Characterizing eating patterns: a comparison of eating occasion definitions

Leech, Rebecca M.; Worsley, Anthony; Timperio, Anna; McNaughton, Sarah A.

doi:10.3945/ajcn.115.114660

Cited by 81 publications

(91 citation statements)

References 38 publications

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“…This definition of EO has been shown to predict variance in total EI and measures of adiposity more strongly than applying EO definitions with no energy criterion (26,27) or differing time intervals (16,27). The EI from EOs within each hour of the day was examined and averaged across the 2 d of dietary recalls.…”

Section: Eosmentioning

confidence: 99%

Temporal eating patterns: associations with nutrient intakes, diet quality, and measures of adiposity

Leech

Timperio

Livingstone

et al. 2017

The American Journal of Clinical Nutrition

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Background: Some evidence suggests that higher energy intake (EI) later in the day is associated with poor diet quality and obesity. However, EI at one eating occasion (EO) is also dependent on EI at surrounding EOs. Studies that examine the distribution of EOs across the day are rare. Objective: The aim of this study was to examine associations between temporal eating patterns, nutrient intakes, diet quality, and measures of adiposity in a representative sample of Australian adults. Design: Dietary data from two 24-h recalls collected during the crosssectional 2011-2012 Australian National Nutrition and Physical Activity Survey were analyzed (n = 4544 adults, aged $19 y). Temporal eating patterns, based on the distribution of EOs across the day, were determined by using latent class analysis. Diet quality estimated adherence to healthy eating recommendations and was assessed by using the 2013 Dietary Guidelines Index (DGI). Multivariate regression models assessed associations between temporal eating patterns, nutrient intakes, diet quality, and adiposity (body mass index, waist circumference, weight status, and central weight status). Models were adjusted for potential confounders and energy misreporting. Results: Three patterns, labeled "conventional," "later lunch," and "grazing," were identified. Compared with a "conventional" or "later lunch" pattern, men and women with a "grazing" pattern had lower DGI scores and higher intakes of discretionary (noncore) foods (P , 0.05). Among women, the "grazing" pattern was associated with overweight or obesity (OR: 1.57; 95% CI: 1.15, 2.13) and central overweight or obesity (OR: 1.73; 95% CI: 1.19, 2.50). These associations were attenuated after the exclusion of energy misreporters and adjustment for total EI. Conclusions: This study found that a "grazing" temporal eating pattern was modestly but significantly associated with poorer diet quality and adiposity among women, after adjustment for covariates and energy misreporting. Future research should consider the impact of energy misreporting on the relation between temporal eating patterns and adiposity. This secondary analysis was registered at anzctr.org.au as ACTRN12617001029381.

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Section: Eosmentioning

confidence: 99%

Temporal eating patterns: associations with nutrient intakes, diet quality, and measures of adiposity

Leech

Timperio

Livingstone

et al. 2017

The American Journal of Clinical Nutrition

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“…The classification of temporal distribution of meals is usually based on cultural norms (67,68) . Recent analysis by Leech et al showed in an Australian survey that a neutral definition (individual eating occasions separated by a specific time interval, such as 15 min) was best in predicting variance in total energy intake (69) . A review by found that most studies included in their review use a participant-identified approach (70) .…”

Section: Food For Thoughtmentioning

confidence: 99%

Meal irregularity and cardiometabolic consequences: results from observational and intervention studies

2016

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Studying irregular meal patterns fits in with the latest research focusing not only on what people eat but also when they eat, also called chrono-nutrition. Chrono-nutrition involves studying the impact of nutrition on metabolism via circadian patterns, including three aspects of time: (ir)regularity, frequency and clock time. The present paper aimed to narratively review research on irregular meal patterns and cardiometabolic consequences. Only few cross-sectional studies and prospective cohort studies were identified, and most of these suggested that eating meals irregularly is associated with a higher risk of the metabolic syndrome and cardiometabolic risk factors, including BMI and blood pressure. This was supported by two randomised controlled intervention studies showing that consuming meals regularly for 2 weeks v. an irregular meal pattern, led to beneficial impact on cardiometabolic risk factors as lower peak insulin, lower fasting total and LDL-cholesterol, both in lean and obese women. In conclusion, the limited evidence on meal regularity and cardiometabolic consequences supports the hypothesis that consuming meals irregularly is adversely associated with cardiometabolic risk. However, it also highlights the need for more large-scale studies, including detailed dietary assessment to further advance the understanding of the impact of chrono-nutrition on public health.

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“…Currently there are few studies which have investigated eating time patterns. Leech (2) investigated temporal eating habits in Australian adults using Latent Class Analysis(LCA). Here we use LCA to investigate the hourly eating patterns of UK adults.…”

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confidence: 99%

“…We investigated whether latent class membership was associated with age, BMI, working hours, living with other people, being married and household income. The association between age and class was assessed using an F Test and the association between other factors and latent class was assessed using a chi (2) test.…”

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confidence: 99%

Investigating eating time patterns in UK adults from The 2008–2012 National Diet and Nutrition Survey

Mansukhani

Palla

2018

Proc. Nutr. Soc.

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Eating later in the day is associated with obesity which in turn is associated with poorer health outcomes (1) . Currently there are few studies which have investigated eating time patterns. Leech (2) investigated temporal eating habits in Australian adults using Latent Class Analysis(LCA). Here we use LCA to investigate the hourly eating patterns of UK adults.Data from four daily food diaries for 2007 women and 1443 men from the 2008-2012 UK National Dietary and Nutrition Survey Rolling Programme (NDNS RP) were analysed. LCA was used to calculate the probability of whether an eating occasion had occurred for every hour of the day for individuals within each distinct class. The average number of kilojoules (kJ) was calculated for each individual for each hour of the day over the four days. We classified an eating occasion to have occurred if an average of more than 210kJ had been consumed by that individual for that hour of the day. Alternative definitions of eating occasions were used but these did not change the interpretation of results (3) . We investigated whether latent class membership was associated with age, BMI, working hours, living with other people, being married and household income. The association between age and class was assessed using an F Test and the association between other factors and latent class was assessed using a chi (2) test.We identified three patterns of eating: a standard eating class (Women 38 % Men 48 %), a later class (Women 46 % Men 33 %) which were likely to eat meals slightly later and an irregular class(Women 16 % Men 18 %) which were less likely to eat meals at a fixed time. We found that for both men and women (p < 0·001 in both cases) younger people ate later. Married as opposed to single men(p = 0·002) ate earlier. People who are degree educated tend to eat earlier(men p = 0·001 women p < 0·001) than their non degree educated peers. And while being in paid employment is associated with eating earlier (men p < 0·001 women p < 0·001) higher household income(men p = 0·050 women p < 0·001) is associated with eating later. We also found that women who work more than 35 hours a week are more likely (p = 0·014) to eat later.Our results suggest that people fall into distinct eating classes and that later eating is associated with various socioeconomic factors. It would be interesting to next investigate how eating time patterns identified via LCA are associated to health outcomes.

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Characterizing eating patterns: a comparison of eating occasion definitions

Cited by 81 publications

References 38 publications

Temporal eating patterns: associations with nutrient intakes, diet quality, and measures of adiposity

Temporal eating patterns: associations with nutrient intakes, diet quality, and measures of adiposity

Meal irregularity and cardiometabolic consequences: results from observational and intervention studies

Investigating eating time patterns in UK adults from The 2008–2012 National Diet and Nutrition Survey

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