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| Apparent incidence resulting from total bias, as a function of specificity. Disease prevalence = 20%. Solid line: median value; dotted lines: first and third quartiles.
Source publication
Using imperfect tests may lead to biased estimates of disease frequency and measures of association. Many studies have looked into the effect of misclassification on statistical inferences. These evaluations were either within a cross-sectional study framework, assessing biased prevalence, or for cohort study designs, evaluating biased incidence ra...
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Cohort design is a type of nonexperimental or observational study design. In a cohort study, the participants do not have the outcome of interest to begin with. They are selected based on the exposure status of the individual. They are then followed over time to evaluate for the occurrence of the outcome of interest. Some examples of cohort studies...
Citations
... It is likely that misclassification bias in our study would be non-differential, as it is not likely that misclassification of TB would be systematic with regard to asthmatic symptoms (35). Non-differential misclassification would imply that the actual association of TB with asthma and respiratory symptoms might be stronger than observed. ...
Background
Tuberculosis (TB) infection induces profound local and systemic, immunological and inflammatory changes that could influence the development of other respiratory diseases; however, the association between TB and asthma is only partly understood. Our objective was to study the association of TB with asthma and respiratory symptoms in a Nordic–Baltic population-based study.
Methods
We included data from the Respiratory Health in Northern Europe (RHINE) study, in which information on general characteristics, TB infection, asthma and asthma-like symptoms were collected using standardised postal questionnaires. Asthma was defined based on asthma medication usage and/or asthma attacks 12 months prior to the study, and/or by a report of ≥three out of five respiratory symptoms in the last 12 months. Allergic/nonallergic asthma were defined as asthma with/without nasal allergy. The associations of TB with asthma outcomes were analysed using logistic regressions with adjustments for age, sex, smoking, body mass index and parental education.
Results
We included 8379 study participants aged 50–75 years, 61 of whom reported having had TB. In adjusted analyses, participants with a history of TB had higher odds of asthma (OR 1.99, 95% CI 1.13–3.47). The associations were consistent for nonallergic asthma (OR 2.17, 95% CI 1.16–4.07), but not for allergic asthma (OR 1.20, 95% CI 0.53–2.71).
Conclusion
We found that in a large Northern European population-based cohort, persons with a history of TB infection more frequently had asthma and asthma symptoms. We speculate that this may reflect long-term effects of TB, including direct damage to the airways and lungs, as well as inflammatory responses.
... Although we used survey weights in our analyses, participation bias cannot be ruled out. 76 In addition, the CES-D-10 tool and the definition of diabetes use self-reported information that come with measuring errors and information bias. 77 These errors may have differed between immigrants and nonimmigrants because of possible language barriers and culture-related social desirability. ...
Background:
A bidirectional association between depression and diabetes exists, but has not been evaluated in the context of immigrant status. Given that social determinants of health differ between immigrants and nonimmigrants, we evaluated the association between diabetes and depression incidence, depression and diabetes incidence, and whether immigrant status modified this association, among immigrants and nonimmigrants in Canada.
Methods:
We employed a retrospective cohort design using data from the Canadian Longitudinal Study on Aging Comprehensive cohort (baseline [2012-2015] and 3-year follow-up [2015-2018]). We defined participants as having diabetes if they self-reported it or if their glycated hemoglobin A1c level was 7% or more; we defined participants as having depression if their Center for Epidemiological Studies Depression score was 10 or higher or if they were currently undergoing depression treatment. We excluded those with baseline depression (Cohort 1) and baseline diabetes (Cohort 2) to evaluate the associations between diabetes and depression incidence, and between depression and diabetes incidence, respectively. We constructed logistic regression models with interaction by immigrant status.
Results:
Cohort 1 (n = 20 723; mean age 62.7 yr, standard deviation [SD] 10.1 yr; 47.6% female) included 3766 (18.2%) immigrants. Among immigrants, 16.4% had diabetes, compared with 15.6% among nonimmigrants. Diabetes was associated with an increased risk of depression in nonimmigrants (adjusted odds ratio [OR] 1.27, 95% confidence interval [CI] 1.08-1.49), but not in immigrants (adjusted OR 1.12, 95% CI 0.80-1.56). Younger age, female sex, weight change, poor sleep quality and pain increased depression risk. Cohort 2 (n = 22 054; mean age 62.1 yr, SD 10.1 yr; 52.2% female) included 3913 (17.7%) immigrants. Depression was associated with an increased risk of diabetes in both nonimmigrants (adjusted OR 1.39, 95% CI 1.16-1.68) and immigrants (adjusted OR 1.60, 95% CI 1.08-2.37). Younger age, male sex, waist circumference, weight change, hypertension and heart disease increased diabetes risk.
