Excess mortality in Denmark, Finland, Norway and Sweden during the COVID-19 pandemic 2020-2022.

BACKGROUND: The Nordic countries represent a unique case study for the COVID-19 pandemic due to socioeconomic and cultural similarities, high-quality comparable administrative register data and notable differences in mitigation policies during the pandemic. We aimed to compare weekly excess mortality in the Nordic countries across the three full pandemic years 2020-2022. METHODS: Using data on weekly all-cause mortality from official administrative registers in Denmark, Finland, Norway and Sweden, we employed time series regression models to assess mortality developments within each pandemic year, with the period 2010-2019 used as reference period. We then compared excess mortality across the countries in 2020-2022, taking differences in population size and age- and sex-distribution into account. Results were age- and sex-standardized to the Danish population of 2020. Robustness was examined with a variety of sensitivity analyses. RESULTS: While Sweden experienced excess mortality in 2020 [75 excess deaths per 100 000 population (95% prediction interval 29-122)], Denmark, Finland and Norway experienced excess mortality in 2022 [52 (14-90), 130 (83-177) and 88 (48-128), respectively]. Weekly death data reveal how mortality started to increase in mid-2021 in Denmark, Finland and Norway, and continued above the expected level through 2022. CONCLUSION: Although the Nordic countries experienced relatively low pandemic excess mortality, the impact and timing of excess mortality differed substantially. These estimates-arguably the most accurate available for any region in capturing pandemic-related excess deaths-may inform future research and policy regarding the complex mortality dynamics in times of a health crisis such as the COVID-19 pandemic.

Comorbidities in women with polycystic ovary syndrome: a sibling study.

BACKGROUND: Polycystic ovary syndrome (PCOS) has previously been associated with several comorbidities that may have shared genetic, epigenetic, developmental or environmental origins. PCOS may be influenced by prenatal androgen excess, poor intrauterine or childhood environmental factors, childhood obesity and learned health risk behaviors. We analyzed the association between PCOS and several relevant comorbidities while adjusting for early-life biological and socioeconomic conditions, also investigating the extent to which the association is affected by familial risk factors. METHODS: This total-population register-based cohort study included 333,999 full sisters, born between 1962 and 1980. PCOS and comorbidity diagnoses were measured at age 17-45 years through national hospital register data from 1997 to 2011, and complemented with information on the study subjects´ early-life and social characteristics. In the main analysis, sister fixed effects (FE) models were used to control for all time-invariant factors that are shared among sisters, thereby testing whether the association between PCOS and examined comorbidities is influenced by unobserved familial environmental, social or genetic factors. RESULTS: Three thousand five hundred seventy women in the Sister sample were diagnosed with PCOS, of whom 14% had obesity, 8% had depression, 7% had anxiety and 4% experienced sleeping, sexual and eating disorders (SSE). Having PCOS increased the odds of obesity nearly 6-fold (adjusted OR (aOR): 5.9 [95% CI:5.4-6.5]). This association was attenuated in models accounting for unobserved characteristics shared between full sisters, but remained considerable in size (Sister FE: aOR: 4.5 [95% CI: 3.6-5.6]). For depression (Sister FE: aOR: 1.4 [95% CI: 1.2-1.8]) and anxiety (Sister FE: aOR: 1.5 [95% CI: 1.2-1.8), there was a small decrease in the aORs when controlling for factors shared between sisters. Being diagnosed with SSE disorders yielded a 2.4 aOR (95% CI:2.0-2.6) when controlling for a comprehensive set of individual-level confounders, which only decreased slightly when controlling for factors at the family level such as shared genes or parenting style. Accounting for differences between sisters in observed early-life circumstances influenced the estimated associations marginally. CONCLUSION: Having been diagnosed with PCOS is associated with a markedly increased risk of obesity and sleeping, sexual and eating disorders, also after accounting for factors shared between sisters and early-life conditions.

A Capture-Recapture-based Ascertainment Probability Weighting Method for Effect Estimation With Under-ascertained Outcomes.

