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  • 1.
    Andersson, Björn
    et al.
    Statistiska institutionen, Uppsala universitet.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Sensitivity analysis of violations of the faithfulness assumption2014In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 84, no 7, p. 1608-1620Article in journal (Other academic)
    Abstract [en]

    We study implications of violations of the fatihfulness condition due to parameter cancellations on estimation of the DAG skeleton. Three settings are investigated: when i) faithfulness is guaranteed ii) faithfulness is not guaranteed and iii) the parameter distributions are concentrated around unfaithfulness (near-unfaithfulness). In a simulation study the effetcs of the different settings are compared using the PC and MMPC algorithms. The results show that the performance in the faithful case is almost unchanged compared to the unrestricted case whereas there is a general decrease in performance under the near-unfaithful case as compared to the unrestricted case. The response to near-unfaithful parameterisations is similar between two algorithms, with the MMPC algorithm having higher true positive rates and the PC algorithm having lower false positive rates.

  • 2.
    Berhan, Yonas
    et al.
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Eliasson, Mats
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Möllsten, Anna
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Dahlquist, Gisela
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Impact of Parental Socioeconomic Status on Excess Mortality in a Population-Based Cohort of Subjects With Childhood-Onset Type 1 Diabetes2015In: Diabetes Care, ISSN 0149-5992, E-ISSN 1935-5548, Vol. 38, no 5, p. 827-832Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: The aim of this study was to analyze the possible impact of parental and individual socioeconomic status (SES) on all-cause mortality in a population-based cohort of patients with childhood-onset type 1 diabetes.

    RESEARCH DESIGN AND METHODS: Subjects recorded in the Swedish Childhood Diabetes Registry (SCDR) from 1 January 1978 to 31 December 2008 were included (n =14,647). The SCDR was linked to the Swedish Cause of Death Registry (CDR) and the Longitudinal Integration Database for Health Insurance and Labour Market Studies (LISA).

    RESULTS: At a mean follow-up of 23.9 years (maximum 46.5 years), 238 deaths occurred in a total of 349,762 person-years at risk. In crude analyses, low maternal education predicted mortality for male patients only (P = 0.046), whereas parental income support predicted mortality in both sexes (P < 0.001 for both). In Cox models stratified by age-at-death group and adjusted for age at onset and sex, parental income support predicted mortality among young adults (≥18 years of age) but not for children. Including the adult patient’s own SES in a Cox model showed that individual income support to the patient predicted mortality occurring at ≥24 years of age when adjusting for age at onset, sex, and parental SES.

    CONCLUSIONS: Exposure to low SES, mirrored by the need for income support, increases mortality risk in patients with childhood-onset type 1 diabetes who died after the age of 18 years.

  • 3.
    Berhan, Yonas
    et al.
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Eliasson, Mats
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Möllsten, Anna
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Dahlquist, Gisela
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Impact of parental socioeconomic status on excess mortality in subjects with childhood onset type-1 diabetesManuscript (preprint) (Other academic)
    Abstract [en]

    Aims/Hypothesis: The aim of this study was to analyze the possible impact of parental and individual socioeconomic status (SES) on all cause mortality in a population based cohort of childhood onset T1D.

    Methods: Subjects recorded in the Swedish Childhood Diabetes Registry (SCDR) January 1 1978 to December 31 2008 were included (n=14 409). The SCDR was linked to the Swedish Cause of Death Register (CDR) and the Longitudinal Integration Database for Health Insurance and Labour Market Studies (LISA). SES measures (education and income support) wtypeere retrieved from the LISA for the years 1990-2010. Mortality data were retrieved from the CDR as of December 31, 2010.

    Results: At a mean follow-up of 24.4 years (maximum 47.5), 238 deaths occurred in a total of 357 048 person-years at risk. In crude analyses, low maternal education predicted mortality for male cases only (p=0.046), while parental income support predicted mortality in both sexes (p<0.001 for both). In Cox models stratified by age at death groups and adjusted for age at onset and sex, parental income support predicted mortality among young adults ( ≥18 years of age) but not for children. Including the adult patient´s own SES in a Cox model showed that individual income support to the patient predicted mortality occurring at ≥ 24 years of age when adjusting for age at onset, sex and parental SES.