Interpretation:
We found an overall bidirectional association between diabetes and depression that was not significantly modified by immigrant status. Screening for diabetes for people with depression and screening for depression for those with diabetes should be considered.
... There was a moderate risk in the assessment of the outcome variable because, despite using validated tools, the studies applied self-reported methods. There were also biases due to classification, with respect to exposure [39], as results may be considered biased if participants are from different areas, as well as if results are from another point in time. In this regard, the risk was moderate in most cases [11,13,15,33,36] (see Additional file 2. Risks of bias.) ...
Our main aim was to examine the evidence of the effects of coronavirus disease confinement on the sleep of children aged 12 years and younger. A systematic review was conducted following the recommendations for Preferred Reporting Items for Systematic Reviews and Meta-Analyses. MEDLINE, Cumulative Index for Nursing and Allied Health Literature, Excerpta Medica Database, Psychological Information Database, and Web Of Science were systematically searched between the period of January 2020 and March 2021. The quality assessment was analysed with the Newcastle-Ottawa quality assessment scale and the National Institutes of Health quality assessment tool for observational cohort and cross-sectional studies. The appraisal tool for cross-sectional studies was applied to cross-sectional studies and each longitudinal study was assessed with the critical appraisal skills programme. Data analysis was carried out through a narrative review. Eight studies were included in the review. Seven studies reported changes in sleep routines and five studies focused on sleep disturbances during confinement. The most important findings were a longer duration of sleep time, an increase in sleep latency, and daytime sleepiness. Whether or not the adverse changes to sleep patterns and bedtime routines seen during the home confinement period have any long-term consequences for children’s sleep and daytime functioning remains unknown.
... Misclassification occurs when an individual, a value, or an attribute is assigned to a category other than that to which it should be assigned. This erroneous classification can lead to incorrect associations being observed between the assigned categories and the outcomes of interest [26], thereby biasing inferences drawn from the data collected [27], often substantially [28], or decreasing the power of the study [29]. As highlighted by Kloos et al. [9], misclassification bias occurs in a broad range of applications, including epidemiology [30], political science [31], and official statistics [32]. ...
A growing body of literature has examined the potential of machine learning algorithms in constructing social indicators based on the automatic classification of digital traces. However, as long as the classification algorithms’ predictions are not completely error-free, the estimate of the relative occurrence of a particular class may be affected by misclassification bias, thereby affecting the value of the calculated social indicator. Although a significant amount of studies have investigated misclassification bias correction techniques, they commonly rely on a set of assumptions that are likely to be violated in practice, which calls into question the effectiveness of these methods. Thus, there is a knowledge gap with respect to the assessment of misclassification bias’s impact on a specific social indicator formula without strict reference to the number of classes. Moreover, given the erroneous nature of automatic classification algorithms, the quality of a predicted indicator can be assessed not only using regression quality metrics, as was done in existing literature, but also using correlation metrics. In this paper, we propose a simulation approach for assessing the impact of misclassification bias on the calculated social indicators in terms of regression and correlation metrics. The proposed approach focuses on indicators calculated based on the distribution of classes and can process any number of classes. The proposed approach allows selecting the most appropriate classification model for a particular social indicator, and vice versa. Moreover, it allows for assessment of the optimistic level of correlation between the indicator calculated based on the results of the classification algorithm and the true underlying indicator.
... Selection bias. Selection bias occurs when there is a systematic difference between those who participate in the study and those who do not (affecting generalisability) [105,106]. Selection bias was reported for 33% of the studies (Table 3). Selection bias may result in over-estimation of outcomes among young people exposed to child protection compared with young people in the general population [89]. ...
Introduction
Over the past decade there has been a marked growth in the use of linked population administrative data for child protection research. This is the first systematic review of studies to report on research design and statistical methods used where population-based administrative data is integrated with longitudinal data in child protection settings.
Methods
The systematic review was conducted according to Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) statement. The electronic databases Medline (Ovid), PsycINFO, Embase, ERIC, and CINAHL were systematically searched in November 2019 to identify all the relevant studies. The protocol for this review was registered and published with Open Science Framework (Registration DOI: 10.17605/OSF.IO/96PX8 )
Results
The review identified 30 studies reporting on child maltreatment, mental health, drug and alcohol abuse and education. The quality of almost all studies was strong, however the studies rated poorly on the reporting of data linkage methods. The statistical analysis methods described failed to take into account mediating factors which may have an indirect effect on the outcomes of interest and there was lack of utilisation of multi-level analysis.
