Physical insults

Kevin Lewis

December 21, 2019

The Association between Mobile Phones and the Risk of Brain Cancer Mortality: A 25-Year Cross-Country Analysis
Hugo Mialon & Erik Nesson
Contemporary Economic Policy, forthcoming


We investigate the relationship between cell phones and brain cancer using brain cancer death rates for 88 countries between 1990 and 2015 from the World Health Organization and country‐level mobile phone subscription rates from the World Bank. We estimate difference‐in‐difference models including country and year fixed effects and time‐varying country covariates. We find that mobile phone subscription rates are positively and statistically significantly associated with death rates from brain cancer 15–20 years later. In falsification tests, we find few positive associations between mobile phone subscription rates and deaths from rectal, pancreatic, stomach, breast or lung cancer or ischemic heart disease. Finally, differential effects models suggest that mobile phone subscription rates are associated with brain cancer deaths 15–19 years later relative to deaths from other causes.

Local Exposure to School Shootings and Youth Antidepressant Use
Maya Rossin-Slater et al.
NBER Working Paper, December 2019


While over 240,000 American students experienced a school shooting in the last two decades, little is known about the impacts of these events on the mental health of surviving youth. Using large-scale prescription data from 2006 to 2015, we examine the effects of 44 school shootings on youth antidepressant use in a difference-in-difference framework. We find that local exposure to fatal school shootings increases youth antidepressant use by 21.4 percent in the following two years. These effects are smaller in areas with a higher density of mental health providers who focus on behavioral, rather than pharmacological, interventions.

The association between obesity and lower working memory is mediated by inflammation: Findings from a nationally representative dataset of U.S. adults
Yingkai Yang et al.
Brain, Behavior, and Immunity, forthcoming


Obesity is often accompanied by lower working memory (e.g., a lower ability to keep goal-relevant information in mind) relative to healthy weight individuals. Understanding this relative working memory impairment has important clinical implications, as working memory is thought to facilitate adherence to weight management programs. Theoretical models of obesity, self-regulation, and inflammation suggest that inflammation plays a role in obesity-related working memory impairments, but to date no study has tested this prediction. Therefore, the current study examined whether inflammation statistically mediated the relationship between obesity and working memory in a nationally representative dataset of U.S. adults from Wave IV of The National Longitudinal Study of Adolescent to Adult Health (N=11,546, age range 25–34). Inflammation was quantified via C-reactive protein (CRP) level, and working memory was assessed using a modified digit span backward task. As expected, cross-sectional analyses showed that a body mass index (BMI) indicative of obesity — as well as greater BMI when BMI was analyzed continuously — and greater CRP were each related to lower working memory. Critically, we found that CRP levels statistically mediated the relationships between obesity/greater BMI and working memory, with CRP accounting for 44.1% of the variance explained in working memory by BMI. Moreover, these findings held both with and without controlling for relevant covariates, including demographic characteristics (e.g., age), socioeconomic status, and behavioral factors (e.g., smoking). Our results therefore point to inflammation as playing an important role in the relationship between obesity and working memory, and suggest that interventions aimed at reducing inflammation may help lessen the cognitive burden of obesity.

Projected U.S. State-Level Prevalence of Adult Obesity and Severe Obesity
Zachary Ward et al.
New England Journal of Medicine, 19 December 2019, Pages 2440-2450

Methods: We developed methods to correct for self-reporting bias and to estimate state-specific and demographic subgroup–specific trends and projections of the prevalence of categories of body-mass index (BMI). BMI data reported by 6,264,226 adults (18 years of age or older) who participated in the Behavioral Risk Factor Surveillance System Survey (1993–1994 and 1999–2016) were obtained and corrected for quantile-specific self-reporting bias with the use of measured data from 57,131 adults who participated in the National Health and Nutrition Examination Survey. We fitted multinomial regressions for each state and subgroup to estimate the prevalence of four BMI categories from 1990 through 2030: underweight or normal weight (BMI [the weight in kilograms divided by the square of the height in meters], <25), overweight (25 to <30), moderate obesity (30 to <35), and severe obesity (≥35). We evaluated the accuracy of our approach using data from 1990 through 2010 to predict 2016 outcomes.

Results: The findings from our approach suggest with high predictive accuracy that by 2030 nearly 1 in 2 adults will have obesity (48.9%; 95% confidence interval [CI], 47.7 to 50.1), and the prevalence will be higher than 50% in 29 states and not below 35% in any state. Nearly 1 in 4 adults is projected to have severe obesity by 2030 (24.2%; 95% CI, 22.9 to 25.5), and the prevalence will be higher than 25% in 25 states. We predict that, nationally, severe obesity is likely to become the most common BMI category among women (27.6%; 95% CI, 26.1 to 29.2), non-Hispanic black adults (31.7%; 95% CI, 29.9 to 33.4), and low-income adults (31.7%; 95% CI, 30.2 to 33.2).

The Dynamic Relationship between Asthma and Obesity in School Children
Yue Zhang et al.
American Journal of Epidemiology, forthcoming


Asthma and obesity are two of the most prevalent chronic health conditions in children. Although there has been compelling evidence of co-occurrence of asthma and obesity, it is uncertain whether asthma contributes to the development of obesity or obesity contributes to the onset of asthma or both. In this study, we used a joint transition modeling approach with cross-lagged structure to understand how asthma and obesity influence each other dynamically over time. Subjects for this study included 5193 kindergarten and first-grade students enrolled from 13 communities in 2002-03 in the Southern California Children’s Health Study (CHS) with up to 10 years of follow-up. We found that non-obese children with diagnosed asthma at a study visit were at 37% increased odds of becoming obese by the next annual visit compared with children without asthma (OR=1.38; 95% CI=1.12-1.71). However, the presence of obesity at the current visit was not statistically significantly associated with asthma onset in the next visit (OR=1.25; 95% CI=0.94-1.62). In conclusion, childhood asthma drives an increase in the onset of obesity among school children, while the onset of obesity does not necessarily imply the future onset of asthma at least in the short term.

Detecting the Effects of Early-Life Exposures: Why Fecundity Matters
Jenna Nobles & Amar Hamoudi
Population Research and Policy Review, December 2019, Pages 783–809


Prenatal exposures have meaningful effects on health across the life course. Innovations in causal inference have shed new light on these effects. Here, we motivate the importance of innovation in the characterization of fecundity, and prenatal selection in particular. We argue that such innovation is crucial for expanding knowledge of the fetal origins of later life health. Pregnancy loss is common, responsive to environmental factors, and closely related to maternal and fetal health outcomes. As a result, selection into live birth is driven by many of the same exposures that shape the health trajectories of survivors. Life course effects that are inferred without accounting for these dynamics may be significantly distorted by survival bias. We use a set of Monte Carlo simulations with realistic parameters to examine the implications of prenatal survival bias. We find that even in conservatively specified scenarios, true fetal origin effects can be underestimated by 50% or more. In contrast, effects of exposures that reduce the probability of prenatal survival but improve the health of survivors will be overestimated. The absolute magnitude of survival bias can even exceed small-effect sizes, resulting in inferences that beneficial exposures are harmful or vice versa. We also find reason for concern that moderately sized true effects, underestimated due to failure to account for selective survival, are missing from scientific knowledge because they do not clear statistical significance filters. This bias has potential real-world costs; policy decisions about interventions to improve maternal and infant health will be affected by underestimated program impact.


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