ABSTRACT
In many countries, assessing food and nutrient intake for research and surveillance purposes is difficult due to the lack of comprehensive, country-specific food and nutrient databases and/or a dietary analysis software program. In this case study, we describe the approach used to adapt a United States (US) dietary analysis software and nutrient database (Nutrition Data System for Research [NDSR]) for use in analyzing 24-hour dietary recalls collected for the Brazil Kids Nutrition and Health Study (KNHS). A team of experts that included individuals knowledgeable about Brazil and US eating traditions was assembled to devise solutions for between-country differences in eating habits, food supply, food nomenclature, and language. Solutions devised relied on several key resources, including the Brazilian Food Composition Table (TBCA) and a list of 200 foods commonly consumed in Brazil. These solutions included creating data entry rules that specified how each reported food should be entered into NDSR, creation of User Recipes for foods lacking a close nutritionally matching food in the NDSR database, and adjustment for food fortification differences as part of the analysis of study data. This case study illustrates that NDSR can be adapted for use outside of the United States through a structured process.
ABSTRACT
PURPOSE: To evaluate the meal timing variability of rotating shift workers throughout a complete shift schedule and its effect on daily energy and macronutrient intake. METHODS: Thirty male shift-workers from a mining company were evaluated in a complete rotation shift cycle over 240 consecutive hours (10 days; two days of morning shifts, two days of evening shifts, 24 h free, two days of night shifts and three days off). Food intake related variables [meal timing, energy (kcal) and macronutrient intake (%)] were assessed by 24 h recall by a trained nutritionist. Mixed models were used to analyze the variation in meal timing and energy and macronutrient intake throughout the shift cycle, as well as the interaction between shift and time ranges (00:00-03:59, 04:00-07:59, 08:00-11:59, 12:00-15:59, 16:00-19:59, 20:00-23:59). RESULTS: The first meal of the day was earlier on night shifts [D6 (3:44 ± 0:33) and D7 (5:52 ± 0:42)] compared to the other shifts (p < 0.001), except for D4 (evening shift; 5:51 ± 0:47) versus D7 (p = 0.999). Night shifts also showed a shorter night fasting (D5-D6, 9.3 h; D6-D7, 9.6 h) than most other nights (p < 0.05), except for the fasting between D1-D2 (11.3 h) and D3-D4 (11.2 h) (p > 0.05). There was no difference in 24 h energy intake throughout the shift cycle (p = 0.065). The analysis of interaction between shift and time ranges showed that night shift (D6) presented a higher intake of energy (441.5 ± 48.4 kcal), percentage of energy (D6: 17.8 ± 1.8%), fat (17.6 ± 2.0%), carbohydrate (17.0 ± 1.7%) and protein (16.4 ± 1.8%) between 00:00 and 03:59 compared with the other shift days (p < 0.05). CONCLUSION: Night shifts seem to contribute to a longer eating window than other shifts. Moreover, there is a higher energy and macronutrients intake during night shifts, which reduces the night fast period and could have implications for metabolic dysregulation.
