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Preliminary evidence suggests that neighborhood environments, such as socioeconomic disadvantage, pedestrian and physical activity infrastructure, and availability of neighborhood destinations (e.g., parks), may be associated with late-life cognitive functioning and risk of Alzheimer's disease and related disorders (ADRD). The supposition is that these neighborhood characteristics are associated with factors such as mental health, environmental exposures, health behaviors, and social determinants of health that in turn promote or diminish cognitive reserve and resilience in later life. However, observed associations may be biased by self-selection or reverse causation, such as when individuals with better cognition move to denser neighborhoods because they prefer many destinations within walking distance of home, or when individuals with deteriorating health choose residences offering health services in neighborhoods in rural or suburban areas (e.g., assisted living). Research on neighborhood environments and ADRD has typically focused on late-life brain health outcomes, which makes it difficult to disentangle true associations from associations that result from reverse causality. In this paper, we review study designs and methods to help reduce bias due to reverse causality and self-selection, while drawing attention to the unique aspects of these approaches when conducting research on neighborhoods and brain aging.

This paper uses data from a population-based case control study of daily activities and assault injury to examine residence-based versus actual path-based approaches to measuring environmental exposures that pose risks for violence among adolescents. Defining environmental exposures based on participant home address resulted in significant misclassification compared to gold standard daily travel path measures. Dividing participant daily travel paths into origin-destination segments, we explore a method for defining spatial counterfactuals by comparing actual trip path exposures to shortest potential trip path exposures. Spatial methods explored herein can be utilized in future research to more accurately quantify environmental exposures and associations with health outcomes. [ABSTRACT FROM AUTHOR]

Bronchial provocation tests using pharmacological agents such as methacholine or histamine are used in epidemiological studies to identify asthma despite recognition of limitations in specificity, positive predictive value and availability of reagents. Hypertonic saline (4.5%) bronchial challenge (HSBC), although less sensitive than pharmacological challenges, is reportedly highly specific in diagnosing current asthma. Added advantages are that reagents are cheap, stable and recognized by participants. Thus, HSBC may offer benefits over pharmacological tests in epidemiological surveys. This paper reports on the second field survey using the test, a study of 99 adults from the timber industry in Western Australia. The test is described and critically appraised as a practical epidemiological tool for assessing asthma prevalence. At a cutoff point of 20% FEV1 fall, HSBC was positive in 8% of subjects, appeared specific for asthma, was safe, well-accepted and easy to use in the field. [ABSTRACT FROM PUBLISHER]

Background: The paper is concerned with the use of epidemiological methods to measure the rates at which different strata of a defined population participate in community health promotion projects. The specific aim was to estimate the incidence rates of participation in projects sponsored by the Western Australian Health Promotion Foundation (Healthway), separately for sociodemographic and health-related behavioural subgroups.Methods: Data were drawn from Healthway sponsorship projects in 1992. Each sport, arts and racing project was associated with promotion of a health message and creation of a health promoting environment. The study used a two-stage sampling design. Thirteen of 57 large sponsorship projects and 30 of 129 small projects were selected. In the second stage, respondents were randomly surveyed from among project participants. A total of 4060 respondents aged > or = 10 years was sampled from the 43 selected projects. Population-based incident participants were estimated and were related to person-years at risk.Results: The total participation rate was 4.01 per person-year. The rate was very high at ages 10-14 years and thereafter declined with increasing age. Compared with the least socially disadvantaged 25% of population, the participation rate fell by around one-third in the medium and high disadvantage groups, but exceeded the baseline by a ratio of 1.85 (95% confidence interval: 1.57-2.18) in the most disadvantaged 10% of population. The effect was most pronounced at ages 10-19 years. Participation was higher in those who smoked, drank alcohol unsafely, reported sunburn and reported low consumption of fruit and vegetables. However, participation was reduced in people who were sedentary.Conclusions: Epidemiological methods can be used to evaluate the distribution of participation of a population in community health promotion projects. The Western Australian Health Promotion Foundation has been successful in reaching disadvantaged youth. [ABSTRACT FROM AUTHOR]

Many occupational diseases which are compensable are of interest in epidemiological studies. In addition, diseases of interest which are not compensable may be discovered during the evaluation of eligibility for compensation. Certain peculiarities of the group of workers who seek compensation (those who receive compensation and those who do not) may make the selection of an appropriate control group difficult. In two recent studies, problems associated with finding controls for cases with a compensable disease and a disease discovered during the evaluation of eligibility for compensation pointed out some of these potential biases. This paper describes the results obtained using different control groups for these studies, proposes reasons for differences in the results and suggests steps which can be taken to ensure the validity of a control group in such studies. [ABSTRACT FROM AUTHOR]

