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Copyright of Revista de Salud Pública is the property of Universidad Nacional de Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: The Liu Comorbidity Index uses the United States Renal Data System (USRDS) to quantify comorbidity in chronic dialysis patients, capturing baseline comorbidities from days 91 through 270 after dialysis initiation. The 270 day survival requirement results in sample size reductions and potential survivor bias. An earlier and shorter time-frame for data capture could be beneficial, if sufficiently similar comorbidity information could be ascertained. Methods: USRDS data were used in a retrospective observational study of 70,114 Medicare- and Medicaid-eligible persons who initiated chronic dialysis during the years 2000-2005. The Liu index was modified by changing the baseline comorbidity capture period to days 1-90 after dialysis initiation for persons continuously enrolled in Medicare. The scores resulting from the original and the modified comorbidity indices were compared, and the impact on sample size was calculated. Results: The original Liu comorbidity index could be calculated for 75% of the sample, but the remaining 25% did not survive to 270 days. Among 52,937 individuals for whom both scores could be calculated, the mean scores for the original and the modified index were 7.4 ± 4.0 and 6.4 ± 3.6 points, respectively, on a 24-point scale. The most commonly calculated difference between scores was zero, occurring in 44% of patients. Greater comorbidity was found in those who died before 270 days. Conclusions: A modified version of the Liu comorbidity index captures the majority of comorbidity in persons who are Medicare-enrolled at the time of chronic dialysis initiation. This modification reduces sample size losses and facilitates inclusion of a sicker portion of the population in whom early mortality is common. [ABSTRACT FROM AUTHOR]

Purpose: To describe the rationale, methodology and baseline data of the Yazd Eye Study, a study in the urban and rural areas of Yazd, a district in the center of Iran. Methods: This population-based cross-sectional study included adults aged 40-80 years from the non-institutionalized population of the Yazd district, in 2010-2011. Using multi-stage, systematic cluster random sampling and a probability proportional to size strategy, 58 clusters of 40 subjects were selected from 251 clusters in different enumeration areas. A detailed interview and eye examination were performed for each eligible participant. The eye examination included refraction testing, uncorrected and best corrected visual acuity testing, slit lamp biomicroscopy, Goldmann applanation tonometry, gonioscopy, dilated fundus examination, visual field, determination of central corneal thickness, and stereoscopic fundus photography. General health assessments and laboratory tests including hemoglobin, hematocrit, glycosylated hemoglobin, fasting blood sugar, serum lipids, and urine albumin to creatinine ratio were also performed to assess anthropometric and systemic risk factors. Results: Of 2320 eligible individuals, 2098 (response rate 90.4%) participated in the study. The mean ± standard deviation age of participants was 54.1 ± 10.0 years, and included 994 men (47.4%) and 1104 women (52.6%). Most participants lived in urban regions (89.2%) and were younger than 60 years old (72.0%). Among the participants, 20.1% were illiterate, and 40.9%, 28.0%, and 11.0% had primary, secondary and college or university level education, respectively. Conclusion: This study is expected to provide an estimate of the prevalence and risk factors of major eye diseases and normal eye indices in the Yazd district. [ABSTRACT FROM AUTHOR]

