This individual's Sleep Start Time is generally highest after a daily total of 270 grams of Carbs intake over the previous 7 days.
Join This Study
Go To Interactive Study
Blue represents the sum of Carbs intake over the previous 7 days
An increase in 7 days cumulative Carbs intake is usually followed by an decrease in Sleep Start Time. (R = -0.073)
Typical values for Sleep Start Time following a given amount of Carbs intake over the previous 7 days.
Typical Carbs intake seen over the previous 7 days preceding the given Sleep Start Time value.
This chart shows how your Carbs changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Carbs on each day of the week.
This chart shows the typical value recorded for Carbs for each month of the year.
This chart shows how your Sleep Start Time changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Sleep Start Time on each day of the week.
This chart shows the typical value recorded for Sleep Start Time for each month of the year.

Abstract

This individual's Sleep Start Time is generally 0.43% higher than normal after a total of 267 grams Carbs intake over the previous 7 days. This individual's data suggests with a medium degree of confidence (p=0.068867898694416, 95% CI -0.135 to -0.011) that Carbs has a very weakly negative predictive relationship (R=-0.07) with Sleep Start Time. The highest quartile of Sleep Start Time measurements were observed following an average 312.75 grams Carbs per day. The lowest quartile of Sleep Start Time measurements were observed following an average 298.29465666652 g Carbs per day.Sleep Start Time is generally 0.15% lower than normal after a total of 298.29465666652 grams of Carbs intake over the previous 7 days. Sleep Start Time is generally 0.43% higher after a total of 312.75 grams of Carbs intake over the previous 7 days.

Objective

The objective of this study is to determine the nature of the relationship (if any) between Carbs and Sleep Start Time. Additionally, we attempt to determine the Carbs values most likely to produce optimal Sleep Start Time values.

Participant Instructions

Record your Carbs daily in the reminder inbox or using the interactive web or mobile notifications.
Get Fitbit here and use it to record your Sleep Start Time. Once you have a Fitbit account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.

Design

This study is based on data donated by one participant. Thus, the study design is consistent with an n=1 observational natural experiment.

Data Analysis

Carbs Pre-Processing
Carbs measurement values below 1 grams were assumed erroneous and removed. No maximum allowed measurement value was defined for Carbs. No missing data filling value was defined for Carbs so any gaps in data were just not analyzed instead of assuming zero values for those times.
Carbs Analysis Settings

Sleep Start Time Pre-Processing
Sleep Start Time measurement values below 60 minutes were assumed erroneous and removed. Sleep Start Time measurement values above 7 days were assumed erroneous and removed. No missing data filling value was defined for Sleep Start Time so any gaps in data were just not analyzed instead of assuming zero values for those times.
Sleep Start Time Analysis Settings

Predictive Analytics
It was assumed that 0 hours would pass before a change in Carbs would produce an observable change in Sleep Start Time. It was assumed that Carbs could produce an observable change in Sleep Start Time for as much as 7 days after the stimulus event.
Predictive Analysis Settings

Data Quantity
1685 raw Carbs measurements with 524 changes spanning 2109 days from 2013-01-12 to 2018-10-22 were used in this analysis. 1957 raw Sleep Start Time measurements with 1172 changes spanning 1956 days from 2013-11-26 to 2019-04-05 were used in this analysis.

Data Sources

Carbs data was primarily collected using QuantiModo. QuantiModo allows you to easily track mood, symptoms, or any outcome you want to optimize in a fraction of a second. You can also import your data from over 30 other apps and devices. QuantiModo then analyzes your data to identify which hidden factors are most likely to be influencing your mood or symptoms.

Sleep Start Time data was primarily collected using Fitbit. Fitbit makes activity tracking easy and automatic.

Limitations

As with any human experiment, it was impossible to control for all potentially confounding variables. Correlation does not necessarily imply causation. We can never know for sure if one factor is definitely the cause of an outcome. However, lack of correlation definitely implies the lack of a causal relationship. Hence, we can with great confidence rule out non-existent relationships. For instance, if we discover no relationship between mood and an antidepressant this information is just as or even more valuable than the discovery that there is a relationship.
We can also take advantage of several characteristics of time series data from many subjects to infer the likelihood of a causal relationship if we do find a correlational relationship. The criteria for causation are a group of minimal conditions necessary to provide adequate evidence of a causal relationship between an incidence and a possible consequence.

