scholarly journals Obesity and risk of infections: results from men and women in the Swedish National March Cohort

2019 ◽  
Author(s):  
Francesca Ghilotti ◽  
Rino Bellocco ◽  
Weimin Ye ◽  
Hans-Olov Adami ◽  
Ylva Trolle Lagerros
Keyword(s):  
Proportional Hazards ◽  
Cox Model ◽  
Normal Weight ◽  
Cox Proportional Hazards ◽  
Event Analysis ◽  
Obese Women ◽  
Cox Models ◽  
Increased Risk ◽  
Repeated Events ◽  
Tract Infections

Abstract Background Previous studies have shown an association between body mass index (BMI) and infections, but the literature on type-specific community acquired infections is still limited. Methods We included 39 163 Swedish adults who completed a questionnaire in September 1997 and were followed through record-linkages until December 2016. Information on BMI was self-reported and infections were identified from the Swedish National Patient Register using International Classification of Diseases (ICD), Tenth Revision (ICD-10) codes. We fitted multivariable Cox proportional hazards models for time-to-first-event analysis, and we used extensions of the standard Cox model when repeated events were included. Results During a 19-year follow-up 32% of the subjects had at least one infection requiring health care contact, leading to a total of 27 675 events. We found an increased incidence of any infection in obese women [hazard ratio (HR) = 1.22; 95% confidence interval (CI) = 1.12; 1.33] and obese men (HR = 1.25; 95% CI = 1.09; 1.43) compared with normal weight subjects. For specific infections, higher incidences were observed for skin infections in both genders (HR = 1.76; 95% CI = 1.47; 2.12 for obese females and HR = 1.74; 95% CI = 1.33; 2.28 for obese males) and gastrointestinal tract infections (HR = 1.44; 95% CI = 1.19; 1.75), urinary tract infections (HR = 1.30; 95% CI = 1.08; 1.55) and sepsis (HR = 2.09; 95% CI = 1.46; 2.99) in obese females. When accounting for repeated events, estimates similar to the aforementioned ones were found. Conclusions Obesity was associated with an increased risk of infections in both genders. Results from multiple-failure survival analysis were consistent with those from classic Cox models.

scholarly journals Estimating cancer risk in relation to tritium exposure from routine operation of a nuclear-generating station in Pickering, Ontario

2013 ◽  
Vol 33 (4) ◽  
pp. 247-256 ◽  
Author(s):  
S Wanigaratne ◽  
E Holowaty ◽  
H Jiang ◽  
TA Norwood ◽  
R Pietrusiak ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Female Breast Cancer ◽  
Cox Proportional Hazards ◽  
Tritium Concentration ◽  
Cox Models ◽  
Adverse Health Effects ◽  
Increased Risk ◽  
Risk Of Cancer

Introduction Evidence suggests that current levels of tritium emissions from CANDU reactors in Canada are not related to adverse health effects. However, these studies lack tritium-specific dose data and have small numbers of cases. The purpose of our study was to determine whether tritium emitted from a nuclear-generating station during routine operation is associated with risk of cancer in Pickering, Ontario. Methods A retrospective cohort was formed through linkage of Pickering and north Oshawa residents (1985) to incident cancer cases (1985–2005). We examined all sites combined, leukemia, lung, thyroid and childhood cancers (6–19 years) for males and females as well as female breast cancer. Tritium estimates were based on an atmospheric dispersion model, incorporating characteristics of annual tritium emissions and meteorology. Tritium concentration estimates were assigned to each cohort member based on exact location of residence. Person-years analysis was used to determine whether observed cancer cases were higher than expected. Cox proportional hazards regression was used to determine whether tritium was associated with radiation-sensitive cancers in Pickering. Results Person-years analysis showed female childhood cancer cases to be significantly higher than expected (standardized incidence ratio [SIR] = 1.99, 95% confidence interval [CI]: 1.08–3.38). The issue of multiple comparisons is the most likely explanation for this finding. Cox models revealed that female lung cancer was significantly higher in Pickering versus north Oshawa (HR = 2.34, 95% CI: 1.23–4.46) and that tritium was not associated with increased risk. The improved methodology used in this study adds to our understanding of cancer risks associated with low-dose tritium exposure. Conclusion Tritium estimates were not associated with increased risk of radiation-sensitive cancers in Pickering.