Background: During the last decades, sex and gender biases have been identified in various areas of biomedical and public health research, leading to compromised validity of research findings. As a response, methodological requirements were developed but these are rarely translated into research practice. The aim of this study is to provide good practice examples of sex/gender sensitive health research.Methods: We conducted a systematic search of research articles published in JECH between 2006 and 2014. An instrument was constructed to evaluate sex/gender sensitivity in four stages of the research process (background, study design, statistical analysis, discussion).Results: In total, 37 articles covering diverse topics were included. Thereof, 22 were evaluated as good practice example in at least one stage; two articles achieved highest ratings across all stages. Good examples of the background referred to available knowledge on sex/gender differences and sex/gender informed theoretical frameworks. Related to the study design, good examples calculated sample sizes to be able to detect sex/gender differences, selected sex/gender sensitive outcome/exposure indicators, or chose different cut-off values for male and female participants. Good examples of statistical analyses used interaction terms with sex/gender or different shapes of the estimated relationship for men and women. Examples of good discussions interpreted their findings related to social and biological explanatory models or questioned the statistical methods used to detect sex/gender differences.Conclusions: The identified good practice examples may inspire researchers to critically reflect on the relevance of sex/gender issues of their studies and help them to translate methodological recommendations of sex/gender sensitivity into research practice. [ABSTRACT FROM AUTHOR]

Introduction: Few studies account for prehospital deaths when estimating incidence and mortality rates of moderate and severe traumatic brain injury (msTBI). In a population-based study, covering both urban and rural areas, including also prehospital deaths, the aim was to estimate incidence and mortality rates of msTBI. Further, we studied the 30-day and 6-month case-fatality proportion of severe TBI in relation to age. Methods: All patients aged ≥17 years who sustained an msTBI in Central Norway were identified by three sources: (1) the regional trauma center, (2) the general hospitals, and (3) the Norwegian Cause of Death Registry. Incidence and mortality rates were standardized according to the World Health Organization's world standard population. Case-fatality proportions were calculated by the number of deaths from severe TBI at 30 days and 6 months, divided by all patients with severe TBI. Results: The overall incidence rates of moderate and severe TBI were 4.9 and 6.7 per 100,000 person-years, respectively, increasing from age 70 years. The overall mortality rate was 3.4 per 100,000 person-years, also increasing from age 70 years. Incidence and mortality rates were highest in men. The case-fatality proportion in people with severe TBI was 49% in people aged 60–69 years and 81% in people aged 70–79 years. Conclusion: The overall incidence and mortality rates for msTBI in Central Norway were low but increased from age 70 years, and among those ≥80 years of age with severe TBI, nearly all died. Overall estimates are strongly influenced by high incidence and mortality rates in the elderly, and studies should therefore report age-specific estimates, for better comparison of incidence and mortality rates. [ABSTRACT FROM AUTHOR]

Contact tracing, where exposed individuals are followed up to break ongoing transmission chains, is a key pillar of outbreak response for infectious disease outbreaks. Unfortunately, these systems are not fully effective, and infections can still go undetected as people may not remember all their contacts or contacts may not be traced successfully. A large proportion of undetected infections suggests poor contact tracing and surveillance systems, which could be a potential area of improvement for a disease response. In this paper, we present a method for estimating the proportion of infections that are not detected during an outbreak. Our method uses next generation matrices that are parameterized by linked contact tracing data and case line-lists. We validate the method using simulated data from an individual-based model and then investigate two case studies: the proportion of undetected infections in the SARS-CoV-2 outbreak in New Zealand during 2020 and the Ebola epidemic in Guinea during 2014. We estimate that only 5.26% of SARS-CoV-2 infections were not detected in New Zealand during 2020 (95% credible interval: 0.243 – 16.0%) if 80% of contacts were under active surveillance but depending on assumptions about the ratio of contacts not under active surveillance versus contacts under active surveillance 39.0% or 37.7% of Ebola infections were not detected in Guinea (95% credible intervals: 1.69 – 87.0% or 1.70 – 80.9%). • Next generation matrices can be used to estimate the proportion of infections that are not detected during an outbreak. • Our method is parameterised by linking case and contact tracing data, which should be routine in responding to outbreaks. • Our method is parameterised by less data than traditional methods. [ABSTRACT FROM AUTHOR]

