Search

Your search keyword '"Kopasker, Daniel"' showing total 39 results
Start Over Author "Kopasker, Daniel"
39 results on '"Kopasker, Daniel"'

2. Incidence of diabetes after SARS-CoV-2 infection in England and the implications of COVID-19 vaccination: a retrospective cohort study of 16 million people

Author

Al Arab, Marwa, Almaghrabi, Fatima, Andrews, Colm, Badrick, Ellena, Baz, Sarah, Beckford, Chelsea, Berman, Samantha, Bolton, Tom, Booth, Charlotte, Bowyer, Ruth, Boyd, Andy, Bridger-Staatz, Charis, Brophy, Sinead, Campbell, Archie, Campbell, Kirsteen C, Carnemolla, Alisia, Carpentieri, Jd, Cezard, Genevieve, Chaturvedi, Nishi, Cheetham, Nathan, Costello, Ruth, Cowling, Thomas, Crane, Matthew, Cuitun Coronado, Jose Ignacio, Curtis, Helen, Denaxas, Spiros, Denholm, Rachel, Di Gessa, Giorgio, Dobson, Richard, Douglas, Ian, Evans, Katharine M, Fang, Chao, Ferreira, Vanessa, Finnigan, Lucy, Fisher, Louis, Flaig, Robin, Folarin, Amos, Forbes, Harriet, Foster, Diane, Fox, Laura, Freydin, Maxim, Garcia, Paz, Gibson, Andy, Glen, Fiona, Goldacre, Ben, Goncalves Soares, Ana, Greaves, Felix, Green, Amelia, Green, Mark, Green, Michael, Griffith, Gareth, Hamill Howes, Lee, Hamilton, Olivia, Herbet, Annie, Herrett, Emily, Hopcroft, Lisa, Horne, Elsie, Hou, Bo, Hughes, Alun, Hulme, William, Huntley, Lizzie, Ip, Samantha, Jacques, Wels, Jezzard, Peter, Jones, Louise, Kanagaratnam, Arun, Karthikeyan Suseeladevi, Arun, Katikireddi, Vittal, Kellas, John, Kennedy, Jonathan I, Kibble, Milla, Knight, Rochelle, Knueppel, Anika, Kopasker, Daniel, Kromydas, Theocharis, Kwong, Alex, Langan, Sinead, Lemanska, Agnieszka, Lukaschuk, Elena, Mackenna, Brain, Macleod, John, Maddock, Jane, Mahalingasivam, Viyaasan, Mansfield, Kathryn, McArdle, Fintan, McCartney, Daniel, McEachan, Rosie, McElroy, Eoin, McLachlan, Stela, Mitchell, Ruth, Moltrecht, Bettina, Morley, Jess, Nab, Linda, Neubauer, Stefan, Nigrelli, Lidia, North, Teri, Northstone, Kate, Oakley, Jacqui, Palmer, Tom, Park, Chloe, Parker, Michael, Parsons, Sam, Patalay, Praveetha, Patel, Kishan, Perez-Reche, Francisco, Piechnik, Stefan, Piehlmaier, Dominik, Ploubidis, George, Rafeti, Elena, Raman, Betty, Ranjan, Yatharth, Rapala, Alicja, Rhead, Rebecca, Roberts, Amy, Sampri, Alexia, Sanders, Zeena-Britt, Santorelli, Gillian, Saunders, Laura C, Shah, Anoop, Shah, Syed Ahmar, Sharp, Steve, Shaw, Richard, Sheard, Laura, Sheikh, Aziz, Silverwood, Richard, Smeeth, Liam, Smith, Stephen, Stafford, Jean, Steptoe, Andrew, Sterne, Jonathan, Steves, Claire, Stewart, Callum, Taylor, Kurt, Tazare, John, Teece, Lucy, Thomas, Richard, Thompson, Ellen, Tilling, Kate, Timpson, Nicholas, Tomlinson, Laurie, Toms, Renin, Tunnicliffe, Elizabeth, Turner, Emma L, Walker, Alex, Walker, Venexia, Walter, Scott, Wang, Kevin, Wei, Yinghui, Whitehorn, Rebecca, Wielgoszewska, Bozena, Wild, James M, Willan, Kathryn, Willans, Robert, Williams, Dylan, Wong, Andrew, Wood, Angela, Woodward, Hannah, Wright, John, Yang, Tiffany, Zaninotto, Paola, Zheng, Bang, Zhu, Jingmin, Eastwood, Sophie, Horne, Elsie M F, Massey, Jon, Hopcroft, Lisa E M, Cuitun Coronado, Jose, Davy, Simon, Dillingham, Iain, Morton, Caroline, and Sterne, Jonathan A C

Published
2024
Full Text
View/download PDF

4. Short-term impacts of Universal Basic Income on population mental health inequalities in the UK: A microsimulation modelling study

Author

Thomson, Rachel M., Kopasker, Daniel, Bronka, Patryk, Richiardi, Matteo, Khodygo, Vladimir, Baxter, Andrew J., Igelström, Erik, Pearce, Anna, Leyland, Alastair H., and Katikireddi, S. Vittal

Subjects
Mental health, Personal income, Employee benefits, Gender equality, Child care, Simulation methods, Mental illness, Employee benefits, Biological sciences
Abstract