    Conclusions/Interpretation: Low parental SES, mirrored by the need of income support, increases mortality risk in childhood onset type-1 diabetics who died after the age of 18 years.

  • 4.
    Berhan, Yonas
    et al.
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Lind, Torbjörn
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Möllsten, Anna
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Dahlqvist, Gisela
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Thirty years of prospective nationwide incidence of childhood type 1 diabetes: the accelerating increase by time tends to level off in Sweden.2011In: Diabetes, ISSN 0012-1797, E-ISSN 1939-327X, Vol. 60, no 2, p. 577-81Article in journal (Refereed)
    Abstract [en]

    Childhood T1D increased dramatically and shifted to a younger age at onset the first 22 years of the study period. We report a reversed trend, starting in 2000, indicating a change in nongenetic risk factors affecting specifically young children.

  • 5.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Statistics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Statistics.
    Covariate selection for non-parametric estimation of treatment effects2005Report (Other academic)
  • 6.
    de Luna, Xavier
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Richardson, Thomas
    Department of Statistics, University of Washington, Box 354322, Washington 98195-4322 Seattle, U.S.A..
    Covariate selection for the non-parametric estimation of an average treatment effect2011In: Biometrika, ISSN 0006-3444, E-ISSN 1464-3510, Vol. 98, no 4, p. 861-875Article in journal (Refereed)
    Abstract [en]

    Observational studies in which the effect of a nonrandomized treatment on an outcome of interest is estimated are common in domains such as labour economics and epidemiology. Such studies often rely on an assumption of unconfounded treatment when controlling for a given set of observed pre-treatment covariates. The choice of covariates to control in order to guarantee unconfoundedness should primarily be based on subject matter theories, although the latter typically give only partial guidance. It is tempting to include many covariates in the controlling set to try to make the assumption of an unconfounded treatment realistic. Including unnecessary covariates is suboptimal when the effect of a binary treatment is estimated nonparametrically. For instance, when using a n1/2-consistent estimator, a loss of efficiency may result from using covariates that are irrelevant for the unconfoundedness assumption. Moreover, bias may dominate the variance when many covariates are used. Embracing the Neyman–Rubin model typically used in conjunction with nonparametric estimators of treatment effects, we characterize subsets from the original reservoir of covariates that are minimal in the sense that the treatment ceases to be unconfounded given any proper subset of these minimal sets. These subsets of covariates are shown to be identified under mild assumptions. These results lead us to propose data-driven algorithms for the selection of minimal sets of covariates.

  • 7.
    Fowler, Philip
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Data-driven Coarsening of Covariates for Causal InferenceManuscript (preprint) (Other academic)
  • 8.
    Hedström, Erik
    et al.
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Incidence of fractures among children and adolescents in rural and urban communities: analysis based on 9,965 fracture events2014In: Injury Epidemiology, ISSN 2197-1714, Vol. 1, no 14Article in journal (Refereed)
    Abstract [en]

    Background: Previous work has explored the significance of residence on injuries. A number of articles reported higher rates of injury in rural as compared to urban settings. This study aimed to evaluate the importance of residency on the occurrence of fractures among children and adolescents within a region in northern Sweden.

    Methods: In a population based study with data from an injury surveillance registry at a regional hospital, we have investigated the importance of sex, age and place of residency for the incidence of fractures among children and adolescents 0-19 years of age using a Poisson logistic regression analysis. Data was collected between 1998 and 2011.

    Results: The dataset included 9,965 cases. Children and adolescents growing up in the most rural communities appeared to sustain fewer fractures than their peers in an urban municipality, risk ratio 0.81 (0.76-0.86). Further comparisons of fracture rates in the urban and rural municipalities revealed that differences were most pronounced for sports related fractures and activities in school in the second decade of life.

    Conclusion: Results indicate that fracture incidence among children and adolescents is affected by place of residency. Differences were associated with activity at injury and therefore we have discussed the possibility that this effect was due to the influence of place on activity patterns.

    The results suggest it is of interest to explore how geographic and demographic variables affect the injury pattern further.