Background: Selection bias and unmeasured confounding are fundamental problems in epidemiology that threaten study internal and external validity. These phenomena are particularly dangerous in internet-based public health surveillance, where traditional mitigation and adjustment methods are inapplicable, unavailable, or out of date. Recent theoretical advances in causal modeling can mitigate these threats, but these innovations have not been widely deployed in the epidemiological community., Objective: The purpose of our paper is to demonstrate the practical utility of causal modeling to both detect unmeasured confounding and selection bias and guide model selection to minimize bias. We implemented this approach in an applied epidemiological study of the COVID-19 cumulative infection rate in the New York City (NYC) spring 2020 epidemic., Methods: We collected primary data from Qualtrics surveys of Amazon Mechanical Turk (MTurk) crowd workers residing in New Jersey and New York State across 2 sampling periods: April 11-14 and May 8-11, 2020. The surveys queried the subjects on household health status and demographic characteristics. We constructed a set of possible causal models of household infection and survey selection mechanisms and ranked them by compatibility with the collected survey data. The most compatible causal model was then used to estimate the cumulative infection rate in each survey period., Results: There were 527 and 513 responses collected for the 2 periods, respectively. Response demographics were highly skewed toward a younger age in both survey periods. Despite the extremely strong relationship between age and COVID-19 symptoms, we recovered minimally biased estimates of the cumulative infection rate using only primary data and the most compatible causal model, with a relative bias of +3.8% and -1.9% from the reported cumulative infection rate for the first and second survey periods, respectively., Conclusions: We successfully recovered accurate estimates of the cumulative infection rate from an internet-based crowdsourced sample despite considerable selection bias and unmeasured confounding in the primary data. This implementation demonstrates how simple applications of structural causal modeling can be effectively used to determine falsifiable model conditions, detect selection bias and confounding factors, and minimize estimate bias through model selection in a novel epidemiological context. As the disease and social dynamics of COVID-19 continue to evolve, public health surveillance protocols must continue to adapt; the emergence of Omicron variants and shift to at-home testing as recent challenges. Rigorous and transparent methods to develop, deploy, and diagnosis adapted surveillance protocols will be critical to their success., (©Nathaniel Stockham, Peter Washington, Brianna Chrisman, Kelley Paskov, Jae-Yoon Jung, Dennis Paul Wall. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 21.07.2022.)

Background Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases worldwide. In high-income countries, low socioeconomic status seems to be related to a high incidence of T2DM, but very little is known about the intermediate factors of this relationship.Method We performed a case-cohort study in eight Western European countries nested in the EPIC study (n = 340 234, 3.99 million person-years of follow-up). A random sub-cohort of 16 835 individuals and a total of 12 403 incident cases of T2DM were identified. Crude and multivariate-adjusted hazard ratios (HR) were estimated for each country and pooled across countries using meta-analytical methods. Age-, gender- and country-specific relative indices of inequality (RII) were used as the measure of educational level and RII tertiles were analysed.Results Compared with participants with a high educational level (RII tertile 1), participants with a low educational level (RII tertile 3) had a higher risk of T2DM [HR: 1.77, 95% confidence interval (CI): 1.69–1.85; P-trend < 0.01]. The HRs adjusted for physical activity, smoking status and propensity score according to macronutrient intake were very similar to the crude HR (adjusted HR: 1.67, 95% CI: 1.52–1.83 in men; HR: 1.88, 95% CI: 1.73–2.05 in women). The HRs were attenuated only when they were further adjusted for BMI (BMI-adjusted HR: 1.36, 95% CI: 1.23–1.51 in men; HR: 1.32, 95% CI: 1.20–1.45 in women).Conclusion This study demonstrates the inequalities in the risk of T2DM in Western European countries, with an inverse relationship between educational level and risk of T2DM that is only partially explained by variations in BMI. [ABSTRACT FROM PUBLISHER]

Abstract: Objective: To compare precision and apparent bias between cohort, nested case–control, self-controlled case series, case–crossover, and case–time–control study designs. Study Design and Setting: Study designs were implemented to evaluate the association between thiazolidinediones (TZDs) and heart failure, TZDs and fracture, and liver enzyme–inducing anticonvulsants and fracture. Results: Effect estimates were similar for the cohort and case–control study; for the association between TZDs and fracture in women, the hazard ratio was 1.36 (1.18, 1.56) and odds ratio (OR) was 1.44 (1.21, 1.70). For this clinical example, the self-controlled case series gave upward bias when follow-up was censored at the outcome (incidence rate ratio [IRR], 7.08; 4.96, 10.09) but was otherwise unbiased (IRR, 1.41; 1.14, 1.75). The retrospective case–crossover OR was 3.24 (2.18, 4.80), which was reduced by either bidirectional sampling (OR, 1.20; 0.98, 1.46) or with the case–time–control design (OR, 1.40; 1.09, 1.81). Findings on apparent bias were similar for the other two clinical examples. In each clinical example, within-person designs had considerably lower precision than the cohort or case–control study designs. Conclusion: When long-term exposures are analyzed, within-person study designs may have lower precision and greater susceptibility to bias. Bias may be reduced by sampling follow-up both before and after the outcome or with the case–time–control study design. [Copyright &y& Elsevier]

