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Measuring the impact of apnea and obesity on circadian activity patterns using functional linear modeling of actigraphy data Cover

Measuring the impact of apnea and obesity on circadian activity patterns using functional linear modeling of actigraphy data

Open Access
|Oct 2011

Figures & Tables

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Figure 1

Data flow for one subject. Plot (a) shows weekdays ordered Monday through Friday from top to bottom, with the time of day indicated on the X and the height of the spike indicating the raw activity level on the Y axis. The plot (b) shows the activity averaged at each minute over the 5 days (black points) and the Fourier expansion representing this patient's circadian activity pattern (red solid line).

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Figure 2

Smoothed activity of 8 subjects fitted by Fourier expansion and shown in separate plots with time recorded on the X axis, and activity level on the Y axis. The top 4 plots show the high apnea subjects and the bottom 4 plots show the low apnea subjects.

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Figure 3

FLM result for 8 subjects. Plot (a) shows the 8 individual circadian activity patterns with blue and red line for high and low apnea groups, respectively. The overall mean circadian activity pattern is the solid black line and the mean circadian activity patterns for the high and low apnea groups are thick blue and red line, respectively. Plot (b) shows F-test result the red solid curve represents the observed statistic F(t) at each time point, the blue dashed and dotted lines correspond to a global and point-wise test of significance at significant level α = 0.05, respectively.

Table 1

Demographic information and sample characteristics

VariableN (%) Mean ± std
(N Total 395)
Female 196(49.87%)
Race African-American134 (35.08%)
Caucasian237 (62.04%)
Presenting Symptoms Snoring279 (70.63%)
Gasping93 (23.54%)
Morning headache67 (16.96%)
RLS symptoms26 (6.58%)
PLMS3 (0.76%)
Witnessed apneas146 (36.96%)
Insomnia42 (10.63%)
Excessive day sleepiness91 (23.04%)
Nonrestorative sleep9 (2.28%)
Mallampati score Class 4145 (41.55%)
Class 3136 (38.97%)
Class 253 (15.19%)
Class 115 (4.30%)
Diagnosis Result OSA292 (73.92%)
RLS5 (1.27%)
Insomnia8 (2.03%)
Hypersomnia20 (5.06%)
BMI > 30 241 (60.86%)
BMI 34.66 ± 8.88
(Median = 34)
Age(years) 47.9 ± 14.8
apnea 22.11 ± 28.11
(Median = 12.95)
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Figure 4

Smoothed Activity for individuals as black solid curves and overall mean as red curves.

Table 2

Three Functional Linear Models

Model 1apnea Main Effect OnlyActivityk(t) = β0(t) + βAHI(t) × AHIk + εk(t)
Model 2BMI Main Effect OnlyActivityk(t) = β0(t) + βBMI(t) × BMIk + εk(t)
Model 3apnea+BMI+interactionActivityk(t) = β0(t) + βAHI(t) × AHIk + βBMI(t) × BMIk +βAHI × BMI (t) × AHIk × BMIk + εk(t)
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Figure 5

FLM result for apnea main effect model. Plot (a) is estimated activity patterns for two apnea groups and 95% confidence band. Plot (b) is F-test result for this model.

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Figure 6

FLM result for BMI main effect model. Plot (a) is estimated activity patterns for two BMI groups and 95% confidence band. Plot (b) is F-test result for this model.

Table 3

Sample size for apnea, BMI mode

apnea Low
(< 10.75)
apnea High
(> = 10.75)
Total
BMI > = 30 6194155
BMI < 30 552277
Total 116116232
Table 4

Four group circadian activity result

apneaBMIGroup Mean
LowLow
LowHigh
HighLow
HighHigh
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Figure 7

FLM result for apnea and BMI model. Plot (a) is estimated activity patterns for the four groups and 95% confidence band. Plot (b) is F-test result for this model.

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Figure 8

FLM result for BMI model treating BMI as continuous. Plot (a) is estimated activity patters for BMI groups. Plot (b) is F-test result for this model.

Language: English
Published on: Oct 13, 2011
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2011 Jia Wang, Hong Xian, Amy Licis, Elena Deych, Jimin Ding, Jennifer McLeland, Cristina Toedebusch, Tao Li, Stephen Duntley, William Shannon, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.