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2. 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
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4. Introduction

Author

Sinha, Ian P., primary, Lee, Alice, additional, Katikireddi, S. Vittal, additional, and Quint, Jennifer K., additional

Published
2023
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8. Psychological distress, depression, anxiety, and life satisfaction following COVID-19 infection: evidence from 11 UK longitudinal population studies

Author

Thompson, Ellen J, Stafford, Jean, Moltrecht, Bettina, Huggins, Charlotte F, Kwong, Alex S F, Shaw, Richard J, Zaninotto, Paola, Patel, Kishan, Silverwood, Richard J, McElroy, Eoin, Pierce, Matthias, Green, Michael J, Bowyer, Ruth C E, Maddock, Jane, Tilling, Kate, Katikireddi, S Vittal, Ploubidis, George B, Porteous, David J, Timpson, Nic, Chaturvedi, Nish, Steves, Claire J, and Patalay, Praveetha

Published
2022
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13. First-dose ChAdOx1 and BNT162b2 COVID-19 vaccines and thrombocytopenic, thromboembolic and hemorrhagic events in Scotland

Author

Simpson, C. R., Shi, T., Vasileiou, E., Katikireddi, S. V., Kerr, S., Moore, E., McCowan, C., Agrawal, U., Shah, S.A., Ritchie, L.D., Murray, J., Pan, J., Bradley, D.T., Stock, S.J., Wood, R., Chuter, A., and Beggs, J.

Subjects
Thromboembolism -- Risk factors, Hemorrhage -- Risk factors, Thrombocytopenia -- Risk factors, Biological sciences, Health
Abstract

Reports of ChAdOx1 vaccine-associated thrombocytopenia and vascular adverse events have led to some countries restricting its use. Using a national prospective cohort, we estimated associations between exposure to first-dose ChAdOx1 or BNT162b2 vaccination and hematological and vascular adverse events using a nested incident-matched case-control study and a confirmatory self-controlled case series (SCCS) analysis. An association was found between ChAdOx1 vaccination and idiopathic thrombocytopenic purpura (ITP) (0-27 d after vaccination; adjusted rate ratio (aRR) = 5.77, 95% confidence interval (CI), 2.41-13.83), with an estimated incidence of 1.13 (0.62-1.63) cases per 100,000 doses. An SCCS analysis confirmed that this was unlikely due to bias (RR = 1.98 (1.29-3.02)). There was also an increased risk for arterial thromboembolic events (aRR = 1.22, 1.12-1.34) 0-27 d after vaccination, with an SCCS RR of 0.97 (0.93-1.02). For hemorrhagic events 0-27 d after vaccination, the aRR was 1.48 (1.12-1.96), with an SCCS RR of 0.95 (0.82-1.11). A first dose of ChAdOx1 was found to be associated with small increased risks of ITP, with suggestive evidence of an increased risk of arterial thromboembolic and hemorrhagic events. The attenuation of effect found in the SCCS analysis means that there is the potential for overestimation of the reported results, which might indicate the presence of some residual confounding or confounding by indication. Public health authorities should inform their jurisdictions of these relatively small increased risks associated with ChAdOx1. No positive associations were seen between BNT162b2 and thrombocytopenic, thromboembolic and hemorrhagic events. New data from the EAVE II cohort in Scotland suggests that a first dose of the ChAdOx1 nCoV-19 vaccine might be associated with a small increase in the risk of idiopathic thrombocytopenic purpura between 0 and 27 d after vaccination., Author(s): C. R. Simpson [sup.1] [sup.2] , T. Shi [sup.2] , E. Vasileiou [sup.2] , S. V. Katikireddi [sup.3] , S. Kerr [sup.2] , E. Moore [sup.4] , C. McCowan [...]

Published
2021
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22. Comparison of two different frailty measurements and risk of hospitalisation or death from COVID-19: findings from UK Biobank

Author

Petermann-Rocha, Fanny, Hanlon, Peter, Gray, Stuart R., Welsh, Paul, Gill, Jason M. R., Foster, Hamish, Katikireddi, S. Vittal, Lyall, Donald, Mackay, Daniel F., O’Donnell, Catherine A., Sattar, Naveed, Nicholl, Barbara I., Pell, Jill P., Jani, Bhautesh D., Ho, Frederick K., Mair, Frances S., and Celis-Morales, Carlos

Published
2020
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25. Protocol for the development of guidance for stakeholder engagement in health and healthcare guideline development and implementation

