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4. COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

Author

Abbasizanjani, Hoda, Ahmed, Nida, Ahmed, Badar, Akbari, Ashley, Akinoso-Imran, Abdul Qadr, Allara, Elias, Allery, Freya, Angelantonio, Emanuele Di, Ashworth, Mark, Ayyar-Gupta, Vandana, Babu-Narayan, Sonya, Bacon, Seb, Ball, Steve, Banerjee, Ami, Barber, Mark, Barrett, Jessica, Bennie, Marion, Berry, Colin, Beveridge, Jennifer, Birney, Ewan, Bojanić, Lana, Bolton, Thomas, Bone, Anna, Boyle, Jon, Braithwaite, Tasanee, Bray, Ben, Briffa, Norman, Brind, David, Brown, Katherine, Buch, Maya, Canoy, Dexter, Caputo, Massimo, Carragher, Raymond, Carson, Alan, Cezard, Genevieve, Chang, Jen-Yu Amy, Cheema, Kate, Chin, Richard, Chudasama, Yogini, Cooper, Jennifer, Copland, Emma, Crallan, Rebecca, Cripps, Rachel, Cromwell, David, Curcin, Vasa, Curry, Gwenetta, Dale, Caroline, Danesh, John, Das-Munshi, Jayati, Dashtban, Ashkan, Davies, Alun, Davies, Joanna, Davies, Gareth, Davies, Neil, Day, Joshua, Delmestri, Antonella, Denaxas, Spiros, Denholm, Rachel, Dennis, John, Denniston, Alastair, Deo, Salil, Dhillon, Baljean, Docherty, Annemarie, Dong, Tim, Douiri, Abdel, Downs, Johnny, Dregan, Alexandru, Ellins, Elizabeth A, Elwenspoek, Martha, Falck, Fabian, Falter, Florian, Fan, Yat Yi, Firth, Joseph, Fraser, Lorna, Friebel, Rocco, Gavrieli, Amir, Gerstung, Moritz, Gilbert, Ruth, Gillies, Clare, Glickman, Myer, Goldacre, Ben, Goldacre, Raph, Greaves, Felix, Green, Mark, Grieco, Luca, Griffiths, Rowena, Gurdasani, Deepti, Halcox, Julian, Hall, Nick, Hama, Tuankasfee, Handy, Alex, Hansell, Anna, Hardelid, Pia, Hardy, Flavien, Harris, Daniel, Harrison, Camille, Harron, Katie, Hassaine, Abdelaali, Hassan, Lamiece, Healey, Russell, Hemingway, Harry, Henderson, Angela, Herz, Naomi, Heyl, Johannes, Hidajat, Mira, Higginson, Irene, Hinchliffe, Rosie, Hippisley-Cox, Julia, Ho, Frederick, Hocaoglu, Mevhibe, Hollings, Sam, Horne, Elsie, Hughes, David, Humberstone, Ben, Inouye, Mike, Ip, Samantha, Islam, Nazrul, Jackson, Caroline, Jenkins, David, Jiang, Xiyun, Johnson, Shane, Kadam, Umesh, Kallis, Costas, Karim, Zainab, Kasan, Jake, Katsoulis, Michalis, Kavanagh, Kim, Kee, Frank, Keene, Spencer, Kent, Seamus, Khalid, Sara, Khawaja, Anthony, Khunti, Kamlesh, Killick, Richard, Kinnear, Deborah, Knight, Rochelle, Kolamunnage-Dona, Ruwanthi, Kontopantelis, Evan, Kurdi, Amanj, Lacey, Ben, Lai, Alvina, Lambarth, Andrew, Larzjan, Milad