OBJECTIVE: Study the determinants of non-response and the potential for non-response bias in a New Zealand survey of occupational exposures and health. METHODS: A random sample of 10,000 New Zealanders aged 20-64 years were invited by mail to take part in a telephone survey. Multiple logistic regression was used to study the determinants of non-response. Whether occupational exposure, lifestyle and health indicators were associated with non-response was studied by standardising their prevalence towards the demographic distribution of the source population, and comparing early with late responders. RESULTS: The response rate was 37%. Younger age, Māori descent, highest and lowest deprivation groups and being a student, unemployed, or retired were determinants of non-contact. Refusal was associated with older age and being a housewife. Prevalence of key survey variables were unchanged after standardising to the demographic distribution of the source population. CONCLUSIONS: Following up the non-responders to the mailed invitations with telephone calls more than doubled the response rate and improved the representativeness of the sample. Although the response rate was low, we found no evidence of major non-response bias. IMPLICATIONS: Judgement regarding the validity of a survey should not be based on its response rate.
OBJECTIVE: Study the determinants of non-response and the potential for non-response bias in a New Zealand survey of occupational exposures and health. METHODS: A random sample of 10,000 New Zealanders aged 20-64 years were invited by mail to take part in a telephone survey. Multiple logistic regression was used to study the determinants of non-response. Whether occupational exposure, lifestyle and health indicators were associated with non-response was studied by standardising their prevalence towards the demographic distribution of the source population, and comparing early with late responders. RESULTS: The response rate was 37%. Younger age, Māori descent, highest and lowest deprivation groups and being a student, unemployed, or retired were determinants of non-contact. Refusal was associated with older age and being a housewife. Prevalence of key survey variables were unchanged after standardising to the demographic distribution of the source population. CONCLUSIONS: Following up the non-responders to the mailed invitations with telephone calls more than doubled the response rate and improved the representativeness of the sample. Although the response rate was low, we found no evidence of major non-response bias. IMPLICATIONS: Judgement regarding the validity of a survey should not be based on its response rate.
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