Author

Petkovic, Jennifer, Riddle, Alison, Akl, Elie A., Khabsa, Joanne, Lytvyn, Lyubov, Atwere, Pearl, Campbell, Pauline, Chalkidou, Kalipso, Chang, Stephanie M., Crowe, Sally, Dans, Leonila, Jardali, Fadi El, Ghersi, Davina, Graham, Ian D., Grant, Sean, Greer-Smith, Regina, Guise, Jeanne-Marie, Hazlewood, Glen, Jull, Janet, Katikireddi, S. Vittal, Langlois, Etienne V., Lyddiatt, Anne, Maxwell, Lara, Morley, Richard, Mustafa, Reem A., Nonino, Francesco, Pardo, Jordi Pardo, Pollock, Alex, Pottie, Kevin, Riva, John, Schünemann, Holger, Simeon, Rosiane, Smith, Maureen, Stein, Airton T., Synnot, Anneliese, Tufte, Janice, White, Howard, Welch, Vivian, Concannon, Thomas W., and Tugwell, Peter

Published
2020
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26. The relationship between time spent on social media and adolescent alcohol use: a longitudinal analysis of the UK Millennium Cohort Study.

Author

Purba, Amrit Kaur, Henderson, Marion, Baxter, Andrew, Katikireddi, S Vittal, and Pearce, Anna

Subjects
ALCOHOLISM risk factors, EVALUATION of medical care, SCIENTIFIC observation, SOCIAL media, TIME, RISK assessment, RESEARCH funding, DESCRIPTIVE statistics, SOCIAL classes, LONGITUDINAL method, ADOLESCENCE
Abstract

Background To estimate the effect of social media use in 14 year olds on risk of and inequalities in alcohol use and binge drinking at 17 years. Methods Using the UK-representative Millennium Cohort Study, the relationship between time spent on social media (assessed using questionnaires [ n  = 8987] and time-use-diaries [ n  = 2520]) with frequency of alcohol use in the past month and binge drinking was estimated using adjusted odds ratios (AORs) or adjusted relative risk ratios (ARRRs). Associations within low and high parental education groups were compared to examine effect modification. Analyses accounted for pre-specified confounders, baseline outcome measures (to address reverse causality), sample design, attrition and item-missingness (through multiple imputation). Results Questionnaire-reported time spent on social media was associated with increased risk of alcohol use and binge drinking in a dose–response manner. Compared to 1-< 30 min/day social media users, 30 min-<1 h/day users were more likely to report alcohol use ≥6 times/month (ARRR 1.62 [95% confidence interval 1.20 to 2.20]) and binge drinking (AOR 1.51 [1.22 to 1.87]), as were 1–<2 h/day users (ARRR 2.61 [1.90 to 3.58]; AOR 2.06 [1.69 to 2.52]) and ≥2 h/day users (ARRR 4.80 [3.65 to 6.32]; AOR 3.07 [2.54 to 3.70]). Social media measured by time-use-diary was associated with higher risks, although not always demonstrating a dose–response relationship. The effect of social media use (vs no-use) on binge drinking was larger in the higher (vs lower) parental education groups. Analyses repeated in complete case samples, and with adjustment for baseline outcome measures revealed consistent findings. Conclusions Findings suggest social media use may increase risk of alcohol use and binge drinking. Regulatory action protecting adolescents from harmful alcohol-related social media content is necessary. [ABSTRACT FROM AUTHOR]

Published
2023
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27. 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
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28. The potential contribution of vaccination uptake to occupational differences in risk of SARS-CoV-2: Analysis of the ONS COVID-19 Infection Survey

Author

Wilkinson, Jack, primary, Demou, Evangelia, additional, Cherrie, Mark, additional, Edge, Rhiannon, additional, Gittins, Matthew, additional, Katikireddi, S Vittal, additional, Kromydas, Theocharis, additional, Mueller, William, additional, Pearce, Neil, additional, van Tongeren, Martie, additional, and Rhodes, Sarah, additional

Published
2023
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32. Additional file 2 of Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK

Author

Kennedy, J, Parker, M, Seaborne, M, Mhereeg, M, Walker, A, Walker, V, Denaxas, S, Kennedy, N, Katikireddi, S. V, and Brophy, S

Abstract

Additional file 2: Table S2. Location origins of the codes used to define the outcomes in the study. Additional notes also provided. ADHD – Attention-deficit/hyperactivity disorder, OCD - obsessive compulsive disorder.