Purpose: Following the implementation of the 3rd version of the Danish National Patient Register (DNPR-3), information on whether hospitalizations were inpatient, outpatient, or emergency room (ER) contacts was no longer readily available. This study examined the positive predictive values (PPV) of a common algorithm to characterize hospitalizations as inpatient, outpatient, or emergency room (ER) contacts in both DNPR-2 and DNPR-3. Patients and Methods: All hospital contacts in North Denmark Region were identified in the DNPR within a 1-year window of the implementation of DNPR-3 in early 2019. An algorithm based upon proportion of overnight (± 50%) and elective (± 50%) contacts for each hospital department was developed. Next, PPVs of these categorizations were computed using manual characterization of all departments and clinics by two experienced clinicians as reference. Second, the reliability of various time intervals to join department contacts and subsequent categorization of overnight hospital stays as proxies for inpatient contacts was explored. Results: The algorithm yielded PPVs of 91% and 89% for hospital units and related contacts categorized as inpatient in DNPR-2 and 100% for both parameters in DNPR-3. In outpatient units, the PPVs were 99% in both DNPR-2 and DNPR-3, whereas the corresponding PPVs were 99.6% and 99% on the contact level. In contrast, the PPV for ERs was 33% in DNPR-2 and 56% in DNPR-3, primarily due to misclassification of outpatient clinics. Still, the proportion of correctly categorized ER contacts was 87% in DNPR-2 and 85% in DNPR-3. Using time intervals from 0 to 12 hours to join department contacts showed that overnight hospitalizations comprised inpatient contacts in 97% in DNPR-2 and 98% in DNPR-3. However, the sensitivity was moderate at 76– 78% for all inpatient hospitalizations in DNPR-2 and DNPR-3. Conclusion: This algorithm accurately categorized hospitalizations as inpatient, outpatient, or ER contacts in both DNPR-2 and DNPR-3. [ABSTRACT FROM AUTHOR]

Contact tracing, where exposed individuals are followed up to break ongoing transmission chains, is a key pillar of outbreak response for infectious disease outbreaks. Unfortunately, these systems are not fully effective, and infections can still go undetected as people may not remember all their contacts or contacts may not be traced successfully. A large proportion of undetected infections suggests poor contact tracing and surveillance systems, which could be a potential area of improvement for a disease response. In this paper, we present a method for estimating the proportion of infections that are not detected during an outbreak. Our method uses next generation matrices that are parameterized by linked contact tracing data and case line-lists. We validate the method using simulated data from an individual-based model and then investigate two case studies: the proportion of undetected infections in the SARS-CoV-2 outbreak in New Zealand during 2020 and the Ebola epidemic in Guinea during 2014. We estimate that only 5.26% of SARS-CoV-2 infections were not detected in New Zealand during 2020 (95% credible interval: 0.243 – 16.0%) if 80% of contacts were under active surveillance but depending on assumptions about the ratio of contacts not under active surveillance versus contacts under active surveillance 39.0% or 37.7% of Ebola infections were not detected in Guinea (95% credible intervals: 1.69 – 87.0% or 1.70 – 80.9%).

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Trafficking in persons is one of the gravest of crimes, but the scope and extent of the crime as measured by the number of victims have scarcely been quantified. Generating data on the population of trafficked persons presents a unique challenge because it tends to be a very hidden population--much more hidden than other hidden populations, such as the homeless population or the drug-injecting population. Epidemiological methods to detect hidden populations have advanced in recent years, with a variety of research papers describing the use of the network scale-up method to detect key affected and other subpopulations. The approach relies on conducting a survey of the general population, in which questions are asked about the number of individuals of interest in the personal network of the respondent and a specific set of questions are devised to estimate the size of the respondent's network. Advantages include the detection of multiple populations of trafficked persons in one survey, the minimization of harm to respondents for divulging first-hand knowledge, and improved statistical accuracy achieved by averaging over a large sample. Disadvantages include limited knowledge of the covariates of the population being surveyed. [ABSTRACT FROM AUTHOR]

In the early stages of response to the SARS-CoV-2 pandemic, it was imperative for researchers to rapidly determine what animal species may be susceptible to the virus, under low knowledge and high uncertainty conditions. In this scoping review, the animal species being evaluated for SARS-CoV-2 susceptibility, the methods used to evaluate susceptibility, and comparing the evaluations between different studies were conducted. Using the PRISMA-ScR methodology, publications and reports from peer-reviewed and gray literature sources were collected from databases, Google Scholar, the World Organization for Animal Health (OIE), snowballing, and recommendations from experts. Inclusion and relevance criteria were applied, and information was subsequently extracted, categorized, summarized, and analyzed. Ninety seven sources (publications and reports) were identified which investigated 649 animal species from eight different classes: Mammalia, Aves, Actinopterygii, Reptilia, Amphibia, Insecta, Chondrichthyes, and Coelacanthimorpha. Sources used four different methods to evaluate susceptibility, in silico, in vitro, in vivo, and epidemiological analysis. Along with the different methods, how each source described "susceptibility" and evaluated the susceptibility of different animal species to SARS-CoV-2 varied, with conflicting susceptibility evaluations evident between different sources. Early in the pandemic, in silico methods were used the most to predict animal species susceptibility to SARS-CoV-2 and helped guide more costly and intensive studies using in vivo or epidemiological analyses. However, the limitations of all methods must be recognized, and evaluations made by in silico and in vitro should be re-evaluated when more information becomes available, such as demonstrated susceptibility through in vivo and epidemiological analysis. [ABSTRACT FROM AUTHOR]

