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To examine trends in the intake of key food groups among Iranian adults between 2005 and 2016, overall, and according to sociodemographic characteristics.
Repeat cross-sectional data from the Iran-STEPwise approach to risk factor surveillance (Iran-WHO STEPS) 2005–2016 were analysed. Regression analyses were used to evaluate trends in the frequency of fruits, vegetables and fish intake and type of oil used over time. Interactions by sex, age and area of residence were examined.
225 221 Iranian adults.
The frequency of vegetables (β: −0·03; 95 % CI (−0·06, −0·00); P-trend = 0·030) and fish (β: −0·09; 95 % CI (−0·10, −0·08); P-trend < 0·001) intake and use of solid fat (OR: 0·70; 95 % CI (0·70, 0·72); P-trend < 0·001) declined, whilst the frequency of fruit intake (β-Coeff: 0·03, 95 % CI (0·01, 0·05); P-trend = 0·014) and liquid oil use (OR: 1·40; 95 % CI (1·3, 1·4); P-trend<0·001) rose. Rising trends in fruit intake were larger in mid-aged (40–60 years) and older (>60 years) adults (P-interaction < 0·001), whilst declines in vegetable (P-interaction < 0·001) and fish intake (P-interaction = 0·001) were larger in older adults. The declining use of solid fat was strongest in middle-aged and older adults (P-interaction = 0·035), while the increasing use of liquid oil was strongest in rural areas (P-interaction = 0·011).
During the nutrition transition, liquid oil use and the frequency of fruit intake rose, while the frequency of vegetables and fish intake declined. Nonetheless, the fatty acid composition and cooking methods are important considerations. The changes observed are concerning from a public health perspective and demonstrate the need for interventions and possible targets for tailored strategies.
This study examined differences in food groups consumed at eating occasions by the level of adherence to dietary guidelines in Australian adults (≤19 years) and whether consumption differed with respect to age, sex and education levels. Secondary analysis of the 2011–2012 National Nutrition and Physical Activity Survey (n 9054) was performed, using one 24-h dietary recall with self-reported eating occasions. Dietary Guideline Index scores were used to assess adherence to the 2013 Australian Dietary Guidelines. Mean differences (95 % CI) in servings of the five food groups and discretionary foods at eating occasions were estimated for adults with higher and lower diet quality, stratified by sex, age group and education. Using survey-based t-tests, differences of at least half a serving with P values < 0·05 were considered meaningful. Compared with adults with lower diet quality, women and men aged 19–50 years with higher diet quality consumed more serves of vegetables at dinner (mean difference (95 % CI), women; 1·0; 95 % CI (0·7, 1·2); men: 0·9; 95 % CI (0·6, 1·3)) and fewer serves of discretionary foods at snacks (women: −0·7; 95 % CI (−0·9, −0·5); men: −1·0; 95 % CI (−1·4, −0·7). Other food groups, such as grains, dairy products and alternatives, meats and alternatives, were not significantly different between adults with lower and higher diet quality, across any eating occasions and age groups. Discretionary food intake at lunch, dinner and snacks was consistently greater among adults with lower diet quality, regardless of education level. Our findings identify dinner and snacks as opportunities to increase vegetable intake and reduce discretionary food intake, respectively.
This systematic review aimed to summarise the level of quality and accuracy of nutrition-related information on websites and social media and determine if quality and accuracy varied between websites and social media or publishers of information.
This systematic review was registered with PROSPERO (CRD42021224277). CINAHL, MEDLINE, Embase, Global Health and Academic Search Complete were systematically searched on 15 January 2021 to identify content analysis studies, published in English after 1989, that evaluated the quality and/or accuracy of nutrition-related information published on websites or social media. A coding framework was used to classify studies’ findings about information quality and/or accuracy as poor, good, moderate or varied. The Academy of Nutrition and Dietetics Quality Criteria Checklist was used to assess the risk of bias.
From 10 482 articles retrieved, sixty-four were included. Most studies evaluated information from websites (n 53, 82·8 %). Similar numbers of studies assessed quality (n 41, 64·1 %) and accuracy (n 47, 73·4 %). Almost half of the studies reported that quality (n 20, 48·8 %) or accuracy (n 23, 48·9 %) was low. Quality and accuracy of information were similar on social media and websites, however, varied between information publishers. High risk of bias in sample selection and quality or accuracy evaluations was a common limitation.
