Modern perspective of the Rice Diet for hypertension and other metabolic diseases

In the early 1940s, before antihypertensive drugs were available, the Rice Diet Programme (RDP) was developed to treat severe hypertension and, later, diabetes and obesity. Despite significant advancements in dietary management for these conditions since then, debates remain regarding the proper guidelines for sodium and macronutrients intakes. The patient care records of RDP offer a unique source of longitudinal examination of a very low sodium (<10 mmol/day), fat, cholesterol and protein diet on blood pressure (BP), other health markers and survival.

In 2019, the Rice Diet Database Project (RDDP) digitised handwritten patient care records and retinal photographs of 17 487 RDP participants, establishing a digital database for analyses. Manual transcription accuracy exceeded 97%. We used regression models to investigate the impact of dietary adherence on systolic BP (SBP) and body weight. Further, we performed Kaplan-Meier survival analysis to compare 5-year survival probability of participants defined by baseline level of SBP.

The database encompasses a wide array of health markers, including BP, weight, urine chloride (UCl) concentration and retinal features that offer a unique resource for studying the impact of the RDP on hypertension, diabetes and obesity. Initial analysis shows reductions in BP and weight as well as improved survival in participants with severe hypertension, underscoring the effectiveness of the diet. The data also permit examining the safety of extreme dietary sodium reduction.The database has numerous strengths (large patient population; extensive, long-term measurements and the use of UCl excretion to document dietary adherence) and limitations (missing data; temporal changes in methodologies over 50 years and lack of control subjects).

The RDDP database allows exploration of the effects of a diet extremely low in sodium, protein, fat and cholesterol on health indicators and patient survival. This report highlights the database's potential for detailed and intricate future analyses.