Modeling the Relationship Between Sleep and Pediatric

Obesity

Andrew AlthouseCarnegie Mellon University, Department of Statistics

Southern Society of Clinical Investigation MeetingsAdolescent Medicine and Pediatrics

Friday, February 23, 2008

Speaker: Andrew Althouse

Andrew Althouse has documented that he has nothing to disclose.

DISCLOSURE STATEMENTDISCLOSURE STATEMENT

Rising Prevalence of Obesity

An NHANES survey conducted in 1980 found 15.0% of adults to be obese.

By 2004, that percentage had increased to 32.9%.

NHANES surveys found that obesity is also becoming more prevalent in children.

Two age groups were studied; each group had a marked increase in the percentage of children that were obese. 1980, age 6-11 2004, age 6-11 1980, age 12-19 2004, age 12-19

1980 vs. 2004 Obesity Prevalence

% O

bese

05

1015

2025

3035

1980 Adult Obesity Rate

2004 Adult Obesity Rate

Challenges of Evaluating Pediatric Obesity

Definitions of “Obesity” Adults: having a Body Mass

Index greater than 30 kg/m2. Children: more difficult

because of growth curve; cannot choose one number as a “cut-off” for obesity

One method defines a child as “obese” if their BMI is above the 95th percentile for their age and gender. 95th percentile today is higher

than the 95th percentile in 1980.

This standard would always suggest that 5% of children were obese; but there are more children with weight problems today than in 1980.

http://www.health.gov/dietaryguidelines/dga2005/document/images/ch3fig3.jpg

Sleep and Obesity: A Connection? Adult Obesity may be connected to

poor sleep habits. Short Sleep --> Increased BMI

Buscemi, Kumar, Nugent, et al. JCSM 2007; 3, 7, 681-688

Gangswich, et al. Sleep 2005; 28: 1289-96.

Singh, et al. JCSM 2005; 1: 357-63

Current research modeling this relationship in childrenNixon, et al. Sleep 2008; 31(1); 71-8.Hasler, et al. Sleep 2004; 27(4): 661-6.Locard, et al. Int J Obes Relat Metab Disord 1992; 16(10): 721-9.

Obese children may be more likely to become obese adults

If we can decrease the prevalence of obesity in children we may be able to decrease the prevalence of obesity in adults

Taheri, S Arch Dis Child 2006;91:881-884

Study Design

Convenience sample of 77 subjects Pediatrician referrals to a dietitian at Texas Tech University

Health Sciences Center (Lubbock, TX) Data collected from January 2006 until March 2007. Subjects completed standard sleep questionnaires

Pediatric Sleep Questionnaire 1: Sleep Habits Pediatric Sleep Questionnaire 2: Behavioral Problems Pediatric Daytime Sleepiness Scale Supplemental questions about daily habits with respect to:

• sleep routine• physical activity• use of electronic media

We chose to focus primarily on the variables related tosleep duration, quality of sleep, and consistency of sleep.

Distribution of Subjects' Age

Age (Years)

Fre

qu

en

cy

0 5 10 15 20

05

10

15

20

4 6 8 10 12 14 16

20

25

30

35

40

45

50

Scatterplot of Subjects' BMI vs. Age

Age (Years)

BM

I

Female Male

2025

3035

4045

50

Boxplot of BMI, Split by Gender

Gender

BM

I

Subject Characteristics

Age: Mean = 10.26 years, SD = 3.42Increasing trend in BMI with age

Gender: 61% Females, 39% MalesFemales: higher median, skewed dist.Males: median approx. 30

Variables of Interest

Our response variable in all models was Body Mass Index (kg/m2). Predictors that we considered:

Sleep Duration: recorded in hours (to the nearest quarter-hour) PSQ 1: high score indicates sleep problems PSQ 2: high score indicates behavioral problems PDSS: high score indicates child is tired during the day Naps: Yes or No Sleep in School: Yes or No Share Room: Yes or No Feel Upon Waking: Rested or Still Tired Sleep Time Difference: difference between weekday bed time and

weekend bed time (recorded in hours) We did not include the variables regarding physical activity or electronic

media use due to sparse data.

