Association of accelerometer-measured physical activity with kidney function in a Japanese population: the DOSANCO Health Study

Associations between leisure time, non-leisure time physical activity, and kidney function in Japanese adults: a cross-sectional study

BACKGROUND

Chronic kidney disease (CKD) contributes to decreased life expectancy. We examined the association between leisure-time physical activity (LTPA), non-leisure-time physical activity (non-LTPA) and kidney function.

METHODS

This was a cross-sectional study including 32 162 community-dwelling adults aged ≥ 20 years from the Tohoku Medical MegaBank community-based cohort study. Kidney function was evaluated using cystatin C-based estimated glomerular filtration rate (eGFR) as well as self-reported LTPA and non-LTPA. CKD was defined as either eGFR decline (≤ 60 mL/min/1.73 m2) or presence of albuminuria (albumin-creatinine ≥ 30 mg/g). The association between domain-specific physical activity and kidney function, and CKD prevalence was examined using multivariable-adjusted ordinary least squares and modified Poisson models.

RESULTS

The mean eGFR was 98.1 (± 13.2) mL/min/1.73 m2. 3 185 (9.9%) participants were classified as having CKD. The mean LTPA and non-LTPA levels were 2.9 (± 4.2) and 16.6 (± 14.2) METs-hour/day, respectively. For LTPA, in the adjusted model, the quartile groups with higher levels had a higher kidney function (β, 0.36; 95% confidence intervals [CI], [0.06, 0.66]; p = 0.019 for the 2nd quartile, β, 0.82; 95% CI, [0.51, 1.14]; p < 0.001 for the 3rd quartile, and β, 1.16; 95% CI, [0.83, 1.49]; p < 0.001 for the 4th quartile), whereas there were no apparent associations for prevalence of CKD. For non-LTPA, 4th quartile was associated with decreased eGFR (β, -0.42; 95% CI, [-0.72, -0.11]; p = 0.007) and higher prevalence of CKD prevalence (Prevalence ratio, 1.12; 95% CI, [1.02, 1.24]; p = 0.022). These associations with kidney function remained consistent in the subgroup analyses divided by demographic and biological variables.

CONCLUSIONS

We observed a positive association between higher LTPA levels and better kidney function, but not association with CKD prevalence. In contrast, higher non-LTPA was negatively associated with both kidney function and CKD prevalence. These findings suggest that promoting LTPA is beneficial for kidney function.

Dose-Response Relationships of Moderate to Vigorous Physical Activity and Sedentary Time With Renal Function Indices in Adolescents With Reduced Renal Function: A Cross-Sectional Study

BACKGROUND

This study aimed to explore the associations between moderate to vigorous physical activity (MVPA) and sedentary time with renal function indices in adolescents with kidney disease.

METHODS

A cross-sectional study was conducted on 719 adolescents (median age 15 y, 40.6% female) with kidney disease from the National Health and Nutrition Examination Survey 2007-2016. The exposures were MVPA time and sedentary time. Renal metabolic parameters included serum uric acid (SUA), creatinine, blood urea nitrogen, the estimated glomerular filtration rate (eGFR), and the albumin creatinine ratio. Weighted multivariate regression analysis was used to estimate associations between exposures and outcomes.

RESULTS

After stratifying MVPA time, the regression effect values β (95% CI) for MVPA on SUA (Q2: -0.22 [-0.41 to -0.03]; Q3: -0.32 [-0.53 to -0.11]) and creatinine (Q2: -0.08 [-0.15 to -0.01]; Q3: -0.04 [-0.11 to 0.03]) gradually decreased with increasing MVPA time. In males (-0.76 [-1.19 to -0.32]), MVPA time was significantly associated with lower SUA levels compared with females (-0.14 [-0.38 to 0.10]). Notably, female adolescents who had an MVPA time exceeding 420 minutes exhibited lower albumin creatinine ratio (-75.37 [-146.63 to -4.11]). In addition, both recreational MVPA time (-0.26 [-0.45 to -0.06]) and sedentary time (-3.15 [-5.83 to -0.46]) were negatively associated with eGFR.

CONCLUSIONS

Our study found an association between MVPA and lower levels of SUA in male adolescents with kidney disease and albuminuria in female adolescents with kidney disease. In addition, MVPA was also negatively associated with creatinine and eGFR, whereas sedentary time was only associated with eGFR. Further studies are needed to confirm these findings.