Background Population mental health in the United Kingdom (UK) has deteriorated, alongside worsening socioeconomic conditions, over the last decade. Policies such as Universal Basic Income (UBI) have been suggested as an alternative economic approach to improve population mental health and reduce health inequalities. UBI may improve mental health (MH), but to our knowledge, no studies have trialled or modelled UBI in whole populations. We aimed to estimate the short-term effects of introducing UBI on mental health in the UK working-age population. Methods and findings Adults aged 25 to 64 years were simulated across a 4-year period from 2022 to 2026 with the SimPaths microsimulation model, which models the effects of UK tax/benefit policies on mental health via income, poverty, and employment transitions. Data from the nationally representative UK Household Longitudinal Study were used to generate the simulated population (n = 25,000) and causal effect estimates. Three counterfactual UBI scenarios were modelled from 2023: 'Partial' (value equivalent to existing benefits), 'Full' (equivalent to the UK Minimum Income Standard), and 'Full+' (retaining means-tested benefits for disability, housing, and childcare). Likely common mental disorder (CMD) was measured using the General Health Questionnaire (GHQ-12, score [greater than or equal to]4). Relative and slope indices of inequality were calculated, and outcomes stratified by gender, age, education, and household structure. Simulations were run 1,000 times to generate 95% uncertainty intervals (UIs). Sensitivity analyses relaxed SimPaths assumptions about reduced employment resulting from Full/Full+ UBI. Partial UBI had little impact on poverty, employment, or mental health. Full UBI scenarios practically eradicated poverty but decreased employment (for Full+ from 78.9% [95% UI 77.9, 79.9] to 74.1% [95% UI 72.6, 75.4]). Full+ UBI increased absolute CMD prevalence by 0.38% (percentage points; 95% UI 0.13, 0.69) in 2023, equivalent to 157,951 additional CMD cases (95% UI 54,036, 286,805); effects were largest for men (0.63% [95% UI 0.31, 1.01]) and those with children (0.64% [95% UI 0.18, 1.14]). In our sensitivity analysis assuming minimal UBI-related employment impacts, CMD prevalence instead fell by 0.27% (95% UI -0.49, -0.05), a reduction of 112,228 cases (95% UI 20,783, 203,673); effects were largest for women (-0.32% [95% UI -0.65, 0.00]), those without children (-0.40% [95% UI -0.68, -0.15]), and those with least education (-0.42% [95% UI -0.97, 0.15]). There was no effect on educational mental health inequalities in any scenario, and effects waned by 2026. The main limitations of our methods are the model's short time horizon and focus on pathways from UBI to mental health solely via income, poverty, and employment, as well as the inability to integrate macroeconomic consequences of UBI; future iterations of the model will address these limitations. Conclusions UBI has potential to improve short-term population mental health by reducing poverty, particularly for women, but impacts are highly dependent on whether individuals choose to remain in employment following its introduction. Future research modelling additional causal pathways between UBI and mental health would be beneficial., Author(s): Rachel M. Thomson 1,*, Daniel Kopasker 1, Patryk Bronka 2, Matteo Richiardi 2, Vladimir Khodygo 1, Andrew J. Baxter 1, Erik Igelström 1, Anna Pearce 1, Alastair H. Leyland [...]

Published
2024
Full Text
View/download PDF

5. Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform

Author

Chaturvedi, Nishi, Park, Chloe, Carnemolla, Alisia, Williams, Dylan, Knueppel, Anika, Boyd, Andy, Turner, Emma L., Evans, Katharine M., Thomas, Richard, Berman, Samantha, McLachlan, Stela, Crane, Matthew, Whitehorn, Rebecca, Oakley, Jacqui, Foster, Diane, Woodward, Hannah, Campbell, Kirsteen C., Timpson, Nicholas, Kwong, Alex, Soares, Ana Goncalves, Griffith, Gareth, Toms, Renin, Jones, Louise, Annie, Herbert, Mitchell, Ruth, Palmer, Tom, Sterne, Jonathan, Walker, Venexia, Huntley, Lizzie, Fox, Laura, Denholm, Rachel, Knight, Rochelle, Northstone, Kate, Kanagaratnam, Arun, Horne, Elsie, Forbes, Harriet, North, Teri, Taylor, Kurt, Arab, Marwa A.L., Walker, Scott, Coronado, Jose I.C., Karthikeyan, Arun S., Ploubidis, George, Moltrecht, Bettina, Booth, Charlotte, Parsons, Sam, Wielgoszewska, Bozena, Bridger-Staatz, Charis, Steves, Claire, Thompson, Ellen, Garcia, Paz, Cheetham, Nathan, Bowyer, Ruth, Freydin, Maxim, Roberts, Amy, Goldacre, Ben, Walker, Alex, Morley, Jess, Hulme, William, Nab, Linda, Fisher, Louis, MacKenna, Brian, Andrews, Colm, Curtis, Helen, Hopcroft, Lisa, Green, Amelia, Patalay, Praveetha, Maddock, Jane, Patel, Kishan, Stafford, Jean, Jacques, Wels, Tilling, Kate, Macleod, John, McElroy, Eoin, Shah, Anoop, Silverwood, Richard, Denaxas, Spiros, Flaig, Robin, McCartney, Daniel, Campbell, Archie, Tomlinson, Laurie, Tazare, John, Zheng, Bang, Smeeth, Liam, Herrett, Emily, Cowling, Thomas, Mansfield, Kate, Costello, Ruth E., Wang, Kevin, Mansfield, Kathryn, Mahalingasivam, Viyaasan, Douglas, Ian, Langan, Sinead, Brophy, Sinead, Parker, Michael, Kennedy, Jonathan, McEachan, Rosie, Wright, John, Willan, Kathryn, Badrick, Ellena, Santorelli, Gillian, Yang, Tiffany, Hou, Bo, Steptoe, Andrew, Giorgio, Di Gessa, Zhu, Jingmin, Zaninotto, Paola, Wood, Angela, Cezard, Genevieve, Ip, Samantha, Bolton, Tom, Sampri, Alexia, Rafeti, Elena, Almaghrabi, Fatima, Sheikh, Aziz, Shah, Syed A., Katikireddi, Vittal, Shaw, Richard, Hamilton, Olivia, Green, Michael, Kromydas, Theocharis, Kopasker, Daniel, Greaves, Felix, Willans, Robert, Glen, Fiona, Sharp, Steve, Hughes, Alun, Wong, Andrew, Howes, Lee Hamill, Rapala, Alicja, Nigrelli, Lidia, McArdle, Fintan, Beckford, Chelsea, Raman, Betty, Dobson, Richard, Folarin, Amos, Stewart, Callum, Ranjan, Yatharth, Carpentieri, Jd, Sheard, Laura, Fang, Chao, Baz, Sarah, Gibson, Andy, Kellas, John, Neubauer, Stefan, Piechnik, Stefan, Lukaschuk, Elena, Saunders, Laura C., Wild, James M., Smith, Stephen, Jezzard, Peter, Tunnicliffe, Elizabeth, Sanders, Zeena-Britt, Finnigan, Lucy, Ferreira, Vanessa, Green, Mark, Rhead, Rebecca, Kibble, Milla, Wei, Yinghui, Lemanska, Agnieszka, Perez-Reche, Francisco, Piehlmaier, Dominik, Teece, Lucy, Parker, Edward, Walker, Alex J., Inglesby, Peter, Curtis, Helen J., Morton, Caroline E., Morley, Jessica, Mehrkar, Amir, Bacon, Sebastian C.J., Hickman, George, Croker, Richard, Evans, David, Ward, Tom, DeVito, Nicholas J., Green, Amelia C.A., Massey, Jon, Smith, Rebecca M., Hulme, William J., Davy, Simon, Andrews, Colm D., Hopcroft, Lisa E.M., Drysdale, Henry, Dillingham, Iain, Park, Robin Y., Higgins, Rose, Cunningham, Christine, Wiedemann, Milan, Maude, Steven, Macdonald, Orla, Butler-Cole, Ben F.C., O'Dwyer, Thomas, Stables, Catherine L., Wood, Christopher, Brown, Andrew D., Speed, Victoria, Bridges, Lucy, Schaffer, Andrea L., Walters, Caroline E., Rentsch, Christopher T., Bhaskaran, Krishnan, Schultze, Anna, Williamson, Elizabeth J., McDonald, Helen I., Tomlinson, Laurie A., Mathur, Rohini, Eggo, Rosalind M., Wing, Kevin, Wong, Angel Y.S., Grieve, Richard, Grint, Daniel J., Mansfield, Kathryn E., Douglas, Ian J., Evans, Stephen J.W., Walker, Jemma L., Cowling, Thomas E., Herrett, Emily L., Parker, Edward P.K., Bates, Christopher, Cockburn, Jonathan, Parry, John, Hester, Frank, Harper, Sam, O'Hanlon, Shaun, Eavis, Alex, Jarvis, Richard, Avramov, Dima, Griffiths, Paul, Fowles, Aaron, Parkes, Nasreen, Nicholson, Brian, Perera, Rafael, Harrison, David, Khunti, Kamlesh, Sterne, Jonathan AC., Quint, Jennifer, Henderson, Alasdair D., Carreira, Helena, Bidulka, Patrick, Warren-Gash, Charlotte, Hayes, Joseph F., Quint, Jennifer K., Katikireddi, Srinivasa Vittal, and Langan, Sinéad M.

