The Correlation between Light Pollution and Sleep
Advisor: Dr Zeynep Araci
Internship Location: ASDRP, Fremont
Onsite Mentor: Dr. Larry Mcmahan
This research project aims to investigate the impact of light pollution on sleep quality. Sleep plays a significant role in our overall health and productivity, and it is therefore important to address factors which could have the potential to affect our sleep quality . In recent years, we can observe a global increase in Artificial Light At Night (ALAN) and its potential role in hindering our sleep quality due to increased urbanization. As a resident of the East Bay, which is a highly urbanized and light polluted region, I seek to understand how varying levels of light pollution influence sleep quality among inhabitants, focusing on regions like Silicon Valley and rural areas. The project essentially aims to determine the extent to which light pollution contributes to sleep disturbances and how strong the relationship between the two is. A primary reason for conducting this research is to draw attention to the significant consequences of light pollution. The methodology that will be used involves surveying diverse populations in areas with varying light pollution levels. I will also be conducting a literature review on light pollution and the factors affecting sleep. The survey includes questions on sleep duration, desired sleep duration, and additional factors influencing the subjects’ sleep quality. By gathering the results of this survey, I aim to establish a correlation between light pollution levels and sleep quality. An anticipated problem would be struggling to reach diverse populations and obtaining sufficient responses, which could potentially lead to delays in data collection. However, I would continue pursuing data collection. A more thorough literature review may be necessary at such a stage to study the relationship between light pollution and sleep quality.
Project Blog
Week 0: Introduction to the project
Welcome to the first blog post for my project. This project is about measuring the correlation between light pollution and sleep quality. I am interested in pursuing this project because sleep is important for several reasons and functions. Sufficient sleep is required for a healthy life. During sleep, our brain and body undergo processes vital to recovery and general health. It is therefore important to sleep sufficiently in order to function healthily and productively throughout the day. However, several factors play a role in the quality of our sleep. Sleep quality can be disturbed by several factors, such as background noise, food consumed, etc. However, in this project, I will be looking into how light pollution in an environment can potentially be another significant factor in someone’s sleep quality.
Light pollution, or the excessive presence of artificial light in the night sky, can hinder sleep quality. Over recent years, the growth of ALAN (Artificial Light At Night) has been increasing at a rate of about 9.6% globally each year. Many of the factors contributing to overall light pollution can be traced to urban sky glow, which is brightness in the night sky over inhabited areas due to light trespass, glare, and confusing/excessive clutter of light sources. By analyzing the presence of ALAN in both urban and remote regions and the causes of ALAN in specific regions, I wish to discover how people’s sleep varies depending on the amount of light pollution present in their region. This project will ultimately answer the following question: how significant of a factor does light pollution play in sleep quality?
Light pollution is prevalent in the region which I live in due to the highly industrial nature of this area, and I am therefore interested in analyzing the relationship between this light pollution and the sleep quality of the region’s inhabitants. A related course I have previously taken was AP U.S. Government and Politics. AP U.S. Government and Politics prepared me with understanding of sampling and data gathering. I also have research experience from a current research project related to cosmology that I am conducting with ASDRP (Aspiring Scholars Directed Research Program). Although I do not currently have significant experience in matters concerning sleep quality and factors affecting it, I will also be studying this in order to excel in the project.
Growing up in the highly populated and industrial Bay Area, I have been exposed to lots of artificial light and find great value in analyzing how the light pollution in this region is affecting the sleep quality of the Bay Area’s inhabitants. People who live in areas like Silicon Valley that have more prevalent light pollution may undergo less sleep quality. It is important to address this because light pollution could potentially be a significant factor in our sleep. However, the purpose of this project is to understand how much light pollution affects our sleep and overall health, and in turn our society.
This research will draw more attention to the issue of light pollution in our society. By drawing attention to this consequence, there will be more awareness and steps to reduce light pollution to better the health of our society’s inhabitants. The reduction of light pollution not only benefits the sleep and health of individuals, but also would reflect positively on the economy due to increased productivity and reduced energy wastage. Thank you for reading my first blog post, and stay tuned for future updates.
