Are we all in this together? Longitudinal assessment of cumulative adversities by socioeconomic position in the first 3 weeks of lockdown in the UK.
Identifieur interne : 002484 ( Main/Corpus ); précédent : 002483; suivant : 002485Are we all in this together? Longitudinal assessment of cumulative adversities by socioeconomic position in the first 3 weeks of lockdown in the UK.
Auteurs : Liam Wright ; Andrew Steptoe ; Daisy FancourtSource :
- Journal of epidemiology and community health [ 1470-2738 ] ; 2020.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Betacoronavirus (MeSH), COVID-19 (MeSH), Coronavirus Infections (economics), Coronavirus Infections (epidemiology), Cost of Illness (MeSH), Economic Recession (MeSH), Female (MeSH), Humans (MeSH), Income (statistics & numerical data), Male (MeSH), Middle Aged (MeSH), Pandemics (economics), Pandemics (prevention & control), Pneumonia, Viral (economics), Pneumonia, Viral (epidemiology), Quality of Life (psychology), Quarantine (economics), Quarantine (psychology), SARS-CoV-2 (MeSH), Sickness Impact Profile (MeSH), Social Conditions (MeSH), Socioeconomic Factors (MeSH), United Kingdom (epidemiology), Young Adult (MeSH).
- MESH :
- geographic , epidemiology : United Kingdom.
- economics : Coronavirus Infections, Pandemics, Pneumonia, Viral, Quarantine.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- prevention & control : Pandemics.
- psychology : Quality of Life, Quarantine.
- statistics & numerical data : Income.
- Adolescent, Adult, Aged, Aged, 80 and over, Betacoronavirus, COVID-19, Cost of Illness, Economic Recession, Female, Humans, Male, Middle Aged, SARS-CoV-2, Sickness Impact Profile, Social Conditions, Socioeconomic Factors, Young Adult.
Abstract
BACKGROUND
Despite media claims that coronavirus disease 2019 (COVID-19) is uniting societies and countries in shared experience, there has been concern that the pandemic is in fact exposing and widening existing inequalities within societies. Data have shown these differences for cases and fatalities, but data on other types of adversities are lacking. Therefore, this study explored the changing patterns of adversity relating to the COVID-19 pandemic by socioeconomic position (SEP) during the early weeks of lockdown in the UK.
METHODS
Data were from 12 527 UK adults in the University College London COVID-19 Social Study (a panel study that involves online weekly data collection from participants during the COVID-19 pandemic). We analysed data collected from 25 March to 14 April 2020. The sample was well-stratified and weighted to population proportions of gender, age, ethnicity, education and country of living. We used Poisson and logit models to assess 10 different types of adverse experiences depending on an index of SEP over time.
RESULTS
There was a clear gradient across the number of adverse events experienced each week by SEP. This was most clearly seen for adversities relating to finances (including loss of employment and cut in income) and basic needs (including access to food and medications) but less for experiences directly relating to the virus. Inequalities were maintained with no reductions in discrepancies between socioeconomic groups over time.
CONCLUSIONS
There were clear inequalities in adverse experiences during the COVID-19 pandemic in the early weeks of lockdown in the UK. Results suggest that measures taken to try to reduce such adverse events did not go far enough in tackling inequality.
