How Much Oxalate Is Too Much? n=1 Analysis

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Papers referenced in the video:

Dietary oxalate to calcium ratio and incident cardiovascular events: a 10-year follow-up among an Asian population

Predicting Age by Mining Electronic Medical Records with Deep Learning Characterizes Differences between Chronological and Physiological Age

Association between low-density lipoprotein cholesterol and cardiovascular mortality in statin non-users: a prospective cohort study in 14.9 million Korean adults

Joint distribution of lipoprotein cholesterol classes. The Framingham study) AND abbott lipoproteins 1983

Incidental lymphopenia and mortality: a prospective cohort study

Blood counts in adult and elderly individuals: defining the norms over eight decades of life

Effect of Aging on Serum Uric Acid Levels: Longitudinal Changes in a Large Japanese Population Group

Liver enzymes and risk of all-cause mortality in general populations: a systematic review and meta-analysis.

Increased red blood cell distribution width (RDW) is associated with higher glycosylated hemoglobin (HbA1c) in the elderly


3 thoughts on “How Much Oxalate Is Too Much? n=1 Analysis

  1. Ron

    Very interesting subject as usual. When you think about it an intersection of microbes, heart disease risk and calcium intake. Oxalobacter formigenes helps to break down oxalates in the gut. Calcium binds with oxalate. Calcium supplementation, but not dietary calcium, can be associated with CVD risk. Apparently, when the 3 are harmonious the outcome is positive. In your opinion, how could a calcium fortified food be any different than a supplement? Especially if the supplement was food based, like hydroxyapatite or red algae, commensurate in dose, and taken along with food?


    1. Michael Lustgarten Post author

      Thanks Ron. I’m not sure, but all intake, whether supplements or food can be compared via correlations with blood biomarkers, and if it’s a net positive, it will show in the correlations. Then, increasing/decreasing the food or supplement can test whether the correlation is causative (or not).



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