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Rodriguez-Lopez M, Leckie G, Kaufman JS, Merlo J. Multilevel modelling for measuring interaction of effects between multiple categorical variables: An illustrative application using risk factors for preeclampsia. Paediatr Perinat Epidemiol 2023; 37:154-164. [PMID: 36357347 PMCID: PMC10098842 DOI: 10.1111/ppe.12932] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 10/17/2022] [Accepted: 10/18/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND Measuring multiple and higher-order interaction effects between multiple categorical variables proves challenging. OBJECTIVES To illustrate a multilevel modelling approach to studying complex interactions. METHODS We apply a two-level random-intercept linear regression to a binary outcome for individuals (level-1) nested within strata (level-2) defined by all observed combinations of multiple categorical exposure variables. As a pedagogic application, we analyse 36 strata defined by five risk factors of preeclampsia (parity, previous preeclampsia, chronic hypertension, multiple pregnancies, body mass index category) among 652,603 women in the Swedish Medical Birth Registry between 2002 and 2010. RESULTS The absolute risk of preeclampsia was 4% but was predicted to vary from 1% to 44% across strata. The stratum discriminatory accuracy was 30% according to the variance partition coefficient (VPC) and 0.73 according to the area under the receiver operating characteristic curve (AUC). While the risk heterogeneity across strata was primarily due to the main effects of the categories defining the strata, 5% of the variation was attributable to their two- and higher-way interaction effects. One stratum presented a positive interaction, and two strata presented negative interaction. CONCLUSIONS Multilevel modelling is an innovative tool for identifying and analysing higher-order interaction effects. Further work is needed to explore how this approach can best be applied to making causal inferences.
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Affiliation(s)
- Merida Rodriguez-Lopez
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden.,Faculty of Health Sciences, Universidad Icesi, Cali, Colombia
| | - George Leckie
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden.,Centre for Multilevel Modelling, University of Bristol, Bristol, UK
| | - Jay S Kaufman
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
| | - Juan Merlo
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden.,Center for Primary Health Care Research, Region Skåne, Malmö, Sweden
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Persmark A, Wemrell M, Zettermark S, Leckie G, Subramanian SV, Merlo J. Precision public health: Mapping socioeconomic disparities in opioid dispensations at Swedish pharmacies by Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA). PLoS One 2019; 14:e0220322. [PMID: 31454361 PMCID: PMC6711500 DOI: 10.1371/journal.pone.0220322] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Accepted: 07/12/2019] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND In light of the opioid epidemic in the United States, there is growing concern about the use of opioids in Sweden as it may lead to misuse and overuse and, in turn, severe public health problems. However, little is known about the distribution of opioid use across different demographic and socioeconomic dimensions in the Swedish general population. Therefore, we applied an intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA), to obtain an improved mapping of the risk heterogeneity of and socioeconomic inequalities in opioid prescription receipt. METHODS AND FINDINGS Using data from 6,846,106 residents in Sweden aged 18 and above, we constructed 72 intersectional strata from combinations of gender, age, income, cohabitation status, and presence or absence of psychological distress. We modelled the absolute risk (AR) of opioid prescription receipt in a series of multilevel logistic regression models distinguishing between additive and interaction effects. By means of the Variance Partitioning Coefficient (VPC) and the area under the receiver operating characteristic curve (AUC), we quantified the discriminatory accuracy (DA) of the intersectional strata for discerning those who received opioid prescriptions from those who did not. The AR of opioid prescription receipt ranged from 2.77% (95% CI 2.69-2.86) among low-income men aged 18-34, living alone, without psychological distress, to 28.25% (95% CI 27.95-28.56) among medium-income women aged 65 and older, living alone, with psychological distress. In a model that conflated both additive and interaction effects, the intersectional strata had a fair DA for discerning opioid users from non-users (VPC = 13.2%, AUC = 0.68). However, in the model that decomposed total effects into additive and interaction effects, the VPC was very low (0.42%) indicating the existence of small interaction effects for a number of the intersectional strata. CONCLUSIONS The intersectional MAIHDA approach aligns with the aims of precision public health, through improving the evidence base for health policy by increasing understanding of both health inequalities and individual heterogeneity. This approach is particularly relevant for socioeconomically conditioned outcomes such as opioid prescription receipt. We have identified intersections of social position within the Swedish population at greater risk for opioid prescription receipt.
