Background: Nutritional rickets is believed to result from the interaction of inadequate serum 25-hydroxyvitamin D [25(OH)D] concentration and dietary calcium intake, but this interaction has not been confirmed in children with rickets. Determining the vitamin D requirements to prevent nutritional rickets has been thwarted by inconsistent case definition, inadequate adjustment for calcium intake and other confounders, and 25(OH)D assay variability. Objectives: To model the 25(OH)D concentration associated with nutritional rickets in calcium-deprived Nigerian children, adjusted for confounding factors, and develop a general approach to define vitamin D status while accounting for calcium intake. Methods: Logistic regression was used to model the association of serum 25(OH)D with having rickets adjusted for calcium intake in a reanalysis of a case-control study in Nigerian children. The matching variables age, sex, weight-for-age z score, and 4 additional significant variables were selected [religion, age began walking, phosphorus intake, and the 25(OH)D × calcium intake interaction] using a rigorous 7-step algorithm. Results: Cases had significantly (P < 0.0001) lower mean ± SD 25(OH)D than controls (33 ± 13 compared with 51 ± 16 nmol/L, respectively), whereas cases and controls had similarly (P = 0.81) low mean dietary calcium intakes (216 ± 88 and 213 ± 95 mg/d, respectively). There was a significant interaction between 25(OH)D and calcium intake [coefficient (95% CI): -0.0006 (-0.0009, -0.0002)]. Accordingly, as calcium intake increased from 130 to 300 mg/d, the adjusted odds of having rickets decreased dramatically with increasing 25(OH)D such that at 200 mg/d, the adjusted odds of having rickets at 47.5 nmol/L was 0.80, whereas it was 0.2 at 62.5 nmol/L. Moreover, at a calcium intake of 300 mg/d, the adjusted odds was 0.16 at a 25(OH)D concentration of 47.5 nmol/L and 0.02 at 62.5 nmol/L. Conclusions: The vitamin D requirement to prevent nutritional rickets varies inversely with calcium intake and vice versa. Also, application of multivariable modeling is essential in defining vitamin D requirements.
