scholarly journals Graphical comparisons of relative disease burden across multiple risk factors

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
John Ferguson ◽  
Neil O’Leary ◽  
Fabrizio Maturo ◽  
Salim Yusuf ◽  
Martin O’Donnell
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Relative Risk ◽  
Disease Burden ◽  
Health Interventions ◽  
Continuous Exposure ◽  
Odds Ratios ◽  
Risk Factor Prevalence ◽  
Attributable Fractions ◽  
Log Odds

Abstract Background Population attributable fractions (PAF) measure the proportion of disease prevalence that would be avoided in a hypothetical population, similar to the population of interest, but where a particular risk factor is eliminated. They are extensively used in epidemiology to quantify and compare disease burden due to various risk factors, and directly influence public policy regarding possible health interventions. In contrast to individual specific metrics such as relative risks and odds ratios, attributable fractions depend jointly on both risk factor prevalence and relative risk. The relative contributions of these two components is important, and usually needs to be presented in summary tables that are presented together with the attributable fraction calculation. However, representing PAF in an accessible graphical format, that captures both prevalence and relative risk, may assist interpretation. Methods Taylor-series approximations to PAF in terms of risk factor prevalence and log-odds ratio are derived that facilitate simultaneous representation of PAF, risk factor prevalence and risk-factor/disease log-odds ratios on a single co-ordinate axis. Methods are developed for binary, multi-category and continuous exposure variables. Results The methods are demonstrated using INTERSTROKE, a large international case control dataset focused on risk factors for stroke. Conclusions The described methods could be used as a complement to tables summarizing prevalence, odds ratios and PAF, and may convey the same information in a more intuitive and visually appealing manner. The suggested nomogram can also be used to visually estimate the effects of health interventions which only partially reduce risk factor prevalence. Finally, in the binary risk factor case, the approximations can also be used to quickly convert logistic regression coefficients for a risk factor into approximate PAFs.

scholarly journals Population attributable fractions for continuously distributed exposures

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
John Ferguson ◽  
Fabrizio Maturo ◽  
Salim Yusuf ◽  
Martin O’Donnell
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Continuous Exposure ◽  
Minimum Risk ◽  
Population Attributable Fractions ◽  
Graphical Comparison ◽  
Attributable Fractions ◽  
Potential Outcomes Framework ◽  
Prior Risk ◽  
Tobacco Usage

AbstractWhen estimating population attributable fractions (PAF), it is common to partition a naturally continuous exposure into a categorical risk factor. While prior risk factor categorization can help estimation and interpretation, it can result in underestimation of the disease burden attributable to the exposure as well as biased comparisons across different exposures and risk factors. Here, we propose sensible PAF estimands for continuous exposures under a potential outcomes framework. In contrast to previous approaches, we incorporate estimation of the minimum risk exposure value (MREV) into our procedures. While for exposures such as tobacco usage, a sensible value of the MREV is known, often it is unknown and needs to be estimated. Second, in the setting that the MREV value is an extreme-value of the exposure lying in the distributional tail, we argue that the natural estimator of PAF may be both statistically biased and highly volatile; instead, we consider a family of modified PAFs which include the natural estimate of PAF as a limit. A graphical comparison of this set of modified PAF for differing risk factors may be a better way to rank risk factors as intervention targets, compared to the standard PAF calculation. Finally, we analyse the bias that may ensue from prior risk factor categorization, examining whether categorization is ever a good idea, and suggest interpretations of categorized-estimands within a causal inference setting.

scholarly journals Population attributable fraction for continuously distributed exposures

2020 ◽  
Author(s):  
John Ferguson ◽  
Fabrizio Maturo ◽  
Salim Yusuf ◽  
Martin O’Donnell
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Population Attributable Fraction ◽  
Continuous Exposure ◽  
Minimum Risk ◽  
Population Attributable Fractions ◽  
Graphical Comparison ◽  
Attributable Fractions ◽  
Potential Outcomes Framework ◽  
Prior Risk

AbstractWhen estimating population attributable fractions (PAF), it is common to partition a naturally continuous exposure into a categorical risk factor. While prior risk factor categorization can help estimation and interpretation, it can result in underestimation of the disease burden attributable to the exposure as well as biased comparisons across different exposures and risk factors. Here, we propose sensible PAF estimands for continuous exposures under a potential outcomes framework. In contrast to previous approaches, we incorporate estimation of the minimum risk exposure value (MREV) into our procedures. While for exposures such as tobacco usage, a sensible value of the MREV is known, often it is unknown and needs to be estimated. Second, in the setting that the MREV value is an extreme-value of the exposure lying in the distributional tail, we argue that the natural estimator of PAF may be both statistically biased and highly volatile; instead, we consider a family of modified PAFs which include the natural estimate of PAF as a limit. A graphical comparison of this set of modified PAF for differing risk factors may be a better way to rank risk factors as intervention targets, compared to the standard PAF calculation. Finally, we analyse the bias that may ensue from prior risk factor categorization, examining whether categorization is ever a good idea, and suggest interpretations of categorized-estimands within a causal inference setting.

