age 55.6 years) from a population-based cohort study for up to 15.3 years. BMI categories were combined with tertiles of total, light, and moderate-to-vigorous physical activity and sedentary time. Cox proportional hazards models estimated hazard ratios (HR) of all-cause mortality with 95% confidence intervals (CI). High total and light intensity physical activity and low sedentary time were associated with a lower risk of mortality in normal weight individuals compared with low active overweight/obese; HR: 0.35 (CI: 0.14, 0.86), HR: 0.33 (CI: 0.12, 0.89), and HR: 0.34 (CI: 0.13, 0.92). Among overweight/obese individuals, those who were medium active in light physical activity had a lower mortality risk, HR: 0.36 (CI: 0.15, 0.83), compared with low active. Medium sedentary individuals had a lower risk, HR: 0.43 (CI: 0.20, 0.94) compared with those who were most sedentary. Associations among the most active or least sedentary tertiles were similar irrespective of BMI category. In conclusion, higher physical activity and lower sedentary time were associated with lower mortality risk irrespective of BMI. Physical activity should be promoted and prescribed to individuals with low physical activity levels irrespective of weight status.

Physical activity volume, intensity, and incident cardiovascular disease

AIMS

The interplay between physical activity (PA) volume and intensity is poorly understood in relation to cardiovascular disease (CVD) risk. This study aimed to investigate the role of PA intensity, over and above volume, in relation to incident CVD.

METHODS AND RESULTS

Data were from 88 412 UK Biobank middle-aged adults (58% women) without prevalent CVD who wore accelerometers on their dominant wrist for 7 days, from which we estimated total PA energy expenditure (PAEE) using population-specific validation. Cox proportional hazards regressions modelled associations between PAEE (kJ/kg/day) and PA intensity (%MVPA; the fraction of PAEE accumulated from moderate-to-vigorous-intensity PA) with incident CVD (ischaemic heart disease or cerebrovascular disease), adjusted for potential confounders. There were 4068 CVD events during 584 568 person-years of follow-up (median 6.8 years). Higher PAEE and higher %MVPA (adjusted for PAEE) were associated with lower rates of incident CVD. In interaction analyses, CVD rates were 14% (95% confidence interval: 5-23%) lower when MVPA accounted for 20% rather than 10% of 15 kJ/kg/d PAEE; equivalent to converting a 14 min stroll into a brisk 7 min walk. CVD rates did not differ significantly between values of PAEE when the %MVPA was fixed at 10%. However, the lowest CVD rates were observed for combinations of both higher PAEE and %MVPA.

CONCLUSION

Reductions in CVD risk may be achievable through higher PA volume and intensity, with the role of moderately intense PA appearing particularly important. This supports multiple approaches or strategies to PA participation, some of which may be more practical or appealing to different individuals.

Associations between physical activity and functional limitations in Native Hawaiian and Pacific Islander middle-aged and older adults in the United States

OBJECTIVES

Physical activity (PA) can help individuals maintain physical function and independence. The association between PA and functional limitations (FL) has not been explored in the Native Hawaiian and Pacific Islander (NHPI) population. The purpose of this study was to examine relationships between PA and FL among NHPI adults (age ≥ 45 years) living in the United States.

DESIGN

Cross-sectional data from the 2014 NHPI-National Health Interview Survey (N = 628) was used to create three constructs of FL based on responses from the Functioning and Disability Survey Module: needing equipment/assistance, having difficulty walking, and having difficulty with performing self-care and other fine motor activities. We used 2-stage least squares regression to examine the relationship between PA and FL of NHPI adults while accounting for the potential endogeneity of PA to FL.

RESULTS

Compared to NHPI adults who met the guideline for recommended levels of aerobic and strengthening PA, those who met only the strengthening guideline experienced less difficulty in two FL constructs (use of medical equipment/assistance and difficulty walking). Those who met the aerobic guideline reported even less difficulties in all three FL constructs. NHPI adults who met both the aerobic and strengthening guidelines experienced the least difficulties in all three FL constructs compared to those who met neither PA guidelines.

CONCLUSIONS

PA is associated with function in this adult NHPI population. Aerobic guidelines alone may be more beneficial than meeting the strengthening guideline alone; however, meeting both the aerobic and strengthening guidelines is most protective against FL.

Physical activity, sedentary behavior and risk of coronary artery disease, myocardial infarction and ischemic stroke: a two-sample Mendelian randomization study

AIMS

Observational evidence suggests that physical activity (PA) is inversely and sedentarism positively related with cardiovascular disease risk. We performed a two-sample Mendelian randomization (MR) analysis to examine whether genetically predicted PA and sedentary behavior are related to coronary artery disease, myocardial infarction, and ischemic stroke.