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Affiliation(s)
- Anna Persmark
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
| | - Maria Wemrell
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
- Department of Gender Studies, Faculty of Social Sciences, Lund University, Lund, Sweden
| | - Sofia Zettermark
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
| | - George Leckie
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
- Centre for Multilevel Modelling, University of Bristol, Bristol, United Kingdom
| | - S. V. Subramanian
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Juan Merlo
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
- Centre for Primary Health Care Research, Region Skåne, Malmö, Sweden
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3
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Terman SW, Guterman EL, Hill CE, Betjemann JP, Burke JF. Factors associated with 30-day readmission for patients hospitalized for seizures. Neurol Clin Pract 2019; 10:122-130. [PMID: 32309030 DOI: 10.1212/cpj.0000000000000688] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Accepted: 04/25/2019] [Indexed: 11/15/2022]
Abstract
Background We sought to determine the cumulative incidence of readmissions after a seizure-related hospitalization and identify risk factors and readmission diagnoses. Methods We performed a retrospective cohort study of adult patients hospitalized with a primary discharge diagnosis of seizure (International Classification of Diseases, Ninth Edition, Clinical Modification codes 345.xx and 780.3x) using the State Inpatient Databases across 11 states from 2009 to 2012. Hospital and community characteristics were obtained from the American Hospital Association and Robert Wood Johnson Foundation. We performed logistic regressions to explore effects of patient, hospital, and community factors on readmissions within 30 days of discharge. Results Of 98,712 patients, 13,929 (14%) were readmitted within 30 days. Reasons for readmission included epilepsy/convulsions (30% of readmitted patients), mood disorders (5%), schizophrenia (4%), and septicemia (4%). The strongest predictors of readmission were diagnoses of CNS tumor (odds ratio [OR] 2.1, 95% confidence interval [CI] 1.9-2.4) or psychosis (OR 1.8, 95% CI 1.7-1.8), urgent index admission (OR 2.0, 95% CI 1.8-2.2), transfer to nonacute facilities (OR 1.7, 95% CI 1.6-1.8), long length of stay (OR 1.7, 95% CI 1.6-1.8), and for-profit hospitals (OR 1.7, 95% CI 1.6-1.8). Our main model's c-statistic was 0.66. Predictors of readmission for status epilepticus included index admission for status epilepticus (OR 3.5, 95% CI 2.6-4.7), low hospital epilepsy volume (OR 0.4, 95% CI 0.3-0.7), and rural hospitals (OR 4.8, 95% CI 2.1-10.9). Conclusion Readmission is common after hospitalization for seizures. Prevention strategies should focus on recurrent seizures, the most common readmission diagnosis. Many factors were associated with readmission, although readmissions remain challenging to predict.
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Affiliation(s)
- Samuel W Terman
- University of Michigan (SWT, CEH), Department of Neurology, Ann Arbor, MI; University of California San Francisco (ELG, JPB), Department of Neurology, San Francisco, CA; Department of Neurology and Stroke Program (JFB), University of Michigan; and Department of Veterans Affairs (JFB), VA Center for Clinical Management and Research, Ann Arbor VA Healthcare System, Ann Arbor, MI
| | - Elan L Guterman
- University of Michigan (SWT, CEH), Department of Neurology, Ann Arbor, MI; University of California San Francisco (ELG, JPB), Department of Neurology, San Francisco, CA; Department of Neurology and Stroke Program (JFB), University of Michigan; and Department of Veterans Affairs (JFB), VA Center for Clinical Management and Research, Ann Arbor VA Healthcare System, Ann Arbor, MI
| | - Chloe E Hill
- University of Michigan (SWT, CEH), Department of Neurology, Ann Arbor, MI; University of California San Francisco (ELG, JPB), Department of Neurology, San Francisco, CA; Department of Neurology and Stroke Program (JFB), University of Michigan; and Department of Veterans Affairs (JFB), VA Center for Clinical Management and Research, Ann Arbor VA Healthcare System, Ann Arbor, MI
| | - John P Betjemann
- University of Michigan (SWT, CEH), Department of Neurology, Ann Arbor, MI; University of California San Francisco (ELG, JPB), Department of Neurology, San Francisco, CA; Department of Neurology and Stroke Program (JFB), University of Michigan; and Department of Veterans Affairs (JFB), VA Center for Clinical Management and Research, Ann Arbor VA Healthcare System, Ann Arbor, MI
| | - James F Burke
- University of Michigan (SWT, CEH), Department of Neurology, Ann Arbor, MI; University of California San Francisco (ELG, JPB), Department of Neurology, San Francisco, CA; Department of Neurology and Stroke Program (JFB), University of Michigan; and Department of Veterans Affairs (JFB), VA Center for Clinical Management and Research, Ann Arbor VA Healthcare System, Ann Arbor, MI
