scholarly journals Association of genetic and behavioral characteristics with the onset of diabetes

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Carmen D. Ng ◽  
Jordan Weiss
Keyword(s):  
Risk Factors ◽  
Diabetes Management ◽  
Cox Regression ◽  
Critical Role ◽  
The United States ◽  
Behavioral Risk ◽  
Survey Period ◽  
Genetic Endowment ◽  
Onset Of Diabetes ◽  
Time Varying Covariates

Abstract Background Prior work has established sociodemographic, lifestyle, and behavioral risk factors for diabetes but the contribution of these factors to the onset of diabetes remains unclear when accounting for genetic propensity for diabetes. We examined the contribution of a diabetes polygenic score (PGS) to the onset of diabetes in the context of modifiable known risk factors for diabetes. Methods Our sample consisted of 15,190 respondents in the United States-based Health and Retirement Study, a longitudinal study with up to 22 years of follow-up. We performed multivariate Cox regression models stratified by race (non-Hispanic white and non-Hispanic black) with time-varying covariates. Results We observed 4217 (27.76%) cases of incident diabetes over the survey period. The diabetes PGS was statistically significantly associated with diabetes onset for both non-Hispanic whites (hazard ratio [HR] = 1.38, 95% confidence interval [CI] = 1.30, 1.46) and non-Hispanic blacks (HR = 1.22, 95% CI = 1.06, 1.40) after adjusting for a range of known risk factors for diabetes, highlighting the critical role genetic endowment might play. Nevertheless, genetics do not downplay the role that modifiable characteristics could still play in diabetes management; even with the inclusion of the diabetes PGS, several behavioral and lifestyle characteristics remained significant for both race groups. Conclusions The effects of genetic and lifestyle characteristics should be taken into consideration for both future studies and diabetes management.

scholarly journals Atrial Fibrillation/flutter Hospitalizations among US Medicaid Recipients with and without Systemic Lupus Erythematosus

2019 ◽  
Vol 47 (9) ◽  
pp. 1359-1365 ◽  
Author(s):  
Sarah K. Chen ◽  
Medha Barbhaiya ◽  
Daniel H. Solomon ◽  
Hongshu Guan ◽  
Kazuki Yoshida ◽  
...  
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Cox Regression ◽  
The United States ◽  
Incidence Rates ◽  
Systemic Lupus ◽  
Cox Models ◽  
Age And Sex

Objective.Systemic lupus erythematosus (SLE) is a multisystem chronic inflammatory autoimmune disease with high prevalence of several risk factors for atrial fibrillation/flutter (AF). However, the incidence and risk of AF in SLE have not been well quantified.Methods.We used the United States Medicaid Analytic eXtract from 2007 to 2010 to identify beneficiaries aged 18–65 years, with prevalent SLE, each matched by age and sex to 4 non-SLE general Medicaid recipients. We estimated the incidence rates (IR) per 1000 person-years (PY) for AF hospitalizations and used multivariable Cox regression to estimate the HR for AF hospitalization.Results.We identified 46,876 US Medicaid recipients with SLE, and 187,504 age- and sex-matched non-SLE controls (93% female; mean age 41.5 ± 12.2 yrs). Known AF risk factors such as hypertension (HTN), cardiovascular disease (CVD), and kidney disease were more prevalent in patients with SLE. During a mean followup of 1.9 ± 1.1 years for SLE, and 1.8 ± 1.1 years for controls, the IR per 1000 PY for AF was 1.4 (95% CI 1.1–1.6) among patients with SLE and 0.7 (95% CI 0.6–0.8) among non-SLE controls. In age- and sex-matched and race-adjusted Cox models, the HR for AF was 1.79 (95% CI 1.43–2.24); after adjustment for baseline HTN and CVD, the adjusted HR was reduced to 1.17 (95% CI 0.92–1.48).Conclusion.SLE was associated with a doubled rate of hospitalization for AF compared to age- and sex-matched general Medicaid patients. In a race-adjusted model, the risk was 80% higher. However, the AF risk factors HTN and CVD were more prevalent among patients with SLE and accounted for the excess risk.

scholarly journals Risk Factors of Lyme Disease: An Intersection of Environmental Ecology and Systems Science

Healthcare ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 66 ◽  
Author(s):  
Nasser Sharareh ◽  
Rachael P. Behler ◽  
Amanda B. Roome ◽  
Julian Shepherd ◽  
Ralph M. Garruto ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lyme Disease ◽  
Multinomial Logistic Regression ◽  
Ground Cover ◽  
The United States ◽  
System Level ◽  
Systems Science ◽  
Behavioral Risk ◽  
Risk Of Exposure ◽  
Risk Categories