Nazarzadeh, Lawler, Deborah, Lawrence, Thomas, Lawson, Claire, Li, Qiuju, Li, Ken, Llinares, Miguel Bernabeu, Lorgelly, Paula, Lowe, Deborah, Lyons, Jane, Lyons, Ronan, Machado, Pedro, Macleod, Mary Joan, Macleod, John, Malgapo, Evaleen, Mamas, Mamas, Mamouei, Mohammad, Manohar, Sinduja, Mapeta, Rutendo, Martelli, Javiera Leniz, Martos, David Moreno, Mateen, Bilal, McCarthy, Aoife, Melville, Craig, Milton, Rebecca, Mizani, Mehrdad, Moncusi, Marta Pineda, Morales, Daniel, Mordi, Ify, Morrice, Lynn, Morris, Carole, Morris, Eva, Mu, Yi, Mueller, Tanja, Murdock, Lars, Nafilyan, Vahé, Nicholson, George, Nikiphorou, Elena, Nolan, John, Norris, Tom, Norris, Ruth, North, Laura, North, Teri-Louise, O'Connell, Dan, Oliver, Dominic, Oluyase, Adejoke, Olvera-Barrios, Abraham, Omigie, Efosa, Onida, Sarah, Padmanabhan, Sandosh, Palmer, Tom, Pasea, Laura, Patel, Riyaz, Payne, Rupert, Pell, Jill, Petitjean, Carmen, Pherwani, Arun, Pickrell, Owen, Pierotti, Livia, Pirmohamed, Munir, Priedon, Rouven, Prieto-Alhambra, Dani, Proudfoot, Alastair, Quinn, Terry, Quint, Jennifer, Raffetti, Elena, Rahimi, Kazem, Rao, Shishir, Razieh, Cameron, Roberts, Brian, Rogers, Caroline, Rossdale, Jennifer, Salim, Safa, Samani, Nilesh, Sattar, Naveed, Schnier, Christian, Schwartz, Roy, Selby, David, Seminog, Olena, Shabnam, Sharmin, Shah, Ajay, Shelton, Jon, Sheppard, James, Sinha, Shubhra, Skrypak, Mirek, Slapkova, Martina, Sleeman, Katherine, Smith, Craig, Sofat, Reecha, Sosenko, Filip, Sperrin, Matthew, Steeg, Sarah, Sterne, Jonathan, Stoica, Serban, Sudell, Maria, Sudlow, Cathie, Sun, Luanluan, Suseeladevi, Arun Karthikeyan, Sweeting, Michael, Sydes, Matt, Takhar, Rohan, Tang, Howard, Thygesen, Johan, Tilston, George, Tochel, Claire, Toit, Clea du, Tomlinson, Christopher, Toms, Renin, Torabi, Fatemeh, Torralbo, Ana, Townson, Julia, Tufail, Adnan, Tungamirai, Tapiwa, Varma, Susheel, Vollmer, Sebastian, Walker, Venexia, Wang, Tianxiao, Wang, Huan, Warwick, Alasdair, Watkinson, Ruth, Watson, Harry, Whiteley, William, Whittaker, Hannah, Wilde, Harry, Wilkinson, Tim, Williams, Gareth, Williams, Michelle, Williams, Richard, Withnell, Eloise, Wolfe, Charles, Wood, Angela, Wright, Lucy, Wu, Honghan, Wu, Jinge, Wu, Jianhua, Yates, Tom, Zaccardi, Francesco, Zhang, Haoting, Zhang, Huayu, Zuccolo, Luisa, Thygesen, Johan H, Mizani, Mehrdad A, Banerjee, Amitava, Lai, Alvina G, Li, Kezhi, Mateen, Bilal A, Sterne, Jonathan A C, Pagel, Christina, and Whiteley, William N