One goal in the post-genome-wide association study era is characterizing gene-environment interactions, including scanning for interactions with all available polymorphisms, not just those showing significant main effects. In recent years, several approaches to such “gene-environment-wide interaction studies” have been proposed. Two contributions in this issue of the American Journal of Epidemiology provide systematic comparisons of the performance of these various approaches, one based on simulation and one based on application to 2 real genome-wide association study scans for type 2 diabetes. The authors discuss some of the broader issues raised by these contributions, including the plausibility of the gene-environment independence assumption that some of these approaches rely upon, the need for replication, and various generalizations of these approaches. [ABSTRACT FROM PUBLISHER]

Copyright of Revista Chilena de Pediatría is the property of Revista Chilena de Pediatria and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article presents the systemic approach for capturing the psychologic-personal perspective in the comprehensive research on spinal cord injury (SCI) of the International Classification of Functioning, Disability and Health (ICF), focusing on what and how to measure. It identifies the areas of research relevant to the psychologic-personal factors in a study. It notes that measurement instruments were collected using measurement reviews, instrument databases, and searches in the literature.

Nearly 50 million Americans report some level of disability in activities of daily living or instrumental activities of daily living. Public health officials advocate for a fresh perspective on disability by considering disability through an epidemiological approach. Should occupational therapists perform this research, and what are the benefits for our profession if we do? This article advocates for enhancing our research knowledge base by including an epidemiological perspective in our research design. The benefits to occupational therapy of this research include (1) increased understanding of the extent and nature of occupational performance disability, (2) advancement of the scope and depth of research for prevention and intervention programs, and (3) improved visibility of the profession as informants for public health policy. Suggestions for preparing researchers to perform these studies and students and practitioners to interpret the studies are provided. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Studying gene-lifestyle interaction may help to identify lifestyle factors that modify genetic susceptibility and uncover genetic loci exerting important subgroup effects. Adequately powered studies with prospective, unbiased, standardised assessment of key behavioural factors for gene-lifestyle studies are lacking. This case-cohort study aims to investigate how genetic and potentially modifiable lifestyle and behavioural factors, particularly diet and physical activity, interact in their influence on the risk of developing type 2 diabetes. Methods: Incident cases of type 2 diabetes occurring in European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts between 1991 and 2007 from eight of the ten EPIC countries were ascertained and verified. Prentice-weighted Cox regression and random-effects meta-analyses were used to investigate differences in diabetes incidence by age and sex. Results: A total of 12,403 verified incident cases of type 2 diabetes occurred during 3.99 million person-years of follow-up of 340,234 EPIC participants eligible for InterAct. We defined a centre-stratified subcohort of 16,154 individuals for comparative analyses. Individuals with incident diabetes who were randomly selected into the subcohort ( n = 778) were included as cases in the analyses. All prevalent diabetes cases were excluded from the study. InterAct cases were followed-up for an average of 6.9 years; 49.7% were men. Mean baseline age and age at diagnosis were 55.6 and 62.5 years, mean BMI and waist circumference values were 29.4 kg/m and 102.7 cm in men, and 30.1 kg/m and 92.8 cm in women, respectively. Risk of type 2 diabetes increased linearly with age, with an overall HR of 1.56 (95% CI 1.48-1.64) for a 10 year age difference, adjusted for sex. A male excess in the risk of incident diabetes was consistently observed across all countries, with a pooled HR of 1.51 (95% CI 1.39-1.64), adjusted for age. Conclusions/interpretation: InterAct is a large, well-powered, prospective study that will inform our understanding of the interplay between genes and lifestyle factors on the risk of type 2 diabetes development. [ABSTRACT FROM AUTHOR]

