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Time-trend analysis, time series designs

Epidemiology: Time-trend Analysis

Time-trend designs are a form of longitudinal ecological study, and can provide a dynamic view of a population’s health status. Data are collected from a population over time to look for trends and changes. Like other ecological studies, the data are collected at a population level and can be used to generate hypotheses for further research, rather than demonstrating causality.

Ecological studies are described elsewhere in these notes, but there are four principal reasons for carrying out between-group studies:1

  • To investigate differences between populations
  • To study group-specific effects, for example of a public health intervention aimed at a group
  • Availability of group-level data, such as healthcare utilisation
  • Cheap and quick if routine data are available

In a time-trend analysis, comparisons are made between groups to help draw conclusions about the effect of an exposure on different populations. Observations are recorded for each group at equal time intervals, for example monthly. Examples of measurements include prevalence of disease, levels of pollution, or mean temperature in a region.

Uses of time-trend analysis

Trends in factors such as rates of disease and death, as well as behaviours such as smoking are often used by public health professionals to assist in healthcare needs assessments, service planning, and policy development. Examining data over time also makes it possible to predict future frequencies and rates of occurrence.

Studies of time trends may focus on any of the following:

  • Patterns of change in an indicator over time – for example whether usage of a service has increased or decreased over time, and if it has, how quickly or slowly the increase or decrease has occurred
  • Comparing one time period to another time period – for example, evaluating the impact of a smoking cessation programme by comparing smoking rates before and after the event
  • Comparing one geographical area or population to another
  • Making future projections – for example to aid the planning of healthcare services by estimating likely resource requirements

Analysis of time-trend studies

The most obvious first step in assessing a trend is to plot the observations of interest by year (or some other time period deemed appropriate). The observations can also be examined in tabular form. These steps form the basis of subsequent analysis and provide an overview of the general shape of the trend, help identify any outliers in the data, and allow the researcher to become familiar with both the rates being studied.2

Detailed knowledge of the statistical methods used in analysis is beyond the scope of MFPH Part A, but methods include:

  • Chi-square test for linear trend
  • Regression analysis

More detailed consideration of analysis is available here

Time series analysis

Time series analysis refers to a particular collection of specialised regression methods that use integrated moving averages and other smoothing techniques to illustrate trends in the data. It involves a complex process that incorporates information from past observations and past errors in those observations into the estimation of predicted values.

Moving averages provide a useful way of presenting time series data, highlighting any long-term trends whilst smoothing out any short-term fluctuations. They are also commonly used to analyse trends in financial analysis. The calculation of moving averages is described in more detail here.

Presentation of trend data

Presentations of time-trend data should usually include the following:

  • Graphical plots displaying the observed data over time
  • Comment on any statistical methods used to transform the data
  • Report average percent change
  • An interpretation of the trends seen

Interpretation of trend data

The results of all ecological studies, including time-series designs should be interpreted with caution:1

  • Data on exposure and outcome may be collected in different ways for different populations
  • Migration of populations between groups during the study period may dilute any difference between the groups
  • Such studies usually rely on routine data sources, which may have been collected for other purposes
  • Ecological studies do not allow us to answer questions about individual risks
  • References

  1. Bailey L, Vardulaki K, Langham J, Chandramohan D. Introduction to Epidemiology. Open University Press, 2005.
  2. www.mchb.hrsa.gov/mchirc/_pubs/trend_analysis.pdf – Accessed 31/01/09

© Helen Barratt 2009