Published
2022
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13. Impact of the COVID-19 pandemic on hospital episodes for falls and fractures associated with new-onset disability and frailty in England: a national cohort study.

Author

Thomas, Seth, Littleboy, Kathryn, Foubert, Josephine, Nafilyan, Vahe, Bannister, Neil, Routen, Ash, Morriss, Richard, Khunti, Kamlesh, Armstrong, Natalie, Gray, Laura J, and Gordon, Adam L

Subjects
RISK assessment, NATIONAL health services, PATIENTS, FRAIL elderly, HOSPITAL admission & discharge, PATIENT care, TIME series analysis, BONE fractures, LONGITUDINAL method, STAY-at-home orders, COVID-19 pandemic, ACCIDENTAL falls, DISEASE risk factors, OLD age
Abstract

Background Older people with frailty are at risk of harm from immobility or isolation, yet data about how COVID-19 lockdowns affected them are limited. Falls and fractures are easily measurable adverse outcomes correlated with frailty. We investigated whether English hospital admission rates for falls and fractures varied from the expected trajectory during the COVID-19 pandemic, and how these varied by frailty status. Methods NHS England Hospital Episode Statistics Admitted Patient Care data were analysed for observed versus predicted outcome rates for 24 January 2020 to 31 December 2021. An auto-regressive integrated moving average time-series model was trained using falls and fracture incidence data from 2013 to 2018 and validated using data from 2019. Models included national and age-, sex- and region-stratified forecasts. Outcome measures were hospital admissions for falls, fractures, and falls and fractures combined. Frailty was defined using the Hospital Frailty Risk Score. Results 144,148,915 pre-pandemic hospital admissions were compared with 42,267,318 admissions after pandemic onset. For the whole population, falls and fracture rates were below predicted for the first period of national lockdown, followed by a rapid return to rates close to predicted. Thereafter, rates followed expected trends. For people living with frailty, however, falls and fractures increased above expected rates during periods of national lockdown and remained elevated throughout the study period. Effects of frailty were independent of age. Conclusions People living with frailty experienced increased fall and fracture rates above expected during and following periods of national lockdown. These remained persistently elevated throughout the study period. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting

Author

Thomas, Seth, primary, Machuel, Perrine, additional, Foubert, Josephine, additional, Nafilyan, Vahe, additional, Bannister, Neil, additional, Colvin, Helen, additional, Routen, Ash, additional, Morriss, Richard, additional, Khunti, Kamlesh, additional, Farooqi, Azhar, additional, Armstrong, Natalie, additional, Gray, Laura, additional, and Gordon, Adam, additional

Published
2023
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19. The effect on women's health of extending parental leave:a quasi-experimental registry-based cohort study

Author

Courtin, Emilie, Rieckmann, Andreas, Bengtsson, Jessica, Nafilyan, Vahe, Melchior, Maria, Berkman, Lisa, Rod, Naja Hulvej, Courtin, Emilie, Rieckmann, Andreas, Bengtsson, Jessica, Nafilyan, Vahe, Melchior, Maria, Berkman, Lisa, and Rod, Naja Hulvej

Abstract

Background Parental leave policies have been hypothesized to benefit mothers' mental health. We assessed the impact of a 6-week extension of parental leave in Denmark on maternal mental health. Methods We linked individual-level data from Danish national registries on maternal sociodemographic characteristics and psychiatric diagnoses. A regression discontinuity design was applied to study the increase in parental leave duration after 26 March 1984. We included women who had given birth between 1 January 1981 and 31 December 1987. Our outcome was a first psychiatric diagnosis following the child's birth, ascertained as the first day of inpatient hospital admission for any psychiatric disorder. We presented cumulative incidences for the 30-year follow-up period and reported absolute risk differences between women eligible for the reform vs not, in 5-year intervals. Results In all, 291 152 women were followed up until 2017, death, emigration or date of first psychiatric diagnosis. The median follow-up time was 29.99 years, corresponding to 10 277 547 person-years at risk. The cumulative incidence of psychiatric diagnoses at 30 years of follow-up was 59.5 (95% CI: 57.4 to 61.6) per 1000 women in the ineligible group and 57.5 (95% CI: 55.6 to 59.4) in the eligible group. Eligible women took on average 32.85 additional days of parental leave (95% CI: 29.20 to 36.49) and had a lower probability of having a psychiatric diagnosis within 5 years [risk difference (RD): 2.4 fewer diagnoses per 1000 women, 95% CI: 1.5 to 3.2] and up to 20 years after the birth (RD: 2.3, 95% CI: 0.4 to 4.2). In subgroup analyses, the risk reduction was concentrated among low-educated, low-income and single women. Conclusions Longer parental leave may confer mental health benefits to women, in particular to those from disadvantaged backgrounds.