  • 9.
    Häggström, Jenny
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Persson, Emma
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    CovSel: An R Package for Covariate Selection When Estimating Average Causal Effects2015In: Journal of Statistical Software, ISSN 1548-7660, E-ISSN 1548-7660, Vol. 68, no 1, p. 1-20Article in journal (Refereed)
    Abstract [en]

    We describe the R package CovSel, which reduces the dimension of the covariate vector for the purpose of estimating an average causal effect under the unconfoundedness assumption. Covariate selection algorithms developed in De Luna, Waernbaum, and Richardson (2011) are implemented using model-free backward elimination. We show how to use the package to select minimal sets of covariates. The package can be used with continuous and discrete covariates and the user can choose between marginal co-ordinate hypothesis tests and kernel-based smoothing as model-free dimension reduction techniques.

  • 10.
    Lind, Torbjörn
    et al.
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Berhan, Yonas
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Dahlquist, Gisela
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Socioeconomic factors, rather than diabetes mellitus per se, contribute to an excessive use of antidepressants among young adults with childhood onset type 1 diabetes mellitus: a register-based study2012In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 55, no 3, p. 617-624Article in journal (Refereed)
    Abstract [en]

    AIMS/HYPOTHESIS: Mood disorders, including depression, are suggested to be prevalent in persons with type 1 diabetes and may negatively affect self-management and glycaemic control and increase the risk of diabetic complications. The aim of this study was to analyse the prevalence of antidepressant (AD) use in adults with childhood onset type 1 diabetes and to compare risk determinants for AD prescription among diabetic patients and a group of matched controls. METHODS: Young adults ≥18 years on 1 January 2006 with type 1 diabetes (n = 7,411) were retrieved from the population-based Swedish Childhood Diabetes Registry (SCDR) and compared with 30,043 age- and community-matched controls. Individual level data were collected from the Swedish National Drug Register (NDR), the Hospital Discharge Register (HDR) and the Labor Market Research database (LMR). RESULTS: ADs were prescribed to 9.5% and 6.8% of the type 1 diabetes and control subjects, respectively. Female sex, having received economic or other social support, or having a disability pension were the factors with the strongest association with AD prescription in both groups. Type 1 diabetes was associated with a 44% (OR 1.44, 95% CI 1.32, 1.58) higher risk of being prescribed ADs in crude analysis. When adjusting for potential confounders including sex, age and various socioeconomic risk factors, this risk increase was statistically non-significant (OR 1.11, 95% CI 0.99, 1.21). CONCLUSIONS/INTERPRETATION: The risk factor patterns for AD use are similar among type 1 diabetic patients and controls, and socioeconomic risk factors, rather than the diabetes per se, contribute to the increased risk of AD use in young adults with type 1 diabetes.

  • 11.
    Möllsten, Anna
    et al.
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Svensson, Maria
    Department of Nephrology, Sahlgrenska University Hospital, Gothenburg, Sweden.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Berhan, Yonas
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Schön, Staffan
    Department of Internal Medicine, Ryhov County Hospital, Jönköping, Sweden.
    Nyström, Lennarth
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.
    Arnqvist, Hans J.
    Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
    Dahlquist, Gisela
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Cumulative risk, age at onset, and sex-specific differences for developing end-stage renal disease in young patients with type 1 diabetes: A nationwide population-based cohort study2010In: Diabetes, ISSN 0012-1797, E-ISSN 1939-327X, Vol. 59, no 7, p. 1803-1808Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE—This study aimed to estimate the current cumulativerisk of end-stage renal disease (ESRD) due to diabeticnephropathy in a large, nationwide, population-based prospectivetype 1 diabetes cohort and specifically study the effects ofsex and age at onset.RESEARCH DESIGN AND METHODS—In Sweden, all incidentcases of type 1 diabetes aged 0–14 years and 15–34 years arerecorded in validated research registers since 1977 and 1983,respectively. These registers were linked to the Swedish RenalRegistry, which, since 1991, collects data on patients who receiveactive uremia treatment. Patients with 13 years duration of type1 diabetes were included (n 11,681).RESULTS—During a median time of follow-up of 20 years, 127patients had developed ESRD due to diabetic nephropathy. Thecumulative incidence at 30 years of type 1 diabetes duration waslow, with a male predominance (4.1% [95% CI 3.1–5.3] vs. 2.5%[1.7–3.5]). In both male and female subjects, onset of type 1diabetes before 10 years of age was associated with the lowestrisk of developing ESRD. The highest risk of ESRD was found inmale subjects diagnosed at age 20–34 years (hazard ratio 3.0 [95%CI 1.5–5.7]). In female subjects with onset at age 20–34 years, therisk was similar to patients’ diagnosed before age 10 years.CONCLUSIONS—The cumulative incidence of ESRD is exceptionallylow in young type 1 diabetic patients in Sweden. There isa striking difference in risk for male compared with femalepatients. The different patterns of risk by age at onset and sexsuggest a role for puberty and sex hormones.

