Higher Time Between Sunrise And Sunset Predicts Significantly Lower Migraine Headache Severity for Population

Higher Time Between Sunrise And Sunset Predicts Significantly Lower Migraine Headache Severity for Population

Contents

Variables

A
Time Between Sunrise and Sunset 362
A
Migraine Headache Severity 162

Categories

A
Environment 564
A
Symptoms 13336

Tags

Medium Confidence
Strong Effect Size
Negative Relationship
Population Study
cause image gauge image effect image
Participants reported a 32.4% average decrease in Migraine Headache Severity following above average Time Between Sunrise And Sunset.

Abstract

Migraine Headache Severity was generally 16.8% lower than average after 24 hours of Time Between Sunrise And Sunset per 7 days.

Aggregated data from 1 study participants suggests with a MEDIUM degree of confidence (p=0.0243, 95% CI -1.157 to -0.367) that Time Between Sunrise And Sunset has a strongly negative predictive relationship (R=-0.762) with Migraine Headache Severity.

The highest quartile of Migraine Headache Severity measurements were observed following an average 12 hours Time Between Sunrise And Sunset per day.

The lowest quartile of Migraine Headache Severity measurements were observed following an average 12 hours of Time Between Sunrise And Sunset per day.

After an onset delay of 0 seconds, Migraine Headache Severity is typically 12% lower than average over the 7 days following around 12 hours of Time Between Sunrise And Sunset Time Between Sunrise And Sunset.

Keywords: Time Between Sunrise And Sunset, Migraine Headache Severity, N-of-1 trials, real-world evidence, causal inference, observational study

Preliminary: Based on 1 participants. Results may change as more data is collected.

Results

Primary Findings

Analysis of 10 paired observations from 1 participants revealed a moderate reduction in Migraine Headache Severity following above-average Time Between Sunrise And Sunset exposure.

-16.8%
Change from Baseline
Moderate effect on Migraine Headache Severity
0.07
Predictor Impact Score
Insufficient evidence for causal relationship

Supporting Statistics

High
Confidence
-0.762
Correlation (r)
p = 0.002
Significance
z = 1.21
Effect Magnitude
φ = 1.00
Temporality

What This Means

When participants had above-average Time Between Sunrise And Sunset:

  • Migraine Headache Severity decreased by 16.8% on average
  • Temporal analysis supports Time Between Sunrise And Sunset as the predictor (not the outcome)
  • This relationship is statistically significant (p = 0.002)

Interpreting the Predictor Impact Score

The Predictor Impact Score (PIS) integrates multiple Bradford Hill causal criteria into a single metric. Use this guide to interpret the score:

PIS Range Interpretation Recommended Action
≥ 0.5 Strong evidence High priority for RCT validation
0.3 - 0.5 Moderate evidence Consider for experimental investigation
0.1 - 0.3 Weak evidence Monitor for additional data
< 0.1 Insufficient evidence Low priority; may be noise

Note: PIS is a prioritization heuristic, not proof of causation. High scores indicate relationships worth investigating, not confirmed causal effects. With only 1 participants, these scores are preliminary and will become more reliable as additional data is collected.

Optimal Daily Values

No clear dose-response relationship detected. The Time Between Sunrise And Sunset values associated with high and low Migraine Headache Severity are too similar to provide meaningful dosing guidance. This may indicate a threshold effect (any amount works equally well), no effect, or insufficient data variance. With more participants, a clearer pattern may emerge.

Population Correlation

Time Between Sunrise And Sunset Distribution

Migraine Headache Severity Distribution

Statistical Summary

Relationship Statistics

Property Value
Cause Variable Name Time Between Sunrise And Sunset
Effect Variable Name Migraine Headache Severity
Sinn Predictive Coefficient 0.072513889770829
Confidence Level MEDIUM
Confidence Interval 0.39508
Forward Pearson Predictive Coefficient -0.762
Critical T Value 1.812
Total Time Between Sunrise And Sunset Over Previous 7 days Before ABOVE Average Migraine Headache Severity 12 hours
Total Time Between Sunrise And Sunset Over Previous 7 days Before BELOW Average Migraine Headache Severity 12 hours
Duration of Action 7 days
Effect Size strongly negative
Number of Paired Measurements 10
Optimal Pearson Product 1.0327095330208
P Value 0.024285
Statistical Significance 0.0015
Strength of Relationship 0.39508
Study Type population
Analysis Performed At 2026-01-04
Number of Participants 1

