Publications

Quantifying the impact of influenza among persons with type 2 diabetes mellitus: A new approach to determine medical and physical activity impact

BACKGROUND: We describe the impact of influenza on medical outcomes and daily activities among people with and without type 2 diabetes mellitus (T2DM).

METHODS: Retrospective cohort analysis of a US health plan offering a digital wellness platform connecting wearable devices capable of tracking steps, sleep, and heart rate. For the 2016 to 2017 influenza season, we compared adults with T2DM to age and gender matched controls. Medical claims were used to define cohorts and identify influenza events and outcomes. Digital tracking data were aggregated at time slices of minute-, day-, week-, and year-level. A pre-post study design compared the peri-influenza period (two weeks before and four weeks after influenza diagnosis) to the six-week preceding period (baseline).

RESULTS: A total of 54 656 T2DM and 113 016 non-DM controls were used for the study. People with T2DM had more influenza claims, vaccinations, and influenza antivirals per 100 people (1.96% vs 1.37%, 34.3% vs 24.3%, and 27.1 vs 22 respectively, P < .001). A total of 1086 persons with T2DM and 1567 controls had an influenza claim (47.4% male, median age 54, 6.4% vs 7.8% trackers, respectively). Glycemic events, pneumonia, and ischemic heart disease increased over baseline during the peri-influenza period for T2DM (1.74-, 7.4-, and 1.6-fold increase respectively, P < .01). In a device wearing subcohort, we observed 10 000 fewer steps surrounding the influenza event, with the lowest (5500 steps) two days postinfluenza. Average heart rate increased significantly (+5.5 beats per minute) one day prior to influenza.

CONCLUSION: Influenza increases rates of pneumonia, heart disease, and abnormal glucose levels among people with T2DM, and negatively impacts daily activities compared to controls.

Selection strategy of patients with dense step tracking data from wearable activity devices in the surrounding 14 days of documented influenza infection.


Selection strategy of patients with dense step tracking data from wearable activity devices in the surrounding 14 days of documented influenza infection.

Impact of influenza infection on steps taken in 14 days before and after influenza diagnosis. Step activity is aggregated per day for people with diabetes (N = 67) and controls (N = 243) in two weeks before and after influenza diagnosis.


Impact of influenza infection on steps taken in 14 days before and after influenza diagnosis. Step activity is aggregated per day for people with diabetes (N = 67) and controls (N = 243) in two weeks before and after influenza diagnosis.

Impact of influenza infection on sleep patterns in 14 days before or after influenza diagnosis.


Impact of influenza infection on sleep patterns in 14 days before or after influenza diagnosis.

‍Impact of influenza vaccine on daily steps taken, sleep duration, and average daily heart rate in 14 days before and after vaccination. Aggregated time series are smoothed to reduce noise. Effect size may be underestimated. Timing of effects may be considered accurate within a 5-day tolerance.


Impact of influenza vaccine on daily steps taken, sleep duration, and average daily heart rate in 14 days before and after vaccination. Aggregated time series are smoothed to reduce noise. Effect size may be underestimated. Timing of effects may be considered accurate within a 5-day tolerance.

Read the full publication here.

Have questions?

CONTACT US
Publications

Quantifying the impact of influenza among persons with type 2 diabetes mellitus: A new approach to determine medical and physical activity impact

BACKGROUND: We describe the impact of influenza on medical outcomes and daily activities among people with and without type 2 diabetes mellitus (T2DM).

METHODS: Retrospective cohort analysis of a US health plan offering a digital wellness platform connecting wearable devices capable of tracking steps, sleep, and heart rate. For the 2016 to 2017 influenza season, we compared adults with T2DM to age and gender matched controls. Medical claims were used to define cohorts and identify influenza events and outcomes. Digital tracking data were aggregated at time slices of minute-, day-, week-, and year-level. A pre-post study design compared the peri-influenza period (two weeks before and four weeks after influenza diagnosis) to the six-week preceding period (baseline).

