Estimating non-response bias in a survey on alcohol consumption: comparison of response waves

AIMS: According to 'the continuum of resistance model' late respondents can be used as a proxy for non-respondents in estimating non-response bias. In the present study, the validity of this model was explored and tested in three surveys on alcohol consumption. METHODS: The three studies collected their data by means of mailed questionnaires on alcohol consumption whereby two studies also performed a non-response follow-up. RESULTS: Comparisons of early respondents, late respondents and non-respondents in one study showed some support for 'the continuum of resistance model', although another study could not confirm this result. Comparison of alcohol consumption between three time response groups showed no significant linear pattern of differences between response waves. CONCLUSIONS: The hypothesis that late respondents are more similar to non-respondents than early respondents, could not be confirmed or rejected. Repeated mailings are effective in obtaining a greater sample size, but seem ineffective in improving the representativeness of alcohol consumption surveys.     

Postal survey on airborne occupational exposure and respiratory disorders in Norway: causes and consequences of non-response.

STUDY OBJECTIVE--The aim was to examine causes for non-response in a community survey, and how non-response influences prevalence estimates of some exposure and disease variables, and associations between the variables. DESIGN--This was a cross sectional questionnaire study with two reminder letters. The questionnaire asked for information on smoking habits, occupational airborne exposure and respiratory disorders. SETTING--A random sample of 4992 subjects from the general population aged 15-70 years of Hordaland County, Norway. MAIN RESULTS--The overall response rate was 90%, with a 63% response to the initial letter. The response rates to the first and second reminder letters were 56% and 36% respectively. In 20% of the non-respondents an uncompleted questionnaire was returned with cause for non-response; in two thirds of these the cause for non-response was that the subject was not resident at the mailing address. A home visit to a random sample of 50 urban non-respondents provided further information on 29 subjects. A wrong address at the Central Population Registry and the subject's feeling of lack of personal benefit from a postal survey were the major reasons for non-response. Smokers were late respondents and subjects with respiratory disorders tended to be early respondents. CONCLUSION--The main reasons for non-response were a wrong mailing address and a feeling of lack of personal benefit from responding. Using only the initial letter would have changed the estimated prevalence of smokers from 39% to 35%. Otherwise, the estimated prevalence of the exposure and disease variables as well as the associations between them were only slightly changed after including the respondents to the first and second reminder letters.     

Effect on Trend Estimates of the Difference between Survey Respondents and Non-respondents: Results from 27 Populations in the WHO MONICA Project

Introduction: In the World Health Organization (WHO) MONICA (multinational MONItoring of trends and determinants in CArdiovascular disease) Project considerable effort was made to obtain basic data on non-respondents to community based surveys of cardiovascular risk factors. The first purpose of this paper is to examine differences in socio-economic and health profiles among respondents and non-respondents. The second purpose is to investigate the effect of non-response on estimates of trends. Methods:Socio-economic and health profile between respondents and non-respondents in the WHO MONICA Project final survey were compared. The potential effect of non-response on the trend estimates between the initial survey and final survey approximately ten years later was investigated using both MONICA data and hypothetical data. Results: In most of the populations, non-respondents were more likely to be single, less well educated, and had poorer lifestyles and health profiles than respondents. As an example of the consequences, temporal trends in prevalence of daily smokers are shown to be overestimated in most populations if they were based only on data from respondents. Conclusions: The socio-economic and health profiles of respondents and non-respondents differed fairly consistently across 27 populations. Hence, the estimators of population trends based on respondent data are likely to be biased. Declining response rates therefore pose a threat to the accuracy of estimates of risk factor trends in many countries.     

Does non-responder bias have a significant effect on the results in a postal questionnaire study?