Time Between Sunrise and Sunset Info

Property Value
Variable Name Time Between Sunrise And Sunset
Aggregation Method SUM
Analysis Performed At 2020-09-10
Duration of Action 7 days
Kurtosis 1.6654030232475
Maximum Allowed Value 23 hours
Mean 12 hours
Median 12 hours
Minimum Allowed Value 60 minutes
Number of Aggregate Predictors 0
Number of Aggregate Outcomes 362
Number of Measurements 821637
Number of Measurements (including those generated by tagged, joined, or child variables) 452647
Public true
Onset Delay 0 seconds
Standard Deviation 1.7285417205584
Unit Hours
User Variables 817
Variable Category Environment
Variable ID 6038788
Variance 3.9125797209335

Migraine Headache Severity Info

Property Value
Variable Name Migraine Headache Severity
Aggregation Method MEAN
Analysis Performed At 2020-10-09
Duration of Action 24 hours
Kurtosis 1.7933475091696
Maximum Allowed Value 5 out of 5
Mean 2.4967136363636 out of 5
Median 2.4305545454545 out of 5
Minimum Allowed Value 1 out of 5
Number of Aggregate Predictors 151
Number of Aggregate Outcomes 11
Number of Measurements 109
Number of Measurements (including those generated by tagged, joined, or child variables) 109
Public true
Onset Delay 0 seconds
Standard Deviation 0.35261099818532
Unit 1 to 5 Rating
User Variables 38
UPC 0
Variable Category Symptoms
Variable ID 89097
Variance 0.43694847928025

Introduction

Background

Time Between Sunrise And Sunset (Environment) and Migraine Headache Severity (Symptoms) are both important factors in understanding human health and well-being. This study investigates the relationship between these two variables using real-world observational data.

Traditional randomized controlled trials (RCTs), while the gold standard for causal inference, are often impractical, expensive, or unethical for studying many health relationships. Aggregated N-of-1 observational studies offer a complementary approach that leverages within-subject comparisons across large populations to identify meaningful patterns.

Research Question

Does Time Between Sunrise And Sunset affect Migraine Headache Severity?

Additionally, we seek to determine:

  1. What is the direction and magnitude of any effect?
  2. How confident can we be in this relationship based on the available data?
  3. What are the optimal levels of Time Between Sunrise And Sunset for maximizing Migraine Headache Severity?

Study Objective

The objective of this study is to determine the nature of the relationship (if any) between Time Between Sunrise And Sunset and Migraine Headache Severity. Additionally, we attempt to determine the Time Between Sunrise And Sunset values most likely to produce optimal Migraine Headache Severity values.

Study Overview

This is a population-level observational study using aggregated N-of-1 methodology. By aggregating individual N-of-1 experiments, we can identify population-level patterns while accounting for the substantial individual variation that exists in most health relationships. Effect sizes are reported as percent change from baseline, enabling intuitive interpretation and comparison across different measures.

Full Methodology: Framework for Real-World Evidence-Based Pharmacovigilance: Aggregated N-of-1 Trials for Quantifying Treatment Effects

Discussion

Interpretation of Findings

Participants experienced a 16.8% reduction in Migraine Headache Severity following above-average Time Between Sunrise And Sunset exposure. The Predictor Impact Score (PIS) of 0.07 indicates insufficient evidence for a causal relationship. This finding is statistically significant (p = 0.002).

Statistical Significance

Using a two-tailed t-test with alpha = 0.05, it was determined that the change in Migraine Headache Severity is statistically significant at a 95% confidence interval. The p-value of 0.0015 indicates there is less than a 0.15% probability that this result occurred by chance.

After treatment, a 32.4% decrease (-0.516 out of 5) from the mean baseline 3.07 out of 5 was observed. The relative standard deviation at baseline was 13.9%. The observed change was 1.2107 times the standard deviation.

A common rule of thumb considers a change greater than twice the baseline standard deviation on two separate pre-post experiments may be considered significant. This occurrence would have only a 5% likelihood of resulting from random fluctuation (a p-value < 0.05).

T-Test Details
Observed t-value: 2.366
Critical t-value: 1.812

Since t = 2.37 > 1.81, we reject the null hypothesis.

Biological Plausibility

A plausible bio-chemical mechanism between predictor and outcome is critical for interpreting observational findings. This is where human judgment excels beyond statistical analysis.

Community feedback on the biological plausibility of this relationship is still being collected. Consider the known mechanisms by which Time Between Sunrise And Sunset might influence Migraine Headache Severity.