scholarly journals Sugary Liquids in the Baby Bottle: Risk for Child Undernutrition and Severe Tooth Decay in Rural El Salvador

2020 ◽  
Vol 18 (1) ◽  
pp. 260
Author(s):  
Priyanka Achalu ◽  
Abhishek Bhatia ◽  
Bathsheba Turton ◽  
Lucy Luna ◽  
Karen Sokal-Gutierrez
Keyword(s):  
Risk Factors ◽  
Early Childhood ◽  
Risk Factor ◽  
Oral Health ◽  
Early Childhood Caries ◽  
Health Interventions ◽  
Tooth Decay ◽  
Child Undernutrition ◽  
Baby Bottle ◽  
Childhood Caries

As communities worldwide shift from consuming traditional diets to more processed snacks and sugar-sweetened beverages (SSBs), increases in child obesity and tooth decay and persistence of undernutrition are particularly apparent in Latin American countries. Further evidence of shared risk factors between child undernutrition and poor oral health outcomes is needed to structure more effective health interventions for children’s nutrition. This study aims to identify dietary, oral health, and sociodemographic risk factors for child undernutrition and severe early childhood caries (sECC) among a convenience sample of 797 caregiver–child pairs from rural Salvadoran communities. Caregiver interviews on child dietary and oral health practices were conducted, and their children’s height, weight, and dental exam data were collected. Multivariable regression analyses were performed using RStudio (version 1.0.143). Caregiver use of SSBs in the baby bottle was identified as a common significant risk factor for child undernutrition (p = 0.011) and sECC (p = 0.047). Early childhood caries (p = 0.023) was also a risk factor for developing undernutrition. Future maternal–child health and nutrition programs should coordinate with oral health interventions to discourage feeding children SSBs in the baby bottle and to advocate for policies limiting SSB marketing to young children and their families.

Abstract WP236: The Urban-Rural Divide: Risk Factor Prevalence in Ischemic Stroke Patients Across Two Decades

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Dinesh V Jillella ◽  
Sara Crawford ◽  
Anne S Tang ◽  
Rocio Lopez ◽  
Ken Uchino
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Ischemic Stroke ◽  
Regression Models ◽  
Stroke Risk ◽  
Stroke Patients ◽  
Stroke Risk Factor ◽  
Risk Factor Prevalence ◽  
Urban Rural ◽  
Artery Disease

Introduction: Regional disparities exist in stroke incidence and stroke related mortality in the United States. We aimed to elucidate the stroke risk factor prevalence trends based on urban versus rural location. Methods: From the National Inpatient Sample database the comorbid stroke risk factors were collected among hospitalized ischemic stroke patients during 2000-2016. Crude and age-and sex-standardized prevalence estimates were calculated for each risk factor during the time periods 2000-2008 and 2009-2016. We compared risk factor prevalence over the defined time periods using regression models, and differences in risk factor trends based on patient location categorized as urban (metropolitan with population of ≥ 1 million) and rural (neither micropolitan or metropolitan) using interaction terms in the regression models. Results: Stroke risk factor prevalence significantly increased from 2000-2008 to 2009-2016. When stratified based on patient location, most risk factors increased in both urban and rural groups. In the crude model, the urban to rural trend difference across 2000-08 and 2009-16 was significant in hypertension (p<0.0001), hyperlipidemia (p=0.0008), diabetes mellitus (p<0.0001), coronary artery disease (p<0.0001), smoking (p<0.0001) and alcohol (p=0.02). With age and sex standardization, the urban to rural trend difference was significant in hypertension (p<0.0001), hyperlipidemia (p=0.0007), coronary artery disease (p=0.01) and smoking (p<0.0001). Conclusion: The prevalence of vascular risk factors among ischemic stroke patients has increased over the last two decades. There exists an urban-rural divide, with rural patients showing larger increases in prevalence of several risk factors compared to urban patients.

scholarly journals The role of young children in a community-wide outbreak of hepatitis A

1997 ◽  
Vol 118 (3) ◽  
pp. 243-252 ◽  
Author(s):  
P. F. SMITH ◽  
J. C. GRABAU ◽  
A. WERZBERGER ◽  
R. A. GUNN ◽  
H. R. ROLKA ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Relative Risk ◽  
Jewish Community ◽  
Attack Rate ◽  
Odds Ratio ◽  
Hepatitis A ◽  
Age Group ◽  
Recurrent Hepatitis