Published
2023
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33. Additional file 1 of Healthcare use attributable to COVID-19: a propensity-matched national electronic health records cohort study of 249,390 people in Wales, UK

Author

Kennedy, J, Parker, M, Seaborne, M, Mhereeg, M, Walker, A, Walker, V, Denaxas, S, Kennedy, N, Katikireddi, S. V, and Brophy, S

Abstract

Additional file 1: Table S1. Individual SARS-CoV-2 testing sites included under each testing location. AE – Accident & Emergency, CTU – Clinical Trials Unit, HC – Hospice Care, ICU – Intensive Care Unit.

Published
2023
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40. Cochrane's risk of bias tool for non-randomized studies (ROBINS-I) is frequently misapplied: A methodological systematic review

Author

Igelström, Erik, Campbell, Mhairi, Craig, Peter, and Katikireddi, S. Vittal

Subjects
Non-randomized studies, Clinical Trials as Topic, Epidemiology, business.industry, Confounding, Psychological intervention, Bias assessment, Risk of bias, Cochrane, Systematic review, Bias, Risk Factors, Rating scale, Humans, Medicine, Original Article, Systematic review methods, Observational study, Observational studies, Methodological quality, business, Evidence synthesis, Systematic Reviews as Topic, Clinical psychology
Abstract

Objectives:\ud We aimed to review how ‘Risk of Bias In Non-randomized Studies–of Interventions’ (ROBINS-I), a Cochrane risk of bias assessment tool, has been used in recent systematic reviews.\ud \ud Study Design and Setting:\ud Database and citation searches were conducted in March 2020 to identify recently published reviews using ROBINS-I. Reported ROBINS-I assessments and data on how ROBINS-I was used were extracted from each review. Methodological quality of reviews was assessed using AMSTAR 2 (‘A MeaSurement Tool to Assess systematic Reviews’).\ud \ud Results:\ud Of 181 hits, 124 reviews were included. Risk of bias was serious/critical in 54% of assessments on average, most commonly due to confounding. Quality of reviews was mostly low, and modifications and incorrect use of ROBINS-I were common, with 20% reviews modifying the rating scale, 20% understating overall risk of bias, and 19% including critical-risk of bias studies in evidence synthesis. Poorly conducted reviews were more likely to report low/moderate risk of bias (predicted probability 57% [95% CI: 47–67] in critically low-quality reviews, 31% [19–46] in high/moderate-quality reviews).\ud \ud Conclusion:\ud Low-quality reviews frequently apply ROBINS-I incorrectly, and may thus inappropriately include or give too much weight to uncertain evidence. Readers should be aware that such problems can lead to incorrect conclusions in reviews.

Published
2021

41. How much of the unemployment effect on mental health is due to income? Mediation analysis in UK data

Author

Rachel Thomson, Kopasker D, Leyland A, Pearce A, and Katikireddi S

Subjects
Public Health, Environmental and Occupational Health
Abstract

Background Employment and income are important determinants of mental health (MH), but the extent to which 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 studied adults 25-64y from nine waves of the representative 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 a General Health Questionnaire-12 score ≥4. We conducted causal mediation analysis using inverse probability of treatment weights to estimate odds ratios (OR) and absolute differences for the effects of unemployment on CMD as measured in the same sweep, before (TE) and after (CDE) blocking the income pathway. The percentage mediated by income was 100*(TE-CDE)/TE, with standard errors calculated via bootstrapping. Multiple imputation addressed missingness. Results The TE of unemployment on short-term 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 job gains (8.77% [0.36-17.19]). Mediation by income was lowest for those aged 25-40y (7.99% [-2.57, 18.51]) and those in poverty (2.63% [-2.22, 7.49]). Conclusions In the UK, a high proportion of the short-term effect of unemployment on MH is not explained by income, particularly for those who are younger or already living in poverty. Population attributable fractions suggested 16.5% of CMD burden was due to unemployment, with 13.9% directly attributable to job loss rather than resultant income changes. Further research is needed across different European countries to determine how different welfare regimes might moderate these effects, and to investigate longer-term effects. Key messages • Unemployment has a clear detrimental effect on MH in the short-term. • Only a small proportion of this effect appears to be mediated by income.