The Rochester Epidemiology Project (REP) is a unique research infrastructure in which the medical records of virtually all persons residing in Olmsted County, Minnesota, for over 40 years have been linked and archived. In the present article, the authors describe how the REP links medical records from multiple health care institutions to specific individuals and how residency is confirmed over time. Additionally, the authors provide evidence for the validity of the REP Census enumeration. Between 1966 and 2008, 1,145,856 medical records were linked to 486,564 individuals in the REP. The REP Census was found to be valid when compared with a list of residents obtained from random digit dialing, a list of residents of nursing homes and senior citizen complexes, a commercial list of residents, and a manual review of records. In addition, the REP Census counts were comparable to those of 4 decennial US censuses (e.g., it included 104.1% of 1970 and 102.7% of 2000 census counts). The duration for which each person was captured in the system varied greatly by age and calendar year; however, the duration was typically substantial. Comprehensive medical records linkage systems like the REP can be used to maintain a continuously updated census and to provide an optimal sampling framework for epidemiologic studies. [ABSTRACT FROM AUTHOR]

The use of a reference control panel in genome-wide association studies is an interesting solution to the problem of how to reduce costs. In such designs, data on relevant environmental factors are usually collected only in cases, making it more difficult to deal with potential gene-environment interactions when testing for genetic association. However, under certain circumstances, neglecting an existing interaction with the environment may be detrimental in terms of statistical power to detect the genetic factor. In this paper, the authors propose a novel method based on a multinomial logistic regression model to overcome the lack of environmental exposure information in controls, by contrasting both exposed and unexposed cases with the control sample. For each case group, a genetic effect-size parameter is estimated, and the genetic association and the gene-environment interaction are tested jointly. The authors evaluate the performance of this method through asymptotic computations and simulations of cases and population controls under different models. In the presence of a gene-environment interaction, this approach outperforms other available methods that test for genetic association and gene-environment interaction either separately or jointly. Interestingly, it even has better power than the joint test requiring full knowledge of the environmental information in both cases and controls. [ABSTRACT FROM PUBLISHER]

Objective: Examine the influences of race, socioeconomic status, sex, and age on barriers to participation in a study of cross-sectional differences and longitudinal changes in health-related outcomes. Methods: We designed a multidisciplinary, community-based, prospective longitudinal epidemiologic study among socioeconomically diverse African Americans and Whites. We recruited 3722 participants from Baltimore, Md. with a mean age of 47.7 (range 30-64) years, 45% males; 2200 African Americans (59%) and 1522 whites (41%); 41% reported household incomes below the 125% poverty delimiter. Results: There were no significant age differences associated with sex or race. Participants below the 125% poverty delimiter were slightly younger than those above the delimiter. Age, race, and sex, but not poverty status, were associated with the likelihood of a physical examination. Older participants, women, and Whites were more likely to complete their examinations. Among those who completed their examinations, there were no age differences associated with sex and poverty status, but African Americans were negligibly younger than Whites. Conclusions: Although some literature suggests that minorities and low-income people are less willing to participate in clinical research, these baseline data suggest that African Americans individuals and individuals from households with incomes below 125% of the poverty level are at least as willing to participate in observational clinical studies as Whites and higher income individuals of similar age and sex. [ABSTRACT FROM AUTHOR]

Statistical interactions between genes and environmental exposures with respect to disease outcomes may help to identify biologic mechanisms and pathways and inform behavioral interventions. The number of persons required for a single study to have sufficient statistical power to detect such interactions may be considered prohibitively large, making a meta-analysis of published literature an apparently attractive alternative. However, meta-analysis of gene-environment interactions using published literature is challenging, with the conclusions being likely to suffer from bias and lack of generalizability. The authors highlight these challenges and biases using an illustrative example: meta-analysis of interactions between the Pro12Ala variant of the peroxisome proliferator-activated receptor γ (PPARγ) gene and various diet and lifestyle factors in the risk of diabetes. The authors conclude that literature-based meta-analysis conducted to examine gene-environment interactions is unlikely to provide a meaningful quantitative conclusion. Alternative strategies are required, including analyses in scientific consortia established to assess main genetic effects, where individual participant data can be shared, allowing both greater power and consistency of analysis methods. However, these consortia are likely to be limited by lack of standardization of the measures of environmental factors. This issue may ultimately only be resolvable by the de novo establishment of large single or multicenter cohorts using comparable methods. [ABSTRACT FROM PUBLISHER]

