892 resultados para Generalized Logistic Model


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A great share of literature on social exclusion has been based mainly on the analysis of official survey data. Whereas these efforts have provided insights into the characteristics and conditions of those people living at the margins of mainstream social relations, they have however failed to encompass those who live beyond these very margins. Meanwhile, research on these hidden subpopulations, such as homeless and other vulnerable groups, remains generally less abundant and is significantly detached from the theoretical core of the debate on social exclusion. The concern about these shortcomings lies at the heart of our research. We seek to bring some light to the area by using data made available by an organization that provides services to people experiencing homelessness in Barcelona (Spain). The data sample contains clients in early stages of exclusion and others in chronic situations. Thus, we attempt to identify some of the variables that operate in preventing the "chronification" of those individuals in situation of social exclusion. Our findings suggest that certain variables such as educational level, income and housing type, which are considered to be central predictors in the analysis of poverty, behave differently when analyzing differences between stages of social exclusion. Although these results cannot be extrapolated to the whole Spanish or European reality, they could provide useful insight for future investigations on this topic.

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The objective was to examine the association between circumcision status and self-reported HIV infection among men who have sex with men (MSM) in Britain who predominantly or exclusively engaged in insertive anal intercourse. In 2007-2008, a convenience sample of MSM living in Britain was recruited through websites, in sexual health clinics, bars, clubs, and other venues. Men completed an online survey which included questions on circumcision status, HIV testing, HIV status, sexual risk behavior, and sexual role for anal sex. The analysis was restricted to 1,521 white British MSM who reported unprotected anal intercourse in the previous 3 months and who said they only or mostly took the insertive role during anal sex. Of these men, 254 (16.7 %) were circumcised. Among men who had had a previous HIV test (n = 1,097), self-reported HIV seropositivity was 8.6 % for circumcised men (17/197) and 8.9 % for uncircumcised men (80/900) (unadjusted odds ratio [OR], 0.97; 95 % confidence interval [95 % CI], 0.56, 1.67). In a multivariable logistic model adjusted for known risk factors for HIV infection, there was no evidence of an association between HIV seropositivity and circumcision status (adjusted OR, 0.79; 95 % CI, 0.43, 1.44), even among the 400 MSM who engaged exclusively in insertive anal sex (adjusted OR, 0.84; 95 % CI, 0.25, 2.81). Our study provides further evidence that circumcision is unlikely to be an effective strategy for HIV prevention among MSM in Britain.

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PURPOSE To extend the capabilities of the Cone Location and Magnitude Index algorithm to include a combination of topographic information from the anterior and posterior corneal surfaces and corneal thickness measurements to further improve our ability to correctly identify keratoconus using this new index: ConeLocationMagnitudeIndex_X. DESIGN Retrospective case-control study. METHODS Three independent data sets were analyzed: 1 development and 2 validation. The AnteriorCornealPower index was calculated to stratify the keratoconus data from mild to severe. The ConeLocationMagnitudeIndex algorithm was applied to all tomography data collected using a dual Scheimpflug-Placido-based tomographer. The ConeLocationMagnitudeIndex_X formula, resulting from analysis of the Development set, was used to determine the logistic regression model that best separates keratoconus from normal and was applied to all data sets to calculate PercentProbabilityKeratoconus_X. The sensitivity/specificity of PercentProbabilityKeratoconus_X was compared with the original PercentProbabilityKeratoconus, which only uses anterior axial data. RESULTS The AnteriorCornealPower severity distribution for the combined data sets are 136 mild, 12 moderate, and 7 severe. The logistic regression model generated for ConeLocationMagnitudeIndex_X produces complete separation for the Development set. Validation Set 1 has 1 false-negative and Validation Set 2 has 1 false-positive. The overall sensitivity/specificity results for the logistic model produced using the ConeLocationMagnitudeIndex_X algorithm are 99.4% and 99.6%, respectively. The overall sensitivity/specificity results for using the original ConeLocationMagnitudeIndex algorithm are 89.2% and 98.8%, respectively. CONCLUSIONS ConeLocationMagnitudeIndex_X provides a robust index that can detect the presence or absence of a keratoconic pattern in corneal tomography maps with improved sensitivity/specificity from the original anterior surface-only ConeLocationMagnitudeIndex algorithm.