Conclusion
We recommend reporting of data linkage processes through following recommended and standardised data linkage processes, which can be achieved through greater co-ordination among data providers and researchers.
... This could lead to misclassification of study participants and dilute the association between iodine deficiency and pre-eclampsia. 33 The estimation of maternal intrathyroid iodine concentration, even though more technical, has been proposed as a more objective measure of prepregnancy iodine nutrition status than spot UIC. 34 Concurrent measurement of spot UIC and serum thyroglobulin may help identify individuals with long-term Open access exposure to iodine deficiency in studies where it is not possible to measure serial UIC and intrathyroid iodine concentration. ...
Background
Although subclinical hypothyroidism in pregnancy is one of the established risk factors for pre-eclampsia, the link between iodine deficiency, the main cause of hypothyroidism, and pre-eclampsia remains uncertain. We conducted a systematic review to determine the iodine nutrition status of pregnant women with and without pre-eclampsia and the risk of pre-eclampsia due to iodine deficiency.
Methods
MEDLINE, EMBASE, Google Scholar, Scopus and Africa-Wide Information were searched up to 30th June 2020. Random-effect model meta-analysis was used to pool mean difference in urinary iodine concentration (UIC) between pre-eclamptic and normotensive controls and pool ORs and incidence rates of pre-eclampsia among women with UIC <150 µg/L.
Results
Five eligible studies were included in the meta-analysis. There was a significant difference in the pooled mean UIC of 254 pre-eclamptic women and 210 normotensive controls enrolled in three eligible case–control studies (mean UIC 164.4 µg/L (95% CI 45.1 to 283.6, p<0.01, I ² >50)). The overall proportions of pre-eclampsia among women with UIC <150 µg/L and UIC >150 µg/L in two cross-sectional studies were 203/214 and 67/247, respectively, with a pooled OR of 0.01 (95% CI 0 to 4.23, p=0.14, I ² >50) for pre-eclampsia among women with UIC >150 µg/L. The overall incidence of pre-eclampsia among women with UIC <150 µg/L and UIC >150 µg/L in two cohort studies was 6/1411 and 3/2478, respectively, with a pooled risk ratio of 2.85 (95% CI 0.42 to 20.05, p=0.09, I ² <25).
Conclusion
Although pre-eclamptic women seem to have lower UIC than normotensive pregnant women, the available data are insufficient to provide a conclusive answer on association of iodine deficiency with pre-eclampsia risk.
PROSPERO registration number
CRD42018099427.
... In the current study, not considering a potential confounding effect of sanitation, immunisation, and safe water may have affected the effect estimates in either direction (641,648). More importantly, specific to the present study, women with a high probability of depression were excluded for ethical reasons which could have affected the number and comparability of exposure between the outcome category, introducing bias that possibly led to underestimation (649). Despite the equivocal evidence, various potential mechanisms have been suggested to explain the potential link between CMDs during pregnancy and the risk of infant illnesses. ...
Executive summary
Introduction: Depression occurring during the perinatal period (from pregnancy through the postnatal period to 12 months postpartum is one of the most common complications of the perinatal period in high- and low-income countries. Perinatal depression has been reported to affect pregnancy, maternal, newborn and child health outcomes. Although several studies have been conducted on perinatal depression in Ethiopia, the mechanisms underlying the relationship between this disorder and risk factors, and the links between the condition and adverse birth and infant health outcomes remain unexplored. Furthermore, there have been no studies conducted to explore how the healthcare system addresses perinatal depression issues in Ethiopia. This PhD thesis has investigated the burden and potential causal mechanisms of perinatal depression and its association with the risk of adverse birth and infant health outcomes in Gondar town, Ethiopia. Health system-related barriers and enablers of accessing perinatal depression services in Ethiopia were also explored.
