Quantifying the number of US men with erectile dysfunction who are potential candidates for penile prosthesis implantation

Introduction

Penile prosthesis implantation (PPI) is a treatment option recommended in clinical guidelines for erectile dysfunction (ED). However, a limited number of urologists perform PPI procedures in the United States.

Aim

To quantify the number of insured men with ED in the United States and project the number of potential candidates for PPI in 2022.

Methods

An Excel-based disease impact model was constructed using a top-down estimation approach. The starting US male population consisted of adult men from 2022 US Census data after exclusion of age-specific mortality rates from the National Vital Statistics Reports. Men with health insurance were included in the model based on insurance status data from the US Census database. ED prevalence and ED treatment rates were obtained from administrative claims data analyses-the Merative MarketScan Commercial Database (18-64 years) and the 5% Medicare Standard Analytical Files (≥65 years)-and literature-based estimates of patient-reported ED prevalence.

Outcomes

The number of men with ED in the United States and the number of potential candidates for PPI were estimated.

Results

By utilizing ED prevalence based on administrative claims, an estimated 8.3% of insured men (10,302,540 estimated men [8,882,548 aged 18-64 years and 1,419,992 aged ≥65 years]) had a diagnosis of ED and sought ED care, out of 124,318,519 eligible US men aged ≥18 years in 2022. An estimated 17.1% of men with an ED diagnosis claim could benefit from PPI in 2022 (1,759,248 men aged ≥18 years). Patient self-reported ED prevalence across all ages ranged from 5.1% to 70.2%. Scenario analyses applying the patient self-reported ED prevalence range revealed the number of men in the United States who could benefit from PPI could have been higher than 1.7 million if their ED symptoms were diagnosed by health care providers.

Clinical Implications

Most men with ED in the United States are undertreated, and many could benefit from PPI.

Strengths and Limitations

This analysis is a US population-level estimation. However, given this study utilized a variety of assumptions, the results may vary if different model assumptions are applied.

Conclusions

This disease impact model estimated that approximately 10.3 million men were diagnosed with ED by their health care providers and sought ED care in the United States in 2022. Of those, 1.7 million men could be PPI candidates and benefit from the treatment option.

Relationship between Urban Environmental Components and Dengue Prevalence in Dhaka City-An Approach of Spatial Analysis of Satellite Remote Sensing, Hydro-Climatic, and Census Dengue Data

Dengue fever is a tropical viral disease mostly spread by the Aedes aegypti mosquito across the globe. Each year, millions of people have dengue fever, and many die as a result. Since 2002, the severity of dengue in Bangladesh has increased, and in 2019, it reached its worst level ever. This research used satellite imagery to determine the spatial relationship between urban environmental components (UEC) and dengue incidence in Dhaka in 2019. Land surface temperature (LST), urban heat-island (UHI), land-use-land-cover (LULC), population census, and dengue patient data were evaluated. On the other hand, the temporal association between dengue and 2019 UEC data for Dhaka city, such as precipitation, relative humidity, and temperature, were explored. The calculation indicates that the LST in the research region varies between 21.59 and 33.33 degrees Celsius. Multiple UHIs are present within the city, with LST values ranging from 27 to 32 degrees Celsius. In 2019, these UHIs had a higher incidence of dengue. NDVI values between 0.18 and 1 indicate the presence of vegetation and plants, and the NDWI identifies waterbodies with values between 0 and 1. About 2.51%, 2.66%, 12.81%, and 82% of the city is comprised of water, bare ground, vegetation, and settlement, respectively. The kernel density estimate of dengue data reveals that the majority of dengue cases were concentrated in the city's north edge, south, north-west, and center. The dengue risk map was created by combining all of these spatial outputs (LST, UHI, LULC, population density, and dengue data) and revealed that UHIs of Dhaka are places with high ground temperature and lesser vegetation, waterbodies, and dense urban characteristics, with the highest incidence of dengue. The average yearly temperature in 2019 was 25.26 degrees Celsius. May was the warmest month, with an average monthly temperature of 28.83 degrees Celsius. The monsoon and post-monsoon seasons (middle of March to middle of September) of 2019 sustained higher ambient temperatures (>26 °C), greater relative humidity (>80%), and at least 150 mm of precipitation. The study reveals that dengue transmits faster under climatological circumstances characterized by higher temperatures, relative humidity, and precipitation.