Online nutrition-related information is often inaccurate and of low quality. Consumers seeking information online are at risk of being misinformed. More action is needed to improve the public’s eHealth and media literacy and the reliability of online nutrition-related information.
Dietary behaviours in early childhood are understudied despite links with later health. Assessing the distribution of key food groups across the day could identify opportunities for improvements. This study aimed to describe the 24-hourly distribution of dietary intakes and frequency of eating occasions for weekdays and weekend days among children aged 18 months and assess associations of eating frequency with vegetable, fruit and discretionary intakes and zBMI. Using two parent-reported 24-h recalls of child dietary intakes from the Melbourne Infant Feeding Activity and Nutrition Trial (InFANT) Program, mean frequency of daily eating occasions and hourly intake distributions were calculated for vegetables, fruits, discretionary foods, and total foods and energy-containing beverages on weekdays (n 428) and weekend days (n 376). Multivariable regression analyses assessed associations between frequency of eating occasions, total intake of food groups and zBMI. Overall, children had 7·8 ± 1·8 (mean ± sd) eating occasions/d on weekdays, where 1·5 ± 0·8 contained vegetables, 2·2 ± 1·1 contained fruit and 2·5 ± 1·5 contained discretionary foods. Weekend day intakes were similar. Energy intakes were highest at dinner time. Intakes of total foods, fruits and discretionary foods were spread across the day (06.00–22.00). Vegetable consumption was mainly about 18.00 with minimal intake at other times. Eating frequency was associated with amount of food consumed but not consistently with zBMI. These 18-month-old children ate frequently throughout the day, with little distinction between weekdays and weekend days. Most eating occasions lacked vegetables, and frequency of discretionary foods was higher than of vegetables. Promoting vegetable consumption at occasions other than dinner could improve vegetable intake.
Changes between diet quality and health-related quality of life (HR-QoL) over 12 years were examined in men and women, in 2844 adults (46 % males; mean age 47·3 (sd 9·7) years) from the Australian Diabetes, Obesity and Lifestyle study with data at baseline, 5 and 12 years. Dietary intake was assessed with a seventy-four-item FFQ. Diet quality was estimated with the Dietary Guideline Index, Mediterranean-Dietary Approaches to Stop Hypertension Diet Intervention for Neurological Delay Index (MIND) and Dietary Inflammatory Index. HR-QoL in terms of global, physical component summary (PCS) and mental component summary (MCS) was assessed with the Short-Form Health Survey-36. Fixed effects regression models adjusted for confounders were performed. Mean MCS increased from baseline (49·0, sd 9·3) to year 12 (50·7, sd 9·1), whereas mean PCS decreased from baseline (51·7, sd 7·4) to year 12 (49·5, sd 8·6). For the total sample, an improvement in MIND was associated with an improvement in global QoL (β = 0·28, 95 % CI (0·007, 0·55)). In men, an improvement in MIND was associated with an improvement in global QoL (β = 0·28, 95 % CI (0·0004, 0·55)). In women, improvement in MIND was associated with improvements in global QoL (β = 0·62 95 % CI (0·38, 0·85)), MCS (β = 0·75, 95 % CI (0·29, 1·22)) and PCS (β = 0·75, 95 % CI (0·29, 1·22)). Positive changes in diet quality were associated with broad improvements in HR-QoL, and most benefits were observed in women when compared to men. These findings support the need for strategies to assist the population in consuming healthy dietary patterns to lead to improvements in HR-QoL.
Despite the increased attention on neighbourhood food environments and dietary behaviours, studies focusing on adolescents are limited. This study aims to characterise typologies of food environments surrounding adolescents and their associations with fast food outlet visitation and snack food purchasing to/from school.
The number of food outlets (supermarket; green grocers; butcher/seafood/deli; bakeries; convenience stores; fast food/takeaways; café and restaurants) within a 1 km buffer from home was determined using a Geographic Information System. Adolescents’ self-reported frequency of fast food outlet visitation and snack food purchasing to/from school. Latent Profile Analysis was conducted to identify typologies of the food environment. Cross-sectional multilevel logistic regression analyses were conducted to examine the relationships between food typologies, fast food outlet visitations and snack food purchasing to/from school.