Published
2023
Full Text
View/download PDF

7. Home working and social and mental wellbeing at different stages of the COVID-19 pandemic in the UK: Evidence from 7 longitudinal population surveys

Author

Wels, Jacques, Wielgoszewska, Bozena, Moltrecht, Bettina, Booth, Charlotte, Green, Michael J., Hamilton, Olivia KL, Demou, Evangelia, Di Gessa, Giorgio, Huggins, Charlotte, Zhu, Jingmin, Santorelli, Gillian, Silverwood, Richard J., Kopasker, Daniel, Shaw, Richard J., Hughes, Alun, Patalay, Praveetha, Steves, Claire, Chaturvedi, Nishi, Porteous, David J., Rhead, Rebecca, Katikireddi, Srinivasa Vittal, and Ploubidis, George B.

Subjects
Biological sciences
Abstract

Background Home working has increased since the Coronavirus Disease 2019 (COVID-19) pandemic's onset with concerns that it may have adverse health implications. We assessed the association between home working and social and mental wellbeing among the employed population aged 16 to 66 through harmonised analyses of 7 UK longitudinal studies. Methods and findings We estimated associations between home working and measures of psychological distress, low life satisfaction, poor self-rated health, low social contact, and loneliness across 3 different stages of the pandemic (T1 = April to June 2020 -first lockdown, T2 = July to October 2020 -eased restrictions, T3 = November 2020 to March 2021 -second lockdown) using modified Poisson regression and meta-analyses to pool results across studies. We successively adjusted the model for sociodemographic characteristics (e.g., age, sex), job characteristics (e.g., sector of activity, pre-pandemic home working propensities), and pre-pandemic health. Among respectively 10,367, 11,585, and 12,179 participants at T1, T2, and T3, we found higher rates of home working at T1 and T3 compared with T2, reflecting lockdown periods. Home working was not associated with psychological distress at T1 (RR = 0.92, 95% CI = 0.79 to 1.08) or T2 (RR = 0.99, 95% CI = 0.88 to 1.11), but a detrimental association was found with psychological distress at T3 (RR = 1.17, 95% CI = 1.05 to 1.30). Study limitations include the fact that pre-pandemic home working propensities were derived from external sources, no information was collected on home working dosage and possible reverse association between change in wellbeing and home working likelihood. Conclusions No clear evidence of an association between home working and mental wellbeing was found, apart from greater risk of psychological distress during the second lockdown, but differences across subgroups (e.g., by sex or level of education) may exist. Longer term shifts to home working might not have adverse impacts on population wellbeing in the absence of pandemic restrictions but further monitoring of health inequalities is required., Author(s): Jacques Wels 1,2,*, Bozena Wielgoszewska 3, Bettina Moltrecht 3, Charlotte Booth 3, Michael J. Green 4, Olivia KL Hamilton 4, Evangelia Demou 4, Giorgio Di Gessa 5, Charlotte Huggins [...]

