Mean corpuscular volume (MCV) is one of the 10 variables included in the biological age calculator, PhenoAge (see https://michaellustgarten.wordpress.com/2019/09/09/quantifying-biological-age/). It’s calculated by dividing the fraction of the blood that contains RBCs (hematocrit) by RBCs (MCV = hematocrit/RBC), thereby identifying the average volume contained within red blood cells. Although the MCV reference range is 80 – 100 femtoliters (10^-15L), what’s optimal in terms of a youthful biological age, and minimized disease risk?
MCV increases during aging. In support of this, using a small subset of samples from the Baltimore Longitudinal Study on Aging (values not in parentheses), MCV increased from average values of 88.8 in young (18-39y), to 91.3 in middle-aged (40-59y), to 92.4 in old (>60y) subjects. Similarly, MCV also increased in the full sample size from the Baltimore Longitudinal Study on Aging (values in parentheses) from 89.2 to 91.1 to 92.9 in young, middle-aged and old, respectively (Araki and Rifkind, 1984):
In a larger study that included 3,358 subjects, MCV increased from median values of 92.2 in women and 93.4 in men younger than 60y to 94.2 and 95.7 in women and men older than 60y, respectively (Lee et al. 2018):
When considering that MCV increases during aging, one would predict that higher levels would be associated with an increased risk of death of all causes. In support of this, in the 36,260 subjects of Yoon et al. (2016), MCV levels > 94.2 in women and > 95.8 in men (Tertile 4) were associated with a 55% and 44% increased risk of death from all causes, respectively, when compared with MCV values between 89.2 – 91.6 in women and 90.5 – 93 in men (Tertile 2):
Collectively, these data suggest that a lower MCV may be better in terms of biologic youth, and for a lower risk of death from all causes. What are my MCV values? I’ve measured MCV 25 times over the past 16 years. In my 30’s, I measured it 7 times, with an average MCV = 90. In my 40’s, I’ve measured it 18 times, for an average value = 91.1. Although these 2 groups of data are not significantly different (p=0.09), the red trendline for these data is slightly up (R2=0.02), which suggests that my MCV is slowly increasing with age:
Although my MCV values are seemingly far from the increased mortality risk of Yoon et al. (> 95.8), it increases during aging, so I’ve definitely got my eye on it. Should it start to increase, I’ll intervene with dietary changes. Stay tuned!
If you’re interested, please have a look at my book!
References
Araki K, Rifkind JM. Age dependent changes in osmotic hemolysis of human erythrocytes. J Gerontol. 1980 Jul;35(4):499-505.
Lee Eun-jin, Kim Mi-young, Lee Eun-yeop, Jeon Beom, Lee Ji-won, Kim Han-sung, Kang Hee-jeong, Lee Young-kyung, Eun Jin Lee, Miyoung Kim, Eunyup Lee, Kibum Jeon, Jiwon Lee, Han-Sung Kim, Hee Jung Kang, Young Kyung Lee.vEstablishment of reference section for general blood test in healthy elderly. Establishing Reference Intervals for Complete Blood Cell Count in Healthy Korean Elderly Individuals. J Lab Med Qual Assur 2018; 40: 27-37. doi.org/10.15263/jlmqa.2018.40.1.27.
Yoon HJ, Kim K, Nam YS, Yun JM, Park M. Mean corpuscular volume levels and all-cause and liver cancer mortality. Clin Chem Lab Med. 2016 Jul 1;54(7):1247-57. doi: 10.1515/cclm-2015-0786.
Michael Lustgarten 
Interesting, but you say that “Should it start to increase, I’ll intervene with dietary changes” Really? What changes? You have a reading audience who may be experience this now. Along with other factors, that may be going the wrong way, such as Sarcopenia, etc.
I don’t think it is helpful to bring these variables without saying what the dietary fix maybe. Especially if you are saying that you’ll intervene with dietary changes, which tell’s me you think you know what those dietary changes may be. Let the rest of us in on it please. I read your blog for info that would help me. Although I am interested in your journey, I am much older than you and won’t be here to see whether you accomplished your goals.
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Hey pete533, the honest answer is that contrary to biomarkers like albumin, and despite dietary data that correlates with that many blood tests, I don’t have strong correlations with MCV, yet. I have another blood scheduled in 2 weeks, so more data will help clarify the situation.
On another note, I’m thinking about removing all my dietary data correlations from these posts, because if I give everything away for free, that isn’t good, either. When I collate all this info into a book aimed at optimizing biological age (coming sonner rather than later), my dietary data and the correlations would be included. But for now, that info is free, as much as I have of it!
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I’m currently training with Apeiron Academy’s epigenetic program, and one thing that’s discussed in the module I’m currently studying (supplements) is that you can tell whether or not a coaching client is taking a multivitamin based on their MCV score — a score over 95 generally suggests the client is not taking a multivitamin (or, not taking a good one).
Generally, it can go up to 100 in people not taking multis, and down around 91 in those who are taking them.
So presumably, this means a good multivitamin is effective in lowering MCV (though of course I can’t say whether this still holds true as we age, or which specific nutrients contribute — speculation is that it’s likely due to B6, B12, thiamine, and/or folate deficiencies). Apeiron generally recommends 1/2 a multivitamin per day for most clients (depending on genetics, etc).
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That’s interesting, Paul. I didn’t see any published literature about MCV and multivitamin use. I wonder where they got that suggestion from. Also, that suggests that some component of the multivitamin can reduce it. Which can?
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Michael — this seems to be just from their own observation that MCV values over 95 correlate very strongly with clients who don’t take their multivitamins, but they haven’t pinned down yet which ingredients make the difference.
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Very interestingly how reduce MCV, my MCV it is 98 now. Im only forty year old.
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Hey Roman, I’d suggest retesting many times in conjunction with diet tracking, and then looking at correlations, to see what you can do to reduce it.
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