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When tilted sideways participants misperceive the visual vertical assessed by means of a luminous line in otherwise complete dark- ness. A recent modeling approach (De Vrijer et al., 2009) claimed that these typical patterns of errors (known as A- and E-effects) could be explained by as- suming that participants behave in a Bayes optimal manner. In this study, we experimentally manipulate participants’ prior information about body-in-space orientation and measure the effect of this manipulation on the subjective visual vertical (SVV). Specifically, we explore the effects of veridical and misleading instructions about body tilt orientations on the SVV. We used a psychophys- ical 2AFC SVV task at roll tilt angles of 0 degrees, 16 degrees and 4 degrees CW and CCW. Participants were tilted to 4 degrees under different instruction conditions: in one condition, participants received veridical instructions as to their tilt angle, whereas in another condition, participants received the mis- leading instruction that their body position was perfectly upright. Our results indicate systematic differences between the instruction conditions at 4 degrees CW and CCW. Participants did not simply use an ego-centric reference frame in the misleading condition; instead, participants’ estimates of the SVV seem to lie between their head’s Z-axis and the estimate of the SVV as measured in the veridical condition. All participants displayed A-effects at roll tilt an- gles of 16 degrees CW and CCW. We discuss our results in the context of the Bayesian model by De Vrijer et al. (2009), and claim that this pattern of re- sults is consistent with a manipulation of precision of a prior distribution over body-in-space orientations. Furthermore, we introduce a Bayesian Generalized Linear Model for estimating parameters of participants’ psychometric function, which allows us to jointly estimate group level and individual level parameters under all experimental conditions simultaneously, rather than relying on the traditional two-step approach to obtaining group level parameter estimates.

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Mathematical models of disease progression predict disease outcomes and are useful epidemiological tools for planners and evaluators of health interventions. The R package gems is a tool that simulates disease progression in patients and predicts the effect of different interventions on patient outcome. Disease progression is represented by a series of events (e.g., diagnosis, treatment and death), displayed in a directed acyclic graph. The vertices correspond to disease states and the directed edges represent events. The package gems allows simulations based on a generalized multistate model that can be described by a directed acyclic graph with continuous transition-specific hazard functions. The user can specify an arbitrary hazard function and its parameters. The model includes parameter uncertainty, does not need to be a Markov model, and may take the history of previous events into account. Applications are not limited to the medical field and extend to other areas where multistate simulation is of interest. We provide a technical explanation of the multistate models used by gems, explain the functions of gems and their arguments, and show a sample application.

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INTRODUCTION Left ventricular thrombus (LVT) formation may worsen the post-infarct outcome as a result of thromboembolic events. It also complicates the use of modern antiplatelet regimens, which are not compatible with long-term oral anticoagulation. The knowledge of the incidence of LVT may therefore be of importance to guide antiplatelet and antithrombotic therapy after acute myocardial infarction (AMI). METHODS In 177 patients with large, mainly anterior AMI, standard cardiac magnetic resonance imaging (CMR) including cine and late gadolinium enhancement (LGE) imaging was performed shortly after AMI as per protocol. CMR images were analysed at an independent core laboratory blinded to the clinical data. Transthoracic echocardiography (TTE) was not mandatory for the trial, but was performed in 64% of the cases following standard of care. In a logistic model, 3 out of 61 parameters were used in a multivariable model to predict LVT. RESULTS LVT was detected by use of CMR in 6.2% (95% confidence interval [CI] 3.1%-10.8%). LGE sequences were best to detect LVT, which may be missed in cine sequences. We identified body mass index (odds ratio 1.18; p = 0.01), baseline platelet count (odds ratio 1.01, p = 0.01) and infarct size as assessed by use of CMR (odds ratio 1.03, p = 0.02) as best predictors for LVT. The agreement between TTE and CMR for the detection of LVT is substantial (kappa = 0.70). DISCUSSION In the current analysis, the incidence of LVT shortly after AMI is relatively low, even in a patient population at high risk. An optimal modality for LVT detection is LGE-CMR but TTE has an acceptable accuracy when LGE-CMR is not available.