Published
2023
Full Text
View/download PDF

11. The effects of economic insecurity on health and wellbeing

Author

Kopasker, Daniel

Subjects
338.4, Economic security, Security (Psychology), Health, Well-being
Abstract

This thesis examines the relationship between concerns regarding future economic misfortune and psychological wellbeing. Economic concerns are often highlighted as a source of distress within populations. The health outcomes resulting from this distress are likely to have economic impacts associated with lost productivity, and the cost of health and social care. The future orientated and subjective nature of this economic insecurity leads to these negative effects being potentially hidden. Through empirical analysis of longitudinal data from the UK, this thesis examines (i) trends in economic insecurity and assesses the potential for more objective measurement, (ii) how the likelihood of experiencing economic insecurity is related to the characteristics of employment relationships, and (iii) estimates the magnitude of the causal effect of economic insecurity on psychological wellbeing. The analysis suggests that despite broadly downward trends of economic insecurity in Great Britain, around one in ten of the working-age population are affected in any single year. Economic insecurity related to work appears to affect the largest proportion of the population. The likelihood of experiencing this form of insecurity is higher amongst temporary employees, those employed within industries that face international competition, and increases with firm tenure. Furthermore, this form of insecurity is shown to negatively impact on mental health, particularly amongst males. These findings have implications for both productivity and population health. The analysis lays a foundation for cross-country analysis of how labour market institutions, employer characteristics, and management practices limit the negative impact of economic insecurity on health and wellbeing.

Published
2017

12. Incidence of diabetes after SARS-CoV-2 infection in England and the implications of COVID-19 vaccination: a retrospective cohort study of 16 million people

Author

Taylor, Kurt, Eastwood, Sophie, Walker, Venexia, Cezard, Genevieve, Knight, Rochelle, Al Arab, Marwa, Wei, Yinghui, Horne, Elsie M F, Teece, Lucy, Forbes, Harriet, Walker, Alex, Fisher, Louis, Massey, Jon, Hopcroft, Lisa E M, Palmer, Tom, Cuitun Coronado, Jose, Ip, Samantha, Davy, Simon, Dillingham, Iain, Morton, Caroline, Greaves, Felix, Macleod, John, Goldacre, Ben, Wood, Angela, Chaturvedi, Nishi, Sterne, Jonathan A C, Denholm, Rachel, Al Arab, Marwa, Almaghrabi, Fatima, Andrews, Colm, Badrick, Ellena, Baz, Sarah, Beckford, Chelsea, Berman, Samantha, Bolton, Tom, Booth, Charlotte, Bowyer, Ruth, Boyd, Andy, Bridger-Staatz, Charis, Brophy, Sinead, Campbell, Archie, Campbell, Kirsteen C, Carnemolla, Alisia, Carpentieri, Jd, Cezard, Genevieve, Chaturvedi, Nishi, Cheetham, Nathan, Costello, Ruth, Cowling, Thomas, Crane, Matthew, Cuitun Coronado, Jose Ignacio, Curtis, Helen, Denaxas, Spiros, Denholm, Rachel, Di Gessa, Giorgio, Dobson, Richard, Douglas, Ian, Evans, Katharine M, Fang, Chao, Ferreira, Vanessa, Finnigan, Lucy, Fisher, Louis, Flaig, Robin, Folarin, Amos, Forbes, Harriet, Foster, Diane, Fox, Laura, Freydin, Maxim, Garcia, Paz, Gibson, Andy, Glen, Fiona, Goldacre, Ben, Goncalves Soares, Ana, Greaves, Felix, Green, Amelia, Green, Mark, Green, Michael, Griffith, Gareth, Hamill Howes, Lee, Hamilton, Olivia, Herbet, Annie, Herrett, Emily, Hopcroft, Lisa, Horne, Elsie, Hou, Bo, Hughes, Alun, Hulme, William, Huntley, Lizzie, Ip, Samantha, Jacques, Wels, Jezzard, Peter, Jones, Louise, Kanagaratnam, Arun, Karthikeyan Suseeladevi, Arun, Katikireddi, Vittal, Kellas, John, Kennedy, Jonathan I, Kibble, Milla, Knight, Rochelle, Knueppel, Anika, Kopasker, Daniel, Kromydas, Theocharis, Kwong, Alex, Langan, Sinead, Lemanska, Agnieszka, Lukaschuk, Elena, Mackenna, Brain, Macleod, John, Maddock, Jane, Mahalingasivam, Viyaasan, Mansfield, Kathryn, McArdle, Fintan, McCartney, Daniel, McEachan, Rosie, McElroy, Eoin, McLachlan, Stela, Mitchell, Ruth, Moltrecht, Bettina, Morley, Jess, Nab, Linda, Neubauer, Stefan, Nigrelli, Lidia, North, Teri, Northstone, Kate, Oakley, Jacqui, Palmer, Tom, Park, Chloe, Parker, Michael, Parsons, Sam, Patalay, Praveetha, Patel, Kishan, Perez-Reche, Francisco, Piechnik, Stefan, Piehlmaier, Dominik, Ploubidis, George, Rafeti, Elena, Raman, Betty, Ranjan, Yatharth, Rapala, Alicja, Rhead, Rebecca, Roberts, Amy, Sampri, Alexia, Sanders, Zeena-Britt, Santorelli, Gillian, Saunders, Laura C, Shah, Anoop, Shah, Syed Ahmar, Sharp, Steve, Shaw, Richard, Sheard, Laura, Sheikh, Aziz, Silverwood, Richard, Smeeth, Liam, Smith, Stephen, Stafford, Jean, Steptoe, Andrew, Sterne, Jonathan, Steves, Claire, Stewart, Callum, Taylor, Kurt, Tazare, John, Teece, Lucy, Thomas, Richard, Thompson, Ellen, Tilling, Kate, Timpson, Nicholas, Tomlinson, Laurie, Toms, Renin, Tunnicliffe, Elizabeth, Turner, Emma L, Walker, Alex, Walker, Venexia, Walter, Scott, Wang, Kevin, Wei, Yinghui, Whitehorn, Rebecca, Wielgoszewska, Bozena, Wild, James M, Willan, Kathryn, Willans, Robert, Williams, Dylan, Wong, Andrew, Wood, Angela, Woodward, Hannah, Wright, John, Yang, Tiffany, Zaninotto, Paola, Zheng, Bang, and Zhu, Jingmin

Abstract

Some studies have shown that the incidence of type 2 diabetes increases after a diagnosis of COVID-19, although the evidence is not conclusive. However, the effects of the COVID-19 vaccine on this association, or the effect on other diabetes subtypes, are not clear. We aimed to investigate the association between COVID-19 and incidence of type 2, type 1, gestational and non-specific diabetes, and the effect of COVID- 19 vaccination, up to 52 weeks after diagnosis.

