Associations of Migration, Socioeconomic Position and Social Relations With Depressive Symptoms - Analyses of the German National Cohort Baseline Data.

Objectives: We analyze whether the prevalence of depressive symptoms differs among various migrant and non-migrant populations in Germany and to what extent these differences can be attributed to socioeconomic position (SEP) and social relations. Methods: The German National Cohort health study (NAKO) is a prospective multicenter cohort study (N = 204,878). Migration background (assessed based on citizenship and country of birth of both participant and parents) was used as independent variable, age, sex, Social Network Index, the availability of emotional support, SEP (relative income position and educational status) and employment status were introduced as covariates and depressive symptoms (PHQ-9) as dependent variable in logistic regression models. Results: Increased odds ratios of depressive symptoms were found in all migrant subgroups compared to non-migrants and varied regarding regions of origins. Elevated odds ratios decreased when SEP and social relations were included. Attenuations varied across migrant subgroups. Conclusion: The gap in depressive symptoms can partly be attributed to SEP and social relations, with variations between migrant subgroups. The integration paradox is likely to contribute to the explanation of the results. Future studies need to consider heterogeneity among migrant subgroups whenever possible.

Authors' response: Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias.

We thank van Tongeren et al for responding to our study on occupational disparities in SARS-CoV-2 infection risks during the first pandemic wave in Germany (1). The authors address the potential for bias resulting from differential testing between occupational groups and propose an alternative analytical strategy for dealing with selective testing. In the following, we want to discuss two aspects of this issue, namely (i) the extent and reasons of differential testing in our cohort and (ii) the advantages and disadvantages of different analytical approaches to study risk factors for SARS-CoV-2 infection. Our study relied on nationwide prospective cohort data including more than 100 000 workers in order to compare the incidence of infections between different occupations and occupational status positions. We found elevated infection risks in personal services and business administration, in essential occupations (including health care) and among people in higher occupational status positions (ie, managers and highly skilled workers) during the first pandemic wave in Germany (2). Van Tongeren's et al main concern is that the correlations found could be affected by a systematic bias because people in healthcare professions get tested more often than employees in other professions. A second argument is that better-off people could be more likely to use testing as they are less affected by direct costs (prices for testing) and the economic hardship associated with a positive test result (eg, loss of earnings in the event of sick leave). We share the authors' view that differential testing must be considered when analysing and interpreting the data. Thus, in our study, we examined the proportion of tests conducted in each occupational group as part of the sensitivity analyses (see supplementary figure S1, accessible at www.sjweh.fi/article/4037). As expected, testing proportions were exceptionally high in medical occupations (due to employer requirements). However, we did not observe systematic differences among non-medical occupations or when categorising by skill-level or managerial responsibility. This might be explained by several reasons. First, SARS-CoV-2 testing was free of charge during the first pandemic wave in Germany, but reporting a risk contact or having symptoms was a necessary condition for testing ( https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html (accessed 5 September 2022). The newspaper article cited by van Tongeren et al is misleading as it refers to a calendar date after our study period. Second, different motivation for testing due to economic hardship in case of a positive test result is an unlikely explanation, because Germany has a universal healthcare system, including paid sick leave and sickness benefits for all workers (3). Self-employed people carry greater financial risks in case of sickness. We therefore included self-employment in the multivariable analyses to address this potential source of bias. While the observed inverse social gradient may be surprising, it actually matches with findings of ecological studies from Germany (4, 5), the United States (6, 7) as well as Spain, Portugal, Sweden, The Netherlands, Israel, and Hong Kong (8), all of which observed higher infection rates in wealthier neighbourhoods during the initial outbreak phase of the pandemic. One possible explanation is the higher mobility of managers and better educated workers, who are more likely to participate in meetings and engage in business travel and holiday trips like skiing. Given the increasing number of studies providing evidence for this hypothesis, we conclude that the inverse social gradient in our study likely reflects different exposure probabilities and is not a result of systematic bias. This also holds true for the elevated infection risks in essential workers, which is actually corroborated by a large body of research (9-11). Regarding differential likelihood of testing, van Tongeren