Consumption of avocado and associations with nutrient, food, and anthropometric measures in a representative survey of Australians: a secondary analysis of the 2011–2012 National Nutrition and Physical Activity Survey

2021 ◽  
pp. 1-19
Author(s):  
Vivienne Guan ◽  
Elizabeth Neale ◽  
Yasmine Probst
Keyword(s):  
Physical Activity ◽  
Waist Circumference ◽  
Dietary Fibre ◽  
Secondary Analysis ◽  
Food Groups ◽  
Anthropometric Measures ◽  
Eating Pattern ◽  
Monounsaturated Fats ◽  
Nutrition And Physical Activity ◽  
Activity Survey

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.

scholarly journals Nut consumption in a representative survey of Australians: a secondary analysis of the 2011–2012 National Nutrition and Physical Activity Survey

2020 ◽  
Vol 23 (18) ◽  
pp. 3368-3378 ◽  
Author(s):  
Cassandra J Nikodijevic ◽  
Yasmine C Probst ◽  
Marijka J Batterham ◽  
Linda C Tapsell ◽  
Elizabeth P Neale
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Body Weight ◽  
Waist Circumference ◽  
Secondary Analysis ◽  
Current Evidence ◽  
Current Evidence Base ◽  
Nutrition And Physical Activity ◽  
Activity Survey ◽  
Nut Intake

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.

scholarly journals Breakfast Choice Is Associated with Nutrient, Food Group and Discretionary Intakes in Australian Adults at Both Breakfast and the Rest of the Day

Nutrients ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 175 ◽  
Author(s):  
Flavia Fayet-Moore ◽  
Andrew McConnell ◽  
Tim Cassettari ◽  
Peter Petocz
Keyword(s):  
Physical Activity ◽  
Waist Circumference ◽  
Fruits And Vegetables ◽  
Economic Status ◽  
Food Group ◽  
Activity Levels ◽  
Food Groups ◽  
Nutrient Intakes ◽  
Breakfast Cereal ◽  
Anthropometric Measures

Breakfast choice is correlated with daily nutrient intakes, but this association may not be solely explained by the breakfast meal. We profiled breakfast consumer groups among Australian adults and compared the role that breakfast versus the rest of the day had on daily intakes of the Five Food Groups, discretionary foods, and nutrients. Breakfast groups were breakfast cereal consumers, non-cereal breakfast consumers, and breakfast skippers. One-day dietary recall data from the 2011–2012 National Nutrition and Physical Activity Survey were analysed (n = 9341, ≥19 years), as well as socio-demographic and anthropometric measures. Twelve per cent of adults were breakfast skippers, 41% were breakfast cereal consumers, and 47% were non-cereal breakfast consumers. Females were more likely to have a non-cereal breakfast than males, and the non-cereal breakfast was predominantly bread-based. Breakfast skipping decreased with age (p < 0.001), while breakfast cereal consumption increased with age (p < 0.001). Breakfast skippers were more likely to be male, had a lower socio-economic status, and lower physical activity levels (p < 0.001). Breakfast skippers had the highest mean body mass index (BMI) and waist circumference (p < 0.001), the lowest intake of wholegrain foods, fruits and vegetables, and the highest intake of discretionary foods (p < 0.001). Breakfast cereal consumers had the lowest mean BMI and waist circumference (p < 0.001) and had healthier diets at both breakfast and throughout the rest of the day. They were the most likely to meet the daily recommended serves for grain foods, fruit, dairy, and vegetables, had the highest wholegrain food intake, and the lowest discretionary intake (p < 0.001). Additionally, breakfast cereal consumers had the most favourable daily nutrient intakes, including the lowest added sugars intakes. Differences in daily diet between breakfast groups were attributed to differences in food choices both at breakfast and throughout the rest of the day.

scholarly journals Diet Quality of Australian Children and Adolescents on Weekdays versus Weekend Days: A Secondary Analysis of the National Nutrition and Physical Activity Survey 2011–2012

