Higher education, lower activity levels

Everyone knows that exercise does you good. In fact, the risk of almost all chronic diseases can be reduced by an active lifestyle. Many large-scale studies have already proved this to be true. However, the data has yet to provide clear evidence on which individual factors – such as age, gender, weight and education – influence physical activity.

Little is known about the specific factors that cause a person to spend more or less time in more or less physically demanding activities.

"Until now, such studies have mostly been conducted with the help of questionnaires, which only produce data with limited validity regarding the actual activity levels of the participants,” says Dr. Lina Jaeschke from the MDC research group on Molecular Epidemiology, which is headed by Professor Tobias Pischon. “In addition, little is known about the specific factors that cause a person to spend more or less time in more or less physically demanding activities.”

A hip-mounted measuring device

Jaeschke and Pischon wanted more concrete knowledge, so they teamed up with 26 other scientists from Germany to carry out a study to measure the physical activity of participants via a device worn on the hips known as an accelerometer.

This device records the wearer’s acceleration, thus enabling the researchers to gain a comprehensive picture of his or her physical activity over several days – around the clock. These devices generally provide more reliable results than the widely used fitness wristbands. “Through our study, we wanted to identify groups of people with particularly low levels of activity in order to help develop public policies that can address these people more effectively and specifically,” says lead author Jaeschke. 

To this end, Jaeschke, Pischon and the team collected data from a pretest of the German National Cohort (NAKO) – a long-term, nationwide health study with around 205,000 participants aged between 20 and 69. The main objective of this study is to gain a better understanding of how the major chronic diseases develop. For their own study, Jaeschke’s group took data from 249 participants with an average age of 51.3 years, who had agreed to wear the motion detector constantly for seven days and nights – save for short interruptions when taking a shower, for example.  

Smokers spend less time in intense physical activity 

Based on the intensity of physical activity recorded, Jaeschke and her colleagues divided the participants’ activities into four categories: inactivity, low-intensity, moderate intensity (such as jogging, gardening or vacuuming) and vigorous-to-very-vigorous intensity (such as highly strenuous sports).

The team then analyzed to what extent the following factors were associated with these levels of physical activity: sex, age, body mass index (BMI), waist circumference, smoking, alcohol consumption, education, employment, income, marital status and reported pre-existing conditions of diabetes and dyslipidemia – a lipid metabolism disorder that usually leads to elevated cholesterol levels. “Some of our results were, of course, expected, such as a decrease in high-intensity activities with increasing age,” says Jaeschke.

The time participants spent in vigorous-to-very-vigorous-intensity activities, for example, was reduced by an average of 0.8 minutes per day every five years. In contrast, the duration of low-intensity activities showed a daily increase of 7.3 minutes over the same period. ”That may not sound like much,” says Jaeschke. “But if you start to look at greater age differences, age becomes an epidemiologically relevant influencing factor for physical activity.” The situation was similar when looking at the factor of smoking: Active smokers spent less time in vigorous-to-very-vigorous activities, but more time in low-intensity activities than those who had never smoked. A higher BMI was associated with less time in low-intensity activity.

Education brings people to a halt

Almost 250 participants wore a motion detector for seven days and nights.

© NAKO Gesundheitsstudie

“What was relatively surprising for us was the finding that those with a university entrance qualification spend more time in inactivity than those with a lower level of education,” says Jaeschke. “Earlier studies had suggested that a higher level of education goes hand in hand with increased physical activity – presumably because these people generally live more health-conscious lives and can also afford things like gym memberships, thus achieving a higher level of activity in their leisure time.”

However, Jaeschke explains, people with a high level of education generally pursue professions that are less physically demanding. This may explain why people with a university entrance qualification recorded longer periods of physical inactivity over the seven days of around-the-clock monitoring.

The researchers also found an unexpectedly clear correlation with the factor of employment: “People who are out of work spend much more time in physical inactivity than those who have a full-time job,” reports Jaeschke. The average daily difference between the two groups was 66.2 minutes. In addition, those without a job during the observation period spent 50.7 minutes less in low-intensity activities each day compared to those with full-time jobs.

Plans are in place for a larger study

Jaeschke admits that one of the limitations of their study is the relatively small number of participants. “In the foreseeable future, however, we will receive data from the first 30,000 or so participants in the NAKO study who have worn the accelerometer for a week,” the researcher says. She and her colleagues will then check their current results against this larger cohort.

Anke Brodmerkel

Further informationen

Pischon Lab

Molecular Epidemiology

• SMOVE brings research into the classroom
• First “wave” of the German National Cohort is completed
• “Our goal is personalized prevention”

Literatur

Jaeschke, Lina et al. (2020): „Factors associated with habitual time spent in different physical activity intensities using multiday accelerometry“, Scientific Reports, DOI:10.1038/s41598-020-57648-w.