Four distinct typologies of food outlets were identified: (1) limited variety/low number; (2) some variety/low number; (3) high variety/medium number and (4) high variety/high number. Adolescents living in Typologies 1 and 2 had three times higher odds of visiting fast food outlets ≥1 per week (Typology 1: OR = 3·71, 95 % CI 1·23, 11·19; Typology 2: OR = 3·65, 95 % CI 1·21, 10·99) than those living in Typology 4. No evidence of association was found between typologies of the food environments and snack food purchasing behaviour to/from school among adolescents.
Local government could emphasise an overall balance of food outlets when designing neighbourhoods to reduce propensity for fast food outlet visitation among adolescents.
The impact of change in socio-economic status (SES) from childhood to adulthood (SES mobility) on adult diet is not well understood. This study examined associations between three SES mobility variables (area disadvantage, education, occupation) and adult diet quality. 1482 Australian participants reported childhood area-level SES in 1985 (aged 10–15 years) and retrospectively reported highest parental education and main occupation (until participant age 12) and own area-level SES, education, occupation and dietary intake in 2004–2006 (aged 26–36 years). A Dietary Guidelines Index (DGI) was calculated from food frequency and habit questionnaires. A higher score (range 0–100) indicated better diet quality. Sex-stratified linear regression models adjusted for confounders. Area-level SES mobility was not associated with diet quality. Compared with stable high (university) education, stable low (school only) was associated with lower DGI scores (males: β = –5·5, 95 % CI: −8·9, –2·1; females: β = –6·3, 95 % CI: −9·3, –3·4), as was downward educational mobility (participant’s education lower than their parents) (males: β = –5·3, 95 % CI: −8·5, –2·0; females: β = –4·5, 95 % CI: −7·2, –1·7) and stable intermediate (vocational) education among males (β = –3·9, 95 % CI: −7·0, −0·7). Compared with stable high (professional/managerial) occupation, stable low (manual/out of workforce) males (β = –4·9, 95 % CI: −7·6, –2·2), and participants with downward occupation mobility (males: β = –3·2, 95 % CI: −5·3, –1·1; females: β = –2·8, 95 % CI: −4·8, –0·8) had lower DGI scores. In this cohort, intergenerational low education and occupation, and downward educational and occupational mobility, were associated with poor adult diet quality.
Dietary guidelines should be underpinned by the best available evidence on relationships between diet and health, including evidence from nutrient-based, food-based and dietary patterns research. The primary aim of the present study was to analyse the systematic reviews conducted to inform the 2013 Australian Dietary Guidelines according to dietary exposure. The secondary aim was to analyse the reviews by health outcome, and design of included studies. To identify the systematic reviews, the dietary guidelines report was used as a starting point and relevant references were retrieved. The evidence report contained the data used in this analysis. Descriptive statistics were used to analyse reviews according to exposure, outcome, and design of included studies. A total of 143 systematic reviews were included in this analysis. Foods were the most common exposure (86·7 % of reviews), followed by nutrients (10·5 %) and dietary patterns (2·8 %). Chronic disease morbidity and/or mortality was the most common outcome (80·4 %), followed by chronic disease risk factors (19·6 %). Most reviews included evidence from cohort or nested case–control studies (92·3 %), many included evidence from case–control studies (61·5 %) and some included evidence from randomised controlled trials (28·7 %). These results reflect the research questions that were asked, the systematic review methods that were used, and the evidence that was available. In developing future iterations of the Australian Dietary Guidelines, there is an opportunity to review the latest evidence from dietary patterns research.
The present study aimed to identify whether discretionary food consumption declined in an intervention focused primarily on promoting fruit and vegetable consumption. We also aimed to identify potential mediators explaining intervention effects on discretionary food consumption.
Secondary analysis of data from the ShopSmart study, a randomised controlled trial involving a 6-month intervention promoting fruit and vegetable consumption. Linear regression models examined intervention effects on discretionary food consumption at intervention completion (T2). A half-longitudinal mediator analyses was performed to examine the potential mediating effect of personal and environmental factors on the association between the intervention effects and discretionary food consumption. Indirect (mediated) effects were tested by the product of coefficients method with bootstrapped se using Andrew Hayes’ PROCESS macro for SPSS.