Published
2024
Full Text
View/download PDF

15. Microsimulation as a flexible tool to evaluate policies and their impact on socioeconomic inequalities in health

Author

Kopasker, Daniel, primary, Katikireddi, Srinivasa Vittal, additional, Santos, João Vasco, additional, Richiardi, Matteo, additional, Bronka, Patryk, additional, Rostila, Mikael, additional, Cecchini, Michele, additional, Ali, Shehzad, additional, Emmert-Fees, Karl, additional, Bambra, Clare, additional, Hoven, Hanno, additional, Backhaus, Insa, additional, Balaj, Mirza, additional, and Eikemo, Terje Andreas, additional

Published
2023
Full Text
View/download PDF

18. Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform

Author

Costello, Ruth E., primary, Tazare, John, additional, Piehlmaier, Dominik, additional, Herrett, Emily, additional, Parker, Edward P.K., additional, Zheng, Bang, additional, Mansfield, Kathryn E., additional, Henderson, Alasdair D., additional, Carreira, Helena, additional, Bidulka, Patrick, additional, Wong, Angel Y.S., additional, Warren-Gash, Charlotte, additional, Hayes, Joseph F., additional, Quint, Jennifer K., additional, MacKenna, Brian, additional, Mehrkar, Amir, additional, Eggo, Rosalind M., additional, Katikireddi, Srinivasa Vittal, additional, Tomlinson, Laurie, additional, Langan, Sinéad M., additional, Mathur, Rohini, additional, Chaturvedi, Nishi, additional, Park, Chloe, additional, Carnemolla, Alisia, additional, Williams, Dylan, additional, Knueppel, Anika, additional, Boyd, Andy, additional, Turner, Emma L., additional, Evans, Katharine M., additional, Thomas, Richard, additional, Berman, Samantha, additional, McLachlan, Stela, additional, Crane, Matthew, additional, Whitehorn, Rebecca, additional, Oakley, Jacqui, additional, Foster, Diane, additional, Woodward, Hannah, additional, Campbell, Kirsteen C., additional, Timpson, Nicholas, additional, Kwong, Alex, additional, Soares, Ana Goncalves, additional, Griffith, Gareth, additional, Toms, Renin, additional, Jones, Louise, additional, Annie, Herbert, additional, Mitchell, Ruth, additional, Palmer, Tom, additional, Sterne, Jonathan, additional, Walker, Venexia, additional, Huntley, Lizzie, additional, Fox, Laura, additional, Denholm, Rachel, additional, Knight, Rochelle, additional, Northstone, Kate, additional, Kanagaratnam, Arun, additional, Horne, Elsie, additional, Forbes, Harriet, additional, North, Teri, additional, Taylor, Kurt, additional, Arab, Marwa A.L., additional, Walker, Scott, additional, Coronado, Jose I.C., additional, Karthikeyan, Arun S., additional, Ploubidis, George, additional, Moltrecht, Bettina, additional, Booth, Charlotte, additional, Parsons, Sam, additional, Wielgoszewska, Bozena, additional, Bridger-Staatz, Charis, additional, Steves, Claire, additional, Thompson, Ellen, additional, Garcia, Paz, additional, Cheetham, Nathan, additional, Bowyer, Ruth, additional, Freydin, Maxim, additional, Roberts, Amy, additional, Goldacre, Ben, additional, Walker, Alex, additional, Morley, Jess, additional, Hulme, William, additional, Nab, Linda, additional, Fisher, Louis, additional, Andrews, Colm, additional, Curtis, Helen, additional, Hopcroft, Lisa, additional, Green, Amelia, additional, Patalay, Praveetha, additional, Maddock, Jane, additional, Patel, Kishan, additional, Stafford, Jean, additional, Jacques, Wels, additional, Tilling, Kate, additional, Macleod, John, additional, McElroy, Eoin, additional, Shah, Anoop, additional, Silverwood, Richard, additional, Denaxas, Spiros, additional, Flaig, Robin, additional, McCartney, Daniel, additional, Campbell, Archie, additional, Smeeth, Liam, additional, Cowling, Thomas, additional, Mansfield, Kate, additional, Costello, Ruth E., additional, Wang, Kevin, additional, Mansfield, Kathryn, additional, Mahalingasivam, Viyaasan, additional, Douglas, Ian, additional, Langan, Sinead, additional, Brophy, Sinead, additional, Parker, Michael, additional, Kennedy, Jonathan, additional, McEachan, Rosie, additional, Wright, John, additional, Willan, Kathryn, additional, Badrick, Ellena, additional, Santorelli, Gillian, additional, Yang, Tiffany, additional, Hou, Bo, additional, Steptoe, Andrew, additional, Giorgio, Di Gessa, additional, Zhu, Jingmin, additional, Zaninotto, Paola, additional, Wood, Angela, additional, Cezard, Genevieve, additional, Ip, Samantha, additional, Bolton, Tom, additional, Sampri, Alexia, additional, Rafeti, Elena, additional, Almaghrabi, Fatima, additional, Sheikh, Aziz, additional, Shah, Syed A., additional, Katikireddi, Vittal, additional, Shaw, Richard, additional, Hamilton, Olivia, additional, Green, Michael, additional, Kromydas, Theocharis, additional, Kopasker, Daniel, additional, Greaves, Felix, additional, Willans, Robert, additional, Glen, Fiona, additional, Sharp, Steve, additional, Hughes, Alun, additional, Wong, Andrew, additional, Howes, Lee Hamill, additional, Rapala, Alicja, additional, Nigrelli, Lidia, additional, McArdle, Fintan, additional, Beckford, Chelsea, additional, Raman, Betty, additional, Dobson, Richard, additional, Folarin, Amos, additional, Stewart, Callum, additional, Ranjan, Yatharth, additional, Carpentieri, Jd, additional, Sheard, Laura, additional, Fang, Chao, additional, Baz, Sarah, additional, Gibson, Andy, additional, Kellas, John, additional, Neubauer, Stefan, additional, Piechnik, Stefan, additional, Lukaschuk, Elena, additional, Saunders, Laura C., additional, Wild, James M., additional, Smith, Stephen, additional, Jezzard, Peter, additional, Tunnicliffe, Elizabeth, additional, Sanders, Zeena-Britt, additional, Finnigan, Lucy, additional, Ferreira, Vanessa, additional, Green, Mark, additional, Rhead, Rebecca, additional, Kibble, Milla, additional, Wei, Yinghui, additional, Lemanska, Agnieszka, additional, Perez-Reche, Francisco, additional, Teece, Lucy, additional, Parker, Edward, additional, Walker, Alex J., additional, Inglesby, Peter, additional, Curtis, Helen J., additional, Morton, Caroline E., additional, Morley, Jessica, additional, Bacon, Sebastian C.J., additional, Hickman, George, additional, Croker, Richard, additional, Evans, David, additional, Ward, Tom, additional, DeVito, Nicholas J., additional, Green, Amelia C.A., additional, Massey, Jon, additional, Smith, Rebecca M., additional, Hulme, William J., additional, Davy, Simon, additional, Andrews, Colm D., additional, Hopcroft, Lisa E.M., additional, Drysdale, Henry, additional, Dillingham, Iain, additional, Park, Robin Y., additional, Higgins, Rose, additional, Cunningham, Christine, additional, Wiedemann, Milan, additional, Maude, Steven, additional, Macdonald, Orla, additional, Butler-Cole, Ben F.C., additional, O'Dwyer, Thomas, additional, Stables, Catherine L., additional, Wood, Christopher, additional, Brown, Andrew D., additional, Speed, Victoria, additional, Bridges, Lucy, additional, Schaffer, Andrea L., additional, Walters, Caroline E., additional, Rentsch, Christopher T., additional, Bhaskaran, Krishnan, additional, Schultze, Anna, additional, Williamson, Elizabeth J., additional, McDonald, Helen I., additional, Tomlinson, Laurie A., additional, Wing, Kevin, additional, Grieve, Richard, additional, Grint, Daniel J., additional, Douglas, Ian J., additional, Evans, Stephen J.W., additional, Walker, Jemma L., additional, Cowling, Thomas E., additional, Herrett, Emily L., additional, Bates, Christopher, additional, Cockburn, Jonathan, additional, Parry, John, additional, Hester, Frank, additional, Harper, Sam, additional, O'Hanlon, Shaun, additional, Eavis, Alex, additional, Jarvis, Richard, additional, Avramov, Dima, additional, Griffiths, Paul, additional, Fowles, Aaron, additional, Parkes, Nasreen, additional, Nicholson, Brian, additional, Perera, Rafael, additional, Harrison, David, additional, Khunti, Kamlesh, additional, Sterne, Jonathan AC., additional, and Quint, Jennifer, additional