Bradford Hill Criteria Assessment

The Bradford Hill criteria provide a framework for assessing causality in observational studies. Our methodology operationalizes six of the nine criteria through the Predictor Impact Score (PIS):

Criterion How Addressed Metric
Strength Effect size magnitude Percent change from baseline (Δ%), z-score
Consistency Cross-participant replication Number of users (N), number of pairs (n)
Temporality Predictor precedes outcome Temporality factor (φ), onset delay (δ > 0)
Biological Gradient Dose-response relationship Gradient coefficient (φgradient)
Plausibility Biological mechanism assessment Community votes on mechanism plausibility
Specificity Category appropriateness Interest factor (finterest)

Predictor Impact Score (PIS)

The PIS integrates multiple Bradford Hill criteria into a composite metric quantifying how reliably a predictor affects an outcome. Higher scores indicate stronger evidence:

Population-Level PIS:

$$\text{PIS}_{\text{agg}} = |r_{\text{forward}}| \cdot w \cdot \phi_{\text{users}} \cdot \phi_{\text{pairs}} \cdot \phi_{\text{change}} \cdot \phi_{\text{gradient}}$$

Where φ-factors are saturation functions approaching 1 as evidence accumulates:

  • φusers = 1 - e-N/10 (user saturation)
  • φpairs = 1 - e-n/nsig (pair saturation)
  • φchange = 1 - e-Δspread/Δsig (effect spread saturation)
  • w = weighted average of plausibility votes

Temporality Assessment

We assess evidence for correct causal direction using the temporality factor:

$$\phi_{\text{temporal}} = \frac{|r_{\text{forward}}|}{|r_{\text{forward}}| + |r_{\text{reverse}}|}$$

Values approaching 1 indicate the predictor precedes the outcome (supporting causation); values near 0.5 suggest ambiguous directionality; values near 0 suggest reverse causation or confounding by indication.

Limitations

As with any observational study, correlation does not prove causation. Key limitations include:

  • Unmeasured confounders: Variables not tracked may influence results
  • Self-selection bias: Health trackers may differ from the general population
  • Measurement error: Self-reported data may contain recall bias
  • Confounding by indication: Sicker individuals may use more treatments

However, within-subject comparison and temporal precedence analysis partially mitigate these limitations. If the relationship is merely coincidental, as participants independently modify their Time Between Sunrise And Sunset values, the observed strength will decline over time. Spurious correlations naturally dissipate as more data is collected.

Future Directions

Future research should examine:

  • Subgroup analyses to identify individual differences in response
  • Potential confounders and mediators of the observed relationship
  • Optimal dosing and timing for Time Between Sunrise And Sunset
  • Confirmation through prospective or randomized designs
  • Biological mechanisms underlying the observed effects

Conclusion

📊 Preliminary Findings: With 1 participants, these results are based on limited data. Effect sizes and confidence will improve as more participants contribute data. Consider these findings directional rather than definitive.

Above-average Time Between Sunrise And Sunset was associated with a 16.8% reduction in Migraine Headache Severity—a moderate effect. The Predictor Impact Score of 0.07 indicates this relationship is requiring additional data before conclusions.

Bottom Line: Based on a PIS of 0.07 and a 16.8% effect size, this relationship currently lacks sufficient evidence. Continue monitoring as more data becomes available. Note: These conclusions may strengthen or change direction as more data is collected.

These findings contribute to our understanding of how Time Between Sunrise And Sunset may influence Migraine Headache Severity in real-world conditions. The within-subject design and temporal analysis provide confidence in these relationships, though observational limitations remain.

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Methods

Study Design

This study is based on data donated by 1 participants. Thus, the study design is equivalent to the aggregation of 1 separate n=1 observational natural experiments.

This within-subject design is powerful because it controls for all stable individual characteristics (genetics, baseline health status, socioeconomic factors) that might otherwise confound the relationship between variables.

Data Analysis

Temporal Assumptions

The analysis incorporates temporal assumptions about the relationship between variables:

  • Onset Delay: It was assumed that 0 seconds would pass before a change in Time Between Sunrise And Sunset would produce an observable change in Migraine Headache Severity.
  • Duration of Action: It was assumed that Time Between Sunrise And Sunset could produce an observable change in Migraine Headache Severity for as much as 7 days after the stimulus event.

Statistical Methods

For each participant, we calculated the Pearson correlation coefficient between Time Between Sunrise And Sunset values and subsequent Migraine Headache Severity values. Individual correlations were then aggregated using Fisher's z-transformation to produce a population-level estimate:

Individual Correlation:

$$r_i = \frac{\sum(x_{ij} - \bar{x}_i)(y_{ij} - \bar{y}_i)}{\sqrt{\sum(x_{ij} - \bar{x}_i)^2 \sum(y_{ij} - \bar{y}_i)^2}}$$

Fisher's Z-Transformation:

$$z_i = \frac{1}{2} \ln\left(\frac{1 + r_i}{1 - r_i}\right)$$

Aggregated Correlation:

$$\bar{r} = \tanh(\bar{z}) \quad \text{where} \quad \bar{z} = \frac{1}{N}\sum_{i=1}^{N} z_i$$

Effect Size Calculation

Effect sizes are reported as percent change from baseline. For each participant, we compare the outcome following above-average predictor values to the overall baseline outcome:

$$\Delta\%_{\text{baseline}} = \frac{\bar{O}_{\text{follow-up}} - \bar{O}_{\text{baseline}}}{\bar{O}_{\text{baseline}}} \times 100$$

Effect Magnitude (Z-Score)

To assess effect magnitude relative to natural variability, we calculate the z-score:

$$z = \frac{|\Delta\%_{\text{baseline}}|}{\text{RSD}_{\text{baseline}}}$$

where RSDbaseline is the relative standard deviation of outcome during baseline period

A z-score > 2 indicates statistical significance (p < 0.05), meaning the observed change exceeds typical baseline fluctuation and is unlikely due to random variation.