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BACKGROUND Viral load and CD4% are often not available in resource-limited settings for monitoring children's responses to antiretroviral therapy (ART). We aimed to construct normative curves for weight gain at 6, 12, 18, and 24 months following initiation of ART in children, and to assess the association between poor weight gain and subsequent responses to ART. DESIGN Analysis of data from HIV-infected children younger than 10 years old from African and Asian clinics participating in the International epidemiologic Databases to Evaluate AIDS. METHODS The generalized additive model for location, scale, and shape was used to construct normative percentile curves for weight gain at 6, 12, 18, and 24 months following ART initiation. Cox proportional models were used to assess the association between lower percentiles (< 50th) of weight gain distribution at the different time points and subsequent death, virological suppression, and virological failure. RESULTS Among 7173 children from five regions of the world, 45% were underweight at baseline. Weight gain below the 50th percentile at 6, 12, 18, and 24 months of ART was associated with increased risk of death, independent of baseline characteristics. Poor weight gain was not associated with increased hazards of virological suppression or virological failure. CONCLUSION Monitoring weight gain on ART using age-specific and sex-specific normative curves specifically developed for HIV-infected children on ART is a simple, rapid, sustainable tool that can aid in the identification of children who are at increased risk of death in the first year of ART.

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The main objective of this study was to develop and validate a computer-based statistical algorithm based on a multivariable logistic model that can be translated into a simple scoring system in order to ascertain stroke cases using hospital admission medical records data. This algorithm, the Risk Index Score (RISc), was developed using data collected prospectively by the Brain Attack Surveillance in Corpus Christ (BASIC) project. The validity of the RISc was evaluated by estimating the concordance of scoring system stroke ascertainment to stroke ascertainment accomplished by physician review of hospital admission records. The goal of this study was to develop a rapid, simple, efficient, and accurate method to ascertain the incidence of stroke from routine hospital admission hospital admission records for epidemiologic investigations. ^ The main objectives of this study were to develop and validate a computer-based statistical algorithm based on a multivariable logistic model that could be translated into a simple scoring system to ascertain stroke cases using hospital admission medical records data. (Abstract shortened by UMI.)^

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In this paper, we extend the debate concerning Credit Default Swap valuation to include time varying correlation and co-variances. Traditional multi-variate techniques treat the correlations between covariates as constant over time; however, this view is not supported by the data. Secondly, since financial data does not follow a normal distribution because of its heavy tails, modeling the data using a Generalized Linear model (GLM) incorporating copulas emerge as a more robust technique over traditional approaches. This paper also includes an empirical analysis of the regime switching dynamics of credit risk in the presence of liquidity by following the general practice of assuming that credit and market risk follow a Markov process. The study was based on Credit Default Swap data obtained from Bloomberg that spanned the period January 1st 2004 to August 08th 2006. The empirical examination of the regime switching tendencies provided quantitative support to the anecdotal view that liquidity decreases as credit quality deteriorates. The analysis also examined the joint probability distribution of the credit risk determinants across credit quality through the use of a copula function which disaggregates the behavior embedded in the marginal gamma distributions, so as to isolate the level of dependence which is captured in the copula function. The results suggest that the time varying joint correlation matrix performed far superior as compared to the constant correlation matrix; the centerpiece of linear regression models.

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The study objectives were to determine risk factors for preterm labor (PTL) in Colorado Springs, CO, with emphasis on altitude and psychosocial factors, and to develop a model that identifies women at high risk for PTL. Three hundred and thirty patients with PTL were matched to 460 control patients without PTL using insurance category as an indirect measure of social class. Data were gathered by patient interview and review of medical records. Seven risk groups were compared: (1) Altitude change and travel; (2) Psychosocial ((a) child, sexual, spouse, alcohol and drug abuse; (b) neuroses and psychoses; (c) serious accidents and injuries; (d) broken home (maternal parental separation); (e) assault (physical and sexual); and (f) stress (emotional, domestic, occupational, financial and general)); (3) demographic; (4) maternal physical condition; (5) Prenatal care; (6) Behavioral risks; and (7) Medical factors. Analysis was by logistic regression. Results demonstrated altitude change before or after conception and travel during pregnancy to be non-significant, even after adjustment for potential confounding variables. Five significant psychosocial risk factors were determined: Maternal sex abuse (p = 0.006), physical assault (p = 0.025), nervous breakdown (p = 0.011), past occupational injury (p = 0.016), and occupational stress (p = 0.028). Considering all seven risk groups in the logistic regression, we chose a logistic model with 11 risk factors. Two risk factors were psychosocial (maternal spouse abuse and past occupational injury), 1 was pertinent to maternal physical condition ($\le$130 lbs. pre-pregnancy weight), 1 to prenatal care ($\le$10 prenatal care visits), 2 pertinent to behavioral risks ($>$15 cigarettes per day and $\le$30 lbs. weight gain) and 5 medical factors (abnormal genital culture, previous PTB, primiparity, vaginal bleeding and vaginal discharge). We conclude that altitude change is not a risk factor for PTL and that selected psychosocial factors are significant risk factors for PTL. ^