Published
2023

20. Occupational differences in COVID-19 incidence, severity, and mortality in the United Kingdom: Available data and framework for analyses

Author

Pearce, Neil, primary, Rhodes, Sarah, additional, Stocking, Katie, additional, Pembrey, Lucy, additional, van Veldhoven, Karin, additional, Brickley, Elizabeth B., additional, Robertson, Steve, additional, Davoren, Donna, additional, Nafilyan, Vahe, additional, Windsor-Shellard, Ben, additional, Fletcher, Tony, additional, and van Tongeren, Martie, additional

Published
2023
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24. The effect on women's health of extending parental leave: a quasi-experimental registry-based cohort study.

Author

Courtin, Emilie, Rieckmann, Andreas, Bengtsson, Jessica, Nafilyan, Vahe, Melchior, Maria, Berkman, Lisa, and Rod, Naja Hulvej

Subjects
PARENTAL leave, HOSPITAL admission & discharge, WOMEN'S health, REGRESSION discontinuity design, PSYCHIATRIC diagnosis, WOMEN'S mental health
Abstract

Background Parental leave policies have been hypothesized to benefit mothers' mental health. We assessed the impact of a 6-week extension of parental leave in Denmark on maternal mental health. Methods We linked individual-level data from Danish national registries on maternal sociodemographic characteristics and psychiatric diagnoses. A regression discontinuity design was applied to study the increase in parental leave duration after 26 March 1984. We included women who had given birth between 1 January 1981 and 31 December 1987. Our outcome was a first psychiatric diagnosis following the child's birth, ascertained as the first day of inpatient hospital admission for any psychiatric disorder. We presented cumulative incidences for the 30-year follow-up period and reported absolute risk differences between women eligible for the reform vs not, in 5-year intervals. Results In all, 291 152 women were followed up until 2017, death, emigration or date of first psychiatric diagnosis. The median follow-up time was 29.99 years, corresponding to 10 277 547 person-years at risk. The cumulative incidence of psychiatric diagnoses at 30 years of follow-up was 59.5 (95% CI: 57.4 to 61.6) per 1000 women in the ineligible group and 57.5 (95% CI: 55.6 to 59.4) in the eligible group. Eligible women took on average 32.85 additional days of parental leave (95% CI: 29.20 to 36.49) and had a lower probability of having a psychiatric diagnosis within 5 years [risk difference (RD): 2.4 fewer diagnoses per 1000 women, 95% CI: 1.5 to 3.2] and up to 20 years after the birth (RD: 2.3, 95% CI: 0.4 to 4.2). In subgroup analyses, the risk reduction was concentrated among low-educated, low-income and single women. Conclusions Longer parental leave may confer mental health benefits to women, in particular to those from disadvantaged backgrounds. [ABSTRACT FROM AUTHOR]

Published
2023
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25. Longitudinal changes in proportionate mortality due to COVID-19 by occupation in England and Wales

Author

Cherrie, Mark, Rhodes, Sarah, Wilkinson, Jack, Mueller, William, Nafilyan, Vahe, Van Tongeren, Martie, Pearce, Neil, and Kreissl, Helen

Subjects
Wales, Logistic Models, proportionate mortality analysis, SARS-CoV-2, occupational inequality, Public Health, Environmental and Occupational Health, Humans, COVID-19, Occupations, Pandemics
Abstract