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Merlo J, Wagner P, Leckie G. A simple multilevel approach for analysing geographical inequalities in public health reports: The case of municipality differences in obesity. Health Place 2019; 58:102145. [DOI: 10.1016/j.healthplace.2019.102145] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2018] [Revised: 05/01/2019] [Accepted: 05/27/2019] [Indexed: 12/14/2022]
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Hernández-Yumar A, Wemrell M, Abásolo Alessón I, González López-Valcárcel B, Leckie G, Merlo J. Socioeconomic differences in body mass index in Spain: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy. PLoS One 2018; 13:e0208624. [PMID: 30532244 PMCID: PMC6287827 DOI: 10.1371/journal.pone.0208624] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Accepted: 11/20/2018] [Indexed: 11/29/2022] Open
Abstract
Many studies have demonstrated the existence of simple, unidimensional socioeconomic gradients in body mass index (BMI). However, in the present paper we move beyond such traditional analyses by simultaneously considering multiple demographic and socioeconomic dimensions. Using the Spanish National Health Survey 2011–2012, we apply intersectionality theory and multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to analyze 14,190 adults nested within 108 intersectional strata defined by combining categories of gender, age, income, educational achievement and living situation. We develop two multilevel models to obtain information on stratum-specific BMI averages and the degree of clustering of BMI within strata expressed by the intra-class correlation coefficient (ICC). The first model is a simple variance components analysis that provides a detailed mapping of the BMI disparities in the population and measures the accuracy of stratum membership to predict individual BMI. The second model includes the variables used to define the intersectional strata as a way to identify stratum-specific interactions. The first model suggests moderate but meaningful clustering of individual BMI within the intersectional strata (ICC = 12.4%). Compared with the population average (BMI = 26.07 Kg/m2), the stratum of cohabiting 18-35-year-old females with medium income and high education presents the lowest BMI (-3.7 Kg/m2), while cohabiting 36-64-year-old females with low income and low education show the highest BMI (+2.6 Kg/m2). In the second model, the ICC falls to 1.9%, suggesting the existence of only very small stratum specific interaction effects. We confirm the existence of a socioeconomic gradient in BMI. Compared with traditional analyses, the intersectional MAIHDA approach provides a better mapping of socioeconomic and demographic inequalities in BMI. Because of the moderate clustering, public health policies aiming to reduce BMI in Spain should not solely focus on the intersectional strata with the highest BMI, but should also consider whole population polices.
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Affiliation(s)
- Aránzazu Hernández-Yumar
- Departamento de Economía Aplicada y Métodos Cuantitativos, Facultad de Economía, Empresa y Turismo, Universidad de La Laguna (ULL), San Cristóbal de La Laguna, Santa Cruz de Tenerife, España
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
- * E-mail:
| | - Maria Wemrell
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
- Department of Gender Studies, Lund University, Lund, Sweden
| | - Ignacio Abásolo Alessón
- Departamento de Economía Aplicada y Métodos Cuantitativos, Facultad de Economía, Empresa y Turismo, Universidad de La Laguna (ULL), San Cristóbal de La Laguna, Santa Cruz de Tenerife, España
| | - Beatriz González López-Valcárcel
- Departamento de Métodos Cuantitativos en Economía y Gestión, Universidad de Las Palmas de Gran Canaria (ULPGC), Las Palmas de Gran Canaria, España
| | - George Leckie
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
- Centre for Multilevel Modelling, University of Bristol, Bristol, United Kingdom
| | - Juan Merlo
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
- Centre for Primary Health Care Research, Region Skåne, Malmö, Sweden
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Merlo J. Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) within an intersectional framework. Soc Sci Med 2018; 203:74-80. [DOI: 10.1016/j.socscimed.2017.12.026] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Revised: 12/14/2017] [Accepted: 12/17/2017] [Indexed: 02/06/2023]