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A case-control study has been conducted examining the relationship between preterm birth and occupational physical activity among U.S. Army enlisted gravidas from 1981 to 1984. The study includes 604 cases (37 or less weeks gestation) and 6,070 controls (greater than 37 weeks gestation) treated at U.S. Army medical treatment facilities worldwide. Occupational physical activity was measured using existing physical demand ratings of military occupational specialties.^ A statistically significant trend of preterm birth with increasing physical demand level was found (p = 0.0056). The relative risk point estimates for the two highest physical demand categories were statistically significant, RR's = 1.69 (p = 0.02) and 1.75 (p = 0.01), respectively. Six of eleven additional variables were also statistically significant predictors of preterm birth: age (less than 20), race (non-white), marital status (single, never married), paygrade (E1 - E3), length of military service (less than 2 years), and aptitude score (less than 100).^ Multivariate analyses using the logistic model resulted in three statistically significant risk factors for preterm birth: occupational physical demand; lower paygrade; and non-white race. Controlling for race and paygrade, the two highest physical demand categories were again statistically significant with relative risk point estimates of 1.56 and 1.70, respectively. The population attributable risk for military occupational physical demand was 26%, adjusted for paygrade and race; 17.5% of the preterm births were attributable to the two highest physical demand categories. ^

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The relationship between serum cholesterol and cancer incidence was investigated in the population of the Hypertension Detection and Follow-up Program (HDFP). The HDFP was a multi-center trial designed to test the effectiveness of a stepped program of medication in reducing mortality associated with hypertension. Over 10,000 participants, ages 30-69, were followed with clinic and home visits for a minimum of five years. Cancer incidence was ascertained from existing study documents, which included hospitalization records, autopsy reports and death certificates. During the five years of follow-up, 286 new cancer cases were documented. The distribution of sites and total number of cases were similar to those predicted using rates from the Third National Cancer Survey. A non-fasting baseline serum cholesterol level was available for most participants. Age, sex, and race specific five-year cancer incidence rates were computed for each cholesterol quartile. Rates were also computed by smoking status, education status, and percent ideal weight quartiles. In addition, these and other factors were investigated with the use of the multiple logistic model.^ For all cancers combined, a significant inverse relationship existed between baseline serum cholesterol levels and cancer incidence. Previously documented associations between smoking, education and cancer were also demonstrated but did not account for the relationship between serum cholesterol and cancer. The relationship was more evident in males than females but this was felt to represent the different distribution of occurrence of specific cancer sites in the two sexes. The inverse relationship existed for all specific sites investigated (except breast) although a level of statistical significance was reached only for prostate carcinoma. Analyses after exclusion of cases diagnosed during the first two years of follow-up still yielded an inverse relationship. Life table analysis indicated that competing risks during the period of follow-up did not account for the existence of an inverse relationship. It is concluded that a weak inverse relationship does exist between serum cholesterol for many but not all cancer sites. This relationship is not due to confounding by other known cancer risk factors, competing risks or persons entering the study with undiagnosed cancer. Not enough information is available at the present time to determine whether this relationship is causal and further research is suggested. ^