Methods: A mixed-methods study was employed to address research questions as follows: (i) to understand what previous studies had found and to assess any gaps in literature, systematic reviews and primary observational studies published between 2007 and 2018 were systematically searched from relevant databases. The quality of the systematic reviews and primary studies were appraised using the Assessment of Multiple Systematic Reviews (AMSTAR) checklist and the Newcastle–Ottawa scale, respectively. (ii) To assess the epidemiology of perinatal depression (using Edinburgh Postnatal Depression Scale (EPDS)), risk factors and effects of perinatal depression on birth and infant health outcomes, a prospective cohort study was conducted. In total, 916 pregnant women were interviewed from six randomly selected urban districts in Gondar town between June 2018 and March 2019. Face-to-face questionnaires were administered using the online Open Data collection Kit (ODK). Enrolled women were followed from pregnancy to up to six months after birth. Using Stata (release 12) software, a mixed-effect linear regression and Structural Equation Modelling (SEM) were used to explore antenatal and postnatal depression risk factors and their potential causal mechanisms. Modified Poisson regression and Generalized SEM were used to estimate the risk of adverse birth outcomes and potential mechanisms. Targeted Maximum Likelihood Estimation (TMLE) was applied to investigate the causal association between perinatal depression and the risk of adverse infant health outcomes. (iii)To explore barriers to and facilitators of access to services that address perinatal depression, a qualitative study was conducted with 13 health service administrators from different levels of the Ethiopian health system. A thematic content analysis was conducted to analyse the qualitative data aided by NVivo 12 software.
Results: The systematic review findings highlighted the following: (i) The global prevalence of antenatal depression (AND) ranged from 7% to 65% and was highest in low-income countries. (ii) Globally, the risk of LBW and preterm birth was 1.49 (95%CI: 1.32, 1.68) and 1.40 (95%CI: 1.16,1.69) times higher in women with AND relative to those with no depression. (iii) Nearly one in three pregnant women in low-income and one in five in middle-income countries had depression symptoms. (iv) The risk of low birth weight (LBW) and preterm birth was found to be 1.66 (95%CI:1.06, 2.61) and 2.41 (95%CI: 1.47, 3.56) times higher in women with AND in low- and middle-income countries (LMICs) relative to those with no depression. (iii) One in four postnatal women in low-income and one in five in middle-income countries had depression symptoms. (iv) The risk of malnutrition (RR=1.39; 95%CI: 1.21, 1.61), non-exclusive breastfeeding (RR=1.55; 95%CI: 1.39,1.74), and common infant illnesses (RR=2.55; 95%CI: 1.41, 4.61) were found to be high in the infants of postnatally depressed women. (v) Perinatal women with depression were more likely to experience abuse or violence, poor social and/or partner support, a history of common mental disorders (CMDs), economic difficulties, and poor obstetric history relative to those without depression. The review found that there was a lack of information on the potential causal links of antenatal and postnatal depression and their effects on birth and infant health outcomes in Ethiopia.
Findings from the preliminary analysis of cohort study indicated that the prevalence of AND was 6.9% (95%CI: 5.3, 8.7). Unplanned pregnancy (standardised β=0.15), having a history of CMDs(standardised β=0.18), fear of giving birth (standardised β=0.29), and adequate food access for the last three months (standardised β=–0.11) were correlated with depression score. Social support (β=–0.21), marital agreement (β=–0.28), and partner support (β=–0.18) appeared to partially mediate the link between the identified stressors and the risk of AND. Findings from the cohort study (sample 916) showed that the cumulative incidence of stillbirth, LBW, and preterm birth was 1.90% (95%CI: 1.11, 3.02), 5.25% (95%CI: 3.88, 6.92), and 16.42% (95%CI: 14.05, 19.01), respectively. Depression had no direct effect on birth outcomes but indirectly affected preterm
birth via partner support. Partner support moderated the association between AND, preterm birth, and LBW. The risk of stillbirth was 3.22 (95%CI: 1.04, 9.98) times higher in women with AND, and 73% (RR: 0.27; 95%CI: 0.07, 0.99) lower in women with higher coping abilities, but this association was attenuated in path analysis.
The analysis of the cohort study (sample 895) indicated the prevalence and incidence proportion of postnatal depression (PND) to be 9.27% (95%: 7.45, 11.36) and 7.77% (95%CI: 6.04, 9.79), respectively. More than two percent of the women showed depression symptoms both in pregnancy and the postnatal period. Postnatal depression was associated with limited postnatal care services (IRR=1.8; 95%CI: 1.0, 3.2), and was predicted by AND (IRR=1.6; 95%CI: 1.4, 1.7) and CMDs before pregnancy (IRR=2.4; 95%CI: 1.4, 4.3). Antenatal depression (standardised total effect=0.36) and history of CMDs before pregnancy (standardised total effect=0.11) had both a direct and an indirect positive effect on PND scores. Low birth weight (standardised β=0.32) and self-reported labour complications (standardised β=0.09) had only direct effects on PND scores.