The goal of the paper is to determine inter-rater reliability of trained examiners performing standardized strength assessments using manual muscle testing (MMT). The authors report on 19 trainees undergoing quality assurance within a multi-site prospective cohort study. Inter-rater reliability for specially trained evaluators (“trainees”) and a reference rater, performing MMT using both simulated and actual patients recovering from critical illness was evaluated. Across 26 muscle groups tested by 19 trainee-reference rater pairs, the median (interquartile range) percent agreement and intraclass correlation coefficient (ICC; 95% CI) were: 96% (91, 98%) and 0.98 (0.95, 1.00), respectively. Across all 19 pairs, the ICC (95% CI) for the overall composite MMT score was 0.99 (0.98–1.00). When limited to actual patients, the ICC was 1.00 (95% CI 0.99–1.00). The agreement (kappa; 95% CI) in detecting clinically significant weakness was 0.88 (0.44–1.00). MMT has excellent inter-rater reliability in trained examiners and is a reliable method of comprehensively assessing muscle strength. [ABSTRACT FROM AUTHOR]

Introduction. Hypoactive sexual desire disorder (HSDD) is a clinically challenging disorder in women. Little is known about the natural history of the disorder and long-term consequences. A longitudinal registry can address these needs. Aim. To design and implement a registry study of HSDD in women to characterize the natural history of HSDD and current treatment practices. Methods. A longitudinal multicenter registry study has been initiated at clinical sites across the United States. A total of 1,500 women (approximately 1,000 premenopausal, 500 postmenopausal) with clinically-diagnosed HSDD, confirmed by the Decreased Sexual Desire Screener, will be recruited over 24 months at up to 40 clinical sites. Participants will be followed with in-clinic or remote, computer-assisted follow-up. Data from the initial implementation phase was analyzed to assess feasibility of the protocol. A qualitative substudy (N = 40) was conducted to assess content validity of the participant questionnaire. Main Outcome Measures. The primary outcome measure for the Registry study is a patient-based global impression of change in HSDD. Secondary outcome measures are derived from two sources: (i) self-administered questionnaire completed by the participant, and (ii) medical history review completed by the clinician. The questionnaire includes validated measures of sexual function, quality of life, relationship factors, and physical and mental health, as well as newly developed questions on treatments and medications. Results. As of February 12, 2009, 290 women (209 premenopausal, 81 postmenopausal) had been recruited from 15 clinical sites. Results of the initial implementation phase and qualitative substudy on the participant questionnaire show that the Registry protocol is highly feasible and the questionnaire consisting of previously validated scales and selected new items has high content validity. Conclusions. As the first longitudinal registry study in female sexual dysfunction, the HSDD Registry will contribute to a broader understanding of the impact and treatment needs of women with clinically diagnosed HSDD. Rosen RC, Connor MK, and Maserejian NN. The HSDD registry for women: a novel patient registry for women with generalized acquired hypoactive sexual desire disorder. J Sex Med 2010;7:1747–1756. [ABSTRACT FROM AUTHOR]

Gene–environment interactions are likely to be involved in the susceptibility to multifactorial diseases but are difficult to detect. Available methods usually concentrate on some particular genetic and environmental factors. In this paper, we propose a new method to determine whether a given exposure is susceptible to interact with unknown genetic factors. Rather than focusing on a specific genetic factor, the degree of familial aggregation is used as a surrogate for genetic factors. A test comparing the recurrence risks in sibs according to the exposure of indexes is proposed and its power is studied for varying values of model parameters. The Exposed versus Unexposed Recurrence Analysis (EURECA) is valuable for common diseases with moderate familial aggregation, only when the role of exposure has been clearly outlined. Interestingly, accounting for a sibling correlation for the exposure increases the power of EURECA. An application on a sample ascertained through one index affected with type 2 diabetes is presented where gene–environment interactions involving obesity and physical inactivity are investigated. Association of obesity with type 2 diabetes is clearly evidenced and a potential interaction involving this factor is suggested in Hispanics (P=0.045), whereas a clear gene–environment interaction is evidenced involving physical inactivity only in non-Hispanic whites (P=0.028). The proposed method might be of particular interest before genetic studies to help determine the environmental risk factors that will need to be accounted for to increase the power to detect genetic risk factors and to select the most appropriate samples to genotype. [ABSTRACT FROM AUTHOR]