Outcome under-ascertainment, characterized by the incomplete identification or reporting of cases, poses a substantial challenge in epidemiologic research. While capture-recapture methods can estimate unknown case numbers, their role in estimating exposure effects in observational studies is not well established. This paper presents an ascertainment probability weighting framework that integrates capture-recapture and propensity score weighting. We propose a nonparametric estimator of effects on binary outcomes that combines exposure propensity scores with data from two conditionally independent outcome measurements to simultaneously adjust for confounding and under-ascertainment. Demonstrating its practical application, we apply the method to estimate the relationship between health care work and coronavirus disease 2019 testing in a Swedish region. We find that ascertainment probability weighting greatly influences the estimated association compared to conventional inverse probability weighting, underscoring the importance of accounting for under-ascertainment in studies with limited outcome data coverage. We conclude with practical guidelines for the method's implementation, discussing its strengths, limitations, and suitable scenarios for application.

Early Life Factors and Polycystic Ovary Syndrome in a Swedish Birth Cohort.

Polycystic ovary syndrome (PCOS) is a medical condition with important consequences for women's well-being and reproductive outcomes. Although the etiology of PCOS is not fully understood, there is increasing evidence of both genetic and environmental determinants, including development in early life. We studied a population of 977,637 singleton women born in in Sweden between 1973 and 1995, followed sometime between the age 15 and 40. The incidence of PCOS was measured using hospital register data during 2001-2012, complemented with information about the women's, parents' and sisters' health and social characteristics from population and health care registers. Cox regression was used to study how PCOS is associated with intergenerational factors, and a range of early life characteristics. 11,594 women in the study sample were diagnosed with PCOS during the follow-up period. The hazard rate for PCOS was increased 3-fold (HR 2.98, 95% CI 2.43-3.64) if the index woman's mother had been diagnosed with PCOS, and with 1.5-fold (HR 1.51, 95% CI 1.39-1.63) if their mother had diabetes mellitus. We found associations of PCOS with lower (<7) one-minute Apgar score (HR 1.19, 95% CI 1.09-1.29) and with post-term birth (HR 1.19, 95% CI 1.13-1.26). Furthermore, heavy (10+ cigarettes/day) maternal smoking (HR 1.30, 95% CI 1.18-1.44) and maternal obesity (HR 1.90, 95% CI 1.62-2.36) were strongly associated with PCOS. This study finds support for the heritability and fetal origins of PCOS. Risk of PCOS could be reduced by further emphasizing the importance of maternal and early life health.

Can non-participants in a follow-up be used to draw conclusions about incidences and prevalences in the full population invited at baseline? An investigation based on the Swedish MDC cohort.

BACKGROUND: Participants in epidemiological cohorts may not be representative of the full invited population, limiting the generalizability of prevalence and incidence estimates. We propose that this problem can be remedied by exploiting data on baseline participants who refused to participate in a re-examination, as such participants may be more similar to baseline non-participants than what baseline participants who agree to participate in the re-examination are. METHODS: We compared background characteristics, mortality, and disease incidences across the full population invited to the Malmö Diet and Cancer (MDC) study, the baseline participants, the baseline non-participants, the baseline participants who participated in a re-examination, and the baseline participants who did not participate in the re-examination. We then considered two models for estimating characteristics and outcomes in the full population: one ("the substitution model") assuming that the baseline non-participants were similar to the baseline participants who refused to participate in the re-examination, and one ("the extrapolation model") assuming that differences between the full group of baseline participants and the baseline participants who participated in the re-examination could be extended to infer results in the full population. Finally, we compared prevalences of baseline risk factors including smoking, risky drinking, overweight, and obesity across baseline participants, baseline participants who participated in the re-examination, and baseline participants who did not participate in the re-examination, and used the above models to estimate the prevalences of these factors in the full invited population. RESULTS: Compared to baseline non-participants, baseline participants were less likely to be immigrants, had higher socioeconomic status, and lower mortality and disease incidences. Baseline participants not participating in the re-examination generally resembled the full population. The extrapolation model often generated characteristics and incidences even more similar to the full population. The prevalences of risk factors, particularly smoking, were estimated to be substantially higher in the full population than among the baseline participants. CONCLUSIONS: Participants in epidemiological cohorts such as the MDC study are unlikely to be representative of the full invited population. Exploiting data on baseline participants who did not participate in a re-examination can be a simple and useful way to improve the generalizability of prevalence and incidence estimates.

Examining the continuum of resistance model in two population-based screening studies in Sweden.

