Table 5

Logistic regression analyses of factors associated with energy intakes below the EER, excessive carbohydrate and insufficient fat intakes
Energy intake below EERa Excessive carbohydrate intakeb Insufficient fat intakec
OR (95% CI) p-value OR (95% CI) p-value OR (95% CI) p-value
Participant characteristics
Age NAd 0.97 (0.96, 0.99) <0.001 0.98 (0.96, 0.99) <0.001
Ethnicity (minority vs other) 0.91 (0.80, 1.04) 0.18 1.00 (0.88, 1.13) 0.95 0.94 (0.83, 1.07) 0.33
Occupation (farmer vs other) NA 1.69 (1.36, 2.09) <0.001 1.53 (1.24, 1.89) <0.001
Education (Highest grade completed; ref = 0-5)
6-9 0.84 (0.66, 1.06) 0.14 0.63 (0.49, 0.80) <0.001 0.64 (0.50, 0.82) <0.001
10-12 0.97 (0.75, 1.25) 0.82 0.52 (0.40, 0.69) <0.001 0.55 (0.42, 0.72) <0.001
College or higher 0.95 (0.69, 1.30) 0.75 0.58 (0.41, 0.82) 0.002 0.58 (0.41, 0.81) 0.001
Household characteristics
Food Insecurity status (ref = moderate/severe)
Mild 0.89 (0.72, 1.11) 0.30 0.69 (0.56, 0.87) 0.001 0.74 (0.60, 0.93) 0.008
Secure 0.66 (0.56, 0.78) <0.001 0.64 (0.54, 0.76) <0.001 0.73 (0.61, 0.86) <0.001
Socioeconomic status quintile (ref = poorest quintile)
Poorer 0.76 (0.62, 0.93) 0.007 0.95 (0.78, 1.15) 0.57 0.89 (0.73, 1.09) 0.25
Average 0.85 (0.69, 1.05) 0.12 0.78 (0.63, 0.96) 0.02 0.78 (0.63, 0.96) 0.02
Richer 0.63 (0.50, 0.79) <0.001 0.58 (0.47, 0.73) <0.001 0.62 (0.50, 0.77) <0.001
Richest 0.50 (0.39, 0.65) <0.001 0.46 (0.36, 0.58) <0.001 0.49 (0.39, 0.63) <0.001

aLower actual intakes than the Estimated Energy Requirement (EER).

bGreater than 65% of total energy intake.

cLess than 20% of total energy intake.

dAge and occupation were used to calculate EER; therefore these variables are not included in the model to predicting the odds of having energy intakes below the estimated EER.

Nguyen et al.

Nguyen et al. Nutrition Journal 2013 12:126   doi:10.1186/1475-2891-12-126

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