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The Melanie Avalon Biohacking Podcast Episode #126 - Azure Grant

Azure Grant is a researcher interested in biological rhythms, hormonal health, and education via participatory research. She received her undergraduate and graduate training in neuroendocrinology from the University of California at Berkeley, and is graduating with a PhD in neuroscience in summer, 2021. Prior to graduate school, Azure trained with the Quantified Self community, and was inspired by the technical skill and poignant questions posed by community members. This experience led her to help develop methods for inclusion of participants in each part of the research process: from asking questions, to data collection and analysis, to reporting; and to recognize a particular need in women's health for accurate, open tools. Her participatory research focuses on developing tools for women's health by defining relationships between the state of hormonal and metabolic systems with the state of easier to measure outputs, like temperature and heart rate.



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11:05 - Azure's Background

13:50 - Body rhythms

Evidence for a Coupled Oscillator Model of Endocrine Ultradian Rhythms

16:30 - Seasonal Rhythms

19:00 - what is driving these rhythms?

21:10 - what was the original cause?

24:10 - the menstrual rhythm

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28:40 - does hormonal birth control cause a loss of ovulatory rhythm?

31:15 - what are the implications of the gender bias in scientific study?

34:45 - predicting the fertility window

Ultradian rhythms in heart rate variability and distal body temperature anticipate onset of the luteinizing hormone surge

Adolescent Development of Biological Rhythms: Estradiol Dependence and Effects of Combined Contraceptives

39:15 - how much of a change is there in Temperature prior to ovulation?

41:50 - cholesterol

Free-Living Humans Cross Cardiovascular Disease Risk Categories Due to Daily Rhythms in Cholesterol and Triglycerides

46:50 - how best to Interpret your cholesterol panels

50:50 - HDL

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The Melanie Avalon Biohacking Podcast Episode #38 - Connie Zack
The Science Of Sauna: Heat Shock Proteins, Heart Health, Chronic Pain, Detox, Weight Loss, Immunity, Traditional Vs. Infrared, And More!

53:05 - how to get more involved in research studies



55:55 - the Q Cycle Study

59:45 - working with oura ring

1:01:00 - data collection

1:04:30 - glucose and diabetes

Multi-Timescale Rhythmicity of Blood Glucose and Insulin Delivery Reveals Key Advantages of Hybrid Closed Loop Therapy

1056-P: Characterization of Multi-timescale Biological Rhythms in Individuals with Type 1 Diabetes

1:07:15 - insulin pumps

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1:13:00 - are there any completely independant rhythms

1:15:20 - Cyanobacteria

1:16:05 - is there any one major thing that will heavily effect rhythms?

1:18:00 - eating rhythms

1:21:00 - upcoming projects


Melanie Avalon: Hi friends, welcome back to the show. I am so incredibly excited about the conversation that I am about to have. Let me tell listeners the backstory behind today's episode. So, as listeners know, I am really, really obsessed with my biohacking device called an Oura ring. For listeners who are not familiar, it's a ring that measures your heart rate variability, your body temperature, your activity levels, your respiration. It really helps just get a picture of your body's rhythms and how you're responding to stress. It's been a really valuable tool in my personal health journey. Listeners have become really obsessed with it as well. I've had the CEO Harpreet on the show twice to do an episode on it. After our last episode, we got off the call and he was like, “You have got to meet this girl, Azure Grant, that we're working with.” Basically, she had been working with Oura on the fertility aspect, part of Oura ring and the temperature and the implications of that. She has a lot of really cool research that she's doing. So, I did a call, and we immediately connected.  

There're so many incredible things that we could talk about. Azure is doing all of this incredible work with just different rhythms in the body, and particularly things with women specifically. And there's just so much information in there. And we were talking right before the call, I read all of the studies that she's worked on. All of her published research, and it's listeners, it's so fascinating. It's so many things that people just aren't talking about. So, this conversation, I knew it just had to happen. Azure, thank you so much for being here. 

Azure Grant: Thank you for that very exciting introduction. That was so kind, and thank you for reading everything and for the opportunity to be here and talk to you. 

Melanie Avalon: Also, congratulations in advance. Azure is actually submitting her dissertation today, which is crazy for her PhD in neuroscience. She's at the University of California at Berkeley. Congratulations in advance for that. Well, I don't know how when do you find out, like, how does that work?  

Azure Grant: I think it will almost definitely have gone through by then, I hope so. It tends to be a pretty quick process once you send it off into the void and people sign it. But thank you so much, it's definitely an exciting day. 

Melanie Avalon: It's very exciting. And your undergrad and grad were in neuroendocrinology, correct? 

Azure Grant: That's correct. It's technically a neuroscience PhD. And the work is really at the intersection of neuroendocrinology, biological rhythms, and participatory research. 

Melanie Avalon: So many things. We were talking before the call, there's so many different directions we could go with this. I guess, just to start things off, could you tell listeners a little bit about your personal story? What got you interested in the work that you're doing today? What are you focusing on? What are you interested in? Just give listeners that picture about yourself?  

Azure Grant: Absolutely. I came to Cal as an undergrad with a really strong interest in neuroscience, having grown up in particular, learning about the interaction between the reproductive system and medication. I had some family who were taking some rather experimental forms of hormone replacement therapy, and really got to watch how they were affected by this over their lives. It gave me a sense of what the term biological rhythm meant from a rather young age. I came into school, not necessarily knowing that I was going to end up studying women's health, but realizing as I went along, that I really resonated with a lot of my interests and a lot of my earlier life experiences. One of the stories that I like to tell really briefly is, I ended up working in a lab as an undergraduate at Lance Kriegsfeld’s lab who would go on to be one of my PhD mentors. He's a wonderful person. We were using continuous temperature sensors to monitor ovulatory cycles in rodents. After a while, it became clear that we had some sensors lying around the lab that could maybe collect the same data in humans. 

I was encouraged by other lab members that maybe we should try collecting some of this data on ourselves. And that really opened the door to seeing the connection between what one can do in the lab and what one might be able to do in the real world. This ended up teaching me so much about my own physiology, and a lot about the field of human female reproductive research. So, I was hooked at that point and there's a lot else to the story, but it's a field that I love and feel very passionate about. 

Melanie Avalon: Was Oura ring around at that time with the temperature tracking? 

Azure Grant: Oura ring came into my awareness a little bit later, although I think they would have been around as a company at the time. Once I learned about them and got to be introduced to them and start using their finger temperature data stream, I found it really interesting. But originally, we're actually using really whatever we could get our hands on these tiny devices called the iButton, which, I think, are designed to be shown thrown in a shipping car and track the temperature of lettuce as it traveled across the country or something like that. But it was very scrappy to begin with. When Oura came on the scene, that was much more of a self-contained solution that I could imagine being used by many people, not just those of us willing to tape strange devices to our wrists. 

