European Journal of Public Health最新文献

Background: Although the global chronic morbidity indicator (GCMI) of the Minimum European Health Module (MEHM) was not specifically designed to monitor chronic disease in the population, it is increasingly used for this purpose in Europe and elsewhere. However, its metrological characteristics have seldom been examined, with various sensitivity issues being raised. The present study investigated the metrological performances of the GCMI and analyzed its implications in terms of prevalence and demographic and socioeconomic gradients of chronic conditions in the population.

Methods: We used data from two large French nationwide representative surveys with cross-sectional and longitudinal data conducted between 2010 and 2021. The surveys used MEHM and collected data on numerous chronic conditions and socioeconomic indicators. Criterion and predictive validity of the GCMI regarding chronic conditions and the resultant socioeconomic gradients were compared with indicators based on reports of individual chronic conditions.

Results: GCMI sensitivity to capture chronic conditions varied from <20 to 80% depending on the chronic condition. Number of chronic conditions, gender, age and education were also associated with GCMI endorsement. However, the GCMI was predictive of mortality and activity limitations independently of individual conditions.

Conclusion: The varying lack of sensitivity depending on the chronic condition and the respondent's sociodemographic status may bias estimates of demographic and socioeconomic gradients compared with indicators based on reports of individual chronic conditions. Differences between GCMI and list-based approaches should be more cautiously considered when monitoring chronic conditions in the population. These approaches should be viewed as complementary rather than contradictory or interchangeable.

Inconsistent results are found regarding social inequalities related to healthcare appointment cancellations during the COVID-19 crisis. Whether rescheduling was associated with social status is unknown. By studying both cancellations and rescheduling, we comprehensively describe which social groups were affected by care disruption. First follow-up of a random population-based cohort was used, including 95 118 people aged 18 or older at baseline and who live in France. Poisson and multinomial regressions were used to study social factors associated with experiencing both medical appointment cancellation by health professionals during the first COVID-19 lockdown, and rescheduling within six months. Among all individuals (including those without scheduled appointment), 21.1% reported cancellations initiated by healthcare professionals. Women, the richest, and those with a chronic disease were the most affected by these cancellations. Although 78.1% who had their appointment cancelled obtained a new appointment within six months, 6.6% failed to reschedule and 15.2% did not want to reschedule. While the oldest were more likely to reschedule, regardless of their health status, the poorest and those with multiple chronic diseases were less likely to do so. Difficulties in rescheduling revealed certain social groups were ultimately more penalized by the restriction of access to care during the first wave of the COVID-19 pandemic. Given that the poorest people, a social group that is in poorer health condition compared to other groups, were the most affected, our results raise questions about the ability of the healthcare system to reduce social health inequalities during a major health crisis.

Given the enormous scale of the COVID-19 pandemic affecting the healthcare sector, limited human resource capacity, and efforts to prevent the spread of COVID-19, occupational health protection could not escape changes. The aim was to identify and compare the regulations regarding the provision of medical occupational check-ups (MOCs) during the pandemic in all European Union member states (EU MS). The study employed the Delphi method, involving experts from EU MS to assess MOC regulations between January 2020 and May 2021. Experts were queried regarding the existence and specifics of MOC regulations, particularly for entrance and periodic MOCs at hazardous and non-hazardous workplaces. Out of the 27 EU MS surveyed, 13 EU MS did not regulate MOCs, while 14 EU MS (51.6%) regulated the provision of MOCs. The regulations were changes in the way MOCs were provided, modifications (postponement in time, alternative provision, e.g. using telemedicine or online connection, or replacing the medical certificate of fitness to work based on the MOC with a declaration by the worker), or interruption without compensation, even for hazardous works. The regulations were in effect for different lengths of time and varied in some countries during the study period. The cumulative duration of MOC interruptions in all EU MS during the study period was 137 months (7.5% of the cumulative study period of 1836 months). Given the different approaches to the provision of MOCs in EU MS, it has proved appropriate to develop an optimal unified framework plan for future similar situations.

Internationally accepted diagnostic criteria recommendations for gestational diabetes (GDM) in 2010 resulted in a rise in global prevalence of GDM. Our aim was to describe the trends in GDM before and after Icelandic guideline changes in 2012 and the trends in pregestational diabetes (PGDM). The study included all singleton births (N = 101 093) in Iceland during 1997-2020. Modified Poisson regression models were used to estimate prevalence ratios (PRs) with 95% confidence intervals (CIs) for risk of GDM overall and by maternal age group, as well as overall risk of PGDM, according to time period of birth. The overall prevalence of GDM by time period of birth ranged from 0.6% (N = 101) in 1997-2000 to 16.2% (N = 2720) in 2017-2020, and the prevalence of PGDM ranged from 0.4% (N = 57) in 1997-2000 to 0.7% (N = 120) in 2017-2020. The overall relative GDM prevalence rate difference before and after 2012 was 380%, and the largest difference was found among women aged <25 years at 473%. Risk of GDM increased in 2017-2020 (PR 14.21, CI 11.45, 17.64) compared to 1997-2000 and was highest among women aged >34 years with PR 19.46 (CI 12.36, 30.63) in 2017-2020. Prevalence rates of GDM and PGDM increased during the study period. An accelerated rate of increase in GDM was found after 2012, overall, and among all maternal age groups. Women aged >34 years had the greatest risk of GDM throughout all time periods, while women aged <25 years appear to have a higher relative rate difference after 2012.