The cumulative incidence of diarrhea, acute respiratory infection (ARI) and malnutrition during the 6-month follow-up (sample 878) was 17.0% (95%CI: 14.5, 19.6), 21.6% (95%CI: 18.89, 24.49), and 14.4% (95%CI: 12.2, 16.9), respectively. Antenatal depression was not causally associated with the risk of ARI (RD=–1.3%; 95%CI: –21.0, 18.5), diarrhea (RD=0.8%; 95%CI: –9.2, 10.9), or malnutrition (RD=–7.3%; 95%CI: –22.0, 21.8). Similarly, there was no evidence of a causal association between PND and the risk of diarrhea (RD=–2.4%; 95%CI: –9.6, 4.9), ARI (RD=–3.2%;95%CI: –12.4, 5.9), or malnutrition (RD=0.9%; 95%CI: –7.6, 9.5).
The qualitative inquiry identified the following barriers to the delivery of perinatal mental health services: (i) low awareness of perinatal depression among health administrators and community members, and (ii) the absence of policies and/or programs that addressed perinatal depression in Ethiopia. However, the introduction of the new mental health gap action program (MhGap), the simplicity of available screening programs and health worker motivation were identified as potential opportunities that could be used to address perinatal depression by the health system in Ethiopia.
Discussion: The cohort study findings estimated a lower prevalence of antenatal and postnatal depression estimates than those found in systematic reviews. Higher incidence of adverse birth and infant health outcomes were observed in the current study than in previously conducted studies in Ethiopia. Partner support during pregnancy mediated the link between depression, LBW and preterm births. A strong association was found between depression during pregnancy and stillbirth. History of CMDs before pregnancy, AND, LBW, and self-reported labour complications were found to increase the risk of PND. There was no evidence of direct associations between perinatal depression and the risk of adverse infant health outcomes.
Conclusion and implications: The thesis findings inform the need to develop national mental health policies, guidelines and strategies that incorporate perinatal depression in Ethiopia. Health providers’ training and reorientation of mental health service towards a holistic approach that engages the community, especially pregnant women, is crucial for enhancing the mental health and wellbeing of pregnant women and their newborn babies. The thesis findings also provide comprehensive evidence that can be used to inform policies and practices that can address issues of perinatal depression in Ethiopia and in similar settings.
... We did not find an association between baseline coercion/sabotage and lower participation in follow-up waves; however, women experiencing new (i.e., unmeasured) coercion/sabotage may have reduced likelihood of participation in follow-up waves of the study. If self-presentation bias inhibits reporting of coercion/ sabotage, that implies substantial measurement error (Rosenbaum 2009), adding noise that biases results towards the null (Copeland et al. 1977;Haine et al. 2018;Höfler 2005). In spite of potentially high measurement error, this study observed an association between coercion/sabotage and subsequent pregnancy for all 3 assessed follow-up time periods, after matching on baseline covariates, including baseline coercion, sabotage, and fertility intentions. ...
Men engaging in reproductive coercion may coerce, force, or deceive female partners into pregnancy. This study evaluates whether the 3-month incidence of pregnancy is higher among women reporting reproductive coercion than similar women reporting no reproductive coercion. We tested this hypothesis in longitudinal data from a sample of African-American women ages 18–24 recruited from community settings in Atlanta, Georgia, US, in 2012–2014 (n = 560). Participants were surveyed at baseline, 3 months, 6 months, 9 months, and 12 months. To reduce selection bias, we used full matching on 22 baseline variables related to demographics, economic power, risky alcohol use, and gender-based power inequality. We used logistic regression in the matched sample with outcome pregnancy 3 months later, controlling for baseline fertility intentions (n = 482, n = 458, n = 452 at respectively 3, 6, 9 months). At 3 months, 15% of women reported reproductive coercion. At 6 months, 11.3% of women reporting coercion were pregnant vs. 4.6% of matched women reporting no coercion (p = 0.06). Women reporting coercion had 3 times the odds of pregnancy as matched women reporting no coercion (AOR 2.95, 95% CI (1.16, 6.98), p = 0.02). Among women pregnant after coercion, only 15% wanted to be pregnant then or sooner. Women reporting reproductive coercion are at greater risk of unwanted or mistimed pregnancies, and the semen exposure that caused these pregnancies could also transmit STI/HIV. Clinicians should screen patients for reproductive coercion; consider using semen exposure biomarkers such as PSA or Yc-PCR to identify condom sabotage or stealthing; and refer women experiencing reproductive coercion to supportive services.