  • 12.
    Pazzagli, Laura
    et al.
    University of Perugia, Department of Economics, Division of Statistics.
    Möllsten, Anna
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Marginal structural model to evaluate the joint effect of socioeconomic exposures on the risk of developing end-stage renal disease in patients with type 1 diabetes: a longitudinal study based on data from the Swedish Childhood Diabetes Study Group2017In: Annals of Epidemiology, ISSN 1047-2797, E-ISSN 1873-2585, Vol. 27, no 8, p. 479-484Article in journal (Refereed)
    Abstract [en]

    Purpose: Diabetic nephropathy is a severe complication of type 1 diabetes (T1D) that may lead to renal failure and end-stage renal disease (ESRD) demanding dialysis and transplantation. The aetiology of diabetic nephropathy is multifactorial and both genes and environmental and life style related factors are involved. In this study we investigate the effect of the socioeconomic exposures unemployment and receiving income support on the development of ESRD in T1D patients, using a marginal structural model in comparison with standard logistic regression models.

    Methods: The study is based on the Swedish Childhood Diabetes Register which in 1977 started to register patients developing T1D before 15 years of age. In the analyses we include patients born between 1965 and 1979, developing diabetes between 1977 and 1994, followed until 2013 (n=4034). A marginal structural model (MSM) was fitted to adjust for both baseline and time-varying confounders.

    Results: The main results of the analysis indicate that being unemployed for more than one year and receiving income support are risk factors for the development of ESRD. Multiple exposure over time to these risk factors increases the risk associated with the disease.

    Conclusions: Using a MSM is an advanced method well suited to investigate the effect of exposures on the risk of complications of a chronic disease with longitudinal data. The results show that socioeconomic disadvantage increases the risk of developing ESRD in patients with type 1 diabetes.

  • 13.
    Persson, Emma
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Häggström, Jenny
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    de Luna, Xavier
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Data-driven algorithms for dimension reduction in causal inference2017In: Computational Statistics & Data Analysis, ISSN 0167-9473, E-ISSN 1872-7352, Vol. 105, p. 280-292Article in journal (Refereed)
    Abstract [en]

    In observational studies, the causal effect of a treatment may be confounded with variables that are related to both the treatment and the outcome of interest. In order to identify a causal effect, such studies often rely on the unconfoundedness assumption, i.e., that all confounding variables are observed. The choice of covariates to control for, which is primarily based on subject matter knowledge, may result in a large covariate vector in the attempt to ensure that unconfoundedness holds. However, including redundant covariates can affect bias and efficiency of nonparametric causal effect estimators, e.g., due to the curse of dimensionality. In this paper, data-driven algo- rithms for the selection of sufficient covariate subsets are investigated. Under the assumption of unconfoundedness we search for minimal subsets of the covariate vector. Based on the framework of sufficient dimension reduction or kernel smoothing, the algorithms perform a backward elim- ination procedure testing the significance of each covariate. Their performance is evaluated in simulations and an application using data from the Swedish Childhood Diabetes Register is also presented.

