Gertner Institute for Epidemiology

Tel Aviv, Israel

Gertner Institute for Epidemiology

Tel Aviv, Israel
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Berchenko Y.,Ben - Gurion University of the Negev | Manor Y.,Chaim Sheba Medical Center | Freedman L.S.,Gertner Institute for Epidemiology | Kaliner E.,Public Health Services | And 6 more authors.
Science Translational Medicine | Year: 2017

A major obstacle to eradicating polio is that poliovirus from endemic countries can be reintroduced to polio-free countries. Environmental surveillance (ES) can detect poliovirus from sewage or wastewaters samples, even in the absence of patients with paralysis. ES is underused, in part because its sensitivity is unknown. We used two unique data sets collected during a natural experiment provided by the 2013 polio outbreak in Israel: ES data from different locations and records of supplemental immunization with the live vaccine. Data from the intersecting population between the two data sets (covering more than 63,000 people) yielded a dose-dependent relationship between the number of poliovirus shedders and the amount of poliovirus in sewage. Using a mixed-effects linear regression analysis of these data, we developed several quantitative tools, such as (i) ascertainment of the number of infected individuals from ES data for application during future epidemics elsewhere, (ii) evaluation of the sensitivity of ES, and (iii) determination of the confidence level of the termination of poliovirus circulation after an outbreak. These results will be valuable in monitoring future outbreaks with ES, and this approach could be used to certify poliovirus elimination or to validate the need for more containment efforts. 2017 © The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science.

Freedman L.S.,Gertner Institute for Epidemiology | Kipnis V.,U.S. National Cancer Institute | Schatzkin A.,U.S. National Cancer Institute | Tasevska N.,U.S. National Cancer Institute | Potischman N.,U.S. National Cancer Institute
Epidemiologic Perspectives and Innovations | Year: 2010

Identifying diet-disease relationships in nutritional cohort studies is plagued by the measurement error in self-reported intakes. The authors propose using biomarkers known to be correlated with dietary intake, so as to strengthen analyses of diet-disease hypotheses. The authors consider combining self-reported intakes and biomarker levels using principal components, Howe's method, or a joint statistical test of effects in a bivariate model. They compared the statistical power of these methods with that of conventional univariate analyses of self-reported intake or of biomarker level. They used computer simulation of different disease risk models, with input parameters based on data from the literature on the relationship between lutein intake and age-related macular degeneration. The results showed that if the dietary effect on disease was fully mediated through the biomarker level, then the univariate analysis of the biomarker was the most powerful approach. However, combination methods, particularly principal components and Howe's method, were not greatly inferior in this situation, and were as good as, or better than, univariate biomarker analysis if mediation was only partial or non-existent. In some circumstances sample size requirements were reduced to 20-50% of those required for conventional analyses of self-reported intake. The authors conclude that (i) including biomarker data in addition to the usual dietary data in a cohort could greatly strengthen the investigation of diet-disease relationships, and (ii) when the extent of mediation through the biomarker is unknown, use of principal components or Howe's method appears a good strategy. © 2010 Freedman et al; licensee BioMed Central Ltd.

Freedman L.S.,Gertner Institute for Epidemiology | Tasevska N.,U.S. National Cancer Institute | Kipnis V.,U.S. National Cancer Institute | Schatzkin A.,U.S. National Cancer Institute | And 3 more authors.
American Journal of Epidemiology | Year: 2010

A major problem in detecting diet-disease associations in nutritional cohort studies is measurement error in self-reported intakes, which causes loss of statistical power. The authors propose using biomarkers correlated with dietary intake to strengthen analyses of diet-disease hypotheses and to increase statistical power. They consider combining self-reported intakes and biomarker levels using principal components or a sum of ranks and relating the combined measure to disease in conventional regression analyses. They illustrate their method in a study of the inverse association of dietary lutein plus zeaxanthin with nuclear cataracts, using serum lutein plus zeaxanthin as the biomarker, with data from the Carotenoids in Age-Related Eye Disease Study (United States, 2001-2004). This example demonstrates that the combined measure provides higher statistical significance than the dietary measure or the serum measure alone, and it potentially provides sample savings of 8%-53% over analysis with dietary intake alone and of 6%-48% over analysis with serum level alone, depending on the definition of the outcome variable and the choice of confounders entered into the regression model. The authors conclude that combining appropriate biomarkers with dietary data in a cohort can strengthen the investigation of diet-disease associations by increasing the statistical power to detect them. © 2010 The Author.

Zhang S.,Texas A&M University | Krebs-Smith S.M.,U.S. National Cancer Institute | Midthune D.,U.S. National Cancer Institute | Buckman D.W.,Management Information Services Inc. | And 4 more authors.
International Journal of Biostatistics | Year: 2011

There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components. We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole grains. We demonstrate numerically that our methods lead to increased speed of computation, converge to reasonable solutions, and have the flexibility to be used in either a frequentist or a Bayesian manner. © 2011 Berkeley Electronic Press. All rights reserved.