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Axelsson Fisk S, Mulinari S, Wemrell M, Leckie G, Perez Vicente R, Merlo J. Chronic Obstructive Pulmonary Disease in Sweden: An intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy. SSM Popul Health 2018; 4:334-346. [PMID: 29854918 PMCID: PMC5976844 DOI: 10.1016/j.ssmph.2018.03.005] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Revised: 03/09/2018] [Accepted: 03/12/2018] [Indexed: 12/13/2022] Open
Abstract
Socioeconomic, ethnic and gender disparities in Chronic Obstructive Pulmonary Disease (COPD) risk are well established but no studies have applied multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) within an intersectional framework to study this outcome. We study individuals at the first level of analysis and combinations of multiple social and demographic categorizations (i.e., intersectional strata) at the second level of analysis. Here we used MAIHDA to assess to what extent individual differences in the propensity of developing COPD are at the intersectional strata level. We also used MAIHDA to determine the degree of similarity in COPD incidence of individuals in the same intersectional stratum. This leads to an improved understanding of risk heterogeneity and of the social dynamics driving socioeconomic and demographic disparities in COPD incidence. Using data from 2,445,501 residents in Sweden aged 45–65, we constructed 96 intersectional strata combining categories of age, gender, income, education, civil- and migration status. The incidences of COPD ranged from 0.02% for young, native males with high income and high education who cohabited to 0.98% for older native females with low income and low education who lived alone. We calculated the intra-class correlation coefficient (ICC) that informs on the discriminatory accuracy of the categorizations. In a model that conflated additive and interaction effects, the ICC was good (20.0%). In contrast, in a model that measured only interaction effects, the ICC was poor (1.1%) suggesting that most of the observed differences in COPD incidence across strata are due to the main effects of the categories used to construct the intersectional matrix while only a minor share of the differences are attributable to intersectional interactions. We found conclusive interaction effects. The intersectional MAIHDA approach offers improved information to guide public health policies in COPD prevention, and such policies should adopt an intersectional perspective. We use multilevel analysis of individual heterogeneity and discriminatory accuracy. There is a clear difference in COPD incidence between intersectional strata. Intersectionality improves mapping of socioeconomic differences in COPD incidence. Preventive measures should be based on intersectional rather than classic analyses.
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Affiliation(s)
- Sten Axelsson Fisk
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Sweden
| | - Shai Mulinari
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Sweden
| | - Maria Wemrell
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Sweden
| | - George Leckie
- Centre for Multilevel Modelling, University of Bristol, UK
| | | | - Juan Merlo
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Sweden.,Center for Primary Health Research, Region Skåne, Malmö, Sweden
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Campillo-Artero C, Serra-Burriel M, Calvo-Pérez A. Predictive modeling of emergency cesarean delivery. PLoS One 2018; 13:e0191248. [PMID: 29360875 PMCID: PMC5779661 DOI: 10.1371/journal.pone.0191248] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 01/02/2018] [Indexed: 01/13/2023] Open
Abstract
OBJECTIVE To increase discriminatory accuracy (DA) for emergency cesarean sections (ECSs). STUDY DESIGN We prospectively collected data on and studied all 6,157 births occurring in 2014 at four public hospitals located in three different autonomous communities of Spain. To identify risk factors (RFs) for ECS, we used likelihood ratios and logistic regression, fitted a classification tree (CTREE), and analyzed a random forest model (RFM). We used the areas under the receiver-operating-characteristic (ROC) curves (AUCs) to assess their DA. RESULTS The magnitude of the LR+ for all putative individual RFs and ORs in the logistic regression models was low to moderate. Except for parity, all putative RFs were positively associated with ECS, including hospital fixed-effects and night-shift delivery. The DA of all logistic models ranged from 0.74 to 0.81. The most relevant RFs (pH, induction, and previous C-section) in the CTREEs showed the highest ORs in the logistic models. The DA of the RFM and its most relevant interaction terms was even higher (AUC = 0.94; 95% CI: 0.93-0.95). CONCLUSION Putative fetal, maternal, and contextual RFs alone fail to achieve reasonable DA for ECS. It is the combination of these RFs and the interactions between them at each hospital that make it possible to improve the DA for the type of delivery and tailor interventions through prediction to improve the appropriateness of ECS indications.