  • 14.
    Persson, Emma
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Estimating a marginal causal odds ratio in a case-control design: analyzing the effect of low birth weight on the risk of type 1 diabetes mellitus2013In: Statistics in Medicine, ISSN 0277-6715, E-ISSN 1097-0258, Vol. 32, no 14, p. 2500-2512Article in journal (Refereed)
    Abstract [en]

    Estimation of marginal causal effects from case-control data has two complications: (i) confounding due to the fact that the exposure under study is not randomized, and (ii) bias from the case-control sampling scheme. In this paper, we study estimators of the marginal causal odds ratio, addressing these issues for matched and unmatched case-control designs when utilizing the knowledge of the known prevalence of being a case. The estimators are implemented in simulations where their finite sample properties are studied and approximations of their variances are derived with the delta method. Also, we illustrate the methods by analyzing the effect of low birth weight on the risk of type 1 diabetes mellitus using data from the Swedish Childhood Diabetes Register, a nationwide population-based incidence register.

  • 15.
    Persson, Emma
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Lind, Torbjörn
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Estimating marginal causal effects in a secondary analysis of case-control data2017In: Statistics in Medicine, ISSN 0277-6715, E-ISSN 1097-0258, Vol. 36, no 15, p. 2404-2419Article in journal (Refereed)
    Abstract [en]

    When an initial case-control study is performed, data can be used in a secondary analysis to evaluate the effect of the case-defining event on later outcomes. In this paper, we study the example in which the role of the event is changed from a response variable to a treatment of interest. If the aim is to estimate marginal effects, such as average effects in the population, the sampling scheme needs to be adjusted for. We study estimators of the average effect of the treatment in a secondary analysis of matched and unmatched case-control data where the probability of being a case is known. For a general class of estimators, we show the components of the bias resulting from ignoring the sampling scheme and demonstrate a design-weighted matching estimator of the average causal effect. In simulations, the finite sample properties of the design-weighted matching estimator are studied. Using a Swedish diabetes incidence register with a matched case-control design, we study the effect of childhood onset diabetes on the use of antidepressant medication as an adult.

  • 16. Petrauskiene, V
    et al.
    Falk, M
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Norberg, Margareta
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Public Health Sciences.
    Eriksson, Jan
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    The risk of venous thromboembolism is markedly elevated in patients with diabetes2005In: Diabetologia, Vol. 48, p. 1017–1021-Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: To survey unnatural deaths among teenagers in northern Sweden and to suggest preventive measures. SETTING: The four northernmost counties (908,000 inhabitants, 1991), forming 55% of the area of Sweden. MATERIAL AND METHODS: All unnatural teenager deaths from 1981 through 2000 were identified in the databases of the Department of Forensic Medicine in Umea, National Board of Forensic Medicine. Police reports and autopsy findings were always studied, social and hospital records if present. RESULTS: Three hundred and fifty-five deaths were found, of which 267 (75%) were males and 88 (25%) females. Ninety out of 327 (28%) tested positive for alcohol. Two hundred and forty-eight (70%) were unintentional and 102 (30%) were intentional deaths, and five (1%) were categorized as undetermined manner of death. Unintentional deaths decreased while the incidence of intentional deaths remained unaffected by time. CONCLUSIONS: Injury-reducing measures have been effective concerning unintentional deaths and the fall in young licensed drivers due to the economical recess have probably also contributed to the decrease. However, there were no signs of decreasing numbers of suicides during the study period, which calls for resources to be allocated to suicide prevention.

  • 17. Pingel, Ronnie
    et al.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Institutet för arbetsmarknads- och utbildningspolitisk utvärdering, IFAU.
    Correlation and Efficiency of Propensity Score-based Estimators for Average Causal Effects2017In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 46, no 5, p. 3458-3478Article in journal (Refereed)
    Abstract [en]

    Propensity score based-estimators are commonly used to estimate causal effects in evaluationresearch. To reduce bias in observational studies researchers might be tempted to include many, perhaps correlated, covariates when estimating the propensity score model. Taking into account that the propensity score is estimated, this study investigates how the efficiency of matching, inverse probability weighting and doubly robust estimators change under the case of correlated covariates. Propositions regarding the large sample variances under certain assumptions on the data generating process are given. The propositions are supplemented by several numerical large sample and finite sample results from a wide range of models. The results show that the covariate correlations may increase or decrease the variances of the estimators. There are several factors that influence how correlation affects the variance of the estimators, including the choice of estimator, the strength of the confounding towards outcome and treatment, and whether a constant or non-constant causal effect is present.

