Lifestyle risk behaviours among adolescents: a two-year longitudinal study of the impact of the COVID-19 pandemic

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Abstract

Objective

To examine changes in the prevalence of six key chronic disease risk factors (the “Big 6”), from before (2019) to during (2021) the COVID-19 pandemic, among a large and geographically diverse sample of adolescents, and whether differences over time are associated with lockdown status and gender.

Design

Prospective cohort study.

Setting

Three Australian states (New South Wales, Queensland and Western Australia) spanning over 3000 km.

Participants

983 adolescents (baseline M _age=12.6, SD=0.5, 54.8% girl) drawn from the control group of the Health4Life Study.

Primary outcomes

The prevalence of physical inactivity, poor diet (insufficient fruit and vegetable intake, high sugar-sweetened beverage intake, high discretionary food intake), poor sleep, excessive recreational screen time, alcohol use and tobacco use.

Results

The prevalence of excessive recreational screen time (prevalence ratios (PR)=1.06, 95% CI=1.03 to 1.11), insufficient fruit intake (PR=1.50, 95% CI=1.26 to 1.79), and alcohol (PR=4.34, 95% CI=2.82 to 6.67) and tobacco use (PR=4.05 95% CI=1.86 to 8.84) increased over the 2-year period, with alcohol use increasing more among girls (PR=2.34, 95% CI=1.19 to 4.62). The prevalence of insufficient sleep declined across the full sample (PR=0.74, 95% CI=0.68 to 0.81); however, increased among girls (PR=1.24, 95% CI=1.10 to 1.41). The prevalence of high sugar-sweetened beverage (PR=0.61, 95% CI=0.64 to 0.83) and discretionary food consumption (PR=0.73, 95% CI=0.64 to 0.83) reduced among those subjected to stay-at-home orders, compared with those not in lockdown.

Conclusion

Lifestyle risk behaviours, particularly excessive recreational screen time, poor diet, physical inactivity and poor sleep, are prevalent among adolescents. Young people must be supported to find ways to improve or maintain their health, regardless of the course of the pandemic. Targeted approaches to support groups that may be disproportionately impacted, such as adolescent girls, are needed.

Trial registration number

Australian New Zealand Clinical Trials Registry (ACTRN12619000431123)

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Most cited references 66

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An interactive web-based dashboard to track COVID-19 in real time

Ensheng Dong, Hongru Du, Lauren Gardner (2020)

In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.

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A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)

Thomas C. Hale, Noam Angrist, Rafael Goldszmidt … (2021)

COVID-19 has prompted unprecedented government action around the world. We introduce the Oxford COVID-19 Government Response Tracker (OxCGRT), a dataset that addresses the need for continuously updated, readily usable and comparable information on policy measures. From 1 January 2020, the data capture government policies related to closure and containment, health and economic policy for more than 180 countries, plus several countries' subnational jurisdictions. Policy responses are recorded on ordinal or continuous scales for 19 policy areas, capturing variation in degree of response. We present two motivating applications of the data, highlighting patterns in the timing of policy adoption and subsequent policy easing and reimposition, and illustrating how the data can be combined with behavioural and epidemiological indicators. This database enables researchers and policymakers to explore the empirical effects of policy responses on the spread of COVID-19 cases and deaths, as well as on economic and social welfare.

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Global trends in insufficient physical activity among adolescents: a pooled analysis of 298 population-based surveys with 1·6 million participants

Regina Guthold, Gretchen Stevens, Leanne Riley … (2020)