et al state that "[i]t is relatively simple to address this problem by using a test-negative design" (1). As van Tongeren et al describe, this is a case-control approach only including individuals who were tested (without considering those who were not tested). However, the proposed analytical strategy can lead to another (more serious) selection bias if testing proportions and/or testing criteria differ between groups (12). This can be easily illustrated when comparing the results based on a time-incidence design with those obtained by a test-negative design as shown in table 1 (see PDF). Both approaches show similar results in terms of vertical occupational differences. Infection was more common if individuals had a high skill level or had a managerial position, but associations were stronger in the time-incidence design and did not reach statistical significance in the test-negative design (as indicated by the confidence intervals overlapping "1"). Unfortunately, the test-negative approach relies on a strongly reduced sample size and thus results in greater statistical uncertainty and loss of statistical power (13). In contrast, the test-negative design yields a different picture when estimating the association between essential occupation and infection risk: In this analysis, essential workers did not differ from non-essential workers in their chance of being infected with SARS-CoV-2 (the test-negative design even exhibits a lower chance for essential workers). This is rather counter-intuitive and is not in accordance with what we know about the occupational hazards of healthcare workers during the pandemic (14). The main problem is that proportions of positive tests are highly unreliable when testing proportions and/or testing criteria differ between groups. As essential workers were tested more often without being symptomatic (due to employer requirements), a lower proportion of positive tests in this group does not necessarily correspond to a lower risk of infection. Consequently, we are not convinced that the test-negative design should be the 'gold standard' for studying risk factors for SARS-CoV-2 infections (15). Especially problematic is the loss of statistical power (increasing the probability of a type II error) and the low validity of the test-positivity when test criteria and/or test proportions differ between groups. References 1. van Tongeren M, Rhodes S, Pearce N. Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias. Scand J Work Environ Health 2022;48(7):586-587. https://doi.org/10.5271/sjweh.4052. 2. Reuter M, Rigó M, Formazin M, Liebers F, Latza U, Castell S, et al. Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany. Scand J Work Environ Health 2022;48:446-56. https://doi.org/10.5271/sjweh.4037. 3. Busse R, Blümel M, Knieps F, Bärnighausen T. Statutory health insurance in Germany: a health system shaped by 135 years of solidarity, self-governance, and competition. Lancet 2017;390:882-97. https://doi.org/10.1016/S0140-6736(17)31280-1. 4. Wachtler B, Michalski N, Nowossadeck E, Diercke M, Wahrendorf M, Santos-Hövener C, et al. Socioeconomic inequalities in the risk of SARS-CoV-2 infection - First results from an analysis of surveillance data from Germany. J Heal Monit 2020;5:18-29. https://doi.org/10.25646/7057. 5. Plümper T, Neumayer E. The pandemic predominantly hits poor neighbourhoods? SARS-CoV-2 infections and COVID-19 fatalities in German districts. Eur J Public Health 2020;30:1176-80. https://doi.org/10.1093/eurpub/ckaa168. 6. Abedi V, Olulana O, Avula V, Chaudhary D, Khan A, Shahjouei S, et al. Racial, Economic, and Health Inequality and COVID-19 Infection in the United States. J Racial Ethn Heal Disparities 2021;8:732-42. https://doi.org/10.1007/s40615-020-00833-4. 7. Mukherji N. The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase. Rev Reg Stud 2022;52. https://doi.org/10.52324/001c.35255. 8. Beese F, Waldhauer J, Wollgast L, Pförtner T, Wahrendorf M, Haller S, et al. Temporal Dynamics of Socioeconomic Inequalities in COVID-19 Outcomes Over the Course of the Pandemic-A Scoping Review. Int J Public Health 2022;67:1-14. https://doi.org/10.3389/ijph.2022.1605128. 9. Nguyen LH, Drew DA, Graham MS, Joshi AD, Guo C-G, Ma W, et al. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Heal 2020;5:e475-83. https://doi.org/10.1016/S2468-2667(20)30164-X. 10. Chou R, Dana T, Buckley DI, Selph S, Fu R, Totten AM. Epidemiology of and Risk Factors for Coronavirus Infection in Health Care Workers. Ann Intern Med 2020;173:120-36. https://doi.org/10.7326/M20-1632. 11. Stringhini S, Zaballa M-E, Pullen N, de Mestral C, Perez-Saez J, Dumont R, et al. Large variation in anti-SARS-CoV-2 antibody prevalence among essential workers in Geneva, Switzerland. Nat Commun 2021;12:3455. https://doi.org/10.1038/s41467-021-23796-4. 12. Accorsi EK, Qiu X, Rumpler E, Kennedy-Shaffer L, Kahn R, Joshi K, et al. How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19. Eur J Epidemiol 2021;36:179-96. https://doi.org/10.1007/s10654-021-00727-7. 13. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd Editio. New York: Routledge; 2013. https://doi.org/10.4324/9780203771587. 14. The Lancet. The plight of essential workers during the COVID-19 pandemic. Lancet 2020;395:1587. https://doi.org/10.1016/S0140-6736(20)31200-9. 15. Vandenbroucke JP, Brickley EB, Pearce N, Vandenbroucke-Grauls CMJE. The Evolving Usefulness of the Test-negative Design in Studying Risk Factors for COVID-19. Epidemiology 2022;33:e7-8. https://doi.org/10.1097/EDE.0000000000001438.