In studies recruited on a voluntary basis, lack of representativity may impair the ability to generalize findings to the target population. Previous studies, primarily based on surveys, have suggested that generalizability may be improved by exploiting data on individuals who agreed to participate only after receiving one or several reminders, as such individuals may be more similar to non-participants than what early participants are. Assessing this idea in the context of screenings, we compared sociodemographic characteristics and health across early, late, and non-participants in two large population-based screening studies in Sweden: STROKESTOP II (screening for atrial fibrillation; 6,867 participants) and SCREESCO (screening for colorectal cancer; 39,363 participants). We also explored the opportunities to reproduce the distributions of characteristics in the full invited populations, either by assuming that the non-participants were similar to the late participants, or by applying a linear extrapolation model based on both early and late participants. Findings showed that early and late participants exhibited similar characteristics along most dimensions, including civil status, education, income, and health examination results. Both these types of participants in turn differed from the non-participants, with fewer married, lower educational attainments, and lower incomes. Compared to early participants, late participants were more likely to be born outside of Sweden and to have comorbidities, with non-participants similar or even more so. The two empirical models improved representativity in some cases, but not always. Overall, we found mixed support that data on late participation may be useful for improving representativeness of screening studies.

Cancer, cardiovascular disease, and all-cause mortality in Iraqi- and Swedish-born individuals in Sweden: the MEDIM cohort study.

Immigrants from the Middle East to Sweden have a twice as high prevalence of type 2 diabetes (T2D) and obesity as native-born Swedes. Both obesity and T2D have been linked to increased incidence of cancer, cardiovascular disease (CVD) and all-cause mortality (ACM); however, data on differences between ethnicities are scarce. In a population-based cohort we aimed to study the impact of Middle Eastern and European ethnicity on ACM, cancer- and CVD related mortality, incidence of cancer and CVD in an eight-year follow-up study. Methods: People born in Iraq or Sweden, who were 30-75 years of age, were invited from 2010 to 2012 to participate in the population based MEDIM study including a health exam, fasting blood sampling, assessment of insulin secretion and action (through oral glucose tolerance test) and questionnaires assessing history of CVD, cancer and T2D. Register data were retrieved from baseline until the 31st of December 2018 from the Swedish National Patient Register and Cause of Death register regarding CVD diagnosis, cancer diagnosis and cause of death. Information regarding diabetes diagnosis was retrieved from the National Diabetes Register. Individuals with a history of cancer or CVD at baseline were excluded. Cox regression analysis was assessed to study the adjusted hazard ratios (HR) for the relationships between ethnicity and ACM, cancer events, CVD events, death from cancer, and death from CVD, with adjustments for age, sex, anthropometrical measures, T2D and lifestyle. A total of 1398 Iraqi- and 757 Swedish-born residents participated in the study. ACM was considerably lower in Iraqi- compared to Swedish-born individuals HR 0.32 (95% CI 0.13-0.79) (p < 0.05). Furthermore, cancer related morbidity and mortality HR 0.39 (0.22-0.69) (p < 0.01) as well as CVD related morbidity and mortality HR 0.56 (0.33-0.95) (p < 0.05) were lower in the Iraqi-born group compared to the Swedish-born group for. The differences in mortality and cancer rates across ethnicities are not fully explained by anthropometric, environmental or metabolic measures but lie elsewhere. Further studies are needed to increase the understanding of contributing mechanisms.

Proxy Variables and the Generalizability of Study Results.

When individuals self-select (or are selected) into a study based on factors that influence the outcome, conclusions may not generalize to the full population. To compensate for this, results may be adjusted, for example, by standardization on the set of common causes of participation and outcome. Although such standardization is useful in some contexts, the common causes of participation and outcome may in practice not be fully observed. Instead, the researcher may have access to one or several variables related to the common causes, that is, to proxies for the common causes. This article defines and examines different types of proxy variables and shows how these can be used to obtain generalizable study results. First of all, the researcher may exploit proxies that influence only participation or outcome but which still allow for perfect generalizability by rendering participation and outcome conditionally independent. Further, generalizability can be achieved by leveraging 2 proxies, one of which is allowed to influence participation and one of which is allowed to influence the outcome, even if participation and outcome do not become independent conditional on these. Finally, approximate generalizability may be obtained by exploiting a single proxy that does not itself influence participation or outcome.

Insulin secretion and action with increasing age - A comparison between Middle Eastern immigrants and native Swedes.

