Usual intake of meat in Australians: secondary analysis of the 2011–12 National Nutrition and Physical Activity Survey using the NCI method

2020 ◽  
Vol 33 (4) ◽  
pp. 505-517 ◽  
Author(s):  
C. L. Birrell ◽  
E. P. Neale ◽  
Y. C. Probst
Nutrients ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 4128
Author(s):  
Dimity C. Dutch ◽  
Rebecca K. Golley ◽  
Brittany J. Johnson

Daily routines may influence children and adolescents’ eating patterns, however the influence of days of the week on dietary intake has rarely been explored. This study aimed to examine discretionary choices intake in the context of diet quality on weekdays versus weekends. A secondary analysis was conducted using the Australian National Nutrition and Physical Activity Survey 2011–2012. Differences in discretionary choices intake and diet quality on weekdays versus weekends, were examined using ANCOVA analyses. Associations between child and parent-proxy characteristics and weekday/weekend discretionary choices intake were examined using multivariable regression models. Primary analyses included 2584 Australian 2–17-year-olds. There were small differences in discretionary choices intake and diet quality between weekdays and weekends in all age subgroups. Compared to weekdays, intakes on weekends were characterized by a higher intake of discretionary choices, and lower total Dietary Guidelines Index for Children and Adolescents (DGI-CA) scores across the age subgroups (all p < 0.01). Parent-proxy discretionary choices intake and child age were predictors of weekday and weekend discretionary choices intake. Parent-proxy obesity weight status compared with healthy weight status was a predictor of weekend intake, while parent-proxy education level was a predictor of weekday discretionary choices intake. Future intervention strategies should target discretionary choices intake on both weekdays and weekends.


2021 ◽  
pp. 1-19
Author(s):  
Vivienne Guan ◽  
Elizabeth Neale ◽  
Yasmine Probst

Abstract Avocados are a rich source of nutrients including monounsaturated fats, dietary fibre, potassium and magnesium, as well as phytochemicals. However, no epidemiological analysis for the associations between avocado consumption and participant anthropometric measures has been conducted in Australia. The present study aimed to perform a secondary analysis of the 2011-2012 National Nutrition and Physical Activity Survey (NNPAS) to quantify avocado consumption in the Australian population and explore the associations between avocado intakes, consumption of nutrients and food groups based on the Australian Dietary Guidelines (ADGs) and anthropometric measurements. Usual avocado consumption in the 2011–2012 NNPAS was determined using the multiple source method regression model. The relationship between avocado consumption and intakes of key nutrients and food groups, and participant weight, BMI and waist circumference were examined using linear regression. Mean avocado intake was 2.56 (95% CI: 2.37, 2.75) grams per day with 15.9 % of Australians considered to be ‘avocado consumers’ (n=21,526,456 population size; n=12,153 observations). Greater consumption (g) of avocados was associated with significantly higher consumption of monounsaturated fats, polyunsaturated fats, dietary fibre, vitamin E, magnesium and potassium, as well as ‘whole grains’, ‘vegetables’, ‘fruit’ and ‘meat and alternatives’ food groups. Greater consumption (g) avocados was associated with significantly lower consumption of carbohydrates and discretionary foods. When adjusted for covariates, greater consumption of avocados was significantly associated with a lower body weight (p=0.034), BMI (p<0.001), and waist circumference (p<0.001). Avocados may be incorporated into an eating pattern, and may be beneficial in weight management.