Women were recruited via the Coles FlyBuys loyalty card database in socio-economically disadvantaged suburbs of Melbourne, Australia.
Analyses included 225 women (116 intervention and 109 control).
Compared with controls, intervention participants consumed fewer discretionary foods at T2, after adjusting for key confounders (B = −0·194, 95 % CI −0·378, −0·010 servings/d; P = 0·039). While some mediators were associated with the outcome (taste, outcome expectancies, self-efficacy, time constraints), there was no evidence that they mediated intervention effects.
The study demonstrated that a behavioural intervention promoting fruit and vegetable consumption among socio-economically disadvantaged participants was effective in reducing discretionary food intake. Although specific mediators were not identified, researchers should continue searching for mechanisms by which interventions have an effect to guide future programme design.
Studies have examined the association between depressive symptoms and dietary patterns; however, only few studies focused on older adults. The present study examines the association between current and past dietary patterns and depression in a community-dwelling adult population aged 55 years and over. Adults (n 4082) were recruited into the Wellbeing, Eating and Exercise for a Long Life study in Victoria, Australia. In 2010 and 2014, data were collected using self-administered questionnaires including a 111-item FFQ, the RAND thirty-six-item Short Form Health Survey of health-related quality of life and the International Physical Activity Questionnaire. Depressive symptoms were assessed using the Geriatric Depression Scale in 2014. Current (2014) and past (2010) dietary patterns were determined using principal component analysis. Association between dietary patterns and depressive symptoms was assessed using a mixed model analysis with adjustment for covariates. Two similar dietary patterns were identified in men and women (n 2142). In women, a healthy dietary pattern (characterised by frequent intake of vegetables, fruits and fish) was associated with lower levels of depressive symptoms (current diet: β = −0·260, 95 % CI −0·451, −0·070; past diet: β = −0·201, 95 % CI −0·390, −0·013). A current unhealthy dietary pattern in women (characterised by frequent intake of red and processed meat, potatoes, hot chips, cakes, deserts and ice cream) was associated with higher levels of depressive symptoms (β = 1·367, 95 % CI 0·679, 2·056). No associations were identified in men. Further research is needed to confirm these findings and to understand the differences that may occur by sex.
The purpose of the current study was to examine associations of individual and aggregated screen-based behaviours, and total sitting time, with healthy and unhealthy dietary intakes among adolescents.
Cross-sectional study of adolescents. Participants self-reported durations of television viewing, computer use, playing electronic games (e-games), total sitting time, daily servings of fruits and vegetables, and frequency of consumption of sugar-sweetened beverages (SSB), diet beverages, fast foods and discretionary snacks. Logistic regression models were conducted to identify associations of screen-based behaviours, total screen time and total sitting time with dietary intakes.
Adolescents (n 939) in School Year 11 (mean age 16·8 years).
The results showed that watching television (≥2 h/d) was positively associated with consuming SSB and diet beverages each week and consuming discretionary snacks at least once daily, whereas computer use (≥2 h/d) was inversely associated with daily fruit and vegetable intake and positively associated with weekly fast-food consumption. Playing e-games (any) was inversely associated with daily vegetable intake and positively associated with weekly SSB consumption. Total screen (≥2 h/d) and sitting (h/d) times were inversely associated with daily fruit and vegetable consumption, with total screen time also positively associated with daily discretionary snack consumption and weekly consumption of SSB and fast foods.
Individual and aggregated screen-based behaviours, as well as total sitting time, are associated with a number of indicators of healthy and unhealthy dietary intake. Future research should explore whether reducing recreational screen time improves adolescents’ diets.