Aims: Little is known how insulin secretion and action change over time in populations of different ethnicities. We studied changes in insulin secretion and action with increasing age in Iraqi-born immigrants and native Swedes, and investigated if the changes were modified by region of origin. Methods: Residents of Malmö, 30-75 years of age born in Iraq or Sweden, were invited to participate in this population-based, cross-sectional study. Health examination, medical history, lifestyle, sociodemographic data, and fasting blood samples were assessed. Oral glucose tolerance tests were performed and insulin secretion (disposition index, DIo) and insulin sensitivity index (ISI) calculated using the Matsuda indices. Results: In total 1881 people participated; 1193 Iraqi- and 688 Swedish born. DIo decreased with increasing age in the total study population (ß for the effect of age on ln DIo: -0.018, 95% CI -0.023 to -0.013, P < 0.001), adjusted for origin, lifestyle and anthropometric measures. DIo was generally lower in Iraqis vs. Swedes (median: 12,712.9 vs. 14,659.2, P = 0.004), but the difference disappeared when adjusted for BMI.Further, ISI declined with increasing age in both Iraqis and Swedes. ISI was generally lower among Iraqis compared to Swedes, (median: 76.9 vs. 102.3, p < .001). The difference could not be fully explained by age, sex, lifestyle, and anthropometric measures. No significant interactions were observed. Conclusions: The levels of DIo and ISI were lower among Iraqis compared to Swedes and declined with increasing age, irrespective of origin.

A regression discontinuity analysis of the social distancing recommendations for older adults in Sweden during COVID-19.

BACKGROUND: This article investigates the impact of a non-mandatory and age-specific social distancing recommendation on isolation behaviours and disease outcomes in Sweden during the first wave of the coronavirus disease 2019 (COVID-19) pandemic (March to July 2020). The policy stated that people aged 70 years or older should avoid crowded places and contact with people outside the household. METHODS: We used a regression discontinuity design-in combination with self-reported isolation data from COVID Symptom Study Sweden (n = 96 053; age range: 39-79 years) and national register data (age range: 39-100+ years) on severe COVID-19 disease (hospitalization or death, n = 21 804) and confirmed cases (n = 48 984)-to estimate the effects of the policy. RESULTS: Our primary analyses showed a sharp drop in the weekly number of visits to crowded places (-13%) and severe COVID-19 cases (-16%) at the 70-year threshold. These results imply that the age-specific recommendations prevented approximately 1800-2700 severe COVID-19 cases, depending on model specification. CONCLUSIONS: It seems that the non-mandatory, age-specific recommendations helped control COVID-19 disease during the first wave of the pandemic in Sweden, as opposed to not implementing a social distancing policy aimed at older adults. Our study provides empirical data on how populations may react to non-mandatory, age-specific social distancing policies in the face of a novel virus.

The value of combining individual and small area sociodemographic data for assessing and handling selective participation in cohort studies: Evidence from the Swedish CardioPulmonary bioImage Study.

OBJECTIVES: To study the value of combining individual- and neighborhood-level sociodemographic data to predict study participation and assess the effects of baseline selection on the distribution of metabolic risk factors and lifestyle factors in the Swedish CardioPulmonary bioImage Study (SCAPIS). METHODS: We linked sociodemographic register data to SCAPIS participants (n = 30,154, ages: 50-64 years) and a random sample of the study's target population (n = 59,909). We assessed the classification ability of participation models based on individual-level data, neighborhood-level data, and combinations of both. Standardized mean differences (SMD) were used to examine how reweighting the sample to match the population affected the averages of 32 cardiopulmonary risk factors at baseline. Absolute SMDs >0.10 were considered meaningful. RESULTS: Combining both individual-level and neighborhood-level data gave rise to a model with better classification ability (AUC: 71.3%) than models with only individual-level (AUC: 66.9%) or neighborhood-level data (AUC: 65.5%). We observed a greater change in the distribution of risk factors when we reweighted the participants using both individual and area data. The only meaningful change was related to the (self-reported) frequency of alcohol consumption, which appears to be higher in the SCAPIS sample than in the population. The remaining risk factors did not change meaningfully. CONCLUSIONS: Both individual- and neighborhood-level characteristics are informative in assessing study selection effects. Future analyses of cardiopulmonary outcomes in the SCAPIS cohort can benefit from our study, though the average impact of selection on risk factor distributions at baseline appears small.

Reweighting a Swedish health questionnaire survey using extensive population register and self-reported data for assessing and improving the validity of longitudinal associations.