OBJECTIVE: This study aimed to understand whether the proportionate mortality of COVID-19 for various occupational groups has varied over the pandemic.METHODS: We used the Office for National Statistics (ONS) mortality data for England and Wales. The deaths (20-64 years) were classified as either COVID-19-related using ICD-10 codes (U07.1, U07.2), or from other causes. Occupational data recorded at the time of death was coded using the SOC10 coding system into 13 groups. Three time periods (TP) were used: (i) January 2020 to September 2020; (ii) October 2020-May 2021; and (iii) June 2021-October 2021. We analyzed the data with logistic regression and compared odds of death by COVID-19 to other causes, adjusting for age, sex, deprivation, region, urban/rural and population density.RESULTS: Healthcare professionals and associates had a higher proportionate odds of COVID-19 death in TP1 compared to non-essential workers but were not observed to have increased odds thereafter. Medical support staff had increased odds of death from COVID-19 during both TP1 and TP2, but this had reduced by TP3. This latter pattern was also seen for social care, food retail and distribution, and bus and coach drivers. Taxi and cab drivers were the only group that had higher odds of death from COVID-19 compared to other causes throughout the whole period under study [TP1: odds ratio (OR) 2.42, 95% confidence interval (CI) 1.99-2.93; TP2: OR 3.15, 95% CI 2.63-3.78; TP3: OR 1.7, 95% CI 1.26-2.29].CONCLUSION: Differences in the odds of death from COVID-19 between occupational groups has declined over the course of the pandemic, although some occupations have remained relatively high throughout.

Published
2022

27. COVID-19 vaccination uptake amongst ethnic minority communities in England: a linked study exploring the drivers of differential vaccination rates.

Author

Gaughan, Charlotte Hannah, Razieh, Cameron, Khunti, Kamlesh, Banerjee, Amitava, Chudasama, Yogini V, Davies, Melanie J, Dolby, Ted, Gillies, Clare L, Lawson, Claire, Mirkes, Evgeny M, Morgan, Jasper, Tingay, Karen, Zaccardi, Francesco, Yates, Thomas, and Nafilyan, Vahe

Subjects
CULTURE, MINORITIES, COVID-19, CONFIDENCE intervals, COVID-19 vaccines, RACE, POPULATION geography, MEDICAL care use, SOCIAL isolation, DESCRIPTIVE statistics, VACCINE hesitancy, RESEARCH funding, ODDS ratio, SOCIODEMOGRAPHIC factors, EDUCATIONAL attainment, RELIGION
Abstract

Background Despite generally high coronavirus disease 2019 (COVID-19) vaccination rates in the UK, vaccination hesitancy and lower take-up rates have been reported in certain ethnic minority communities. Methods We used vaccination data from the National Immunisation Management System (NIMS) linked to the 2011 Census and individual health records for subjects aged ≥40 years (n = 24 094 186). We estimated age-standardized vaccination rates, stratified by ethnic group and key sociodemographic characteristics, such as religious affiliation, deprivation, educational attainment, geography, living conditions, country of birth, language skills and health status. To understand the association of ethnicity with lower vaccination rates, we conducted a logistic regression model adjusting for differences in geographic, sociodemographic and health characteristics. Results All ethnic groups had lower age-standardized rates of vaccination compared with the white British population, whose vaccination rate of at least one dose was 94% (95% CI: 94%–94%). Black communities had the lowest rates, with 75% (74–75%) of black African and 66% (66–67%) of black Caribbean individuals having received at least one dose. The drivers of these lower rates were partly explained by accounting for sociodemographic differences. However, modelled estimates showed significant differences remained for all minority ethnic groups, compared with white British individuals. Conclusions Lower COVID-19 vaccination rates are consistently observed amongst all ethnic minorities. [ABSTRACT FROM AUTHOR]

Published
2023
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30. Corrigendum to: COVID-19 vaccination uptake amongst ethnic minority communities in England: a linked study exploring the drivers of differential vaccination rates