This study aims to examine repeatability of reduced rank regression (RRR) methods in calculating dietary patterns (DP) and cross-sectional associations with overweight (OW)/obesity across European and Australian samples of adolescents. Data from two cross-sectional surveys in Europe (2006/2007 Healthy Lifestyle in Europe by Nutrition in Adolescence study, including 1954 adolescents, 12–17 years) and Australia (2007 National Children’s Nutrition and Physical Activity Survey, including 1498 adolescents, 12–16 years) were used. Dietary intake was measured using two non-consecutive, 24-h recalls. RRR was used to identify DP using dietary energy density, fibre density and percentage of energy intake from fat as the intermediate variables. Associations between DP scores and body mass/fat were examined using multivariable linear and logistic regression as appropriate, stratified by sex. The first DP extracted (labelled ‘energy dense, high fat, low fibre’) explained 47 and 31 % of the response variation in Australian and European adolescents, respectively. It was similar for European and Australian adolescents and characterised by higher consumption of biscuits/cakes, chocolate/confectionery, crisps/savoury snacks, sugar-sweetened beverages, and lower consumption of yogurt, high-fibre bread, vegetables and fresh fruit. DP scores were inversely associated with BMI z-scores in Australian adolescent boys and borderline inverse in European adolescent boys (so as with %BF). Similarly, a lower likelihood for OW in boys was observed with higher DP scores in both surveys. No such relationships were observed in adolescent girls. In conclusion, the DP identified in this cross-country study was comparable for European and Australian adolescents, demonstrating robustness of the RRR method in calculating DP among populations. However, longitudinal designs are more relevant when studying diet–obesity associations, to prevent reverse causality.
Evidence linking dietary patterns (DP) and obesity and hypertension prevalence is inconsistent. We aimed to identify DP derived from energy density, fibre and sugar intakes, as well as Na, K, fibre, SFA and PUFA, and investigate associations with obesity and hypertension. Adults (n 4908) were included from the cross-sectional Australian Health Survey 2011–2013. Two 24-h dietary recalls estimated food and nutrient intakes. Reduced rank regression derived DP with dietary energy density (DED), fibre density and total sugar intake as response variables for obesity and Na:K, SFA:PUFA and fibre density as variables for hypertension. Poisson regression investigated relationships between DP and prevalence ratios (PR) of overweight/obesity (BMI≥25 kg/m2) and hypertension (blood pressure≥140/90 mmHg). Obesity-DP1 was positively correlated with fibre density and sugars and inversely with DED. Obesity-DP2 was positively correlated with sugars and inversely with fibre density. Individuals in the highest tertile of Obesity-DP1 and Obesity-DP2, compared with the lowest, had lower (PR 0·88; 95 % CI 0·81, 0·95) and higher (PR 1·09; 95 % CI 1·01, 1·18) prevalence of obesity, respectively. Na:K and SFA:PUFA were positively correlated with Hypertension-DP1 and inversely correlated with Hypertension-DP2, respectively. There was a trend towards higher hypertension prevalence in the highest tertile of Hypertension-DP1 compared with the lowest (PR 1·18; 95 % CI 0·99, 1·41). Hypertension-DP2 was not associated with hypertension. Obesity prevalence was inversely associated with low-DED, high-fibre and high-sugar (natural sugars) diets and positively associated with low-fibre and high-sugar (added sugars) diets. Hypertension prevalence was higher on low-fibre and high-Na and SFA diets.
FFQs are a popular method of capturing dietary information in epidemiological studies and may be used to derive dietary exposures such as nutrient intake or overall dietary patterns and diet quality. As FFQs can involve large numbers of questions, participants may fail to respond to all questions, leaving researchers to decide how to deal with missing data when deriving intake measures. The aim of the present commentary is to discuss the current practice for dealing with item non-response in FFQs and to propose a research agenda for reporting and handling missing data in FFQs.
Single imputation techniques, such as zero imputation (assuming no consumption of the item) or mean imputation, are commonly used to deal with item non-response in FFQs. However, single imputation methods make strong assumptions about the missing data mechanism and do not reflect the uncertainty created by the missing data. This can lead to incorrect inference about associations between diet and health outcomes. Although the use of multiple imputation methods in epidemiology has increased, these have seldom been used in the field of nutritional epidemiology to address missing data in FFQs. We discuss methods for dealing with item non-response in FFQs, highlighting the assumptions made under each approach.
Researchers analysing FFQs should ensure that missing data are handled appropriately and clearly report how missing data were treated in analyses. Simulation studies are required to enable systematic evaluation of the utility of various methods for handling item non-response in FFQs under different assumptions about the missing data mechanism.