  • 18. Pingel, Ronnie
    et al.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics. Institute for Evaluation of Labour Market and Education Policy, Uppsala, Sweden.
    Effects of correlated covariates on the asymptotic efficiency of matching and inverse probability weighting estimators for causal inference2015In: Statistics (Berlin), ISSN 0233-1888, E-ISSN 1029-4910, Vol. 49, no 4, p. 795-814Article in journal (Refereed)
    Abstract [en]

    In observational studies, the overall aim when fitting a model for the propensity score is to reduce bias for an estimator of the causal effect. To make the assumption of an unconfounded treatment plausible researchers might include many, possibly correlated, covariates in the propensity score model. In this paper, we study how the asymptotic efficiency of matching and inverse probability weighting estimators for average causal effects change when the covariates are correlated. We investigate the case with multivariate normal covariates, a logistic model for the propensity score and linear models for the potential outcomes and show results under different model assumptions. We show that the correlation can both increase and decrease the large sample variances of the estimators, and that the correlation affects the asymptotic efficiency of the estimators differently, both with regard to direction and magnitude. Moreover, the strength of the confounding towards the outcome and the treatment plays an important role.

  • 19.
    Svensson, Maria
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Sundkvist, Göran
    Arnqvist, Hans J
    Björk, Elisabeth
    Blohmé, Göran
    Bolinder, Jan
    Henricsson, Marianne
    Nyström, Lennarth
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Public Health Sciences.
    Torffvit, Ole
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Östman, Jan
    Eriksson, Jan W
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Signs of nephropathy may occur early in young adults with diabetes despite modern diabetes management: Results from the nationwide population-based Diabetes Incidence Study in Sweden (DISS)2003In: Diabetes Care, Vol. 26, p. 2903-2909Article in journal (Refereed)
  • 20.
    Toppe, Cecilia
    et al.
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics. Department of Internal Medicine, Ryhov County Hospital, Jönköping, Sweden.
    Möllsten, Anna
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Schön, Staffan
    Swedish Renal Registry, Jönköping, Sweden.
    Gudbjörnsdottir, Soffia
    Swedish National Diabetes Register, Gothenburg, Sweden.
    Landin-Olsson, Mona
    Diabetes Incidence Study in Sweden Department of Clinical Sciences, Lund University, Lund, Sweden.
    Dahlquist, Gisela
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Decreasing Cumulative Incidence of End-Stage Renal Disease in Young Patients With Type 1 Diabetes in Sweden: a 38-Year Prospective Nationwide Study2019In: Diabetes Care, ISSN 0149-5992, E-ISSN 1935-5548, Vol. 42, no 1, p. 27-31Article in journal (Refereed)
    Abstract [en]

    Objective: Diabetic nephropathy is a serious complication of type 1 diabetes. Recent studies indicate that end-stage renal disease (ESRD) incidence has decreased or that the onset of ESRD has been postponed; therefore, we wanted to analyze the incidence and time trends of ESRD in Sweden.

    Research design and methods: In this study, patients with duration of type 1 diabetes >14 years and age at onset of diabetes 0–34 years were included. Three national diabetes registers were used: the Swedish Childhood Diabetes Register, the Diabetes Incidence Study in Sweden, and the National Diabetes Register. The Swedish Renal Registry, a national register on renal replacement therapy, was used to identify patients who developed ESRD.

    Results: We found that the cumulative incidence of ESRD in Sweden was low after up to 38 years of diabetes duration (5.6%). The incidence of ESRD was lower in patients with type 1 diabetes onset in 1991–2001 compared to onset in 1977–1984 and 1985–1990, independently of diabetes duration.

    Conclusion: The risk of developing ESRD in Sweden in this population is still low and also seems to decrease with time.

