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    Wu, Yue Zhang, Wei Zhang, Lin Schwebel, David C. Ning, Peishan Cheng, Xunjie Deng, Xin Li, Li Deng, Jing and Hu, Guoqing 2016. Non-fatal injuries treated outside a hospital in Hunan, China: results from a household interview survey. The European Journal of Public Health, p. ckw114.


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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

  • Sandy Burden (a1), Yasmine Probst (a2), David Steel (a1) and Linda Tapsell (a2)
  • DOI: http://dx.doi.org/10.1017/S1368980011003326
  • Published online: 08 December 2011
Abstract
AbstractObjective

To 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.

Design

The 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.

Setting

The ANCNPAS07 used a complex sample design involving stratification, a high degree of clustering and estimation weights.

Subjects

Australian children aged 2–16 years.

Results

Design 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.

Conclusions

Ignoring 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.

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Copyright
Corresponding author
*Corresponding author: Email sburden@uow.edu.au
Linked references
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This list contains references from the content that can be linked to their source. For a full set of references and notes please see the PDF or HTML where available.

2.R Clark & DG Steel (2002) The effect of using household as a sampling unit. Int Stat Rev 70, 289314.

4.RL Chambers & CJ Skinner (2003) Analysis of Survey Data. Chichester: Wiley and Sons.

5.D Pfeffermann (1996) The use of sampling weights for survey data analysis. Stat Methods Med Res 5, 239261.

13.J Gambino (2009) Design effect caveats. Am Stat 63, 141146.

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Public Health Nutrition
  • ISSN: 1368-9800
  • EISSN: 1475-2727
  • URL: /core/journals/public-health-nutrition
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