Carroll R.J.,Texas A&M University | Midthune D.,U.S. National Cancer Institute | Subar A.F.,U.S. National Cancer Institute | Shumakovich M.,U.S. National Cancer Institute | And 3 more authors.
American Journal of Epidemiology | Year: 2012

With the advent of Internet-based 24-hour recall (24HR) instruments, it is now possible to envision their use in cohort studies investigating the relation between nutrition and disease. Understanding that all dietary assessment instruments are subject to measurement errors and correcting for them under the assumption that the 24HR is unbiased for usual intake, here the authors simultaneously address precision, power, and sample size under the following 3 conditions: 1) 1-12 24HRs; 2) a single calibrated food frequency questionnaire (FFQ); and 3) a combination of 24HR and FFQ data. Using data from the Eating at America's Table Study (1997-1998), the authors found that 4-6 administrations of the 24HR is optimal for most nutrients and food groups and that combined use of multiple 24HR and FFQ data sometimes provides data superior to use of either method alone, especially for foods that are not regularly consumed. For all food groups but the most rarely consumed, use of 2-4 recalls alone, with or without additional FFQ data, was superior to use of FFQ data alone. Thus, if self-administered automated 24HRs are to be used in cohort studies, 4-6 administrations of the 24HR should be considered along with administration of an FFQ. © 2012 The Author.

Bader D.,Technion - Israel Institute of Technology | Kugelman A.,Technion - Israel Institute of Technology | Boyko V.,Gertner Institute for Epidemiology | Levitzki O.,Gertner Institute for Epidemiology | And 5 more authors.
Pediatrics | Year: 2010

OBJECTIVES: The goals were to assess risk factors and mortality rate changes overtime and to develop simple estimates of mortality rates for specific groups of infants at 23 to 26 weeks of gestation. METHODS: Data from the Israel national very low birth weight infant database on 3768 infants born in 1995-2006 with gestational ages (GAs) of 23 to 26 weeks were evaluated, and we developed a tool for estimating infants' mortality rates. RESULTS: Major factors associated with death were GA, genderspecific birth weight percentile, prenatal steroid therapy, and multiple births. There was a steady decrease in mortality rates for all GAs during the study period. In 2004-2006, mortality rates before discharge were 89%, 67%, 46%, and 26% for infants with GAs of 23, 24, 25, and 26 weeks, respectively. Estimated mortality rates were calculated as the sum of the percentages determined for each of 4 parameters, as follows: GA of 26, 25, 24, or 23 weeks, 0%, 17%, 34%, and 51%, respectively (P < .001); birth weight percentile of >75th, 25th to 75th, or <25th, 0%, 16%, and 32%, respectively (P < .001); no prenatal steroid treatment, +22% (P < .001); multiple birth, +7% (P = .1). Estimated mortality rates for the 48 subgroups of infants ranged from 0% to 100% and correlated well with observed rates (intraclass correlation coefficient: 0.89). CONCLUSION: Mortality rates for infants born at 23 to 26 weeks of gestation could be estimated simply on the basis of GA, gender-specific birth weight quartiles, prenatal corticosteroid therapy, and multiple births.

Gal G.,Gertner Institute for Epidemiology | Gal G.,The Academic College of Tel-Aviv-Yaffo | Levav I.,Mental Health Services | Gross R.,Gertner Institute for Epidemiology | Gross R.,Tel Aviv University
Journal of Nervous and Mental Disease | Year: 2011

Childhood and adolescence abuse is a risk factor for later psychopathology. We examined the association between the age when sexual (SA) and physical (PA) abuse first occurred and mood and anxiety disorders and their respective age of onset, emotional distress, and sleep disturbances. Data were gathered from the Israel-based component of the World Mental Health Survey (N = 4859). Abuse was elicited by direct questions. Psychiatric disorders were diagnosed with the Composite International Diagnostic Interview, emotional distress with the 12-item General Health Questionnaire, and sleep disturbances by self-report. Multivariate analyses indicated an increased risk for psychopathology among subjects who reported childhood SA and PA. SA was associated with lifetime mood (odds ratio [OR] = 1.7) and anxiety (OR = 2.3) disorders; PA with lifetime anxiety disorder (OR = 2.8); and any abuse with increased risk for lifetime mood (OR = 1.7) and 12-month anxiety disorders (OR = 1.8). Earlier onset of SA or PA was associated with increased risk for later psychopathology. Copyright © 2011 by Lippincott Williams & Wilkins.

