Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Displaying data and interpreting results

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Overview Summarizing data Displaying results Interpretation of results

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Summarizing data Summary statistics that are used for summarizing STEPS data: –Prevalence –Mean –Median

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Summarizing data - prevalence Prevalence = proportion of a population –e.g., % of people who smoke daily We use WHO-recognized cut-points for continuous variables. –e.g. % of people who are overweight (have a BMI of 25 or higher)

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Summarizing data – mean and median Mean and median are measures of central tendency. Mean provides the average of a set of values, and is used for normally distributed variables (such as BMI). Median provides the mid-point of a set of values, and is used for non-normally distributed variables (such as time spent in physical activity). –The median enables you to say: 50% of the respondents had a response more or less than [median value].

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Summarizing data – estimates and true values All sample-based surveys lack some amount of precision due to non-sampling and sampling error. Prevalence, mean or median from a sample are estimated values. Standard error (SE) is usually calculated to show the amount of uncertainty, or error, in an estimated value. It takes into consideration the sample size & distribution (standard deviation) of your sample. Confidence intervals (CI) are calculated from the SE and are a more user- friendly way to show to show the amount of precision in your results.

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Summarizing Data - estimates and true values, cont. Epi Info and most other stats programs automatically calculate the Standard Error and the Confidence Intervals for you. Keep in mind … –The more precise your results, the more confidence you can have in them! –Thus, the shorter the interval the better!

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Confidence Intervals (CI) Typically calculated by multiplying the standard error (SE) by 1.96: CI = SE * 1.96 Expressed as a range around the estimate: 42% (40% - 44%) or 42% (+2%) The interval shows the range of the estimates that would be obtained were all possible samples used. A 95% CI suggests that if 100 samples were drawn, the estimate obtained from each (a mean or prevalence value) would fall within that interval 95 of 100 times.

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Summarizing data – median and IQR When a sample median is reported, an inter-quartile range (IQR) [25%; 75%] should be reported too. Example: median time (in mins) spent in physical activity per week = 60, IQR [20; 180] → Half of the sample engages in 60 minutes of PA per week or less, ¼ of it in 20 minutes or less, ¾ of it in 180 minutes or less

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Displaying data Visual methods can make the point much stronger than simply describing the data. Appropriate use of tables and graphs can enhance the message you are delivering. But they have potential to confuse or convey wrong messages. Always be sure to explain your table or graph in the text of your report. –For every table or graph, there should be a reference to it in the text.

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Tables Good for when exact numbers need to be presented. Because your STEPS report will be the reference for results from your STEPS survey, it will have a lot of tables! Best Practice: –Clear table title and column / row headings –Minimal use of grid lines –Leave enough space so columns/rows are easy to read

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Tables, example Example of a typical "prevalence table" from the STEPS Data Book:

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Graphs For STEPS data, bar graphs and pie charts are most often used. Bar graphs show quantities represented by horizontal or vertical bars and are useful for displaying: –Several categories of results at once (e.g. males vs. females) Pie charts show proportions in relation to a whole, with each wedge representing a percentage of the total and are useful for displaying: –Parts of a whole in percentages

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Graphs: Best Practice Emphasize one idea at a time in a figure. Pay careful attention to the scaling of the graph. Provide a title, units and labels: the graph or table should be self-explanatory! If possible, mention the total sample size of the data set for which the graph or chart is made. Be sparing and consistent with use of colour, fonts and "enhancements".

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Watch the scale!

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Title and Label!

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Title and Label! Smoking status

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Show the sample size Include error bars where possible.

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Keep it simple "Exploding" pie charts and other 3D graphics are not necessary. They distract from your data and may even make your graph harder to read.

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Pie Charts Pie charts should be used sparingly and are generally more useful when there are marked differences between the segments: Value labels make them easier to read.

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Bar Chart example Bar Charts can also be used to show parts of a whole.

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Bar Chart example Remember that in addition to males vs. females, other sub-group comparisons, such as age group, may be interesting to graph.

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Interpretation of results How to test for subgroup differences? For which population are results representative? What could have influenced results? How to interpret results in a context?

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Look for overall pattern, then deviation from the pattern. Look for extreme values (outliers) and gaps. Locate center and spread of distribution. Compare graphs with same scale - look for max, min. Interpretation of results, cont.

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Confidence Intervals - Method for Testing for Subgroup Differences Possible subgroups –Males and Females –Age groups (25 – 34, 35 – 44, etc) –Countries, Regions, Cities, etc. Question – Are they different? Answer – Look at the 95% confidence intervals (CI’s) –If the CI’s overlap – they are not statistically different –If the CI’s do not overlap – they are statistically different

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Are they different? Participants who are overweight Males % ( ) Females – 12.6% ( )

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Are they different? Participants who are overweight Males % ( ) Females – 12.6% ( )

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Are they different? Participants who have raised blood pressure Males ( ) Females – 11.2 ( )

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Are they different? Participants who have raised blood pressure Males ( ) Females – 11.2 ( )

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Representativeness of results Questions that should be discussed: –What population are these results representative for (ages, regional coverage)? –How was the response-rate? –Can any information be obtained about persons who did not respond?

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Influence on results What could have influenced the results? Is it possible that results over- / underestimate true values? (every study has limitations) –Season –Social desirability –Missing values –Methods used (e. g., for sampling, data analysis)

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Results in a context If possible, results should be put in a context for interpretation: –Comparison with previous surveys in the same population –Comparison with surveys using the same methodology in other populations

Surveillance and Population-based Prevention Department for Prevention of Noncommunicable Diseases Summary Prevalence, mean and median are used as summary statistics for reporting STEPS data. CI should be provided with prevalence and mean values, IQR with median values. The most effective ways of presenting data are tables and graphs. Results should be interpreted with regards to accuracy, representativeness and methods used. If possible, results should be compared to other surveys.