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Jay S. Kaufman
McGill University
Socioeconomic statusPopulationMedicineConfoundingEnvironmental health
10Publications
7H-index
163Citations
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Publications 11
Newest
#1Nathalie Auger (UdeM: Université de Montréal)H-Index: 24
#2Zhong-Cheng Luo (UdeM: Université de Montréal)H-Index: 20
Last. William D. Fraser (UdeM: Université de Montréal)H-Index: 71
view all 7 authors...
Abstract Background The incidence of preeclampsia is increasing, but effects on women and infants are unclear. We measured the incidence of preeclampsia over time in a large Canadian population, and assessed trends in maternal and infant morbidity and mortality. Methods We carried out a population-based study of 1,901,376 linked hospital discharge abstracts for all deliveries in the province of Quebec, Canada from 1989 through 2012. We computed the annual incidence of preeclampsia, and used log ...
15 CitationsSource
#1Britt McKinnon (McGill University)H-Index: 10
#2Sam Harper (McGill University)H-Index: 33
Last. Jay S. Kaufman (McGill University)H-Index: 7
view all 3 authors...
Objectives To examine socioeconomic and health system determinants of wealth-related inequalities in neonatal mortality rates (NMR) across 48 low- and middle-income countries.
4 CitationsSource
#1Britt McKinnon (McGill University)H-Index: 10
#2Seungmi YangH-Index: 17
Last. Jay S. KaufmanH-Index: 7
view all 6 authors...
In the United States, a higher risk of preterm birth among black women than among white women is well established.1–3 This racial disparity is of great concern because preterm birth is a leading cause of perinatal mortality and is predictive of developmental problems and adverse health outcomes later in life.4 The underlying causes of the racial disparity in preterm birth in the US are not well understood, although research has suggested contributing roles for a wide range of factors, including ...
10 CitationsSource
Obesity and smoking are independently associated with a higher mortality risk, but previous studies have reported conflicting results about the relationship between these 2 time-varying exposures. Using prospective longitudinal data (1987-2007) from the Atherosclerosis Risk in Communities Study, our objective in the present study was to estimate the joint effects of obesity and smoking on all-cause mortality and investigate whether there were additive or multiplicative interactions. We fit a joi...
11 CitationsSource
#1Britt McKinnon (McGill University)H-Index: 10
#2Nathalie Auger (UdeM: Université de Montréal)H-Index: 24
Last. Jay S. Kaufman (McGill University)H-Index: 7
view all 3 authors...
Background Smoke-free legislation may have positive effects on birth outcomes. Given that smoking and secondhand smoke during pregnancy vary with socioeconomic position, legislation may have greater effects in some socioeconomic groups. For this study, we evaluated the impact of a 2006 ban on smoking in public places in the Canadian province of Quebec on preterm birth, small-for-gestational-age birth and birth weight, and on educational differences in these birth outcomes. Methods We analysed da...
10 CitationsSource
#1Russell SteeleH-Index: 33
#2Ian ShrierH-Index: 44
Last. Robert W. PlattH-Index: 74
view all 4 authors...
In randomized controlled trials, the intention-to-treat estimator provides an unbiased estimate of the causal effect of treatment assignment on the outcome. However, patients often want to know what the effect would be if they were to take the treatment as prescribed (the patient-oriented effect), and several researchers have suggested that the more relevant causal effect for this question is the complier average causal effect (CACE), also referred to as the local average treatment effect. Sophi...
4 CitationsSource
#1Ghassan B. Hamra (Drexel University)H-Index: 14
#2Jay S. Kaufman (McGill University)H-Index: 7
Last. Anjel Vahratian (UM: University of Michigan)H-Index: 15
view all 3 authors...
Model selection is an integral, yet contentious, component of epidemiologic research. Unfortunately, there remains no consensus on how to identify a single, best model among multiple candidate models. Researchers may be prone to selecting the model that best supports their a priori, preferred result; a phenomenon referred to as “wish bias”. Directed acyclic graphs (DAGs), based on background causal and substantive knowledge, are a useful tool for specifying a subset of adjustment variables to ob...
3 CitationsSource
#1Geneviève Gariépy (McGill University)H-Index: 18
#2Brett D. Thombs (McGill University)H-Index: 47
Last. Norbert Schmitz (McGill University)H-Index: 42
view all 6 authors...
Aim To investigate the effect of the neighbourhood built environment on trajectories of depression symptom episodes in adults from the general Canadian population. Research Design and Methods We used 10 years of data collection (2000/01-2010/11) from the Canadian National Population Health Study (n = 7114). Episodes of depression symptoms were identified using the Composite International Diagnostic Interview Short-Form. We assessed the presence of local parks, healthy food stores, fast food rest...
10 CitationsSource
#1Hailey R. Banack (McGill University)H-Index: 11
#2Jay S. Kaufman (McGill University)H-Index: 7
Smoking is often identified as a confounder of the obesity–mortality relationship. Selection bias can amplify the magnitude of an existing confounding bias. The objective of the present report is to demonstrate how confounding bias due to cigarette smoking is increased in the presence of collider stratification bias using an empirical example and directed acyclic graphs. The empirical example uses data from the Atherosclerosis Risk in Communities (ARIC) study, a prospective cohort study of 15,79...
27 CitationsSource
#1Geneviève Gariépy (McGill University)H-Index: 18
#2Jay S. Kaufman (McGill University)H-Index: 7
Last. Norbert Schmitz (McGill University)H-Index: 42
view all 5 authors...
Background Depression is a common co-illness in people with diabetes. Evidence suggests that the neighbourhood environment impacts the risk of depression, but few studies have investigated this effect in those with diabetes. We examined the effect of a range of neighbourhood characteristics on depression in people with Type 2 diabetes. Methods This cohort study used five waves of data from 1298 participants with Type 2 diabetes from the Diabetes Health Study (2008–2013). We assessed depression u...
5 CitationsSource
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