Migraine, Fibromyalgia, and Depression among People with IBS: A Prevalence Study

BACKGROUND. Case descriptions suggest IBS patients are more likely to have other disorders, including migraine, fibromyalgia, and depression. We sought to examine the prevalence of these conditions in cohorts of people with and without IBS. METHODS. The source of data was a large U.S. health plan from January 1, 1996 though June 30, 2002. We identified all people with a medical claim associated with an ICD-9 code for IBS. A non-IBS cohort was a random sample of people with an ICD-9 code for routine medical care. In the cohorts, we identified all claims for migraine, depression, and fibromyalgia. We estimated the prevalence odds ratios (PORs) of each of the three conditions using the Mantel-Haenszel method. We conducted quantitative sensitivity analyses to quantify the impact of residual confounding and in differential outcome identification. RESULTS. We identified 97,593 people in the IBS cohort, and a random sample of 27,402 people to compose the non-IBS comparison cohort. With adjustment, there was a 60% higher odds in the IBS cohort of having any one of the three disorders relative to the comparison cohort (POR 1.6, 95% CI 1.5 – 1.7). There was a 40% higher odds of depression in the IBS cohort (POR 1.4, 95% CI 1.3 – 1.4). The PORs for fibromyalgia and migraine were similar (POR for fibromyalgia 1.8, 95% CI 1.7 – 1.9; POR for migraine 1.6, 95% CI 1.4 – 1.7). Differential prevalence of an unmeasured confounder, or imperfect sensitivity or specificity of outcome detection would have impacted the observed results. CONCLUSION. People in the IBS cohort had a 40% to 80% higher prevalence odds of migraine, fibromyalgia, and depression

Simple Estimators of the Intensity of Seasonal Occurrence

Background: Edwards's method is a widely used approach for fitting a sine curve to a time-series of monthly frequencies. From this fitted curve, estimates of the seasonal intensity of occurrence (i.e., peak-to-low ratio of the fitted curve) can be generated. Methods: We discuss various approaches to the estimation of seasonal intensity assuming Edwards's periodic model, including maximum likelihood estimation (MLE), least squares, weighted least squares, and a new closed-form estimator based on a second-order moment statistic and non-transformed data. Through an extensive Monte Carlo simulation study, we compare the finite sample performance characteristics of the estimators discussed in this paper. Finally, all estimators and confidence interval procedures discussed are compared in a re-analysis of data on the seasonality of monocytic leukemia. Results: We find that Edwards's estimator is substantially biased, particularly for small numbers of events and very large or small amounts of seasonality. For the common setting of rare events and moderate seasonality, the new estimator proposed in this paper yields less finite sample bias and better mean squared error than either the MLE or weighted least squares. For large studies and strong seasonality, MLE or weighted least squares appears to be the optimal analytic method among those considered. Conclusion: Edwards's estimator of the seasonal relative risk can exhibit substantial finite sample bias. The alternative estimators considered in this paper should be preferred

Thrombosis after Travel

Rothman discusses a new study by Cannegieter and colleagues which looked at the interaction of lengthy travel with other risk factors for venous thromboembolism

Lockdown timing and efficacy in controlling COVID-19 using mobile phone tracking

Background Italy's severe COVID-19 outbreak was addressed by a lockdown that gradually increased in space, time and intensity. The effectiveness of the lockdown has not been precisely assessed with respect to the intensity of mobility restriction and the time until the outbreak receded. Methods We used processed mobile phone tracking data to measure mobility restriction, and related those data to the number of new SARS-CoV-2 positive cases detected on a daily base in the three most affected Italian regions, Lombardy, Veneto and Emilia-Romagna, from February 1 through April 6, 2020, when two subsequent lockdowns with increasing intensity were implemented by the Italian government. Findings During the study period, mobility restriction was inversely related to the daily number of newly diagnosed SARS-CoV-2 positive cases only after the second, more effective lockdown, with a peak in the curve of diagnosed cases of infection occurring 14 to 18 days from lockdown in the three regions and 9 to 25 days in the included provinces. An effective reduction in transmission must have occurred nearly immediately after the tighter lockdown, given the lag time of around 10 days from asymptomatic infection to diagnosis. The period from lockdown to peak was shorter in the areas with the highest prevalence of the infection. This effect was seen within slightly more than one week in the most severely affected areas. Interpretation It appears that the less rigid lockdown led to an insufficient decrease in mobility to reverse an outbreak such as COVID-19. With a tighter lockdown, mobility decreased enough to bring down transmission promptly below the level needed to sustain the epidemic. Funding No funding sources have been used for this work

Association of Apgar score at five minutes with long-term neurologic disability and cognitive function in a prevalence study of Danish conscripts