Melanie Avalon: One of the most mind-blowing things people don't think about, so when people think about rhythms, people are pretty familiar with circadian rhythm, 24-hour cycle. Some people are starting to hear about infradian rhythms, cycles longer than 24 hours. I feel very few people are aware of, I don't even know how to say right, ultradian rhythms.  

Azure Grant: That's perfect.  

Melanie Avalon: Less than 24 hours. What are these rhythms, for listeners that are not familiar? What are the different types of rhythms in the body and what do they signify? 

Azure Grant: It's a great question. It's also one of the questions that really drew me into being interested in this field. When I think about biological rhythms, one of the best analogies that I've heard for this is to think about a symphony orchestra, in which you're listening to a rhythm, but you might have faster and slower rhythms interposed being played by different instruments, being played by different sections of instruments working together, and creating this synchronized coherent song made up of many different rhythmic components. Our bodies are very much like this, even if they're not producing sound, they're producing hormones, electrical impulses, behaviors, in a very synchronized manner. What does that mean on a more concrete level? If we start at the a much longer timescale over them, and then work down to faster sub rhythms. Most of us have heard of seasonality. Many animals are more obviously seasonal than humans and that maybe they hibernate like a bear. But humans are actually seasonal as well. Our blood sugar tends to have a seasonal rhythm, our sleep tends to change across the seasons, you might think about sleeping a little bit more in the winter. Actually, many different systems in our body show this seasonal change.  

Women in particular, have a rhythm of the ovulatory or menstrual cycle that takes place about once a month, I can call it every three to six weeks and be a bit more inclusive. But this is really interesting particular to two females. A little bit faster than this is the circadian rhythm, the one that most of us have heard of. Thanks, especially to that recent Nobel Prize that was shared by circadian researchers. These are rhythms that occur approximately once every 24 hours, and are coordinated by not only a central clock at the base of the brain, but are also coordinated by oscillators in most of the cells throughout our body interacting together. So those daily rhythms are important for the functioning of systems all across our body from our metabolism, reproduction, nervous system, behavior, cognition. And that's the second fastest timescale that I like to think about.  

Although, it really is turtles all the way down, we could go down to talking about oscillations of neurons at the brain at very high frequencies. But the place that I'll stop is talking about what you mentioned this ultradian or within-a-day rhythms. I found these ones extremely fascinating, starting in undergraduate, because once one is introduced to the concept, these within-a-day ultradian rhythms become very intuitive. If you can imagine waking up and going about your day, and maybe you get hungry three or four times a day, maybe you have periods of work where you are really focused, and then you get a little bit tired and need to step back and take a break. Maybe you have times when you can really sit and be still. And then other times throughout the day, when you want to get up and move around. All of these are example of ultradian rhythms, and they really are baked in to the brain and body. So, it's not only that these oscillations are coming from the choices that we make personally, they're really generated, it seems within the brain coordinated across different systems. 

In particular, bringing this back to you, the topic of network physiology or female reproduction, these rhythms change in a very stereotyped manner across the ovulatory cycle, as well as across other points in female productive life, like adolescence or menopause or pregnancy. On the whole, our bodies are these massively coordinated coupled oscillator systems at multiple timescales, really acting like this giant, beautiful symphony across all of our different systems. And I've always found this concept very compelling since I've learned about it. 

Melanie Avalon: Can I just say I am so enjoying this conversation? This is super fascinating. People talk about circadian rhythms a lot, but the other stuff, I just don't hear much about it. Seasonal rhythms are infradian rhythms. 

Azure Grant: Yeah. The breakdown of language, there's infradian, meaning longer than a day, dia day. Circa-dian, meaning about a day. Ultradian is a little bit more of a funny word, meaning beyond a day. So, in this case, I tend to think about it as ultra-fast, but that's the basic breakdown of language. 

Melanie Avalon: A major question I have about all these rhythms. Where are they stored? Is it primarily determined internally by the various cells in the body? Is it more determined by external factors, like light? What is driving these rhythms?  

Azure Grant: It's a very good question, and it does to a certain extent depend on the rhythm of choice. So, I might focus in a little bit more on the shorter timescales, but these rhythms are endogenously generated and peripherally reinforced. Meaning that systems within the body help keep these oscillations going. But that the body, of course, is listening to the outside world. So, cues like light in the environment, for instance, the length of the day for seasonal rhythm is a big one. Things like temperature in the environment, even things on the timescale of the ovulatory cycle, like the presence of other females or other males in the environment can influence that rhythm. Within a day timescale in certain species, things like the presence of predators in the environment that are maybe out at certain times of day and not others can influence that. So, it's really a combination of both generated within the body and then always listening in to reinforcement from the environment.  

The reason that I think that that's really important is that the goal of our bodies, if we can attribute a goal to them, is to be keeping synchronized with and adapted to the environment. For instance, if an animal wants to keep very well synchronized with the 24-hour, day and night, their body might not have a perfect 24-hour clock on its own, it might have a clock, that's 23 hours and 50 minutes each day. But if that animal or person is constantly seeing the daylight in the morning, and getting food cues at the right time, then their body can be constantly doing these little tunings and little adjustments to keep synchronized with the constraints of the day.  

Melanie Avalon: The peripheral cues, were they the original cause, like the initial 24-hour rhythm, would it have been determined by the peripheral cues? And then it became endogenous evolutionarily? 

Azure Grant: Yeah, I think that's a great question and an idea that that makes a lot of sense. I'm not an evolutionary biologist by any means. When we think about cells in more primordial times and what would have been useful or adaptive for them to do, they would have been looking to when energy was available in their environment for them to take in, metabolize, grow and reproduce. And historically speaking, there's more energy coming into the earth during the daylight hours and less during the nighttime. We can imagine that one of the very early functions of clocks, so clocks in bacteria, clocks in organisms that would then photosynthesize, would be enabling processes to occur within the cell that enabled energy capture during the day, and quiescence or repair during the nighttime. Although it's been a very, very long geologic time from then to now.  

We're now exquisitely adapted not only to the fact that there's more energy around during the day, but that we're surrounded by organisms that are all on their own clocks, trying to adapt to the needs of their environment. Whether we're avoiding predators or seeking out the coffee shop that we want to go to at the time when it opens right in the morning, we're constantly making these adaptations of trying to adjust our physiology to our environment. That process of adjustment is continual and it's one of the battles that I think we all go through socially today, in terms of trying to adjust to a really rapidly changing environment that tries to keep us turned on all the time, even though our bodies expect to have these very stable, rhythmic periods of activity and rest. 

Melanie Avalon: I feel like especially in the biohacking world because when you see the biohacking universe, it can seem like, “Oh, it's all of this technology to try to do something that is beyond normal human experience.” But I think so much of it is literally just trying to return our bodies to that natural rhythm that we're accustomed to. Like tackling your blue light exposure, your sleep, like it's really just trying to mitigate our modern environment to go back to that original rhythm in a way. 