Increase in Mental Disorders During the COVID-19 Pandemic-The Role of Occupational and Financial Strains.

BACKGROUND: Numerous studies have reported an increase in mental disorders during the COVID-19 pandemic, but the exact reasons for this development are not well understood. In this study we investigate whether pandemic-related occupational and financial changes (e.g., reduced working hours, working from home, financial losses) were associated with increased symptoms of depression and anxiety compared with the situation before the pandemic. METHODS: We analyzed data from the German National Cohort (NAKO) Study. Between May and November 2020, 161 849 study participants answered questions on their mental state and social circumstances. Their responses were compared with data from the baseline survey before the pandemic (2014-2019). Linear fixed-effects models were used to determine whether individual changes in the severity of symptoms of depression (PHQ-9) or anxiety (GAD-7) were associated with occupational/ financial changes (controlling for various covariates). RESULTS: The prevalence of moderate or severe symptoms of depression and anxiety increased by 2.4% and 1.5%, respectively, during the COVID-19 pandemic compared with the preceding years. The mean severity of the symptoms rose slightly. A pronounced increase in symptoms was observed among those who became unemployed during the pandemic (+ 1.16 points on the depression scale, 95% confidence interval [0.91; 1.41], range 0-27). Increases were also seen for reduced working hours with no short-time allowance, increased working hours, working from home, insecurity regarding employment, and financial strain. The deterioration in mental health was largely statistically explained by the occupational and financial changes investigated in the model. CONCLUSION: Depressive symptoms and anxiety disorders increased slightly in the study population during the first year of the COVID-19 pandemic. Occupational and financial difficulties were an essential contributory factor. These strains should be taken into account both in the care of individual patients and in the planning of targeted prevention measures.

[Physical activity in the German National Cohort (NAKO): use of multiple assessment tools and initial results]. / Körperliche Aktivität in der NAKO Gesundheitsstudie: erste Ergebnisse des multimodalen Erhebungskonzepts.