Published
2022

42. Assessing performance of the Healthcare Access and Quality Index, overall and by select age groups, for 204 countries and territories, 1990-2019: a systematic analysis from the Global Burden of Disease Study 2019

Author

Lozano, R., Haakenstad, A., Yearwood, J. A., Fullman, N., Bintz, C., Bienhoff, K., Weaver, M. R., Nandakumar, V., Joffe, J. N., LeGrand, K. E., Knight, M., Abbafati, C., Abbasi-Kangevari, M., Abdoli, A., Zuniga, R. A. A., Adedeji, I. A., Adekanmbi, V., Adetokunboh, O. O., Afzal, M. S., Afzal, S., Agudelo-Botero, M., Ahinkorah, B. O., Ahmad, S., Ahmadi, A., Ahmadi, S., Ahmed, A., Rashid, T. A., Aji, B., Akande-Sholabi, W., Alam, K., Al Hamad, H., Alhassan, R. K., Ali, L., Alipour, V., Aljunid, S. M., Ameyaw, E. K., Amin, T. T., Amu, H., Amugsi, D. A., Ancuceanu, R., Andrade, P. P., Anjum, A., Arabloo, J., Arab-Zozani, M., Ariffin, H., Arulappan, J., Aryan, Z., Ashraf, T., Atnafu, D. D., Atreya, A., Ausloos, M., Avila-Burgos, L., Ayano, G., Ayanore, M. A., Azari, S., Badiye, A. D., Baig, A. A., Bairwa, M., Bakkannavar, S. M., Baliga, S., Banik, P. C., Barnighausen, T. W., Barra, F., Barrow, A., Basu, S., Bayati, M., Belete, R., Bell, A. W., Bhagat, D. S., Bhagavathula, A. S., Bhardwaj, P., Bhardwaj, N., Bhaskar, S., Bhattacharyya, K., Bhutta, Z. A., Bibi, S., Bijani, A., Bikbov, B., Biondi, A., Bolarinwa, O. A., Bonny, A., Brenner, H., Buonsenso, D., Burkart, K., Busse, R., Butt, Z. A., Butt, N. S., dos Santos, F. L. C., Cahuana Hurtado, Lucero, Camera, Luis Alberto, Cardenas, R., Carneiro, V. L. A., Catala-Lopez, F., Chandan, J. S., Charan, J., Chavan, P. P., Chen, S. M., Chen, S., Choudhari, S. G., Chowdhury, E. K., Chowdhury, M. A. K., Cirillo, M., Corso, B., Dadras, O., Dahlawi, S. M. A., Dai, X. C., Dandona, L., Dandona, R., Dangel, W. J., Davila-Cervantes, C. A., Davletov, K., Deuba, K., Dhimal, M., Dhimal, M. L., Djalalinia, S., Do, H. P., Doshmangir, L., Duncan, B. B., Effiong, A., Ehsani-Chimeh, E., Elgendy, I. Y., Elhadi, M., El Sayed, I., El Tantawi, M., Erku, D. A., Eskandarieh, S., Fares, J., Farzadfar, F., Ferrero, S., Desideri, L. F., Fischer, F., Foigt, N. A., Foroutan, M., Fukumoto, T., Gaal, P. A., Gaihre, S., Gardner, W. M., Garg, T., Obsa, A. G., Ghafourifard, M., Ghashghaee, A., Ghith, N., Gilani, S. A., Gill, P. S., Goharinezhad, S., Golechha, M., Guadamuz, J. S., Guo, Y. M., Das Gupta, R., Gupta, R., Gupta, V. K., Gupta, V. B., Hamiduzzaman, M., Hanif, A., Haro, J. M., Hasaballah, A. I., Hasan, M. M., Hasan, M. T., Hashi, A., Hay, S. I., Hayat, K., Heidari, M., Heidari, G., Henry, N. J., Herteliu, C., Holla, R., Hossain, S., Hossain, S. J., Hossain, M. B. H., Hosseinzadeh, M., Hostiuc, S., Hoveidamanesh, S., Hsieh, V. C. R., Hu, G. Q., Huang, J. J., Huda, M. M., Ifeagwu, S. C., Ikuta, K. S., Ilesanmi, O. S., Irvani, S. S. N., Islam, R. M., Islam, S. M. S., Ismail, N. E., Iso, H., Isola, G., Itumalla, R., Iwagami, M., Jahani, M. A., Jahanmehr, N., Jain, R., Jakovljevic, M., Janodia, M. D., Jayapal, S. K., Jayaram, S., Jha, R. P., Jonas, J. B., Joo, T., Joseph, N., Jurisson, M., Kabir, A., Kalankesh, L. R., Kalhor, R., Kamath, A. M., Kamenov, K., Kandel, H., Kantar, R. S., Kapoor, N., Karanikolos, M., Katikireddi, S. V., Kavetskyy, T., Kawakami, N., Kayode, G. A., Keikavoosi-Arani, L., Keykhaei, M., Khader, Y. S., Khajuria, H., Khalilov, R., Khammarnia, M., Khan, M. N., Khan, M. A. B., Khan, M., Khezeli, M., Kim, M. S., Kim, Y. J., Kisa, S., Kisa, A., Klymchuk, V., Koly, K. N., Korzh, O., Kosen, S., Koul, P. A., Defo, B. K., Kumar, G. A., Kusuma, D., Kyu, H. H., Larsson, A. O., Lasrado, S., Lee, W. C., Lee, Y. H., Lee, C. B., Li, S. S., Lucchetti, G., Mahajan, P. B., Majeed, A., Makki, A., Malekzadeh, R., Malik, A. A., Malta, D. C., Mansournia, M. A., Mantovani, L. G., Martinez-Valle, A., Martins-Melo, F. R., Masoumi, S. Z., Mathur, M. R., Maude, R. J., Maulik, P. K., McKee, M., Mendoza, W., Menezes, R. G., Mensah, G. A., Meretoja, A., Meretoja, T. J., Mestrovic, T., Michalek, I. M., Mirrakhimov, E. M., Misganaw, A., Misra, S., Moazen, B., Mohammadi, M., Mohammed, S., Moitra, M., Mokdad, A. H., Molokhia, M., Monasta, L., Moni, M. A., Moradi, G., Moreira, R. S., Mosser, J. F., Mostafavi, E., Mouodi, S., Nagarajan, A. J., Nagata, C., Naghavi, M., Nangia, V., Swamy, S. N., Narayana, A. I., Nascimento, B. R., Nassereldine, H., Nayak, B. P., Nazari, J., Negoi, I., Nepal, S., Kandel, S. N., Ngunjiri, J. W., Nguyen, H. L. T, Nguyen, C. T., Ningrum, D. N. A., Noubiap, J. J., Oancea, B., Oghenetega, O. B., Oh, I. H., Olagunju, A. T., Olakunde, B. O., Bali, A. O., Omer, E., Onwujekwe, O. E., Otoiu, A., Padubidri, J. R., Palladino, R., Pana, A., Panda-Jonas, S., Pandi-Perumal, S. R., Pardhan, S., Pasupula, D. K., Pathak, P. K., Patton, G. C., Pawar, S., Pereira, J., Pilania, M., Piroozi, B., Podder, V., Pokhrel, K. N., Postma, M. J., Prada, S. I., Syed, Z. Q., Rabiee, N., Radhakrishnan, R. A., Rahman, M. M., Rahman, M., Rahman, M. H. U., Rahmani, A. M., Ranabhat, C. L., Rao, C. R., Rao, S. J., Rasella, D., Rawaf, S., Rawaf, D. L., Rawal, L., Renzaho, A. M. N., Reshmi, B., Resnikoff, S., Rezapour, A., Riahi, S. M., Ripon, R. K., Sacco, S., Sadeghi, M., Saeed, U., Sahebkar, A., Sahiledengle, B., Sahoo, H., Sahu, M., Salama, J. S., Salamati, P., Samy, A. M., Sanabria, J., Santric-Milicevic, M. M., Sathian, B., Sawhney, M., Schmidt, M. I., Seidu, A. A., Sepanlou, S. G., Seylani, A., Shaikh, M. A., Sheikh, A., Shetty, A., Shigematsu, M., Shiri, R., Shivakumar, K. M., Shokri, A., Singh, J. A., Sinha, D. N., Skryabin, V. Y., Skryabina, A. A., Sofi-Mahmudi, A., Sousa, R. A. R. C., Stephens, J. H., Sun, J., Szocska, M., Tabares-Seisdedos, R., Tadbiri, H., Tamiru, A. T., Thankappan, K. R., Topor-Madry, R., Tovani-Palone, M. R., Tran, M. T. N., Tran, B. X., Tripathi, N., Tripathy, J. P., Troeger, C. E., Uezono, D. R., Ullah, S., Ullah, A., Unnikrishnan, B., Vacante, M., Tahbaz, S. V., Valdez, P. R., Vasic, M., Veroux, M., Vervoort, D., Violante, F. S., Vladimirov, S. K., Vlassov, V., Vo, B., Waheed, Y., Wamai, R. G., Wang, Y. P., Wang, Y. Z., Ward, P., Wiangkham, T., Yadav, L., Jabbari, S. H. Y., Yamagishi, K., Yaya, S., Yazdi-Feyzabadi, V., Yi, S. Y., Yigit, V., Yonemoto, N., Younis, M. Z., Yu, C. H., Yunusa, I., Bin Zaman, S., Zastrozhin, M. S., Zhang, Z. J., Zhong, C. W., Zuniga, Y. M. H., Lim, S. S., Murray, C. J. 