Davidson S.,Helen Schneider Hospital for Women | Davidson S.,Tel Aviv University | Natan D.,Maccabi Healthcare Services | Novikov I.,Gertner Institute for Epidemiology | And 5 more authors.
Clinical Nutrition | Year: 2011

Background & aims: The risk of childhood obesity, an increasingly prevalent problem worldwide, might be predictable by early body mass index measurements. This study sought to develop body mass index and weight-for-length ratio references for infants born at 33-42 weeks gestation and to validate these data against the growth curves of the World Health Organization Multicenter Growth Reference Study. Methods: Data were collected from the Neonatal Registry of Rabin Medical Center for all healthy singleton babies born live at 33-42 weeks gestation. Crude and smoothed reference tables and graphs for body mass index and weight-for-length ratio by gestational age were created for males and females, separately. Results: Birth weight, length, and body mass index percentiles for full-term neonates were similar to the World Health Organization study, reinforcing the generalizability of our reference charts for infants born at 33-42 weeks. Cutoff values for small for date (<5th, <10th percentile) and large for date (>85th, >95th percentile) infants differed across gestational ages in both pre-term and full-term infants. Conclusions: As body proportionality indexes provide an assessment of body mass and fatness relative to length, we suggest that BMI and Wt/L ratio percentiles be added to weight and length growth curves as a routine intrauterine growth assessment at birth. © 2011 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism.

Twig G.,Sheba Medical Center | Twig G.,Israel Defense Forces | Gluzman I.,Israel Defense Forces | Gluzman I.,Tel Aviv University | And 21 more authors.
Diabetes Care | Year: 2014

OBJECTIVE: Diabetes is a risk factor for an accelerated rate of cognitive decline and dementia. However, the relationship between cognitive function and the subsequent development of diabetes is unclear. RESEARCH DESIGN AND METHODS: We conducted a historical-prospective cohort study merging data collected at premilitary recruitment assessment with information collected at the Staff Periodic Examination Center of the Israeli Army Medical Corps. Included were men aged 25 years or older without a history of diabetes at the beginning of follow-up with available data regarding their general intelligence score (GIS), a comprehensive measure of cognitive function, at age 17 years. RESULTS: Among 35,500 men followed for a median of 5.5 years, 770 new cases of diabetes were diagnosed. After adjustment for age, participants in the lowest GIS category had a 2.6-fold greater risk for developing diabetes compared with those in the highest GIS category. In multivariable analysis adjusted for age, BMI, fasting plasma glucose, sociogenetic variables, and lifestyle risk factors, those in the lowest GIS category had a twofold greater risk for incident diabetes when compared with the highest GIS category (hazard ratio 2.1 [95% CI 1.5 -3.1]; P < 0.001). Additionally, participants in the lowest GIS category developed diabetes at a mean age of 39.5 ± 4.7 years and those in the highest GIS group at amean age of 41.5 ± 5.1 years (P for comparison 0.042). CONCLUSIONS: This study demonstrates that in addition to a potential causal link between diabetes and enhanced cognitive decline, lower cognitive function at late adolescence is independently associated with an elevated risk for future diabetes. © 2014 by the American Diabetes Association.

Sevilya Z.,Weizmann Institute of Science | Leitner-Dagan Y.,Weizmann Institute of Science | Pinchev M.,Technion - Israel Institute of Technology | Kremer R.,Rambam Health Care Campus | And 7 more authors.
Cancer Prevention Research | Year: 2014

DNA repair is a prime mechanism for preventing DNA damage, mutation, and cancers. Adopting a functional approach, we examined the association with lung cancer risk of an integrated DNA repair score, measured by a panel of three enzymatic DNA repair activities in peripheral blood mononuclear cells. The panel included assays for AP endonuclease 1 (APE1), 8-oxoguanine DNA glycosylase (OGG1), and methylpurine DNA glycosylase (MPG), all of which repair oxidative DNA damage as part of the base excision repair pathways. A blinded population-based case-control study was conducted with 96 patients with lung cancer and 96 control subjects matched by gender, age (±1 year), place of residence, and ethnic group (Jews/non-Jews). The three DNA repair activities were measured, and an integrated DNA repair OMA (OGG1, MPG, and APE1) score was calculated for each individual. Conditional logistic regression analysis revealed that individuals in the lowest tertile of the integrated DNA repair OMA score had an increased risk of lung cancer compared with the highest tertile, with OR = 9.7;95% confidence interval (CI), 3.1-29.8; P < 0.001, or OR = 5.6; 95% CI, 2.1-15.1; P < 0.001 after cross-validation. These results suggest that pending validation, this DNA repair panel of risk factors may be useful for lung cancer risk assessment, assisting prevention and referral to early detection by technologies such as low-dose computed tomography scanning. ©2014 AACR.

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