Here is a weekly schedule for my project:
Week 1: Read sources necessary for gaining background information and context.
Week 2: Finish the goals of Week 1.
Week 3: Set up surveys and send them out to the subjects.
Week 4: Begin collecting data from the survey responses and analyzing them.
Week 5: Continue the goals of Week 4.
Week 6: Conduct an in-depth analysis which accounts for the regions’ levels of light pollution.
Week 7: Continue the goals of Week 6.
Week 8: Begin final analysis and develop conclusions. Begin writing the outline of the paper.
Week 9: Finalize conclusions. Begin writing the paper.
Week 10: Analyze the conclusions, and include the analysis in the paper.
Week 11: Double check all the sources.
Week 12: Finalize the paper and review it.
Week 1: Initial literature review
Welcome to the second post for this project. In the previous post, I gave a general introduction to the issue of light pollution and explained the goals of this project. Light pollution is the excessive presence of artificial light in the night sky. I will understand the relationship that light pollution has with sleep quality, if there is any. This week, I studied a few scientific papers that discussed both the relationship sleep has with health and the effects that exposure to artificial light has on sleep and health. In this post, I will explain my analysis of these studies and will also describe my future direction for the weeks to come.
“Factors associated with short and long sleep” by Christopher A Magee, Donald C Iverson, and Peter Caputi describes a study of 49,405 Australian adults. The study aimed to identify factors associated with short sleep and long sleep, and the researchers found that short sleep was associated with long working hours and obesity while long sleep tended to be associated with low physical activity levels and pregnancy. Essentially, health issues or abnormal circumstances have been shown to be correlated with unhealthy sleep behaviors.
I will now talk about a paper that discusses the effects of artificial light on organisms’ sleep and health. “Hormonally mediated effects of artificial light at night on behavior and fitness: linking endocrine mechanisms with function” by Jenny Q. Quyang, Scott Davies, and Davide Dominoni discusses a study regarding the effects of ALAN (Artificial Light At Night) on biological functions. The paper talks about the functions of the pineal, reproductive, adrenal, and thyroid axes and how organisms’ exposure to ALAN interrupts the functions of these endocrine axes. Exposure to the artificial light suppresses melatonin, resulting in sleep problems and health issues. It has also been shown to interrupt reproductive cycles in the organisms.
I will finally briefly discuss “Impacts of streetlights on sleep in urban birds” by Anne E. Aulsebrook, which is a work consisting of 6 chapters to explain the impact that exposure to artificial light had on the sleep of birds. The first chapter discusses how artificial light affects wildlife reproduction and an organism’s natural life cycle. Artificial light exposure has also been shown to interrupt the timing of seasonal reproduction. The second chapter explores the importance of sleep and the methodology of how scientists study sleep behaviors in animals. The chapter discusses how animals are to be studied in natural environments and should be studied carefully under the knowledge that animals may appear to be asleep when they may actually be awake. The third chapter introduces humans and discusses how both humans and wildlife can suffer from ALAN. Artificial light at night can disrupt sleep patterns, and the chapter goes on to describe health implications caused by these disruptions. The fourth chapter explores a study done specifically on pigeons. Exposure to ALAN reduced the amount of REM and non-REM sleep that the pigeons had, and these effects lasted for over a day after the initial exposure to this artificial light. The fifth chapter’s study is similar to the fourth chapter. However, this chapter discusses the exposure of artificial light via streetlights on the sleep of black swans. The study found that the streetlights reduced the amount of sleep the swans got at night. The sixth chapter essentially recaps the findings and information that were provided throughout the discussed studies, in addition to also providing a future outlook for research in regards to artificial light exposure and its effects on sleep.