Abstract: Objective: To estimate the difference between the number of subjects actually included in pediatric sequential trials and the sample size that would have been included with a fixed-sample design. Study Design and Setting: A systematic review of pediatric sequential trials was performed. Methodological quality was assessed using a criteria list based on the CONSORT (Consolidated Standards of Reporting Trials) statement, and data were extracted by two reviewers independently. Where possible, fixed sample size calculations were performed using the same assumptions as those of the sequential design, and compared with the reported number of included patients. Results: Twenty-four sequential trials, published between 1963 and 2005, were found. In nine studies, the information about the assumptions was sufficient to calculate a fixed sample size. The median reduction in included sample size in these trials compared with the fixed sample size calculation was 52 subjects (range: −22 to 229), a reduction of 35% (range: −42% to 90%) of the fixed sample size. The median sample size reduction when considering the number of subjects included in the analysis until crossing of the boundaries was 77% (range: 15–90%). Conclusion: Sequential design is a useful method for optimizing the sample size in pediatric clinical trials and may lead to substantial sample size reductions. [Copyright &y& Elsevier]

Decisions about how occupation is used in epidemiologic research can affect conclusions about the importance of socioeconomic and environmental factors in explaining disparities for outcomes such as cardiovascular disease. A review of practices in the collection and use of occupational data was conducted among population-based cardiovascular studies in the United States. Studies were identified for review from the National Heart, Lung, and Blood Institute website and the biomedical database, Computer Retrieval of Information on Scientific Projects, by use of selected criteria. Data collection instruments and study publications were retrieved and reviewed for 30 of 33 studies (91%). Most of the studies (83%) collected at least descriptive occupational data, and more than half (60%) collected data on workplace hazards. The reviewed studies produced 80 publications in which occupational data were used in analyses, most often as an indicator of socioeconomic status. Authors rarely acknowledged known conceptual and empirical links among socioeconomic status, employment stability, and working conditions. Underutilization of data on workplace conditions was found. Existing data could be used more effectively to examine the contribution of work-related social and environmental conditions to the development of modifiable cardiovascular disease through multiple pathways. [ABSTRACT FROM PUBLISHER]

Copyright of Revista Dental Press de Ortodontia e Ortopedia Facial is the property of Dental Press International and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study examined the associations between asymmetric handgrip strength (HGS) and multimorbidity in American adults. Secondary analyses of data from persons aged at least 40 years from the 2011–2012 and 2013–2014 waves of the National Health and Nutrition Examination Survey were conducted. A handheld dynamometer collected HGS on each hand and persons with a strength imbalance >10% between hands were classified as having asymmetric HGS. Adults with the presence of ≥2 of the following conditions had multimorbidity: cardiovascular disease, chronic obstructive pulmonary disease, chronic kidney disease, asthma, arthritis, cancer, obesity, stroke, hypertension, high cholesterol, and diabetes. Of the n = 3483 participants included, n = 2700 (77.5%) had multimorbidity. A greater proportion of adults with multimorbidity had HGS asymmetry (n = 1234 (45.7%)), compared to persons living without multimorbidity (n = 314 (40.1%); p < 0.05). Relative to individuals without asymmetry, adults with asymmetric HGS had 1.31 (95% confidence interval (CI): 1.03–1.67) greater odds for multimorbidity. Moreover, persons with HGS asymmetry had 1.22 (CI: 1.04–1.44) greater odds for accumulating morbidities. Asymmetric strength, as another indicator of diminished muscle function, is linked to chronic morbidity status. Healthcare providers should recommend healthy behaviors for reducing asymmetries to improve muscle function and mitigate morbidity risk after completing asymmetry screenings. [ABSTRACT FROM AUTHOR]