... This pattern of misclassification is known as nondifferential misclassification (i.e., an imperfect reporting of the outcome that is unlikely to be associated with the exposition). A previous study demonstrated that for diseases with prevalence <20% (similar to most foot lesions), this type of bias would have very little effect on measures of disease frequency and of association with exposures, even for diagnostic tests with moderate sensitivity (e.g., 80%), as long as the specificity of the diagnostic test remains high (Haine et al., 2018). In our case, this means that as long as our hoof trimmers were not classifying healthy cows as diseased, and even if they underreported some of the lesions, our estimates of foot lesions prevalence and of association between herd-and cow-level predictors and probability of lesions would be unbiased. ...
Our first objective was to estimate the prevalence of foot lesions by type of milking system in dairy cows examined during regular hoof-trimming sessions between 2015 and 2018 in Québec dairy herds. A secondary objective was to describe the effect of day-to-day variation, cow, and herd characteristics on the prevalence of foot lesions. Data included 52,427 observations (on a cow during a specific trimming session) performed on 28,470 cows (≥2 yr old) from 355 herds. Only observations from trimming sessions in which ≥90% of the lactating herd was trimmed were considered. Lesions were recorded at the hoof level by 17 trained hoof trimmers between March 23, 2015, and July 10, 2018, using a computerized recording system. Hoof-level information was then matched with cow information and centralized at the Eastern Canada Dairy Herd Improvement. Foot lesions were classified into 6 categories: infectious, white line disease, heel erosion, ulcers, hemorrhages, and any type of foot lesions. Prevalence of each outcome was quantified using the marginal predicted mean probability estimated from a null generalized linear mixed model with a logit link, and accounted for clustering of observations by cow and by herd. Variance was partitioned to assess the variation in the probability of the outcomes attributable to each level of the data structure (day of exam, cow, and herd). Prevalence of a given foot lesion as function of milking system and of various explanatory variables (mean herd size, herd average daily production, breed of the cow, age of the cow at trimming, and year of the visit) was then estimated using a generalized linear mixed model. At least 1 foot lesion was observed in 29% of cows examined during regular trimming sessions in Québec from 2015 to 2018. Prevalence for any type of lesion was 27% for pipeline, 38% for robotic milking, and 41% for milking parlors. The highest prevalence of infectious lesions (mainly digital dermatitis) was observed in milking parlors and robotic systems, while the most prevalent lesions in pipeline were hemorrhages. Herd-level factors explained most of the disease probability for infectious diseases, heel erosion, and hemorrhages. Therefore, control of these diseases should be based on applying best herd-management practices. On the other hand, probabilities of white line disease and sole ulcers were mainly determined by cow-level characteristics.
... Our study has also some limitations. Although we used the survey weights in our analyses, participation bias cannot be ruled out (Haine et al., 2018). Our study included only community-dwelling individuals. ...
AimsEarly diagnosis and treatment of depression are associated with better prognosis. We used baseline data of the Canadian Longitudinal Study on Aging (2012–2015; ages 45–85 years) to examine differences in prevalence and predictors of undiagnosed depression (UD) between immigrants and non-immigrants at baseline and persistent and/or emerging depressive symptoms (DS) 18 months later. At this second time point, we also examined if a mental health care professional (MHCP) had been consulted.
Methods
We excluded individuals with any prior mood disorder and/or current anti-depressive medication use at baseline. UD was defined as the Center for Epidemiological Studies Depression 10 score ⩾10. DS at 18 months were defined as Kessler 10 score ⩾19. The associations of interest were examined in multivariate logistic regression models.
ResultsOur study included 4382 immigrants and 18 620 non-immigrants. The mean age (standard deviation) in immigrants was 63 (10.3) years v. 65 (10.7) years in non-immigrants and 52.1% v. 57.1% were male. Among immigrants, 12.2% had UD at baseline of whom 34.2% had persistent DS 18 months later v. 10.6% and 31.4%, respectively, among non-immigrants. Female immigrants were more likely to have UD than female non-immigrants (odds ratio 1.50, 95% confidence interval 1.25–1.80) but no difference observed for men. The risk of persistent DS and consulting an MHCP at 18 months did not differ between immigrants and non-immigrants.
Conclusions
Female immigrants may particularly benefit from depression screening. Seeking mental health care in the context of DS should be encouraged.