Lyme disease (LD) cases have been on the rise throughout the United States, costing the healthcare system up to $1.3 billion per year, and making LD one of the greatest threats to public health. Factors influencing the number of LD cases range from environmental to system-level variables, but little is known about the influence of vegetation (canopy, understory, and ground cover) and human behavioral risk on LD cases and exposure to infected ticks. We determined the influence of various risk factors on the risk of exposure to infected ticks on 22 different walkways using multinomial logistic regression. The model classifies the walkways into high-risk and low-risk categories with 90% accuracy, in which the understory, human risk, and number of rodents are significant indicators. These factors should be managed to control the risk of transmission of LD to humans.

scholarly journals Revisiting the Association Between Cardiovascular Risk Factors and Diabetes

2009 ◽  
Vol 35 (5) ◽  
pp. 770-777 ◽  
Author(s):  
Kyeongra Yang ◽  
Eileen R. Chasens ◽  
Susan M. Sereika ◽  
Lora E. Burke
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Smoking Status ◽  
Strong Predictor ◽  
Large Population ◽  
The United States ◽  
Behavioral Risk ◽  
Increased Risk

Purpose The purpose of this study was to examine the association between cardiovascular risk factors and the presence of diabetes in a large population-level dataset. Methods A secondary analysis was conducted using data from the 2007 Behavioral Risk Factor Surveillance System, a population-based survey (n = 403,137) conducted in the United States. Results The majority of the respondents were middle-aged and overweight. Approximately half of the sample reported little or no physical activity. Estimates from a logistic regression model for a weighted sample of white, black, and Hispanic adults revealed that having hypertension or elevated cholesterol was a strong predictor of diabetes even when controlling for age, gender, race, education, income, body mass index, smoking status, and physical activity. Conclusions The results confirmed the importance of diabetes educators counseling patients with hypertension or hypercholesterolemia about their increased risk for developing diabetes.

Trends in Health-Related Behavioral Risk Factors Among Pregnant Women in the United States: 2001–2009

2012 ◽  
Vol 21 (3) ◽  
pp. 255-263 ◽  
Author(s):  
Guixiang Zhao ◽  
Earl S. Ford ◽  
James Tsai ◽  
Chaoyang Li ◽  
Indu B. Ahluwalia ◽  
...  
Keyword(s):  
United States ◽  
Risk Factors ◽  
Pregnant Women ◽  
The United States ◽  
Behavioral Risk Factors ◽  
Behavioral Risk ◽  
Health Related

scholarly journals A cross-sectional analysis of demographic and behavioral risk factors of SARS-CoV-2 antibody positivity among a sample of U.S. college students

2021 ◽  
Author(s):  
Sina Kianersi ◽  
Christina Ludema ◽  
Jonathan T. Macy ◽  
Edlin Garcia ◽  
Chen Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Undergraduate Students ◽  
Online Survey ◽  
Control Strategies ◽  
The United States ◽  
Romantic Partners ◽  
Colleges And Universities ◽  
Behavioral Risk ◽  
Drinking Alcohol ◽  
Cross Sectional

AbstractBackgroundColleges and universities across the United States are developing and implementing data-driven prevention and containment measures against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Identifying risk factors for SARS-CoV-2 seropositivity could help to direct these efforts.ObjectiveTo estimate the associations between demographic factors and social behaviors and SARS-CoV-2 seropositivity and self-reported positive SARS-CoV-2 diagnostic test.MethodsIn September 2020, we randomly sampled Indiana University Bloomington (IUB) undergraduate students. Participants completed a cross-sectional, online survey about demographics, SARS-CoV-2 testing history, relationship status, and risk behaviors. Additionally, during a subsequent appointment, participants were tested for SARS-CoV-2 antibodies using a fingerstick procedure and SARS-CoV-2 IgM/IgG rapid assay kit. We used unadjusted modified Poisson regression models to evaluate the associations between predictors of both SARS-CoV-2 seropositivity and self-reported positive SARS-CoV-2 infection history.ResultsOverall, 1,076 students were included in the serological testing analysis, and 1,239 students were included in the SARS-CoV-2 infection history analysis. Current seroprevalence of SARS-CoV-2 was 4.6% (95% CI: 3.3%, 5.8%). Prevalence of self-reported SARS-CoV-2 infection history was 10.3% (95% CI: 8.6%, 12.0%). Greek membership, having multiple romantic partners, knowing someone in one’s immediate environment with SARS-CoV-2 infection, drinking alcohol more than 1 day per week, and hanging out with more than 4 people when drinking alcohol increased both the likelihood of seropositivity and SARS-CoV-2 infection history.ConclusionOur findings have implications for American colleges and universities and could be used to inform SARS-C0V-2 prevention and control strategies on such campuses.

