Predicting age by mining electronic medical records with deep learning characterizes differences between chronological and physiological age https://pubmed.ncbi.nlm.nih.gov/29113935/
Effects of blood triglycerides on cardiovascular and all-cause mortality: a systematic review and meta-analysis of 61 prospective studies https://pubmed.ncbi.nlm.nih.gov/24164719/
High-density lipoprotein cholesterol and all-cause mortality by sex and age: a prospective cohort study among 15.8 million adults https://pubmed.ncbi.nlm.nih.gov/33313654/
Papers referenced in the video: Chocolate consumption and all-cause and cause-specific mortality in a US population: a post hoc analysis of the PLCO cancer screening trial https://pubmed.ncbi.nlm.nih.gov/34329196/
Short-term administration of dark chocolate is followed by a significant increase in insulin sensitivity and a decrease in blood pressure in healthy persons https://pubmed.ncbi.nlm.nih.gov/15755830/
Other RCTs for the effect of chocolate on health: Sub-Chronic Consumption of Dark Chocolate Enhances Cognitive Function and Releases Nerve Growth Factors: A Parallel-Group Randomized Trial https://pubmed.ncbi.nlm.nih.gov/31744119/
Habitual cocoa intake reduces arterial stiffness in postmenopausal women regardless of intake frequency: a randomized parallel-group study https://pubmed.ncbi.nlm.nih.gov/27881914/
High Flavonoid Cocoa Supplement Ameliorates Plasma Oxidative Stress and Inflammation Levels While Improving Mobility and Quality of Life in Older Subjects: A DoubleBlind Randomized Clinical Trial https://pubmed.ncbi.nlm.nih.gov/31056655/
Higher dietary fibre intake is associated with increased skeletal muscle mass and strength in adults aged 40 years and older https://pubmed.ncbi.nlm.nih.gov/34585…
A defined, plant-based diet utilized in an outpatient cardiovascular clinic effectively treats hypercholesterolemia and hypertension and reduces medications https://pubmed.ncbi.nlm.nih.gov/29575…
Blood urea nitrogen (BUN) is one of the 19 variables found on the biological age calculator, aging.ai. It measures the amount of nitrogen, as contained in urea (i.e., blood urea nitrogen, BUN) in your blood. The reference range for BUN is 5 – 20 mg/dL, but within that range, what’s optimal?
First, BUN increases during aging, from 11 – 13 mg/dL in 20 yr olds to 20 – 22 mg/dL in 90 yr olds (Wang et al. 2017):
The importance of the age-related increase in BUN is illustrated by the finding that risk of death for all causes increases above 15 mg/dL:
Also note that maximally decreased risk for all cause mortality was associated with BUN values between 5 – 15 mg/dL. In addition, even though a BUN value = 20 mg/dL is technically within the reference range, risk of death for all causes would be 50% higher when compared with someone that had BUN levels between 5 – 15 mg/dL. Collectively, based on the aging and all-cause mortality data, I’d argue that 5 – 13 mg/dL may be the optimal range for BUN.
In other words, the main source of dietary nitrogen is protein, so if you eat a lot of protein, you’ll make a lot of urea. Circulating levels of urea can be easily calculated by measuring BUN, via: Urea [mg/dL]= BUN [mg/dL] * 2.14). Therefore, measuring BUN can then be used to determine if your protein intake is too high or too low.
What’s my BUN? As shown below, I’ve measured BUN 22 times since 2015. In line with the Young et al. (2000) data that showed an almost perfectly linear correlation between dietary nitrogen intake with urea production, similarly, as my dietary protein intake has increased, so have my BUN levels. The correlation between my dietary protein intake with BUN is strong (r = 0.76, R^2 = 0.575, p-value = 4.3E-05):
Note that my BUN is (purposefully) below 15 mg/dL, the upper limit for reduced all-cause mortality risk in Solinger and Rothman (2013), and within the 11 – 13 mg/dL range reported for the 20 yr olds of Wang et al. (2017).
For more recent tracked data, see the video!
References
Solinger AB, Rothman SI. Risks of mortality associated with common laboratory tests: a novel, simple and meaningful way to set decision limits from data available in the Electronic Medical Record. Clin Chem Lab Med. 2013 Sep;51(9):1803-13.
Wang Z, Li L, Glicksberg BS, Israel A, Dudley JT, Ma’ayan A. Predictingage by miningelectronicmedicalrecords with deeplearningcharacterizesdifferences between chronological and physiologicalage. J Biomed Inform. 2017 Dec;76:59-68. doi: 10.1016/j.jbi.2017.11.003.
Young VR, El-Khoury AE, Raguso CA, Forslund AH, Hambraeus L. Rates of urea production and hydrolysis and leucine oxidation change linearly over widely varying protein intakes in healthy adults. J Nutr. 2000 Apr;130(4):761-6.
If you’re interested, please have a look at my book!
How does the gut microbiome and its metabolic products affect muscle mass, muscle composition, and physical function? In this presentation, I review the evidence, then I present recent data from our group.