RESULTS: A total of 54 656 T2DM and 113 016 non-DM controls were used for the study. People with T2DM had more influenza claims, vaccinations, and influenza antivirals per 100 people (1.96% vs 1.37%, 34.3% vs 24.3%, and 27.1 vs 22 respectively, P < .001). A total of 1086 persons with T2DM and 1567 controls had an influenza claim (47.4% male, median age 54, 6.4% vs 7.8% trackers, respectively). Glycemic events, pneumonia, and ischemic heart disease increased over baseline during the peri-influenza period for T2DM (1.74-, 7.4-, and 1.6-fold increase respectively, P < .01). In a device wearing subcohort, we observed 10 000 fewer steps surrounding the influenza event, with the lowest (5500 steps) two days postinfluenza. Average heart rate increased significantly (+5.5 beats per minute) one day prior to influenza.

CONCLUSION: Influenza increases rates of pneumonia, heart disease, and abnormal glucose levels among people with T2DM, and negatively impacts daily activities compared to controls.

Selection strategy of patients with dense step tracking data from wearable activity devices in the surrounding 14 days of documented influenza infection.


Selection strategy of patients with dense step tracking data from wearable activity devices in the surrounding 14 days of documented influenza infection.

Impact of influenza infection on steps taken in 14 days before and after influenza diagnosis. Step activity is aggregated per day for people with diabetes (N = 67) and controls (N = 243) in two weeks before and after influenza diagnosis.


Impact of influenza infection on steps taken in 14 days before and after influenza diagnosis. Step activity is aggregated per day for people with diabetes (N = 67) and controls (N = 243) in two weeks before and after influenza diagnosis.

Impact of influenza infection on sleep patterns in 14 days before or after influenza diagnosis.


Impact of influenza infection on sleep patterns in 14 days before or after influenza diagnosis.

‍Impact of influenza vaccine on daily steps taken, sleep duration, and average daily heart rate in 14 days before and after vaccination. Aggregated time series are smoothed to reduce noise. Effect size may be underestimated. Timing of effects may be considered accurate within a 5-day tolerance.


Impact of influenza vaccine on daily steps taken, sleep duration, and average daily heart rate in 14 days before and after vaccination. Aggregated time series are smoothed to reduce noise. Effect size may be underestimated. Timing of effects may be considered accurate within a 5-day tolerance.

Read the full publication here.

Have questions?

CONTACT US
Publications

Quantifying the impact of influenza among persons with type 2 diabetes mellitus: A new approach to determine medical and physical activity impact

Samson SI, Konty K, Lee WN, Quisel T, Foschini L, Kerr D, Liska J, Mills H, Hollingsworth R, Greenberg M, Beal AC

BACKGROUND: We describe the impact of influenza on medical outcomes and daily activities among people with and without type 2 diabetes mellitus (T2DM).

METHODS: Retrospective cohort analysis of a US health plan offering a digital wellness platform connecting wearable devices capable of tracking steps, sleep, and heart rate. For the 2016 to 2017 influenza season, we compared adults with T2DM to age and gender matched controls. Medical claims were used to define cohorts and identify influenza events and outcomes. Digital tracking data were aggregated at time slices of minute-, day-, week-, and year-level. A pre-post study design compared the peri-influenza period (two weeks before and four weeks after influenza diagnosis) to the six-week preceding period (baseline).

RESULTS: A total of 54 656 T2DM and 113 016 non-DM controls were used for the study. People with T2DM had more influenza claims, vaccinations, and influenza antivirals per 100 people (1.96% vs 1.37%, 34.3% vs 24.3%, and 27.1 vs 22 respectively, P < .001). A total of 1086 persons with T2DM and 1567 controls had an influenza claim (47.4% male, median age 54, 6.4% vs 7.8% trackers, respectively). Glycemic events, pneumonia, and ischemic heart disease increased over baseline during the peri-influenza period for T2DM (1.74-, 7.4-, and 1.6-fold increase respectively, P < .01). In a device wearing subcohort, we observed 10 000 fewer steps surrounding the influenza event, with the lowest (5500 steps) two days postinfluenza. Average heart rate increased significantly (+5.5 beats per minute) one day prior to influenza.

CONCLUSION: Influenza increases rates of pneumonia, heart disease, and abnormal glucose levels among people with T2DM, and negatively impacts daily activities compared to controls.

Selection strategy of patients with dense step tracking data from wearable activity devices in the surrounding 14 days of documented influenza infection.