Fe deficiency remains the most common nutritional deficiency worldwide and young children are at particular risk. Preventative food-based strategies require knowledge of current intakes, sources of Fe, and factors associated with low Fe intakes; yet few data are available for Australian children under 2 years. This study’s objectives were to determine intakes and food sources of Fe for Australian infants and toddlers and identify non-dietary factors associated with Fe intake. Dietary, anthropometric and socio-demographic data from the Melbourne Infant Feeding, Activity and Nutrition Trial Program were analysed for 485 infants (mean age: 9·1 (sd 1·2) months) and 423 toddlers (mean age: 19·6 (sd 2·6) months) and their mothers. Dietary intakes were assessed via 24-h recalls over 3 non-consecutive days. Prevalence of inadequate Fe intake was estimated using the full probability approach. Associations between potential non-dietary predictors (sex, breast-feeding status, age when introduced to solid foods, maternal age, maternal education, maternal employment status and mother’s country of birth) and Fe intakes were assessed using linear regression. Mean Fe intakes were 9·1 (sd 4·3) mg/d for infants and 6·6 (sd 2·4) mg/d for toddlers. Our results showed that 32·6 % of infants and 18·6 % of toddlers had inadequate Fe intake. Main food sources of Fe were Fe-fortified infant formula and cereals for infants and toddlers, respectively. Female sex and current breast-feeding were negatively associated with infant Fe intakes. Introduction to solid foods at or later than 6 months was negatively associated with Fe intake in toddlers. These data may facilitate food-based interventions to improve Australian children’s Fe intake levels.
We aimed to investigate the association between multiple measures of socio-economic position (SEP) and diet quality, using a diet quality index representing current national dietary guidelines, in the Australian adult population.
Cross-sectional study. Linear regression analyses were used to estimate the association between indicators of SEP (educational attainment, level of income and area-level disadvantage) and diet quality (measured using the Dietary Guideline Index (DGI)) in the total sample and stratified by sex and age (≤55 years and >55 years).
A large randomly selected sample of the Australian adult population.
Australian adults (n 9296; aged ≥25 years) from the Australian Diabetes, Obesity and Lifestyle Study.
A higher level of educational attainment and income and a lower level of area-level disadvantage were significantly associated with a higher DGI score, across the gradient of SEP. The association between indicators of SEP and DGI score was consistently stronger among those aged ≤55 years compared with their older counterparts. The most disadvantaged group had a DGI score between 2 and 5 units lower (depending on the marker of SEP) compared with the group with the least disadvantage.
A higher level of SEP was consistently associated with a higher level of diet quality for all indicators of SEP examined. In order to reduce socio-economic inequalities in diet quality, healthy eating initiatives need to act across the gradient of socio-economic disadvantage with a proportionate focus on those with greater socio-economic disadvantage.
To investigate: (i) how lunch frequency of adolescents varies between schools and between classes within schools; (ii) the associations between frequency of lunch and individual sociodemographic factors and school characteristics; and (iii) if any observed associations between lunch frequency and school characteristics vary by gender and age groups.
Cross-sectional study in which students and school headmasters completed self-administered questionnaires. Associations were estimated by multilevel multivariate logistic regression.
The Danish arm of the Health Behaviour in School-Aged Children study 2010.
Students (n 4922) aged 11, 13 and 15 years attending a random sample of seventy-three schools.
The school-level and class-level variations in low lunch frequency were small (intraclass correlation coefficient <2·1 %). At the individual level, low lunch frequency was most common among students who were boys, 13- and 15-year-olds, from medium and low family social class, descendants of immigrants, living in a single-parent family and in a reconstructed family. School-level analyses suggested that having access to a canteen at school was associated with low lunch frequency (OR=1·47; 95% CI 1·14, 1·89). Likewise not having an adult present during lunch breaks was associated with low lunch frequency (OR=1·44; 95% CI 1·18, 1·75). Cross-level interactions suggested that these associations differed by age group.
Lunch frequency among Danish students appears to be largely influenced by sociodemographic factors. Additionally, the presence of an adult during lunch breaks promotes frequent lunch consumption while availability of a canteen may discourage frequent lunch consumption. These findings vary between older and younger students.
