Nonresponse bias in a follow-up study of 19-year-old adolescents born as preterm infants

E T M Hille1, L Elbertse, J Bennebroek Gravenhorst

  • 1TNO Quality of Life, Leiden, The Netherlands. et.hille@pg.tno.nl

Pediatrics
|November 3, 2005
PubMed

Insights

Boys, non-Dutch adolescents, and those with low maternal education were more likely to be nonresponders in a 19-year follow-up of preterm infants. Nonresponse can skew results, necessitating methods to quantify and address bias in long-term studies.

Area of Science:

  • Developmental Pediatrics
  • Longitudinal Studies
  • Public Health

Background:

  • Preterm birth is associated with long-term medical, psychological, and social challenges.
  • Assessing outcomes in adulthood requires robust follow-up methodologies.
  • Understanding factors influencing participant response is crucial for study validity.

Purpose of the Study:

  • To determine the impact of demographic and neonatal factors on response rates in a 19-year follow-up of preterm infants.
  • To analyze how response status (full, postal, or nonresponse) relates to outcomes.
  • To identify biases introduced by nonresponse in long-term follow-up studies.

Main Methods:

  • A cohort of 1338 infants born preterm (<32 weeks gestation or <1500g) was followed for 19 years.
  • Survivors (n=959) were categorized into full responders (62.1%), postal responders (11.4%), and nonresponders (26.5%).
  • Demographic, neonatal, and outcome data were compared across response groups.

Main Results:

  • Male sex, non-Dutch ethnicity, and low maternal education were associated with higher nonresponse and postal response rates.
  • Special education and severe handicap increased the likelihood of nonresponse and postal response.
  • Full responders had higher educational attainment at age 19 compared to postal responders.

Conclusions:

  • Demographic factors significantly influence response rates in long-term follow-up of preterm survivors.
  • Nonresponse can lead to an underestimation of adverse outcomes in the assessed cohort.
  • Quantifying nonresponse bias and employing statistical methods like data imputation are essential for reliable long-term study findings.
Abstract

Related Concept Videos

Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
Longitudinal Studies01:26

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
Cross-Sectional Research01:50

Cross-Sectional Research

In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...