Journal of Epidemiology and Community Health最新文献

Background: The opioid overdose mortality crisis in the USA is an ongoing public health epidemic. Ongoing law enforcement strategies to disrupt local unregulated drug markets can have an iatrogenic effect of increasing overdose by driving consumers towards new suppliers with unpredictable drug products of unknown potency.

Methods: Cross-sectional study using point-level information on law enforcement opioid-related drug seizures from property room data, opioid-related non-fatal overdose events from emergency medical services and block group-level social determinants of health data from multiple sources. Using an endemic-epidemic spatiotemporal regression model, we estimated the degree to which exposure to drug supply disruptions triggers future overdose events within small space-time distances in Indianapolis, Indiana.

Results: Neighbourhoods with more structural racism, economic deprivation or urban blight were associated with higher rates of non-fatal overdose. Exposure to an opioid-related drug seizure event had a significant and positive effect on the epidemic probability of non-fatal overdose. An opioid seizure that occurred within 250 m and 3 days, 250 m and 7 days, and 250 m and 14 days of an overdose event increased the risk of a new non-fatal overdose by 2.62 (rate ratio (RR)=2.62, 95% CI 1.87 to 3.67), 2.17 (RR=2.17, 95% CI 1.87 to 2.59) and 1.83 (RR=1.83, 95% CI 1.66 to 2.02), respectively. Similar spatiotemporal patterns were observed in a smaller spatial bandwidth.

Conclusions: Results demonstrated that overdoses exhibit a community spread process, which is exacerbated following law enforcement strategies to disrupt the unregulated drug market. We discuss decriminalisation and increasing resources that promote safer drug use to combat this public health crisis.

The interest in the impact of urban environmental exposures (UrbEEs) on mental health has greatly increased in the last two decades. Researchers have tended to measure said exposures either via objective measurement procedures (eg, air pollution campaigns and geographic information systems computations) or by self-reported techniques such as the use of scales and questionnaires. It has been suggested that studying both the objective features of the environments and people's perceptions are key to understand environmental determinants of health and might be needed to tailor effective interventions. However, there is little guidance on how to approach this matter, the comparability between objective and subjective accounts of UrbEEs and, more importantly, suitable statistical procedures to deal with the practicalities of this kind of data. In this essay, we aim to build the case for the joint use of both sets of variables in epidemiological studies and propose socioecological models as a valid theoretical framework to accommodate these. In the methodological sphere, we will also review current literature to select examples of (un)appropriate subjective accounts of urban exposures and propose a series of statistical procedures to estimate the total, direct and indirect effects of UrbEEs on mental health and the potential associations between objective and subjective UrbEEs accounts.

Objective: To examine the association between precarious employment and risk of work-related COVID-19 infection in Ontario, Canada.

Methods: We combined data from an administrative census of workers' compensation claims with corresponding labour force statistics to estimate rates of work-related COVID-19 infection between April 2020 and April 2022. Precarious employment was imputed using a job exposure matrix capturing temporary employment, low wages, irregular hours, involuntary part-time employment and a multidimensional indicator of 'low', 'medium', 'high' and 'very high' overall exposure to precarious employment. We used negative binomial regression models to quantify associations between precarious employment and accepted compensation claims for COVID-19.

Results: We observed a monotonic association between precarious employment and work-related COVID-19 claims. Workers with 'very high' exposure to precarious employment presented a nearly fivefold claim risk in models controlling for age, sex and pandemic wave (rate ratio (RR): 4.90, 95% CI 4.07 to 5.89). Further controlling for occupational exposures (public facing work, working in close proximity to others, indoor work) somewhat attenuated observed associations. After accounting for these factors, workers with 'very high' exposure to precarious employment were still nearly four times as likely to file a successful claim for COVID-19 (RR: 3.78, 95% CI 3.28 to 4.36).

Conclusions: During the first 2 years of the pandemic, precariously employed workers were more likely to acquire a work-related COVID-19 infection resulting in a successful lost-time compensation claim. Strategies aiming to promote an equitable and sustained recovery from the pandemic should consider and address the notable risks associated with precarious employment.

Background: The association of maternal cigarette smoking during pregnancy with severe neonatal morbidity (SNM) is still inconclusive. We aimed to examine the associations of the timing and the intensity of maternal cigarette smoking with infant SNM in the USA.

Methods: We used birth certificate data of 12 150 535 women aged 18-49 years who had live singleton births from the 2016-2019 US National Vital Statistics System. Women self-reported the daily number of cigarettes they consumed before pregnancy and in each trimester of pregnancy. Composite SNM was defined as one or more of the following complications: assisted ventilation immediately following delivery, assisted ventilation for >6 hours, neonatal intensive care unit admission, surfactant replacement therapy, suspected neonatal sepsis, and seizure.