An Hasidic Jewish community has experienced recurrent hepatitis A outbreaks since 1980. To assess risk factors for illness during a 1985–6 outbreak, the authors reviewed case records and randomly selected 93 households for an interview and serologic survey. In the outbreak, 117 cases of hepatitis A were identified, with the highest attack rate (4·2%) among 3–5 year olds. Among the survey households, the presence of 3–5 year olds was the only risk factor that increased a household's risk of hepatitis A (indeterminant relative risk, P=0·02). Furthermore, case households from the outbreak were more likely to have 3–5 year olds than were control households from the survey (odds ratio=16·4, P<0·001). Children 3–5 years old were more likely to have hepatitis A and may have been the most frequent transmitters of hepatitis A in this community. Hepatitis A vaccination of 3–5 year olds can protect this age group and might prevent future outbreaks in this community.

scholarly journals Trends of Prevalence of Uncontrolled Risk Factors for Cerebrocardiovascular Disease: Southern Italy from 1988/9 to 2008/9

Cholesterol ◽  
2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Vincenzo Capuano ◽  
Norman Lamaida ◽  
Ernesto Capuano ◽  
Rocco Capuano ◽  
Eduardo Capuano ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Cardiovascular Disease ◽  
Risk Factor ◽  
Southern Italy ◽  
Cross Sectional ◽  
Targeted Interventions ◽  
Risk Factor Prevalence ◽  
Cross Sectional Studies ◽  
Prevention Of Cardiovascular Disease

The aim of this study was to determine the trends of cardiovascular risk factor prevalence between 1988/9 and 2008/9 in the 25–74-year-old population in an area of Southern Italy. We compared three cross-sectional studies conducted in random population samples, in 1988/9, 1998/9, and 2008/9 in Salerno, Italy. The methodology of data collection (lipid profile, systolic and diastolic blood pressure, glycaemia, and smoking) and conducting tests which the population underwent during the three phases was standardized and comparable. Prevalence of diabetes, hypertension, hypercholesterolemia, and smoking was calculated and standardized for age. A total of 3491 subjects were included. From 1988/9 to 2008/9, in males, the prevalence of all four risk factors was reduced. In women, there was a clear reduction of hypertension, a similar prevalence of hypercholesterolemia, and an increase of smoking and diabetes. In the area of Salerno, our data confirm that the global prevalence of the major risk factors is decreasing in men, but their absolute values are still far from optimization. In women, diabetes and smoking showed a negative trend, therefore requiring targeted interventions. These data are now used as a base for executive targeted programs to improve prevention of cardiovascular disease in our community.

scholarly journals A Causally Naïve and Rigid Population Model of Disease Occurrence Given Two Non-Independent Risk Factors

2018 ◽  
Vol 10 (2) ◽  
Author(s):  
Olaf Dammann ◽  
Kenneth Chui ◽  
Anselm Blumer
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Retinopathy Of Prematurity ◽  
Population Model ◽  
Outcome Variable ◽  
Risk Factor Prevalence ◽  
Disease Occurrence ◽  
Independent Risk Factors ◽  
Simulation Results ◽  
Changes In Risk

We describe a computational population model with two risk factors and one outcome variable in which the prevalence (%) of all three variables, the association between each risk factor and the disease, as well as the association between the two risk factors is the input. We briefly describe three examples: retinopathy of prematurity, diabetes in Panama, and  smoking and obesity as risk factors for diabetes. We describe and discuss the simulation results in these three scenarios including how the published information is used as input and how changes in risk factor prevalence changes outcome prevalence.

Abstract MP007: Epicardial Fat Thickness: Distribution of and Associations With Cardiovascular Risk Factors in the Framingham Heart Study

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Michael L Chuang ◽  
Philimon Gona ◽  
Noriko Oyama-Manabe ◽  
Carol J Salton ◽  
Udo Hoffmann ◽  
...  
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Risk Factor ◽  
Cvd Risk Factors ◽  
Odds Ratios ◽  
Cvd Risk ◽  
Epicardial Fat Thickness ◽  
Heart Study ◽  
Fat Thickness ◽  
Fat Volume