Selection strategy of patients with dense step tracking data from wearable activity devices in the surrounding 14 days of documented influenza infection.

Impact of influenza infection on steps taken in 14 days before and after influenza diagnosis. Step activity is aggregated per day for people with diabetes (N = 67) and controls (N = 243) in two weeks before and after influenza diagnosis.


Impact of influenza infection on steps taken in 14 days before and after influenza diagnosis. Step activity is aggregated per day for people with diabetes (N = 67) and controls (N = 243) in two weeks before and after influenza diagnosis.

Impact of influenza infection on sleep patterns in 14 days before or after influenza diagnosis.


Impact of influenza infection on sleep patterns in 14 days before or after influenza diagnosis.

‍Impact of influenza vaccine on daily steps taken, sleep duration, and average daily heart rate in 14 days before and after vaccination. Aggregated time series are smoothed to reduce noise. Effect size may be underestimated. Timing of effects may be considered accurate within a 5-day tolerance.


Impact of influenza vaccine on daily steps taken, sleep duration, and average daily heart rate in 14 days before and after vaccination. Aggregated time series are smoothed to reduce noise. Effect size may be underestimated. Timing of effects may be considered accurate within a 5-day tolerance.

Read the full publication here.

Have questions?

CONTACT US
Publications

Quantifying the impact of influenza among persons with type 2 diabetes mellitus: A new approach to determine medical and physical activity impact

Publications

Quantifying the impact of influenza among persons with type 2 diabetes mellitus: A new approach to determine medical and physical activity impact

BACKGROUND: We describe the impact of influenza on medical outcomes and daily activities among people with and without type 2 diabetes mellitus (T2DM).

METHODS: Retrospective cohort analysis of a US health plan offering a digital wellness platform connecting wearable devices capable of tracking steps, sleep, and heart rate. For the 2016 to 2017 influenza season, we compared adults with T2DM to age and gender matched controls. Medical claims were used to define cohorts and identify influenza events and outcomes. Digital tracking data were aggregated at time slices of minute-, day-, week-, and year-level. A pre-post study design compared the peri-influenza period (two weeks before and four weeks after influenza diagnosis) to the six-week preceding period (baseline).

RESULTS: A total of 54 656 T2DM and 113 016 non-DM controls were used for the study. People with T2DM had more influenza claims, vaccinations, and influenza antivirals per 100 people (1.96% vs 1.37%, 34.3% vs 24.3%, and 27.1 vs 22 respectively, P < .001). A total of 1086 persons with T2DM and 1567 controls had an influenza claim (47.4% male, median age 54, 6.4% vs 7.8% trackers, respectively). Glycemic events, pneumonia, and ischemic heart disease increased over baseline during the peri-influenza period for T2DM (1.74-, 7.4-, and 1.6-fold increase respectively, P < .01). In a device wearing subcohort, we observed 10 000 fewer steps surrounding the influenza event, with the lowest (5500 steps) two days postinfluenza. Average heart rate increased significantly (+5.5 beats per minute) one day prior to influenza.

CONCLUSION: Influenza increases rates of pneumonia, heart disease, and abnormal glucose levels among people with T2DM, and negatively impacts daily activities compared to controls.

Selection strategy of patients with dense step tracking data from wearable activity devices in the surrounding 14 days of documented influenza infection.


Selection strategy of patients with dense step tracking data from wearable activity devices in the surrounding 14 days of documented influenza infection.

Impact of influenza infection on steps taken in 14 days before and after influenza diagnosis. Step activity is aggregated per day for people with diabetes (N = 67) and controls (N = 243) in two weeks before and after influenza diagnosis.


Impact of influenza infection on steps taken in 14 days before and after influenza diagnosis. Step activity is aggregated per day for people with diabetes (N = 67) and controls (N = 243) in two weeks before and after influenza diagnosis.

Impact of influenza infection on sleep patterns in 14 days before or after influenza diagnosis.


Impact of influenza infection on sleep patterns in 14 days before or after influenza diagnosis.

‍Impact of influenza vaccine on daily steps taken, sleep duration, and average daily heart rate in 14 days before and after vaccination. Aggregated time series are smoothed to reduce noise. Effect size may be underestimated. Timing of effects may be considered accurate within a 5-day tolerance.