From reading about these studies, I have learned about what really defines a healthy amount of sleep and the relationship that sleep has with several biological functions. I have also learned the impact that exposure to ALAN has on sleep quality in both humans and wildlife. For the next couple of weeks, I will be continuing to expand my knowledge in this field by reading more scientific literature and publications that delve into relevant research and their findings. I will also begin constructing the survey and refining the methodology that will be used to collect and analyze data from human subjects in areas of varying levels of light pollution. Thank you for reading this post.
Week 2: Understanding sleep
Welcome to the third post for this project. In the previous post, I explained my progress in a literature review I am currently conducting to learn about sleep and light pollution. I learned about how exposure to artificial light affects the quality of sleep in both humans and animals . This week, I have been reading The Science of Sleep: What It Is, How It Works, and Why It Matters. In this post, I will explain my analysis of what I have read so far and will also describe my future direction for the weeks to come.
Chapter 1 of this book covers the following concepts: 1) What sleep is 2) How the electrical activity of the brain is measured 3) The organization of the sleep stages 4) How sleep studies are performed 4) REM sleep and Non-REM sleep 5) How much sleep we need vs how much we get 6) relevant information about neurotransmitters and 7) what dreams are. This first chapter provides us with a great introduction to information we should know about sleep. Relevant information covered in later chapters talk about the consequences of failing to sleep healthily, the circadian rhythm, circadian regulation models, the relationship between melatonin and sleep, how aging is related to sleep quality, the hormones secreted during sleep, and sleep disorders. In this post, I will be talking specifically about some of the most important information I learned from the first chapter. My next post will discuss relevant information from the chapters to follow.
The book describes sleep to be a period of decreased awareness and the “rhythmic appearance” of certain stages. The stages can be defined by looking at an electroencephalogram which allows us to observe the brain waves, along with an electrooculogram which records eye movements, and an electromyogram which measures muscle activity. The period of sleep can be broken down into the following stages: the waking stage, the three non-rapid eye movement stages, and the rapid eye movement stage. The waking stage is when we are alert, and our brain waves are dominated by beta waves. The NREM sleep stages can be categorized by the following stages: N1, N2, and N3. The N1 stage is considered drowsiness. The brain waves slow down from beta waves to alpha waves, eye movements slow down, and muscle activity decreases. In N2, brain waves continue to become slower but there is also activity called sleep spindles, which are bursts of faster activity. In N3, brain waves become very slow and turn into delta waves. This stage is crucial for growth hormone release and physical healing. The REM stage is when we have bursts of rapid eye movements, but there is very little muscle activity. It is during this stage that we dream. Our brains are highly active, and our brain waves are similar to the waves in the waking stage. We consolidate memories and process emotions. As we sleep, we cycle through the stages of sleep multiple times, with the sleep cycle starting with the NREM stages and progressing to REM sleep.
Although I will not be utilizing the devices necessary for analyzing the brain activity of my subjects as they sleep, I will be utilizing a questionnaire which will be used to qualitatively analyze their quality of sleep. The book mentions that although studies say that typical sleep is in the area of 7.5 to 8.5 hours, “primarily about 8.17 hours”, the amount of sleep we need is difficult to define. We learn about sleep debt, which is a term used to describe lack of sleep. The book describes that a sleep debt is difficult to compensate for, as there are physical limitations such as the natural body clock which would prevent one from simply sleeping for an appropriate length of time after attempting to sleep at the beginning of the morning, or something of the sort that is unnatural. One particular consequence of developing a sleep debt is that waste products of metabolism are not able to be as efficiently cleaned out from the brain. There are several other consequences of lack of sufficient sleep, and the factors which define sufficient sleep may slightly vary depending on an individual’s specific circumstances, environment, and health.
As I continue to learn about sleep via reading this book and other sources of information, I will continue to finalize both my initial survey and short questionnaire (that will be taken nearly daily) which will be sent out to the subjects soon. I will also be reading about artificial light and its general impacts on sleep and beyond. Thank you for reading this post, and I look forward to updating you with my progress in this project.