Data Analytics in Physical Activity Studies With Accelerometers: Scoping Review

BACKGROUND

Monitoring free-living physical activity (PA) through wearable devices enables the real-time assessment of activity features associated with health outcomes and provision of treatment recommendations and adjustments. The conclusions of studies on PA and health depend crucially on reliable statistical analyses of digital data. Data analytics, however, are challenging due to the various metrics adopted for measuring PA, different aims of studies, and complex temporal variations within variables. The application, interpretation, and appropriateness of these analytical tools have yet to be summarized.

OBJECTIVE

This research aimed to review studies that used analytical methods for analyzing PA monitored by accelerometers. Specifically, this review addressed three questions: (1) What metrics are used to describe an individual's free-living daily PA? (2) What are the current analytical tools for analyzing PA data, particularly under the aims of classification, association with health outcomes, and prediction of health events? and (3) What challenges exist in the analyses, and what recommendations for future research are suggested regarding the use of statistical methods in various research tasks?

METHODS

This scoping review was conducted following an existing framework to map research studies by exploring the information about PA. Three databases, PubMed, IEEE Xplore, and the ACM Digital Library, were searched in February 2024 to identify related publications. Eligible articles were classification, association, or prediction studies involving human PA monitored through wearable accelerometers.

RESULTS

After screening 1312 articles, 428 (32.62%) eligible studies were identified and categorized into at least 1 of the following 3 thematic categories: classification (75/428, 17.5%), association (342/428, 79.9%), and prediction (32/428, 7.5%). Most articles (414/428, 96.7%) derived PA variables from 3D acceleration, rather than 1D acceleration. All eligible articles (428/428, 100%) considered PA metrics represented in the time domain, while a small fraction (16/428, 3.7%) also considered PA metrics in the frequency domain. The number of studies evaluating the influence of PA on health conditions has increased greatly. Among the studies in our review, regression-type models were the most prevalent (373/428, 87.1%). The machine learning approach for classification research is also gaining popularity (32/75, 43%). In addition to summary statistics of PA, several recent studies used tools to incorporate PA trajectories and account for temporal patterns, including longitudinal data analysis with repeated PA measurements and functional data analysis with PA as a continuum for time-varying association (68/428, 15.9%).

CONCLUSIONS

Summary metrics can quickly provide descriptions of the strength, frequency, and duration of individuals' overall PA. When the distribution and profile of PA need to be evaluated or detected, considering PA metrics as longitudinal or functional data can provide detailed information and improve the understanding of the role PA plays in health. Depending on the research goal, appropriate analytical tools can ensure the reliability of the scientific findings.

Accelerometer-Measured Physical Activity Data Sets (Global Physical Activity Data Set Catalogue) That Include Markers of Cardiometabolic Health: Systematic Scoping Review

BACKGROUND

Cardiovascular disease accounts for 17.9 million deaths globally each year. Many research study data sets have been collected to answer questions regarding the relationship between cardiometabolic health and accelerometer-measured physical activity. This scoping review aimed to map the available data sets that have collected accelerometer-measured physical activity and cardiometabolic health markers. These data were then used to inform the development of a publicly available resource, the Global Physical Activity Data set (GPAD) catalogue.

OBJECTIVE

This review aimed to systematically identify data sets that have measured physical activity using accelerometers and cardiometabolic health markers using either an observational or interventional study design.

METHODS

Databases, trial registries, and gray literature (inception until February 2021; updated search from February 2021 to September 2022) were systematically searched to identify studies that analyzed data sets of physical activity and cardiometabolic health outcomes. To be eligible for inclusion, data sets must have measured physical activity using an accelerometric device in adults aged ≥18 years; a sample size >400 participants (unless recruited participants in a low- and middle-income country where a sample size threshold was reduced to 100); used an observational, longitudinal, or trial-based study design; and collected at least 1 cardiometabolic health marker (unless only body mass was measured). Two reviewers screened the search results to identify eligible studies, and from these, the unique names of each data set were recorded, and characteristics about each data set were extracted from several sources.