Background: Graphical representation of data is one of the most easily comprehended forms of explanation. The current study describes a simple visualization tool which may allow greater understanding of medical and epidemiological data. Method: We propose a simple tool for visualization of data, known as a “quilt plot”, that provides an alternative to presenting large volumes of data as frequency tables. Data from the Australian Needle and Syringe Program survey are used to illustrate “quilt plots”. Conclusion: Visualization of large volumes of data using “quilt plots” enhances interpretation of medical and epidemiological data. Such intuitive presentations are particularly useful for the rapid assessment of problems in the data which cannot be readily identified by manual review. We recommend that, where possible, “quilt plots” be used along with traditional quantitative assessments of the data as an explanatory data analysis tool. [ABSTRACT FROM AUTHOR]

Objectives Previous and ongoing epidemiological surveillance of sports and recreation injuries (SRI) has been cross-sectional in nature, utilised a subset of injuries based on athletic trainer availability, or focused on elite and professional athletes. In the United States, surveillance is often prohibitively expensive and not well funded by national organisations or agencies, except for the case of some professional and elite sports. This paper details the methodology, barriers, and successes of using deterministic linkage to combine emergency department and hospitalisation data with a single identifier for use in surveilling sports injuries for persons aged 5 to 18 years. Design Data linkage of a population cohort. Methods We performed deterministic linkage of administrative emergency department and hospitalisation data from the state of Florida in the US. Data was acquired from the Florida Agency for Health Care Administration. With limited identifiers available due to privacy, we combined data across multiple years using a near universal identifier. We identified sport and recreation injuries using a modified External Cause of Injury Morbidity Matrix and ICD codes across all possible diagnoses. Finally, we obtained descriptive statistics of records that were successfully linked and those that were not to assess similarities between the groups. Results We found 384,731 visits for SRI over a seven-year period. We were able to link approximately 70% of the records using a single identifier. There were statistically significant differences by age, sex, payer, and race/ethnicity for the records that were linked compared to the records that were not linked. Conclusions This study is significant because while similar methods have been used to examine other conditions (e.g. asthma), few have linked multiple types of administrative data especially with nearly no identifiers to examine sports and recreation injuries. This method was found useful to identify injuries over time for the same individuals seeking care in emergency departments, or in hospital inpatient settings, though future work will need to address the limitations of this method. If we expect to move health surveillance forward as budgets for it become even more limited, we must develop and improve methods to do it with fewer resources, including using data that has great limitations. Keywords deterministic linkage; epidemiological methods; epidemiology; surveillance; public health; data cleaning; data linkage; reformatting; SAS; Python; injury surveillance; disease surveillance; health surveillance; biostatistics

We propose a modified self‐controlled case series (SCCS) method to handle both event‐dependent exposures and high event‐related mortality. This development is motivated by an epidemiological study undertaken in France to quantify potential risks of cardiovascular events associated with COVID‐19 vaccines. Event‐dependence of vaccinations, and high event‐related mortality, are likely to arise in other SCCS studies of COVID‐19 vaccine safety. Using this case study and simulations to broaden its scope, we explore these features and the biases they may generate, implement the modified SCCS model, illustrate some of the properties of this model, and develop a new test for presence of a dose effect. The model we propose has wider application, notably when the event of interest is death. [ABSTRACT FROM AUTHOR]

Disease control is of paramount importance in public health, with infectious disease extinction as the ultimate goal. Although diseases may go extinct due to random loss of effective contacts where the infection is transmitted to new susceptible individuals, the time to extinction in the absence of control may be prohibitively long. Intervention controls are typically defined on a deterministic schedule. In reality, however, such policies are administered as a random process, while still possessing a mean period. Here, we consider the effect of randomly distributed intervention as disease control on large finite populations. We show explicitly how intervention control, based on mean period and treatment fraction, modulates the average extinction times as a function of population size and rate of infection spread. In particular, our results show an exponential improvement in extinction times even though the controls are implemented using a random Poisson distribution. Finally, we discover those parameter regimes where random treatment yields an exponential improvement in extinction times over the application of strictly periodic intervention. The implication of our results is discussed in light of the availability of limited resources for control. [ABSTRACT FROM AUTHOR]