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Padubidri, J, Palladino, R, Pana, A, Panda-Jonas, S, Pandi-Perumal, S, Pardhan, S, Pasupula, D, Pathak, P, Patton, G, Pawar, S, Pereira, J, Pilania, M, Piroozi, B, Podder, V, Pokhrel, K, Postma, M, Prada, S, Quazi Syed, Z, Rabiee, N, Radhakrishnan, R, Rahman, M, Rahmani, A, Ranabhat, C, Rao, C, Rao, S, Rasella, D, Rawaf, S, Rawaf, D, Rawal, L, Renzaho, A, Reshmi, B, Resnikoff, S, Rezapour, A, Riahi, S, Ripon, R, Sacco, S, Sadeghi, M, Saeed, U, Sahebkar, A, Sahiledengle, B, Sahoo, H, Sahu, M, Salama, J, Salamati, P, Samy, A, Sanabria, J, Santric-Milicevic, M, Sathian, B, Sawhney, M, Schmidt, M, Seidu, A, Sepanlou, S, Seylani, A, Shaikh, M, Sheikh, A, Shetty, A, Shigematsu, M, Shiri, R, Shivakumar, K, Shokri, A, Singh, J, Sinha, D, Skryabin, V, Skryabina, A, Sofi-Mahmudi, A, Sousa, R, Stephens, J, Sun, J, Szocska, M, Tabares-Seisdedos, R, Tadbiri, H, Tamiru, A, Thankappan, K, Topor-Madry, R, Tovani-Palone, M, Tran, M, Tran, B, Tripathi, N, Tripathy, J, Troeger, C, Uezono, D, Ullah, S, Ullah, A, Unnikrishnan, B, Vacante, M, Valadan Tahbaz, S, Valdez, P, Vasic, M, Veroux, M, Vervoort, D, Violante, F, Vladimirov, S, Vlassov, V, Vo, B, Waheed, Y, Wamai, R, Wang, Y, Ward, P, Wiangkham, T, Yadav, L, Yahyazadeh Jabbari, S, Yamagishi, K, Yaya, S, Yazdi-Feyzabadi, V, Yi, S, Yigit, V, Yonemoto, N, Younis, M, Yu, C, Yunusa, I, Zaman, S, Zastrozhin, M, Zhang, Z, Zhong, C, Zuniga, Y, Lim, S, Murray, C, Lozano, R, Bill & Melinda Gates Foundation, King Edward Medical University (Pakistán), Kuwait University (Kuwait), Romanian National Authority for Scientific Research and Innovation, Romanian Ministry of Research Innovation and Digitalization, Alexander von Humboldt Foundation, Federal Ministry of Education & Research (Alemania), Unión Europea. Comisión Europea. H2020, University of Aberdeen (Reino Unido), Novo Nordisk Foundation, National Health and Medical Research Council (Australia), National Research, Development and Innovation Office (Hungria), National Records of Scotland (Reino Unido), Medical Research Council (Reino Unido), Scottish Government (Reino Unido), Jatiya Kabi Kazi Nazrul Islam University (Bangladesh), Xiamen University Malaysia (Malasia), National Council for Scientific and Technological Development (Brasil), Ministero della Salute (Italia), Fondazione IRCCS. Istituto Nazionale dei Tumori, King College London, IRCCS Materno Infantile Burlo Garofolo (Italia), Edwards Lifesciences Foundation, Fundação de Amparo à Pesquisa do Estado de Minas Gerais (Brasil), Manipal Academy of Higher Education (India), Ministerio de Ciencia e Innovación. Centro de Excelencia Severo Ochoa (España), Government of Catalonia (España), International Center of Medical Sciences Research (Pakistán), Ain Shams University (Egipto), Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red - CIBERSAM (Salud Mental), INCLIVA Health Research Institute (España), Canadian Institutes of Health Research, Australian Government, and Ministry of Education, Science and Technological Development (Serbia)