Azure Grant: Yeah, I agree. I think that's a really great perspective and really well put. This is one of the things that I really love and resonate with about the self-tracking community is that, it's not necessarily about trying to overcome the limits of biology, but it's more about trying to have a deeper understanding of one's own physiology, and then learn how to more optimally work with that, so that we can be healthy and accomplish the things that we want to accomplish. 

Melanie Avalon: The menstrual cycle and all of those rhythms, a question I actually get a lot from listeners is, are those rhythms always happening? Even if you don't have a cycle or postmenopausal or they only when you have active, certain hormones happening? 

Azure Grant: That's a great question. A little bit about the menstrual cycle in general. Most of us had a health class at some point, even though it might have been a while, where we're shown this picture of curves of estrogen and progesterone and LH across at an approximately 28-day window, and we're taught that earlier in the cycle in the follicular preovulatory phase, estrogen undergoes this rise and then a fall, triggering a surge of the hormone, luteinizing hormone, and LH which then, hopefully, but not always triggers an ovulation. Then there's a big hill of the hormone progesterone and then estrogen and progesterone fall off at the end, and we get a menstruation again. This curve is often all were presented with about the menstrual cycle early on, and we're often presented with it in maybe a way where we expect it to be not very variable, and maybe not necessarily affect other systems.  

One thing that was very interesting for me to learn back in the day was that this oscillation of hormones is not only impacting reproduction, it's also impacting heart rate, heart rate variability, body temperature, metabolism, even mood and cognition as people are finding out more recently. When I spoke earlier about how our bodies comprise coupled oscillator systems at multiple timescales across the body, that really applies to the menstrual cycle as well. So, it's not only a change that affects reproduction, but it can affect many, many things in our lives.  

When you ask, if a person doesn't have an ovulatory cycle, for any number of reasons, whether age related or choice related, that is a very open question in some regards, but it does appear in many cases that in the absence of an ovulatory cycle, some systems may possibly remain on that rhythm for a little bit, but that over time, those systems may decohere and lose that, that timescale of oscillation. And that's something that we've seen borne out in some peripheral metrics, especially body temperature. And that seemed to be borne out in other systems as well, but I think the question that you're asking is, is very much a topic that needs to be studied more at each particular stage of life or under each particular condition that results in the absence of an ovulatory cycle. 

Melanie Avalon: So, it's possible that if a person is on hormonal birth control, that is completely affecting that cycle, that they might be losing some of those rhythms? 

Azure Grant: Absolutely. Hormonal birth control is a really interesting example. If you're thinking about something, like, imagine implant that delivers a tonic dose of something a progestin progesterone analogue, that is going to prevent the person from ovulating. If you look at their continuous data, it does most often prevent that person from having an ovulatory cycle in the typical fashion. We still don't know a ton about, maybe there's still some system in the body that is keeping time in the background, but because the body is listening in for those approximately monthly oscillations of estrogen, progesterone, LH because it's listening in for approximately monthly oscillations in the receptors of those hormones. Once that's not happening anymore, for whatever reason, including the tonically high dose of progestin, then other systems may have really lost that time keeper. It's not impossible that there are other contributing time keepers to the system that are not as well identified yet, but from what I've seen so far in the cases of contraceptive use, it does seem like it's a fairly effective way to remove ovulatory cycle associated oscillations across systems, at least in terms of heart rate, heart rate variability, temperature and blood glucose. 

Melanie Avalon: Because I'm just thinking more, because I think when people are trying to really get a grasp or an understanding of their cycle, oftentimes we just focus on the hormone levels. But it sounds like because of all of these rhythms, like there's so much more than just the reproductive hormones, like the hormones could be a certain level, but there are all these other systems that are listening in or adapt to it accordingly beyond just the hormones. 

Azure Grant: Yeah. It's a little bit like, if you think about a spiderweb, and you poke one part of it, say that poke is adding hormonal birth control to a system, that isn't only felt in that one part of the spiderweb. It resonates throughout the network, and has ripple effects. And those ripple effects are something that are under study, but that there is much more to learn about, but it's very difficult to impact one system in the body in isolation and not expect there to be affects in other systems as well. 

Melanie Avalon: Just in general, the clinical literature, what do you think are the implications of so much of the literature being done on males compared to females, and how these rhythms might be affecting things?  

Azure Grant: Yeah, that's a great question, and I think very much an ongoing issue. Irv Zucker, who's one of the fathers of circadian biology was professor at UC Berkeley and was around when I was on campus, a very sweet guy and very dedicated to this particular cause of arguing for the inclusion of female subjects and women in clinical trials in research more generally, and he fought for this for a very long time, and continues to do so. Actually, help succeed in getting it mandated that women be included in clinical trials, which is fantastic. What's the result of for a very long time, women not being included in research?  

One of the arguments for this originally was that, “Oh, because females have an ovulatory cycle, that must make them very variable. And we want to reduce variance from outside causes in our studies. So, we should probably only use males.” The funny thing is that when you look across many different systems in the body, males tend to be more variable, or at least as variable in a great number of systems and encourage listeners to look up some of Irv’s papers with Brian Prendergast or Ben Smarr or others, Annaliese Beery on this topic, because they're really fascinating. And they do make one question, this idea that women are more variable because it doesn't necessarily seem to be the case.  

In fact, to the contrary, the presence of the ovulatory cycle seems to impart a very predictable variability. Even if different systems are oscillating up and down, they're doing so in a way that one can learn to anticipate, and therefore adapt to over time. Whereas in the absence of that timescale of oscillation, males can often be a bit more variable on a fast timescale, or perhaps in a less predictable manner. So, my hope is that in the future, this trend continues, and I think we've seen a lot of progress across my lifetime, in terms of greater inclusion of women and tailoring of more products and services to be able to serve this underserved majority of the population. But I think where my brain goes, is trying to look forward to other underserved portions of the lifespan. For instance, pregnancy is a time of life, during which many pharmaceuticals are not yet tested, during which we still need to learn a lot about how different systems are working compared to the nonpregnant state. And that's only the tip of the iceberg. There's a lot in science that needs an extreme amount of diversification that I really hope, we're able to achieve, in part through doing work that involves wearable sensors at scale, in part through really making an effort to provide more education to people and more participatory research opportunities. So, yeah, it's been really interesting to see and learn about this issue and how researchers have approached trying to argue for inclusion of more diverse populations in research. 

Melanie Avalon: First of all, thank you so much for what you're doing. I'm so passionate about this. For listeners, we'll put links in the show notes to all the studies that Azure has worked on. But speaking to that the pregnancy, one of your studies was talking about like the fertility window. What have you found in your research on predicting the fertility window for normal everyday people? The way it's done historically and the potential future of it. 