Background: The vulnerability of clinical trials to volunteer bias is under-reported. Volunteer bias is systematic error due to differences between those who choose to participate in studies and those who do not. Methods and Results: This paper extends the applications of the concept of volunteer bias by using data from a trial of probiotic supplementation for childhood atopy in healthy dyads to explore 1) differences between a) trial participants and aggregated data from publicly available databases b) participants and non-participants as the trial progressed 2) impact on trial findings of weighting data according to deprivation (Townsend) fifths in the sample and target populations. 1) a) Recruits (n = 454) were less deprived than the target population, matched for area of residence and delivery dates (n = 6,893) (mean [SD] deprivation scores 0.09[4.21] and 0.79[4.08], t = 3.44, df = 511, p<0.001). b) i)As the trial progressed, representation of the most deprived decreased. These participants and smokers were less likely to be retained at 6 months (n = 430[95%]) (OR 0.29,0.13–0.67 and 0.20,0.09–0.46), and 2 years (n = 380[84%]) (aOR 0.68,0.50–0.93 and 0.55,0.28–1.09), and consent to infant blood sample donation (n = 220[48%]) (aOR 0.72,0.57–0.92 and 0.43,0.22–0.83). ii)Mothers interested in probiotics or research or reporting infants’ adverse events or rashes were more likely to attend research clinics and consent to skin-prick testing. Mothers participating to help children were more likely to consent to infant blood sample donation. 2) In one trial outcome, atopic eczema, the intervention had a positive effect only in the over-represented, least deprived group. Here, data weighting attenuated risk reduction from 6.9%(0.9–13.1%) to 4.6%(−1.4–+10.5%), and OR from 0.40(0.18–0.91) to 0.56(0.26–1.21). Other findings were unchanged. Conclusions: Potential for volunteer bias intensified during the trial, due to non-participation of the most deprived and smokers. However, these were not the only predictors of non-participation. Data weighting quantified volunteer bias and modified one important trial outcome. Trial Registration: This randomised, double blind, parallel group, placebo controlled trial is registered with the International Standard Randomised Controlled Trials Register, Number (ISRCTN) 26287422. Registered title: Probiotics in the prevention of atopy in infants and children. [ABSTRACT FROM AUTHOR]

Abstract: In this paper I critique the increasing standardization of obesity. Specifically, I consider two ‘definitional turns’: the way language has been standardized to such an extent that it obscures uncertainty and variation, and the appearance of objectivity through quantification and standardized measurement. These, I suggest, have fostered a simplified picture of obesity, promoting the classification of weight and thereby facilitating the emergence of the ‘obesity epidemic’. These definitional turns fail to acknowledge the distinctions between fat and mass and intraclass variation within weight categories. A consequence of this process of simplification has been the erroneous application of population level information to individuals in a clinical context, with potentially harmful results. [Copyright &y& Elsevier]

The objectives of this paper are to predict life years lost associated with obesity-related diseases (ORDs) for U.S. non-smoking adults, and to examine the relationship between those ORDs and mortality. Data from the National Health Interview Survey, 1997–2000, were used. We employed mixed proportional hazard models to estimate the association between those ORDs and mortality and used simulations to project life years lost associated with the ORDs. We found that obesity-attributable comorbidities are associated with large decreases in life years and increases in mortality rates. The life years lost associated with ORDs is more marked for younger adults than older adults, for blacks than whites, for males than females, and for the more obese than the less obese. Using U.S. non-smoking adults aged 40 to 49 years as an example to illustrate percentage of the life years lost associated with ORDs, we found that the mean life years lost associated with ORDs for U.S. non-smoking black males aged 40 to 49 years with a body mass index above 40 kg/m2 was 5.43 years, which translates to a 7.5% reduction in total life years. White males of the same age range and same degree of obesity lost 5.23 life years on average – a 6.8% reduction in total life years, followed by black females (5.04 years, a 6.5% reduction in life years), and white females (4.7 years, a 5.8% reduction in life years). Overall, ORDs increased chances of dying and lessened life years by 0.2 to 11.7 years depending on gender, race, BMI classification, and age. [ABSTRACT FROM AUTHOR]

Background: Population-based studies provide the understanding of health-need required for effective public health policy and service-planning. Mental disorders are an important but, until recently, neglected agenda in global health. This paper reviews the coverage and limitations in global epidemiological data for mental disorders and suggests strategies to strengthen the data. Methods: Systematic reviews were conducted for population-based epidemiological studies in mental disorders to inform new estimates for the global burden of disease study. Estimates of population coverage were calculated, adjusted for study parameters (age, gender and sampling frames) to quantify regional coverage. Results: Of the 77,000 data sources identified, fewer than 1% could be used for deriving national estimates of prevalence, incidence, remission, and mortality in mental disorders. The two major limitations were (1) highly variable regional coverage, and (2) important methodological issues that prevented synthesis across studies, including the use of varying case definitions, the selection of samples not allowing generalization, lack of standardized indicators, and incomplete reporting. North America and Australasia had the most complete prevalence data for mental disorders while coverage was highly variable across Europe, Latin America, and Asia Pacific, and poor in other regions of Asia and Africa. Nationally-representative data for incidence, remission, and mortality were sparse across most of the world. Discussion: Recent calls to action for global mental health were predicated on the high prevalence and disability of mental disorders. However, the global picture of disorders is inadequate for planning. Global data coverage is not commensurate with other important health problems, and for most of the world's population, mental disorders are invisible and remain a low priority. [ABSTRACT FROM AUTHOR]