Background and aim: In epidemiological questionnaire studies results can be influenced by non-responder bias. However, in respiratory epidemiology this has been analysed in very few recently published papers. The aim of our paper is to assess if the results found in our previous postal questionnaire study in an adult population in Northern Finland were biased by non-response. Methods: A random sample of 385 persons from the 1284 non-responders in a previous postal questionnaire study was examined. The same questionnaire as in the original study was again mailed to these persons, and those still not answering were contacted by phone. Results: Totally 183 complete answers (48%) were collected. Lack of interest (56%) and forgetting to mail the response letter (22%) were the most common reasons to non-response. Typical non-responders were young men and current smokers who less frequently reported respiratory symptoms in exercise and asthma than the responders in the original study. Answers collected by phone gave for some questions higher prevalence rates than postal answers. Conclusion: Firstly, in this population the response rate (83.6%) in the original study was high enough to provide reliable results for respiratory symptoms and diseases, only the prevalence of current smoking was biased by non-response. Secondly, the methods used for collecting responses in a non-response study may influence the results.     

Generalizability of valuations on health states collected with the EuroQolc-questionnaire

Problem: Non-response and non-usable response were found in population surveys on valuation of health states. If non-response is selective regarding valuations, then generalization of the resulting values to the whole survey population is not permitted. This could limit the use of empirical utility values in resource allocation in health care. Methods: Response behaviour of a sample of 1400 from the Dutch general population to the mailed EuroQol^c-questionnaire was analyzed by four methods. I. Phoning resolute non-respondents; II. comparison of zip code characteristics of respondents and non-respondents (because individual data on background characteristics were not available for the non-respondents); III. analysis of response over time (wave-analysis); IV: comparison of background variables of successful (less than two valuations missing) and unsuccessful respondents, combined with analysis of the effect of these background variables on valuations. Results: No indications for selective non-response were found, although the phenomenon appeared hard to investigate. The successful response came from a slightly younger and better educated subsample. However, a general influence of age and educational level on valuations could not be shown. This finding is consistent with the literature. Conclusion: Although the existence of selective non-response cannot be excluded, its relevance can be considered to be small. This finding is encouraging for the use of empirical utility values in allocative decisions.     

Recruitment methods and differences in early, late and non-respondents in the first MONICA-Catalonia population survey

The early response rate in the first MONICA-Catalonia population survey was 52.7% and the final response rate was 73.8%. The intensity of recruitment effort in this survey led to a considerable increase in response rate (20%), with the extra cost per late respondent being relatively low ($13.9). Added recruitment effort was most effective in the youngest age group, 25-34 years. It was also more effective among women living in urban areas than among those from rural areas. In men, early respondents had a higher proportion of smokers than late respondents, and in women, early respondents had higher systolic and diastolic blood pressure levels and were more aware of their history of high blood pressure than late respondents. Non-respondents were less educated than respondents in both sexes, and this was more marked in women. No differences were found in the proportion of smokers between respondents and non-respondents. Respondents were more aware of their high blood pressure history than non-respondents. The recruitment costs and distribution of non-response components are given.     

Extended recruitment efforts minimize attrition but not necessarily bias

ObjectivesThere has been a debate about the effect of extended recruitment efforts on attrition and bias. The aims of the present study are (1) to investigate the effectiveness of extensive multimode recruitment procedures; (2) to study their effect on attrition and bias; and (3) to determine the potential predictors of attrition.Study Design and SettingWe used data from the longitudinal population-based study of health in Pomerania.ResultsUsing multimode recruitment methods, we reached a follow-up response proportion of 83.6%. In-person contacts at home turned out to be an effective recruitment tool. Sociodemographic and health characteristics of late respondents and converted nonrespondents were most distinct from early respondents but not necessarily indicative of nonrespondents. Analyzing attrition bias, extended recruitment efforts produced an effect only for sociodemographic characteristics but not for health-related indicators. The strongest predictors for attrition from the regression model were late recruitment at baseline, unemployment, low educational level, female sex, and smoking habit.ConclusionExtended recruitment efforts appeared justified in terms of response maximization. However, enhanced response proportions may not necessarily minimize bias. In our analysis, aiming for a high-response proportion in terms of health-related indicators had no effect, because late respondents did not differ from early respondents.     