scholarly journals Risk Factors for Patient–Ventilator Asynchrony and Its Impact on Clinical Outcomes: Analytics Based on Deep Learning Algorithm

2020 ◽  
Vol 7 ◽  
Author(s):  
Huiqing Ge ◽  
Kailiang Duan ◽  
Jimei Wang ◽  
Liuqing Jiang ◽  
Lingwei Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Tidal Volume ◽  
Clinical Outcomes ◽  
Regression Models ◽  
Negative Binomial ◽  
Cox Regression ◽  
Plateau Pressure ◽  
Care Hospital ◽  
Time Varying ◽  
Time Varying Covariates

Background and objectives: Patient–ventilator asynchronies (PVAs) are common in mechanically ventilated patients. However, the epidemiology of PVAs and its impact on clinical outcome remains controversial. The current study aims to evaluate the epidemiology and risk factors of PVAs and their impact on clinical outcomes using big data analytics.Methods: The study was conducted in a tertiary care hospital; all patients with mechanical ventilation from June to December 2019 were included for analysis. Negative binomial regression and distributed lag non-linear models (DLNM) were used to explore risk factors for PVAs. PVAs were included as a time-varying covariate into Cox regression models to investigate its influence on the hazard of mortality and ventilator-associated events (VAEs).Results: A total of 146 patients involving 50,124 h and 51,451,138 respiratory cycles were analyzed. The overall mortality rate was 15.6%. Double triggering was less likely to occur during day hours (RR: 0.88; 95% CI: 0.85–0.90; p < 0.001) and occurred most frequently in pressure control ventilation (PCV) mode (median: 3; IQR: 1–9 per hour). Ineffective effort was more likely to occur during day time (RR: 1.09; 95% CI: 1.05–1.13; p < 0.001), and occurred most frequently in PSV mode (median: 8; IQR: 2–29 per hour). The effect of sedatives and analgesics showed temporal patterns in DLNM. PVAs were not associated mortality and VAE in Cox regression models with time-varying covariates.Conclusions: Our study showed that counts of PVAs were significantly influenced by time of the day, ventilation mode, ventilation settings (e.g., tidal volume and plateau pressure), and sedatives and analgesics. However, PVAs were not associated with the hazard of VAE or mortality after adjusting for protective ventilation strategies such as tidal volume, plateau pressure, and positive end expiratory pressure (PEEP).

Dynamic risk for first onset of depressive disorders in adolescence: does change matter?

2021 ◽  
pp. 1-9
Author(s):  
Wenting Mu ◽  
Kaiqiao Li ◽  
Yuan Tian ◽  
Greg Perlman ◽  
Giorgia Michelini ◽  
...  
Keyword(s):  
Risk Factors ◽  
Depressive Disorders ◽  
Cox Regression ◽  
Average Level ◽  
Risk Level ◽  
Social Risk ◽  
Dynamic Risk ◽  
First Onset ◽  
Time Varying Covariates ◽  
Chronic Risk

Abstract Background Risk factors for depressive disorders (DD) change substantially over time, but the prognostic value of these changes remains unclear. Two basic types of dynamic effects are possible. The ‘Risk Escalation hypothesis’ posits that worsening of risk levels predicts DD onset above average level of risk factors. Alternatively, the ‘Chronic Risk hypothesis’ posits that the average level rather than change predicts first-onset DD. Methods We utilized data from the ADEPT project, a cohort of 496 girls (baseline age 13.5–15.5 years) from the community followed for 3 years. Participants underwent five waves of assessments for risk factors and diagnostic interviews for DD. For illustration purposes, we selected 16 well-established dynamic risk factors for adolescent depression, such as depressive and anxiety symptoms, personality traits, clinical traits, and social risk factors. We conducted Cox regression analyses with time-varying covariates to predict first DD onset. Results Consistently elevated risk factors (i.e. the mean of multiple waves), but not recent escalation, predicted first-onset DD, consistent with the Chronic Risk hypothesis. This hypothesis was supported across all 16 risk factors. Conclusions Across a range of risk factors, girls who had first-onset DD generally did not experience a sharp increase in risk level shortly before the onset of disorder; rather, for years before onset, they exhibited elevated levels of risk. Our findings suggest that chronicity of risk should be a particular focus in screening high-risk populations to prevent the onset of DDs. In particular, regular monitoring of risk factors in school settings is highly informative.