DOI: 10.1136/jech-2020-214475
PubMed: 32503892
PubMed Central: PMC7298206
Links to Exploration step
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<author><name sortKey="Fancourt, Daisy" sort="Fancourt, Daisy" uniqKey="Fancourt D" first="Daisy" last="Fancourt">Daisy Fancourt</name>
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<term>Betacoronavirus (MeSH)</term>
<term>COVID-19 (MeSH)</term>
<term>Coronavirus Infections (economics)</term>
<term>Coronavirus Infections (epidemiology)</term>
<term>Cost of Illness (MeSH)</term>
<term>Economic Recession (MeSH)</term>
<term>Female (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Income (statistics & numerical data)</term>
<term>Male (MeSH)</term>
<term>Middle Aged (MeSH)</term>
<term>Pandemics (economics)</term>
<term>Pandemics (prevention & control)</term>
<term>Pneumonia, Viral (economics)</term>
<term>Pneumonia, Viral (epidemiology)</term>
<term>Quality of Life (psychology)</term>
<term>Quarantine (economics)</term>
<term>Quarantine (psychology)</term>
<term>SARS-CoV-2 (MeSH)</term>
<term>Sickness Impact Profile (MeSH)</term>
<term>Social Conditions (MeSH)</term>
<term>Socioeconomic Factors (MeSH)</term>
<term>United Kingdom (epidemiology)</term>
<term>Young Adult (MeSH)</term>
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<keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>United Kingdom</term>
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<keywords scheme="MESH" qualifier="economics" xml:lang="en"><term>Coronavirus Infections</term>
<term>Pandemics</term>
<term>Pneumonia, Viral</term>
<term>Quarantine</term>
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<term>Pneumonia, Viral</term>
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<keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Income</term>
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<keywords scheme="MESH" xml:lang="en"><term>Adolescent</term>
<term>Adult</term>
<term>Aged</term>
<term>Aged, 80 and over</term>
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<term>COVID-19</term>
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<front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b>
</p>
<p>Despite media claims that coronavirus disease 2019 (COVID-19) is uniting societies and countries in shared experience, there has been concern that the pandemic is in fact exposing and widening existing inequalities within societies. Data have shown these differences for cases and fatalities, but data on other types of adversities are lacking. Therefore, this study explored the changing patterns of adversity relating to the COVID-19 pandemic by socioeconomic position (SEP) during the early weeks of lockdown in the UK.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>METHODS</b>
</p>
<p>Data were from 12 527 UK adults in the University College London COVID-19 Social Study (a panel study that involves online weekly data collection from participants during the COVID-19 pandemic). We analysed data collected from 25 March to 14 April 2020. The sample was well-stratified and weighted to population proportions of gender, age, ethnicity, education and country of living. We used Poisson and logit models to assess 10 different types of adverse experiences depending on an index of SEP over time.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>RESULTS</b>
</p>
<p>There was a clear gradient across the number of adverse events experienced each week by SEP. This was most clearly seen for adversities relating to finances (including loss of employment and cut in income) and basic needs (including access to food and medications) but less for experiences directly relating to the virus. Inequalities were maintained with no reductions in discrepancies between socioeconomic groups over time.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b>
</p>
<p>There were clear inequalities in adverse experiences during the COVID-19 pandemic in the early weeks of lockdown in the UK. Results suggest that measures taken to try to reduce such adverse events did not go far enough in tackling inequality.</p>
</div>
</front>
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<Abstract><AbstractText Label="BACKGROUND">Despite media claims that coronavirus disease 2019 (COVID-19) is uniting societies and countries in shared experience, there has been concern that the pandemic is in fact exposing and widening existing inequalities within societies. Data have shown these differences for cases and fatalities, but data on other types of adversities are lacking. Therefore, this study explored the changing patterns of adversity relating to the COVID-19 pandemic by socioeconomic position (SEP) during the early weeks of lockdown in the UK.</AbstractText>
<AbstractText Label="METHODS">Data were from 12 527 UK adults in the University College London COVID-19 Social Study (a panel study that involves online weekly data collection from participants during the COVID-19 pandemic). We analysed data collected from 25 March to 14 April 2020. The sample was well-stratified and weighted to population proportions of gender, age, ethnicity, education and country of living. We used Poisson and logit models to assess 10 different types of adverse experiences depending on an index of SEP over time.</AbstractText>
<AbstractText Label="RESULTS">There was a clear gradient across the number of adverse events experienced each week by SEP. This was most clearly seen for adversities relating to finances (including loss of employment and cut in income) and basic needs (including access to food and medications) but less for experiences directly relating to the virus. Inequalities were maintained with no reductions in discrepancies between socioeconomic groups over time.</AbstractText>
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<CopyrightInformation>© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.</CopyrightInformation>
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