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Affiliation(s)
- Carlos Campillo-Artero
- Centre for Research in Health and Economics, Universitat Pompeu Fabra, Barcelona, Spain
- Balearic Health Service, Palma de Mallorca, Spain
| | - Miquel Serra-Burriel
- Centre for Research in Health and Economics, Universitat Pompeu Fabra, Barcelona, Spain
- Balearic Health Service, Palma de Mallorca, Spain
- Universitat de Barcelona, Barcelona, Spain
- Centre for Research in Health and Economics, Universitat Pompeu Fabra, Barcelona, Spain
| | - Andrés Calvo-Pérez
- Hospital de Manacor, Obstetrics and Gynecology, Carretera Manacor Alcudia, Manacor, Balearic Islands, Majorca, Spain
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Merlo J, Mulinari S, Wemrell M, Subramanian SV, Hedblad B. The tyranny of the averages and the indiscriminate use of risk factors in public health: The case of coronary heart disease. SSM Popul Health 2017; 3:684-698. [PMID: 29349257 PMCID: PMC5769103 DOI: 10.1016/j.ssmph.2017.08.005] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2017] [Revised: 08/14/2017] [Accepted: 08/14/2017] [Indexed: 12/29/2022] Open
Abstract
Modern medicine is overwhelmed by a plethora of both established risk factors and novel biomarkers for diseases. The majority of this information is expressed by probabilistic measures of association such as the odds ratio (OR) obtained by calculating differences in average “risk” between exposed and unexposed groups. However, recent research demonstrates that even ORs of considerable magnitude are insufficient for assessing the ability of risk factors or biomarkers to distinguish the individuals who will develop the disease from those who will not. In regards to coronary heart disease (CHD), we already know that novel biomarkers add very little to the discriminatory accuracy (DA) of traditional risk factors. However, the value added by traditional risk factors alongside simple demographic variables such as age and sex has been the subject of less discussion. Moreover, in public health, we use the OR to calculate the population attributable fraction (PAF), although this measure fails to consider the DA of the risk factor it represents. Therefore, focusing on CHD and applying measures of DA, we re-examine the role of individual demographic characteristics, risk factors, novel biomarkers and PAFs in public health and epidemiology. In so doing, we also raise a more general criticism of the traditional risk factors’ epidemiology. We investigated a cohort of 6103 men and women who participated in the baseline (1991–1996) of the Malmö Diet and Cancer study and were followed for 18 years. We found that neither traditional risk factors nor biomarkers substantially improved the DA obtained by models considering only age and sex. We concluded that the PAF measure provided insufficient information for the planning of preventive strategies in the population. We need a better understanding of the individual heterogeneity around the averages and, thereby, a fundamental change in the way we interpret risk factors in public health and epidemiology. There is a plethora of differences in “average” risk between exposed and unexposed groups of individuals. Individual heterogeneity around average values is seldom considered in Public Health. Measures of discriminatory accuracy (DA) informs on the underlying individual heterogeneity. Most know risk factors and other categorizations associated with diseases have low DA. We need a fundamental change in the way we investigate risk factors and other categorizations in Public Health.
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Key Words
- ACE, Average causal effect
- AUC, Area under the ROC curve
- CABG, Coronary artery bypass graft
- CHD, Coronary heart disease
- CRP, C-reactive protein
- Coronary heart disease
- DA, Discriminatory accuracy
- Discriminatory accuracy
- FPF, False positive fraction
- HDL, High-density lipoprotein cholesterol
- HR, Hazard ratios
- ICE, Individual causal effect
- Individual heterogeneity
- LDL, Low-density lipoprotein cholesterol
- Lp-PLA2, Lipoprotein-associated phospholipase A2
- MDC study, The Malmö Diet and Cancer
- Multilevel analysis
- NTBNP, N-terminal pro–brain natriuretic peptide
- OR, Odds ratio
- Over-diagnosis
- Overtreatment
- PAF, Population attributable fraction
- PAH, Phenylalanine hydroxylase
- PCI, Percutaneous coronary intervention
- PKU, Phenylketonuria
- Population attributable fraction
- RCT, Randomized clinical trial
- ROC, Receiver operating characteristic
- RR, Relative risk
- Risk factors
- TPF, True positive fraction
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Affiliation(s)
- Juan Merlo
- Unit of Social Epidemiology, CRC, Faculty of Medicine, Lund University, Sweden.,Center for Primary Health Care Research, Region Skåne, Malmö, Sweden
| | - Shai Mulinari
- Unit of Social Epidemiology, CRC, Faculty of Medicine, Lund University, Sweden.,Department of Sociology, Faculty of Social Sciences, Lund University, Lund, Sweden
| | - Maria Wemrell
- Unit of Social Epidemiology, CRC, Faculty of Medicine, Lund University, Sweden
| | - S V Subramanian
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Bo Hedblad