scholarly journals Lopinavir/Ritonavir and Darunavir/Cobicistat in Hospitalized COVID-19 Patients: Findings From the Multicenter Italian CORIST Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Augusto Di Castelnuovo ◽  
Simona Costanzo ◽  
Andrea Antinori ◽  
Nausicaa Berselli ◽  
Lorenzo Blandi ◽  
...  
Keyword(s):  
Observational Study ◽  
Propensity Scores ◽  
Proportional Hazards ◽  
Real Life ◽  
Cox Proportional Hazards ◽  
Event Analysis ◽  
Multicenter Observational Study ◽  
Protein Levels ◽  
Cox Proportional Hazards Models ◽  
Increased Risk

Background: Protease inhibitors have been considered as possible therapeutic agents for COVID-19 patients.Objectives: To describe the association between lopinavir/ritonavir (LPV/r) or darunavir/cobicistat (DRV/c) use and in-hospital mortality in COVID-19 patients.Study Design: Multicenter observational study of COVID-19 patients admitted in 33 Italian hospitals. Medications, preexisting conditions, clinical measures, and outcomes were extracted from medical records. Patients were retrospectively divided in three groups, according to use of LPV/r, DRV/c or none of them. Primary outcome in a time-to event analysis was death. We used Cox proportional-hazards models with inverse probability of treatment weighting by multinomial propensity scores.Results: Out of 3,451 patients, 33.3% LPV/r and 13.9% received DRV/c. Patients receiving LPV/r or DRV/c were more likely younger, men, had higher C-reactive protein levels while less likely had hypertension, cardiovascular, pulmonary or kidney disease. After adjustment for propensity scores, LPV/r use was not associated with mortality (HR = 0.94, 95% CI 0.78 to 1.13), whereas treatment with DRV/c was associated with a higher death risk (HR = 1.89, 1.53 to 2.34, E-value = 2.43). This increased risk was more marked in women, in elderly, in patients with higher severity of COVID-19 and in patients receiving other COVID-19 drugs.Conclusions: In a large cohort of Italian patients hospitalized for COVID-19 in a real-life setting, the use of LPV/r treatment did not change death rate, while DRV/c was associated with increased mortality. Within the limits of an observational study, these data do not support the use of LPV/r or DRV/c in COVID-19 patients.

Proportionally Difficult: Testing for Nonproportional Hazards in Cox Models

2010 ◽  
Vol 18 (2) ◽  
pp. 189-205 ◽  
Author(s):  
Luke Keele
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Model ◽  
Standard Test ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Cox Models ◽  
Nonproportional Hazards ◽  
Specification Errors ◽  
Hazards Model

The Cox proportional hazards model is widely used to model durations in the social sciences. Although this model allows analysts to forgo choices about the form of the hazard, it demands careful attention to the proportional hazards assumption. To this end, a standard diagnostic method has been developed to test this assumption. I argue that the standard test for nonproportional hazards has been misunderstood in current practice. This test detects a variety of specification errors, and these specification errors must be corrected before one can correctly diagnose nonproportionality. In particular, unmodeled nonlinearity can appear as a violation of the proportional hazard assumption for the Cox model. Using both simulation and empirical examples, I demonstrate how an analyst might be led astray by incorrectly applying the nonproportionality test.

scholarly journals Higher risk of dementia in English older individuals who are overweight or obese