Prevalence estimation of intellectual disability using national administrative and household survey data: The importance of survey question specificity

Background

Variability in prevalence estimation of intellectual disability has been attributed to heterogeneity in study settings, methodologies, and intellectual disability case definitions. Among studies based on national household survey data specifically, variability in prevalence estimation has partly been attributed to the level of specificity of the survey questions employed to determine the presence of intellectual disability.

Specific aims & method

Using standardised difference scoring, and ‘intellectual disability’ survey data from the 2007 Northern Ireland Survey on Activity Limitation and Disability (NISALD) (N=23,689) and the 2011 Northern Ireland Census (N=1,770,217) the following study had two aims. First, we aimed to demonstrate the effects of survey question specificity on intellectual disability prevalence estimation. Second, we aimed to produce reliable estimates of the geographic variation of intellectual disability within private households in Northern Ireland while also assessing the socio-demographic, health-related and disability characteristics of this population.

Findings

Prevalence estimates generated using the more crudely classified intellectual disability Census data indicated a prevalence of 2% for the overall population, 3.8% for children aged between 0 and 15 years, and 1.5% for citizens aged 16 years or older. Intellectual disability prevalence estimates generated using the more explicitly defined 2007 NISALD data indicated a population prevalence of 0.5% for the overall population, 1.3% for children aged between 0 and 15 years, and 0.3% for citizens aged 16 years or older. The NISALD estimates were consistent with most recent international meta-analysis prevalence estimates. According to the NISALD data, the majority of those with an intellectual disability were male, lived outside Belfast, and experienced severe intellectual disability, with multiple comorbid health conditions.

Discussion

The current findings highlight the importance of survey question specificity in the estimation of intellectual disability prevalence and provide reliable prevalence estimates of intellectual disability in Northern Ireland. The findings also demonstrate the utility of administrative data for detecting and understanding intellectual disability, and inform recommendations on how to maximise use of future intellectual disability Census data

Influence of Family and Community Socioeconomic Status on the Risk of Adolescent Drug Use

Background: Adolescent drug use increases the risk of mental, physical and social problems later in life and so it is important to understand its complex etiology that likely includes socioeconomic status (SES). We undertook the present analysis using data from a population-based retrospective cohort study to examine the influence of family and community SES in relation to adolescent drug use. We hypothesized that lower levels of community and parental SES would increase the risk of use and that there would be stronger associations for the more proximate family-level factors. Methods: We used self-administered questionnaires (N=1,402) to obtain information on use of marijuana, inhalants, heroin, cocaine/crack, psychedelics/hallucinogens, Ritalin without a prescription, and club drugs during adolescence. Family SES was gathered from birth certificate data on maternal educational level and paternal occupation. Community SES characteristics at birth, age 10 and age 18 were obtained from the US Census Bureau. Results: An increased risk of adolescent drug use was associated with lower maternal education, non-white collar occupations among fathers, and lower community median income, and poverty and unemployment levels at age 18. The strongest associations were seen for the use of multiple drugs (Risk Ratio (RR): 1.7, 95% CI: 1.4-2.2), inhalants (RR: 2.5, 95% CI: 1.5-2.2), crack/cocaine (RR: 2.8, 95% CI: 1.7-4.5), psychedelics/hallucinogens (RR: 1.8, 95% CI: 1.4-2.4), and club/designer drugs (RR: 1.8, 95% CI: 1.2-2.7) among adolescents whose mothers had only a high school education. Conclusions: These results suggest that use of certain drugs during adolescence is associated with both family and community SES measures. However, maternal education appears to have the greatest influence on use, suggesting that a multi-level approach that engages mothers is needed to prevent adolescent drug use.