Diabetes Management in San Diego’s Chamorro Community

2005 ◽  
Vol 31 (3) ◽  
pp. 379-390 ◽  
Author(s):  
Phillis L. Wu ◽  
Georgia Robins Sadler ◽  
Victoria Nguyen ◽  
Manli Shi ◽  
Elizabeth A. Gilpin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Health Care Providers ◽  
Intervention Program ◽  
Diabetes Management ◽  
Diabetes Risk ◽  
Community Leaders ◽  
Behavioral Risk ◽  
Collaborative Partnerships ◽  
Care Providers ◽  
Convenience Sample

Purpose The purpose of this study was to assess the diabetes risk status, incidence, and morbidity within San Diego’s Chamorro community as a foundation to help community leaders and health care providers create culturally customized health promotion interventions. Methods The Behavioral Risk Factor Surveillance Survey was used to query a randomly selected, convenience sample of San Diego Chamorros (N = 228) drawn from the Chamorro Directory International. Based on individual survey responses, participants were mailed personalized health-promoting information. Subsequently, they received information that addressed the most commonly observed overall threats to the Chamorro community’s health. Results A higher than average prevalence of diabetes and gestational diabetes was reported by study participants along with a high prevalence of the risk factors associated with the premature onset of diabetes and its consequences. Conclusion Collaborative partnerships between health professionals and community leaders can help identify opportunities and strategies for improving the health of the nation’s population subgroups. San Diego’s Chamorro community leaders now have a clearer understanding of the prevalence of diabetes risk factors within their community and can begin working with public health educators to create culturally aligned diabetes prevention and management programs. Given the willingness of Chamorro leaders to get involved in the development of a diabetes awareness campaign and the community’s closely knit social network, it should be possible to promote (1) community participation in the intervention program, (2) an increase in the community’s adherence to recommended behavioral changes, and (3) identification of additional program modifications that will further enhance the program’s cultural relevance.

scholarly journals Risk factors of damage in early diagnosed systemic lupus erythematosus: results of the Italian multicentre Early Lupus Project inception cohort

Rheumatology ◽  
2019 ◽  
Vol 59 (9) ◽  
pp. 2272-2281 ◽  
Author(s):  
Matteo Piga ◽  
Alberto Floris ◽  
Gian Domenico Sebastiani ◽  
Imma Prevete ◽  
Florenzo Iannone ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lupus Erythematosus ◽  
Cox Regression ◽  
Univariate Analysis ◽  
Damage Index ◽  
Inception Cohort ◽  
Damage Development ◽  
Increased Risk ◽  
Time Varying Covariates ◽  
Improve Patient

Abstract Objective To investigate risk factors for damage development in a prospective inception cohort of early diagnosed SLE patients. Methods The Early Lupus Project recruited an inception cohort of patients within 12 months of SLE classification (1997 ACR criteria). At enrolment and every 6 months thereafter, the SLICC/ACR Damage Index was recorded. The contribution of baseline and time-varying covariates to the development of damage, defined as any SLICC/ACR Damage Index increase from 0 to ≥1, was assessed using univariate analysis. Forward-backward Cox regression models were fitted with covariates with P < 0.05 to identify factors independently associated with the risk of damage development. Results Overall, 230 patients with a mean (s.d.) age of 36.5 (14.4) years were eligible for this study; the mean number of visits per patient was 5.3 (2.7). There were 51 (22.2%) patients with SLICC/ACR Damage Index ≥1 after 12 months, 59 (25.6%) after 24 months and 67 (29.1%) after 36 months. Dyslipidaemia [P = 0.001; hazard ratio (HR) 2.9; 95% CI 1.5, 5.6], older age (P = 0.001; HR 3.0; 95% CI 1.6, 5.5), number of organs/systems involved (P = 0.002; HR 1.4; 95% CI 1.1, 1.8) and cardiorespiratory involvement (P = 0.041; HR 1.9; 95% CI 1.0, 3.7) were independently associated with an increased risk of developing damage. Risk profiles for damage development differed for glucocorticoid-related and -unrelated damage. HCQ use (P = 0.005; HR 0.4; 95% CI 0.2, 0.8) reduced the risk of glucocorticoid-unrelated damage. Conclusion We identified risk factors of damage development, but little effect of glucocorticoids, in this early SLE cohort. Addressing modifiable risk factors from the time of SLE diagnosis might improve patient outcomes.

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