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Background Past and recent evidence shows that radionuclides in drinking water may be a public health concern. Developmental thresholds for birth defects with respect to chronic low level domestic radiation exposures, such as through drinking water, have not been definitely recognized, and there is a strong need to address this deficiency in information. In this study we examined the geographic distribution of orofacial cleft birth defects in and around uranium mining district Counties in South Texas (Atascosa, Bee, Brooks, Calhoun, Duval, Goliad, Hidalgo, Jim Hogg, Jim Wells, Karnes, Kleberg, Live Oak, McMullen, Nueces, San Patricio, Refugio, Starr, Victoria, Webb, and Zavala), from 1999 to 2007. The probable association of cleft birth defect rates by ZIP codes classified according to uranium and radium concentrations in drinking water supplies was evaluated. Similar associations between orofacial cleft birth defects and radium/radon in drinking water were reported earlier by Cech and co-investigators in another of the Gulf Coast region (Harris County, Texas).50, 55 Since substantial uranium mining activity existed and still exists in South Texas, contamination of drinking water sources with radiation and its relation to birth defects is a ground for concern. ^ Methods Residential addresses of orofacial cleft birth defect cases, as well as live births within the twenty Counties during 1999-2007 were geocoded and mapped. Prevalence rates were calculated by ZIP codes and were mapped accordingly. Locations of drinking water supplies were also geocoded and mapped. ZIP codes were stratified as having high combined uranium (≥30μg/L) vs. low combined uranium (<30μg/L). Likewise, ZIP codes having the uranium isotope, Ra-226 in drinking water, were also stratified as having elevated radium (≥3 pCi/L) vs. low radium (<3 pCi/L). A linear regression was performed using STATA® generalized linear model (GLM) program to evaluate the probable association between cleft birth defect rates by ZIP codes and concentration of uranium and radium via domestic water supply. These rates were further adjusted for potentially confounding variables such as maternal age, education, occupation, and ethnicity. ^ Results This study showed higher rates of cleft births in ZIP codes classified as having high combined uranium versus ZIP codes having low combined uranium. The model was further improved by adding radium stratified as explained above. Adjustment for maternal age and ethnicity did not substantially affect the statistical significance of uranium or radium concentrations in household water supplies. ^ Conclusion Although this study lacks individual exposure levels, the findings suggest a significant association between elevated uranium and radium concentrations in tap water and high orofacial birth defect rates by ZIP codes. Future case-control studies that can measure individual exposure levels and adjust for contending risk factors could result in a better understanding of the exposure-disease association.^

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My dissertation focuses mainly on Bayesian adaptive designs for phase I and phase II clinical trials. It includes three specific topics: (1) proposing a novel two-dimensional dose-finding algorithm for biological agents, (2) developing Bayesian adaptive screening designs to provide more efficient and ethical clinical trials, and (3) incorporating missing late-onset responses to make an early stopping decision. Treating patients with novel biological agents is becoming a leading trend in oncology. Unlike cytotoxic agents, for which toxicity and efficacy monotonically increase with dose, biological agents may exhibit non-monotonic patterns in their dose-response relationships. Using a trial with two biological agents as an example, we propose a phase I/II trial design to identify the biologically optimal dose combination (BODC), which is defined as the dose combination of the two agents with the highest efficacy and tolerable toxicity. A change-point model is used to reflect the fact that the dose-toxicity surface of the combinational agents may plateau at higher dose levels, and a flexible logistic model is proposed to accommodate the possible non-monotonic pattern for the dose-efficacy relationship. During the trial, we continuously update the posterior estimates of toxicity and efficacy and assign patients to the most appropriate dose combination. We propose a novel dose-finding algorithm to encourage sufficient exploration of untried dose combinations in the two-dimensional space. Extensive simulation studies show that the proposed design has desirable operating characteristics in identifying the BODC under various patterns of dose-toxicity and dose-efficacy relationships. Trials of combination therapies for the treatment of cancer are playing an increasingly important role in the battle against this disease. To more efficiently handle the large number of combination therapies that must be tested, we propose a novel Bayesian phase II adaptive screening design to simultaneously select among possible treatment combinations involving multiple agents. Our design is based on formulating the selection procedure as a Bayesian hypothesis testing problem in which the superiority of each treatment combination is equated to a single hypothesis. During the trial conduct, we use the current values of the posterior probabilities of all hypotheses to adaptively allocate patients to treatment combinations. Simulation studies show that the proposed design substantially outperforms the conventional multi-arm balanced factorial trial design. The proposed design yields a significantly higher probability for selecting the best treatment while at the same time allocating substantially more patients to efficacious treatments. The proposed design is most appropriate for the trials combining multiple agents and screening out the efficacious combination to be further investigated. The proposed Bayesian adaptive phase II screening design substantially outperformed the conventional complete factorial design. Our design allocates more patients to better treatments while at the same time providing higher power to identify the best treatment at the end of the trial. Phase II trial studies usually are single-arm trials which are conducted to test the efficacy of experimental agents and decide whether agents are promising to be sent to phase III trials. Interim monitoring is employed to stop the trial early for futility to avoid assigning unacceptable number of patients to inferior treatments. We propose a Bayesian single-arm phase II design with continuous monitoring for estimating the response rate of the experimental drug. To address the issue of late-onset responses, we use a piece-wise exponential model to estimate the hazard function of time to response data and handle the missing responses using the multiple imputation approach. We evaluate the operating characteristics of the proposed method through extensive simulation studies. We show that the proposed method reduces the total length of the trial duration and yields desirable operating characteristics for different physician-specified lower bounds of response rate with different true response rates.