METHODS AND RESULTS

We used single nucleotide polymorphisms (SNPs) associated with self-reported moderate to vigorous PA (n = 17), accelerometer based PA (n = 7) and accelerometer fraction of accelerations > 425 milli-gravities (n = 7) as well as sedentary behavior (n = 6) in the UK Biobank as instrumental variables in a two sample MR approach to assess whether these exposures are related to coronary artery disease and myocardial infarction in the CARDIoGRAMplusC4D genome-wide association study (GWAS) or ischemic stroke in the MEGASTROKE GWAS. The study population included 42,096 cases of coronary artery disease (99,121 controls), 27,509 cases of myocardial infarction (99,121 controls), and 34,217 cases of ischemic stroke (404,630 controls). We found no associations between genetically predicted self-reported moderate to vigorous PA, accelerometer-based PA or accelerometer fraction of accelerations > 425 milli-gravities as well as sedentary behavior with coronary artery disease, myocardial infarction, and ischemic stroke.

CONCLUSIONS

These results do not support a causal relationship between PA and sedentary behavior with risk of coronary artery disease, myocardial infarction, and ischemic stroke. Hence, previous observational studies may have been biased.

The bidirectional associations between leisure time physical activity change and body mass index gain. The Tromsø Study 1974-2016

OBJECTIVES

To examine whether leisure time physical activity changes predict subsequent body mass index (BMI) changes, and conversely, whether BMI changes predict subsequent leisure time physical activity changes.

METHODS

This prospective cohort study included adults attending ≥3 consecutive Tromsø Study surveys (time: T1, T2, T3) during 1974-2016 (n = 10779). If participants attended >3 surveys, we used the three most recent surveys. We computed physical activity change (assessed by the Saltin-Grimby Physical Activity Level Scale) from T1 to T2, categorized as Persistently Inactive (n = 992), Persistently Active (n = 7314), Active to Inactive (n = 1167) and Inactive to Active (n = 1306). We computed BMI change from T2 to T3, which regressed on preceding physical activity changes using analyses of covariance. The reverse association (BMI change from T1 to T2 and physical activity change from T2 to T3; n = 4385) was assessed using multinomial regression.

RESULTS

Average BMI increase was 0.86 kg/m² (95% CI: 0.82-0.90) from T2 to T3. With adjustment for sex, birth year, education, smoking and BMI at T2, there was no association between physical activity change from T1 to T2 and BMI change from T2 to T3 (Persistently Inactive: 0.89 kg/m² (95% CI: 0.77-1.00), Persistently Active: 0.85 kg/m² (95% CI: 0.81-0.89), Active to Inactive: 0.90 kg/m² (95% CI: 0.79-1.00), Inactive to Active 0.85 kg/m² (95% CI: 0.75-0.95), p = 0.84). Conversely, increasing BMI was associated with Persistently Inactive (odds ratio (OR): 1.17, 95% CI: 1.08-1.27, p < 0.001) and changing from Active to Inactive (OR: 1.16, 95% CI: 1.07-1.25, p < 0.001) compared with being Persistently Active.

CONCLUSIONS

We found no association between leisure time physical activity changes and subsequent BMI changes, whereas BMI change predicted subsequent physical activity change. These findings indicate that BMI change predicts subsequent physical activity change at population level and not vice versa.

Device-Measured Physical Activity, Sedentary Behaviors, Built Environment, and Adiposity Gain in Older Women: A Seven-Year Prospective Study

The search for determinants of adiposity gain in older women has become vitally important. This study aimed to (1) analyze the adiposity gain based on the participants’ age and (2) determine the prospective associations of baseline intrapersonal, built environment, physical activity, and sedentary behavior variables with the adiposity gain in older women. This was a seven-year prospective study (baseline: 2009 to 2012; follow-up: 2016 to 2019) in older women (n = 178, baseline age = 62.8 ± 4.1 years). Baseline and follow-up adiposity (bioelectrical impedance) and baseline physical activity, sedentary behavior (accelerometers), and intrapersonal and built environment (Neighborhood Environment Walkability Scale questionnaire) variables were included. The body mass index (BMI) increment tended to be inversely associated with the women’s age (p = 0.062). At follow-up, 48, 57, and 54% of the women had a relevant increase (d-Cohen > 0.2) in their BMI, percentage of body fat, and fat mass index, respectively. The women that spent ≥8 h/day being sedentary were 2.2 times (1.159 to 4.327 CI95%, p < 0.02) more likely to increase BMI (0.82 to 0.85 kg/m²) than non-sedentary women. No built environment variables were associated with seven-year adiposity gain (all ps > 0.05). A reduction in sedentary time should be promoted for adiposity gain prevention and health preservation in older women.

Physical Activity and Mortality Across Levels of Adiposity: A Prospective Cohort Study From the UK Biobank

OBJECTIVE

To examine the combined and stratified associations of physical activity and adiposity measures, modelled as body mass index (BMI), abdominal adiposity (waist circumference), and body fat percentage (BF) with all-cause mortality.