The prevention of neurodegenerative dementias, such as Alzheimer disease, is a growing public health concern, because of a lack of effective curative treatment options and a rising global prevalence. Various potential risk or preventive factors have been suggested by epidemiologic research, including modifiable lifestyle factors, such as social contacts, leisure activities, physical exercise, and diet, as well as some preventive pharmacologic strategies, such as hormone replacement therapy, nonsteroidal antiinflammatory drugs, and Ginkgo biloba. Some factors have been targeted by interventions tested in randomized controlled trials, but many of the results are in conflict with observational evidence. The aim of this paper is to review the epidemiologic data linking potential protective factors to dementia or cognitive decline and to discuss the methodological limitations that could explain conflicting results. A thorough review of the literature suggests that, even if there are consistent findings from large observational studies regarding preventive or risk factors for dementia, few randomized controlled trials have been designed specifically to prove the protective effects of interventions based on such factors on dementia incidence. Because of the multifactorial origin of dementia, it appears that multidomain interventions could be a suitable candidate for preventive interventions, but designing such trials remains very challenging for researchers. [ABSTRACT FROM PUBLISHER]

Different research groups sometimes carry out comparable studies. Combining the data can make it possible to address additional research questions, particularly for small observational studies such as those frequently seen in palliative care research. We present a systematic approach to pool individual subject data from observational studies that addresses differences in research design, illustrating the approach with two prospective observational studies on treatment and outcomes of lower respiratory tract infection in US and Dutch nursing home residents. Benefits of pooling individual subject data include enhanced statistical power, the ability to compare outcomes and validate models across sites or settings, and opportunities to develop new measures. In our pooled dataset, we were able to evaluate treatments and end-of-life decisions for comparable patients across settings, which suggested opportunities to improve care. In addition, greater variation in participants and treatments in the combined dataset allowed for subgroup analyses and interaction hypotheses, but required more complex analytic methods. Pitfalls included the large amount of time required for equating study procedures and variables and the need for additional funding. [ABSTRACT FROM AUTHOR]

Purpose: Poor living conditions are posited as an underlying cause of American Indian (AI) infant mortality, which is unusually high in the postneonatal period. We explore whether the effects of neighborhood poverty on AI infant death are identifiable by using observational data. Methods: Vital records for infants born between 1990 and 1999 to AI women in a metropolitan area (n = 4751) are linked with tract-level poverty data. A counterfactual framework, an explicit causal contrast study design, and propensity score matching methods were used. For each comparison, we created exchangeable groups by matching infants with the same probability of exposure to poverty when one was exposed and the other was not. Results: Our results suggest that neighborhood poverty has little effect on AI infant death outcomes. Importantly, the study design makes transparent the challenge of identifying appropriate analytic comparison groups in studies of neighborhood poverty and health. Conclusions: Collecting additional data will likely not overcome the fact that AIs with a high probability of living in poverty rarely reside in low-poverty neighborhoods. Yet, some of them must if a meaningful counterfactual comparison is to be made and the effects of neighborhood poverty on AI infant death are to be identified. [Copyright &y& Elsevier]

Abstract: Background: Systematic reviews should include as many articles as possible. However, many systematic reviews use only databases with high English language content as sources of trials. Literatura Latino Americana e do Caribe em Ciências da Saúde (LILACS) is an underused source of trials, and there is not a validated strategy for searching clinical trials to be used in this database. Objective: The objective of this study was to develop a sensitive search strategy for clinical trials in LILACS. Study Design and Setting: An analytical survey was performed. Several single and multiple-term search strategies were tested for their ability to retrieve clinical trials in LILACS. Sensitivity, specificity, and accuracy of each single and multiple-term strategy were calculated using the results of a hand-search of 44 Chilean journals as gold standard. Results: After combining the most sensitive, specific, and accurate single and multiple-term search strategy, a strategy with a sensitivity of 97.75% (95% confidence interval [CI]=95.98–99.53) and a specificity of 61.85 (95% CI=61.19–62.51) was obtained. Conclusions: LILACS is a source of trials that could improve systematic reviews. A new highly sensitive search strategy for clinical trials in LILACS has been developed. It is hoped this search strategy will improve and increase the utilization of LILACS in future systematic reviews. [Copyright &y& Elsevier]