RESULTS

A total of 17,391 study reports were identified, and after screening, 319 were eligible, with 122 unique data sets in these study reports meeting the review inclusion criteria. Data sets were found in 49 countries across 5 continents, with the most developed in Europe (n=53) and the least in Africa and Oceania (n=4 and n=3, respectively). The most common accelerometric brand and device wear location was Actigraph and the waist, respectively. Height and body mass were the most frequently measured cardiometabolic health markers in the data sets (119/122, 97.5% data sets), followed by blood pressure (82/122, 67.2% data sets). The number of participants in the included data sets ranged from 103,712 to 120. Once the review processes had been completed, the GPAD catalogue was developed to house all the identified data sets.

CONCLUSIONS

This review identified and mapped the contents of data sets from around the world that have collected potentially harmonizable accelerometer-measured physical activity and cardiometabolic health markers. The GPAD catalogue is a web-based open-source resource developed from the results of this review, which aims to facilitate the harmonization of data sets to produce evidence that will reduce the burden of disease from physical inactivity.

Associations of Prolonged Occupational Sitting with the Spectrum of Kidney Disease: Results from a Cohort of a Half-Million Asian Adults

BACKGROUND

Kidney diseases are viewed as continuously progressing diseases from microalbuminuria and chronic kidney disease (CKD), to end-stage renal disease (ESRD) and its mortality including deaths. The report on the association between prolonged sitting and kidney diseases is limited.

METHODS

We examined a cohort of 455,506 participants in a screening program in Taiwan conducted between 1996 and 2017. Data on occupational sedentary behavior and physical activity were collected with a standardized questionnaire. The outcomes of ESRD and death were identified by linking with the Catastrophic Illness Dataset and Cause of Death Data. The association between prolonged sitting and CKD, the incidence of ESRD, and death were assessed using logistic regression models to compute odds ratios (ORs) and Cox proportional hazards models for hazard ratios (HRs).

RESULTS

More than half of the participants, i.e., 265,948 (58.4%), were categorized as "prolonged sitting" during their work. During a median of 13 years of follow-up, we identified 2227 individuals undergoing dialysis and 25,671 deaths. Prolonged occupational sitting was significantly associated with a higher risk of CKD (OR: 1.26, 95% confidence interval: 1.21, 1.31), ESRD (HR: 1.19, 95% CI 1.03, 1.38), and kidney-specific mortality (HR: 1.43, 95% CI 1.07, 1.91) compared to mostly standing participants after controlling for physical activity and other risk factors. Inactive prolonged sitting carries a significantly higher risk of ESRD than physically active mostly standing participants (HR: 1.34, 95% CI 1.04, 1.73). However, active prolonged sitting decreased the risk of ESRD (HR: 1.03, 95% CI 0.79, 1.34) compared to inactive prolonged sitting.

CONCLUSION

The results suggest that prolonged occupational sitting is associated with a greater risk of the spectrum of kidney disease, proteinuria, CKD, dialysis (ESRD), and mortality for all causes and kidney diseases. Physical activity, even at a minimal level of 15 min/day (90 min/week) of moderate-intensity exercise, was associated with a reduction in these risks.

Internet use and physical activity of older adults during the COVID-19 pandemic: a cross-sectional study in a northern Japanese City

Background

Little is known of whether Internet use is associated with physical activity among socially isolated older adults during the coronavirus disease 2019 (COVID-19) pandemic. This study investigated the association between Internet use and physical activity, and whether this association differs depending on social isolation among community-dwelling Japanese older adults.

Methods

A cross-sectional study was conducted with 1048 community-dwelling residents aged 65–90 years. Data were obtained using a self-reported questionnaire in August 2020. Physical activity was assessed using the International Physical Activity Questionnaire-Short Form. Multivariable logistic regression analyses were used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between Internet use and moderate-to-vigorous physical activity (MVPA).

Results

Internet use showed a significant association with MVPA (OR = 1.42, 95% CI: 1.06–1.90) after adjusting for age, sex, self-reported socioeconomic status, and other health-related characteristics. When the results were stratified by social participation and living status, Internet use was associated with a significantly higher likelihood of MVPA among participants with no social participation (OR = 1.81, 95% CI: 1.03–3.17) and living with family (OR = 1.40, 95% CI: 1.02–1.93).

Conclusion

Internet use was associated with sufficient physical activity, and this association may differ depending on the social isolation among community-dwelling older adults in Japan.