BACKGROUND: Physical activity is a complex behavior that is difficult to measure validly and reliably in large, population-based studies. Data on physical activity are available for the initial 100,000 participants of the German National Cohort. OBJECTIVES: To describe the baseline physical activity assessment in the cohort and to present initial descriptive results. MATERIAL AND METHODS: Physical activity was assessed using a combination of tools, including two self-administered questionnaires, the Questionnaire on Annual Physical Activity Pattern (QUAP) and the Global Physical Activity Questionnaire (GPAQ); a computer-based 24­h physical activity recall (cpar24); and 7­day accelerometry (Actigraph GT3X/+; ActiGraph, Pensacola, FL, USA). RESULTS: The availability of data varied between assessment instruments (QUAP: n = 16,372; GPAQ: n = 90,900; cpar24: n = 23,989; accelerometry: n = 35,218). Analyses across measurement tools showed that on average, women spent 75 to 216 min/d, and men spent 73 to 224 min/d in moderate or higher intensity total physical activity. Persons aged 20-39 years spent 66 to 200 min/d, and persons aged 40-69 years spent 78 to 244 min/d in moderate or higher intensity total physical activity. CONCLUSIONS: Initial baseline analyses of physical activity in this cohort show the value of using a combination of questionnaires, 24­h recalls, and a movement sensor. The comprehensive data collection represents a valuable resource for future analyses and will improve our understanding of the association between physical activity and disease prevention.

Feasibility and relative validity of a digital photo-based dietary assessment: results from the Nutris-Phone study.

OBJECTIVE: For dietary assessment, mobile devices with a camera can be used as an alternative to hand-written paper records. The Nutritional Tracking Information Smartphone (Nutris-Phone) study aimed to examine relative validity and feasibility of a photo-based dietary record in everyday life. DESIGN: Parallel to the photo-based technique, a weighed record was performed. Participant satisfaction was assessed by questionnaire. A trained nutrition scientist evaluated portion sizes and nutrient content was calculated (DGExpert). Spearman correlation and Bland-Altman analyses were applied. SETTING: Healthy, non-pregnant volunteers (≥18 years) without intent to lose weight recruited at Ulm University, Germany. SUBJECTS: Sixty-six participants (36 % males, median age 22·0 (interquartile range 20·0-25·0) years) took pictures of foods and beverages consumed with a commercially available mobile phone. RESULTS: Significant correlation between the photo-based and weighed record was observed: energy (r=0·991), carbohydrate (r=0·980), fat (r=0·972), protein (r=0·988), fibre (r=0·941). Bland-Altman analyses indicated comparable means and acceptable 95 % limits of agreement (energy: -345·2 to 302·9 kJ (-82·5 to 72·4 kcal); carbohydrate: -15·2 to 13·1 g; fat: -6·4 to 6·4 g; protein: -5·9 to 5·6 g; fibre: -2·7 to 2·5 g). However, with increasing intake level, underestimation by the digital method was present (except for fat, all P<0·01). Over 80 % of participants were satisfied with the photo-based record. In nearly 90 %, technical implementation was without major problems. CONCLUSIONS: Compared with a weighed record, the photo-based dietary record seems to be valid, feasible and user-friendly to estimate energy, macronutrient and fibre intakes, although a systematic bias with increasing levels of intake should be kept in mind.

Area Deprivation and Regional Disparities in Treatment and Outcome Quality of 29,284 Pediatric Patients With Type 1 Diabetes in Germany: A Cross-sectional Multicenter DPV Analysis.

OBJECTIVE: This study analyzed whether area deprivation is associated with disparities in health care of pediatric type 1 diabetes in Germany. RESEARCH DESIGN AND METHODS: We selected patients <20 years of age with type 1 diabetes and German residence documented in the "diabetes patient follow-up" (Diabetes-Patienten-Verlaufsdokumentation [DPV]) registry for 2015/2016. Area deprivation was assessed by quintiles of the German Index of Multiple Deprivation (GIMD 2010) at the district level and was assigned to patients. To investigate associations between GIMD 2010 and indicators of diabetes care, we used multivariable regression models (linear, logistic, and Poisson) adjusting for sex, age, migration background, diabetes duration, and German federal state. RESULTS: We analyzed data from 29,284 patients. From the least to the most deprived quintile, use of continuous glucose monitoring systems (CGMS) decreased from 6.3 to 3.4% and use of long-acting insulin analogs from 80.8 to 64.3%, whereas use of rapid-acting insulin analogs increased from 74.7 to 79.0%; average HbA1c increased from 7.84 to 8.07% (62 to 65 mmol/mol), and the prevalence of overweight from 11.8 to 15.5%, but the rate of severe hypoglycemia decreased from 12.1 to 6.9 events/100 patient-years. Associations with other parameters showed a more complex pattern (use of continuous subcutaneous insulin infusion [CSII]) or were not significant. CONCLUSIONS: Area deprivation was associated not only with key outcomes in pediatric type 1 diabetes but also with treatment modalities. Our results show, in particular, that the access to CGMS and CSII could be improved in the most deprived regions in Germany.

