Association among Dietary Inflammatory Index, sleep quality and nutritional status in fixed daytime and rotating shift workers.

Rotating shift workers had significantly higher total energy intake than fixed daytime workers.

• Cross-sectional study of 52 male workers at a defense industry factory in Ankara, Türkiye, in fixed daytime or rotating shift schedules.
• Dietary intake was assessed with 24-h dietary recalls on three non-consecutive days.
• The abstract reports the difference as significant at p < 0.05.

Rotating shift workers had higher intakes of fructose, total fat, saturated and monounsaturated fatty acids, and cholesterol than fixed daytime workers.

• Macronutrient intakes were calculated from three 24-h recalls.
• Differences were reported as significant at p < 0.05.
• The abstract does not give group means for these nutrients.

Rotating shift workers had higher intakes of several micronutrients, including vitamin A, folate, iron, calcium, and phosphorus.

• Micronutrient intakes were calculated from three non-consecutive 24-h recalls.
• Differences were significant at p < 0.05 compared with fixed daytime workers.

Mean Dietary Inflammatory Index (DII) scores did not differ significantly between fixed daytime and rotating shift workers.

• Fixed daytime: 0.2 ± 1.86; rotating shift: -0.2 ± 2.25.
• DII was computed from dietary recall data to assess the inflammatory potential of the diet.
• Both groups had mean scores near zero, with wide variability.

Higher DII scores were positively correlated with poorer global sleep quality (PSQI score).

• Correlation between DII and global PSQI: r = 0.278, p = 0.046.
• Sleep quality was assessed with the Pittsburgh Sleep Quality Index.
• Higher PSQI scores indicate worse sleep quality.

DII scores were positively correlated with the PSQI sleep duration and daytime dysfunction component scores.

• Sleep duration component: r = 0.319, p = 0.021.
• Daytime dysfunction component: r = 0.287, p = 0.039.

The association between DII and overall sleep quality was no longer statistically significant after adjustment for confounders.

• Adjustment covariates were age, BMI, smoking status, physical activity, and work schedule.
• This suggests the unadjusted correlation may be partly explained by these factors.

The authors conclude that dietary habits, pro-inflammatory dietary patterns, and poor sleep quality may be co-existing factors associated with metabolic risk.

• Anthropometric, body composition, blood pressure, and biochemical measures (glucose, lipid profile, CRP, homocysteine) were collected using standardised protocols.
• The authors suggest that addressing these factors may contribute to better overall metabolic health.
• The design is cross-sectional with a small all-male sample (n = 52).