PATIENTS AND METHODS

Using the UK Biobank cohort, we extracted quintiles of self-reported weekly physical activity. Categories of measured BMI, waist circumference, and BF were generated. Joint associations between physical activity-adiposity categories and mortality were examined using Cox proportional hazards models adjusted for demographic, behavioral, and clinical covariates. Physical activity-mortality associations were also examined within adiposity strata. Participants were followed from baseline (2006 to 2010) through January 31, 2018.

RESULTS

A total of 295,917 participants (median follow-up, 8.9 years, during which 6684 deaths occurred) were included. High physical activity was associated with lower risk of premature mortality in all strata of adiposity except for those with BMI ≥35 kg/m². Highest risk (HR, 1.54; 95% CI; 1.33 to 1.79) was observed in individuals with low physical activity and high BF as compared with the high physical activity-low BF referent. High physical activity attenuated the risk of high adiposity when using BF (HR, 1.24; 95% CI; 1.04 to 1.49), but the association was weaker with BMI (HR, 1.45; 95% CI; 1.21 to 1.73). Physical activity also attenuated the association between mortality and high waist circumference.

CONCLUSION

Low physical activity and adiposity were both associated with a higher risk of premature mortality, but high physical activity attenuated the increased risk with adiposity irrespective of adiposity metric, except in those with a BMI ≥35 kg/m².

Do declines in occupational physical activity contribute to population gains in body mass index? Tromsø Study 1974-2016

OBJECTIVE

To examine whether occupational physical activity changes predict future body mass index (BMI) changes.

METHODS

This longitudinal cohort study included adult participants attending ≥3 consecutive Tromsø Study surveys (examinations 1, 2 and 3) from 1974 to 2016 (N=11 308). If a participant attended >3 surveys, the three most recent surveys were included. Occupational physical activity change (assessed by the Saltin-Grimby Physical Activity Level Scale) was computed from the first to the second examination, categorised into persistently inactive (n=3692), persistently active (n=5560), active to inactive (n=741) and inactive to active (n=1315). BMI change was calculated from the second to the third examination (height being fixed at the second examination) and regressed on preceding occupational physical activity changes using analysis of covariance adjusted for sex, birth year, smoking, education and BMI at examination 2.

RESULTS

Overall, BMI increased by 0.84 kg/m2 (95% CI 0.82 to 0.89). Following adjustments as described previously, we observed no differences in BMI increase between the occupational physical activity change groups (Persistently Inactive: 0.81 kg/m2, 95% CI 0.75 to 0.87; Persistently Active: 0.87 kg/m2, 95% CI 0.82 to 0.92; Active to Inactive: 0.81 kg/m2, 95% CI 0.67 to 0.94; Inactive to Active: 0.91 kg/m2, 95% CI 0.81 to 1.01; p=0.25).

CONCLUSION

We observed no prospective association between occupational physical activity changes and subsequent BMI changes. Our findings do not support the hypothesis that occupational physical activity declines contributed to population BMI gains over the past decades. Public health initiatives aimed at weight gain prevention may have greater success if focusing on other aspects than occupational physical activity.

Physical activity levels in adults and elderly from triaxial and uniaxial accelerometry. The Tromsø Study

Introduction

Surveillance of physical activity at the population level increases the knowledge on levels and trends of physical activity, which may support public health initiatives to promote physical activity. Physical activity assessed by accelerometry is challenged by varying data processing procedures, which influences the outcome. We aimed to describe the levels and prevalence estimates of physical activity, and to examine how triaxial and uniaxial accelerometry data influences these estimates, in a large population-based cohort of Norwegian adults.

Methods

This cross-sectional study included 5918 women and men aged 40–84 years who participated in the seventh wave of the Tromsø Study (2015–16). The participants wore an ActiGraph wGT3X-BT accelerometer attached to the hip for 24 hours per day over seven consecutive days. Accelerometry variables were expressed as volume (counts·minute^-1 and steps·day^-1) and as minutes per day in sedentary, light physical activity and moderate and vigorous physical activity (MVPA).

Results

From triaxial accelerometry data, 22% (95% confidence interval (CI): 21–23%) of the participants fulfilled the current global recommendations for physical activity (≥150 minutes of MVPA per week in ≥10-minute bouts), while 70% (95% CI: 69–71%) accumulated ≥150 minutes of non-bouted MVPA per week. When analysing uniaxial data, 18% fulfilled the current recommendations (i.e. 20% difference compared with triaxial data), and 55% (95% CI: 53–56%) accumulated ≥150 minutes of non-bouted MVPA per week. We observed approximately 100 less minutes of sedentary time and 90 minutes more of light physical activity from triaxial data compared with uniaxial data (p<0.001).

Conclusion

The prevalence estimates of sufficiently active adults and elderly are more than three times higher (22% vs. 70%) when comparing triaxial bouted and non-bouted MVPA. Physical activity estimates are highly dependent on accelerometry data processing criteria and on different definitions of physical activity recommendations, which may influence prevalence estimates and tracking of physical activity patterns over time.