2020 ◽  
Vol 49 (4) ◽  
pp. 1353-1365 ◽  
Author(s):  
Yixuan Ma ◽  
Olesya Ajnakina ◽  
Andrew Steptoe ◽  
Dorina Cadar
Keyword(s):  
Body Weight ◽  
Abdominal Obesity ◽  
Central Obesity ◽  
Proportional Hazards ◽  
Normal Weight ◽  
Cox Proportional Hazards ◽  
Older Individuals ◽  
Obese Women ◽  
Dementia Incidence

Abstract Background Several risk factors contribute to dementia, but the role of obesity remains unclear. This study investigated whether increased body weight or central obesity were associated with a higher risk of developing dementia in a representative sample of older English adults. Methods We studied 6582 participants from the English Longitudinal Study of Ageing (ELSA) who were aged ≥50 years and were dementia-free at baseline, that being either wave 1 (2002–2003) for study members who started at wave 1, or at either wave 2 (2004–2005) or 4 (2008–2009) for those who began the study as refreshment samples. Body mass index (BMI) was measured at baseline and categorized into normal weight (18.5–24.9 kg/m2), overweight (25–29.9 kg/m2) and obese (≥30 kg/m2). Central obesity was defined as a waist circumference (WC) >88 cm for women and >102 cm for men. Cumulative incidence of dementia was ascertained based on physician-diagnosed dementia, an overall score >3.38 on the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) and Hospital Episodes Statistics (HES) data at every ELSA wave from baseline until wave 8 (2016–2017). Cox proportional hazards models were used to assess the association between baseline BMI levels or abdominal obesity in relation to dementia incidence during the mean follow-up period of 11 years. Results From the overall sample, 6.9% (n = 453) of participants developed dementia during the follow-up period of maximum 15 years (2002–2017). Compared with participants with normal weight, those who were obese at baseline had an elevated risk of dementia incidence [hazard ratio (HR) = 1.34, 95% confidence interval (CI) 1.07–1.61] independent of sex, baseline age, apolipoprotein E-ε4 (APOE-ε4), education, physical activity, smoking and marital status. The relationship was slightly accentuated after additionally controlling for hypertension and diabetes (HR = 1.31, 95% CI 1.03–1.59). Women with central obesity had a 39% greater risk of dementia compared with non-central obese women (HR = 1.39, 95% CI 1.12–1.66). When compared with a normal BMI and WC group, the obese and high WC group had 28% (HR = 1.28, 95% CI 1.03–1.53) higher risk of dementia. Conclusions Our results suggest that having an increased body weight or abdominal obesity are associated with increased dementia incidence. These findings have significant implications for dementia prevention and overall public health.

Obesity and its impact on outcomes in stage III colon cancer (CC) patients receiving adjuvant chemotherapy (AC).

2019 ◽  
Vol 37 (4_suppl) ◽  
pp. 627-627
Author(s):  
Qirui Ding ◽  
Geoff McKinnon ◽  
Yuan Xu ◽  
Winson Y. Cheung
Keyword(s):  
Proportional Hazards ◽  
Population Based ◽  
Normal Weight ◽  
Cox Proportional Hazards ◽  
Stage Iii ◽  
Time Interval ◽  
Obese Patients ◽  
Cancer Specific Survival ◽  
Cox Models ◽  
The Impact

