̽��ֱ�� of Cambridge - Soren Brage

Daily 11 minute brisk walk enough to reduce risk of early death

cjb250 — Wed, 01 Mar 2023 00:29:21 +0000

In a study published today in the British Journal of Sports Medicine, the researchers say that 11 minutes a day (75 minutes a week) of moderate-intensity physical activity – such as a brisk walk – would be sufficient to lower the risk of diseases such as heart disease, stroke and a number of cancers.

Cardiovascular diseases – such as heart disease and stroke – are the leading cause of death globally, responsible for 17.9 million deaths per year in 2019, while cancers were responsible for 9.6 million deaths in 2017. Physical activity – particularly when it is moderate-intensity – is known to reduce the risk of cardiovascular disease and cancer, and the NHS recommends that adults do at least 150 minutes of moderate-intensity activity or 75 minutes of vigorous-intensity activity a week.

To explore the amount of physical activity necessary to have a beneficial impact on several chronic diseases and premature death, researchers from the Medical Research Council (MRC) Epidemiology Unit at the ̽��ֱ�� of Cambridge carried out a systematic review and meta-analysis, pooling and analysing cohort data from all of the published evidence. This approach allowed them to bring together studies that on their own did not provide sufficient evidence and sometimes disagreed with each other to provide more robust conclusions.

In total, they looked at results reported in 196 peer-reviewed articles, covering more than 30 million participants from 94 large study cohorts, to produce the largest analysis to date of the association between physical activity levels and risk of heart disease, cancer, and early death.

̽��ֱ��researchers found that, outside of work-related physical activity, two out of three people reported activity levels below 150 min per week of moderate-intensity activity and fewer than one in ten managed more than 300 min per week.

Broadly speaking, they found that beyond 150 min per week of moderate-intensity activity, the additional benefits in terms of reduced risk of disease or early death were marginal. But even half this amount came with significant benefits: accumulating 75 min per week of moderate-intensity activity brought with it a 23% lower risk of early death.

Dr Soren Brage from the MRC Epidemiology Unit said: “If you are someone who finds the idea of 150 minutes of moderate-intensity physical activity a week a bit daunting, then our findings should be good news. Doing some physical activity is better than doing none. This is also a good starting position – if you find that 75 minutes a week is manageable, then you could try stepping it up gradually to the full recommended amount.”

Seventy-five minutes per week of moderate activity was also enough to reduce the risk of developing cardiovascular disease by 17% and cancer by 7%. For some specific cancers, the reduction in risk was greater – head and neck, myeloid leukaemia, myeloma, and gastric cardia cancers were between 14-26% lower risk. For other cancers, such as lung, liver, endometrial, colon, and breast cancer, a 3-11% lower risk was observed.

Professor James Woodcock from the MRC Epidemiology Unit said: “We know that physical activity, such as walking or cycling, is good for you, especially if you feel it raises your heart rate. But what we’ve found is there are substantial benefits to heart health and reducing your risk of cancer even if you can only manage 10 minutes every day.”

̽��ֱ��researchers calculated that if everyone in the studies had done the equivalent of at least 150 min per week of moderate-intensity activity, around one in six (16%) early deaths would be prevented. One in nine (11%) cases of cardiovascular disease and one in 20 (5%) cases of cancer would be prevented.

However, even if everyone managed at least 75 min per week of moderate-intensity physical activity, around one in ten (10%) early deaths would be prevented. One in twenty (5%) cases of cardiovascular disease and nearly one in thirty (3%) cases of cancer would be prevented.

Dr Leandro Garcia from Queen’s ̽��ֱ�� Belfast said: “Moderate activity doesn’t have to involve what we normally think of exercise, such as sports or running. Sometimes, replacing some habits is all that is needed. For example, try to walk or cycle to your work or study place instead of using a car, or engage in active play with your kids or grand kids. Doing activities that you enjoy and that are easy to include in your weekly routine is an excellent way to become more active.”

̽��ֱ��research was funded by the Medical Research Council and the European Research Council.

What counts as moderate-intensity physical activity?

Moderate-intensity physical activity raises your heart rate and makes you breathe faster, but you would still be able to speak during the activity. Examples include:

Brisk walking
Dancing
Riding a bike
Playing tennis
Hiking

Reference
Garcia, L, Pearce, M, Abbas, A, Mok, A & Strain, T et al. Non-occupational physical activity and risk of cardiovascular disease, cancer, and mortality outcomes: a dose response meta-analysis of large prospective studies. British Journal of Sports Medicine; 28 Feb 2023; DOI: 10.1136/bjsports-2022-105669

One in ten early deaths could be prevented if everyone managed at least half the recommended level of physical activity, say a team led by researchers at the ̽��ֱ�� of Cambridge.

If you are someone who finds the idea of 150 minutes of moderate-intensity physical activity a week a bit daunting, then our findings should be good news. Doing some physical activity is better than doing none

Soren Brage

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Feet walking on gravel

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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Fitness levels accurately predicted using wearable devices – no exercise required

sc604 — Thu, 01 Dec 2022 10:00:18 +0000

Normally, tests to accurately measure VO2max – a key measurement of overall fitness and an important predictor of heart disease and mortality risk – require expensive laboratory equipment and are mostly limited to elite athletes. ̽��ֱ��new method uses machine learning to predict VO2max – the capacity of the body to carry out aerobic work – during everyday activity, without the need for contextual information such as GPS measurements.