Author

Gaughan, Charlotte Hannah, primary, Razieh, Cameron, additional, Khunti, Kamlesh, additional, Banerjee, Amitava, additional, Chudasama, Yogini V, additional, Davies, Melanie J, additional, Dolby, Ted, additional, Gillies, Clare L, additional, Lawson, Claire, additional, Mirkes, Evgeny M, additional, Morgan, Jasper, additional, Tingay, Karen, additional, Zaccardi, Francesco, additional, Yates, Thomas, additional, and Nafilyan, Vahe, additional

Published
2022
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31. COVID-19 vaccination uptake amongst ethnic minority communities in England: a linked study exploring the drivers of differential vaccination rates

Author

Gaughan, Charlotte Hannah, primary, Razieh, Cameron, additional, Khunti, Kamlesh, additional, Banerjee, Amitava, additional, Chudasama, Yogini V, additional, Davies, Melanie J, additional, Dolby, Ted, additional, Gillies, Clare L, additional, Lawson, Claire, additional, Mirkes, Evgeny M, additional, Morgan, Jasper, additional, Tingay, Karen, additional, Zaccardi, Francesco, additional, Yates, Thomas, additional, and Nafilyan, Vahe, additional

Published
2022
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37. Occupational differences in COVID-19 incidence, severity, and mortality in the United Kingdom: Available data and framework for analyses [version 1; peer review: 1 approved, 2 approved with reservations]:Available data and framework for analyses

Author

Pearce, Neil, Rhodes, Sarah, Stocking, Katie, Pembrey, Lucy, Veldhoven, Karin van, Brickley, Elizabeth B., Robertson, Steve, Davoren, Donna, Nafilyan, Vahe, Windsor-Shellard, Ben, Fletcher, Tony, Tongeren, Martie van, and Kreissl, Helen

Subjects
Occupation, Epidemiology, COVID-19, Manchester Environmental Research Institute, ResearchInstitutes_Networks_Beacons/MERI
Abstract

There are important differences in the risk of SARS-CoV-2 infection and death depending on occupation. Infections in healthcare workers have received the most attention, and there are clearly increased risks for intensive care unit workers who are caring for COVID-19 patients. However, a number of other occupations may also be at an increased risk, particularly those which involve social care or contact with the public. A large number of data sets are available with the potential to assess occupational risks of COVID-19 incidence, severity, or mortality. We are reviewing these data sets as part of the Partnership for Research in Occupational, Transport, Environmental COVID Transmission (PROTECT) initiative, which is part of the National COVID-19 Core Studies. In this report, we review the data sets available (including the key variables on occupation and potential confounders) for examining occupational differences in SARS-CoV-2 infection and COVID-19 incidence, severity and mortality. We also discuss the possible types of analyses of these data sets and the definitions of (occupational) exposure and outcomes. We conclude that none of these data sets are ideal, and all have various strengths and weaknesses. For example, mortality data suffer from problems of coding of COVID-19 deaths, and the deaths (in England and Wales) that have been referred to the coroner are unavailable. On the other hand, testing data is heavily biased in some periods (particularly the first wave) because some occupations (e.g. healthcare workers) were tested more often than the general population. Random population surveys are, in principle, ideal for estimating population prevalence and incidence, but are also affected by non-response. Thus, any analysis of the risks in a particular occupation or sector (e.g. transport), will require a careful analysis and triangulation of findings across the various available data sets.