Large herbivore conservation in a changing world: Surface water provision and adaptability allow wildebeest to persist after collapse of long-range movements

Large herbivores, particularly wide-ranging species, are extensively impacted by land use transformation and other anthropogenic barriers to movement. The adaptability of a species is, therefore, crucial to determining whether populations can persist in ever smaller subsets of their historical home ranges. Access to water, by drinking or from forage moisture, is an essential requirement, and surface water provision is thus a long-established, although controversial, conservation practice. In the arid Kgalagadi Transfrontier Park (KTP), South Africa, surface water provision in the 1930s facilitated the establishment of a sedentary wildebeest (Connochaetes taurinus) population in a region historically accessed only in the wet season, via now collapsed long-distance movements. Here, we investigate the behaviour and diet of this wildebeest population, and how these relate to water in the landscape, to better understand the process of transitioning from a mobile to sedentary population. Data from 26 monthly surveys reveal that wildebeest distributions are shaped by water availability and salinity, shade, forage, season and possibly predator detectability. Areas with saline or no water are used predominantly in the wet season when forage moisture is high. Wet season movements beyond the study area mean the timing of wildebeest grazing in these regions matches historical timing. Grass utilization field data suggest that the KTP grazer population experiences forage deficits during the dry season, when ~80% of grass tufts are grazed and C:N and crude protein levels decline. Nonetheless, dung isotope data show that wildebeest meet their crude protein intake requirements during the dry season, likely by consuming unprecedentedly high levels of browse (>33%). While restoring the full historical range and movements of most large herbivore populations is not possible, these findings highlight that understanding the behavioural and dietary adaptability of a species can augment 'next best' efforts to conserve viable populations while home ranges contract.

Quantifying calf mortality on dairy farms: Challenges and solutions

In the Netherlands, the mortality rate of ear-tagged calves <1 yr is one of the indicators that is continuously monitored in census data and is defined as the number of deceased calves relative to the number of calf-days-at-risk. In 2017, yearly calf mortality rates were published in the lay press and resulted in discussions about the calculation of this parameter among stakeholders because the same parameter appeared to be calculated in many different ways by different organizations. These diverse definitions of calf mortality answered different aims such as early detection of deviations, monitoring trends, or providing insight into herd-specific results, but were difficult to understand by stakeholders. The aim of this study was to evaluate several definitions of calf mortality for scientific validity, usefulness for policymakers, and comprehensibility by farmers. Based on expert consultations, 10 definitions for calf mortality were evaluated that assessed different age categories, time periods, and denominators. Differences in definitions appeared to have a large effect on the magnitude of mortality. For example, with the original mortality parameter, the mortality rate was 16.5% per year. When the first year of life was subdivided into 3 age categories, the mortality rate was 3.3, 4.5, and 3.1% for postnatal calves (≤14 d), preweaned calves (15-55 d), and weaned calves (56 d-1 yr), respectively. Although it was logical that these mortality rates were lower than the original, the sum of the 3 separate mortality rates was also lower than the original mortality rate. The reason was that the number of calves present in a herd and the risk of mortality are not randomly distributed over a calf's first year of life and the conditional nature of mortality rates when calculated for different age categories. Ultimately, 4 parameters to monitor calf mortality in Dutch dairy herds were chosen based on scientific value, usefulness for monitoring of trends, and comprehensibility by farmers: perinatal calf mortality risk (i.e., mortality before, during, or shortly after the moment of birth up to the moment of ear-tagging), postnatal calf mortality risk (≤14 d), preweaned calf mortality rate (15-55 d), and weaned calf mortality rate (56 d-1 yr). Slight differences in definitions of parameters can have a major effect on results, and many factors have to be taken into account when defining an important health indicator such as mortality. Our evaluation resulted in a more thorough understanding of the definitions of the selected parameters and agreement by the stakeholders to use these key indicators to monitor calf mortality.

Brazilian chronic dialysis survey 2017

INTRODUCTION

Having national data on chronic dialysis is essential in treatment planning.

OBJECTIVE

To present data of the survey from the Brazilian Society of Nephrology on patients with chronic kidney disease on dialysis in July 2017.