Abstract: Objective: Recruitment of pediatric patients in randomized clinical trials is hampered by the rarity of many conditions and by ethical constraints. The objective of this paper is to give an overview of design options to obtain a statistically valid result while including a minimum number of subjects. Study Design and Setting: Overview and discussion of several approaches to conduct valid randomized clinical trials in rare diseases and vulnerable populations. Results: Sequential designs have been developed as efficient ways to evaluate accumulating information from a clinical trial, thereby reducing the average size of trials. Different sequential procedures exist, including group sequential designs, boundaries designs, and adaptive designs. The sample size attained at the end of the trial is unknown at the start. The sample size for a given set of α, β, and effect size may turn out to be larger than with a classical fixed sample size approach. Simulations have shown that on average, sample sizes are smaller. Conclusion: There are several possibilities to optimize the number of subjects in a clinical trial. The rarity of many disorders in children and the ethical requirements in this patient population should not obstruct the performance of well-designed research to support clinical decision making. [Copyright &y& Elsevier]

Copyright of Zeitschrift für Ärztliche Fortbildung und Qualität im Gesundheitswesen is the property of Elsevier GmbH, Urban & Fischer Verlag and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rising multiple sclerosis incidence over the last 50 years and geographic patterns of occurrence suggest an environmental role in the causation of this multifactorial disease. Design options for epidemiological studies of environmental causes of multiple sclerosis are limited by the low incidence of the disease, possible diagnostic delay and budgetary constraints. We describe scientific and methodological issues considered in the development of the Australian Multicentre Study of Environment and Immune Function (the Ausimmune Study), which seeks, in particular, to better understand the causes of the well-known MS positive latitudinal gradient. A multicentre, case-control design down the eastern seaboard of Australia allows the recruitment of sufficient cases for adequate study power and provides data on environmental exposures that vary by latitude. Cases are persons with an incident first demyelinating event (rather than prevalent multiple sclerosis), sourced from a population base using a two tier notification system. Controls, matched on sex, age (within two years) and region of residence, are recruited from the general population. Biases common in case-control studies, eg, prevalence-incidence bias, admission-rate bias, non-respondent bias, observer bias and recall bias, as well as confounding have been carefully considered in the study design and conduct of the Ausimmune Study. [ABSTRACT FROM AUTHOR]

Abstract: Background and Objective: To examine the extent of bias introduced to diagnostic test validity research by the use of post hoc data driven analysis to generate an optimal diagnostic cut point for each data set. Methods: Analysis of simulated data sets of test results for diseased and nondiseased subjects, comparing data driven to prespecified cut points for various sample sizes and disease prevalence levels. Results: In studies of 100 subjects with 50% prevalence a positive bias of five percentage points of sensitivity or specificity was found in 6 of 20 simulations. For studies of 250 subjects with 10% prevalence a positive bias of 5% was observed in 4 of 20 simulations. Conclusion: The use of data-driven cut points exaggerates test performance in many simulated data sets, and this bias probably affects many published diagnostic validity studies. Prespecified cut points, when available, would improve the validity of diagnostic test research in studies with less than 50 cases of disease. [Copyright &y& Elsevier]

Purpose: The purpose of this assessment was to evaluate reporting of observational studies in the pediatric dental literature. Methods: This assessment included the following steps: (1) developing a model for reporting information in clinical dentistry studies; (2) identifying treatment comparisons in pediatric dentistry that were evaluated by at least 5 observational studies; (3) abstracting from these studies any data indicated by applying the reporting model; and (4) comparing available data elements to the desired data elements in the reporting model. Results: The reporting model included data elements related to: (1) patients; (2) providers; (3) treatment details; and (4) study design. Two treatment comparisons in pediatric dentistry were identified with 5 or more observational studies: (1) stainless steel crowns vs amalgams (10 studies); and (2) composite restorations vs amalgam (5 studies). Results from studies comparing the same treatments varied substantially. Data elements from the reporting model that could have explained some of the variation were often reported inadequately or not at all. Conclusions: Reporting of observational studies in the pediatric dental literature may be inadequate for an informed interpretation of the results. Models similar to that used in this study could be used for developing standards for the conduct and reporting of observational studies in pediatric dentistry. [ABSTRACT FROM AUTHOR]