Week 3: Updates to the methodology
Welcome to the fourth post for this project. In the previous post, I explained my analysis of some content discussed in the beginning of The Science of Sleep: What It Is, How It Works, and Why It Matters. I learned significant information about sleep which is important to know for this project. While I have been continuing to read this book, I have also read “Monitoring and Improving Personalized Sleep Quality from Long-Term Lifelogs” by Wenbin Gan, Minh-Son Dao, and Koji Zettsu. I have also made some important changes to my approach of surveying the subjects in this project. In this post, I will explain my analysis of the paper I have read and will also describe the changes I have made to my methodology.
“Monitoring and Improving Personalized Sleep Quality from Long-Term Lifelogs” proposes a framework for personalized sleep monitoring by making use of lifelogs. The paper addresses the problem of how it is difficult to track personalized sleep quality in everyday life, and the paper also addresses issues with traditional methods used in sleep research. Clinical sleep studies are expensive and very inaccessible. The paper proposes the use of lifelogs, which are comprehensive records of a person’s daily activities. The framework proposed by the paper uses machine learning to create a personalized sleep quality model by using the lifelogs to create a more holistic picture of sleep than what traditional methods are capable of. Additionally, this framework would be capable of identifying patterns in lifelog data and can therefore predict future disruptions or changes to someone’s sleep quality.
The research discussed essentially makes general lifestyle a significant factor when analyzing a subject’s sleep quality. This is similar to my own project, as although I will be correlating levels of light pollution to subjects’ reported sleep qualities, I also am accounting for environmental and other general factors that are affecting the subjects’ sleep quality. I will now discuss changes that I have made to the methodology of the project.
Previously, I have been planning on conducting a 3 week program in which the subjects would self report their sleep quality every morning via reporting the times they aimed to fall asleep/wake up at and the times they actually fell asleep/woke up at. However, from the research I have conducted so far, I realized that there are several factors that affect an individual’s sleep quality beyond how much time they slept for, as the time itself only represents quantity. The quality itself is dependent on things such as environment, lifestyle, and behaviors undergone during sleep. I have researched medically developed sleep scales, and I discovered a sleep scale titled Sleep Quality Scale which was developed by Hyergeon Yi, Kyungrim Shin, and Chol Shin. This covers six domains of sleep quality: daytime symptoms, restoration after sleep, problems initiating sleep, problems maintaining sleep, difficulty waking, and sleep satisfaction. I emailed one of the authors in regards to their sleep scale and introduced myself and this project, and asked for permission to use their sleep scale. While I wait for their response, I will be continuing to read relevant parts of The Science of Sleep: What It Is, How It Works, and Why It Matters.
I will also be making progress on writing a scientific paper, and within the next two weeks I will have sent out a survey to the subjects. If the creators of the Sleep Quality Scale positively respond to my reaching out, then I will begin my surveying. If they respond negatively or do not get back to me within the next two weeks, then I will be using my own sleep scale that I have developed based on my research of human sleep and factors affecting sleep. I will continue to refine this, and I will keep this in case I am unable to borrow the sleep quality scale that was created by Dr. Shin and his teammates. Thank you for reading this post, and I look forward to keeping you updated on the progress being made in this project.
Week 4: Factors in assessment of sleep quality, and progress in research paper
Welcome to the fifth post for this project. In the previous post, I explained my analysis of the scientific paper “Monitoring and Improving Personalized Sleep Quality from Long-Term Lifelogs” by Wenbin Gan, Minh-Son Dao, and Koji Zettsu. I connected the content discussed in that paper to the methodology of my project, and I elaborated on my methodology and changes that have been made. In this post, I will discuss the progress being made in my methodology as well as progress that I have made in writing the research paper.
Before I delve into the current progress, I will first talk about a paper I have read titled “Sleep Health at the Genomic Level: Six Distinct Factors and Their Relationships with Psychopathology” by Claire L Morrison and others. This paper discusses the correlation between low sleep quality and prevalence of mental health disorders. The authors of this paper propose the Sleep Health Index, a model to assess sleep quality according to six factors:
sleep efficiency
measures time spent sleeping during the time spent in bed.
circadian preference
someone's natural tendency to sleep at a certain time of day.
sleep alertness
how well-rested someone feels after waking up from their sleep.
sleep duration
the total amount of time someone spends sleeping.
non-insomnia sleep time
how much time was spent sleeping other than time spent battling insomnia (difficulty falling/staying asleep).
sleep regularity
the consistency of someone’s sleep patterns.