Nutrients ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 4128
Author(s):  
Dimity C. Dutch ◽  
Rebecca K. Golley ◽  
Brittany J. Johnson
Keyword(s):  
Physical Activity ◽  
Children And Adolescents ◽  
Diet Quality ◽  
Weight Status ◽  
Secondary Analysis ◽  
Healthy Weight ◽  
Discretionary Choices ◽  
Nutrition And Physical Activity ◽  
Activity Survey ◽  
Parent Proxy

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.

scholarly journals The relevance of whole grain food definitions in estimation of whole grain intake: a secondary analysis of the National Nutrition and Physical Activity Survey 2011–2012

2020 ◽  
Vol 23 (8) ◽  
pp. 1307-1319 ◽  
Author(s):  
Katrina R Kissock ◽  
Elizabeth P Neale ◽  
Eleanor J Beck
Keyword(s):  
Physical Activity ◽  
Age Groups ◽  
Secondary Analysis ◽  
Dry Weight ◽  
Healthy Foods ◽  
Whole Grain ◽  
Substantial Impact ◽  
Nutrition And Physical Activity ◽  
Mean Differences ◽  
Activity Survey

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.

How to use replicate weights in health survey analysis using the National Nutrition and Physical Activity Survey as an example

2019 ◽  
Vol 22 (18) ◽  
pp. 3315-3326
Author(s):  
Carole L Birrell ◽  
David G Steel ◽  
Marijka J Batterham ◽  
Ankur Arya
Keyword(s):  
Physical Activity ◽  
Health Survey ◽  
Large Scale ◽  
Sample Design ◽  
Sampling Weights ◽  
Complex Sample ◽  
Unbiased Estimates ◽  
Nutrition And Physical Activity ◽  
Activity Survey ◽  
Complex Sample Design

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.

scholarly journals The impact of complex survey design on prevalence estimates of intakes of food groups in the Australian National Children's Nutrition and Physical Activity Survey

2011 ◽  
Vol 15 (8) ◽  
pp. 1362-1372 ◽  
Author(s):  
Sandy Burden ◽  
Yasmine Probst ◽  
David Steel ◽  
Linda Tapsell
Keyword(s):  
Physical Activity ◽  
Survey Design ◽  
Food Groups ◽  
Sample Design ◽  
Complex Survey ◽  
Children's Nutrition ◽  
Prevalence Estimates ◽  
Complex Survey Design ◽  
Activity Survey ◽  
The Impact

AbstractObjectiveTo assess the impact of the complex survey design used in the 2007 Australian National Children's Nutrition and Physical Activity Survey (ANCNPAS07) on prevalence estimates for intakes of groups of foods in the population of children.DesignThe impacts on prevalence estimates were determined by calculating design effects for values for food group consumption. The implications of ignoring elements of the sample design including stratification, clustering and weighting are discussed.SettingThe ANCNPAS07 used a complex sample design involving stratification, a high degree of clustering and estimation weights.SubjectsAustralian children aged 2–16 years.ResultsDesign effects ranging from <1 to 5 were found for the values of mean consumption and proportion of the population consuming the food groups. When survey weights were ignored, prevalence estimates were also biased.ConclusionsIgnoring the complex survey design used in the ANCNPAS07 could result in underestimating the width of confidence intervals, higher mean square errors and biased estimators. The magnitude of these effects depends on both the parameter under consideration and the chosen estimator.

scholarly journals Associations between markers of health and playing golf in an Australian population

2019 ◽  
Vol 5 (1) ◽  
pp. e000517 ◽  
Author(s):  
Brad Stenner ◽  
Amber D Mosewich ◽  
Jonathan D Buckley ◽  
Elizabeth S Buckley
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Secondary Analysis ◽  
Health Related Quality ◽  
Australian Population ◽  
Physically Active ◽  
Related Quality ◽  
Health Related ◽  
Activity Survey

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.

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