Azure Grant: Yeah, absolutely, so one interest that I have held for a while is in the interactions between the autonomic nervous system. Thinking about outputs like changing heart rate regulation, changing heart rate variability interaction, thermoregulations of body temperature outputs, and then reproductive hormones. Something that many listeners will have probably heard of over time, is that one can use an oral thermometer in the early morning, and if you're careful and do this at the same time, consistently every day you can see a pattern emerge across your menstrual cycle. What that pattern is, is lower temperatures during the follicular or preovulatory phase and then elevated temperatures after ovulation.  

The reason that that is thought to happen is in part because estradiol has some substrate in the brain to directly help cool the body and progesterone in reverse in combination with estradiol has the neural substrate to warm the body as well as influence systems like metabolism to increase metabolism a little bit, which also heats you up. This really fascinating pattern was identified over 100 years ago, more or at least recorded over 100 years ago, it's probably been known about for much longer by this Dutch gynecologist Theodoor van de Velde. And he wrote this big long book about how one could theoretically use body temperature to monitor not only the ovulatory cycle, but pregnancy and menopause. This has helped contribute over time to a lot of study in that field, as well as taking charge of your fertility is a book that many people will know about how to use oral thermometry, also called Basal Body Temperature, or BBT, to track the ovulatory cycle. With that background, what have we learned by using more continuous, rather than once per day metrics to try to understand something about fertility.  

One of the challenges with this, over 100-year-old technique is that it doesn't provide predictions about the future, at least it doesn't provide very accurate predictions about the future. It can tell you pretty roughly, when you've ovulated in the past, it can tell you when you're likely to no longer be fertile, because about 24 hours after ovulation, one is much less likely to be able to get pregnant as opposed to the approximate week leading up to ovulation. Although that's a pretty variable window. If you're an individual going about your daily life and wanting to know, “Hey, when am I going to be able to get pregnant next week? Should I try to conceive or should I try to avoid pregnancy?” Only having tools that accurately can tell you about your past is not as useful. It's a bit like having a weather report that tells you it was raining yesterday, is not going to help you plan your vacation for next week.  

One of the things that I was lucky enough to get to work with some really amazing people with in graduate school was trying to use continuous data to create tools that would allow us to make accurate predictions about future fertility within a given cycle. And so that's something that we were able to do was to say, if we look at patterns, within a day, biological rhythmic patterns of body temperature and heart rate variability, we can, in essence, see when the preovulatory luteinizing hormone surge is coming. Theoretically, if this were validated and extended in larger and more diverse cohorts, to be able to say, “All right, we're going to tell you that in the next few days, you're likely to have an LH surge, which means, within the next few days after that, you're likely to ovulate.” And this would be giving a person much more time, ahead of time to be able to understand when they're likely to be fertile, and then to plan accordingly in their lives. And then to do that without necessarily having to take a urine-based hormone test, or remember to take an oral body temperature, and hopefully this kind of thing could be done in the background, such that a person could be receiving an alert or having a more passive manner of tracking. 

Melanie Avalon: So, I've never done any of the personal body temperature fertility tracking, like how big of a surge, is it in body temperature? Is it like a degree? 

Azure Grant: That's a great question, and it actually depends on the location of body that the measurement is taken from. So, within the mouth where these measurements have historically been taken, it can be about a degree, maybe a little less, so it's not a huge fluctuation, and the magnitude of that fluctuation can depend on the person, can depend on the weight gain or weight loss. But, yeah, in general, it's quite a small variation. Within other parts of the body, so say the finger, the wrist, the abdomen, the core, a sensor that is ingested or recorded from somewhere within the body, the magnitude of that change can vary a little bit. 

Melanie Avalon: I feel that also speaks to the massive importance of constantly, I don't know if it'll be latitude or longitude, constantly tracking body temperature, in one area, like with an Oura ring or something over an extended period of time, so that can learn what a surge actually looks like in the context of that person's entire body. Just wearing things like a CGM, for example, or my Oura ring. It's becoming clearer and clearer to me each day, how a single snapshot of testing something could give a really potentially misleading picture about everything, like when you don't have the context of how things are changing. 

Azure Grant: Absolutely. People often talk about this as, if you were to turn on the radio for 10 seconds each day, you might get a sense of like, “Oh, who might be speaking, or maybe I heard a few words and can hear whether the context sounds good or bad.” But you're really not going to know what the story is, as compared to if you listen to the radio all day long, every day, you're going to learn a lot more. And I think the same is can really be said, of continuous metrics, whether it's glucose, body temperature, heart rate, hopefully more of our hormones in the future, or whether it's single time point metrics. The finger-prick glucose tests, the oral thermometer, the quickly taking your pulse at the doctor's office, having the opportunity to see each metric from the body as a signal, rather than as a single number completely changes how you can interpret, learn, and make predictions for the future, based on that output. 

Melanie Avalon: Speaking to that, a lot of people will just get an annual checkup, for example. So, they might get one blood test once a year, showing everything at that one moment in time, and the conclusions they might draw, it could be so many different things. One of your papers, you were talking about how cholesterol changes throughout the day. Honestly, that paper blew my mind. It's one of the things, I think it's going to stick with me for the rest of my life because there's so much debate out there about cholesterol levels and LDL and triglycerides and HDL, and this paper, maybe you can elaborate on it a little bit the work that you did. Looking at how those levels fluctuated throughout the day in different individuals, and how did it fluctuate? It was very surprising to me. 

Azure Grant: Absolutely. I appreciate you reading this. This topic actually was a big surprise to me when I learned about this as well. I'd grown up with the idea that you go and get your cholesterol checked at the doctor's office, and then you learn whether you have high cholesterol and whether you're likely to get heart disease and then if your cholesterol is too high, you get put on a statin, it lowers it back down and end of story. And then over the course of this project that generated the paper you referred to, which was done in concert with the quantified self-community as a participant led project, was a really amazing group of people I was lucky to work with. We ended up collecting cholesterol data from finger-prick assays at times all across the day including some very dedicated participants, including Steven Jonas and Ben Smarr, and many others who took these measurements every single hour of the day. We learned that cholesterol as you might expect varies on time of day that had been reported a bit in literature previously, what we learned most was that cholesterol could actually cross risk categories within a single day.  

Although this is something that, I think, is part of medical knowledge, it is not something that an individual is necessarily going to know when they go into to get a blood test. Cholesterol and triglycerides are higher in the afternoon hours than they are in the morning hours. Almost every individual or maybe it was even every individual in this cohort crossed at least one risk category. Say from healthy to moderate risk or moderate risk to higher risk across the course of a single day. Meaning that if that individual had gone into the doctor 3:00 PM versus 8:00 AM, they might have received different feedback about whether they needed to start taking medication or whether they needed to be concerned about these test results. Put into context for a lot of us in the study, including people who had been given that kind of feedback from clinicians in the past, that time of day matters, that single time point assays can give very different results depending on when they're taken.  