Subjects
Adult, Adolescent, Population, Global Health, Health Services Accessibility, Global Burden of Disease, Health system quality, Young Adult, Nations, Health systems, health care access, Risk Factors, Quality-Adjusted Life Year, Humans, Child, Global Burden of Disease Study 2019, Health-care access, Aged, Quality of Health Care, quality, performance, The Healthcare Access and Quality Index, Risk Factor, Infant, Newborn, Infant, eu-repo/semantics/review [info], Public Health, Global Health, Social Medicine and Epidemiology, General Medicine, Health-care quality, Middle Aged, 3141 Health care science, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Indicator, Medical-care, Child, Preschool, Deaths, Amenable mortality, Quality-Adjusted Life Years, Age groups, Trends, Human
Abstract

Background: Health-care needs change throughout the life course. It is thus crucial to assess whether health systems provide access to quality health care for all ages. Drawing from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019), we measured the Healthcare Access and Quality (HAQ) Index overall and for select age groups in 204 locations from 1990 to 2019. Methods: We distinguished the overall HAQ Index (ages 0-74 years) from scores for select age groups: the young (ages 0-14 years), working (ages 15-64 years), and post-working (ages 65-74 years) groups. For GBD 2019, HAQ Index construction methods were updated to use the arithmetic mean of scaled mortality-to-incidence ratios (MIRs) and risk-standardised death rates (RSDRs) for 32 causes of death that should not occur in the presence of timely, quality health care. Across locations and years, MIRs and RSDRs were scaled from 0 (worst) to 100 (best) separately, putting the HAQ Index on a different relative scale for each age group. We estimated absolute convergence for each group on the basis of whether the HAQ Index grew faster in absolute terms between 1990 and 2019 in countries with lower 1990 HAQ Index scores than countries with higher 1990 HAQ Index scores and by Socio-demographic Index (SDI) quintile. SDI is a summary metric of overall development. Findings: Between 1990 and 2019, the HAQ Index increased overall (by 19·6 points, 95% uncertainty interval 17·9-21·3), as well as among the young (22·5, 19·9-24·7), working (17·2, 15·2-19·1), and post-working (15·1, 13·2-17·0) age groups. Large differences in HAQ Index scores were present across SDI levels in 2019, with the overall index ranging from 30·7 (28·6-33·0) on average in low-SDI countries to 83·4 (82·4-84·3) on average in high-SDI countries. Similarly large ranges between low-SDI and high-SDI countries, respectively, were estimated in the HAQ Index for the young (40·4-89·0), working (33·8-82·8), and post-working (30·4-79·1) groups. Absolute convergence in HAQ Index was estimated in the young group only. In contrast, divergence was estimated among the working and post-working groups, driven by slow progress in low-SDI countries. Interpretation: Although major gaps remain across levels of social and economic development, convergence in the young group is an encouraging sign of reduced disparities in health-care access and quality. However, divergence in the working and post-working groups indicates that health-care access and quality is lagging at lower levels of social and economic development. To meet the needs of ageing populations, health systems need to improve health-care access and quality for working-age adults and older populations while continuing to realise gains among the young. O Adetokunboh acknowledges support from Department of Science and Innovation and National Research Foundation. S Afzal acknowledges the institutional support of King Edward Medical University. S Aljunid acknowledges Department of Health Policy and Management, College of Public Health, Health Science Centre, Kuwait University for the approval and support to participate in this research project. M Ausloos, C Herteliu, and A Pana acknowledge partial support by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. C Herteliu also acknowledges partial support by a grant of the Romanian Ministry of Research Innovation and Digitalization, MCID, project number ID-585-CTR-42-PFE-2021. T Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the Federal Ministry of Education and Research. B Bikbov acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 703226. Institute of Applied Health Sciences; School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Scotland. The salary for N Ghith is covered by a grant from Novo Nordisk Foundation (NNF16OC0021856). V B Gupta acknowledges funding support from National Health and Medical Research Council (NHMRC) Australia. V K Gupta acknowledges funding support from National Health and Medical Research Council (NHMRC) Australia. T Joo acknowledges support from the National Research, Development and Innovation Office of Hungary under grant RRF-2.3.1-21-2022-00006 (Data-driven Health Division of Health Security National Laboratory). S Vittal Katikireddi acknowledges funding from a NRS Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2), and the Scottish Government Chief Scientist Office (SPHSU17). M N Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Mymensingh, Bangladesh. Y J Kim acknowledges support from the Research Management Centre Xiamen University Malaysia [XMUMRF/2020-C6/ITCM/0004]. G Lucchetti is a grantee of the Brazilian National Council for Scientific and Technological Development Research Productivity - Level 1D. L Mantovani acknowledges support by Italian Ministry of Health Ricerca Corrente - IRCCS Multimedica. M Molokhia acknowledges support by the National Institute for Health Research Biomedical Research Center at Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London. L Monasta reports support for the present manuscript from the Italian Ministry of Health on project Ricerca Corrente 34/2017 and payments made to the Institute for Maternal and Child Health IRCCS Burlo Garofolo. R Moreira acknowledges the CNPQ productivity grant (316607/2021-5). B R Nascimento is partially supported by CNPq (Research Productivity Grant, 312382/2019-7), the Edwards Lifesciences Foundation (Improving the prevention and detection of Heart Valve disease across the Lifespan, 2021), and FAPEMIG (grant APQ-000627-20). J R Padubidri acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India for their constant support in conducting research. D Rasella reports financial support from the Spanish Ministry of Science and Innovation and State Research Agency through the Centro de Excelencia Severo Ochoa 2019-2023 programme (CEX2018-000806-S), and financial support from the Generalitat de Catalunya through the Centres de Recerca de Catalunya programme. U Saeed would like to acknowledge the International Center of Medical Sciences Research (ICMSR), Islamabad (44000), Pakistan. A M Samy acknowledges the support from Ain Shams University and the Egyptian Fulbright Mission Program. U Saeed would like to acknowledge Kasturba Medical College, Mangalore. Manipal Academy of Higher Education, Manipal for supporting research activities. R T-S is supported by the Spanish Ministry of Science and Innovation, Institute of Health Carlos III, CIBERSAM, INCLIVA (PID2021-129099OB-I00). D Vervoort is supported by the Canadian Institutes of Health Research (CIHR) Vanier Canada Graduate Scholarship. S B Zaman acknowledges receiving a scholarship from the Australian Government Research Training Program (RTP) in support of his academic career. Serbian part of this GBD contribution was co-financed through Grant OI 175 014 of the Ministry of Education Science and Technological Development of The Republic of Serbia. This work was supported, in whole or in part, by the Bill & Melinda Gates Foundation OPP1152504. Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. Sí