Published
2021

39. DAGs of occupation and COVID V1.pdf

Author

Wilkinson, Jack, Beale, Sarah, Cherrie, Mark, Edge, Rhiannon, Fishwick, David, Gittins, Matthew, Katikireddi, S. Vittal, Mcelvenny, Damien, Nafilyan, Vahe, Pearce, Neil, Rhodes, Sarah, and Van tongeren, Martie

Subjects
111705 Environmental and Occupational Health and Safety, FOS: Health sciences
Abstract

Directed acyclic graphs (DAGs) may be used to represent our knowledge (or assumptions) about a data-generating process. A DAG may then be used to identify which variables should or should not be adjusted for in a statistical analysis in order to answer particular questions relating to the effect of an exposure on an outcome. The purpose of this document is to collate directed acyclic graphs (DAGs) that have been used in the study of the effects of occupation on COVID-19-related health outcomes (e.g. infection, severity, mortality). By collating DAGs, we hope to identify points of consensus and of contention. We also hope that this collection might form the basis for critical discussion, which may in turn lead to new proposals.This document is intended to be updated as new DAGs concerning occupation and COVID-19-related outcomes emerge. However, we have not undertaken any sort of systematic searchstrategy in order to identify relevant DAGs, and so this collection is unlikely to be comprehensive. The document represents the beginning of a live and ongoing data collection exercise, rather than one which is complete.We present DAGs in alphabetical order (first author surname) together with limited details relating to the objectives of the study, the design of each study, the methodology for constructing the DAG, and details of how the DAG was used.We then present a table of minimal sufficient adjustment sets for the total effect of occupation on outcome implied by each DAG.The document concludes with some brief comments and observations about the DAGs, and information about how to leave feedback is provided. We have redrawn some of the DAGs using Daggity (daggity.net) for consistency of presentation.

Published
2021
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40. Occupational differences in COVID-19 incidence, severity, and mortality in the United Kingdom: Available data and framework for analyses

Author

Pearce, Neil, primary, Rhodes, Sarah, additional, Stocking, Katie, additional, Pembrey, Lucy, additional, van Veldhoven, Karin, additional, Brickley, Elizabeth B., additional, Robertson, Steve, additional, Davoren, Donna, additional, Nafilyan, Vahe, additional, Windsor-Shellard, Ben, additional, Fletcher, Tony, additional, and van Tongeren, Martie, additional

Published
2021
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42. Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic

Author

Banerjee, Amitava, primary, Chen, Suliang, additional, Pasea, Laura, additional, Lai, Alvina G, additional, Katsoulis, Michail, additional, Denaxas, Spiros, additional, Nafilyan, Vahe, additional, Williams, Bryan, additional, Wong, Wai Keong, additional, Bakhai, Ameet, additional, Khunti, Kamlesh, additional, Pillay, Deenan, additional, Noursadeghi, Mahdad, additional, Wu, Honghan, additional, Pareek, Nilesh, additional, Bromage, Daniel, additional, McDonagh, Theresa A, additional, Byrne, Jonathan, additional, Teo, James T H, additional, Shah, Ajay M, additional, Humberstone, Ben, additional, Tang, Liang V, additional, Shah, Anoop S V, additional, Rubboli, Andrea, additional, Guo, Yutao, additional, Hu, Yu, additional, Sudlow, Cathie L M, additional, Lip, Gregory Y H, additional, and Hemingway, Harry, additional

Published
2021
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43. An external validation of the QCovid risk prediction algorithm for risk of mortality from COVID-19 in adults: national validation cohort study in England

Author

Nafilyan, Vahe, primary, Humberstone, Ben, additional, Mehta, Nisha, additional, Diamond, Ian, additional, Coupland, Carol, additional, Lorenzi, Luke, additional, Pawelek, Piotr, additional, Schofield, Ryan, additional, Morgan, Jasper, additional, Brown, Paul, additional, Lyons, Ronan, additional, Sheikh, Aziz, additional, and Hippisley-Cox, Julia, additional

Published
2021
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45. Estimated impact of the COVID-19 pandemic on cancer services and excess 1-year mortality in people with cancer and multimorbidity: near real-time data on cancer care, cancer deaths and a population-based cohort study