627 Background: Obesity may complicate CC surgery, which can result in potential AC delays. We aimed to determine the effect of body mass index (BMI) and body surface area (BSA) on CC outcomes, accounting for variations in the time interval between surgery and AC. Methods: We analyzed a population-based cohort of patients from Alberta, Canada who were diagnosed with stage III CC from 2011 to 2016 and underwent AC. Patients were grouped based on their baseline BSA (underweight, < 20 kg/m2; normal, 20-24; overweight, 25-29; obese ≥ 30) and BMI (< 2 m2 vs ≥ 2 m2). Logistic regression models were constructed to examine the effect of BMI/BSA on delays between surgery and AC. The Kaplan-Meier method was used to estimate overall (OS) and cancer-specific survival (CSS) and Cox proportional hazards models were developed to evaluate the impact of BMI/BSA on these outcomes, adjusting for confounders. Results: We examined 915 patients: median age was 64 years, 510 (56%) were men and 155 (17%) had a Charlson comorbidity index (CCI) ≥ 2. In this cohort, 126 (14%), 623 (68%) and 166 (18%) were stage IIIA, IIIB and IIIC, respectively. In total, 132 (14%) were underweight, 452 (49%) normal weight, 233 (26%) overweight and 98 (11%) obese. Based on the Mosteller formula, 527 (58%) patients had normal BSA and 368 (42%) had high BSA. Obese patients were more likely to be men (67% vs 56%, p < 0.001) and had worse CCI (28% vs 17% with CCI ≥ 2, p = 0.03) when compared to non-obese patients. Neither BMI (p = 0.14) nor BSA (p = 0.44) correlated with AC delays after surgery. Similar OS and CSS were observed regardless of BMI and BSA (p = 0.76 and 0.80 for OS and p = 0.60 and 0.89 for CSS, respectively). In multivariate Cox models, only worse nodal stage was associated with inferior OS and CSS (HR 4.74, 95%CI 1.96-11.47, p < 0.001 for OS; HR 4.92, 95%CI 1.42-17.00, p = 0.006 for CSS, comparing IIIC vs IIIA), but BMI and BSA were not (see Table). Conclusions: Obesity as measured by BMI and BSA did not correlate with AC delays or worse outcomes in stage III CC patients. [Table: see text]

MO138ASSOCIATION OF NT-PROBNP WITH OBESITY IN CKD PATIENTS

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Ting-Yun Lin ◽  
Szu-Chun Hung
Keyword(s):  
Heart Failure ◽  
Clinical Outcomes ◽  
Body Mass ◽  
Proportional Hazards ◽  
Normal Weight ◽  
Cox Proportional Hazards ◽  
Asymptomatic Patients ◽  
Cox Proportional Hazards Models ◽  
Increased Risk ◽  
Ckd Stage

Abstract Background and Aims Obesity is associated with lower circulating levels of N-terminal pro-BNP (NT-proBNP) both in the general population and in patients with heart failure. In asymptomatic patients with CKD, NT-proBNP levels are generally elevated. The prevalence of obesity is markedly increasing among patients with CKD. However, whether obesity affects NT-proBNP levels and thresholds for increased risk of clinical outcomes is unclear. Method We examined the associations between NT-proBNP and obesity in 408 stage 3–5 CKD patients (268 men and 140 women; mean age 65±13 years) free of heart failure at baseline, who were categorized into 3 groups according to body mass index (BMI; kg/m2) as normal (&lt;24.0), overweight (24.0–27.9), and obese (≥28.0). Multivariate Cox proportional hazards models were used to compare the risk associations of NT-proBNP with the composite of ESKD (needing chronic dialysis or kidney transplantation) or all-cause mortality across BMI categories. Results NT-proBNP levels were significantly lower in obese patients than in normal weight and overweight subjects (P &lt;0.001). Within each CKD stage, NT-proBNP levels decreased with increasing BMI. In a multivariate analysis, NT-proBNP was inversely associated with obesity, as well as BMI and its fat and lean body mass components (all P &lt;0.001), independent of demographics, comorbidities, and severity of CKD. During a median follow-up of 2.2 years, 117 patients progressed to ESKD and 46 patients died. Overall, higher NT-proBNP levels were independently associated with ESKD or death (HR, 1.52; 95% CI, 1.22–1.89). Specifically, higher NT-proBNP levels were consistently associated with poor outcomes in all BMI categories (P for interaction = 0.096). Conclusion Obese CKD patients have significantly lower NT-proBNP levels. Nevertheless, BMI category did not modify the relationship between NT-proBNP and clinical outcomes. Increased risk may be seen at relatively lower levels of NT-proBNP in obese CKD patients.