Results: Maternal cigarette smoking either before pregnancy or during any trimester of pregnancy significantly increased the risk of infant SNM, even at a very low intensity (ie, 1-2 cigarettes per day). For example, compared with women who did not smoke before pregnancy, the adjusted odds ratios and 95% confidence intervals (OR, 95% CI) of composite SNM in the newborn from women who smoked 1-2, 3-5, 6-9, 10-19, and ≥20 cigarettes per day before pregnancy were 1.16 (1.13 to 1.19), 1.22 (1.20 to 1.24), 1.26 (1.23 to 1.29), 1.27 (1.25 to 1.28), and 1.31 (1.30 to 1.33), respectively. Furthermore, smokers who stopped smoking during pregnancy still had a higher risk of composite SNM than never smokers before and throughout pregnancy.

Conclusions: Maternal cigarette smoking before or during pregnancy increased the risk of infant SNM, even at a low dose of 1-2 cigarettes/day. Interventions should emphasise the detrimental effects of even light smoking before and during pregnancy.

Background: Previous studies on the associations between socioeconomic status (SES) and cutaneous malignant melanoma (CMM) failed to distinguish the effects of different SES factors under an individual-data-based prospective study design.

Methods: Based on UK Biobank (UKB) and China Kadoorie Biobank (CKB), we estimated the effects of four SES factors on transitions from baseline to CMM in situ, subsequently to invasive CMM and further CMM mortality by applying multistate models. We further explored to which extent the associations between SES and CMM incidence could be explained by potential mediators including sun exposure, lifestyle and ageing in UKB.

Results: In multistate analyses, good household income was independently associated with an increased risk of CMM in situ (HR=1.38, 95% CI: 1.21 to 1.58) and invasive CMM (HR=1.34, 95% CI: 1.22 to 1.48) in UKB. These findings were partly validated in CKB. Especially in UKB, we observed an increased risk of CMM in situ and invasive CMM among participants with good type of house; only good education was independently associated with lower risk of evolving to invasive CMM among patients with CMM in situ (HR=0.69, 95% CI: 0.52 to 0.92); only good household income was independently associated with lower risk of CMM mortality among patients with CMM (HR=0.65, 95% CI: 0.45 to 0.95). In mediation analysis, the proportions attributable to the mediating effect were <6% for all selected variables, including self-reported sun exposure-related factors.

Conclusion: SES factors have different effects on the incidence and progression of CMM. The association between SES and incident CMM is neither causal nor well explained by selected mediators.

Background: This study explores socioeconomic differences in acceptability and preferences for policies that aim to reduce socioeconomic health inequalities. The investigated policies range from structural policies, requiring no individual agency, to agentic policies, which depend on the individual agency for behaviour change.

Methods: An online, cross-sectional survey was conducted among 1182 participants, stratified by education and representative of Dutch adults (aged 25-65) for age and gender. Across 31 policies, including structural socioeconomic policies, structural housing and neighbourhood policies, structural and agento-structural behavioural policies (facilitating behaviour) and agentic policies (focusing on information provision for behaviour change), acceptability was measured on a 7-point scale, preferences were measured using participants' top-5 policy choices. Regression analyses examined socioeconomic differences in acceptability and preferences based on education and income, controlling for age, gender, receiving welfare, and employment.

Results: People in lower socioeconomic positions were more likely to accept and favour structural socioeconomic policies, whereas those in higher socioeconomic positions were more likely to accept and favour structural housing and neighbourhood, structural and agento-structural behavioural, and agentic policies. Socioeconomic differences were the largest for agentic policies. Overall, 83.3% preferred at least one structural socioeconomic policy, while only 32% preferred an agentic policy. Most preferred was eliminating taxes on fruits and vegetables, (preferred by 41.4%), and least preferred was a campaign promoting healthy nutrition (preferred by 3.9%).

Conclusions: These socioeconomic differences in policy support underscore the need for inclusive policymaking processes. Including the perspectives of people in lower socioeconomic positions helps to ensure that their needs are met.

Background: Previous studies investigating the association between obesity and diabetes often did not consider the role of time-varying covariates affected by previous obesity status. This study quantified the association between obesity and diabetes using parametric g-formula.

Methods: We included 8924 participants without diabetes from the Korean Genome and Epidemiology Study-Ansan and Ansung study(2001-2002)-with up to the seventh biennial follow-up data from 2015 to 2016. Obesity status was categorised as normal (body mass index (BMI) <23.5 kg/m²), overweight (23.5-24.9 kg/m²), obese 1 (25.0-27.4 kg/m²) and obese 2 (≥27.5 kg/m²). Hazard ratios (HRs) comparing baseline or time-varying obesity status were estimated using Cox models, whereas risk ratio (RR) was estimated using g-formula.

Results: The Cox model for baseline obesity status demonstrated an increased risk of diabetes in overweight (HR 1.85; 95% CI=1.48-2.31), obese 1 (2.40; 1.97-2.93) and obese 2 (3.65; 2.98-4.47) statuses than that in normal weight status. Obesity as a time-varying exposure with time-varying covariates had HRs of 1.31 (1.07-1.60), 1.55 (1.29-1.86) and 2.58 (2.14-3.12) for overweight, obese 1 and obese 2 statuses. Parametric g-formula comparing if everyone had been in each obesity category versus normal over 15 years showed increased associations of RRs of 1.37 (1.34-1.40), 1.78 (1.76-1.80) and 2.42 (2.34-2.50).