Objectives: The paper describes the creation of a new scale to measure intimate partner violence (IPV) among gay and bisexual men. Methods: Seven focus group discussions were held with gay and bisexual men, focusing on defining intimate partner violence: 30 forms of IPV were identified. A venue-recruited sample of 912 gay and bisexual men was surveyed, examining definitional understanding and recent experiences of each of the 30 forms of IPV. Participants were also asked questions from the CDC definition of intimate partner violence and the short-form of the Conflicts Tactics Scale (CTS2S). Factor analysis of responses to the definitional questions was used to create the IPV-GBM scale, and the prevalence of intimate partner violence was compared with that identified by the CDC and CTS2S measures of intimate partner violence. Results: A 23-item scale, with 5 unique domains, was created, with strong internal reliability (Cronbach Alpha >.90). The IPV-GBM scale mirrored both the CDC and CTS2S definitions of intimate partner violence, but contained additional domains such as controlling violence, monitoring behaviors, emotional violence, and HIV-related violence. The new scale identified a significantly higher prevalence of IPV than either of the more commonly used measures. Conclusions: The results presented here provide encouraging evidence for a new, more accurate measure of intimate partner violence among gay and bisexual men in the U.S. [ABSTRACT FROM AUTHOR]

Background: Intravaginal practices (IVP) are highly prevalent in sub-Saharan African and have been implicated as risk factors for HIV acquisition. However, types of IVP vary between populations, and detailed information on IVP among women at risk for HIV in different populations is needed. We investigated IVP among women who practice transactional sex in two populations: semi-urban, facility workers in Tanzania who engage in opportunistic sex work; and urban, self-identified sex workers and bar workers in Uganda. The aim of the study was to describe and compare IVP using a daily pictorial diary. Methodology/Principal Findings: Two hundred women were recruited from a HIV prevention intervention feasibility study in Kampala, Uganda and in North-West Tanzania. Women were given diaries to record IVP daily for six weeks. Baseline data showed that Ugandan participants had more lifetime partners and transactional sex than Tanzanian participants. Results from the diary showed that 96% of Tanzanian participants and 100% of Ugandan participants reported intravaginal cleansing during the six week study period. The most common types of cleansing were with water only or water and soap. In both countries, intravaginal insertion (e.g. with herbs) was less common than cleansing, but insertion was practiced by more participants in Uganda (46%) than in Tanzania (10%). In Uganda, participants also reported more frequent sex, and more insertion related to sex. In both populations, cleansing was more often reported on days with reported sex and during menstruation, and in Uganda, when participants experienced vaginal discomfort. Participants were more likely to cleanse after sex if they reported no condom use. Conclusions: While intravaginal cleansing was commonly practiced in both cohorts, there was higher frequency of cleansing and insertion in Uganda. Differences in IVP were likely to reflect differences in sexual behaviour between populations, and may warrant different approaches to interventions targeting IVP. Vaginal practices among women at high risk in Uganda and Tanzania: recorded behaviour from a daily pictorial diary. [ABSTRACT FROM AUTHOR]

This article provides a fully Bayesian approach for modeling of single-dose and complete pharmacokinetic data in a population pharmacokinetic (PK) model. To overcome the impact of outliers and the difficulty of computation, a generalized linear model is chosen with the hypothesis that the errors follow a multivariate Student t distribution which is a heavy-tailed distribution. The aim of this study is to investigate and implement the performance of the multivariate t distribution to analyze population pharmacokinetic data. Bayesian predictive inferences and the Metropolis-Hastings algorithm schemes are used to process the intractable posterior integration. The precision and accuracy of the proposed model are illustrated by the simulating data and a real example of theophylline data. [ABSTRACT FROM AUTHOR]

