Elsevier

Public Health

Volume 122, Issue 11, November 2008, Pages 1152-1166
Public Health

Original research
Missing data on retrospective recall of early-life socio-economic position in surveillance systems: An additional disadvantage?

https://doi.org/10.1016/j.puhe.2008.04.013Get rights and content

Summary

Objectives

Inclusion of information on early-life socio-economic position (SEP) in population chronic disease and risk factor surveillance systems enables better monitoring of effects of policies and interventions on health inequities and intergenerational disadvantage. Examining data quality, in terms of item non-response, informs choices about which indicators of early-life SEP to include in surveillance questionnaires. This study examined differences in recall of indicators of early-life SEP between different socio-economic groups.

Study design

Cross-sectional population survey.

Methods

A representative population of people aged 18 years and over living in South Australia (n = 2999) was selected at random from the electronic white pages, and a computer-assisted telephone interview was administered.

Results

Respondents with missing data on early-life SEP indicators were disadvantaged in terms of current SEP compared with those who provided this information. Among all respondents, the highest proportions of missing data were observed for maternal grandfather's main occupation (27.2%), and mother's (20.1%) and father's (19.6%) highest level of education. Family structure, housing tenure and family financial situation when the respondent was 10 years old, and mother's and father's main occupation were the indicators of early-life SEP that performed best in terms of recall.

Conclusions

The differential response to early-life SEP questions according to current circumstances has implications for chronic disease surveillance examining the life-course impact of socio-economic disadvantage.

Introduction

The life-course approach to measuring socio-economic position (SEP) offers insight into understanding social variations in health1 and the manner in which biological, psychological, social and economic factors are associated with health and illness. Measuring SEP across the life course is necessary to underpin policies, programmes and interventions that protect against accumulation of socio-economic risk. Population health surveillance systems focusing on chronic conditions and risk factors need to consider measurement of SEP over the life course to monitor its impact on health and illness of different population groups. This is particularly important in the context of growing evidence about the significance of the social determinants of health in determining health inequities.2, 3

Population health surveillance is defined as ‘the ongoing systematic collection, analysis and interpretation of outcome-specific data, closely integrated with the timely dissemination of these data to those responsible for preventing and controlling disease’.4 Surveillance of chronic conditions and their associated risk factors and determinants consists of continuous data collection in repeated, independent, cross-sectional surveys. This necessarily relies on retrospective recall of SEP during early life, including from childhood, adolescence and early adulthood, in addition to information on current adult SEP, to provide a picture of SEP and how it changes over the life course. As health inequities are increasing or remaining static in most contexts, surveillance data are vital to monitor and inform policies that impact on these inequities.

The particular indicators of early-life SEP collected both prospectively and retrospectively in previous longitudinal and cross-sectional studies have depended on several factors, including the data available in birth cohort studies, the health outcomes being investigated, the life-course theory (e.g. cumulative, pathway or critical period approach) shaping the research, and the time and place in which the data were collected.5

Monitoring the health of population groups with different SEP experiences over their life course requires that indicators of early-life SEP be introduced into surveillance systems. Therefore, the aims of this study were to: (1) determine the proportion of adult respondents in a representative population survey who can recall information about their early-life SEP; and (2) examine whether those respondents who provide information about their early-life SEP differ from those with missing data in terms of current sociodemographic and health variables.

Section snippets

Participants

Households in South Australia with a connected telephone and the number listed in the electronic white pages (EWP) were eligible for selection. In households sampled at random during September 2004, the person aged 18 years or over who was last to have a birthday was selected for interview. These people were non-replaceable and up to six call backs were made to recruit respondents. A letter was sent to each household prior to interview with information about the purpose of the survey.

Results

The distribution of early-life SEP and the proportion of respondents with missing early-life SEP information are listed in Table 1. The proportion of those with missing data was highest for maternal grandfather's main occupation [27.2%, 95% confidence interval (CI) 25.6–28.8], mother's highest level of education (20.1%, 95% CI 18.7–21.5) and father's highest level of education (19.6%, 95% CI 18.2–21.0); lower for family financial situation at 10 years of age (9.0%, 95% CI 8.0–10.1), father's

Discussion

In this representative population health survey, family structure, housing tenure and family financial situation when the respondent was 10 years old, and mother's and father's main occupation were the indicators of early-life SEP that respondents were more likely to recall. There were few differences between those with and without missing data for these indicators. Fewer respondents recalled information about maternal grandfather's main occupation and mother's and father's highest level of

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