Histogram of Sleep Duration

Sleep Duration (Hours)

Fre

qu

en

cy

6 7 8 9 10 11 12 13

05

10

15

20

6 7 8 9 10 11 12

46

810

12

14

16

Scatterplot of Age vs. Sleep Duration

Sleep Duration (Hours)

Ag

e

6 7 8 9 10 11 12

20

25

30

35

40

45

50

Scatterplot of BMI vs. Sleep Duration

Sleep Duration (Hours)

BM

I

Sleep Duration

Mean = 9.08 hours

SD = 1.09

Negative correlation w/BMI:

Less Sleep = Higher BMI

Negative correlation w/Age:

Less Sleep = Higher Age

PSQ 1 Scores

PSQ 1 Score

Fre

qu

en

cy

0 2 4 6 8 10 12 14

05

10

15

0 2 4 6 8 10 12 14

20

25

30

35

40

45

50

Subjects' BMI vs. PSQ 1 Score

PSQ 1 Score

BM

I

PSQ 2 Scores

PSQ 2 Score

Fre

qu

en

cy

0 1 2 3 4 5 6

05

10

15

20

25

30

No Problems Behavior Problems

20

25

30

35

40

45

50

BMI by Presence of Behavior Problems

Behavior Problems

BM

I

PDSS Scores

PDSS Score

Fre

quen

cy

0 5 10 15 20 25

05

1015

5 10 15 20

2025

3035

4045

50

BMI vs. PDSS Score

PDSS Score

BM

I

Weekday/Weekend Bed Time Difference

Difference in Weekday/Weekend Bed Time

Fre

quen

cy

-1 0 1 2 3 4 5

05

1015

0 1 2 3 4

2025

3035

4045

50

BMI vs. Bed Time Difference

Difference in Weekday/Weekend Bed Time

BM

I

No Naps Naps

20

25

30

35

40

45

50

BMI by Naps

Naps

BM

I

Doesn't Fall Asleep Falls Asleep

20

25

30

35

40

45

50

BMI by Sleep in School

Sleep in School

BM

I

Doesn't Share Room Shares Room

20

25

30

35

40

45

50

BMI by Sharing Room

Share Room

BM

I

Still Tired Rested

20

25

30

35

40

45

50

BMI by Feel Upon Waking (Subjective)

Feel Upon Waking

BM

I

Adjusted Statistical Modeling

Variable Coefficient 90% Confidence Interval P-Value

Age 2.451 (0.156, 4.748) 0.08925

Gender : Male -2.061 (-4.770, 0.648) 0.22084

PSQ1 -0.161 (-0.725, 0.403) 0.64310

PSQ2 (Categorical) 0.443 (-5.084, 5.970) 0.89627

PDSS 0.301 (0.039, 0.563) 0.06853

Sleep Duration 1.822 (-0.905, 4.550) 0.28129

Bed Time Difference 0.972 (-0.142, 2.085) 0.16158

Feel Upon Waking : Rested -2.165 (-8.361, 4.031) 0.57057

Naps 4.278 (0.893, 7.663) 0.04602

Sleep in School 2.946 (0.060, 5.830) 0.10355

Share Room -4.622 (-7.180, -2.064) 0.00562

Age*Sleep Duration -0.228 (-0.481, 0.025) 0.14812

PSQ2(cat)*Feel Upon Waking 7.809 (1.282, 14.336) 0.05799

The Age Cutoff

Interaction between age and sleep duration creates a “cutoff” at age 8 where the effect of the variable sleep duration changes.

This equation summarizes the effects of Age and Sleep:2.451*(Age) + 1.822*(Sleep) – 0.228*(Age*Sleep)

Age Predicted BMI:

8 Hrs Sleep

Predicted BMI:

9 Hrs Sleep

Effect of 1-Hour Sleep Increase on Predicted BMI

5 17.71 18.89 0.68

8 19.95 19.95 0

11 21.47 20.79 -0.68

14 23.35 21.98 -1.37

Note the change in direction of the effect.Increased magnitude as children get farther from age 8.

Behavioral Problems & Their Implications

Strong interaction between the presence of behavioral problems (determined by PSQ 2) and “Feel Upon Waking.” No behavioral problems: “rested” children had a lower

expected BMI than “still tired” children. With behavioral problems: “rested” children had a higher

expected BMI than “still tired” children.

PSQ 2 Problem Feel Upon Waking Predicted Change in Expected BMI

No (0) Rested (1) -2.47

No (0) Still Tired (0) 0

Yes (1) Still Tired (0) 0.08

Yes (1) Rested (1) 5.25

Summary of Findings

Protective Effects: Sharing a Room Male Increased Sleep (if over age 8)

Increased Risk: Taking Naps Inconsistent Sleep Patterns Feeling Rested (with Behavioral Problems)

Future Work

Current study limitations Sparse data: physical activity and electronic media use Difficulty understanding supplemental questions

Ongoing: Redesign of questionnaires; pre-testing Analysis of parent-child reliability issues

Manuscript in progress Designing longitudinal study with sleep-

intervention arm

Acknowledgements

NSF VIGRE (grant #: DMS-0240019) Dr. Rebecca Nugent, Carnegie Mellon University, Statistics Dr. Kenneth Nugent, TTUHSC Internal Medicine Dr. Rishi Raj, TTUHSC Internal Medicine Dr. Rita Corona, TTUHSC Internal Medicine Dr. Yasir Yaqub, TTUHSC Internal Medicine Dr. WM Hall, TTUHSC Pediatrics