流行病学调查中影响应答率的相关因素与对策探讨

目的 本文旨在了解我国15岁以上人群开展健康相关流行病学调查的应答情况,分析造成无应答的具体原因,进而初步探讨提高应答率的有效途径,为今后开展流行病学现况调查提高应答率提供参考。方法 通过分析在重庆市进行的中国重要心血管病患病率调查中两种调查模式开展的方式和效果,探讨造成无应答的原因,进而开展干预试验和效果评价。结果 集中模式在初期预调查中问卷的完成率只有20.00%,应答率为13.48%;分散模式的问卷完成率也仅31.16%,应答率为25.19%。经过对被调查者以及项目相关核心人员采取一系列激励措施后,正式调查时两种调查模式的应答率均达到预期60%左右。结论 集中模式调查在质量控制方面具有优势,但调查时间越长成本越高,并且没有后续措施提高应答率;分散模式调查在成本控制和应答率上具有优势,对无应答者通过预约入户调查可进一步提高应答率,但调查时间长,质量控制相对难度较高。提高应答率应把握两个关键：找到调查对象和吸引调查对象参与调查。     

Contactable Non-responders Show Different Characteristics Compared to Lost to Follow-Up Participants: Insights from an Australian Longitudinal Birth Cohort Study

Objective This research aims to identify predictors of attrition in a longitudinal birth cohort study in Australia and assess differences in baseline characteristics and responses in subsequent follow-up phases between contactable non-responders and uncontactable non-responders deemed “lost to follow-up (LTF)”. Methods 3368 women recruited from three public hospitals in Southeast Queensland and Northern New South Wales during antenatal visits in 2006–2011 completed a baseline questionnaire to elicit information on multiple domains of exposures. A follow-up questionnaire was posted to each participant at 1 year after birth to obtain mother’s and child’s health and development information. Multivariate logistic regression was used to model the association between exposures and respondents’ status at 1 year. The effect of an inverse-probability-weighting method to adjust for non-response was studied. Results Overall attrition at 1-year was 35.4 %; major types of attrition were “contactable non-response” (27.6 %) and “LTF” (6.7 %). These two attrition types showed different responses at the 3-year follow-up and involved different predictors. Besides shared predictors (first language not English, higher risk of psychological distress, had smoked during pregnancy, higher levels of family conflict), distinguishable predictors of contactable non-responders were younger age, having moved home in the past year and having children under 16 in the household. Attrition rates increased substantially from 20 % in 2006 to 54 % in 2011. Conclusions This observed trend of increased attrition rates raises concern about the use of traditional techniques, such as “paper-based” questionnaires, in longitudinal cohort studies. The supplementary use of electronic communications, such as online survey tools and smart-device applications, could provide a better alternative.     

Predicting risk among non-respondents in prospective studies

Potential non-response bias was investigated in a follow-up study of 2,011 chronically disabled patients. 82.5% and 73.3% of the study subjects responded to self-administered mail questionnaires respectively at 6-month and 1-year follow-up. Information on employment status, the outcome of interest, of approximately 90% of the non-respondents was obtained from indirect sources. Employment rate was lower among the non-respondents than the respondents. Non-response was associated with age, social class, previous employment record, and the type of disability; but none of these characteristics were associated with the outcome. Out of the five known independent risk factors for unemployment, only one (incompletion of rehabilitation course) was associated with non-response. The employment rate among the respondents was also assessed according to the delay in response, that is the number of reminders sent to achieve response. The outcome among- the late respondents was similar to that among the nonrespondents. These data suggest that (a) risk estimates may be biased even when the response rate is greater than 80%, (b) the prevalence of risk factors among non-respondents may not indicate the presence or the degree of non-response bias, but (c) reliable estimates can be obtained from extrapolations of the rates among the respondents according to the delay in response.     

Lifestyle surveys--the complete answer?