Impact of influenza vaccine on daily steps taken, sleep duration, and average daily heart rate in 14 days before and after vaccination. Aggregated time series are smoothed to reduce noise. Effect size may be underestimated. Timing of effects may be considered accurate within a 5-day tolerance.

Read the full publication here.

Have questions?

CONTACT US

Quantifying the impact of influenza among persons with type 2 diabetes mellitus: A new approach to determine medical and physical activity impact

November 21, 2019
Publications

Quantifying the impact of influenza among persons with type 2 diabetes mellitus: A new approach to determine medical and physical activity impact

November 21, 2019
Publications

Quantifying the impact of influenza among persons with type 2 diabetes mellitus: A new approach to determine medical and physical activity impact

Samson SI, Konty K, Lee WN, Quisel T, Foschini L, Kerr D, Liska J, Mills H, Hollingsworth R, Greenberg M, Beal AC

November 21, 2019
Publications

Quantifying the impact of influenza among persons with type 2 diabetes mellitus: A new approach to determine medical and physical activity impact

November 21, 2019
Publications
Eve: Evidation's brand mark which is a yellow glowing orb

BACKGROUND: We describe the impact of influenza on medical outcomes and daily activities among people with and without type 2 diabetes mellitus (T2DM).

METHODS: Retrospective cohort analysis of a US health plan offering a digital wellness platform connecting wearable devices capable of tracking steps, sleep, and heart rate. For the 2016 to 2017 influenza season, we compared adults with T2DM to age and gender matched controls. Medical claims were used to define cohorts and identify influenza events and outcomes. Digital tracking data were aggregated at time slices of minute-, day-, week-, and year-level. A pre-post study design compared the peri-influenza period (two weeks before and four weeks after influenza diagnosis) to the six-week preceding period (baseline).

RESULTS: A total of 54 656 T2DM and 113 016 non-DM controls were used for the study. People with T2DM had more influenza claims, vaccinations, and influenza antivirals per 100 people (1.96% vs 1.37%, 34.3% vs 24.3%, and 27.1 vs 22 respectively, P < .001). A total of 1086 persons with T2DM and 1567 controls had an influenza claim (47.4% male, median age 54, 6.4% vs 7.8% trackers, respectively). Glycemic events, pneumonia, and ischemic heart disease increased over baseline during the peri-influenza period for T2DM (1.74-, 7.4-, and 1.6-fold increase respectively, P < .01). In a device wearing subcohort, we observed 10 000 fewer steps surrounding the influenza event, with the lowest (5500 steps) two days postinfluenza. Average heart rate increased significantly (+5.5 beats per minute) one day prior to influenza.

CONCLUSION: Influenza increases rates of pneumonia, heart disease, and abnormal glucose levels among people with T2DM, and negatively impacts daily activities compared to controls.

Selection strategy of patients with dense step tracking data from wearable activity devices in the surrounding 14 days of documented influenza infection.


Selection strategy of patients with dense step tracking data from wearable activity devices in the surrounding 14 days of documented influenza infection.

Impact of influenza infection on steps taken in 14 days before and after influenza diagnosis. Step activity is aggregated per day for people with diabetes (N = 67) and controls (N = 243) in two weeks before and after influenza diagnosis.


Impact of influenza infection on steps taken in 14 days before and after influenza diagnosis. Step activity is aggregated per day for people with diabetes (N = 67) and controls (N = 243) in two weeks before and after influenza diagnosis.

Impact of influenza infection on sleep patterns in 14 days before or after influenza diagnosis.


Impact of influenza infection on sleep patterns in 14 days before or after influenza diagnosis.

‍Impact of influenza vaccine on daily steps taken, sleep duration, and average daily heart rate in 14 days before and after vaccination. Aggregated time series are smoothed to reduce noise. Effect size may be underestimated. Timing of effects may be considered accurate within a 5-day tolerance.


Impact of influenza vaccine on daily steps taken, sleep duration, and average daily heart rate in 14 days before and after vaccination. Aggregated time series are smoothed to reduce noise. Effect size may be underestimated. Timing of effects may be considered accurate within a 5-day tolerance.

Read the full publication here.

Download app