Summary Background Physical activity has many health benefits for young people. In 2018, WHO launched More Active People for a Healthier World, a new global action on physical activity, including new targets of a 15% relative reduction of global prevalence of insufficient physical activity by 2030 among adolescents and adults. We describe current prevalence and trends of insufficient physical activity among school-going adolescents aged 11–17 years by country, region, and globally. Methods We did a pooled analysis of cross-sectional survey data that were collected through random sampling with a sample size of at least 100 individuals, were representative of a national or defined subnational population, and reported prevalence of of insufficient physical activity by sex in adolescents. Prevalence had to be reported for at least three of the years of age within the 10–19-year age range. We estimated the prevalence of insufficient physical activity in school-going adolescents aged 11–17 years (combined and by sex) for individual countries, for four World Bank income groups, nine regions, and globally for the years 2001–16. To derive a standard definition of insufficient physical activity and to adjust for urban-only survey coverage, we used regression models. We estimated time trends using multilevel mixed-effects modelling. Findings We used data from 298 school-based surveys from 146 countries, territories, and areas including 1·6 million students aged 11–17 years. Globally, in 2016, 81·0% (95% uncertainty interval 77·8–87·7) of students aged 11–17 years were insufficiently physically active (77·6% [76·1–80·4] of boys and 84·7% [83·0–88·2] of girls). Although prevalence of insufficient physical activity significantly decreased between 2001 and 2016 for boys (from 80·1% [78·3–81·6] in 2001), there was no significant change for girls (from 85·1% [83·1–88·0] in 2001). There was no clear pattern according to country income group: insufficient activity prevalence in 2016 was 84·9% (82·6–88·2) in low-income countries, 79·3% (77·2–87·5) in lower–middle-income countries, 83·9% (79·5–89·2) in upper–middle-income countries, and 79·4% (74·0–86·2) in high-income countries. The region with the highest prevalence of insufficient activity in 2016 was high-income Asia Pacific for both boys (89·0%, 62·8–92·2) and girls (95·6%, 73·7–97·9). The regions with the lowest prevalence were high-income western countries for boys (72·1%, 71·1–73·6), and south Asia for girls (77·5%, 72·8–89·3). In 2016, 27 countries had a prevalence of insufficient activity of 90% or more for girls, whereas this was the case for two countries for boys. Interpretation The majority of adolescents do not meet current physical activity guidelines. Urgent scaling up of implementation of known effective policies and programmes is needed to increase activity in adolescents. Investment and leadership at all levels to intervene on the multiple causes and inequities that might perpetuate the low participation in physical activity and sex differences, as well as engagement of youth themselves, will be vital to strengthen the opportunities for physical activity in all communities. Such action will improve the health of this and future young generations and support achieving the 2030 Sustainable Development Goals. Funding WHO.

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Author and article information

Journal

Journal ID (nlm-ta): BMJ Open

Journal ID (iso-abbrev): BMJ Open

Journal ID (hwp): bmjopen

Journal ID (publisher-id): bmjopen

Title: BMJ Open

Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )

ISSN (Electronic): 2044-6055

Publication date Collection: 2022

Publication date (Electronic): 19 May 2022

Publication date PMC-release: 19 May 2022

Volume: 12

Issue: 6

Electronic Location Identifier: e060309

Affiliations

[1 ] departmentThe Matilda Centre for Research Excellence in Mental Health and Substance Use , The University of Sydney , Sydney, New South Wales, Australia

[2 ] departmentDepartment of Psychology , Macquarie University , Sydney, New South Wales, Australia

Author notes

[Correspondence to ] Dr Lauren Anne Gardner; lauren.gardner@ 123456sydney.edu.au

Author information

Lauren Anne Gardner http://orcid.org/0000-0002-8592-6691

Jennifer Debenham http://orcid.org/0000-0002-9596-9484

Cath Chapman http://orcid.org/0000-0002-2460-6862

Katrina Elizabeth Champion http://orcid.org/0000-0001-8319-9366

Article

Publisher ID: bmjopen-2021-060309

DOI: 10.1136/bmjopen-2021-060309

PMC ID: 9170793

PubMed ID: 35649588

SO-VID: 82a1513a-0480-40e6-b81e-31e5345f7da7

License:

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

History

Date received : 17 December 2021

Date accepted : 04 May 2022

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ScienceOpen disciplines: Medicine

Keywords: covid-19,public health,epidemiology

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ScienceOpen disciplines: Medicine

Keywords: covid-19, public health, epidemiology

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Lifestyle risk behaviours among adolescents: a two-year longitudinal study of the impact of the COVID-19 pandemic

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Abstract

Objective

Design

Setting

Participants

Primary outcomes

Results

Conclusion

Trial registration number

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 66

An interactive web-based dashboard to track COVID-19 in real time

A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)

Global trends in insufficient physical activity among adolescents: a pooled analysis of 298 population-based surveys with 1·6 million participants

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Cited by 13

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