Introduction: High pericardial fat volume (fatVOL) is associated with excess cardiovascular disease (CVD), but analyses for true fat volume can be time-consuming and require specialized software. Linear epicardial fat thickness (fatTHK) can be measured quickly from cardiac magnetic resonance (MRI) images and may serve as a surrogate for fatVOL. We sought to determine the distribution and CVD risk factor correlates of high fatTHK and to compare fatTHK with fatVOL in a community-dwelling adult cohort. Methods: Participants were drawn from the Framingham Heart Study Offspring cohort (N=995, aged 65±9 years, 54% women) and underwent cardiac MRI (SSFP sequence) and multidetector CT during 2002-2005. Clinical and risk factor covariates were obtained at the preceding cycle 7 examination (1998-2001). FatVOL was determined from volumetric MDCT data. FatTHK was measured from the MRI 4-chamber view over the midlevel right ventricular free wall at end-diastole. A healthy referent subsample (N=328), free of major CVD risk factors, was used to determine sex-specific cut points for high fatTHK. Odds ratios for high (>90th percentile) fatVOL and fatTHK versus common CVD risk factors were determined. Results: FatTHK was greater in men than women and increased with age in both sexes. FatTHK correlated with fatVOL at r=0.45 (p less than 0.001) High fatTHK was >=16.0 mm in men and >=13.3 mm in women, with 20.1% prevalence in men and 18.1 % in women. In both sexes, high fatVOL was associated ( Table ) with obesity, metabolic syndrome, dysglycemia, hypertension, prevalent CVD and hypertriglyceridemia. Similar associations, with slightly lower odds ratios, were seen for fatTHK. Conclusions: Greater fatTHK is associated with an excess burden of multiple CVD risk factors. Although correlation between linear fatTHK and true fatVOL was relatively modest, both measures appear to have similar associations with common CVD risk factors. FatTHK may be advantageous in that it can be determined quickly using standard MRI sequences for ventricular function. Table. Odds Ratios for High Pericardial Fat vs. Common CVD Risk Factors fatVOL: Men fatVOL: Women fatTHK: Men fatTHK: Women Obesity, BMI >=30 kg/m2 4.34 (2.78–6.78) 3.13 (2.03–4.82) 2.52 (1.77–3.60) 2.62 (1.84–3.74) Metabolic Syndrome 3.72 (2.38–5.83) 2.60 (1.65–4.08) 2.59 (1.75–3.84) 2.21 (1.53–3.17) Dysglycemia, FPG >=100 mg/dL 2.64 (1.72–4.06) 3.05 (1.98–4.68) 1.75 (1.22–2.50) 1.56 (1.10–2.23) Hypertension, S>=140 or D>=90 mmHg 2.51 (1.66–3.78) 1.96 (1.30–2.97) 2.10 (1.48–2.98) 1.58 (1.13–2.22) Prevalent CVD 1.94 (1.17–3.21) 2.48 (1.41–4.38) 1.73 (1.17–2.55) 1.83 (1.19–2.81) Triglycerides >=150 mg/dL 1.89 (1.25–2.86) 2.21 (1.43–3.42) 1.64 (1.15–2.34) 1.98 (1.38–2.82) Low HDL: M<40, W<50 mg/dL 1.57 (1.03–2.38) 1.44 (0.91–2.28) 1.40 (0.98–1.99) 2.57 (1.80–3.67)

Abstract P267: Geographic Patterns of Cardiovascular Disease Risk Factor Prevalence in the Continental US

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
Matthew S Loop ◽  
George Howard ◽  
Gustavo de los Campos ◽  
Mohammad Z Al-Hamdan ◽  
Monika M Safford ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Risk Factor ◽  
Geographic Variation ◽  
Smoking Prevalence ◽  
Local Population ◽  
Community Dwelling ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Risk Factor Prevalence

Objectives: Our understanding of geographic variation in cardiovascular disease (CVD) risk factors is based upon self-reported variables or geographically limited coverage. Our objective was to explore geographic variation in measured hypertension, measured diabetes, measured dyslipidemia, and self-reported current smoking prevalence. Methods: We used baseline data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, whose community-dwelling participants were recruited nationally between 2003 and 2007. Participants underwent a telephone interview and in-home examination. Hypertension, diabetes, and dyslipidemia were based on physiologic measures or reported medication use. Current cigarette smoking was self-reported. Using participants’ residential latitude and longitude, we tested for clustering of each risk factor using the difference in Ripley’s K functions test and, when we found evidence of clustering, used thin plate regression splines (TPRS) in a logistic regression framework to create age- race-, and sex-adjusted maps of risk factor prevalence. Results: Risk factor status and location data were available for 27,787 of the 30,239 participants (92%). Mean (±SD) age of these participants was 65(±9) years, 41% were black, 55% were women, 59% had hypertension, 22% had diabetes, 54% had dyslipidemia, and 15% were current smokers. We found statistically significant geographic clustering of hypertension, diabetes, and smoking prevalence, but not dyslipidemia. The regions with the highest prevalence varied across risk factors (Figure 1). Conclusions: Louisiana and Mississippi might require the most intense management of CVD risk factors. These maps show variation across and within administrative units, providing an accurate representation of geographic variation in risk factor prevalence. High resolution maps could be put to use by healthcare organizations to justify requests for higher reimbursement rates based upon local population health.

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