Epidemiology最新文献

Background: Children with cystic fibrosis (CF) from socioeconomically deprived areas have poorer growth, worse lung function, and shorter life expectancy than their less-deprived peers. While early growth is associated with lung function around age 6, it is unclear whether improving early growth in the most deprived children reduces inequalities in lung function.

Methods: We used data from the UK CF Registry, tracking children born 2000-2010 up to 2016. We extended the interventional disparity effects approach to the setting of a longitudinally measured mediator. Applying this approach, we estimated the association between socioeconomic deprivation (children in the least vs. most deprived population quintile; exposure) and lung function at first measurement (ages 6-8, outcome), and the role of early weight trajectories (ages 0-6) as mediators of this relationship. We adjusted for baseline confounding by sex, birthyear, and genotype and time-varying intermediate confounding by lung infection.

Results: The study included 853 children, with 165 children from the least and 172 from the most deprived quintiles. The average lung function difference between the least and most deprived quintiles was 4.5% of predicted forced expiratory volume in 1 second (95% confidence interval: 1.1-7.9). If the distribution of early weight trajectories in the most deprived children matched that in the least deprived children, this difference would reduce to 4% (95% confidence interval: 0.57- 7.4).

Conclusion: Socioeconomic deprivation has a strong negative association with lung function for children with CF. We estimate that improving early weight trajectories in the most deprived children would only marginally reduce these inequalities.

Background: The nature and timing of increasing educational inequity in US life expectancy prior to the COVID-19 pandemic suggests that long-term adverse labor market conditions secondary to globalization and technological change played a role for less-educated workers, but this has not been tested.

Methods: We exploit spatiotemporal variation in mortality and long-term economic conditions at the year and commuting zone level to estimate the relationship between macroeconomic restructuring and diverging mortality trends, 1990-2017, by race, gender, and education. Our measure of macroeconomic restructuring is based on the baseline industrial mix of an area, a measure that is plausibly exogenous to mortality.

Results: Mortality trends were substantially worse in commuting zones experiencing long-term economic stagnation than in others. For both White and Black adults, this relationship was strongest in the lowest quartile of the education distribution. Residence in commuting zones in the top quartile of our measure of economic conditions was associated with an additional 1-2 years lived between ages 25 and 84 compared to living in a commuting zone in the bottom quartile. The primary mediators of these divergent mortality trends were cancer, cardiovascular and metabolic diseases, and diseases of other internal body systems. Deaths from suicide or substance abuse did not contribute importantly toward accounting for the estimated impact of long-term economic stagnation on mortality.

Conclusions: In our study, diverging trends in US life expectancy were associated with macroeconomic changes witnessed over the last half-century. The causes of death mediating this link were largely found in rates of death from stress-related internal diseases.

Plant-capture is a specialized variant of traditional capture-recapture methods used to estimate the size of a population. In epidemiologic literature, a notable application of this method is the estimation of the size of homeless populations through point-in-time street surveys. With this approach, decoys referred to as "plants" are introduced into the population to estimate the capture probability. Previous plant-capture studies have not systematically accounted for uncertainty in the capture status of individual plants. To address this, we propose three increasingly complex hierarchical modeling approaches to formally incorporate uncertainty into the plant-capture model arising from the capture status of plants and heterogeneity between survey sites. We then apply our methods to estimate the size of the homeless population in large US cities in the context of the "S-Night" study conducted by the US Census Bureau. Details on the frequentist and Bayesian implementations of our models, along with empirical evaluations of their statistical performance, are provided in the supplementary materials.

Background: Public health and social measures are crucial for controlling the spread of pathogens. However, well-tailored assessments of their impact remain elusive, particularly considering time-varying immunity established from prior exposures and its waning.

Methods: We developed a mathematical model to estimate the time-varying basic reproduction number, accounting for the dynamics of underlying immunity. Applying this framework, we retrospectively assessed the impact of public health and social measures implemented from November 2021-April 2022 on SARS-CoV-2 transmission in Korea and discussed potential biases from ignoring underlying immunity.

Results: Our proposed model estimated a notable attenuation in the impact of public health on social measures on SARS-CoV-2 transmission in Korea with the emergence of the Omicron variants while remaining effective throughout the Delta and Omicron periods. These changes during the Omicron period became evident only upon adjusting for underlying immunity and were correlated with observed human mobility patterns in Korea.

Conclusions: Our findings support the importance of incorporating underlying immunity in evaluating public health and social measures, particularly in the presence of substantial changes over a short period such as widespread infections or vaccination. This model would stand as a tool for informing public health planning, capable of mitigating the overall disease burden in future epidemics.

Background: Collaborative research consortia provide an efficient method to increase sample size, enabling evaluation of subgroup heterogeneity and rare outcomes. In addition to missing data challenges faced by all cohort studies like nonresponse and attrition, collaborative studies have missing data due to differences in study design and measurement of the contributing studies.

Methods: We extend ROSETTA, a latent variable method that creates common measures across datasets collecting the same latent constructs with only partial overlap in measures, to define a common measure of socioeconomic status (SES) across cohorts with varying indicators in the Environmental influences on Child Health Outcomes Cohort, a consortium of pregnancy and pediatric cohorts.

