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This individual's Sleep Quality is generally highest after a daily total of 0 milligrams of Sodium intake over the previous 7 days.
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Blue represents the sum of Sodium intake over the previous 7 days
An increase in 7 days cumulative Sodium intake is usually followed by an decrease in Sleep Quality. (R = -0.096)
Typical values for Sleep Quality following a given amount of Sodium intake over the previous 7 days.
Typical Sodium intake seen over the previous 7 days preceding the given Sleep Quality value.
This chart shows how your Sodium changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Sodium on each day of the week.
This chart shows the typical value recorded for Sodium for each month of the year.
This chart shows how your Sleep Quality changes over time.
Each column represents the number of days this value occurred.
This chart shows the typical value recorded for Sleep Quality on each day of the week.
This chart shows the typical value recorded for Sleep Quality for each month of the year.

Abstract

This individual's Sleep Quality is generally 2% higher than normal after a total of 0 milligrams Sodium intake over the previous 7 days. This individual's data suggests with a medium degree of confidence (p=0.1741135594896, 95% CI -0.259 to 0.067) that Sodium has a very weakly negative predictive relationship (R=-0.1) with Sleep Quality. The highest quartile of Sleep Quality measurements were observed following an average 16 milligrams Sodium per day. The lowest quartile of Sleep Quality measurements were observed following an average 20676.483353182 mg Sodium per day.Sleep Quality is generally 2% lower than normal after a total of 20676.483353182 milligrams of Sodium intake over the previous 7 days. Sleep Quality is generally 2% higher after a total of 16 milligrams of Sodium intake over the previous 7 days.

Objective

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

Participant Instructions

Record your Sodium daily in the reminder inbox or using the interactive web or mobile notifications.
Get Sleep as Android here and use it to record your Sleep Quality. Once you have a Sleep as Android 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

Sodium Pre-Processing
Sodium measurement values below 0 milligrams were assumed erroneous and removed. No maximum allowed measurement value was defined for Sodium. It was assumed that any gaps in Sodium data were unrecorded 0 milligrams measurement values.
Sodium Analysis Settings

Sleep Quality Pre-Processing
Sleep Quality measurement values below 1 out of 5 were assumed erroneous and removed. Sleep Quality measurement values above 5 out of 5 were assumed erroneous and removed. No missing data filling value was defined for Sleep Quality so any gaps in data were just not analyzed instead of assuming zero values for those times.
Sleep Quality Analysis Settings

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

Data Quantity
1775 raw Sodium measurements with 576 changes spanning 2085 days from 2013-01-12 to 2018-09-28 were used in this analysis. 635 raw Sleep Quality measurements with 312 changes spanning 2520 days from 2012-05-06 to 2019-04-01 were used in this analysis.

Data Sources

Sodium 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 Quality data was primarily collected using Sleep as Android. Smart alarm clock with sleep cycle tracking. Wakes you gently in optimal moment for pleasant mornings.

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 Sodium intake and Sleep Quality

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. 285 paired data points were used in this analysis. Assuming that the relationship is merely coincidental, as the participant independently modifies their Sodium 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 Sodium intake and Sleep Quality 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.

Relationship Statistics

Property Value
Cause Variable Name Sodium intake
Effect Variable Name Sleep Quality
Sinn Predictive Coefficient 0.1263
Confidence Level medium
Confidence Interval 0.16307618935678
Forward Pearson Correlation Coefficient -0.096
Critical T Value 1.646
Total Sodium intake Over Previous 7 days Before ABOVE Average Sleep Quality 16 milligrams
Total Sodium intake Over Previous 7 days Before BELOW Average Sleep Quality 20 milligrams
Duration of Action 7 days
Effect Size very weakly negative
Number of Paired Measurements 285
Optimal Pearson Product 0.025662290954249
P Value 0.1741135594896
Statistical Significance 0.9994
Strength of Relationship 0.16307618935678
Study Type individual
Analysis Performed At 2019-04-04

Sodium Statistics

Property Value
Variable Name Sodium
Aggregation Method SUM
Analysis Performed At 2019-01-25
Duration of Action 7 days
Kurtosis 15.609671520523
Mean 824.2 milligrams
Median 0 milligrams
Minimum Allowed Value 0 milligrams
Number of Changes 576
Number of Correlations 352
Number of Measurements 1775
Onset Delay 0 seconds
Standard Deviation 1849.75773078
Unit Milligrams
Variable ID 1449
Variance 3421603.6625805

Sleep Quality Statistics

Property Value
Variable Name Sleep Quality
Aggregation Method MEAN
Analysis Performed At 2019-04-01
Duration of Action 7 days
Kurtosis 2.7819199718877
Maximum Allowed Value 5 out of 5
Mean 3.3303 out of 5
Median 3.2325582504272 out of 5
Minimum Allowed Value 1 out of 5
Number of Changes 312
Number of Correlations 924
Number of Measurements 635
Onset Delay 0 seconds
Standard Deviation 0.83531375879634
Unit 1 to 5 Rating
UPC 754185214911
Variable ID 1448
Variance 0.69774907563447

Tracking Sodium

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

Tracking Sleep Quality

Get Sleep as Android here and use it to record your Sleep Quality. Once you have a Sleep as Android account, you can import your data from the Import Data page. This individual's data will automatically be imported and analyzed.
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https://lh6.googleusercontent.com/-BHr4hyUWqZU/AAAAAAAAAAI/AAAAAAAIG28/2Lv0en738II/photo.jpg Principal Investigator - Mike Sinn