METHODS

Data was collected from dialysis units in Brazil. The data collection was done using a questionnaire completed online by the dialysis units.

RESULTS

Two hundred and ninety-one centers (38.4%) answered the questionnaire. In July 2017, the estimated total number of dialysis patients was 126,583. National estimates of prevalence and incidence rates of dialysis patients per million population (pmp) were 610 (range: 473 in the North region and 710 in the Midwest) and 194, respectively. The incidence rate of new dialysis patients with diagnosis of diabetic nephropathy was 77 pmp. The annual gross mortality rate was 19.9%. Of the prevalent patients, 93.1% were on hemodialysis and 6.9% on peritoneal dialysis, with 31,226 (24%) on the waiting list for renal transplantation. Venous catheter was used as access in 22.6% of patients on hemodialysis. The prevalence rate of positive serology for hepatitis C continued with a tendency to decrease (3.3%).

CONCLUSION

The absolute number of patients and rates of incidence and prevalence on dialysis continued to increase; the mortality rate tended to rise. There were obvious regional and state discrepancies in these rates.

Enhancing Areal Interpolation Frameworks through Dasymetric Refinement to Create Consistent Population Estimates across Censuses

To assess micro-scale population dynamics effectively, demographic variables should be available over temporally consistent small area units. However, fine-resolution census boundaries often change between survey years. This research advances areal interpolation methods with dasymetric refinement to create accurate consistent population estimates in 1990 and 2000 (source zones) within tract boundaries of the 2010 census (target zones) for five demographically distinct counties in the U.S. Three levels of dasymetric refinement of source and target zones are evaluated. First, residential parcels are used as a binary ancillary variable prior to regular areal interpolation methods. Second, Expectation Maximization (EM) and its data-extended version leverage housing types of residential parcels as a related ancillary variable. Finally, a third refinement strategy to mitigate the overestimation effect of large residential parcels in rural areas uses road buffers and developed land cover classes. Results suggest the effectiveness of all three levels of dasymetric refinement in reducing estimation errors. They provide a first insight into the potential accuracy improvement achievable in varying geographic and demographic settings but also through the combination of different refinement strategies in parts of a study area. Such improved consistent population estimates are the basis for advanced spatio-temporal demographic research.

Validating Population Estimates for Harmonized Census Tract Data, 2000-2010

Social scientists regularly rely on population estimates when studying change in small areas over time. Census tract data in the United States are a prime example, since there are substantial shifts in tract boundaries from decade to decade. This study compares alternative estimates of the 2000 population living within 2010 tract boundaries to the Census Bureau's own re-tabulation. All methods of estimation are subject to error; this is the first study to directly quantify the error in alternative interpolation methods for U.S. census tracts. A simple areal weighting method closely approximates the estimates provided by one standard source (the Neighborhood Change Data Base or NCDB), with some improvement provided by considering only area not covered by water. More information is used by the Longitudinal Tract Data Base (LTDB), which relies on a combination of areal and population interpolation as well as ancillary data about water-covered areas. Another set of estimates provided by NHGIS uses data about land cover in 2001 and the current road network and distribution of population and housing units at the block level. Areal weighting alone results in a large error in a substantial share of tracts that were divided in complex ways. The LTDB and NHGIS perform much better in all situations, but are subject to some error when boundaries of both tracts and their component blocks are redrawn. Users of harmonized tract data should be watchful for potential problems in either of these data sources.

Housing conditions of home-based care patients in Botswana and the implications for HIV care