Results: Starting with 52 indicators of prenatal SES from 39,372 participants across 53 cohorts, ROSETTA created three factors representing key domains of SES: income and education, insurance and poverty, and unemployment. At least one factor score was available for 34,528 participants; two factors were available for more participants than any single indicator. Factors fit the data well, had content validity, and were correlated with alternative measures of SES (for income & education factor, r= 0.40-0.89). Higher SES as measured by the factor scores was associated with lower odds of prenatal smoking:OR income & education 0.42 (95% CI 0.38, 0.45). Missing data were reduced compared to most methods, except for multiple imputation.

Conclusions: ROSETTA aids in pooled analysis of individual participant data by creating measures on a common scale and maximizing data in the presence of missing and mismatched measures.

Background: Hospital regionalization involves balancing hospital volume and travel time. We investigated how hospital volume and travel time affect perinatal mortality and the risk of delivery in transit using three different study designs.

Methods: This nationwide cohort study used data from the Medical Birth Registry of Norway (1999-2016) and Statistics Norway. We compared estimates across three designs: (1) Observed confounder adjustment: Comparing women giving birth at hospitals of different sizes and travel times (1,066,332 births), (2) Sibling comparison: Comparing women who moved between hospital catchment areas between births (203,464 births), (3) Neighbor comparison: comparing women living in neighboring municipalities, but in different hospital catchment areas (460,776 births).

Results: The study population included 5080 (0.48%) perinatal deaths and 7063 deliveries in transit (0.66%). For hospitals with 2000 compared with 500 births/year, observed confounder adjustment showed 1.81 times higher perinatal mortality (95% confidence interval [CI] 1.21-2.73). However, sibling and neighbor comparisons showed a factor 0.64 (95% CI 0.43-0.97) and 0.61% (95% CI 0.43-0.88) lower perinatal mortality, respectively. Increased travel time was strongly associated with higher perinatal mortality using observed confounder adjustment, but this was not supported by the other designs. Longer travel time was consistently linked to an increased risk of delivery in transit.

Conclusions: Perinatal mortality was higher in high-volume hospitals when adjusting for observed confounders. However, triangulating inferences from the other designs suggested the opposite, estimating that observed confounder control was insufficient. This supports the idea that access to higher-volume hospitals could improve perinatal outcomes at the population level.

Background: Helicobacter pylori (H. pylori) has been inconsistently associated with risk of Alzheimer disease. The exposure assessment period has often overlapped with the prodromal time of Alzheimer disease. Cognitive disorders might increase vulnerability to infectious pathogens, complicating the ascertainment of temporal relationship between H. pylori infection and Alzheimer disease.

Methods: This Finnish nested case-control study included 70,520 persons with incident Alzheimer disease diagnosed between 2005-2011 and 281,233 age-, sex-, and region of residence-matched controls. We obtained information on comorbidities and drug use from the national healthcare registers. We identified dispensed H. pylori eradication treatments from the Prescription register. We considered exposure at least 5 years before Alzheimer disease diagnosis in the main analysis. We compared risk of Alzheimer disease between H. pylori eradication treatment users and nonusers using confounder-adjusted (comorbidities and other drug use) conditional logistic regression. We assessed cumulative exposure by calculating the number of eradication treatments.

Results: The prevalence of exposure to H. pylori eradication treatment at least 5 years before the outcome was 4.1% in cases and 3.9% in controls. The odds ratio (95% confidence interval) was 1.06 (1.02-1.11) in the crude and 1.03 (0.99-1.07) in the confounder-adjusted model. We observed no association between cumulative exposure and risk of Alzheimer disease.

Conclusion: Our results, reflecting diagnosed and treated H. pylori infection late in life, do not support the hypothesis of H. pylori as an independent risk factor for Alzheimer disease. The previously reported association may be explained by reverse association and confounding.

Background: The overdose epidemic remains largely driven by opioids, but county-level prevalence of opioid misuse is unknown. Without this information, public health and policy responses are limited by a lack of knowledge on the scope of the problem.

Methods: Using an integrated abundance model, we estimate annual county-level prevalence of opioid misuse for counties in North Carolina from 2016 to 2021. The model integrates county-level observed counts of illicit opioid overdose deaths, people receiving prescriptions for buprenorphine, and people served by treatment programs. It also incorporates state-level survey estimates of misuse prevalence. County-level social and environmental covariates are also accounted for in the model. Data are integrated through a Bayesian hierarchical model to estimate posterior distributions of the parameters.

Results: In general, the estimated prevalence of misuse was decreasing over the study period. Estimated prevalence was above average in the western and southeastern parts of the state. We also estimated that the proportion of people who misuse opioids who fatally overdosed increased sharply over the study period as the median estimated proportion in 2021 was more than 8 times greater than 2016. The proportion of people who misuse opioids who received buprenorphine and were served by treatment programs increased over the study period.

Conclusions: Estimates from our integrated abundance model fill an important gap in public health knowledge about the local prevalence of people who misuse opioids and can be used to inform an adequate and equitable allocation of resources to communities across the state.