scholarly journals Levels of ankle–brachial index and the risk of diabetes mellitus complications

2020 ◽  
Vol 8 (1) ◽  
pp. e000977
Author(s):  
Lia Alves-Cabratosa ◽  
Marc Comas-Cufí ◽  
Anna Ponjoan ◽  
Maria Garcia-Gil ◽  
Ruth Martí-Lluch ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Proportional Hazards ◽  
Microvascular Complications ◽  
Ankle Brachial Index ◽  
Cardiovascular Prevention ◽  
Cox Proportional Hazards ◽  
Cox Models ◽  
Complications Of Diabetes ◽  
Increased Risk

ObjectiveWe sought to compare the association of categorized ankle–brachial index (ABI) with mortality and complications of diabetes in persons with no symptoms of peripheral arterial disease (PAD) and in primary cardiovascular disease prevention.Research design and methodsThis is a retrospective cohort study of persons with type 2 diabetes aged 35–85 years, from 2006 to 2011. Data were obtained from the Sistema d'Informació per al Desenvolupament de la Investigació en Atenció Primària (SIDIAPQ). Participants had an ABI measurement that was classified into six categories. For each category of ABI, we assessed the incidence of mortality; macrovascular complications of diabetes: acute myocardial infarction (AMI), ischemic stroke, and a composite of these two; and microvascular complications of this metabolic condition: nephropathy, retinopathy, and neuropathy. We also estimated the HRs for these outcomes by ABI category using Cox proportional hazards models.ResultsData from 34 689 persons with type 2 diabetes were included. The mean age was 66.2; 51.5% were men; and the median follow-up was 6.0 years. The outcome with the highest incidence was nephropathy, with 24.4 cases per 1000 person-years in the reference category of 1.1≤ABI≤1.3. The incidences in this category for mortality and AMI were 15.4 and 4.1, respectively. In the Cox models, low ABI was associated with increased risk and was significant from ABI lower than 0.9; below this level, the risk kept increasing steeply. High ABI (over 1.3) was also associated with significant increased risk for most outcomes.ConclusionsThe studied categories of ABI were associated with different risks of type 2 diabetes complications in persons asymptomatic for PAD, who were in primary cardiovascular prevention. These findings could be useful to optimize preventive interventions according to the ABI category in this population.

scholarly journals smoothHR: An R Package for Pointwise Nonparametric Estimation of Hazard Ratio Curves of Continuous Predictors

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Luís Meira-Machado ◽  
Carmen Cadarso-Suárez ◽  
Francisco Gude ◽  
Artur Araújo
Keyword(s):  
Survival Data ◽  
Degrees Of Freedom ◽  
Proportional Hazards ◽  
Cox Model ◽  
Cox Proportional Hazards ◽  
Hazard Ratio ◽  
Cox Models ◽  
Smoothing Methods ◽  
Coronary Syndrome ◽  
Continuous Predictors

The Cox proportional hazards regression model has become the traditional choice for modeling survival data in medical studies. To introduce flexibility into the Cox model, several smoothing methods may be applied, and approaches based on splines are the most frequently considered in this context. To better understand the effects that each continuous covariate has on the outcome, results can be expressed in terms of splines-based hazard ratio (HR) curves, taking a specific covariate value as reference. Despite the potential advantages of using spline smoothing methods in survival analysis, there is currently no analytical method in theRsoftware to choose the optimal degrees of freedom in multivariable Cox models (with two or more nonlinear covariate effects). This paper describes anRpackage, calledsmoothHR, that allows the computation of pointwise estimates of the HRs—and their corresponding confidence limits—of continuous predictors introduced nonlinearly. In addition the package provides functions for choosing automatically the degrees of freedom in multivariable Cox models. The package is available from theRhomepage. We illustrate the use of the key functions of thesmoothHRpackage using data from a study on breast cancer and data on acute coronary syndrome, from Galicia, Spain.