2020 ◽  
Vol 23 (8) ◽  
pp. 1307-1319 ◽  
Author(s):  
Katrina R Kissock ◽  
Elizabeth P Neale ◽  
Eleanor J Beck

AbstractObjective:To determine the impacts of using a whole grain food definition on measurement of whole grain intake compared with calculation of total grams of intake irrespective of the source.Design:The Australian whole grain database was expanded to identify foods that comply with the Healthgrain whole grain food definition (≥30 % whole grains on a dry weight basis, whole grain ingredients exceeds refined grain and meeting accepted standards for healthy foods based on local regulations). Secondary analysis of the National Nutrition and Physical Activity Survey (NNPAS) 2011–2012 dietary intake data included calculation of whole grain intakes based on intake from foods complying with the Healthgrain definition. These were compared with intake values where grams of whole grain in any food had been included.Setting:Australia.Participants:Australians (≥2 years) who participated in the NNPAS 2011–2012 (n 12 153).Results:Following expansion of the whole grain database, 214 of the 609 foods containing any amount of whole grain were compliant with the Healthgrain definition. Significant mean differences (all P < 0·05) of 2·84–6·25 g/d of whole grain intake (5·91–9·44 g/d energy adjusted) were found when applying the Healthgrain definition in comparison with values from foods containing any whole grain across all age groups.Conclusions:Application of a whole grain food definition has substantial impact on calculations of population whole grain intakes. While use of such definitions may prove beneficial in settings such as whole grain promotion, the underestimation of total intake may impact on identification of any associations between whole grain intake and health outcomes.


2020 ◽  
Vol 23 (18) ◽  
pp. 3368-3378 ◽  
Author(s):  
Cassandra J Nikodijevic ◽  
Yasmine C Probst ◽  
Marijka J Batterham ◽  
Linda C Tapsell ◽  
Elizabeth P Neale

AbstractObjective:Nut consumption is associated with a range of health benefits. The current study aimed to examine nut consumption in the 2011–2012 National Nutrition and Physical Activity Survey (NNPAS) and to investigate associations between nut intake, nutrient intake and anthropometric and blood pressure measurements.Design:Secondary analysis of the 2011–2012 NNPAS. Usual consumption of nuts in the 2011–2012 NNPAS was determined, and nut consumption was compared with population recommendations of 30 g nuts per day. The relationship between nut consumption and intakes of key nutrients, anthropometric outcomes (weight, BMI and waist circumference) and blood pressure was examined using linear regression for participants aged over 18 years.Setting:Australia.Participants:Australians (2 years and older, n 12 153) participating in the representative 2011–2012 NNPAS.Results:Mean nut intake was 4·61 (95 % CI: 4·36, 4·86) g/d, with only 5·6 % of nut consumers consuming 30 g of nuts per day. Nut consumption was associated with significantly greater intakes of fibre, vitamin E, Fe, Mg and P. There was no association between nut consumption and body weight, BMI, waist circumference, or blood pressure.Conclusions:Exploration of nut consumption in a representative sample of Australians identified that nut intake does not meet recommendations. Higher nut consumption was not adversely associated with higher body weight, aligning with the current evidence base. Given the current levels of nut consumption in Australia, strategies to increase nut intake to recommended levels are required.


2019 ◽  
Vol 22 (18) ◽  
pp. 3315-3326
Author(s):  
Carole L Birrell ◽  
David G Steel ◽  
Marijka J Batterham ◽  
Ankur Arya

AbstractObjective:To conduct nutrition-related analyses on large-scale health surveys, two aspects of the survey must be incorporated into the analysis: the sampling weights and the sample design; a practice which is not always observed. The present paper compares three analyses: (1) unweighted; (2) weighted but not accounting for the complex sample design; and (3) weighted and accounting for the complex design using replicate weights.Design:Descriptive statistics are computed and a logistic regression investigation of being overweight/obese is conducted using Stata.Setting:Cross-sectional health survey with complex sample design where replicate weights are supplied rather than the variables containing sample design information.Participants:Responding adults from the National Nutrition and Physical Activity Survey (NNPAS) part of the Australian Health Survey (2011–2013).Results:Unweighted analysis produces biased estimates and incorrect estimates of se. Adjusting for the sampling weights gives unbiased estimates but incorrect se estimates. Incorporating both the sampling weights and the sample design results in unbiased estimates and the correct se estimates. This can affect interpretation; for example, the incorrect estimate of the OR for being a current smoker in the unweighted analysis was 1·20 (95 % CI 1·06, 1·37), t= 2·89, P = 0·004, suggesting a statistically significant relationship with being overweight/obese. When the sampling weights and complex sample design are correctly incorporated, the results are no longer statistically significant: OR = 1·06 (95 % CI 0·89, 1·27), t = 0·71, P = 0·480.Conclusions:Correct incorporation of the sampling weights and sample design is crucial for valid inference from survey data.