BACKGROUND: In cohorts with voluntary participation, participants may not be representative of the underlying population, leading to distorted estimates. If the relevant sources of selective participation are observed, it is however possible to restore the representativeness by reweighting the sample to resemble the target population. So far, few studies in epidemiology have applied reweighting based on extensive register data on socio-demographics and disease history, or with self-reported data on health and health-related behaviors. METHODS: We examined selective participation at baseline and the first two follow-ups of the Scania Public Health Cohort (SPHC), a survey conducted in Southern Sweden in 1999/2000 (baseline survey; n = 13,581 participants, 58% participation rate), 2005 (first follow-up, n = 10,471), and 2010 (second follow-up; n = 9,026). Survey participants were reweighted to resemble the underlying population with respect to a broad range of socio-demographic, disease, and health-related characteristics, and we assessed how selective participation impacted the validity of associations between self-reported overall health and dimensions of socio-demographics and health. RESULTS: Participants in the baseline and follow-up surveys were healthier and more likely to be female, born in Sweden, middle-aged, and have higher socioeconomic status. However, the differences were not very large. In turn, reweighting the samples to match the target population had generally small or moderate impacts on associations. Most examined regression coefficients changed by less than 20%, with virtually no changes in the directions of the effects. CONCLUSION: Overall, selective participation with respect to the observed factors was not strong enough to substantially alter the associations with self-assessed health. These results are consistent with an interpretation that SPHC has high validity, perhaps reflective of a relatively high participation rate. Since validity must be determined on a case-by-case basis, however, researchers should apply the same method to other health cohorts to assess and potentially improve the validity.

Statins Decrease the Risk of Orbitopathy in Newly Diagnosed Patients with Graves Disease.

CONTEXT/OBJECTIVE: The aim of this study was to examine the effect of statins and other lipid-lowering agents on the development of Graves orbitopathy (GO) in patients with newly diagnosed Graves disease (GD). METHODS: Our sample included the full adult population of individuals living in Sweden with newly diagnosed GD between 2005 and 2018 (n = 34 894). We compared the GO incidence in statin users (n = 5574) and nonusers (n = 34 409) by applying Cox regression with a time-varying exposure variable. We adjusted for age, sex, and treatment for hyperthyroidism in the multivariate analyses. RESULTS: Periods of nonusage lasted for a median of 4.3 years (interquartile range [IQR] 1.2-8.4), whereas periods of usage lasted for a median of 4.7 years (IQR 2.0-8.1). Among statin users, 77.1% had used simvastatin, 28.9% atorvastatin, and 8.2% had used other statins. Statin users were found to be significantly less likely to develop GO. In the main analysis based on the full cohort, the unadjusted hazard ratio (HR) was 0.74 (CI 0.65-0.84, P < .001), whereas full adjustment altered the effect to 0.87 (CI 0.76-1.00, P = .04). The main results were largely driven by men; the fully adjusted HR was 0.78 (CI 0.58-1.04, P = .09) for men and 0.91 (CI 0.79-1.06, P = .24) for women. Lipid-lowering agents other than statins did not exhibit a similar protective effect. CONCLUSION: In newly diagnosed patients with GD, treatment with statins may protect against the development of GO. Statins should be investigated in a clinical trial as a preventive treatment for GO in newly diagnosed patients with GD.

Assessment of selection bias due to dropouts in the follow-up of the Scania Public Health Cohort.

Aims: To investigate potential differences between participants and dropouts in the 2005 follow-up of the Scania Public Health Cohort Study regarding the prevalence of commonly studied health determinants and whether these factors had differential associations with three health outcomes: all-cause mortality and purchase of prescribed cardiovascular or psychotropic drugs during a 10-year follow-up period. Methods: The Scania Public Health Cohort was initiated in 1999/2000, with randomly invited participants aged 18-80 years from the general population (58% participation). Questionnaire data from 10,462 participants and 2576 dropouts in the 2005 follow-up (80% participation) were linked to public registers on mortality and purchase of prescribed drugs. Results: Age, male gender, being born abroad, low educational level, low self-rated mental and general health and daily smoking were all related to dropping out. The 10-year mortality was higher among dropouts (13.4% versus 11.9%; age-adjusted hazard ratio 1.6, 95% confidence interval: 1.4-1.8). In 13 out of 18 analyses, similar associations between health determinants and outcomes were found across participants and dropouts. However, being born outside of Sweden was associated with higher risks for all three poor health outcomes among participants, but not so among dropouts. Conclusions: Despite selective participation at follow-up, there was little evidence of selection bias, insofar as estimated associations were generally similar across participants, dropouts and the whole cohort. This finding is important for the assessment of the validity of prospective findings from this cohort and similar ones, where the loss of individuals at consecutive follow-ups of exposure is non-negligible.