Published
2023
Full Text
View/download PDF

20. Systems science methods in public health: what can they contribute to our understanding of and response to the cost-of-living crisis?

Author

Höhn, Andreas, primary, Stokes, Jonathan, additional, Pollack, Roxana, additional, Boyd, Jennifer, additional, Chueca Del Cerro, Cristina, additional, Elsenbroich, Corinna, additional, Heppenstall, Alison, additional, Hjelmskog, Annika, additional, Inyang, Elizabeth, additional, Kopasker, Daniel, additional, Sonthalia, Shreya, additional, Thomson, Rachel M, additional, Zia, Kashif, additional, Katikireddi, Srinivasa Vittal, additional, and Meier, Petra, additional

Published
2023
Full Text
View/download PDF

21. To what extent does income explain the effect of unemployment on mental health? Mediation analysis in the UK Household Longitudinal Study.

Author

Thomson, Rachel M., Kopasker, Daniel, Leyland, Alastair, Pearce, Anna, and Katikireddi, S. Vittal

Subjects
*UNEMPLOYMENT, *ECONOMIC status, *MENTAL health, *FACTOR analysis, *QUESTIONNAIRES, *DESCRIPTIVE statistics, *DISEASE prevalence, *ODDS ratio, *POVERTY, *LONGITUDINAL method
Abstract

Background: Employment and income are important determinants of mental health (MH), but the extent that unemployment effects are mediated by reduced income is unclear. We estimated the total effect (TE) of unemployment on MH and the controlled direct effect (CDE) not acting via income. Methods: We included adults 25–64 years from nine waves of the UK Household Longitudinal Study (n = 45 497/ obs = 202 297). Unemployment was defined as not being in paid employment; common mental disorder (CMD) was defined as General Health Questionnaire-12 score ≥4. We conducted causal mediation analysis using double-robust marginal structural modelling, estimating odds ratios (OR) and absolute differences for effects of unemployment on CMD in the same year, before (TE) and after (CDE) blocking the income pathway. We calculated percentage mediation by income, with bootstrapped standard errors. Results: The TE of unemployment on CMD risk was OR 1.66 (95% CI 1.57–1.76), with 7.09% (6.21–7.97) absolute difference in prevalence; equivalent CDEs were OR 1.55 (1.46–1.66) and 6.08% (5.13–7.03). Income mediated 14.22% (8.04–20.40) of the TE. Percentage mediation was higher for job losses [15.10% (6.81–23.39)] than gains [8.77% (0.36–17.19)]; it was lowest for those 25–40 years [7.99% (−2.57 to 18.51)] and in poverty [2.63% (−2.22 to 7.49)]. Conclusions: A high proportion of the short-term effect of unemployment on MH is not explained by income, particularly for younger people and those in poverty. Population attributable fractions suggested 16.49% of CMD burden was due to unemployment, with 13.90% directly attributable to job loss rather than resultant income changes. Similar analytical approaches could explore how this differs across contexts, by other factors, and consider longer-term effects. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