Background: MDM2 is a major negative regulator of p53, and a single nucleotide polymorphism (SNP) in the MDM2 promoter region SNP309 has been demonstrated to be associated with an increased MDM2 expression and a significantly earlier age of onset of several tumors, including gastric cancer. Several studies were published to evaluate the association between SNP309 and gastric cancer risk. However, the results remain conflicting rather than conclusive. Objective: The aim of this study was to assess the association between the MDM2 SNP309 polymorphism and gastric risk. Methods: We performed a meta-analysis to investigate this relationship. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the strength of the association. The pooled ORs were performed for codominant model, dominant model, and recessive model, respectively. Results: Five published case-control studies, including 1,621 gastric cancer cases and 2,639 controls were identified. We found that the MDM2 SNP309 polymorphism was associated with a significantly increased risk of gastric cancer risk when all studies were pooled into the meta-analysis (GG versus TT, OR = 1.54; 95%CI = 1.04–2.29, and GG versus GT/TT, OR = 1.49, 95%CI = 1.30–1.72). Furthermore, Egger's test did not show any evidence of publication bias (P = 0.799 for GG versus TT). Conclusion: Our results suggest that the MDM2 SNP309 polymorphism may be a low-penetrant risk factor for the development of gastric cancer. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: IDD info, a new software for managing survey data of Iodine Deficiency Disorders (IDD), is presented in this paper. IDD Info aims to create IDD project databases, process, analyze various national or regional surveillance data and form final report. It has series measures of choosing database from existing ones, revising it, choosing indicators from pool to establish database and adding indicators to pool. It also provides simple tools to scan one database and compare two databases, to set IDD standard parameters, to analyze data by single indicator and multi-indicators, and finally to form typeset report with content customized. Methods: IDD Info was developed using Chinese national IDD surveillance data of 2005. Its validity was evaluated by comparing with survey report given by China CDC. Results: The IDD Info is a professional analysis tool, which succeeds in speeding IDD data analysis up to about 14.28% with respect to standard reference routines. It consequently enhances analysis performance and user compliance. Conclusions: IDD Info is a practical and accurate means of managing the multifarious IDD surveillance data that can be widely used by non-statisticians in national and regional IDD surveillance. [Copyright &y& Elsevier]

Background: In August 2021, we published in Environmental Health a Toolkit for detecting misused epidemiological methods with the goal of providing an organizational framework for transparently evaluating epidemiological studies, a body of evidence, and resultant conclusions. Tsuda et al., the first group to utilize the Toolkit in a systematic fashion, have offered suggestions for its modification.Main Body: Among the suggested modifications made by Tsuda et al., we agree that rearrangement of Part A of the Toolkit to reflect the sequence of the epidemiological study process would facilitate its usefulness. Expansion or adaptation of the Toolkit to other disciplines would be valuable but would require the input of discipline-specific expertise. We caution against using the sections of the Toolkit to produce a tally or cumulative score, because none of the items are weighted as to importance or impact. Rather, we suggest a visual representation of how a study meets the Toolkit items, such as the heat maps used to present risk of bias criteria for studies included in Cochrane reviews. We suggest that the Toolkit be incorporated in the sub-specialty known as "forensic epidemiology," as well as in graduate training curricula, continuing education programs, and conferences, with the recognition that it is an extension of widely accepted ethics guidelines for epidemiological research.Conclusion: We welcome feedback from the research community about ways to strengthen the Toolkit as it is applied to a broader assemblage of research studies and disciplines, contributing to its value as a living tool/instrument. The application of the Toolkit by Tsuda et al. exemplifies the usefulness of this framework for transparently evaluating, in a systematic way, epidemiological research, conclusions relating to causation, and policy decisions.Postscript: We note that our Toolkit has, most recently, inspired authors with discipline-specific expertise in the field of Conservation Biology to adapt it for use in the Biological Sciences. [ABSTRACT FROM AUTHOR]

The article discusses research challenges and considerations in investigating rare exposures using breast hypoplasia. Topics include International Board Certified Lactation Consultants (IBCLCs) assist breastfeeding women to overcome a variety of common breastfeeding problems; and Clinicians may recognize the condition or may attribute insufficient milk supply to more common reasons.

Background: The 'years of potential life lost' (YPLL) is a public health measure in widespread use. However, the index does not apply to the comparisons between different populations or across different time periods. It also has the limit of being cross-sectional in nature, quantifying current burden but not future impact on society.Methods: A new years-lost index is proposed-the 'cumulative rate of potential life lost' (CRPLL). It is a simple combination of the 'cumulative rate' (CR) and the YPLL. Vital statistics in Taiwan are used for demonstration and comparison of the new index with existing health-status measures.Results: The CRPLL serves the purpose of between-group comparison. It can also be considered a projection of future impact, under the assumption that the age-specific mortality rates in the current year prevail. For a rare cause of death, it can be interpreted as the expected years (days) of potential life lost during a subject's lifetime.Conclusions: The CRPLL has several desirable properties, rendering it a promising alternative for quantifying health status. [ABSTRACT FROM AUTHOR]