- Unit for Cardiovascular Epidemiology, CRC, Faculty of Medicine, Lund University, Sweden
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Rodriguez-Lopez M, Wagner P, Perez-Vicente R, Crispi F, Merlo J. Revisiting the discriminatory accuracy of traditional risk factors in preeclampsia screening. PLoS One 2017; 12:e0178528. [PMID: 28542517 PMCID: PMC5444844 DOI: 10.1371/journal.pone.0178528] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Accepted: 05/15/2017] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Preeclampsia (PE) is associated with a high risk of perinatal morbidity and mortality. However, there is no consensus in the definition of high-risk women. AIM To question current definition of high PE risk and propose a definition that considers individual heterogeneity to improves risk classification. METHODS A stratified analysis by parity was conducted using the Swedish Birth Register between 2002-2010 including 626.600 pregnancies. The discriminatory accuracy (DA) of traditional definitions of high-risk women was compared with a new definition based on 1) specific combinations of individual variables and 2) a centile cut-off of the probability of PE predicted by a multiple logistic regression model. RESULTS None of the classical risk-factors alone reached an acceptable DA. In multiparous, any combination of a risk-factor with previous PE or HBP reached a +LR>10. The combination of obesity and multiple pregnancy reached a good DA particularly in the presence of previous preeclampsia (positive likelihood ratio (LR+) = 26.5 or chronic hypertension (HBP) LR+ = 40.5. In primiparous, a LR+>15 was observed in multiple pregnancies with the simultaneous presence of obesity and diabetes mellitus or with HBP. Predicted probabilities above 97 centile in multiparous and 99 centile in primiparous provided high (LR+ = 12.5), and moderate (LR+ = 5.85), respectively. No one risk factor alone or in combination provided a LR- sufficiently low to rule-out the disease. CONCLUSIONS In preeclampsia prediction the combination of specific risk factors provided a better discriminatory accuracy than traditional single risk approach. Our results contribute to a more personalized risk estimation of preeclampsia.
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Affiliation(s)
- Merida Rodriguez-Lopez
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
- Fetal i+D Fetal Medicine Research Center, BCNatal—Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), Institut Clínic de Ginecologia, Obstetricia i Neonatologia, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Universitat de Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Philippe Wagner
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
| | - Raquel Perez-Vicente
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
| | - Fatima Crispi
- Fetal i+D Fetal Medicine Research Center, BCNatal—Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), Institut Clínic de Ginecologia, Obstetricia i Neonatologia, Institut d'Investigacions Biomèdiques August Pi i Sunyer, Universitat de Barcelona, and Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain
| | - Juan Merlo
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden
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11
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Axelsson Fisk S, Merlo J. Absolute rather than relative income is a better socioeconomic predictor of chronic obstructive pulmonary disease in Swedish adults. Int J Equity Health 2017; 16:70. [PMID: 28472960 PMCID: PMC5418843 DOI: 10.1186/s12939-017-0566-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2017] [Accepted: 04/25/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND While psychosocial theory claims that socioeconomic status (SES), acting through social comparisons, has an important influence on susceptibility to disease, materialistic theory says that socioeconomic position (SEP) and related access to material resources matter more. However, the relative role of SEP versus SES in chronic obstructive pulmonary disease (COPD) risk has still not been examined. METHOD We investigated the association between SES/SEP and COPD risk among 667 094 older adults, aged 55 to 60, residing in Sweden between 2006 and 2011. Absolute income in five groups by population quintiles depicted SEP and relative income expressed as quintile groups within each absolute income group represented SES. We performed sex-stratified logistic regression models to estimate odds ratios and the area under the receiver operator curve (AUC) to compare the discriminatory accuracy of SES and SEP in relation to COPD. RESULTS Even though both absolute (SEP) and relative income (SES) were associated with COPD risk, only absolute income (SEP) presented a clear gradient, so the poorest had a three-fold higher COPD risk than the richest individuals. While the AUC for a model including only age was 0.54 and 0.55 when including relative income (SES), it increased to 0.65 when accounting for absolute income (SEP). SEP rather than SES demonstrated a consistent association with COPD. CONCLUSIONS Our study supports the materialistic theory. Access to material resources seems more relevant to COPD risk than the consequences of low relative income.