2019 ◽  
Vol 5 (1) ◽  
pp. e000517 ◽  
Author(s):  
Brad Stenner ◽  
Amber D Mosewich ◽  
Jonathan D Buckley ◽  
Elizabeth S Buckley

ObjectiveTo investigate associations between markers of health and playing golf in an Australian population.MethodsSecondary analysis of data from the Australian National Nutrition and Physical Activity Survey to compare selected health outcomes between golfers (n=128) and non-golfers (n=4999).ResultsGolfers were older than non-golfers (mean±SD 57.7±14.2 years, 48.5±17.6 years, p<0.05). A higher proportion of golfers were overweight or obese compared with non-golfers (76% vs 64%, p<0.05), and golfers were more likely to have been diagnosed with ischaemic heart disease (IHD) at some time in their life (OR 2.8, 95% CI 1.0 to 7.8). However, neither the risk of being overweight or obese (OR 1.4, 95% CI 0.9 to 2.2) or having been diagnosed with IHD (OR 2.1, 95% CI 0.8 to 5.8), were significant after controlling for age. Golfers were more physically active than non-golfers (8870±3810 steps/day vs 7320±3640 steps/day, p<0.05) and more likely to report high health-related quality of life (HRQoL) than non-golfers (OR 1.8; 95% CI 1.0 to 3.3), but not after adjusting for physical activity (OR 1.4, 95% CI 0.9 to 2.2).ConclusionCompared with non-golfers, golfers were more likely to be overweight or obese and to have been diagnosed with IHD, but not after adjusting for golfers being older. Golfers were more likely to report a higher HRQoL, but not after adjusting for golfers being more physically active. There may be an association between golfers being more physically active than non-golfers and reporting a higher HRQoL.


2019 ◽  
Vol 22 (15) ◽  
pp. 2793-2802 ◽  
Author(s):  
Sofia Vilela ◽  
Daniela Correia ◽  
Milton Severo ◽  
Andreia Oliveira ◽  
Duarte Torres ◽  
...  

AbstractObjective:To evaluate daily eating frequency (main meals and snacks) in relation to weight status in children aged 3–9 years, representative of the Portuguese population.Design:Cross-sectional study. Dietary intake was estimated as the mean of two non-consecutive days of food diaries, followed by face-to-face interviews. Weight and height were measured by trained observers. Eating occasions (EO) were defined by the children’s caregiver; an EO was considered separate if the time of consumption was different from other EO and it provided at least 209 kJ (50 kcal). Main meals defined as ‘breakfast’, ‘lunch’ and ‘dinner’ could be selected only once per day. The remaining EO were considered snacks. The association between eating frequency and overweight/obesity was evaluated through logistic regressions weighted for the population distribution.Setting:National Food, Nutrition and Physical Activity Survey of the Portuguese population, 2015–2016.Participants:Portuguese children aged 3–9 years with complete dietary data and anthropometric measurements (n 517).Results:Overall, the number of daily EO ranged from 3·5 to 11, and on average children had 5·7 daily EO. After adjustment for child’s sex, age and total energy intake, and considering only plausible energy intake reporters, having < 3 snacks/d was positively associated with being overweight/obese (OR = 1·98; 95 % CI 1·00, 3·90), compared with having ≥ 3 snacks/d.Conclusions:Lower daily frequency of EO was associated with increased odds of being overweight or obese in children. A higher eating frequency, maintaining the same energy intake, seems to contribute to a healthy body weight in children.


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