One of the most fun parts about this study was, because it was a participant led research project. Each individual in the cohort came to the project with a personal question or hypothesis that they wanted to answer in the course of the study, and we got to put a couple of those case studies into the manuscript overall. One had to do with how do triglycerides coordinate with self-perceived hunger over the day, as you might expect, triglycerides fat in the blood go up after you eat a nice fatty meal. When this person was hungry, their triglycerides were low, when this person was feeling nice and full, their triglycerides were relatively higher. And they made this beautiful chart of perceived hunger and trigs across an entire day where you can see both the circadian and these interacting ultradian rhythms.  

And beyond that, another participant tracked cholesterol across her menstrual cycle and showed this lovely curve where there was actually a really marked change from like about 170 to 220 over the course of her menstrual cycle that she had not previously been aware of, but that would impact the feedback she was likely to get from her doctor, depending on the phase of cycle that you would go into the clinic. So, yeah, it was a really interesting process, not only to see the scientific data, but really to put it in a personal context for each of the participants. To hear their stories and feedback about how this information would influence what they thought about the feedback that they received at a clinic would influence maybe when they chose to go into a clinic, and really made everyone think about the historical context for how risk categories were determined, and how treatments were designed to treat population averages rather than specific individual needs. We're at this interesting point of time, where we finally have enough data to really start to understand an individual's experience, but we don't have enough scientific knowledge at an aggregate level about those types of individuals to be able to create as targeted treatments as we would maybe like. It was a very fun bleeding edge type of project. 

Melanie Avalon: Yeah, because that was one of the notes I wrote down from it was that every participant at some point crossed into a risk category based on the time that it was taken. So many times, there are studies that gets sensationalized in the media, were like these crazy headlines. And you're like, “Is that actually what the study said?” But honestly, I feel you should submit this study to a PR firm, because I want everybody to know this, people get very, very fixated and concerned about their cholesterol panels. And like you said, people get put on statins, and just the implications of this that had they taken the test at a different time that day, it could have potentially been a very different picture. It's very confusing, though. Having done that study for you, personally, if you were to get a cholesterol panel, having this knowledge, how do you personally interpret your own data, when you get a cholesterol panel? 

Azure Grant: That's a really great question. The whole topic was really a rabbit hole into-- there's a lot of discussion about the interpretation of cholesterol and what it means for heart disease and what kind of particle are you looking at size wise and how do you treat it? These are very active, ongoing discussions that that definitely, I think, outpace what we're commonly told as individuals about how to think about these metrics. I don't want to indicate that this is the only thing talking about this. It's far from it was a small study, but it really did open our eyes into this whole world that these arguments are happening.  

It's one piece of context that I would bring with me when I go to the doctor and I get a single time point metric, because I do know that when these risk categories were established, for instance, that they were established on data points taken from people at multiple phases of circadian rhythmicity, and multiple phases of ultradian rhythm, and they weren't perfectly controlled in this manner. There is a sense in which risk is calculated based on having a sufficiently high level at any time of day or under any condition. But I think what it mainly brings home to me is to not necessarily make my decisions based on any single one measurement, if that measurement isn't in a very crazy high-risk category, and also to try to work with a clinician who has an understanding of variability of health metrics over time and who is willing to have a discussion with me about interpreting the finding. I think that's really the most important thing to me, is that the more I learned, the more it stresses needing to have a close relationship with a caretaker and to be able to discuss new findings as they arrive. 

Melanie Avalon: I love that so much. And, yeah, I hadn't even thought about what you just said about the implications, looking backwards at the conclusions that we've drawn about health based on all of these population studies. Now we know that maybe there are different potential readings that could have happened. I guess the trends would probably still emerge, but it definitely begs for a more nuanced picture of just everything. 

Azure Grant: The more we learn, the more we have a grain of salt to add to interpretation of past findings. I think that really can have some positive effects for many people in terms of encouraging individuals to gain more health literacy, do more self-monitoring, and hopefully, in the future, have more resources allocated towards giving people a more in-depth health education, training more literacy skills into the population, even training people on how to use the scientific method in an everyday sense to reason about their own health. So, yeah, I think it points out a lot of ways in which we could improve and provide better for one another as a society. 

Melanie Avalon: The other note I took from it that I thought was so, so interesting was that HDL was the one factor that didn't seem to significantly change based on time.  

Azure Grant: Yeah, HDL was a little bit more variable based on individual. I also don't want to over interpret based on the results of this one particular test can give, because now, there are a lot of different categories of particle size, that that one looks everything from very low-density lipoprotein, VLDL, to LDL, to HDL, even more dense categories. What I would take away from that is, I think it would be very interesting if it has not been done already, to do this kind of time-of-day analysis, looking at a full breakdown of particle size, and then to try to really understand specifically, what the circadian dynamics are of regulation of each one of these outputs. 

Melanie Avalon: For studies like that, did they take finger pricks every hour? How did they test it? 

Azure Grant: These were finger-prick tests, as you can imagine, these were very dedicated participants. 

Melanie Avalon: Oh, my goodness. As far as people getting more actively involved in research studies, is there a platform or a way that people can do that? Or, how do people get more involved in things like this? 

Azure Grant: It's a very good question. Well, I would say, many more opportunities have emerged over the past, call it decade, and especially within the past five years, for people to get involved in research projects of interest, or to find communities of other people who have similar personal questions that they want to answer with their own health data. The quantified self is a community of people founded in the Bay Area, a little over a decade ago, and has grown into a global community since then, that was my introduction to the world of self-tracking, and the world of trying to develop a participant-led research methods. But there are communities all over the world that patients like me, clinical groups one in San Diego called Project Apollo that I'm a big fan of, Bioloop Sleep, there are a ton of these out there. I'm only mentioning a few that I'm thinking of off the top of my head. Citizen Science Alliance, Open Humans, there really are a ton. I think even things like platforms, such as meetup.com have enabled interest groups to find each other and to try to figure out how to coordinate on projects of interest.  

This is really an ongoing question of, there isn't one single platform to my knowledge that serves the purpose of connecting people interested in creating participatory research projects on any topic, and that really provides the skills and resources to get those to happen, I think, it's still a rapidly changing and growing field that I hope more people become interested in and that I particularly hope can be more integrated into education. 

Melanie Avalon: Now I'm just thinking, I'm like, “Future business endeavor here.” Start a centralized platform to connect researchers to participants, that would be so cool. 

Azure Grant: Oh, absolutely. I don't want to downplay, many people are working really hard at solving different parts of this problem. The platforms that I mentioned are, they're doing some really amazing things to try to break this problem of trying to create a new form of research that involves people in each stage of the scientific method, and that is really far more directly benefiting participants than traditional research has been. It's a really big, tangled, interesting problem to tackle that's going to take a lot of different iterations to make progress towards. I'm really encouraged by the progress that is happening so far. But absolutely, no, I think there will be many more companies in this space and hopefully a lot more investment in it in the future. 

Melanie Avalon: I'll put links in the show notes to all of those ones that Azure mentioned. Maybe people can check them out and get more involved. What was your Q cycle study? Was that anything that you talked about already or is that something different? 