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Affiliation(s)
- Sten Axelsson Fisk
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, CRC, Jan Waldeströms gata, 35, S-205 02 Malmö, Sweden
| | - Juan Merlo
- Unit for Social Epidemiology, Faculty of Medicine, Lund University, CRC, Jan Waldeströms gata, 35, S-205 02 Malmö, Sweden
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Mulinari S, Wemrell M, Rönnerstrand B, Subramanian SV, Merlo J. Categorical and anti-categorical approaches to US racial/ethnic groupings: revisiting the National 2009 H1N1 Flu Survey (NHFS). CRITICAL PUBLIC HEALTH 2017. [DOI: 10.1080/09581596.2017.1316831] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Affiliation(s)
- Shai Mulinari
- Faculty of Social Sciences, Department of Sociology, Lund University, Lund, Sweden
- Faculty of Medicine, Department of Clinical Sciences, Unit of Social Epidemiology, Lund University, Malmö, Sweden
| | - Maria Wemrell
- Faculty of Medicine, Department of Clinical Sciences, Unit of Social Epidemiology, Lund University, Malmö, Sweden
| | - Björn Rönnerstrand
- Department of Political Science, University of Gothenburg, Göteborg, Sweden
| | - S. V. Subramanian
- Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, MA, USA
| | - Juan Merlo
- Faculty of Medicine, Department of Clinical Sciences, Unit of Social Epidemiology, Lund University, Malmö, Sweden
- Center for Primary Health Care Research, Region Skåne, Malmö, Sweden
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Wemrell M, Mulinari S, Merlo J. An intersectional approach to multilevel analysis of individual heterogeneity (MAIH) and discriminatory accuracy. Soc Sci Med 2017; 178:217-219. [PMID: 28274599 DOI: 10.1016/j.socscimed.2017.02.040] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Accepted: 02/28/2017] [Indexed: 12/14/2022]
Affiliation(s)
- Maria Wemrell
- Unit of Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden.
| | - Shai Mulinari
- Unit of Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden; Department of Sociology, Faculty of Social Sciences, Lund University, Lund, Sweden
| | - Juan Merlo
- Unit of Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden; Center for Primary Health Research, Region Skåne, Malmö, Sweden
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Wemrell M, Mulinari S, Merlo J. Intersectionality and risk for ischemic heart disease in Sweden: Categorical and anti-categorical approaches. Soc Sci Med 2017; 177:213-222. [PMID: 28189024 DOI: 10.1016/j.socscimed.2017.01.050] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Revised: 01/17/2017] [Accepted: 01/23/2017] [Indexed: 12/13/2022]
Abstract
Intersectionality theory can contribute to epidemiology and public health by furthering understanding of power dynamics driving production of health disparities, and increasing knowledge about heterogeneities within, and overlap between, social categories. Drawing on McCall, we relate the first of these potential contributions to categorical intersectionality and the second to anti-categorical intersectionality. Both approaches are used in study of risk of ischemic heart disease (IHD), based on register data on 3.6 million adults residing in Sweden by 2010, followed for three years. Categorical intersectionality is here coupled with between-group differences in average risk calculation, as we use intersectional categorizations while estimating odds ratios through logistic regressions. The anti-categorical approach is operationalized through measurement of discriminatory accuracy (DA), i.e., capacity to accurately categorize individuals with or without a certain outcome, through computation of the area under the curve (AUC). Our results show substantial differences in average risk between intersectional groupings. The DA of social categorizations is found to be low, however, due to outcome variability within and overlap between categories. We argue that measures of DA should be used for proper interpretation of differences in average risk between social (or any other) categories. Tension between average between-group risk and the DA of categorizations, which can be related to categorical and anti-categorical intersectional analyses, should be made explicit and discussed to a larger degree in epidemiology and public health.
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Affiliation(s)
- Maria Wemrell
- Unit of Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden.
| | - Shai Mulinari
- Unit of Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden; Department of Sociology, Faculty of Social Sciences, Lund University, Lund, Sweden
| | - Juan Merlo
- Unit of Social Epidemiology, Faculty of Medicine, Lund University, Malmö, Sweden; Center for Primary Health Research, Region Skåne, Malmö, Sweden
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