These 6 factors, the authors argue, allow for a much more comprehensive assessment of someone’s sleep rather than simply referring to the amount of time one spends sleeping.
I will now relate this model to the Sleep Quality Scale, a sleep scale developed by Hyergeon Yi, Kyungrim Shin, and Chol Shin. The SQS is a questionnaire that assesses an individual’s sleep quality according to the following six domains of sleep quality: daytime symptoms, restoration after sleep, problems initiating and maintaining sleep, difficulty waking, and sleep satisfaction. The SQS’s 6 domains of sleep quality cover a total of 28 questions, each of which can be connected to one of the 6 factors of sleep discussed in Morrison’s paper. I am currently in the midst of talking with the authors regarding the usage of SQS in this project.
I have designed a questionnaire, as I already mentioned in the previous post, which contains questions that fall under the six factors described in the SQS. This questionnaire is to be used if I am unable to use the SQS in this project. I additionally have written an introduction that will be incorporated in the final research paper. This introduction consists of a description and overview of light pollution, an overview of sleep, and brief statements describing the relationship that exposure to artificial light can have on sleep quality. As I have already located some subjects to answer the questionnaire for this project, I will continue to find more subjects. I will also continue to be in touch with the authors of SQS and soon will finalize the questionnaire to be delivered in this methodology. Thank you for reading this post.
Week 5: Progress in methodology and literature paper
Welcome to my new post for this project. In the previous post, I delved into the typical factors used to assess the quality of an individual’s sleep. As I reach out to potential subjects for data collection, I am also making progress in writing my literature paper. In this post, I will primarily be discussing the progress made in the literature paper, as well as discussing the status of the questionnaire that will be distributed to the subjects.
In the previous post, I discussed my completion of an introduction to the literature paper. It begins with a brief explanation of light pollution. The concept of light pollution is then tied to its negative consequences, and the consequence of a potentially negatively affected sleep quality is highlighted. The importance of sleep is briefly mentioned, and a short explanation of how light pollution could negatively affect natural sleep patterns is provided. The goals of this project are then described. This introduction allows a smooth transition into the rest of the paper, specifically the literature review section, which follows the introduction section.
I have been working on the literature review section. The literature review section is divided into three subsections: sleep quality, light pollution, and the connection between sleep quality and light pollution. For the subsection dedicated to sleep quality, I have covered and am still working on the following topics: what sleep is, sleep’s functions in the body, the factors affecting sleep quality, and methods of studying sleep quality. For the subsection dedicated to light pollution, I have covered and am still working on the following topics: what light pollution is, causes of light pollution, increasing prevalence of light pollution, and the consequences of light pollution. For the subsection dedicated to the connection between sleep quality and light pollution, I plan to cover the following topic: the impact of exposure to artificial light on sleep quality with several analyses of relevant research done with animals under this topic.
After the literature review section is the methodology section. The methodology section will cover the exact steps I have taken to collect and analyze reported sleep quality scores from a sample of subjects that come from varying levels of light pollution. The methodology is still underway, as I am still reaching out to potential subjects. The sleep questionnaire that I will be using will likely be my own, as I have not yet heard a positive nor negative response (in regards to necessary consent for usage of the Sleep Quality Scale) from the lead developer of the SQS, a sleep quality questionnaire I initially planned on using for this project. In the next paragraph, I will describe the primary factors that encompass the questions in my sleep quality questionnaire.