Author

Lai, Alvina G, primary, Pasea, Laura, additional, Banerjee, Amitava, additional, Hall, Geoff, additional, Denaxas, Spiros, additional, Chang, Wai Hoong, additional, Katsoulis, Michail, additional, Williams, Bryan, additional, Pillay, Deenan, additional, Noursadeghi, Mahdad, additional, Linch, David, additional, Hughes, Derralynn, additional, Forster, Martin D, additional, Turnbull, Clare, additional, Fitzpatrick, Natalie K, additional, Boyd, Kathryn, additional, Foster, Graham R, additional, Enver, Tariq, additional, Nafilyan, Vahe, additional, Humberstone, Ben, additional, Neal, Richard D, additional, Cooper, Matt, additional, Jones, Monica, additional, Pritchard-Jones, Kathy, additional, Sullivan, Richard, additional, Davie, Charlie, additional, Lawler, Mark, additional, and Hemingway, Harry, additional

Published
2020
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47. Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic

Author

Banerjee, Amitava, primary, Chen, Suliang, additional, Pasea, Laura, additional, Lai, Alvina G., additional, Katsoulis, Michail, additional, Denaxas, Spiros, additional, Nafilyan, Vahe, additional, Williams, Bryan, additional, Wong, Wai Keong, additional, Bakhai, Ameet, additional, Khunti, Kamlesh, additional, Pillay, Deenan, additional, Noursadeghi, Mahdad, additional, Wu, Honghan, additional, Pareek, Nilesh, additional, Bromage, Daniel, additional, McDonagh, Theresa A., additional, Byrne, Jonathan, additional, Teo, James T.H., additional, Shah, Ajay M, additional, Humberstone, Ben, additional, Tang, Liang V., additional, Shah, Anoop S. V., additional, Rubboli, Andrea, additional, Guo, Yutao, additional, Hu, Yu, additional, Sudlow, Cathie L. M., additional, Lip, Gregory Y. H., additional, and Hemingway, Harry, additional

Published
2020
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48. The effect on women’s health of extending parental leave: a quasi-experimental registry-based cohort study

Author

Courtin, Emilie, Rieckmann, Andreas, Bengtsson, Jessica, Nafilyan, Vahe, Melchior, Maria, Berkman, Lisa, Hulvej Rod, Naja, Courtin, Emilie, Rieckmann, Andreas, Bengtsson, Jessica, Nafilyan, Vahe, Melchior, Maria, Berkman, Lisa, and Hulvej Rod, Naja

Abstract

Background: Parental leave policies have been hypothesized to benefit mothers’ mental health. We assessed the impact of a 6-week extension of parental leave in Denmark on maternal mental health. Methods: We linked individual-level data from Danish national registries on maternal sociodemographic characteristics and psychiatric diagnoses. A regression discontinuity design was applied to study the increase in parental leave duration after 26 March 1984. We included women who had given birth between 1 January 1981 and 31 December 1987. Our outcome was a first psychiatric diagnosis following the child’s birth, ascertained as the first day of inpatient hospital admission for any psychiatric disorder. We presented cumulative incidences for the 30-year follow-up period and reported absolute risk differences between women eligible for the reform vs not, in 5-year intervals. Results: In all, 291 152 women were followed up until 2017, death, emigration or date of first psychiatric diagnosis. The median follow-up time was 29.99 years, corresponding to 10 277 547 person-years at risk. The cumulative incidence of psychiatric diagnoses at 30 years of follow-up was 59.5 (95% CI: 57.4 to 61.6) per 1000 women in the ineligible group and 57.5 (95% CI: 55.6 to 59.4) in the eligible group. Eligible women took on average 32.85 additional days of parental leave (95% CI: 29.20 to 36.49) and had a lower probability of having a psychiatric diagnosis within 5 years [risk difference (RD): 2.4 fewer diagnoses per 1000 women, 95% CI: 1.5 to 3.2] and up to 20 years after the birth (RD: 2.3, 95% CI: 0.4 to 4.2). In subgroup analyses, the risk reduction was concentrated among low-educated, low-income and single women. Conclusions: Longer parental leave may confer mental health benefits to women, in particular to those from disadvantaged backgrounds.

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