STUDY OBJECTIVES: These were as follows: to study incompleteness of data, herein called item non-response, generated by a self completion questionnaire; to identify the characteristics of item non-responders and the types of questions liable to high item non-response rates; and to discuss possible reasons for item non-response. DESIGN: Item non-response patterns in 12,307 responders (62%) to a representative postal survey based on a stratified sample drawn from family health services authorities' (FHSA) registers were investigated. MAIN OUTCOME MEASURES: Data were analysed for item non-response in three groups depending on when the questionnaire was returned (wave analysis). The overall completion rate of the questionnaire was examined and the natural logarithm of the proportion of completed questions was used as an outcome variable in multiple regression analysis. Item nonresponse to key questions and questions of different types was examined. RESULTS: Wave analysis: the overall completion rate of the questionnaire was 86% in questionnaires returned before the first reminder and 83%-84% in those sent back after subsequent reminders. Overall pattern of item non-response; respondents failed to complete a mean of 15% and a median of 10% of the questionnaire. All questions in the questionnaire had some item non-response, ranging from 1% to 85%. Completion rates were associated with gender, age, indicators of lower socioeconomic status, and general health status. Individual questions: particular types of questions were liable to have higher item non-response, for example, linked binary questions. CONCLUSIONS: Item non-response in population postal surveys is likely to present problems in the interpretation of data by introducing bias additional to that of total non-response. Item non-response does not increase greatly with later returns, suggesting that the quality of data across responses generated by two reminders is similar. There are obstacles to reducing item non-response, such as respondent error or socioeconomic and health characteristics of the general population, that cannot be totally overcome. However, the evidence that individuals tend to complete only options within questions that apply to them and their positive behaviour is useful information for those designing questionnaires and interpreting survey data.     

Does survey non-response bias the association between occupational social class and health?

AIMS: A non-response rate of 20-40%is typical in questionnaire studies. The authors evaluate non-response bias and its impact on analyses of social class inequalities in health. METHODS: Set in the context of a health survey carried out among the employees of the City of Helsinki (non-response 33%) in 2000-02. Survey response and non-response records were linked with a personnel register to provide information on occupational social class and long sickness absence spells as an indicator of health status. RESULTS: Women and employees in higher occupational social classes were more likely to respond. Non-respondents had about 20-30% higher sickness absence rates. Relative social class differences in sickness absence in the total population were similar to those among either respondents or non-respondents. CONCLUSIONS: In working populations survey non-response does not seriously bias analyses of social class inequalities in sickness absence and possibly health inequalities more generally.     

Non-response bias in a sample survey on alcohol consumption

In a non-response follow-up study, non-respondents of the original mailed questionnaire were approached again by house visits in order to compare their alcohol consumption with that of the respondents of the same mailed questionnaire. Differences in alcohol consumption between respondents and non-respondents were found. There is strong evidence for overrepresentation of non-response among abstainers, but weak evidence among frequent excessive drinkers.     

Characteristics of non-response in the Danish Health Interview Surveys, 1987-1994

BACKGROUND: The types and quantity of non-response in surveys influence the extent to which the results may be generalized. This study analysed trends in non-response in the Danish Health Interview Surveys from 1987 to 1994 and used the National Patient Registry to assess whether non-response biased the estimated population prevalence of morbidity when solely based on responders. METHODS: The data were for the 23,096 adults sampled for the Danish Health Interview Surveys in 1987, 1991 and 1994. All were followed using the National Patient Registry to obtain such information as hospital admissions. RESULTS: Non-response increased from 20.0% in 1987 to 22.6% in 1994. Four combinations of background variables characterized the non-response: gender and age; gender and civil status; county of residence and age; survey year and age. Non-respondents and respondents had identical gender- and age-standardized hospital admission rates for approximately 5 years before and 2 years after data collection, but non-respondents had a significantly higher rate immediately before and during data collection. Admissions rates were analysed according to reasons for non-response. Refusers had a lower admission rate than respondents before data collection but similar during and after data collection. The rate was higher during the whole period among ill or disabled non-respondents. Among people who could not be contacted during the data collection period a higher admission rate was only found immediately before and during data collection. CONCLUSIONS: Although admission rates differed between respondents and non-respondents these differences were too small to bias the estimated population prevalence of morbidity when solely based on respondents.     