Correcting for selective participation in cohort studies using auxiliary register data without identification of non-participants.

Aims: Selective participation may hamper the validity of population-based cohort studies. The resulting bias can be alleviated by linking auxiliary register data to both the participants and the non-participants of the study, estimating propensity scores for participation and correcting for participation based on these. However, registry holders may not be allowed to disclose sensitive data on (invited) non-participants. Our aim is to provide guidance on how adequate bias correction can be achieved by using auxiliary register data but without disclosing information that could be linked to the subset of non-participants. Methods: We show how existing methods can be used to estimate generalisation weights under various data disclosure scenarios where invited non-participants are indistinguishable from uninvited ones. We also demonstrate how the methods can be implemented using Nordic register data. Results: Inverse-probability-of-sampling weights estimated within a random sample of the target population in which the non-respondents are disclosed are equivalent in expectation to analogous weights in a scenario where the non-participants and uninvited individuals from the population are indistinguishable. To minimise the risk of disclosure when the entire population is invited to participate, investigators should instead consider inverse-odds-of-sampling weights, a method that has previously been suggested for transporting study results to external populations. Conclusions: Generalisation weights can be estimated from auxiliary register data without disclosing information on invited non-participants.

A directed acyclic graph for interactions.

BACKGROUND: Directed acyclic graphs (DAGs) are of great help when researchers try to understand the nature of causal relationships and the consequences of conditioning on different variables. One fundamental feature of causal relations that has not been incorporated into the standard DAG framework is interaction, i.e. when the effect of one variable (on a chosen scale) depends on the value that another variable is set to. In this paper, we propose a new type of DAG-the interaction DAG (IDAG), which can be used to understand this phenomenon. METHODS: The IDAG works like any DAG but instead of including a node for the outcome, it includes a node for a causal effect. We introduce concepts such as confounded interaction and total, direct and indirect interaction, showing that these can be depicted in ways analogous to how similar concepts are depicted in standard DAGs. This also allows for conclusions on which treatment interactions to account for empirically. Moreover, since generalizability can be compromised in the presence of underlying interactions, the framework can be used to illustrate threats to generalizability and to identify variables to account for in order to make results valid for the target population. CONCLUSIONS: The IDAG allows for a both intuitive and stringent way of illustrating interactions. It helps to distinguish between causal and non-causal mechanisms behind effect variation. Conclusions about how to empirically estimate interactions can be drawn-as well as conclusions about how to achieve generalizability in contexts where interest lies in estimating an overall effect.

Liothyronine Use in Hypothyroidism and its Effects on Cancer and Mortality.

Background: The prescription of liothyronine (LT3) to treat hypothyroidism is increasing worldwide; however, the long-term safety of LT3 use has yet to be determined. Previous studies have suggested a possible association between LT3 use and breast cancer. The aim of this study was to examine the effects of LT3 use on cancer incidence and mortality. Methods: Our sample included the full adult population of individuals living in Sweden with at least three purchases of thyroid hormone therapy between July 2005 and December 2017. Individual-level data on drug purchases were linked to registry data on cancer incidence and mortality. There were 575,461 individuals with at least three purchases, of which 11,147 had made at least three purchases of LT3, including combinations of levothyroxine (LT4) and LT3. Individuals were followed for a median follow-up time of 8.1 years. We applied Cox regression with a time-varying exposure variable, comparing LT3 users (individuals with at least three cumulative purchases of LT3) with LT4-only users (the rest). Outcomes included breast cancer incidence, any cancer incidence, all-cause mortality, any cancer mortality, and breast cancer mortality. We adjusted for age, sex, previous thyroid cancer, previous other cancer, use of antithyroid preparations, use of sex hormones, and dose in multivariate analyses. Results: Multivariate analyses produced a hazard ratio of 0.93 (95% confidence interval [0.75-1.15]) for breast cancer incidence (only females), 0.97 (0.87-1.08) for any cancer incidence, 0.69 (0.61-0.77) for all-cause mortality, 0.78 (0.62-0.98) for any cancer mortality, and 0.91 (0.50-1.66) for breast cancer mortality (only females). Conclusions: In this large, Swedish, long-term registry-based study, the use of LT3 did not lead to increased breast cancer incidence, any cancer incidence, all-cause mortality, any cancer mortality, or breast cancer mortality compared with LT4 use. Somewhat surprisingly, there was evidence of lower mortality in LT3 users in models adjusting for dose, potentially an artifact of underlying associations between dose and health status/diagnosis.

