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. 2014 Apr 17;144(6):979–987. doi: 10.3945/jn.114.192336

TABLE 5.

Contribution of inflammation to population estimates of micronutrient deficiency among children in rural Nepal (n = 1000)1

Indicator Cutoff PRR2 PAR (95% CI)3 Population prevalence explained by presence of inflammation4
Retinol, μmol/L <0.7 3.95 0.484 (0.319, 0.609) +4.1%
<1.05 1.34 0.098 (0.060, 0.136) +5.4%
β-Carotene, μmol/L <0.09 1.27 0.081 (0.028, 0.130) +3.3%
PLP, nmol/L <20 1.40 0.111 (0.060, 0.160) +4.8%
Folic acid, nmol/L <13.6 2.32 0.294 (0.094, 0.450) +1.8%
Ferritin, μg/L <15 0.66 −0.118 (−0.238, −0.010) −1.2%
TfR, mg/L >8.3 1.38 0.107 (0.052, 0.158) +4.3%
Total circulating selenium, μmol/L <0.89 1.24 0.070 (0.035, 0.104) +4.2%
Any deficiency ≥1 1.06 0.019 (0.008, 0.030) +1.7%
Multiple deficiencies ≥2 1.24 0.070 (0.038, 0.099) +4.6%
1

Limited to micronutrient indicators in plasma where significant differences in prevalence of deficiency by inflammatory status occurred, from Table 4. PAR, population attributable risk; PLP, pyridoxal-5′-phosphate; PRR, prevalence rate ratio; TfR, transferrin receptor.

2

Calculated as the prevalence of deficiency among children with inflammation divided by the prevalence in children without inflammation, from Table 4.

3

Calculated as Pe(PRR−1)/(Pe(PRR−1)+1), where Pe is the proportion of the population exposed to inflammation (0.316) (39, 40). 95% CIs were calculated as lower limit = 1−exp(ln(1−PAR)+1.96s); upper limit = 1−exp(ln(1−PAR)−1.96s), where “s” is calculated as the square root of [b+(a+d)PAR]/nc, and b = number with inflammation but no deficiency, a = number with inflammation and deficiency, d = number with no inflammation or deficiency, n = total number of participants, c = children with deficiency but no inflammation, according to Fleiss (40).

4

Calculated as PAR × population prevalence of deficiency, from Table 2; equivalent to the prevalence of deficiency among children in the whole sample (from Table 2) minus the prevalence in those without inflammation (from Table 4).