Published
2022

43. 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
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44. Mental health outcomes following COVID-19 infection: Evidence from 11 UK longitudinal population studies

Author

Thompson, Ellen J., primary, Stafford, Jean, additional, Moltrecht, Bettina, additional, Huggins, Charlotte F., additional, Kwong, Alex S. F., additional, Shaw, Richard J., additional, Zaninotto, Paola, additional, Patel, Kishan, additional, Silverwood, Richard J., additional, McElroy, Eoin, additional, Pierce, Matthias, additional, Green, Michael J., additional, Bowyer, Ruth C. E., additional, Maddock, Jane, additional, Tilling, Kate, additional, Katikireddi, S. Vittal, additional, Ploubidis, George B., additional, Porteous, David J., additional, Timpson, Nic, additional, Chaturvedi, Nish, additional, Steves, Claire J., additional, and Patalay, Praveetha, additional

Published
2022
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46. Potential importance of residual confounding in systematic reviews of observational studies: Answer to Mathur and VanderTweele

Author

Verbeek, Jos H., primary, Whaley, Paul, additional, Morgan, Rebecca L., additional, Taylor, Kyla W., additional, Rooney, Andrew A., additional, Schwingshackl, Lukas, additional, Hoving, Jan L., additional, Vittal Katikireddi, S., additional, Shea, Beverley, additional, Mustafa, Reem A., additional, Murad, M.Hassan, additional, and Schünemann, Holger J., additional

Published
2022
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47. Social media as a determinant of health.

Author

Purba, Amrit Kaur, Pearce, Anna, Henderson, Marion, McKee, Martin, and Katikireddi, S Vittal

Subjects
SOCIAL media, INTERNET access, HEALTH services accessibility, SOCIAL determinants of health, DISINFORMATION, DIGITAL divide, HEALTH, INFORMATION resources, ONLINE social networks, HEALTH behavior, INTERPERSONAL relations, PRACTICAL politics, PUBLIC health, SELF-perception
Abstract

The article explores the potential mechanisms of social media as a determinant of health. It considers the role of social media in improving the flow of health information and in strengthening social connections and interpersonal relations. It discusses the association of social media to self-esteem, social comparison and obsessive-compulsive behavior, adverse effects of digital marketing on health behaviors, health consequences of dis/misinformation, and distortion of public health discourse.

Published
2024
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49. An approach to quantifying the potential importance of residual confounding in systematic reviews of observational studies: A GRADE concept paper

Author

Verbeek, Jos H., primary, Whaley, Paul, additional, Morgan, Rebecca L., additional, Taylor, Kyla W., additional, Rooney, Andrew A., additional, Schwingshackl, Lukas, additional, Hoving, Jan L., additional, Vittal Katikireddi, S., additional, Shea, Beverley, additional, Mustafa, Reem A., additional, Murad, M. Hassan, additional, and Schünemann, Holger J., additional

Published
2021
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