Estimating the Effect of Recurrent Infectious Diseases on Nutritional Status: Sampling Frequency, Sample-size, and Bias

Wolf-Peter Schmidt,Stephen P Luby,Bernd Genser,Zaid Chalabi

doi:10.3329/jhpn.v29i4.8447

Abstract

There is an ongoing interest in studying the effect of common recurrent infections and conditions, such as diarrhoea, respiratory infections, and fever, on the nutritional status of children at risk of malnutrition. Epidemiological studies exploring this association need to measure infections with sufficient accuracy to minimize bias in the effect estimates. A versatile model of common recurrent infections was used for exploring how many repeated measurements of disease are required to maximize the power and logistical efficiency of studies investigating the effect of infectious diseases on malnutrition without compromising the validity of the estimates. Depending on the prevalence and distribution of disease within a population, 15-30 repeat measurements per child over one year should be sufficient to provide unbiased estimates of the association between infections and nutritional status. Less-frequent measurements lead to a bias in the effect size towards zero, especially if disease is rare. In contrast, recall error can lead to exaggerated effect sizes. Recall periods of three days or shorter may be preferable compared to longer recall periods. The results showed that accurate estimation of the association between recurrent infections and nutritional status required closer follow-up of study participants than studies using recurrent infections as an outcome measure. The findings of the study provide guidance for choosing an appropriate sampling strategy to explore this association.

Highlights

Nutritional status is an important risk factor for many infectious diseases in childhood [1,2,3] and for impairments in cognitive development and premature death [1]
Using a versatile model of common recurrent infections [11], we explored how many repeated measurements of disease are required to maximize the power and logistical efficiency of studies investigating the effect of infectious diseases on malnutrition without compromising the validity of the estimates
Our analysis shows that random error in the measurement of the disease estimates can lead to estimates biased towards zero while recall error may inflate the size of the effect

Summary

Introduction

Nutritional status is an important risk factor for many infectious diseases in childhood [1,2,3] and for impairments in cognitive development and premature death [1]. To set the right public-health priorities to achieve sustained improvements in health and economic development in low-income settings, it is important to obtain a better understanding of the link between infectious diseases and nutrition [5]. Another challenge is the choice of the surveillance strategy to measure the prevalence of infections which, in contrast to assessing the nutritional status of children, usually requires many repeated measurements. The presence or absence of infection is much more variable over time than, for example, the child’s weight or height. It is not clear how precise the measurement of the prevalence of the infectious disease under study needs to be to estimate reliably the association between recurrent infections and nutritional status. The objective of this study was to identify the optimal balance between two contrasting barriers to obtaining valid estimates:

Objectives

Methods

Results

Conclusion