Traditionally, nutrition research has focused on individual nutrients, and more recently dietary patterns. However, there has been relatively little focus on dietary intake at the level of a ‘meal’. The purpose of the present paper was to review the literature on adults' meal patterns, including how meal patterns have previously been defined and their associations with nutrient intakes and diet quality. For this narrative literature review, a comprehensive search of electronic databases was undertaken to identify studies in adults aged ≥ 19 years that have investigated meal patterns and their association with nutrient intakes and/or diet quality. To date, different approaches have been used to define meals with little investigation of how these definitions influence the characterisation of meal patterns. This review identified thirty-four and fourteen studies that have examined associations between adults' meals patterns, nutrient intakes and diet quality, respectively. Most studies defined meals using a participant-identified approach, but varied in the additional criteria used to determine individual meals, snacks and/or eating occasions. Studies also varied in the types of meal patterns, nutrients and diet quality indicators examined. The most consistent finding was an inverse association between skipping breakfast and diet quality. No consistent association was found for other meal patterns, and little research has examined how meal timing is associated with diet quality. In conclusion, an understanding of the influence of different meal definitions on the characterisation of meal patterns will facilitate the interpretation of the existing literature, and may provide guidance on the most appropriate definitions to use.
Sufficient dairy food consumption during adolescence is necessary for preventing disease. While socio-economically disadvantaged adolescents tend to consume few dairy foods, some eat quantities more in line with dietary recommendations despite socio-economic challenges. Socio-economic variations in factors supportive of adolescents’ frequent dairy consumption remain unexplored. The present study aimed to identify cross-sectional and longitudinal associations between intrapersonal, social and environmental factors and adolescents’ frequent dairy consumption at baseline and two years later across socio-economic strata, and to examine whether socio-economic position moderated observed effects.
Online surveys completed at baseline (2004–2005) and follow-up (2006–2007) included a thirty-eight-item FFQ and questions based on social ecological models examining intrapersonal, social and environmental dietary influences.
Thirty-seven secondary schools in Victoria, Australia.
Australian adolescents (n 1201) aged 12–15 years, drawn from a sub-sample of 3264 adolescents (response rate=33 %).
While frequent breakfast consumption was cross-sectionally associated with frequent dairy consumption among all adolescents, additional associated factors differed by socio-economic position. Baseline dairy consumption longitudinally predicted consumption at follow-up. No further factors predicted frequent consumption among disadvantaged adolescents, while four additional factors were predictive among advantaged adolescents. Socio-economic position moderated two predictors; infrequently eating dinner alone and never purchasing from school vending machines predicted frequent consumption among advantaged adolescents.
Nutrition promotion initiatives aimed at improving adolescents’ dairy consumption should employ multifactorial approaches informed by social ecological models and address socio-economic differences in influences on eating behaviours; e.g. selected intrapersonal factors among all adolescents and social factors (e.g. mealtime rules) among advantaged adolescents.
Findings from research that has assessed the influence of dietary factors on child obesity have been equivocal. In the present study, we aimed to test the hypothesis that a positive change in diet quality is associated with favourable changes in BMI z-scores (zBMI) in schoolchildren from low socio-economic backgrounds and to examine whether this effect is modified by BMI category at baseline. The present study utilised data from a subsample (n 216) of the Resilience for Eating and Activity Despite Inequality study, a longitudinal cohort study with data collected in 2007–8 (T1) and 2010–11 (T2) in socio-economically disadvantaged women and children (5–12 years at T1). Dietary data were collected using a FFQ and diet quality index (DQI) scores derived at both time points. The objective measures of weight, height and physical activity (accelerometers) were included. The other variables were reported in the questionnaires. We examined the association between change in DQI and change in zBMI, using linear regression analyses adjusted for physical activity, screen sedentary behaviour and maternal education level both in the whole sample and in the sample stratified by overweight status at baseline. After accounting for potential covariates, change in diet quality was found to be inversely associated with change in zBMI only in children who were overweight at baseline (P= 0·035), thus supporting the hypothesis that improvement in diet quality is associated with a concurrent improvement in zBMI among already overweight children, but not among those with a normal BMI status. The identification of modifiable behaviours such as diet quality that affect zBMI longitudinally is valuable to inform future weight gain prevention interventions in vulnerable groups.