Conclusions: Higher BMI classification category was associated with increased risk of diabetes after accounting for time-varying covariates using g-formula. The results from g-formula were smaller than when considering baseline obesity status only but comparable with the results from time-varying Cox model.

Background: Australia has experienced extreme fire weather in recent years. Information on the impact of fine particulate matter (PM _2.5 ) from landscape fires (LFs) on cardiorespiratory hospital admissions is limited.

Methods: We conducted a population-based time series study to assess associations between modelled daily elevated PM _2.5 at a 1.5×1.5 km resolution using a modified empirical PM _2.5 exposure model during LFs and hospital admissions for all-cause and cause-specific respiratory and cardiovascular diseases for the study period (2015-2017) in Perth, Western Australia. Multivariate Poisson regressions were used to estimate cumulative risk ratios (RR) with lag effects of 0-3 days, adjusted for sociodemographic factors, weather and time.

Results: All-cause hospital admissions and overall cardiovascular admissions increased significantly across each elevated PM _2.5 concentration on most lag days, with the strongest associations of 3% and 7%, respectively, at the high level of ≥12.60 µg/m³ on lag 1 day. For asthma hospitalisation, there was an excess relative risk of up to 16% (RR 1.16, 95% CI 1.00 to 1.35) with same-day exposure for all people, up to 93% on a lag of 1 day in children and up to 52% on a lag of 3 days in low sociodemographic groups. We also observed an increase of up to 12% (RR 1.12, 95% CI 1.02 to 1.24) for arrhythmias on the same exposure day and with over 154% extra risks for angina and 12% for heart failure in disadvantaged groups.

Conclusions: Exposure to elevated PM _2.5 concentrations during LFs was associated with increased risks of all-cause hospital admissions, total cardiovascular conditions, asthma and arrhythmias.

Background: There is little information on the differential impact of the COVID-19 pandemic on mortality by occupation. The objective was to examine changes in mortality during the COVID-19 period compared with the prepandemic period in different occupational groups in Spain.

Methods: Average mortality in the entire period 2020-2021, and each of its semesters, was compared, respectively, with the average mortality in the entire period 2017-2019, and the corresponding semester (first or second) of this last period, across occupational skill levels. For this, age-standardised death rates and age-adjusted mortality rate ratios (MRRs) obtained through Poisson regression were used. Data were obtained from the National Institute of Statistics and the Labour Force Survey.

Results: The excess all-cause mortality during the 2020-2021 pandemic period by the MRR was higher in low-skilled (1.18, 95% CI 1.16 to 1.20) and medium-skilled workers (1.14; 95% CI 1.13 to 1.15) than high-skilled workers (1.04; 95% CI 1.02 to 1.05). However, the greatest excess mortality was observed in low-skilled workers in 2020 and in medium-skilled workers in 2021. Focusing on causes of death other than COVID-19, low-skilled workers showed the highest MRR from cardiovascular diseases (1.31; 95% CI 1.26 to 1.36) and high-skilled workers the lowest (1.02; 95% CI 0.98 to 1.02). However, this pattern was reversed for mortality from external causes, with low-skilled workers showing the lowest MRR (1.04; 95% CI 0.97 to 1.09) and high-skilled workers the highest (1.08; 95% CI 1.03 to 1.13).

Conclusion: Globally, in Spain, during the 2020-2021 COVID-19 epidemic period, low-skilled workers experienced a greater excess all-cause mortality than other occupational groups, but this was not the case during the entire epidemic period or for all causes of death.

Background: Healthy diet might protect against cardiometabolic diseases, but uncertainty exists about its definition and role in adolescence.

Method: In a subset of Hong Kong's 'Children of 1997' birth cohort (n=2844 out of 8327), we prospectively examined sex-specific associations of food consumption and dietary pattern, proxied by the Global Diet Quality Score (GDQS) at~12.0 years, with cardiometabolic risk factors and metabolomics at~17.6 years.

Result: Higher vegetable (-0.04 SD, 95% CIs: -0.09 to 0.00) and soy consumption (-0.05 SD, 95% CI: -0.09 to -0.01) were associated with lower waist-to-hip ratio. Higher fruit and vegetable consumption were associated with lower fasting glucose (p<0.05). Higher fish consumption was associated with 0.06 SD (95% CI: 0.01 to 0.10) high-density lipoprotein cholesterol and -0.07 SD (95% CI: -0.11 to -0.02) triglycerides. After correcting for multiple comparisons (p<0.001), higher fish, fruit and vegetable consumption were associated with higher fatty acid unsaturation, higher concentration and percentage of omega-3 and a lower ratio of omega-6/omega-3. At nominal significance (p<0.05), higher fish consumption was associated with lower very-low-density lipoprotein and triglycerides relevant metabolomics. Higher vegetable and fruit consumption were associated with lower glycolysis-related metabolomics. Lower sugar-sweetened beverages (SSBs) consumption was associated with lower branched-chain amino acids. Similar associations with adiposity and metabolomics biomarkers were observed for GDQS.

Conclusions: Higher consumption of fruit, vegetables and fish and lower ice cream and SSBs consumption were associated with lower cardiometabolic risk in adolescents.