Factors Associated with Antenatal Care Utilization Among Rural Women in Lao People’s Democratic Republic

This study aims at exploring factors related to the antenatal care (ANC) utilization in rural areas of Lao PDR. A quantitative, cross-sectional interview study was conducted in the Khammouane and Champasack provinces. The study population comprised all currently pregnant women 15–45 years of age with a gestational period beyond 32 weeks plus all women who had given birth during the last 12 months. With the informed consent of all eligible women, 460 respondents were included in the study and interviewed using a structured questionnaire. Multiple logistic regression analysis was applied to determine factors significantly related to ANC use. Fifty-one percent of the respondents had at least one ANC visit. Among the users, 63% had visited ANC three times or more but only 28% attended during the first trimester. After adjusting for other factors, using a 95% Confidence Interval (CI), statistically significant associations were found between ANC use and the following factors: women whose husbands were salaried employees (OR = 2.66, CI = 1.45–4.88); women younger than 18 years old at first pregnancy (OR 0.56, CI = 0.28–0.97); women perceiving ANC as somewhat useful (OR = 2.88, CI = 1.26–6.61) or very useful (OR = 7.45, CI = 3.59–15.46). Awareness of the usefulness of ANC was related to more frequent use and could be one focus of community intervention to increase utilization.     

Alcohol and other substance use among a sample of young people in the Solomon Islands

Objective: Investigate alcohol and other substance use, with a focus on harmful alcohol use patterns, among young people in the Solomon Islands. Methods: A structured, interviewer‐administered questionnaire was administered to respondents aged 15–24 years across four of the country's provinces in late 2015. Results: Four hundred young people completed the questionnaire across urban, peri‐urban and rural communities. The most common substances ever used by participants were betel nut (94%), licit/store‐bought and/or illicit alcohol (79%) and tobacco (76%). Lifetime and recent substance use was particularly common among male respondents; e.g. 89% of male participants reported ever using any alcohol versus 54% of females (p<0.001). Harmful alcohol use patterns were common. Conclusions: Our sample generally reported higher levels of substance use compared to previous research in the Solomon Islands, including in relation to the country's relatively recent (2012/13) Household Income and Expenditure Survey. Implications for public health: Our study made considerable advances in addressing key knowledge gaps regarding alcohol and other substance use among young people in the Solomon Islands. Evidence‐based initiatives to address early initiation of alcohol and other substance use and the progression to more problematic use patterns among young people in the Solomon Islands need to be explored.     

Response and Non-response to a Quality-of-Life Question on Sexual Life: A Case Study of the Simple mean Imputation Method

We investigated the non-response rates to the question “I am satisfied with my sex life” in the Functional Assessment of Cancer Therapy – General questionnaire in Chinese (n = 769), Malay (n = 41) and Indian (n = 33) patients in Singapore, a multi-ethnic society whose residents are said to have a conservative sexual attitude. Non-response rates to the question were 44%, 22% and 24% in the three groups respectively. The rates were much higher than that reported previously in a US study (7%) and used in the associated simulation study of the simple mean imputation method. We further examined the Chinese respondents in detail. The odds of non-response and the scores among the responders were associated with several demographic and clinical characteristics. Using the checklist proposed by Fayers et al. [Stat Med 1998; 17: 679–696] to assess the data patterns, we found that the application of the simple mean imputation is questionable. We employed an alternative (multiple) imputation procedure that took into account covariates that predicted the odds of non-response and the observed response scores. We compared the analytic results based on different approaches to handling missing values, and found that analysis based on the simple mean imputation gave results similar to that based on multiply imputed data even in this quite extreme example.     