The sleep quality questionnaire that I made consists of the following factors: sleep duration, restoration after sleep, sleep efficiency, sleep regularity, sleep environment, and lifestyle. Sleep duration refers to the amount of time spent in bed, and this domain would also include circadian preference (preferred time of sleeping). Restoration after sleep refers to the individual’s feeling of well-restedness after waking up from their sleep. Sleep efficiency refers to the amount of time the individual spent sleeping while in bed. Sleep regularity refers to consistency of the individual’s sleep patterns. Sleep environment covers whether the individual sleeps with lights on, listens to music or sleeps through background noise, etc. Lifestyle covers physical and mental health, exposure to artificial lighting vs natural lighting, certain medical conditions or the usage of certain medications, etc.
I will be finalizing my subjects and sending out the questionnaire to them very soon in order to begin my data collection. I will also be continuing to make progress on my literature paper. I look forward to keeping you updated on this project’s progress. Thank you for reading this post.
Week 6: Distribution of Sleep Quality questionnaire, progress in research paper
Welcome to the seventh post for this project. In the previous post, I delved into an explanation of my progress in the research paper, as well as an insight into my methodology. In this post I will discuss the further progress I have made in writing my paper as well as the progress I have made in the methodology.
In the previous post, I discussed my progress in the literature review section of the paper. The literature review section is divided into the following three subsections: sleep quality, light pollution, and the connection between sleep quality and light pollution. I have written sufficient explanations of relevant topics under each subsection and have also cited sources, but I am still working on my written analysis of these sources. However, so far, a basic structure with fundamental content for the literature review section is complete.
I have also begun working on the methodology section this week. In the methodology section, I am covering the steps I have taken to collect and analyze reported sleep quality scores from a sample of subjects that come from varying levels of light pollution. In the previous post, I discussed how I emailed a professor in regards to permission to use the Sleep Quality Scale, a developed and tested sleep questionnaire that assesses sleep quality, for my project. However, due to a lack of response, I have resorted to my own developed sleep scale. This sleep scale consists of 21 questions related to sleep quality, and the questions are categorized under the following: sleep duration, restoration after sleep, sleep efficiency, sleep regularity, sleep environment, and lifestyle. Based on the answers to the 21 questions, a numerical score representing sleep quality is created for the subject.
In addition to the 21 questions in the questionnaire, I also ask for the subject’s zip code so that I can obtain the light pollution index of the general location in which they reside. I do not ask for the subject’s name or other identifying information except for their email address, which I use to email their sleep quality score to. I have currently sent the questionnaire to 11 subjects, and I plan to have sent it out to around 15 more subjects next week.
In order to obtain the light pollution index of a subject’s general location, I resort to using publicly available data from NASA VIIRS which is viewable on the website lightpollutionmap.info, the most recent data being from December 2023. I have looked for subjects who come from areas of both high and low indexes of light pollution in order to get more varied data.
As I continue to collect data (sleep quality scores from subjects) this week and next week, I will be recording them and looking for any noticeable discrepancies between the data reported from the subjects living in areas of noticeably different indexes of light pollution. Such a trend would suggest that there is in fact a correlation between light pollution and sleep quality. I will continue to polish my literature review section and write my methodology section. Thank you for reading this post, and I look forward to keeping you updated on my progress.
Week 7: Distributing sleep questionnaire, analyzing data
Welcome to the eighth post for this project. In the previous post, I delved into an explanation of both my progress in the research paper and the progress made in the methodology. In this post I will mainly discuss the progress I have made in the data collection this week.
In the previous post, I explained the progress being made in the methodology section of the research paper. The methodology section discusses the questions that compose the sleep quality questionnaire and the method of how the responses are analyzed. The questions are categorized under the following: sleep duration, restoration after sleep, sleep efficiency, sleep regularity, sleep environment, and lifestyle. These factors listed have been determined from my research of published sleep quality studies. I score the answers to a subject’s submitted response of the questionnaire on a scale of 1 to 4 points per question or a scale of -1 to -4 points per question depending on the question and what its answers imply for sleep quality. The points get added up and a score representing the subject’s sleep quality is determined. The sleep quality scores of several subjects that have taken the sleep questionnaire will be compared and correlated to the light pollution indexes of their reported regions. After doing so I will look for a trend that indicates a correlation between light pollution index and the sleep quality score.