  • 21.
    Waernbaum, I
    et al.
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Blohmé, G
    Ostman, J
    Sundkvist, G
    Eriksson, Jan
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Arnqvist, H J
    Bolinder, J
    Nyström, Lennarth
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Public Health Sciences.
    Excess mortality in incident cases of diabetes mellitus aged 15 to 34 years at diagnosis: a population-based study (DISS) in Sweden.2006In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 49, no 4, p. 653-659Article in journal (Refereed)
  • 22.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Covariate selection and propensity score specification in causal inference2008Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis makes contributions to the statistical research field of causal inference in observational studies. The results obtained are directly applicable in many scientific fields where effects of treatments are investigated and yet controlled experiments are difficult or impossible to implement.

    In the first paper we define a partially specified directed acyclic graph (DAG) describing the independence structure of the variables under study. Using the DAG we show that given that unconfoundedness holds we can use the observed data to select minimal sets of covariates to control for. General covariate selection algorithms are proposed to target the defined minimal subsets.

    The results of the first paper are generalized in Paper II to include the presence of unobserved covariates. Morevoer, the identification assumptions from the first paper are relaxed.

    To implement the covariate selection without parametric assumptions we propose in the third paper the use of a model-free variable selection method from the framework of sufficient dimension reduction. By simulation the performance of the proposed selection methods are investigated. Additionally, we study finite sample properties of treatment effect estimators based on the selected covariate sets.

    In paper IV we investigate misspecifications of parametric models of a scalar summary of the covariates, the propensity score. Motivated by common model specification strategies we describe misspecifications of parametric models for which unbiased estimators of the treatment effect are available. Consequences of the misspecification for the efficiency of treatment effect estimators are also studied.

  • 23.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Model misspecification and robustness in causal inference: comparing matching with doubly robust estimation2012In: Statistics in Medicine, ISSN 0277-6715, E-ISSN 1097-0258, Vol. 31, no 15, p. 1572-1581Article in journal (Refereed)
    Abstract [en]

    In this paper we compare the robustness properties of a matching estimator with a doubly robust estimator. We describe the robustness properties of matching and subclassification estimators by showing how misspecification of the propensity score model cam result in consistent estimation of the average causal effect. The propensity scores are covariate scores, which are a class of functions that removes bias due to all observed covariates. When matching on a parametric model (e.g. a propensity or prognostic score), the matching estimator is robust to model misspecifications if the misspecified model belongs to the class of covariate scores. The implication is that there are multiple possibilities for the matching estimator in contrast to the doubly robust estimator in which the researcher has two chances to make reliable inference. In simulations, we compare the finite sample properties of the matching estimator with a simple inverse probability weighting estimator and a doubly robust estimator. For the misspecifications in our study the mean square error of the matching estimator is smaller than the mean square error of both the simple inverse probability weighting estimator and the doubly robust estimator-

  • 24.
    Waernbaum, Ingeborg
    Umeå University, Faculty of Social Sciences, Department of Statistics.
    Propensity score model specification for estimation of average treatment effects2010In: Journal of Statistical Planning and Inference, ISSN 0378-3758, E-ISSN 1873-1171, Vol. 140, no 7, p. 1948-1956Article in journal (Refereed)
    Abstract [en]

    Treatment effect estimators that utilize the propensity score as a balancing score, e.g., matching and blocking estimators are robust to misspecifications of the propensity score model when the misspecification is a balancing score. Such misspecifications arise from using the balancing property of the propensity score in the specification procedure. Here, we study misspecifications of a parametric propensity score model written as a linear predictor in a strictly monotonic function, e.g. a generalized linear model representation. Under mild assumptions we show that for misspecifications, such as not adding enough higher order terms or choosing the wrong link function, the true propensity score is a function of the misspecified model. Hence, the latter does not bring bias to the treatment effect estimator. It is also shown that a misspecification of the propensity score does not necessarily lead to less efficient estimation of the treatment effect. The results of the paper are highlighted in simulations where different misspecifications are studied.

  • 25.
    Waernbaum, Ingeborg
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Dahlquist, Gisela
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Low mean temperature rather than few sunshine hours are associated with an increased incidence of type 1 diabetes in children2016In: European Journal of Epidemiology, ISSN 0393-2990, E-ISSN 1573-7284, Vol. 31, no 1, p. 61-65Article in journal (Refereed)
    Abstract [en]

    The well-known north-south gradient and the seasonal variability in incidence of childhood type1 diabetes indicate climatological factors to have an effect on the onset. Both sunshine hours and a low temperature may be responsible. In the present study we tried to disentangle these effects that tend to be strongly connected.