The list of the criteria is as follows:
Strength (A.K.A. Effect Size)
A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal. There is a very weakly negative relationship between Carbs intake and Sleep Start Time

Consistency (A.K.A. Reproducibility)
Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect. Furthermore, in accordance with the law of large numbers (LLN), the predictive power and accuracy of these results will continually grow over time. 485 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Carbs intake values, the observed strength of the relationship will decline until it is below the threshold of significance. To it another way, in the case that we do find a spurious correlation, suggesting that banana intake improves mood for instance, one will likely increase their banana intake. Due to the fact that this correlation is spurious, it is unlikely that you will see a continued and persistent corresponding increase in mood. So over time, the spurious correlation will naturally dissipate.

Specificity
Causation is likely if a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship.

Temporality
The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay). The confidence in a causal relationship is bolstered by the fact that time-precedence was taken into account in all calculations.

Biological Gradient
Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.

Plausibility
A plausible bio-chemical mechanism between cause and effect is critical. This is where human brains excel. Based on our responses so far, 1 humans feel that there is a plausible mechanism of action and 0 feel that any relationship observed between Carbs intake and Sleep Start Time is coincidental.

Coherence
Coherence between epidemiological and laboratory findings increases the likelihood of an effect. It will be very enlightening to aggregate this data with the data from other participants with similar genetic, diseasomic, environmentomic, and demographic profiles.

Experiment
All of human life can be considered a natural experiment. Occasionally, it is possible to appeal to experimental evidence.

Analogy
The effect of similar factors may be considered.

Potential Issues Identified During Analysis
The average of effect values expected to be lower than average (12.025538707103) are actually higher than the average (12.00706921944). This suggests a weak relationship or insufficient data.
The average of effect values expected to be higher than average (11.955005624297) are actually lower than the average (12.00706921944). This suggests a weak relationship or insufficient data.
The low effect change is greater than the high effect change.

Relationship Statistics

Property Value
Cause Variable Name Carbs intake
Effect Variable Name Sleep Start Time
Sinn Predictive Coefficient 0.1231
Confidence Level medium
Confidence Interval 0.061939539642125
Forward Pearson Correlation Coefficient -0.073
Critical T Value 1.646
Total Carbs intake Over Previous 7 days Before ABOVE Average Sleep Start Time 312.75 grams
Total Carbs intake Over Previous 7 days Before BELOW Average Sleep Start Time 298.295 grams
Duration of Action 7 days
Effect Size very weakly negative
Number of Paired Measurements 485
Optimal Pearson Product -0.0068424403133381
P Value 0.068867898694416
Statistical Significance 0.99998576705788
Strength of Relationship 0.061939539642125
Study Type individual
Analysis Performed At 2019-06-24

Carbs Statistics

Property Value
Variable Name Carbs
Aggregation Method SUM
Analysis Performed At 2019-04-06
Duration of Action 7 days
Kurtosis 7.1411124449315
Mean 298.78 grams
Median 265.5 grams
Minimum Allowed Value 1 grams
Number of Changes 524
Number of Correlations 256
Number of Measurements 1685
Onset Delay 0 seconds
Standard Deviation 160.36096264167
Unit Grams
UPC 817047020287
Variable ID 1285
Variance 25715.638339363

Sleep Start Time Statistics

Property Value
Variable Name Sleep Start Time
Aggregation Method MEAN
Analysis Performed At 2019-06-22
Duration of Action 24 hours
Kurtosis 7.2090714169912
Maximum Allowed Value 7 days
Mean 12 hours
Median 12 hours
Minimum Allowed Value 60 minutes
Number of Changes 1172
Number of Correlations 3170
Number of Measurements 1957
Onset Delay 0 seconds
Standard Deviation 1.7421945503096
Unit Hours
Variable ID 5211821
Variance 3.0352418511285

Tracking Carbs

Record your Carbs daily in the reminder inbox or using the interactive web or mobile notifications.

Tracking Sleep Start Time

Get Fitbit here and use it to record your Sleep Start Time. Once you have a Fitbit account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.
Join This Study

https://lh6.googleusercontent.com/-BHr4hyUWqZU/AAAAAAAAAAI/AAAAAAAIG28/2Lv0en738II/photo.jpg Principal Investigator - Mike Sinn