Last week I distributed my questionnaire to 11 subjects. I have distributed it to 6 more subjects this week. I plan on distributing it to more subjects this weekend and reaching at least 30 subjects by the end of next week. I have conducted an analysis of my current responses and realized that there does not seem to be a significantly strong correlation between sleep quality and light pollution index of their reported regions; however, my sample size is still relatively small and I need more subjects to make a sufficient analysis.
As mentioned in the previous post, I resort to using publicly available data from NASA VIIRS which is viewable on the website lightpollutionmap.info, the most recent data being from December 2023. The light pollution index is representative of general radiance in the region, and the unit for radiance is watt per steradian per centimeter squared. The average light pollution index of the data I currently have is roughly 70.0 on a scale of 0.10 to 150.
As I continue to collect data (sleep quality scores from subjects) this week and next week, I will be recording them and looking for any noticeable discrepancies between the data reported from the subjects living in areas of noticeably different indexes of light pollution. In addition to the data collection, which is currently the majority of my work in this project at this point in time, I will continue to polish my methodology section and finalize most of the sections of the research paper that I have been working on for the past few weeks.
Thank you for reading this post, and I look forward to keeping you updated on my progress.
Post 9: Survey distribution and data analysis
Welcome to the ninth post for this project.
In my previous post, I mentioned that there was not a significant correlation between light pollution index and sleep quality score based on the data my subjects has provided. Sleep quality scores have differed, and the majority of the light pollution indexes tended to be relatively near 70.0 watts per steradian per centimeter squared with few being closer to 90.0 watts per steradian per centimeter squared. In my study, I have used publicly available NASA VIIRS data to get the light pollution index of the subject’s reported region.
I have distributed the questionnaire to 5 more subjects this week, and I have done an analysis of their sleep quality scores and mapped it to the light pollution index of their respective regions. From the responses I received this week, I noticed more variation in the light pollution indexes from the region they were reporting from while there also being variation in their calculated sleep quality scores. I have not yet noticed a strong trend between light pollution index and sleep quality. This is a potential obstacle that I may continue to face in data analysis, which would essentially assert that there isn’t a strong relationship between light pollution index of an environment and someone’s sleep quality. While such a relationship is not entirely negligible, it is likely overridden by the other factors of sleep quality.
I do look/hope to find out there is a relationship between light pollution and sleep quality, although other factors of sleep quality can override it and which will show in the data. I look forward to sharing the data with everyone and an analysis of it soon, once it has all been compiled and when I have reached my target response count. I will continue to reach out to more subjects for more responses to gather more data.
As I continue to collect data this week, I will be recording them and looking for any noticeable discrepancies between the data reported from the subjects living in areas of noticeably different indexes of light pollution. Upon completion of data collection, I will be prepared to provide a full analysis in the context of my literature review and my original theory that light pollution has a strong correlation with sleep quality. Thank you for reading this post, and I look forward to keeping you updated on my progress.
Post 10: Data analysis, reflections, areas of improvement
Welcome to the tenth post for this project. This week, I have analyzed my 30 responses in the context of their light pollution index. While light pollution may not be a significant factor in the sleep quality of the subjects, this project does highlight how other factors of sleep quality such as artificial light exposure throughout the day, sleep efficiency, and sleep regularity comparatively play a more significant role in determining sleep quality. The subjects whose responses demonstrated higher sleep quality (sleep quality scores in this project fall on a numerical scale of -39 to 24 points) than others reported positive answers for questions regarding the factors listed above.
I must also address how studies regarding how exposure to artificial light affects animals’ sleep qualities would be quite different from this study. This particular study involves distributing a sleep questionnaire to humans; while the questionnaire is fairly valid and has been directly influenced by thorough research regarding the several factors affecting human sleep quality and ways of assessing sleep quality, an analysis of an individual’s sleep quality in context of specific factors would be more accurate when directly observing the individual’s behavior along with the use of certain equipment such as the EEG, EOG, and EMG.