Background: Various methods of analysis have been used to study age-period-cohort models. The main aim of this paper is to illustrate and compare three such methods. Those of Clayton and Schifflers, Robertson and Boyle, and De Carli and La Vecchia. The main differences between these methods lie in their approach to distinguish between linear-period and linear-cohort effects. Clayton and Schifflers do not attempt to solve this identification problem, whereas Robertson and Boyle, and De Carli and La Vecchia attempt to tackle this question.Methods: In order to study the assumptions and problems of these methods, we analysed data from 2678 subjects aged 30-84 in Yorkshire, UK, who were diagnosed with non-Hodgkin's lymphoma (NHL) during the period 1978-1991. Loglinear Poisson models were used to examine the effects of age, period and cohort.Results: All three methods of analysis agree that, after stratification for sex and county, the age-standardized rate has been increasing at about 5% per year. The Robertson-Boyle method differed from the Clayton-Schifflers method in showing a significant non-linear cohort effect, and a significant county-cohort interaction. The method of De Carli-La Vecchia agreed more closely with Clayton-Schifflers than with Robertson-Boyle.Conclusions: The linear increase in incidence would lead to a doubling of the number of cases within 15 years. There is controversy over whether the identification problem can be solved and should be solved. Many authors would not rely on the results of the methods of Robertson and Boyle, or De Carli and La Vacchia. [ABSTRACT FROM AUTHOR]

The hypothalamus-pituitary-adrenal (HPA) axis plays an important role in primary aldosteronism. Aldosterone biosynthesis is regulated not only by angiotensin II in the renin-angiotensin-aldosterone system, but also by adrenocorticotropic hormone (ACTH), one of the key components of the HPA axis. Although previous studies have reported cortisol cosecretion in primary aldosteronism, particularly aldosterone-producing adenoma (APA), the clinical relevance of such aldosterone and cortisol cosecretion from APA and hypertension or other metabolic disorders has not been fully established. Several somatic mutations including KCNJ5 and CACNA1D are known to induce autonomous production of aldosterone in APA, and the aldosterone responsiveness to ACTH may vary according to each mutation. The ACTH stimulation test has been reported to be a useful tool to distinguish the subtypes of primary aldosteronism (e.g., unilateral vs bilateral) in some studies, but it has not been commonly applied in clinical practice due to limited evidence. Given the recent advancement of imaging, omics research, and computational approach, it is important to summarize the most updated evidence to disentangle the potential impact of cortisol excess in primary aldosteronism and whether the ACTH stimulation test needs to be considered during the diagnostic process of primary aldosteronism. In this article, we conducted a systematic review of epidemiological studies about (i) cortisol cosecretion in primary aldosteronism and (ii) the ACTH stimulation test for the diagnosis of primary aldosteronism (including subtype diagnosis). Then, we discussed potential biases (e.g., confounding bias, overadjustment, information bias, selection bias, and sampling bias) in the previous studies and introduced some advanced epidemiological/statistical methods to minimize these limitations. A better understanding of biases and epidemiological perspective on this topic would allow us to produce further robust evidence and balanced discussion about the causal mechanisms involving the HPA axis and clinical usefulness of the ACTH stimulation test among patients with primary aldosteronism. [ABSTRACT FROM AUTHOR]

Background: Most health surveys have experienced a decline in response rates. A structured approach to evaluate whether a decreasing - and potentially more selective - response over time biased estimated trends in health behaviours is lacking. We developed a framework to explore the role of differential non-response over time. This framework was applied to a repeated cross-sectional survey in which the response rate gradually declined.Methods: We used data from a survey conducted biannually between 1995 and 2017 in the city of Rotterdam, The Netherlands. Information on the sociodemographic determinants of age, sex, and ethnicity was available for respondents and non-respondents. The main outcome measures of prevalence of sport participation and watching TV were only available for respondents. The framework consisted of four steps: 1) investigating the sociodemographic determinants of responding to the survey and the difference in response over time between sociodemographic groups; 2) estimating variation in health behaviour over time; 3) comparing weighted and unweighted prevalence estimates of health behaviour over time; and 4) comparing associations between sociodemographic determinants and health behaviour over time.Results: The overall response rate per survey declined from 47% in 1995 to 15% in 2017. The probability of responding was higher among older people, females, and those with a Western background. The response rate declined in all subgroups, and a faster decline was observed among younger persons and those with a non-Western ethnicity as compared to older persons and those with a Western ethnicity. Variation in health behaviours remained constant. Prevalence estimates and associations did not follow the changes in response over time. On the contrary, the difference in probability of participating in sport gradually decreased between males and females, while no differential change in the response rate was observed.Conclusions: Providing insights on non-response patterns over time is essential to understand whether declines in response rates may have influenced estimated trends in health behaviours. The framework outlined in this study can be used for this purpose. In our example, in spite of a major decline in response rate, there was no evidence that the risk of non-response bias increased over time. [ABSTRACT FROM AUTHOR]