Azure Grant: The Q cycle study is related to what we talked about earlier in terms of using content continuous temperature and heart rate variability rhythms to anticipate when a preovulatory LH surge is likely to occur. We talked a little bit about it, but I can give you the rundown on it if you would like.  

Melanie Avalon: Sure, yes. 

Azure Grant: As I said, my research interests are in network physiology, the study of coordination among different systems in the body and time. The subfield that I focused in has brought me into female reproductive health, focusing on how thermoregulation, say, body temperature, autonomic nervous system and the reproductive system interact. It turns out that these systems appear to be very closely coupled and actually to help regulate one another for within the brain, in particular, in the hypothalamus. That concept is one of the things that helped motivate the creation of Q cycle.  

Q cycle was a study that grew out of having been lucky enough to have the chance to work with quantified self, and having met a really impressive group of people interested in monitoring the ovulatory cycle, pregnancy and menopause using time series data from wearable devices. I actually met a lot of these people through the cholesterol study when I was getting to work with QS full time. So, I ended up proposing a study in grad school about investigating continuous temperature, heart rate, heart rate variability and reproductive hormone patterns across the female lifespan. We hypothesize that those close interactions could enable a person to make predictions and assessments of their reproductive status.  

For instance, having an LH surge, about to hit menopause, pregnant, without necessarily measuring any hormones at all, purely from analyzing features of temperature and cardiac output. This hypothesis was intriguing to us and was based on a lot of historical work in the field of ultradian rhythms and coupled oscillations. We got to form a cohort of self-trackers interested in monitoring their own reproductive health and develop a project that would enable everyone to collect data of personal interest while contributing to this larger group wide research question of, “Could we anticipate when LH surges occur?” Which is the paper that we ended up putting out last year, was an individual that was menopausal differentiable from individuals who was premenopausal, and then what does pregnancy look like was a question we ended up following up on later.  

The Q cycle study was very enjoyable because, A, everybody that was a part of it was an individual who really wanted to learn about their own reproductive health and who came into the study with some kind of question or motivation that they wanted to answer using the study data. We got to work closely together not only to collect that data, but also to develop questions, develop individual analyses, and to correspond and do things like share papers back and forth to try to understand what we were seeing, and ended up getting to communicate for years about this and a lot of these people, we still keep in touch. It was very satisfying from a scientific point of view and from knowing that we got to watch each other learn along the way. And that really reinforced for me an interest in the process of what we call participatory or in its most extreme form participant-led research. It very much helped with being able to interpret the data to know each individual's personal context surrounding that data. 

Melanie Avalon: Are you actively communicating or working with Oura with their developments with all of this? 

Azure Grant: Oura was actually very helpful for that particular project, because they donated the devices that were used. So, yeah, they had been very helpful, they developed this very cool device. I don't actually work for them, but I have had a lot of experience getting to know them over time, and I think they're at this interesting point, as a company where they have a lot of extremely valuable data. And I think one of their best qualities, historically, has been a willingness to openly share their raw data and their raw minute by minute time series, with researchers for the purpose of making new discoveries. And that is a really rare and precious quality that companies don't tend to preserve over time. That was fantastic. And they did go on to serve projects, one was called TemPredict run by Ashley Mason, Rick Hecht, and Ben Smarr, and others to study COVID and sickness throughout the pandemic. They also had donated some retrospective data about pregnancy for research and are involved in a lot of exciting projects. My hope is that that continues. 

Melanie Avalon: Is it individual users data or is it anonymous data? 

Azure Grant: Oh, that's a good question. The point I was trying to get across is that over the course of their being a company, they have been part of some really exciting academic collaborations, wherein, Oura users can opt in to participate in a study and share data with researchers for the purpose of scientific discovery. I think that process of academic public collaboration is super important and can also be quite rare, especially when the goal is to rapidly turn around findings that are shared with the public in an open and validatable, verifiable manner. I don't know what they do, I'm an outside academic person, but the hope is that it's limited things of a Big Brother nature. 

Melanie Avalon: Yeah, same here. Actually, everything that you just said, that's what I really saw when COVID happened, and yeah, they were asking for people who wanted to participate in a certain arm with a data and a lot of my listeners did that. I thought it was really cool, and they've talked about a lot in my Facebook group. So, I agree. That was one of the first things I thought when I saw them doing that with COVID. I was like, “That's so cool.” It's very forward thinking and it's very present. It gets people involved, like right now, which is something that you don't really experience. I haven't experienced with any other wearable device or biohacking thing. I think, it's really, really promising for the future of wearables, of what we can learn about everybody about science and health conditions. So, I think it's a really great thing.  

Azure Grant: Yeah, I'm super proud of and impressed with the researchers working to make that happen and make those collaborations work, because it is the kind of thing where when we look at the Apples and Fitbits of the world and say, “Hey, there's all this data, why is this not serving individuals more?” It gets very caught up in all these ideas of, how can the business protect itself for as long as possible and their growth, and there's a lot of secrecy involved, and a lot of things that are at odds with the practices of academic research. I think it's very inspiring to watch private-public partnerships that try to maintain the integrity of the scientific process, and that try to also ensure they're giving back in a prompt and open manner, something to the individuals that are generating that data, because that's a very core principle to many members of the self-tracking community and many scientists. When we generate data, whether it's from a wearable device or from web browsing that that's our data from our bodies, and that we are owners, or at the very least co-owners of that information. Finding partners that that uphold that kind of standard is a challenge, but it's great to see when there're examples of that succeeding. 

Melanie Avalon: Also, in the wearable world, and a topic that we haven't dived into yet is, glucose and insulin and diabetes and metabolic health in that regards. I'm also the host of the Intermittent Fasting Podcast and so I get so many questions about blood sugar, insulin. Most people, it's something we talked about already, they are really going off of the snapshot picture that they get that one time they go to the doctor's office. Especially with blood sugar wearing a CGM, it's really eye opening how much blood sugar changes throughout the day. But you've done interesting research on the rhythms of insulin and blood sugar control and diabetes. I was wondering if you could just tell us a little bit about what you found in that sphere. 

Azure Grant: Absolutely. This actually ties back again to the quantified self-community, and someone named Dana Lewis, who's-- I'm not even sure what to call her, amazing person, but a combination of researcher and communicator and community leader, many, many other things. But Dana is someone who I met through quantified self who has had type 1 diabetes for a long time. For those of you that don't know type 1 diabetes, happens when an individual is no longer able to produce their own insulin, the hormone that regulates blood sugar within the body. When an individual can't produce insulin on their own, they have to take it exogenously, so from an outside source, and that means that they're having to find a way to replace a very key hormone in the body all the time for the rest of life.  