    Exposure data were sunshine hours and mean temperature respectively obtained from eleven meteorological stations in Sweden which were linked to incidence data from geographically matched areas. Incident cases during 1983-2008 were retrieved from the population based Swedish childhood diabetes register. We used generalized additive models to analyze the incidence as a function of mean temperature and hours of sun adjusted for the time trend, age and sex.

    In our data set the correlation between sun hours and temperature was weak (r=0.36) implying that it was possible to estimate the effect of these variables in a regression model. We fit a general additive model with a smoothing term for the time trend. In the model with sun hours we found no significant effect on T1 incidence (p=0.17) whereas the model with temperature as predictor was significant (p=0.05) when adjusting for the time trend, sex and age. Adding sun hours in the model where mean temperature was already present did not change the effect of temperature.

    There is an association with incidence of type1 diabetes in children and low mean temperature independent of a possible effect of sunshine hours after adjustment for age, sex and time trend. The findings may mirror the cold effect on insulin resistance and accords with the hypothesis that overload of an already ongoing beta cell destruction may accelerate disease onset.

  • 26.
    Waernbaum, Ingeborg
    et al.
    Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
    Dahlquist, Gisela
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Lind, Torbjörn
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Perinatal risk factors for type 1 diabetes revisited: a population-based register study2019In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 62, no 7, p. 1173-1184Article in journal (Refereed)
    Abstract [en]

    Aims/hypothesis: Single-centre studies and meta-analyses have found diverging results as to which early life factors affect the risk of type 1 diabetes during childhood. We wanted to use a large, nationwide, prospective database to further clarify and analyse the associations between perinatal factors and the subsequent risk for childhood-onset type 1 diabetes using a case–control design.

    Methods: The Swedish Childhood Diabetes Register was linked to the Swedish Medical Birth Register and National Patient Register, and 14,949 cases with type 1 diabetes onset at ages 0–14 years were compared with 55,712 matched controls born from the start of the Medical Birth Register in 1973 to 2013. After excluding confounders (i.e. children multiple births, those whose mother had maternal diabetes and those with a non-Nordic mother), we used conditional logistic regression analyses to determine risk factors for childhood-onset type 1 diabetes. We used WHO ICD codes for child and maternal diagnoses.

    Results: In multivariate analysis, there were small but statistically significant associations between higher birthweight z score (OR 1.08, 95% CI 1.06, 1.10), delivery by Caesarean section (OR 1.08, 95% CI 1.02, 1.15), premature rupture of membranes (OR 1.08, 95% CI 1.01, 1.16) and maternal urinary tract infection during pregnancy (OR 1.39, 95% CI 1.04, 1.86) and the subsequent risk of childhood-onset type 1 diabetes. Birth before 32 weeks of gestation was associated with a lower risk of childhood-onset type 1 diabetes compared with full-term infants (OR 0.54, 95% CI 0.38, 0.76), whereas birth between 32 and 36 weeks’ gestation was associated with a higher risk (OR 1.24, 95% CI 1.14, 1.35). In subgroup analyses (birth years 1992–2013), maternal obesity was independently associated with subsequent type 1 diabetes in the children (OR 1.27, 95% CI 1.15, 1.41) and rendered the association with Caesarean section non-significant. In contrast to previous studies, we found no association of childhood-onset type 1 diabetes with maternal–child blood-group incompatibility, maternal pre-eclampsia, perinatal infections or treatment of the newborn with phototherapy for neonatal jaundice. The proportion of children with neonatal jaundice was significantly higher in the 1973–1982 birth cohort compared with later cohorts.

    Conclusions/interpretation: Perinatal factors make small but statistically significant contributions to the overall risk of childhood-onset type 1 diabetes. Some of these risk factors, such as maternal obesity, may be amendable with improved antenatal care. Better perinatal practices may have affected some previously noted risk factors over time.

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