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Background. Kidney disease is a growing public health phenomenon in the U.S. and in the world. Downstream interventions, dialysis and renal transplants covered by Medicare's renal disease entitlement policy in those who are 65 years and over have been expensive treatments that have been not foolproof. The shortage of kidney donors in the U.S. has grown in the last two decades. Therefore study of upstream events in kidney disease development and progression is justified to prevent the rising prevalence of kidney disease. Previous studies have documented the biological route by which obesity can progress and accelerate kidney disease, but health services literature on quantifying the effects of overweight and obesity on economic outcomes in the context of renal disease were lacking. Objectives . The specific aims of this study were (1) to determine the likelihood of overweight and obesity in renal disease and in three specific adult renal disease sub-populations, hypertensive, diabetic and both hypertensive and diabetic (2) to determine the incremental health service use and spending in overweight and obese renal disease populations and (3) to determine who financed the cost of healthcare for renal disease in overweight and obese adult populations less than 65 years of age. Methods. This study was a retrospective cross-sectional study of renal disease cases pooled for years 2002 to 2009 from the Medical Expenditure Panel Survey. The likelihood of overweight and obesity was estimated using chi-square test. Negative binomial regression and generalized gamma model with log link were used to estimate healthcare utilization and healthcare expenditures for six health event categories. Payments by self/family, public and private insurance were described for overweight and obese kidney disease sub-populations. Results. The likelihood of overweight and obesity was 0.29 and 0.46 among renal disease and obesity was common in hypertensive and diabetic renal disease population. Among obese renal disease population, negative binomial regression estimates of healthcare utilization per person per year as compared to normal weight renal disease persons were significant for office-based provider visits and agency home health visits respectively (p=0.001; p=0.005). Among overweight kidney disease population health service use was significant for inpatient hospital discharges (p=0.027). Over years 2002 to 2009, overweight and obese renal disease sub-populations had 53% and 63% higher inpatient facility and doctor expenditures as compared to normal weight renal disease population and these result were statistically significant (p=0.007; p=0.026). Overweigh renal disease population had significant total expenses per person per year for office-based and outpatient associated care. Overweight and obese renal disease persons paid less from out-of-pocket overall compared to normal weight renal disease population. Medicare and Medicaid had the highest mean annual payments for obese renal disease persons, while mean annual payments per year were highest for private insurance among normal weight renal disease population. Conclusion. Overweight and obesity were common in those with acute and chronic kidney disease and resulted in higher healthcare spending and increased utilization of office-based providers, hospital inpatient department and agency home healthcare. Healthcare for overweight and obese renal disease persons younger than 65 years of age was financed more by private and public insurance and less by out of pocket payments. With the increasing epidemic of obesity in the U.S. and the aging of the baby boomer population, the findings of the present study have implications for public health and for greater dissemination of healthcare resources to prevent, manage and delay the onset of overweight and obesity that can progress and accelerate the course of the kidney disease.^