Direct healthcare costs associated with device assessed and self-reported physical activity: results from a cross-sectional population-based study View Full Text


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Article Info

DATE

2018-08-03

AUTHORS

Florian M. Karl, Maximilian Tremmel, Agnes Luzak, Holger Schulz, Annette Peters, Christa Meisinger, Rolf Holle, Michael Laxy

ABSTRACT

BackgroundPhysical inactivity (PIA) is an important risk factor for many chronic conditions and therefore might increase healthcare utilization and costs. This study aimed to analyze the association of PIA using device assessed and self-reported physical activity (PA) data with direct healthcare costs.MethodsCross-sectional data was retrieved from the population based KORA FF4 study (Cooperative Health Research in the Region of Augsburg) that was conducted in southern Germany from 2013 to 2014 (n = 2279). Self-reported PA was assessed with two questions regarding sports related PA in summer and winter and categorized into “high activity”, “moderate activity”, “low activity” and “no activity”. In a subsample (n = 477), PA was assessed with accelerometers and participants were categorized into activity quartiles (“very high”, “high”, “low” and “very low”) according to their mean minutes per day spent in light intensity, or in moderate-vigorous PA (MVPA). Self-reported healthcare utilization was used to estimate direct healthcare costs. We regressed direct healthcare costs on PA using a two-part gamma regression, adjusted for age, sex and socio-demographic variables. Additional models, including and excluding potential additional confounders and effect mediators were used to check the robustness of the results.ResultsAnnual direct healthcare costs of individuals who reported no sports PA did not differ from those who reported high sports PA [+€189, 95% CI: -188, 598]. In the subsample with accelerometer data, participants with very low MVPA had significantly higher annual costs than participants with very high MVPA [+€986, 95% CI: 15, 1982].ConclusionDevice assessed but not self-reported PIA was associated with higher direct healthcare costs. The magnitude and significance of the association depended on the choice of covariates in the regression models. Larger studies with device assessed PA and longitudinal design are needed to be able to better quantify the impact of PIA on direct healthcare costs. More... »

PAGES

966

References to SciGraph publications

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30075768


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        "description": "BackgroundPhysical inactivity (PIA) is an important risk factor for many chronic conditions and therefore might increase healthcare utilization and costs. This study aimed to analyze the association of PIA using device assessed and self-reported physical activity (PA) data with direct healthcare costs.MethodsCross-sectional data was retrieved from the population based KORA FF4 study (Cooperative Health Research in the Region of Augsburg) that was conducted in southern Germany from 2013 to 2014 (n\u2009=\u20092279). Self-reported PA was assessed with two questions regarding sports related PA in summer and winter and categorized into \u201chigh activity\u201d, \u201cmoderate activity\u201d, \u201clow activity\u201d and \u201cno activity\u201d. In a subsample (n\u2009=\u2009477), PA was assessed with accelerometers and participants were categorized into activity quartiles (\u201cvery high\u201d, \u201chigh\u201d, \u201clow\u201d and \u201cvery low\u201d) according to their mean minutes per day spent in light intensity, or in moderate-vigorous PA (MVPA). Self-reported healthcare utilization was used to estimate direct healthcare costs. We regressed direct healthcare costs on PA using a two-part gamma regression, adjusted for age, sex and socio-demographic variables. Additional models, including and excluding potential additional confounders and effect mediators were used to check the robustness of the results.ResultsAnnual direct healthcare costs of individuals who reported no sports PA did not differ from those who reported high sports PA [+\u20ac189, 95% CI: -188, 598]. In the subsample with accelerometer data, participants with very low MVPA had significantly higher annual costs than participants with very high MVPA [+\u20ac986, 95% CI: 15, 1982].ConclusionDevice assessed but not self-reported PIA was associated with higher direct healthcare costs. The magnitude and significance of the association depended on the choice of covariates in the regression models. Larger studies with device assessed PA and longitudinal design are needed to be able to better quantify the impact of PIA on direct healthcare costs.", 
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    30 schema:description BackgroundPhysical inactivity (PIA) is an important risk factor for many chronic conditions and therefore might increase healthcare utilization and costs. This study aimed to analyze the association of PIA using device assessed and self-reported physical activity (PA) data with direct healthcare costs.MethodsCross-sectional data was retrieved from the population based KORA FF4 study (Cooperative Health Research in the Region of Augsburg) that was conducted in southern Germany from 2013 to 2014 (n = 2279). Self-reported PA was assessed with two questions regarding sports related PA in summer and winter and categorized into “high activity”, “moderate activity”, “low activity” and “no activity”. In a subsample (n = 477), PA was assessed with accelerometers and participants were categorized into activity quartiles (“very high”, “high”, “low” and “very low”) according to their mean minutes per day spent in light intensity, or in moderate-vigorous PA (MVPA). Self-reported healthcare utilization was used to estimate direct healthcare costs. We regressed direct healthcare costs on PA using a two-part gamma regression, adjusted for age, sex and socio-demographic variables. Additional models, including and excluding potential additional confounders and effect mediators were used to check the robustness of the results.ResultsAnnual direct healthcare costs of individuals who reported no sports PA did not differ from those who reported high sports PA [+€189, 95% CI: -188, 598]. In the subsample with accelerometer data, participants with very low MVPA had significantly higher annual costs than participants with very high MVPA [+€986, 95% CI: 15, 1982].ConclusionDevice assessed but not self-reported PIA was associated with higher direct healthcare costs. The magnitude and significance of the association depended on the choice of covariates in the regression models. Larger studies with device assessed PA and longitudinal design are needed to be able to better quantify the impact of PIA on direct healthcare costs.
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    37 Germany
    38 KORA FF4 study
    39 MethodsCross-sectional data
    40 PA
    41 PIA
    42 accelerometer
    43 accelerometer data
    44 activity
    45 activity data
    46 activity quartile
    47 additional confounders
    48 additional models
    49 age
    50 annual cost
    51 association
    52 choice
    53 choice of covariates
    54 chronic conditions
    55 conditions
    56 confounders
    57 cost
    58 covariates
    59 cross-sectional population-based study
    60 data
    61 days
    62 design
    63 devices
    64 direct healthcare costs
    65 effect mediators
    66 factors
    67 gamma regression
    68 healthcare costs
    69 healthcare utilization
    70 high activity
    71 higher annual costs
    72 higher direct healthcare costs
    73 impact
    74 important risk factor
    75 inactivity
    76 individuals
    77 intensity
    78 larger study
    79 light intensity
    80 longitudinal design
    81 low activity
    82 magnitude
    83 mean minutes
    84 mediators
    85 minutes
    86 model
    87 moderate activity
    88 moderate-vigorous PA
    89 participants
    90 physical activity
    91 physical activity data
    92 population
    93 population-based study
    94 quartile
    95 questions
    96 regression
    97 regression models
    98 results
    99 risk factors
    100 robustness
    101 self-reported PA
    102 self-reported healthcare utilization
    103 self-reported physical activity
    104 self-reported physical activity data
    105 sex
    106 significance
    107 socio-demographic variables
    108 southern Germany
    109 sports
    110 study
    111 subsample
    112 summer
    113 utilization
    114 variables
    115 winter
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