Can the validity of a cohort be improved by reweighting based on register data? Evidence from the Swedish MDC study.

BACKGROUND: In any study with voluntary participation, self-selection risks leading to invalid conclusions. If the determinants of selection are observed, it is however possible to restore the parameters of interest by reweighting the sample to match the population, but this approach has seldom been applied in epidemiological research. METHODS: We reweighted the Malmö Diet and Cancer (MDC) study based on population register data on background variables, including socio-demographics and hospital admissions for both participants and the background population. Following individuals from baseline in 1991-1996 and at most until 2016, we studied mortality (all-cause, cancer, and CVD), incidences (cancer and CVD), and associations between these outcomes and background variables. Results from the unweighted and reweighted participant sample were compared with those from the background population. RESULTS: Mortality was substantially lower in participants than in the background population, but reweighting the sample helped only little to make the numbers similar to those in the background population. For incidences and associations, numbers were generally similar between participants and the background population already without reweighting, rendering reweighting unnecessary. CONCLUSION: Reweighting samples based on an extensive range of sociodemographic characteristics and previous hospitalizations does not necessarily yield results that are valid for the population as a whole. In the case of MDC, there appear to be important factors related to both mortality and selection into the study that are not observable in registry data, making it difficult to obtain accurate numbers on population mortality based on cohort participants. These issues seem less relevant for incidences and associations, however. Overall, our results suggest that representativeness must be judged on a case-by-case basis.

A novel framework for classification of selection processes in epidemiological research.

BACKGROUND: Selection and selection bias are terms that lack consistent definitions and have varying meaning and usage across disciplines. There is also confusion in current definitions between underlying mechanisms that lead to selection and their consequences. Consequences of selection on study validity must be judged on a case-by-case basis depending on research question, study design and analytical decisions. The overall aim of the study was to develop a simple but general framework for classifying various types of selection processes of relevance for epidemiological research. METHODS: Several original articles from the epidemiological literature and from related areas of observational research were reviewed in search of examples of selection processes, used terminology and description of the underlying mechanisms. RESULTS: We classified the identified selection processes in three dimensions: i) selection level (selection at the population level vs. study-specific selection), ii) type of mechanism (selection in exposure vs. selection in population composition), iii) timing of the selection (at exposure entry, during exposure/follow-up or post-outcome). CONCLUSIONS: Increased understanding of when, how, and why selection occur is an important step towards improved validity of epidemiological research.

Sex-based differences in ED management of critically ill patients with sepsis: a nationwide cohort study.

PURPOSE: To compare management and outcomes for critically ill women and men with sepsis in the emergency medical services (EMS), the emergency department (ED) and the ICU. METHODS: We used two prospectively compiled Swedish national quality registers, the National Quality Sepsis Registry and the Swedish Intensive Care Registry to identify a nationwide cohort of 2720 adults admitted to an ICU within 24 h of arrival to any of 32 EDs, with a diagnosis of severe sepsis or septic shock between 2008 and 2015. RESULTS: Patients were 44.5% female. In the EMS, a higher fraction of men had all vital signs recorded-54.4 vs 49.9% (p = 0.02) and received IV fluids and oxygen-40.0 vs 34.8% (p = 0.02). In the ED, men had completed 1-h sepsis bundles in 41.5% of cases compared to 30.0% in women (p < 0.001), and shorter time to antibiotics-65 (IQR 30-136) vs 87 min (IQR 39-172) (p = 0.0001). There was no significant difference between men and women regarding ICU nursing workload, mechanical ventilation or ICU length of stay. In severity-adjusted multivariable analysis, OR for women achieving a completed sepsis bundle, compared to men was 0.64 (CI 0.51-0.81). Thirty-day mortality was 25.0% for women and 23.1% for men (p = 0.24). Adjusted OR for female death was 1.28 (CI 1.00-1.64), but the increased mortality was not mediated by differential bundle completion. CONCLUSIONS: Women and men with severe sepsis or septic shock received differential care in the ED, but this did not explain higher odds of death in women.