ArticlePublic health nutrition2019
How to use replicate weights in health survey analysis using the National Nutrition and Physical Activity Survey as an example.
Article in Public health nutrition, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
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- Comparison of associations of intake of ultra-processed and non-ultra-processed whole-grain foods with cardiometabolic risk measures in Australian and US adults.European journal of nutrition · 2026Article
- Pulse consumption of Australian adolescents: characteristics and consumption patterns in a national survey.The British journal of nutrition · 2026Article
- Silent echoes: understanding and predicting the widespread mental health impact of mass shootings.Frontiers in public health · 2026Article
- Evaluating factors associated with awareness and attitude towards pre-exposure prophylaxis among cisgender sexually active women in Ghana.BMC public health · 2025Article
- Workforce Psychological Distress and Absenteeism in Australia: The Correlates of Industry, Age, and Gender.Asia-Pacific journal of public health · 2025Article
- Childhood Transitions Between Weight Status Categories: Evidence from the UK Millennium Cohort Study.PharmacoEconomics · 2024Article
- Avocado intake and cardiometabolic risk factors in a representative survey of Australians: a secondary analysis of the 2011-2012 national nutrition and physical activity survey.Nutrition journal · 2024Article
- Exploring Functions and Predictors of Digital Health Engagement Among German Internet Users: Survey Study.Journal of medical Internet research · 2023Article
- Investigating the measurement of academic resilience in Aotearoa New Zealand using international large-scale assessment data.Educational assessment, evaluation and accountability · 2023Article
- 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.The British journal of nutrition · 2022Article
- The Profiling of Diet and Physical Activity in Reproductive Age Women and Their Association with Body Mass Index.Nutrients · 2022Article
- Nut consumption in a representative survey of Australians: a secondary analysis of the 2011-2012 National Nutrition and Physical Activity Survey.Public health nutrition · 2020Article
- Industry differences in psychological distress and distress-related productivity loss: A cross-sectional study of Australian workers.Journal of occupational healthArticle
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveTo 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.
designDescriptive statistics are computed and a logistic regression investigation of being overweight/obese is conducted using Stata.
settingCross-sectional health survey with complex sample design where replicate weights are supplied rather than the variables containing sample design information.
participantsResponding adults from the National Nutrition and Physical Activity Survey (NNPAS) part of the Australian Health Survey (2011-2013).
resultsUnweighted 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.
conclusionsCorrect incorporation of the sampling weights and sample design is crucial for valid inference from survey data.
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