Excess Medical Care Costs Associated with Physical Inactivity among Korean Adults: Retrospective Cohort Study

Seasonal differences in participation and time spent in physical activity in Russia: The Know Your Heart survey

This study aimed to assess the levels and investigate socioeconomic, demographic, and health-related predictors of winter and summer physical activity (PA) in Russia using the data from the Know Your Heart population survey conducted in Novosibirsk and Arkhangelsk (2015-2018; n = 5068; aged 35-69 years). Employing a series of probit, Tobit, and the Cragg models, we separated the predictors of the probability of participating in leisure-time PA from the predictors of time spent in PA. Our study showed that financial constraints limited males' participation in winter PA (probability of participation decreased by 12 percentage points) and females' engagement in winter and summer PA (decrease in the number of hours of practicing PA by approximately 1 h a week). Education, self-reported health, smoking, and cues to action had different impacts on both probability and time spent in PA in winter and summer. We also found significant gender differences in participation and time spent in PA across seasons. Older age, poor health, and smoking were greater obstacles to PA for males compared to females both in winter and summer. However, males were more likely to follow physician's advice to lose weight and take up physical exercise. Information campaigns that promote physical activities, including those that are free of charge, are needed to help limit barriers to PA for people with low socioeconomic status and individuals with little or no exercise experience. Also, making sports more accessible to citizens by providing free and low-cost sports facilities can increase their participation and time spent in PA, improving individual health and productivity.

Impact of physical activity on healthcare costs: a systematic review

BACKGROUND

This systematic review aims to describe the relation between physical inactivity and healthcare costs, by taking into account healthcare costs of physical-inactivity-related diseases (common practice), including physical-activity-related injuries (new) and costs in life-years gained due to avoiding diseases (new), whenever available. Moreover, the association between physical inactivity and healthcare costs may both be negatively and positively impacted by increased physical activity.

METHODS

A systematic review was conducted, including records reporting on physical (in)activity in relation to healthcare costs for a general population. Studies were required to report sufficient information to calculate the percentage of total healthcare costs potentially attributable to physical inactivity.

RESULTS

Of the 264 records identified, 25 were included in this review. Included studies showed substantial variation in the assessment methods of physical activity and in type of costs included. Overall, studies showed that physical inactivity is related to higher healthcare costs. Only one study included costs of healthcare resources used in prolonged life when physical-inactivity-related diseases were averted, showing net higher healthcare costs. No study included healthcare costs for physical-activity-related injuries.

CONCLUSIONS

Physical inactivity is associated with higher healthcare costs in the general population in the short-term. However, in the long-term aversion of diseases related with physical inactivity may increase longevity and, as a consequence, healthcare costs in life-years gained. Future studies should use a broad definition of costs, including costs in life-years gained and costs related to physical-activity-related injuries.

The effect of physical activity on health outcomes in people with moderate-to-severe traumatic brain injury: a rapid systematic review with meta-analysis

BACKGROUND

In 2020, the World Health Organization (WHO) released the first global physical activity and sedentary behaviour guidelines for children and adults living with disability. The evidence informing the guidelines though is not specific to people living with traumatic brain injury (TBI), but rather comes from other disabling conditions such as Parkinson's disease, and stroke. There remains a clear lack of direct evidence of the effects of physical activity for people living with TBI. The objective of this rapid review was to identify direct evidence of the effect of physical activity on health outcomes in people with moderate-to-severe TBI to inform adaptation of the WHO physical activity guidelines into clinical practice guidelines.

METHODS

We conducted a rapid systematic review with meta-analysis of randomised controlled trials, including people of any age with moderate-to-severe TBI, investigating physical activity interventions compared to either usual care, a physical activity intervention with different parameters, or a non-physical activity intervention. Four databases (CENTRAL, SPORTDiscus, PEDro, Ovid MEDLINE) were searched from inception to October 8, 2021. The primary outcomes were physical function, cognition, and quality of life.

RESULTS

Twenty-three studies were included incorporating 812 participants (36% females, majority working-age adults, time post-TBI in studies ranged from 56 days (median) to 16.6 years (mean)). A range of physical activity interventions were evaluated in rehabilitation (n = 12 studies), community (n = 8) and home (n = 3) settings. We pooled data from the end of the intervention for eight outcomes. Participation in a virtual reality physical activity intervention improved mobility, assessed by the Community Balance and Mobility Scale (range 0 to 96; higher score indicates better mobility) more than standard balance training (two studies, 80 participants, Mean Difference = 2.78, 95% CI 1.40 to 4.16; low certainty evidence). There was uncertainty of effect for the remaining outcomes, limited by small sample sizes, diverse comparators and a wide range of outcome measures.

CONCLUSION

This review consolidates the current evidence base for the prescription of physical activity for people with moderate-to-severe TBI. There remains a pressing need for further rigorous research in order to develop practice guidelines to support clinical decision-making when prescribing physical activity in this population.

