Optimizing Biological Age: RDW%

Can biological age be optimized? The red blood cell (RBC) distribution width (RDW%) is one of the variables included in the PhenoAge biological age calculator (see https://michaellustgarten.com/2019/09/09/quantifying-biological-age/). Although the RDW% reference range is 11.5% – 14.5%, what values are optimal in terms a youthful biological age, and minimized disease risk?

First, let’s define RDW%. RDW% is calculated by dividing the standard deviation of the average mean corpuscular volume (i.e. the average volume inside red blood cells, defined as MCV, upper right panel; image via Danese et al. 2015). When the volume inside red blood cells is approximately the same across all RBCs (upper left panel), the RDW% will be narrow, as shown by the dashed line in the upper right panel.  Conversely, during aging and in many diseases, the size and volume of RBCs are altered, resulting in a more broad RDW% (bottom left and right panels):


In terms of RDW%, what’s optimal for health and longevity? In the the largest study  (3,156,863 subjects) that investigated the association for risk of death for all causes with RDW%, maximally reduced risk of death was observed for RDW% between 11.4 – 12.5% (percentiles 1-5, 5-25), with mortality risk increasing for values < 11.3%, and > 12.6% (Tonelli et al. 2019):

rdw 2

This has been confirmed in other relatively large studies (240,477 subjects), as RDW% values < 12.5% were associated with maximally reduced all-cause mortality risk, with values > 12.5 associated with an increasing all-cause mortality risk (Pilling et al. 2018):

rdw 3

How does RDW% change during aging? For the 1,907 subjects of Lippi et al. (2014), RDW% increased during aging:

rdw 4

In support of this finding, RDW% also increased during aging in a larger study that included 8,089 subjects (Hoffmann et al. 2015).

Collectively, when considering the all-cause mortality and aging data, RDW% values ~ 12.5% may be optimal for health and longevity. What are my RDW% values? Plotted below are 18 RDW% measurements since 2015 (blue circles). First, note my average RDW% during that time (black line) is 12.8%, which isn’t far from the 12.5% that may be optimal for health and longevity. However, note the trend line (red), which indicates that my RDW% values are increasing during aging!

rdw 5

How do I plan on reducing my RDW%? A moderate strength correlation exists between my calorie intake with RDW% (r = 0.53), with a higher daily average calorie intake being associated with a higher RDW%:
my rdw
My plan is to shoot for a daily calorie intake ~2600 over the next month, and then retest my RDW% (and the rest of the CBC). Hopefully that brings my RDW% down to 12.5% or less. If that doesn’t work, I’ll re-calibrate, and try something else!

If you’re interested, please have a look at my book!


Danese E, Lippi G, Montagnana M. Red blood cell distribution width and cardiovascular diseasesJ Thorac Dis. 2015 Oct;7(10):E402-11. doi: 10.3978/j.issn.2072-1439.2015.10.04.

Hoffmann JJ, Nabbe KC, van den Broek NM. Red cell distribution width and mortality in older adults: a meta-analysis. Clin Chem Lab Med. 2015 Nov;53(12):2015-9. doi: 10.1515/cclm-2015-0155.

Lippi G, Salvagno GL, Guidi GC. Red blood cell distribution width is significantly associated with aging and gender. Clin Chem Lab Med. 2014 Sep;52(9):e197-9. doi: 10.1515/cclm-2014-0353.

Pilling LC, Atkins JL, Kuchel GA, Ferrucci L, Melzer D. Red cell distribution width and common disease onsets in 240,477 healthy volunteers followed for up to 9 years. PLoS One. 2018 Sep 13;13(9):e0203504. doi: 10.1371/journal.pone.0203504.

Tonelli M, Wiebe N, James MT, Naugler C, Manns BJ, Klarenbach SW, Hemmelgarn BR. Red cell distribution width associations with clinical outcomes: A population-based cohort studyPLoS One. 2019 Mar 13;14(3):e0212374. doi: 10.1371/journal.pone.0212374.

