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J Epidemiol. 2010;20(6):446-52. Epub 2010 Sep 18.

Characteristics of accelerometry respondents to a mail-based surveillance study.

Author information

1
Department of Preventive Medicine and Public Health, Tokyo Medical University, Tokyo, Japan. inoue@tokyo-med.ac.jp

Abstract

BACKGROUND:

Differences in the characteristics of respondents and nonrespondents to a survey can be a cause of selection bias. The aim of this study was to determine the sociodemographic and lifestyle characteristics of respondents to a field-based accelerometry survey.

METHODS:

A cross-sectional mail survey was sent to 4000 adults (50% male; age 20 to 69 years) who were randomly selected from the registries of residential addresses of 4 cities in Japan. There were 1508 respondents (responding subsample) to the initial questionnaire. A total of 786 participants from the responding subsample also agreed to wear an accelerometer for 7 days (accelerometer subsample). Age, sex, and city of residence were compared between the accelerometer subsample and all 3214 nonrespondents, including those who did not respond to the initial questionnaire. In addition, multiple logistic regression analyses were used to compare the sociodemographic and lifestyle characteristics of the accelerometer subsample and the 722 respondents who participated in the questionnaire survey but not the accelerometry (questionnaire-only subsample).

RESULTS:

As compared with all nonrespondents, the accelerometer subsample included significantly more women, middle-aged and older adults, and residents of specific cities. Multiple logistic regression analyses comparing the accelerometer and questionnaire-only subsamples revealed that participation in the accelerometry survey was greater among nonsmokers (odds ratio, 1.35; 95% confidence interval, 1.02-1.79) and persons who reported a habit of leisure walking (1.56, 1.21-2.01).

CONCLUSIONS:

Sex, age, city of residence, smoking status, and leisure walking were associated with participation in accelerometry. This response pattern reveals potential selection bias in mail-based accelerometry studies.

PMID:
20877141
PMCID:
PMC3900821
[Indexed for MEDLINE]
Free PMC Article
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