One thing that Dana has been very integral to, is to trying to build artificial pancreas systems. So basically, a robot outside of the body that delivers insulin in an intelligent manner that is more coordinated with the body's natural and meal-induced oscillations in glucose and provide a healthier manner of regulating blood glucose over life, and therefore improve the health and the quality of life of people with type 1 diabetes. So, I met her through quantified self and we ended up writing a grant together, and wanting to study some large-scale blood glucose datasets, including ones generated from her “do it yourself” artificial pancreas system OpenAPS and the Nightscout service, because there remain a lot of open questions about what did the patterns of glucose and insulin administration look like in diabetes? How do they change based on the method of administering insulin and how do they change across life by male or female, by exercise status by all kinds of things? It is one of these worlds where now that you have the continuous glucose monitor, and the data from an insulin pump, and you can get every few minutes time series of these outputs over many years. One can spend a whole career investigating just questions from those datasets.  

We felt very lucky to have the opportunity to do some initial explorations in glucose and insulin data in their biological rhythms to understand how different strategies of hormone replacement impact metabolism. 

Melanie Avalon: Is that what insulin pumps are or is that something different, this pancreas outside the body? 

Azure Grant: Yeah. That's a good thing to breakdown a little bit. An artificial pancreas system allows a continuous glucose monitor. Something that has a little needle that sits in the interstitial space and samples glucose every few minutes, allows that device to communicate with an insulin pump, which is taking a reservoir of insulin sitting outside the body, and that is able to inject it into the body in a programmable fashion. Prior to the existence of these devices, what a person with type 1 diabetes would do, would be to manually measure their blood glucose with a finger-prick assay, do a series of calculations based on, for instance, if they had just eaten something, how many grams of carb were in that meal. Based on many years in most people amassed of knowledge about how do they tend to respond to meals and tend to respond to different amounts of insulin. And that person would make a decision about manually how much insulin did they want to inject to manage that blood sugar and try to keep it within a healthy range if possible. If we think about that, that process seems incredibly difficult.  

In practice, people with type 1 diabetes end up being at risk for other endocrine and metabolic health problems across life, including the subsequent development of type 2 diabetes. The purpose of an artificial pancreas system is to take that process of listening to how much blood sugar is currently present, to listen to how many grams of carbs or other food items a person has ingested, to perhaps listen to the activity that that person is carrying on throughout the day. Are they on a hike or are they sitting down? And to integrate that into a calculation about how much insulin to provide and I think these systems are only going to become more integrative over time, take in more information about that person, and be able to perform better and more precise calculations. Hopefully, something along that line can be doing calculations that enable assessment of that person's biological rhythms, and to be able to help reinforce and maintain things like ultradian, circadian, and even longer timescales of rhythm. Those are questions that we're just beginning to address, and that I'm very excited to see where they go in the future. They also have really strong implications for hormone replacement therapy and other systems like the reproductive system.  

Melanie Avalon: Ooh, that's exciting. That's very cool. And just hearing you say that about historically how type 1 diabetes use insulin, and especially now having worn a CGM myself and seeing how much blood sugar fluctuates, that's scary. That's like just shooting in the dark with the insulin. That's overwhelming. 

Azure Grant: In some ways, yes. One of the things that it makes me be appreciative of the most, is the massive amount of practical knowledge, intuition, technical information that people with type 1 diabetes have to integrate across every single day of their lives. These people are very highly educated and trained, really have to pay attention to themselves. I find that level of knowledge extremely impressive. And, yes, practically we have seen that people that use more traditional therapy types have poor blood glucose regulation, than people who are using what's called a Hybrid Closed Loop or some kind of artificial pancreas system. It's definitely a combination of a lot of human intelligence with hopefully taking some of the simpler decisions about that very complex regulatory process and automating them, so that a person has a bit more freedom in their daily life. 

Melanie Avalon: Actually, I'm just thinking about that more because it's true. It would make a person what type 1 diabetes going through that method, they must become really in tune with our body, which is a good thing. I'm just thinking now about how many things we do. It's not to that level of type 1 diabetes, where the potential effects could be very grave, or really, really significant. But people take supplements, really, and things like that and never really test anything. It's just really interesting the things we do and how we interpret our experience of the world. It's really interesting. I always wonder what the data is actually looking like. For listeners, though, if they would like to get their own CGM, because Azure, by the way, do wear CGM often or how do you feel about CGMs? 

Azure Grant: I wore one for two or three months. Oh my gosh, my personal experience with CGM is, I had ghost sensations for months, about was going to knock it off whenever I took off a sweater or something like that? It was amazing data. I was so grateful to have it. I really want to do it again. But at the same time, it gave me much more sympathy for people who do have to wear these all the time because there is a downside to having a needle in your arm 24/7. 

Melanie Avalon: It's really, really eye opening. When I first used one, I got really addicted and I wore one for a few months and then I was like, “Okay, no more.” But now I'm back. I've been wearing one again recently. I have one on right now, actually. For listeners if you'd like to get your own because, historically, there was a huge wall. We really had to have a prescription or be diabetic to get a CGM. But now there are companies that are like, we've been talking about throughout this show, bridging the gap. So, you can go to melanieavalon.com/levelscgm, that will let you skip their waitlist and get a CGM or you can go to melanieavalon.com/nutrisensecgm. The code MELANIEAVALON will get you a discount on their CGM. So, that's some resources for people.  

I have a very specific granular question, all of the different rhythms that we've talked about, because we've talked about how all the different processes could affect each other. Are there any rhythms that are completely independent and not really affected by external factors that you know of? And then I have like a second part question to it, are all of them interconnected? 

Azure Grant: That's a very interesting question. I think different people may answer it differently. But to my knowledge, all the timescales of rhythm that I am aware of, in an intact organism, do have some way of taking in information about the environment, and then integrating it into the output of that system, at least when we're talking about organisms, like complex mammals or humans in particular. It is true, these are actually very interesting, there's KaiA, B, and C. These molecules that if you will put them in a test tube, they will generate oscillations all on their own, and they can just sit there oscillating. 

Melanie Avalon: What are they? Are they things on our body naturally?  

Azure Grant: No, they're not actually mammalian at all. Susan Golden is a very cool researcher at UCSD, who's studied the circadian rhythms of cyanobacteria for her career, and part of that is looking at these KaiA, B, and C is what these things are called, where if you put them together in a test group, they can just generate these oscillations all on their own. And she's a really impressive, interesting researcher. So that is to say, there are systems where, through transcription, translation feedback loops in mammals or molecular interactions, oscillations can be generated and independently sustained. However, when we're thinking about an organism, like a human or another mammal, these systems are very much evolved to whether you're thinking about a very short neural timescale of milliseconds or whether you're thinking about seasonality, there's a strong component of taking in information from one surroundings in order to influence the speed, the amplitude, the synchronicity of oscillation. I guess, I'm saying yes and no. 

Melanie Avalon: Do you know what the cyanobacteria-- was it in all cyanobacteria are just some species? The reason I'm wondering like, isn't spirulina cyanobacteria? I wonder if my spirulina has its own rhythm. 