Hospital admission in children and adolescents with or without type 1 diabetes from Germany: An analysis of statutory health insurance data on 12 million subjects.

OBJECTIVE: To compare the chance of hospital admissions in children and adolescents with type 1 diabetes (T1D) to that without T1D from Germany. METHODS: Data were provided by the German information system for health care data which contains information on all patients with a statutory health insurance. The years 2009 and 2011 were considered. Children and adolescents (0 to ≤19 years of age; n = 12 030 242) were included. Unadjusted odds ratios (ORs) with 95% confidence interval (95% CI) were used to compare the hospitalization rate for patients with (n = 26 444) or without T1D (12 003 798). T1D was identified by documented insulin treatment and by ICD-code E10/14. Results were stratified by age-group (0-5; >5-10; >10-15, >15-19 years) and gender. RESULTS: In all age-groups, the hospitalization chance in patients with T1D was higher compared to that of their peers (database 2011). The highest OR was observed in >5 to 10-year-old patients (OR 8.1; 95% CI: 7.7-8.5), followed by patients >10 to 15 years (OR 7.4; 95% CI: 7.1-7.7) and patients ≤5 years (OR 5.3; 95% CI: 4.8-5.7). The lowest OR was present in patients >15 to 19 years (OR 4.0; 95% CI: 3.9-4.2). Overall, OR for hospital admission were higher in girls with T1D compared to boys. The most frequent reasons for hospitalization in T1D were "T1D without complications" (68.4%) and "T1D with ketoacidosis" (18.6%). CONCLUSIONS: Children and adolescents with T1D in Germany had a 4 to 8 times higher hospitalization chance compared to children without T1D. The OR in T1D patients compared to peers were higher in girls than in boys. High rates of elective hospital admission in Germany may contribute to these results.

Access to Difficult-to-reach Population Subgroups: A Family Midwife Based Home Visiting Service for Implementing Nutrition-related Preventive Activities - A Mixed Methods Explorative Study.

Health and social inequality are tightly linked and still pose an important public health problem. However, vulnerable and disadvantaged populations are difficult to reach for health-related interventions. Given the long-lasting effects of an adverse, particular nutrition-related, intrauterine and neonatal environment on health development (perinatal programming), an early and easy access is essential for sustainable interventions. The goal of this explorative study was therefore to elucidate whether an existing access of family midwives (FMs) to families in need of support could be an option to implement effective public health and nutrition interventions. To that end three research objectives were formulated: (1) to determine whether a discernible impact of home visits by FMs can be described; (2) to identify subgroups among these families in need of more specific interventions; (3) to determine how relevant nutrition-related topics are for both FMs and the supported families. For addressing these objectives a mixed methods design was used: Routine documentation data from 295 families visited by a family midwife (FM) were analyzed (secondary analysis), and structured expert interviews with FMs were conducted and analyzed. Study reporting followed the STROBE (STrengthening the Reporting of OBservational studies in Epidemiology) statement. Based on the FMs reports, a significant improvement (p < 0.001) regarding psycho-social variables could be determined after the home visits. Single mothers, however, seemed to benefit less from the FMs service compared to their counterparts (p = 0.015). Nutritional counseling was demanded by 89% of the families during the home visits. In addition, nutrition-related topics were reported in the interviews to be of high interest to both families and the FMs. Based on the obtained results it is concluded that FMs home visits offer a promising access to vulnerable and disadvantaged families for implementing nutrition-related preventive activities.