<p>Abstract</p> <p>Background</p> <p>Apgar score is used for rapid assessment of newborns. Low five-minute Apgar score has been associated with increased risk of severe neurologic outcome, but data on milder outcomes, particularly in the long term, are limited. We aimed to examine the association of five-minute Apgar score with prevalence of neurologic disability and with cognitive function in early adulthood.</p> <p>Methods</p> <p>We conducted a prevalence study among draft-liable men born in Denmark in 1978–1983 and presenting for the mandatory army evaluation in a northern Danish conscription district. We linked records of this evaluation, which includes medical exam and intelligence testing, with the conscripts' records in the Medical Birth Registry, containing perinatal data. We examined prevalence of neurologic disability and of low cognitive function according to five-minute Apgar score.</p> <p>Results</p> <p>Less than 1% (136/19,559) of the conscripts had 5-minute Apgar scores <7. Prevalence of neurologic disability was 2.2% (435/19,559) overall; among conscripts with Apgar scores <7, 7–9, and 10 (reference), it was 8.8%, 2.5%, and 2.2% respectively. The corresponding prevalences of low cognitive function (intelligence test score in the bottom quartile) were 34.9%, 27.2%, and 25.0%. The outcomes were more prevalent if Apgar score <7 was accompanied by certain fetal or obstetric adversities. After accounting for perinatal characteristics, 5-mintue Apgar score <7 was associated with prevalence ratios of 4.02 (95% confidence interval: 2.24; 7.24) for neurologic disability and 1.33 (0.94; 1.88) for low cognitive function.</p> <p>Conclusion</p> <p>A five-minute Apgar score <7 has a consistent association with prevalence of neurologic disability and with low cognitive function in early adulthood.</p

Treatment Effects in the Presence of Unmeasured Confounding: Dealing With Observations in the Tails of the Propensity Score Distribution--A Simulation Study

Frailty, a poorly measured confounder in older patients, can promote treatment in some situations and discourage it in others. This can create unmeasured confounding and lead to nonuniform treatment effects over the propensity score (PS). The authors compared bias and mean squared error for various PS implementations under PS trimming, thereby excluding persons treated contrary to prediction. Cohort studies were simulated with a binary treatment T as a function of 8 covariates X. Two of the covariates were assumed to be unmeasured strong risk factors for the outcome and present in persons treated contrary to prediction. The outcome Y was simulated as a Poisson function of T and all X’s. In analyses based on measured covariates only, the range of PS's was trimmed asymmetrically according to the percentile of PS in treated patients at the lower end and in untreated patients at the upper end. PS trimming reduced bias due to unmeasured confounders and mean squared error in most scenarios assessed. Treatment effect estimates based on PS range restrictions do not correspond to a causal parameter but may be less biased by such unmeasured confounding. Increasing validity based on PS trimming may be a unique advantage of PS's over conventional outcome models

Leukemia risk in children exposed to benzene and PM10 from vehicular traffic: a case-control study in an Italian population.

Benzene, a recognized occupational leukemogen in adults, has been implicated by sparse and conflicting epidemiologic evidence in the etiology of childhood leukemia. We carried out a population-based case-control study in a northern Italy population involving 83 cases with childhood leukemia diagnosed in the years 1998-2009 and 332 matched controls. We assessed residential exposure to benzene and to particulate matter ≤10 µm (PM10) from motorized traffic using geocoded residences and detailed emission and dispersion modeling. Exposure to benzene, and to a lesser extent to PM10, appeared to be independently associated with an excess leukemia risk. When we stratified the study population by age, the relative risk associated with benzene exposure was higher among children aged less than five years. Overall, these findings suggest that low levels of benzene exposure released from motorized traffic may increase the risk of childhood leukemia, and do not rule out an independent effect of PM10

Association between Outdoor Air Pollution and Childhood Leukemia: A Systematic Review and Dose-Response Meta-Analysis.

BackgroundA causal link between outdoor air pollution and childhood leukemia has been proposed, but some older studies suffer from methodological drawbacks. To the best of our knowledge, no systematic reviews have summarized the most recently published evidence and no analyses have examined the dose-response relation.ObjectiveWe investigated the extent to which outdoor air pollution, especially as resulting from traffic-related contaminants, affects the risk of childhood leukemia.MethodsWe searched all case-control and cohort studies that have investigated the risk of childhood leukemia in relation to exposure either to motorized traffic and related contaminants, based on various traffic-related metrics (number of vehicles in the closest roads, road density, and distance from major roads), or to measured or modeled levels of air contaminants such as benzene, nitrogen dioxide, 1,3-butadiene, and particulate matter. We carried out a meta-analysis of all eligible studies, including nine studies published since the last systematic review and, when possible, we fit a dose-response curve using a restricted cubic spline regression model.ResultsWe found 29 studies eligible to be included in our review. In the dose-response analysis, we found little association between disease risk and traffic indicators near the child's residence for most of the exposure range, with an indication of a possible excess risk only at the highest levels. In contrast, benzene exposure was positively and approximately linearly associated with risk of childhood leukemia, particularly for acute myeloid leukemia, among children under 6 y of age, and when exposure assessment at the time of diagnosis was used. Exposure to nitrogen dioxide showed little association with leukemia risk except at the highest levels.DiscussionOverall, the epidemiologic literature appears to support an association between benzene and childhood leukemia risk, with no indication of any threshold effect. A role for other measured and unmeasured pollutants from motorized traffic is also possible. https://doi.org/10.1289/EHP4381