Health-related and work-related aspects associated with sick leave: a comparison of chronically ill and non-chronically ill workers

Objectives: Our aims were to study to what extent chronically ill workers (CIWs) take more sick leave than non-chronically ill workers (NCIWs) and to explore which health-related and work-related aspects are associated with the sick leave patterns of the two groups. Methods: A questionnaire on work, health and sick leave was sent to all employees of a university in The Netherlands (response: 49.1%). Analyses were conducted for 444 CIWs and 1,347 NCIWs. Odds ratios (ORs) were calculated to quantify the contribution of being chronically ill to sick leave in general, frequent sick leave, prolonged sick leave, and present sick leave. The contributions of health-related and work-related aspects to sick leave were investigated by multiple logistic regression analyses for both CIWs and NCIWs separately. Results: CIWs showed significantly increased ORs for general, frequent, prolonged and present sick leave when compared with NCIWs. Fatigue, emotional exhaustion and perceived health complaints showed stronger associations with sick leave for both CIWs and NCIWs than various work-related aspects. Workers of 46 years of age and older showed less sick leave than workers under the age of 36. Male respondents and scientific personnel showed less frequent sick leave than the other respondents, and so did respondents working more than 40 h a week, compared with part-timers. The final regression models explained 8%–16% of the variance in sick leave. Conclusions: CIWs take two to three times more and longer sick leave than NCIWs. Health-related aspects are more strongly associated with sick leave than work-related aspects for both CIWs and NCIWs. Sick leave patterns were, nevertheless, only partly explained by health-related and work-related aspects. In any case, future studies of sick leave should certainly take the presence of chronic disease into account as an important determinant of sick leave.     

Factors impacting questionnaire response in a Dutch retrospective cohort study

PURPOSE: To study questionnaire length, type of consent, approach to recruitment, and subject characteristics on participation in epidemiologic studies. METHODS: As part of a health survey among Dutch subjects treated for ear, nose, and throat disorders in childhood, we conducted a pilot study of 200 individuals who were randomly assigned to one of four categories, defined by length of questionnaire (long vs. short) and type of consent form (basic vs. multi-option). In addition, among 8402 subjects eligible to be in the main study (average age 41 years in 1997), we examined the effect of approach to recruitment and subject characteristics on participation rates. RESULTS: The pilot study showed a non-significant 10% increase in participation rate using the shorter questionnaire, but no differences by type of consent form. In the full survey, the participation rate was 49% after the first mailing. Response increased by 15% after a written reminder and by 10% after a telephone survey. The total participation rate was 74%. Attained age, sex, exposure status, age at exposure, and response to an earlier survey were determinants of participation rates. Among male non-participants, outright refusal was less frequent than non-response. The refusal rate, unlike the non-response rate, was positively associated with older age at time of survey. CONCLUSIONS: Health survey participation is influenced by questionnaire length, frequency of contact, and subject characteristics.     

Use of vitamins,trace elements,or herbal products does not differ between cancer patients and population in general

Objective: To examine how widely cancer patients use vitamins, trace elements, and herbal products. Methods: The Health and Social Support Study (HeSSup) population consisted of a stratified random sample drawn from the Finnish Population Register in four age groups: 20–24, 30–34, 40–44, and 50–54 years. The survey was carried out by postal questionnaire during 1998, with a response rate of 40.0%. Altogether, 19 626 individuals returned the follow-up questionnaire during 2003, a response rate of 75.8%. The sample comprised 167 individuals diagnosed with malignant cancer from 1998 to 2002 according to the Finnish Cancer Registry. Respondents in 2003 were asked about their use of vitamins, trace elements, or herbal products during the last year. Four randomly selected age- and sex-matched controls for comparison were selected for every cancer patient. Results: One in three among both cancer patients and controls had not used vitamins, trace elements, or herbal products at all. In this respect, there were no statistically significant differences between cancer patients and their respective controls.

Conclusion: If the use of these products is useless, cancer patients act as reasonable as the population in general. If their use is generally recommended for supplementary therapy, cancer patients do not follow recommendations.