Comparison of Prevalence of Hyperlipidemia, Medical Expenses, Inpatient, Emergency and Outpatient According to the Level of Physical Activity of Korean Adults: A Cross-Sectional Study of 2018 Korea Medical Panel

OBJECTIVES The purpose of this study is to compare the difference in the prevalence of hyperlipidemia according to the level of physical activity in adults, and to compare the difference between annual personal medical expenses, hospitalization, emergency and outpatient use depending on the level of physical activity for hyperlipidemia patients.METHODS The 2018 Korea medical panel data was used (14,489 adults and 2,559 Hyperlipidemia). Physical activity was measured with short form of IPAQ and converted to MET-minutes per week. The days of hospitalization, and personal medical expenses were compared, and frequency analysis, logistic regression, ANOVA and chi-square were performed.RESULTS The prevalence of hyperlipidemia based on the inactive group were decreased both minimally active group (OR = 0.94) and the active group (OR = 0.74, p<0.01). Annual personal medical expenses I (p<.01) and II (p<.01) with hyperlipidemia were all showed significant differences depending on the level of physical activity. On active group basis, medical expenses showed slight differences of 3.0 to 3.2% with the minimally activity group, but that of the inactive group were 19.3 ~ 21.7% higher. The annual days of hospitalization were 6.8 ± 7.2 days in activity group, minimally activity group 7.1 ± 7.2 days, inactive group 11.7 ± 26.0 days. There was no significant difference in the annual days of hospitalization and emergency between the three groups. In particular, the annual days of outpatient increased sharply at the inactive group. Participation in physical activity has been shown to have a significant effect on hospitalization and decreasing use of emergency rooms.CONCLUSIONS Hyperlipidemia prevalence was similar to inactive groups and minimally activity groups, and that of activity groups was 0.74. On medical expenses of hyperlipidemia, the activity and minimally activity group was similar, the inactivity group was 19.3 to 21.7% higher. Physical activity was found to have a positive effect on hospitalization and emergency use reduction.

The association between physical activity and hospital payments for acute admissions in the Australian population aged 45 and over

Physical activity (PA) is a key component of a healthy life, and it is hypothesised that individuals with higher levels of PA utilise fewer hospital resources. Quantifying the association between PA and hospital resource use is of interest to both payers and planners but estimates of its size in the general population are rare. In this paper we provide estimates of the association between PA and payments to hospitals in the Australian population over age 45. We use data from 45 and Up Study, a survey that contains health and lifestyle factors information about approximately 260,000 individuals over age 45 living in NSW, linked to hospital and death data. The linked data set allows to define a unique indicator for the level of PA over the week prior to the survey interview and to calculate payments to hospitals over the next year. We use Coarsened Exact Matching and multivariate analysis to study the relationship between PA and hospital payments, controlling for chronic health conditions, risk factors, standard socioeconomic variables and death. Our results clearly indicate that there is a statistically significant association between PA and lower hospital payments. While the size of the association depends to some extent on the covariates used in the model the conclusions are robust to changes in model specification. We also perform a sub-group analysis and show that the cost savings associated with PA are significantly larger for older and lower income populations. This study shows that if one is interested in lowering hospital expenditures then increasing PA levels is a policy that has the potential of being effective. It also shows that one does not need to target the entire population to achieve cost savings but can limit the intervention to the older population and/or the one in the lowest socioeconomic status.

The economic burden of physical inactivity: a systematic review and critical appraisal

OBJECTIVE

To summarise the literature on the economic burden of physical inactivity in populations, with emphases on appraising the methodologies and providing recommendations for future studies.

DESIGN

Systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO registration number CRD42016047705).

DATA SOURCES

Electronic databases for peer-reviewed and grey literature were systematically searched, followed by reference searching and consultation with experts.

ELIGIBILITY CRITERIA

Studies that examined the economic consequences of physical inactivity in a population/population-based sample, with clearly stated methodologies and at least an abstract/summary written in English.

RESULTS

Of the 40 eligible studies, 27 focused on direct healthcare costs only, 13 also estimated indirect costs and one study additionally estimated household costs. For direct costs, 23 studies used a population attributable fraction (PAF) approach with estimated healthcare costs attributable to physical inactivity ranging from 0.3% to 4.6% of national healthcare expenditure; 17 studies used an econometric approach, which tended to yield higher estimates than those using a PAF approach. For indirect costs, 10 studies used a human capital approach, two used a friction cost approach and one used a value of a statistical life approach. Overall, estimates varied substantially, even within the same country, depending on analytical approaches, time frame and other methodological considerations.

CONCLUSION

Estimating the economic burden of physical inactivity is an area of increasing importance that requires further development. There is a marked lack of consistency in methodological approaches and transparency of reporting. Future studies could benefit from cross-disciplinary collaborations involving economists and physical activity experts, taking a societal perspective and following best practices in conducting and reporting analysis, including accounting for potential confounding, reverse causality and comorbidity, applying discounting and sensitivity analysis, and reporting assumptions, limitations and justifications for approaches taken. We have adapted the Consolidated Health Economic Evaluation Reporting Standards checklist as a guide for future estimates of the economic burden of physical inactivity and other risk factors.