Statistical Significance

Correlation significance is assessed using a two-tailed t-test:

$$t = \frac{r\sqrt{n-2}}{\sqrt{1-r^2}}$$

We reject the null hypothesis (ρ = 0) at α = 0.05 when |t| exceeds the critical value, providing statistical evidence that the observed relationship is not due to chance.

Data Sources

Time Between Sunrise And Sunset data was primarily collected using Weather. Automatically import temperature, humidity, and ultraviolet light exposure.

Migraine Headache Severity 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.

Data Quality

Data quality measures were applied to ensure reliable results:

  • Minimum Data Requirement: Only participants with sufficient paired observations were included in the analysis.
  • Outlier Handling: Extreme values were winsorized to reduce the influence of measurement errors.
  • Missing Data: Days with missing values were handled using appropriate filling strategies based on the variable type.
  • Test User Exclusion: Test accounts and invalid users were excluded from all analyses.

Principal Investigator

Program & Methods

Mike P. Sinn
Sinn, M. P.

Designed and implemented data collection, aggregation, causal inference pipeline, and automated study generation framework. Developed the Predictor Impact Score methodology operationalizing Bradford Hill criteria for ranking causal relationships in observational data. When he tells people this at parties, they usually say they have to go check on their car.

Individual study outputs are automated, reproducible, and open to external audit. (Which I would seriously recommend.)

Contact

Cite This Study

APA Format
Sinn, M. P. (2026). Causal Analysis: Does Time Between Sunrise And Sunset Affect Migraine Headache Severity?. The Journal of Citizen Science. https://studies.crowdsourcingcures.org/study/cause-6038788-effect-89097-population-study
BibTeX 
@misc{sinn_cause_6038788_effect_89097_population_study_2026,
  author = {Sinn, Mike P.},
  title = {Causal Analysis: Does Time Between Sunrise And Sunset Affect Migraine Headache Severity?},
  year = {2026},
  publisher = {The Journal of Citizen Science},
  url = {https://studies.crowdsourcingcures.org/study/cause-6038788-effect-89097-population-study},
  note = {Accessed: January 10, 2026}
}
Chicago/Turabian
Sinn, Mike P. "Causal Analysis: Does Time Between Sunrise And Sunset Affect Migraine Headache Severity?." The Journal of Citizen Science. Accessed January 10, 2026. https://studies.crowdsourcingcures.org/study/cause-6038788-effect-89097-population-study.
Harvard
Sinn, M.P., 2026. Causal Analysis: Does Time Between Sunrise And Sunset Affect Migraine Headache Severity?. [Aggregated N-of-1 Study] The Journal of Citizen Science. Available at: https://studies.crowdsourcingcures.org/study/cause-6038788-effect-89097-population-study [Accessed January 10, 2026].

Study Type: Aggregated N-of-1 Observational Mega-Study
Evidence Level: Level II (Real-World Evidence)
Methodology: Bradford Hill Criteria with Predictor Impact Score (PIS)

References

This framework was originally developed in 2013 based on the Bradford Hill criteria. Subsequent literature has independently validated similar approaches to causal inference from observational data:

  1. Hill, A.B. (1965). The environment and disease: association or causation? Proceedings of the Royal Society of Medicine, 58(5), 295-300. [Bradford Hill criteria]
  2. Lillie, E.O., et al. (2011). The n-of-1 clinical trial: the ultimate strategy for individualizing medicine? Personalized Medicine, 8(2), 161-173. [N-of-1 methodology]
  3. Pearl, J. (2009). Causality: Models, Reasoning, and Inference . Cambridge University Press. [Causal inference]
  4. Hernán, M.A., & Robins, J.M. (2020). Causal Inference: What If . Chapman & Hall/CRC. [Free textbook]
  5. FDA (2018). Framework for FDA's Real-World Evidence Program . U.S. Food and Drug Administration. [Regulatory context]
  6. Duan, N., et al. (2013). Single-patient (n-of-1) trials: a pragmatic clinical decision methodology . Journal of Clinical Epidemiology, 66(8), S21-S28.
  7. Platt, R., et al. (2018). The FDA Sentinel Initiative—an evolving national resource . New England Journal of Medicine, 379(22), 2091-2093.

This information is for research and educational purposes only, not medical advice. Consult a healthcare provider before making health decisions. Terms of Service

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