scholarly journals Glycemic Status and Infection Risk in Nondiabetic Autologous Hematopoietic Cell Transplantation Recipients

2016 ◽  
Vol 18 (3) ◽  
pp. 344-350 ◽  
Author(s):  
Marilyn J. Hammer ◽  
Gail D’Eramo Melkus ◽  
M. Tish Knobf ◽  
Corey Casper ◽  
Jason Fletcher ◽  
...  
Keyword(s):  
Cell Transplantation ◽  
Hematopoietic Cell Transplantation ◽  
Proportional Hazards ◽  
Cox Model ◽  
Cox Proportional Hazards ◽  
Hematopoietic Cell ◽  
Cancer Center ◽  
Glycemic Status ◽  
Increased Risk ◽  
Autologous Hct

Background: Patients undergoing hematopoietic cell transplantation (HCT) for hematological malignancies experience a number of challenges during treatment. There is growing evidence that malglycemia (hyperglycemia, hypoglycemia, and/or increased glycemic variability) contributes to HCT-related complications, even in patients without preexisting diabetes. The purpose of this pilot study was to investigate factors influencing glycemic status and associated infection occurrences in nondiabetic autologous HCT recipients. Methods: Oncology patients without preexisting diabetes treated with autologous HCT at a National Cancer Institute–designated cancer center were followed from admission through discharge or 28 days post-HCT. Patients had morning fasting laboratory tests. Descriptive statistics and Cox proportional hazards models were used to examine associations between BG levels and risk for infection while adjusting for baseline covariates including age, body mass index (BMI), cumulative glucocorticoid dose, and diagnosis. Results: The sample included 28 female and 25 male predominately non-Hispanic White patients (mean age 55.7 years, SD = 11.32). Blood glucose (BG) range was 35–325 mg/dl. Twenty-three patients incurred at least one infection. BMI ≥ 25 kg/m2 was associated with high BG and infections. In the multivariate Cox model, an increase of 1 interquartile range in BG 2 days before infection was associated with a moderately increased risk of infection (hazard ratio = 1.44, p = .008). Conclusions: Understanding the contributors to and consequences of malglycemic events can lead to better protocols for identifying patients at greater risk for infection. Further investigation is warranted for interventions to mitigate BG events for improved outcomes.

Underweight rather than adiposity is an important predictor of death in rural Chinese adults: a cohort study

2021 ◽  
pp. jech-2020-214821
Author(s):  
Yun Chen ◽  
Na Wang ◽  
Xiaolian Dong ◽  
Xuecai Wang ◽  
Jianfu Zhu ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Normal Weight ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Important Predictor ◽  
Hazards Model ◽  
Increased Risk ◽  
All Cause Mortality ◽  
A Prospective Study

BackgroundTo assess the associations of body mass index (BMI) with all-cause and cause-specific mortalities among rural Chinese.MethodsA prospective study of 28 895 individuals was conducted from 2006 to 2014 in rural Deqing, China. Height and weight were measured. The association of BMI with mortality was assessed by using Cox proportional hazards model and restricted cubic spline regression.ResultsThere were a total of 2062 deaths during an average follow-up of 7 years. As compared with those with BMI of 22.0–24.9 kg/m2, an increased risk of all-cause mortality was found for both underweight men (BMI <18.5 kg/m2) (adjusted HR (aHR): 1.45, 95% CI: 1.18 to 1.79) and low normal weight men (BMI of 18.5–21.9 kg/m2) (aHR: 1.20, 95% CI: 1.03 to 1.38). A J-shaped association was observed between BMI and all-cause mortality in men. Underweight also had an increased risk of cardiovascular disease and cancer mortalities in men. The association of underweight with all-cause mortality was more pronounced in ever smokers and older men (60+ years). The results remained after excluding participants who were followed up less than 1 year.ConclusionThe present study suggests that underweight is an important predictor of mortality, especially for elderly men in the rural community of China.

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