26. Home working and its association with social and mental wellbeing at different stages of the COVID-19 pandemic: Evidence from seven UK longitudinal population surveys

Author

Wels, Jacques, primary, Wielgoszewska, Bożena, additional, Moltrecht, Bettina, additional, Booth, Charlotte, additional, Green, Michael J, additional, Hamilton, Olivia KL, additional, Demou, Evangelia, additional, Gessa, Giorgio Di, additional, Huggins, Charlotte, additional, Zhu, Jingmin, additional, Santorelli, Gillian, additional, Silverwood, Richard J., additional, Kopasker, Daniel, additional, Shaw, Richard J., additional, Hughes, Alun, additional, Patalay, Praveetha, additional, Steves, Claire, additional, Chaturvedi, Nish, additional, Porteous, David, additional, Rhead, Rebecca, additional, Katikireddi, Srinivasa Vittal, additional, and Ploubidis, George B., additional

Published
2022
Full Text
View/download PDF

28. Effects of poverty on mental health in the UK working-age population: causal analyses of the UK Household Longitudinal Study.

Author

Thomson, Rachel M, Kopasker, Daniel, Leyland, Alastair, Pearce, Anna, and Katikireddi, S Vittal

Subjects
*STATISTICAL models, *MENTAL health, *INCOME, *POVERTY, *LONGITUDINAL method, *ODDS ratio
Abstract

Background Addressing poverty through taxation or welfare policies is likely important for public mental health; however, few studies assess poverty's effects using causal epidemiology. We estimated the effect of poverty on mental health. Methods We used data on working-age adults (25–64 years) from nine waves of the UK Household Longitudinal Survey (2009–19; n  = 45 497/observations = 202 207 following multiple imputation). We defined poverty as a household equivalized income <60% median, and the outcome likely common mental disorder (CMD) as a General Health Questionnaire-12 score ≥4. We used double-robust marginal structural modelling with inverse probability of treatment weights to generate absolute and relative effects. Supplementary analyses separated transitions into/out of poverty, and stratified by gender, education, and age. We quantified potential impact through population attributable fractions (PAFs) with bootstrapped standard errors. Results Good balance of confounders was achieved between exposure groups, with 45 830 observations (22.65%) reporting poverty. The absolute effect of poverty on CMD prevalence was 2.15% [%-point change; 95% confidence interval (CI) 1.45, 2.84]; prevalence in those unexposed was 20.59% (95% CI 20.29%, 20.88%), and the odds ratio was 1.17 (95% CI 1.12, 1.24). There was a larger absolute effect for transitions into poverty [2.46% (95% CI 1.56, 3.36)] than transitions out of poverty [–1.49% (95% CI –2.46, –0.53)]. Effects were also slightly larger in women than men [2.34% (95% CI 1.41, 3.26) versus 1.73% (95% CI 0.72, 2.74)]. The PAF for moving into poverty was 6.34% (95% CI 4.23, 8.45). Conclusions PAFs derived from our causal estimates suggest moves into poverty account for just over 6% of the burden of CMD in the UK working-age population, with larger effects in women. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

30. The effects of minimum unit pricing for alcohol on food purchases: Evaluation of a natural experiment

Author

Kopasker, Daniel, Whybrow, Stephen, McKenzie, Lynda, McNamee, Paul, and Ludbrook, Anne

Subjects
Health (social science), Health Policy, Public Health, Environmental and Occupational Health
Abstract

Background: \ud On the 1st of May 2018 Scotland became the first country to introduce minimum unit pricing (MUP) for alcohol sales. The objective of this study is to identify the effects of this policy instrument on food purchasing by evaluating a natural experiment.\ud \ud Methods: \ud Longitudinal analysis compares regions with similar characteristics but differing exposure to MUP (Scotland and the north of England). Secondary data from the Kantar Worldpanel on itemised purchases between April 2017 and April 2019 provided a total sample of 8051 households. The outcomes analysed are weekly household expenditure (£s) and purchase volume (grams), both overall and disaggregated to 16 product categories.\ud \ud Results: \ud Following the introduction of MUP, total household food expenditure in Scotland declined by 1.0%, 95%CI [-1.9%, −0.0%], and total food volume declined by 0.8%, 95%CI [-1.7%, 0.2%] compared to the north of England. There is variation in response between product categories, with less spending on fruit and vegetables and increased spending on crisps and snacks.\ud \ud Conclusion: \ud Minimum unit pricing for alcohol has displaced some household food purchasing and the pattern of changes in food categories appears to be less desirable from a healthy diet perspective. However, changes caused by a minimum price at a nominal 50 pence per unit of alcohol are relatively small.

Published
2021

31. Systems science methods in public health: what can they contribute to our understanding of and response to the cost-of-living crisis?