In what is by far the largest study of its kind, the researchers gathered activity data from more than 11,000 participants in the Fenland Study using wearable sensors, with a subset of participants tested again seven years later. ̽��ֱ��researchers used the data to develop a model to predict VO2max, which was then validated against a third group that carried out a standard lab-based exercise test. ̽��ֱ��model showed a high degree of accuracy compared to lab-based tests, and outperforms other approaches.

Some smartwatches and fitness monitors currently on the market claim to provide an estimate of VO2max, but since the algorithms powering these predictions aren’t published and are subject to change at any time, it’s unclear whether the predictions are accurate, or whether an exercise regime is having any effect on an individual’s VO2max over time.

̽��ֱ��Cambridge-developed model is robust, transparent and provides accurate predictions based on heart rate and accelerometer data only. Since the model can also detect fitness changes over time, it could also be useful in estimating fitness levels for entire populations and identifying the effects of lifestyle trends. ̽��ֱ��results are reported in the journal npj Digital Medicine.

A measurement of VO2max is considered the ‘gold standard’ of fitness tests. Professional athletes, for example, test their VO2max by measuring their oxygen consumption while they exercise to the point of exhaustion. There are other ways of measuring fitness in the laboratory, like heart rate response to exercise tests, but these require equipment like a treadmill or exercise bike. Additionally, strenuous exercise can be a risk to some individuals.

“VO2max isn’t the only measurement of fitness, but it’s an important one for endurance, and is a strong predictor of diabetes, heart disease, and other mortality risks,” said co-author Dr Soren Brage from Cambridge’s Medical Research Council (MRC) Epidemiology Unit. “However, since most VO2max tests are done on people who are reasonably fit, it’s hard to get measurements from those who are not as fit and might be at risk of cardiovascular disease.”

“We wanted to know whether it was possible to accurately predict VO2max using data from a wearable device, so that there would be no need for an exercise test,” said co-lead author Dr Dimitris Spathis from Cambridge’s Department of Computer Science and Technology. “Our central question was whether wearable devices can measure fitness in the wild. Most wearables provide metrics like heart rate, steps or sleeping time, which are proxies for health, but aren’t directly linked to health outcomes.”

̽��ֱ��study was a collaboration between the two departments: the team from the MRC Epidemiology Unit provided expertise in population health and cardiorespiratory fitness and data from the Fenland Study – a long-running public health study in the East of England – while the team from the Department of Computer Science and Technology provided expertise in machine learning and artificial intelligence for mobile and wearable data.

Participants in the study wore wearable devices continuously for six days. ̽��ֱ��sensors gathered 60 values per second, resulting in an enormous amount of data before processing. “We had to design an algorithm pipeline and appropriate models that could compress this huge amount of data and use it to make an accurate prediction,” said Spathis. “ ̽��ֱ��free-living nature of the data makes this prediction challenging because we’re trying to predict a high-level outcome (fitness) with noisy low-level data (wearable sensors).”

̽��ֱ��researchers used an AI model known as a deep neural network to process and extract meaningful information from the raw sensor data and make predictions of VO2max from it. Beyond predictions, the trained models can be used for the identification of sub-populations in particular need of intervention related to fitness.

̽��ֱ��baseline data from 11,059 participants in the Fenland Study was compared with follow-up data from seven years later, taken from a subset of 2,675 of the original participants. A third group of 181 participants from the UK Biobank Validation Study underwent lab-based VO2max testing to validate the accuracy of the algorithm. ̽��ֱ��machine learning model had strong agreement with the measured VO2max scores at both baseline (82% agreement) and follow-up testing (72% agreement).

“This study is a perfect demonstration of how we can leverage expertise across epidemiology, public health, machine learning and signal processing,” said co-lead author Dr Ignacio Perez-Pozuelo.

̽��ֱ��researchers say that their results demonstrate how wearables can accurately measure fitness, but transparency needs to be improved if measurements from commercially available wearables are to be trusted.

“It’s true in principle that many fitness monitors and smartwatches provide a measurement of VO2max, but it’s very difficult to assess the validity of those claims,” said Brage. “ ̽��ֱ��models aren’t usually published, and the algorithms can change on a regular basis, making it difficult for people to determine if their fitness has actually improved or if it’s just being estimated by a different algorithm.”

“Everything on your smartwatch related to health and fitness is an estimate,” said Spathis. “We’re transparent about our modelling and we did it at scale. We show that we can achieve better results with the combination of noisy data and traditional biomarkers. Also, all our algorithms and models are open-sourced and everyone can use them.”

“We’ve shown that you don’t need an expensive test in a lab to get a real measurement of fitness – the wearables we use every day can be just as powerful, if they have the right algorithm behind them,” said senior author Professor Cecilia Mascolo from the Department of Computer Science and Technology. “Cardio-fitness is such an important health marker, but until now we did not have the means to measure it at scale. These findings could have significant implications for population health policies, so we can move beyond weaker health proxies such as the Body Mass Index (BMI).”

̽��ֱ��research was supported in part by Jesus College, Cambridge and the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI). Cecilia Mascolo is a Fellow of Jesus College, Cambridge.

Reference:
Dimitris Spathis et al. ‘Longitudinal cardio-respiratory fitness prediction through wearables in free-living environments.’ npj Digital Medicine (2022). DOI: 10.1038/s41746-022-00719-1

Cambridge researchers have developed a method for measuring overall fitness accurately on wearable devices – and more robustly than current consumer smartwatches and fitness monitors – without the wearer needing to exercise.

You don’t need an expensive test in a lab to get a real measurement of fitness – the wearables we use every day can be just as powerful, if they have the right algorithm behind them

Cecilia Mascolo

Oscar Wong via Getty Images

Woman checking her smart watch and mobile phone after run

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