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Open Access Research article

Temporal patterns in count-to-ten fetal movement charts and their associations with pregnancy characteristics: a prospective cohort study

Brita Askeland Winje1*, Jo Røislien12 and J Frederik Frøen1

Author affiliations

1 Division of Epidemiology, Norwegian Institute of Public Health, PO Box 4404 , Nydalen, 0403, Oslo, Norway

2 Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway

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Citation and License

BMC Pregnancy and Childbirth 2012, 12:124  doi:10.1186/1471-2393-12-124

Published: 6 November 2012

Abstract

Background

Fetal movement counting has long been suggested as a screening tool to identify impaired placental function. However, quantitative limits for decreased fetal movement perform poorly for screening purposes, indicating the need for methodological refinement. We aimed to identify the main individual temporal patterns in fetal movement counting charts, and explore their associations with pregnancy characteristics.

Methods

In a population-based prospective cohort in Norway, 2009–2011, women with singleton pregnancies counted fetal movements daily from pregnancy week 24 until delivery using a modified "count-to-ten” procedure. To account for intra-woman correlation of observations, we used functional data analysis and corresponding functional principal component analysis to identify the main individual temporal patterns in fetal movement count data. The temporal patterns are described by continuous functional principal component (FPC) curves, with an individual score on each FPC for each woman. These scores were later used as outcome variables in multivariable linear regression analyses, with pregnancy characteristics as explanatory variables.

Results

Fetal movement charts from 1086 pregnancies were included. Three FPC curves explained almost 99% of the variation in the temporal data, with the first FPC, representing the individual overall counting time, accounting for 91% alone. There were several statistically significant associations between the FPCs and various pregnancy characteristics. However, the effects were small and of limited clinical value.

Conclusions

This statistical approach for analyzing fetal movement counting data successfully captured clinically meaningful individual temporal patterns and how these patterns vary between women. Maternal body mass index, gestational age and placental site explained little of the variation in the temporal fetal movement counting patterns. Thus, a perceived decrease in fetal movement should not be attributed to a woman’s basic pregnancy characteristics, but assessed as a potential marker of risk.

Keywords:
Fetal movement; Kick counting; Decreased fetal movement; Functional data analysis; Principal components; Temporal pattern