Exposure-lag response of smoking prevalence on lung cancer incidence using a distributed lag non-linear model

Time Dependence Between Tobacco Consumption and Lung Cancer Mortality in Spain

OBJECTIVES

Lung cancer is the leading cause of cancer death and the second most common cancer in both sexes worldwide, with tobacco being its main risk factor. The aim of this study is to establish the temporal relationship between smoking prevalence and lung cancer mortality in Spain.

METHODS

To model the time dependence between smoking prevalence and lung cancer mortality, a distributed lag non-linear model was applied adjusting for sex, age, year of mortality and population at risk. Smoking prevalence data from 1991-2020 were used. Considering a maximum lag of 25 years, mortality data from 2016-2020 were included. The effect of prevalence on mortality for each lag is presented in terms of relative risk (RR). To identify the lag at which smoking prevalence has the greatest effect on mortality, the RR of the different lags were compared.

RESULTS

The optimal lag observed between smoking prevalence and lung cancer mortality in Spain was 15 years. The maximum RR was 2.9 (95%CI: 2.0-4.3) for a prevalence of 71% and a 15-year lag. The RR was 1.8 for a prevalence of 33%, an approximate median value between 1991-2020, and a 15-year lag.

CONCLUSIONS

In Spain, lung cancer mortality is affected by smoking prevalence 15 years prior. Knowing the evolution of the smoking prevalence series in a country and establishing a lag time is essential to predict how lung cancer incidence and mortality will evolve.

Light at night and lung cancer risk: A worldwide interdisciplinary and time-series study

Background

Light at night (LAN) has become a concern in interdisciplinary research in recent years. This global interdisciplinary study aimed to explore the exposure-lag-response association between LAN exposure and lung cancer incidence.

Methods

LAN data were obtained from the Defense Meteorological Satellite Program's Operational Linescan System. Data of lung cancer incidence, socio-demographic index, and smoking prevalence of populations in 201 countries/territories from 1992 to 2018 were collected from the Global Burden of Disease Study. Spearman correlation tests and population-weighted linear regression analysis were used to evaluate the correlation between LAN exposure and lung cancer incidence. A distributed lag nonlinear model (DLNM) was used to assess the exposure-lag effects of LAN exposure on lung cancer incidence.

Results

The Spearman correlation coefficients were 0.286-0.355 and the population-weighted linear regression correlation coefficients were 0.361-0.527. After adjustment for socio-demographic index and smoking prevalence, the Spearman correlation coefficients were 0.264-0.357 and the population-weighted linear regression correlation coefficients were 0.346-0.497. In the DLNM, the maximum relative risk was 1.04 (1.02-1.06) at LAN exposure of 8.6 with a 2.6-year lag time. After adjustment for socio-demographic index and smoking prevalence, the maximum relative risk was 1.05 (1.02-1.07) at LAN exposure of 8.6 with a 2.4-year lag time.

Conclusion

High LAN exposure was associated with increased lung cancer incidence, and this effect had a specific lag period. Compared with traditional individual-level studies, this group-level study provides a novel paradigm of effective, efficient, and scalable screening for risk factors.

A life-course approach to tackling noncommunicable diseases in women

Women's health has been critically underserved by a failure to look beyond women's sexual and reproductive systems to adequately consider their broader health needs. In almost every country in the world, noncommunicable diseases are the leading causes of death for women. Among these, cardiovascular disease (including heart disease and stroke) and cancer are the major causes of mortality. Risks for these conditions exist at each stage of women's lives, but recognition of the unique needs of women for the prevention and management of noncommunicable diseases is relatively recent and still emerging. Once they are diagnosed, treatments for these diseases are often costly and noncurative. Therefore, we call for a strategic, innovative life-course approach to identifying disease triggers and instigating cost-effective measures to minimize exposure in a timely manner. Prohibitive barriers to implementing this holistic approach to women's health exist in both the social arena and the medical arena. Recognizing these impediments and implementing practical approaches to surmounting them is a rational approach to advancing health equity for women, with ultimate benefits for society as a whole.

Exposure-lag response of fine particulate matter on intrauterine fetal death: an analysis using a distributed lag non-linear model in Linxia Hui Autonomous Prefecture, China

The results of studies on intrauterine fetal death (IUFD) caused by exposure to fine particulate matter (PM_2.5) during pregnancy are inconsistent. Further exploration of the dose-response relationship and exposure window is required. We aimed to provide a reference for policy formulation by estimating the exposure-lag relationship of PM_2.5 on IUFD and looking for sensitive exposure windows. IUFD data was obtained from China Children Under 5 Death Surveillance Network in Linxia Hui Autonomous Prefecture from 2016 to 2020. Air pollution data and temperature data were obtained from ambient air monitoring stations and China Meteorological Data Network, respectively. The moving average is used to describe the trend and seasonality of PM_2.5 exposure; the distributed lag non-linear model (DLNM) is used to estimate the exposure-lag effect; the sandwich estimators are used to correct the variance-covariance matrix; and the model selected by Akaike's Information Criterion (AIC) finally adjusts gender, temperature, and district. About 180,622 infants were enrolled in the study, including 952 IUFDs (5.27‰). The median of PM_2.5 exposure is 34.08 μg/m³. There is an exposure-lag effect of PM_2.5 on IUFD approximate to a wavy shape; the concentration with effect is 40-90 μg/m³; and the sensitive lag time is 1, 2, 3, 8, 9, and 10 months. The maximum RR value of the exposure-lag effect of PM_2.5 on IUFD is 1.61 [95% CI 1.19, 2.19], in which the concentration of PM_2.5 is 62 μg/m³, and the lag month is 9 months. In the case of less than 6 months lag, the maximum RR value of the exposure-lag effect of PM_2.5 on IUFD is 1.43 [95% CI 1.24, 1.67], in which the concentration of PM_2.5 is 73 μg/m³, and the lag month is 3 months. Exposure to PM_2.5 concentrations above 40 μg/m³ may increase the risk of IUFD, especially in the first and third trimesters.

Applying the Bradford Hill Criteria for Causation to Repetitive Head Impacts and Chronic Traumatic Encephalopathy

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with a history of repetitive head impacts (RHI). CTE was described in boxers as early as the 1920s and by the 1950s it was widely accepted that hits to the head caused some boxers to become "punch drunk." However, the recent discovery of CTE in American and Australian-rules football, soccer, rugby, ice hockey, and other sports has resulted in renewed debate on whether the relationship between RHI and CTE is causal. Identifying the strength of the evidential relationship between CTE and RHI has implications for public health and medico-legal issues. From a public health perspective, environmentally caused diseases can be mitigated or prevented. Medico-legally, millions of children are exposed to RHI through sports participation; this demographic is too young to legally consent to any potential long-term risks associated with this exposure. To better understand the strength of evidence underlying the possible causal relationship between RHI and CTE, we examined the medical literature through the Bradford Hill criteria for causation. The Bradford Hill criteria, first proposed in 1965 by Sir Austin Bradford Hill, provide a framework to determine if one can justifiably move from an observed association to a verdict of causation. The Bradford Hill criteria include nine viewpoints by which to evaluate human epidemiologic evidence to determine if causation can be deduced: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy. We explored the question of causation by evaluating studies on CTE as it relates to RHI exposure. Through this lens, we found convincing evidence of a causal relationship between RHI and CTE, as well as an absence of evidence-based alternative explanations. By organizing the CTE literature through this framework, we hope to advance the global conversation on CTE mitigation efforts.