Michael Lustgarten

Ph.D, Physiology, University of Texas Health Science Center at San Antonio, 2009 B.S., Biochemistry, Queens College, 2003 B.A, English Textual Studies, 1994, Syracuse University

11 thoughts on “Optimizing Biological Age: RDW%

  1. Great post, as usual. How fast can you reasonably expect to decrease your RDW ? It seems to me as it could be a long term project, with no significant results visible in the next few months. Also, even with successful resulting metrics, how significant can that be correlated with greater longevity? Thanks for your insight.

    1. Thanks psavignac. I’ve had lower RDW% values (see the plot), which means some combination of diet, exercise, or body weight resulted in that lower RDW% value. It’s up to me to figure out the variables that most influence it. I’m confident I’ll get it to ~12.5%, if not sooner than later.

      In terms of it being a long term project, that’s ok-more data will help determine what influences it…

  2. Great post. I found my RDW tracked with LDL and triglycerides. I added 2 scallops per day to my mainly vegan diet and my LDL and triglycerides doubled to about 130 in about 2 months and my RDW went from 12.4 to 13.7. I track my Phenoage with a an Excel spreadsheet created by John G Cramer using the Levine formulas.

    1. For me, over 18 measurements, there is a weak correlation between RDW% with LDL (R2=0.01), but stronger with TGs (R2=0.20).

  3. Great post Michael, as usual. You might have crossed this already: I normally track MCV but my lab does NOT give RDW. So I have MCV values and relative reference intervals but not RDW. I just wonder if you know about a mean to estimate RDW from MCV. I understand the two are related but I wonder if you know more. It is about using correctly the two values, i.e. MCV and RDW, in Levine’s Phenotypic Age formula. RDW has a larger weight factor when compared to MCV in the formula even if you cannot deduce from that RDW is more important than MCV for biological age.

    1. There is a way to calculate the RDW from MCV, but you’d need the standard deviation of the average red blood cell size, which isn’t provided on blood tests…

      1. Exactly, that is my problem. By definition: RDW-CV = (Standard deviation of MCV ÷ MCV) × 100 (wiki). I thought that from the ref intervals of the MCV I could estimate a SD but obviously not. Anyway, I am using a couple of RDW measurements done in a different lab few years ago but wished to be more precise. Thank you for your reply !

  4. I always wondered about the relative high weight of RDW in Levine’s Phenotypic Age calculator (say when compared to CRP/inflammation). Even if comparison of the various biomarkers needs to be exercised with caution (due to the the weight not being standardized), the clinical impact of RDW seems to be well recognized, which might provide an explication:

    “…Variability in red blood cell (RBC) volumes (RBC distribution width: RDW) increases with age and is a strong predictor of mortality, incident CAD and cancer. In a study of 116,666 UK Biobank volunteers, genetic variants explained 29% of RDW individuals aged over 60 years and 33.8% of RDW in those aged < 50 years [222]. RDW was associated with 194 independent genetic signals (119 intronic), 71 implicated in autoimmune disease, body mass index, Alzheimer’s disease, longevity, age at menopause, bone density, myostasis, Parkinson’s disease and age-related macular degeneration. Pathway analysis showed enrichment for telomere maintenance, ribosomal RNA and apoptosis…"

    Morris BJ, Willcox BJ, Donlon TA. Genetic and epigenetic regulation of human aging and longevity. Biochim Biophys Acta Mol Basis Dis. 2019;1865(7):1718-1744.

    1. Key point: “Variability in red blood cell (RBC) volumes (RBC distribution width: RDW) increases with age and is a strong predictor of mortality, incident CAD and cancer”

  5. Great explanation of the significance of RDW, Dr. L –and Albedo, too! Thank you.

    I, too, was mystified by the high weight given to this marker in the PhenoAge formula. Before finding Dr. L. I had noticed my RDW values were a little low in the range and made a note to do a little research to see if this was a problem. Apparently not!

    Now, although I can see my values have been creeping upward toward 12, I’m reassured and fascinated by this research. I still have no idea what part of my metabolism I have to thank for my relatively low values, nor what actions I can take to sustain them, but it’s nice to know my genes (probably) seem to have it all worked out.

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