Background: The literature on the association between fine particulate matter (PM2.5) exposure and gestational diabetes mellitus (GDM) risk has focused mainly on exposure during the first and second trimesters, and the research results are inconsistent. Therefore, this study aimed to investigate the associations between PM2.5 exposure during preconception, the first trimester and second trimester and GDM risk in pregnant women in Guangzhou.

Methods: A retrospective cohort study of 26 354 pregnant women was conducted, estimating PM2.5, particulate matter with a diameter >10 µm (PM10), sulphur dioxide (SO2), carbon monoxide (CO) and ozone (O3) exposure during preconception and the first and second trimesters. Analyses were performed using Cox proportional hazards models and nonlinear distributed lag models.

Results: The study found that exposure to PM2.5 or a combination of two pollutants (PM2.5+PM10, PM2.5+SO2, PM2.5+CO and PM2.5+O3) was found to be significantly associated with GDM risk (P < 0.05). In the second trimester, with significant interactions found for occupation and anaemia between PM2.5 and GDM. When the PM2.5 concentrations were ≥19.56, ≥25.69 and ≥23.87 μg/m3 during preconception and the first and second trimesters, respectively, the hazard ratio for GDM started to increase. The critical window for PM2.5 exposure was identified to be from 9 to 11 weeks before conception.

Conclusions: Our study results suggest that PM2.5 exposure during preconception and the first and second trimesters increases the risk of GDM, with the preconception period appearing to be the critical window for PM2.5 exposure.

Background: Social inequalities in multimorbidity may occur due to familial and/or individual factors and may differ between men and women. Using population-based multi-generational data, this study aimed to (1) assess the roles of parental and individual education in the risk of multimorbidity and (2) examine the potential effect modification by sex.

Methods: Data were analysed from 62 060 adults aged 50+ who participated in the Survey of Health, Ageing and Retirement in Europe, comprising 14 European countries. Intergenerational educational trajectories (exposure) were High-High (reference), Low-High, High-Low and Low-Low, corresponding to parental-individual educational attainments. Multimorbidity (outcome) was ascertained between 2013 and 2020 as self-reported occurrence of ≥2 diagnosed chronic conditions. Inequalities were quantified as multimorbidity-free years lost (MFYL) between the ages of 50 and 90 and estimated via differences in the area under the standardized cumulative risk curves. Effect modification by sex was assessed via stratification.

Results: Low individual education was associated with higher multimorbidity risk regardless of parental education. Compared to the High-High trajectory, Low-High was associated with -0.2 MFYL (95% confidence intervals: -0.5 to 0.1), High-Low with 3.0 (2.4-3.5), and Low-Low with 2.6 (2.3-2.9) MFYL. This pattern was observed for both sexes, with a greater magnitude for women. This effect modification was not observed when only diseases diagnosed independently of healthcare-seeking behaviours were examined.

Conclusions: Individual education was the main contributor to intergenerational inequalities in multimorbidity risk among older European adults. These findings support the importance of achieving a high education to mitigate multimorbidity risk.

Background: Some studies have reported an increase in suicides after the start of daylight saving time (DST), but the evidence is mixed and more research about proposed mechanisms (disrupted sleep, changing light exposure) is needed.

Methods: In our preregistered study, we analyzed change in suicide rates in the 2 weeks before/after DST, based on data between 1980 and 2022 from Austria, Switzerland and Sweden, using Poisson regression models and changepoint analyses. To explore the impact of disrupted sleep, we repeated the analysis for retired people who are likely less bound to DST, and for younger people. To explore the effect of changed daylight exposure, we repeated the analysis for northern and southern regions because twilight and daylight exposure varies by latitude.

Results: Suicide rates did not significantly increase after the start of DST (adjusted incidence rate ratio IRR = 0.98, 95% CI 0.91-1.06, P = 0.66, n = 13 362 suicides) or after DST ended (adjusted IRR = 0.99, 95% CI 0.91-1.07, P = 0.76, n = 12 319 suicides). There were no statistically significant findings among younger or older subgroups and also not in Sweden and Austria/Switzerland. No changepoints were detected.

Conclusions: There were no significant changes in suicide rates associated with DST and no clear evidence to support proposed mechanisms (light exposure, disruption of sleep). Our study is one of the largest and was adequately powered. Nonetheless, even larger studies to detect smaller effects could be important to inform the debate about harms and benefits of DST.