People living with HIV or with a terminal disease face frequent health risks due to opportunistic infections which affect their way of life and dramatically increase their risk of death. Increasingly, terminally ill patients in Botswana are cared for at home, hence the need to understand their housing conditions. Despite a high volume of HIV-related studies undertaken in Botswana, little research has examined the relationship between patients' housing conditions and quality of care at home. Using existing government data from the Botswana 2001 Population and Housing Census, we investigated the housing situation for the households in the national home-based care (HBC) programme. Data were available for 8 872 households having residents enrolled in the programme. The findings indicate that the majority of patients under HBC are faced with housing-related features that can affect their quality of care and chances of recovery. The largest proportion of households had six or more individuals sharing one or two rooms, which raises health concerns for the spread of communicable diseases. In rural areas, few of the HBC households had indoor piped water, proper waste disposal or flush toilets. The lack of basic amenities such as these creates problems for patients as well as for caregivers. We advocate for policy that will address and cater to housing as part of a comprehensive and effective HBC programme. Housing determines where, how and when homecare is provided for sick individuals; therefore, achieving healthy living environments and housing assistance for HBC patients must be addressed by the government. It is recommended that an evaluation of a patient's home should be a first step in their enrolment in the HBC programme. Thereafter, HIV-infected or affected household members should be advised and assisted to make the necessary housing changes to maintain quality of life or accelerate the homecare patient's recovery.

Harmonizing Disparate Data across Time and Place: The Integrated Spatio-Temporal Aggregate Data Series

In this article, the authors describe a new data infrastructure project being developed at the Minnesota Population Center. The Integrated Spatio-Temporal Aggregate Data Series (ISTADS) will make it easier for researchers to use publicly available aggregate data for the United States over a time span that covers virtually the entire life of the nation: 1790-2012. In addition to facilitating access and ease of use, ISTADS will facilitate the use of these various data sets in mapping and spatial analysis.

Big Data: Large-Scale Historical Infrastructure from the Minnesota Population Center

The Minnesota Population Center (MPC) provides aggregate data and microdata that have been integrated and harmonized to maximize crosstemporal and cross-spatial comparability. All MPC data products are distributed free of charge through an interactive Web interface that enables users to limit the data and metadata being analyzed to samples and variables of interest to their research. In this article, the authors describe the integrated databases available from the MPC, report on recent additions and enhancements to these data sets, and summarize new online tools and resources that help users to analyze the data over time. They conclude with a description of the MPC's newest and largest infrastructure project to date: a global population and environment data network.

Community characteristics associated with HIV risk among injection drug users in the San Francisco Bay Area: a multilevel analysis

Community characteristics have been associated with racial and ethnic health disparities for a wide range of ailments and conditions. Previous research has found that rates of AIDS cases among injection drug users (IDUs) vary by community characteristics. However, few studies have examined whether community characteristics are associated with HIV risk behaviors among IDUs. To address this gap in the literature, we examined the associations between census-tract-level community characteristics and injection-related and sex-related HIV risk behaviors among IDUs in the San Francisco Bay Area. Individual HIV risk behaviors were collected from 4,956 IDUs between 1998 and 2002. Using 2000 US census data, we constructed four census-level community measures: percent African American, percent male unemployment, percent of households that receive public assistance, and median household income. All community variables were measured continuously. Multilevel modeling was used to determine if community characteristics were associated with recent (in the last 6 months) receptive and distributive syringe sharing, multiple sex partners, and unprotected sex risk while controlling for potential individual-level confounders. In bivariate analysis, most of the census-tract-level community characteristics were significantly associated with injection-related HIV risk, while no community characteristics were associated with sex-related risk. However, results from multivariate multilevel models indicate that only percent African American in a census tract was associated with receptive [adjusted odds ratio (AOR) = 0.93; 95% confidence interval (CI) = 0.89, 0.99] and distributive syringe sharing (AOR = 0.94; 95% CI = 0.92, 0.99), net of individual-level characteristics. Accounting for individual-level factors in the multivariate model in the sex-related risk models revealed a significant inverse relationship between percent African American and propensity to engage in unprotected sex (AOR = 0.95; 95% CI = 0.92, 0.99); community-level characteristics remained unassociated with multiple sex partners. In this exploratory analysis, percent African American in a census tract was inversely associated with injection-related risk. The census-tract-level community characteristics we examined seem to exert little influence on individual risk among long-term chronic IDUs. More research is needed examining the influence of other community characteristics that were unmeasured in this paper but might be related to sex and drug risk among IDUs such as shooting galleries, crack houses, drug markets, and availability of preventive HIV services.