Trend analysis for national surveys: Application to all variables from the Canadian Health Measures Survey cycle 1 to 4

Abstract

BackgroundTrend analysis summarizes patterns over time in the data to show the direction of change and can be used to investigate uncertainties in different time points and associations with other factors. However, this approach is not widely applied to national surveys and only selected outcomes are investigated. This study demonstrates a research framework to conduct trend analysis for all variables in a national survey, the Canadian Health Measures Survey (CHMS).Data and methodsThe CHMS cycle 1 to 4 was implemented between 2007 and 2015. The characteristics of all variables were screened and associated to the weight variables. Missing values were identified and cleaned according to the User Guide. The characteristics of all variables were extracted and used to guide data cleaning. Trend analysis examined the statistical significance of candidate predictors: the cycles, age, sex, education, household income and body mass index (BMI). R (v3.2) and RStudio (v0.98.113) were used to develop the framework.ResultsThere were 26557 variables in 79 data files from four cycles. There were 1055 variables significantly associated with the CHMS cycles and 2154 associated with the BMI after controlling for other predictors. The trend of blood pressure was similar to those published.ConclusionTrend analysis for all variables in the CHMS is feasible and is a systematic approach to understand the data. Because of trend analysis, we have detected data errors and identified several environmental biomarkers with extreme rates of change across cycles. The impact of these biomarkers has not been well studied by Statistics Canada or others. This framework can be extended to other surveys, especially the Canadian Community Health Survey.

Opportunities and Challenges From Leading Trends in a Biomonitoring Project: Canadian Health Measures Survey 2007–2017

“…We used the biomonitoring data from CHMS cycles 1-5 (8). The five cycles were implemented between 2007 and 2009, 2009 and 2011, 2012 and 2013, 2014 and 2015, and 2016 and 2017 (8).…”

“…More than 5,000 Canadians residing in 10 provinces aged 3-79 years were interviewed in each cycle (8). There were face-to-face interviews to record demographic and socioeconomic characteristics, as well as mobile clinic visits to retrieve blood and urine samples (8). Data on accelerometer-measured daily activities, lung function measured by a spirometer, medication, diagnosis of selected major disease, lifestyle, and health behavior, such as smoking and alcohol consumption, were also obtained (8).…”

“…Statistics Canada, the Public Health Agency of Canada, and Health Canada have been involved in the CHMS since its development before 2007 (7). The results from the CHMS help us to understand and track the levels of disease biomarkers and environmental chemicals, many of which have been considered health hazards by Health Canada (8).…”

“…Moreover, levels of environmental chemicals or biomarkers have not been considered for time trends. Trend analysis aims to illustrate the relationships between repeated measures (8). The time trends of many health measures have been regularly studied and updated using other biomonitoring data, especially those related to large disease burden and economic impact (18,19).…”

“…Given the same amount of chemicals, larger distributional volumes can lead to lower concentrations in human bodies (24), and BMI is an important indicator of obesity. Obesity is becoming more prevalent and has emerged as one of the major issues in public health (8,25). It is not clear whether obesity and BMI increases may play a role in the increases or decreases of biomarker trends.…”