Who is at risk of irregular meal intake? Results from a population-based study

A systematic review of associations between day-to-day variability in meal pattern and body weight, components of the metabolic syndrome and cognitive function

BACKGROUND

Meal pattern is a potential health determinant. Previously, mean values for properties of meal pattern, such as daily meal frequency, have been considered. Means, however, obscure variability between-day (irregular or chaotic eating). This systematic review aimed to identify and critique published methods used to characterise between-day variability in meal pattern, and to explore relationships between this and obesity, as well as associated health outcomes.

METHODS

Using relevant databases, a systematic search was undertaken for studies with adults and children in which between-day variability in meal pattern was measured, and related to body weight, metabolic syndrome components and cognitive function.

RESULTS

In 34 papers identified (28 observational and six intervention studies), between-day variability in meal pattern was characterised by a variety of methods. These ranged from single questions about intake regularity to more complex methods quantifying the degree of variability. Assumptions were made, such as there being three main meals, resulting in dissociation from the "clock time" of eating. In 24 of the papers, between-day variability in meal pattern was associated with negative weight and health outcomes including higher weight, reduced thermogenic response to meals and poorer academic achievement.

CONCLUSIONS

Between-day variability in meal pattern is a promising research area that might inform low-cost public health interventions. However, current methods of characterising between-day variability tend to make assumptions and be inconsistent in the meal pattern properties considered. Well controlled dietary intervention studies are required to confirm causation.

The number of household members as a risk factor for peptic ulcer disease

Peptic ulcer disease (PUD) is caused by many sociodemographic and economic risk factors other than H. pylori infection. However, no studies reported an association between PUD and the number of household members. We showed the number of family members affected by PUD based on sex in a Korean population. This cross-sectional study used 1998–2009 data from the Korea National Health and Nutrition Examination Survey of the Korea Centers for Disease Control and Prevention. Multiple binary logistic regression models adjusted for confounders were constructed to analyze the association of PUD with the number of household members. The number of household members was associated with PUD, age, body mass index (BMI), waist circumference, systolic blood pressure, hemoglobin, glucose, location (urban/rural), income, education level, stress, current drinking, and smoking in both sexes. Men with other household members had a higher PUD risk compared to men or women living alone (reference), and the opposite was observed for women. Men with 4 household members had a higher PUD risk than men living alone in the model adjusted for age, BMI, income, location, education, and stress (OR = 2.04 [95% CI 1.28–3.27], p value = .003). Women with more than 6 household members had a lower PUD risk than women living alone in the adjusted model (OR = 0.50 [0.33–0.75], p value = .001). Women with more household members had a lower PUD risk. However, more men had PUD than women regardless of the number of household members.

Employment status and temporal patterns of energy intake: Nutrition and Health Survey in Taiwan, 2005–2008

Objective

To (i) identify the major temporal patterns of energy intake among adults; (ii) examine the association between employment status and the patterns; and (iii) examine the association between dietary quality and the patterns.

Design

Secondary analysis based on the cross-sectional population-based nutrition survey in Taiwan, 2005–2008. Based on energy intake levels at six time intervals of a day derived from 24 h recall data, we applied cluster analysis to identify major temporal patterns of energy intake. Self-reported employment status was categorized into six groups: full-time, part-time, no job, student, homemaker and retired. Multinomial logistic regression models were fitted to test the association between temporal patterns of energy intake and employment groups.

Setting

Non-institutionalized community dwellers.

Subjects

Non-pregnant adults (≥19 years old) with total energy intake between 2092 and 20920 kJ/d (500 and 5000 kcal/d; n 4508).

Results

Five major patterns were identified, which can be seen as the traditional meal pattern and its variants. About 20 % of adults had the traditional pattern. The most prevalent pattern was the delayed morning meal pattern (33 %), which had lower Ca and P intakes than the traditional pattern. About 14 % of adults had the delayed lunchtime pattern, which had lower protein, PUFA, fibre, Ca, P, vitamin D and vitamin E intakes than the traditional. Adjusted prevalence of the delayed lunchtime pattern was highest among full-time students (34 %), followed by part-time workers (24 %), and was lower in retired (8 %), homemakers (11 %) and full-time employed adults (12 %).

Conclusion

Adults’ temporal patterns of energy intake, which varied with their employment status, affected their dietary quality.

The effectiveness of healthy meals at work on reaction time, mood and dietary intake: a randomised cross-over study in daytime and shift workers at an university hospital

Our dietary habits affect both cognitive performance and mood. The aim of the study was to examine the effect of increased availability of healthy meals and water at work on healthcare staff. The study used an 8-week randomised cross-over design. A total of sixty physicians, nurses and nursing assistants, including sixteen working on shifts, were recruited. The participants received a self-selected keyhole-labelled (Nordic nutrition label) lunch, snack and bottled water during each shift throughout the intervention period. Reaction time (Go/No-Go test), mood-related scores (POMS) and dietary intake were assessed at run-in, and at the end of the intervention and the control periods. The intake of fat (P=0·030) and PUFA (P=0·003) was lower, and the intake of carbohydrate (P=0·008), dietary fibre (P=0·031) and water (P<0·001) was greater in the intervention period than in the control period. The intervention had no effect on reaction time or any of the mood-related scores in the group as a whole. In shift-working participants, the intervention period resulted in a 31·1 % lower Fatigue-Inertia Score (P=0·003), a 15·3 % higher Vigour-Activity Score (P=0·041) and a 42·7 % lower Total Mood Disturbance Score (P=0·017), whereas the only dietary component that significantly improved was water intake (P=0·034), when compared with the control period. Providing healthy meals, snacks and water during working hours seems to be an effective way of improving employees' dietary intake. Moreover, increased intake of water may be associated with beneficial effects on fatigue, vigour and total mood in shift-working healthcare staff.

A Review of the Effects of Lunch: On Adults’ Short-term Cognitive Functioning

Because of widespread irregular lunch consumption by both children and adults, information on the effects of lunch on short-term cognitive functioning is relevant to public health. In September 2012, a MEDLINE search was conducted for studies in which the effects of lunch on cognitive performance were examined. Eleven experimental studies published from 1981 to 1996 were found and evaluated; all involved adults. In three studies, the effects of lunch and lunch skipping were compared; the remaining studies involved a determination of the effects of lunch size and lunch composition. Results of studies in which lunch was compared with no lunch indicate that lunch leads to potential impairment of some aspects of cognitive functioning in the early afternoon. Lunch size may influence cognitive functioning, with impairment more likely to occur after a large lunch than a small lunch. Furthermore, in comparison with low-fat lunches, high-fat lunches seem to result in slower but more accurate responses to some cognitive tasks. However, these suggestions must be viewed with caution, as they are based on only a few studies and are not thoroughly supported by high-quality evidence. In addition, results obtained with adults are not applicable to children. Thus, the potential effects of lunch need further examination in children and adults.