The light pollution index of an environment differs from direct exposure to artificial light. An analysis of my responses confirms that sleep quality score has been correlated with answers to certain questions such as exposure to artificial light throughout the day and exposure to sunlight throughout the day, as opposed to light pollution index (radiation) of the general region of the subject’s place of residence. I have also noticed that the sleep quality scores are strongly correlated with other factors in the questionnaire that fall under sleep efficiency, sleep consistency, and general lifestyle (this includes light exposure throughout the day).
Aside from discussing my current stage of analyzing the data, I need to also address that there are two main areas of improvement in regards to the conduct of distributing the survey in this project, and those are the following: the sample size and sample variety. A sample of 30 subjects, while sufficient for conducting an analysis, could be increased in the future for stronger analyses. Additionally, in terms of sample variety, it would be more beneficial to have subjects that varied more in their light pollution indexes. I have been writing these areas of improvement to include them in the end of my scientific paper.
As I continue to write about my observations in the data I have collected, I am also writing a piece to acknowledge the harms of light pollution on the general public and the environment. Although this project may determine that human sleep quality is not significantly affected by light pollution index, it is important to reiterate the harms of light pollution and the importance of implementing practices, such as light shielding, to limit light pollution in our society for both the benefit of nature and our general benefit. Thank you for reading this post.
Post 11: Conclusions, questions, and the presentation
Welcome to the final post for this project. This post will focus on some conclusions I have reached this week and my current status of creating a presentation that briefly yet effectively conveys this project’s purpose, findings, and message to the general public.
According to an analysis of the data regarding my respondents’ performance in each of the categories in the survey, sleep efficiency and general lifestyle (without context of artificial light exposure) had a much stronger correlation to overall sleep quality score than did exposure to artificial light. Exposure to artificial light is separate from light pollution (measured in radiance). Analysis of the relationship between light pollution and sleep quality scores showed a strong lack of a relationship. Most of my subjects come from regions within the range of 10.60 nWatts per cm-2 per sr-1 and 21.00 nWatts per cm-2 per sr-1. Very few respondents came from regions with radiance exceeding 36 nWatts per cm-2 per sr-1.
My data analysis left me wondering if I had reached more subjects whose regions had radiance exceeding 36 nWatts per cm-2 per sr-1, would my data have looked differently? Would there have been some correlation, or would there still be a lack of correlation? I believe there needs to be a continuation of research done with more subjects on both the higher and lower ends of the light pollution scale. The other question I have is— why is exposure to artificial light shown to have such a weak correlation with sleep quality scores relative to the other factors? Although countless studies show how artificial light exposure negatively affects our sleep quality, and although the artificial sleep category has been universally scored with the lowest points than all the other categories in the questionnaire, the category does not demonstrate a trend consistent with the sleep quality scores. This leads me to believe that I may have made a few missteps in the development of my sleep quality scale, although there are still trends my data analysis has shown that are fairly consistent with what current research has to say about the factors that affect sleep quality, such as sleep efficiency and general lifestyle (without context of artificial light exposure) .
As for the presentation, I have found some difficulty in maintaining conciseness, as there is so much context I feel is necessary, such as the stages of sleep, understanding circadian rhythms, how the VIIRS is used to measure light pollution, etc. However, I am working to find the most crucial elements of each topic to swiftly move past the context so that I can focus on my data analysis and the conclusions. One part of my conclusions includes the reflections and implications of the analysis of how different factors have been shown to correlate with sleep quality scores. However, my conclusions also include the challenges faced/areas of improvement and my call to action to the audience in regards to bettering our sleep quality and what we can do to reduce light pollution, and I especially look forward to sharing this part of the presentation with you all.
It has been a fun 11 weeks of keeping you all updated on this project. There is so much I have learned throughout the past 3 months about light pollution, sleep, and more. Thank you all for reading this post, and thank you for reading my previous posts if you have been following the progress of this project.