Author

Ho¨hn, Andreas, Stokes, Jonathan, Pollack, Roxana, Boyd, Jennifer, Chueca Del Cerro, Cristina, Elsenbroich, Corinna, Heppenstall, Alison, Hjelmskog, Annika, Inyang, Elizabeth, Kopasker, Daniel, Sonthalia, Shreya, Thomson, Rachel M, Zia, Kashif, Katikireddi, Srinivasa Vittal, and Meier, Petra

Abstract

BackgroundMany complex public health evidence gaps cannot be fully resolved using only conventional public health methods. We aim to familiarise public health researchers with selected systems science methods that may contribute to a better understanding of complex phenomena and lead to more impactful interventions. As a case study, we choose the current cost-of-living crisis, which affects disposable income as a key structural determinant of health.MethodsWe first outline the potential role of systems science methods for public health research more generally, then provide an overview of the complexity of the cost-of-living crisis as a specific case study. We propose how four systems science methods (soft systems, microsimulation, agent-based and system dynamics models) could be applied to provide more in-depth understanding. For each method, we illustrate its unique knowledge contributions, and set out one or more options for studies that could help inform policy and practice responses.ResultsDue to its fundamental impact on the determinants of health, while limiting resources for population-level interventions, the cost-of-living crisis presents a complex public health challenge. When confronted with complexity, non-linearity, feedback loops and adaptation processes, systems methods allow a deeper understanding and forecasting of the interactions and spill-over effects common with real-world interventions and policies.ConclusionsSystems science methods provide a rich methodological toolbox that complements our traditional public health methods. This toolbox may be particularly useful in early stages of the current cost-of-living crisis: for understanding the situation, developing solutions and sandboxing potential responses to improve population health.

Published
2023
Full Text
View/download PDF

34. Firm size distribution and employment fluctuations: Theory and evidence

Author

Görg, Holger, Henze, Philipp, Jienwatcharamongkhol, Viroj, Kopasker, Daniel, Molana, Hassan, Montagna, Catia, and Sjöholm, Fredrik

Subjects
Employment, L20, ddc:330, Fluctuations, E23, E20, Firm distribution, Firm size
Abstract

This paper studies the effect of the firm-size distribution on the relationship between employment and output. We construct a theoretical model, which predicts that changes in demand for industry output have larger effects on employment in industries characterised by a distribution that is more skewed towards smaller firms. Industry-specific shape parameters of the firm size distributions are estimated using firm-level data from Germany, Sweden and the UK, and used to augment a relationship between industry-level employment and output. Our empirical results align with the predictions of the theory and confirm that the size distribution of firms is an important determinant of the relationship between changes in output and employment.

Published
2016

36. Negative Shocks, Job Creation, and Selection

Author

Kopasker, Daniel, Görg, Holger, Molana, Hassan, Montagna, Catia, and Kreickemeier, Udo

Subjects
competitive selection, international trade, Dewey-Dezimalklassifikation -- Sozialwissenschaften (3) -- Wirtschaft (33) -- Arbeitsökonomie (331), Dewey Decimal Classification -- Social sciences (3) -- Economics (33) -- Labor economics (331), Job creation, jel:E22, employment subsidies, jel:E64, jel:F41, Classificazione decimale Dewey -- Social sciences (3) -- Economics (33) -- Labor economics (331), Job creation, employment subsidies, competitive selection, international trade, jel:F12, Deweyev decimalni sistem klasifikacije -- Social sciences (3) -- Economics (33) -- Labor economics (331), European Projects -- FP7 (euprojects1) -- OpenAire (euprojects1.1) -- Socio-economic sciences and the humanities (euprojects1.1.7), ddc:330, E22, F12, E64, F41
Abstract

WWWforEurope Working Paper No. 11, 35 Pages High inter-country variability characterises the responsiveness of both output to (exogenous) shocks and employment to output contractions. We argue that intercountry differences in firm-size distributions contribute to explaining this variability. Within an open economy model, we show that competitive selection processes are an important channel through which a shock affects aggregate employment. Intra-industry selection is then shown to influence the effectiveness of active labour market policies in countering the employment and welfare effects of a negative shock. We estimate a measure of the shape parameter of firm size distribution and study its effect on the employment-output relationship for a number of OECD countries. Our results confirm the key predictions of the theory.

Published
2013

38. The Role of Threat and Economic Uncertainty in Support for Scottish Independence

Author

Kopasker, Daniel

Abstract

Existing research has consistently shown that perceptions of the potential economic consequences of Scottish independence are vital to levels of support for constitutional change. This paper attempts to investigate the mechanism by which expectations of the economic consequences of independence are formed. A hypothesised causal micro-level mechanism is tested that relates constitutional preferences to the existing skill investments of the individual. Evidence is presented that larger skill investments are associated with a greater likelihood of perceiving economic threats from independence. Additionally, greater perceived threat results in lower support for independence. The impact of uncertainty on both positive and negative economic expectations is also examined. While uncertainty has little effect on negative expectations, it significantly reduces the likelihood of those with positive expectations supporting independence. Overall, it appears that a general economy-wide threat is most significant, and it is conjectured that this stems a lack of information on macroeconomic governance credentials.

Published
1998
Full Text
View/download PDF

39. Health Equity and Its Economic Determinants (HEED): protocol for a pan-European microsimulation model for health impacts of income and social security policies

Author

Katikireddi, Srinivasa Vittal, Kopasker, Daniel, Pearce, Anna, Leyland, Alastair H., Rostila, Mikael, and Richiardi, Matteo

Subjects
General Medicine
Abstract

IntroductionGovernment policies on taxation and social security are important determinants of population health outcomes and health inequalities. However, there is a shortage of evidence to inform policymakers of the health consequences of such policies. The Health Equity and Its Economic Determinants project aims to assess the potential impacts of different taxation and social security policies across Europe on population health and health inequalities using a computer-based simulation that provides projections over multiple health domains.Methods and analysisIn the first phase, key input parameters for the model will be estimated using estimation techniques that control for the effects of prior exposure on time-varying confounders and mediators (g-methods). The second phase will involve developing and validating the microsimulation model for the UK. Policy proposals, developed with policymakers, will be simulated in the third phase to investigate the impacts of income tax and social security changes on population health and health inequalities. In the final phase, the microsimulation model will be extended across other European countries.Ethics and disseminationThis project will use deidentified secondary data for which ethical approval and consents were received by the original data collectors. No further ethical approval will be required for our main analytical datasets. Dissemination plans include academic publications, conference presentations, accessible policy briefings, mass media engagement and a project website. Both the syntax and the underlying synthetic data for the HEED microsimulation model will be made freely available through GitHub and the project website.

Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results