Azure Grant: Unless you're harvesting it fresh, I don't think the spirulina that I have, it's a nice blue powder sitting in my cabinet is actively oscillating at all, but no, you're right. Spirulina as cyanobacteria in the genus spirulina. I don't know if they use KaiA, B and C or another form of these molecules. But yeah, you're right.  

Melanie Avalon: This may take the award for the craziest rabbit hole I think I've gone on this show. [laughs]  

Azure Grant: [laughs] I was going to say the tangent you didn't expect, but no, yeah, it's a very good question. 

Melanie Avalon: The second part was, out of all the external factors that affect things, is there one thing that really affects everything, like light or body temperature maybe? Or is it all different peripheral factors affect things differently? 

Azure Grant: I think light is one of the strongest cues in terms of the most studied in the field of circadian rhythmicity and seasonality in particular, in impacting and reinforcing and synchronizing biological rhythms. Temperature is one for humans, it's apparently not as strong of a factor, but it is present. Of course, since you hosted the Intermittent Fasting Podcast, you must have talked about a ton that food metabolic intake and timing of taking in food is a very strong cue to biological rhythmic systems. But I think beyond that, it is important to consider that there are many, many things impacting these systems and social cues are not to be underestimated in our modern environment, any medications that we take, or hormones that we take, or even some supplements like melatonin, of course, is something that's commonly taken. These have a large impact on our biological rhythms as well. 

Melanie Avalon: I've recently been writing a really long blog post. I've been trying to read every single paper I can find on rhythms and how they affect eating. So, ghrelin and leptin and glucose and insulin, it's really hard to wade through because there's definitely this dominating idea that eating early is better, but then it's hard to navigate through that and actually look at the data beyond the bias, and see what's actually happening. On top of that, there's just not a lot of studies that look at people, because a lot of our listeners do intermittent fasting with a later eating window. There's just not a lot of studies that look at late eating with fasting all day. Normally, it's looking at like eating and eating later. 

Azure Grant: Right. It's fascinating and there is this temptation to be as reductive as possible, or to try to generate findings that can then be applied to all of humanity. Although it really does seem like eating earlier in the day is metabolically more manageable. Maybe even in cultures like Spain, where you would traditionally take a nap in the afternoon and then eat quite a late dinner. I don't think we should underestimate human variability and the fact that we have cultures adapted to many different types of eating schedules and environmental constraints. One of the themes that often emerges in this research is, its stability of routine is a really important factor. Even if you find something really strange or off the wall that works for you, if you do that consistently across your life, then that can count for a lot, even if maybe it's not what the average person's ideal time of eating is.  

I'm often reminded of people who are extremely long lived and people ask them, “What's the secret to your long life?” And they say, “Oh, well, every day, I eat my bacon and eggs with a whole lot of maple syrup on them. And that's what I do.” [laughs] Or people who say, “I eat plenty of chocolate.” So, yeah, I think it's both when and how consistently, that play a big role.  

Melanie Avalon: 100%, that's the conclusion I'm probably going to draw. I don't want to make like a blanket statement, but looking at the data, it does seem that early-ish or maybe mid-afternoon eating is most appropriate, especially if it's like an intermittent fasting type pattern., I think that's probably where the benefits lie for most people. I wish I was an early eating person, but I just know I'm not. So, I'm not going to try to force myself into that hole. 

Azure Grant: Yeah, that's a really important takeaway as well, especially once one is in the practice of trying different things and paying attention. So going through this personal science method of trying to understand how different routines impact on an individual basis, is that if you're reading that the average person has something that they should do every day, and you try that and it really doesn't work for you, but something a little bit different does, and that's not something to be easily discounted. 

Melanie Avalon: Exactly. I love that so much. Well, this has been absolutely amazing. Azure, you have so much incredible work that you're doing. Was there any other topic you wanted to touch on, before we wrapped up? 

Azure Grant: Oh, my gosh. This has been so fun to talk to you. You ask wonderful questions and you know so much. I feel we could do probably many of these. I feel this is a really good start.  I feel I could probably talk about quantified self or reproductive health across the lifespan or any of these things, but we've done a ton already. What do you think? At some point, I'll start sounding more nonsensical, if not already. 

Melanie Avalon: No, you've been absolutely amazing. What are you most excited about right now that you're working on? 

Azure Grant: I'm very excited about trying to help build tools for health monitoring across the lifespan for women. Many tools in the field of female reproductive health are targeted towards helping someone get pregnant or helping someone avoid pregnancy, and relatively fewer tools are targeted towards, for instance, helping teen girls understand their adolescence and whether it's going healthily or not, relatively few tools are targeted towards helping people who have fertility issues, very few tools are targeted towards continuous monitoring of pregnancy, and menopause as well as very underserved. One of the things I'm most excited for about the future is, in continuing to create examples of how continuous wearable data could help create metrics that help individuals understand their reproductive health across the entire lifespan, and then be able to make more informed decisions based on it.  

Melanie Avalon: Well, that is absolutely incredible. I cannot thank you enough for it. I can't tell you how many times, I get questions from listeners asking everything that you just said, like wanting to know more how they can learn about that practically in their own lives, and the work that you're doing is really, really painting a potentially wonderful future for getting more clarity with all that. So, I cannot thank you enough. For listeners, we'll put links in the show notes, like I said to all of the papers, but are there any links that you'd like to put out there for listeners to follow your work? 

Azure Grant: I will probably share a Google Scholar or website. Could I follow up with you via email maybe with a couple links? 

Melanie Avalon: Yeah, that'd be great. For listeners, we'll put in the show notes all of the links that Azure has. And, yeah, this has been absolutely amazing. So, the last question, I actually ask every single guest on this show, and it's just because I realize more and more each day how important mindset is. What is something that you're grateful for?  

Azure Grant: I'm very grateful, especially after going through as we all have, the COVID pandemic, for the people that I know, and I'm getting to reconnect with a little bit more now. The fact that there's something that we can learn from everybody that we talk to, and I'm really grateful for the kindness and intelligence of my friends and family and mentors, especially finishing up a PhD right now and getting to move on into the world. I'm feeling very inspired by the researchers and friends and folks like you that I get the opportunity to talk to you and learn from. So, thank you very much for having me today, and for your wonderful questions and for letting me learn from you. 

Melanie Avalon: No, thank you. Thank you for letting me learn from you, and thank you so much for being here. Again, everything that you're doing, and I'm going to eagerly follow all of your future research and we'll have to bring you back in the future with more updates on all of the things that you've learned, because this has been absolutely incredible. 

Azure Grant: Well, likewise, I'm looking forward to hearing some of your new podcasts that keep coming out. And it's been very lovely to talk with you. So, thank you so much. 

Melanie Avalon: And congratulations in advance on submitting your dissertation today.  

Azure Grant: Thank you. [laughs] Thank you so much.  

Melanie Avalon: Thanks, Azure. Bye. 

Azure Grant: Bye. 

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