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Background Although books and articles guiding the methods of sample size calculation for prevalence studies are available, we aim to guide, assist and report sample size calculation using the present calculators. Results We present and discuss four parameters (namely level of confidence, precision, variability of the data, and anticipated loss) required for sample size calculation for prevalence studies. Choosing correct parameters with proper understanding, and reporting issues are mainly discussed. We demonstrate the use of a purposely-designed calculators that assist users to make proper informed-decision and prepare appropriate report. Conclusion Two calculators can be used with free software (Spreadsheet and RStudio) that benefit researchers with limited resources. It will, hopefully, minimize the errors in parameter selection, calculation, and reporting. The calculators are available at: ( https://sites.google.com/view/sr-ln/ssc ).

Gingival recession (GR) is considered a public health problem which is highly prevalent across different populations. Accuracy of psychometric properties of prevalence estimates of GR reported in epidemiological studies is important to facilitate setting public health goals, planning of public health programs, implementation of best practices and thereby developing public health policy. However, the reported prevalence estimates are influenced by the methodological variations among different studies, as observed in our recently published systematic review and meta-analysis on the global prevalence of GR. It substantially limits the comparability between studies and inferences about the true global variation in the prevalence of GR are difficult to establish. To address these issues, this commentary suggests to follow the standardized principles related to study design, clinical examination protocol, and characteristics of study subjects in future epidemiological studies on prevalence estimates of GR. Furthermore, the inclusion of additional domains in the reporting data is suggested for a deeper insight into the patterns of GR in different populations. Our suggestions are derived from a pragmatic approach and their consistent implementation would improve the reporting quality and achieve uniformity in future studies, thus benefitting the research in this area.

Background Australia does not have a national healthcare associated infection (HAI) surveillance program. Only one HAI point prevalence study has been undertaken in 1984. The objective of this study was to estimate the burden of healthcare associated infection (HAI) in acute adult inpatients in Australia. Methods A cross sectional point prevalence study (PPS) was conducted in a sample of large acute care hospitals. All data were collected by two trained Research Assistants. Surveillance methodology was based on the European Centre for Disease Prevention and Control (ECDC) PPS Protocol with variation in the sampling method in that only acute inpatients ≥ 18 years old were included. ECDC HAI definitions were applied. Results Data was collected between August and November 2018. A total of 2767 patients from 19 hospitals were included in the study. The median age of patients was 67, and 52.9% of the sample were male. Presence of a multi-drug resistant organism was documented for 10.3% of the patients. There were 363 HAIs present in 273 patients. The prevalence of patients with a HAI was 9.9% (95%CI: 8.8–11.0). Hospital prevalence rates ranged from 5.7% (95%CI:2.9–11.0) to 17.0% (95%CI:10.7–26.1). The most common HAIs were surgical site infection, pneumonia and urinary tract infection, comprising 64% of all HAIs identified. Conclusion This is the first HAI PPS to be conducted in Australia in 34 years. The prevalence rate is higher than the previous Australian study and that reported by the ECDC, however differences in methodology limit comparison. Regular, large scale HAI PPS should be undertaken to generate national HAI data to inform and drive national interventions.

Context: The world is aging rapidly through \"demographic transition.\" The aging leads to CI Refers as Cognitive Impairment (CI) - a risk factor for dementia. A community-based cross-sectional study was conducted among the elderly aged ≥50 years. Objectives: The objective of the study is to estimate the prevalence of cognitive dysfunction among the elderly and to identify the associated sociodemographic variables. Settings and Design: This was a community-based cross-sectional study in rural and urban field areas of a medical college. Subjects and Methods: Participants aged ≥50 years were interviewed using a structured questionnaire and screened for cognitive dysfunction using Gujarati version of Mini-Mental Status Examination. A score of 23 out of 30 was taken as the cutoff. Written informed consent was obtained from participants. Statistical Analysis Used: Univariate and multivariate analyses were done using SPSS version 17 and Epi Info version 6 to identify significant variables. Results: Of 560 participants, 140 (25%) had CI. Rural (27.6%) and female (29.8%) prevalence was higher than urban (18.5%) and male (19.1%) prevalence. On multivariate analysis, age ≥60 years (odds ratio [OR]: 2.98) and illiteracy (OR: 39.8) had significant positive association with outcome; being employed (OR: 0.18), living with spouse (OR: 0.07), and living with spouse and children (OR: 0.08) had significant negative association with outcome. Conclusions: CI - a precursor of dementia - has serious clinical and public health consequences. Awareness generation and capacity building of primary health-care workers and family caregivers are core control strategies.

Background Healthcare-associated infections (HAIs) represent a major Public Health issue. Hospital-based prevalence studies are a common tool of HAI surveillance, but data quality problems and non-representativeness can undermine their reliability. Methods This study proposes three algorithms that, given a convenience sample and variables relevant for the outcome of the study, select a subsample with specific distributional characteristics, boosting either representativeness (Probability and Distance procedures) or risk factors’ balance (Uniformity procedure). A “Quality Score” (QS) was also developed to grade sampled units according to data completeness and reliability. The methodologies were evaluated through bootstrapping on a convenience sample of 135 hospitals collected during the 2016 Italian Point Prevalence Survey (PPS) on HAIs. Results The QS highlighted wide variations in data quality among hospitals (median QS 52.9 points, range 7.98–628, lower meaning better quality), with most problems ascribable to ward and hospital-related data reporting. Both Distance and Probability procedures produced subsamples with lower distributional bias (Log-likelihood score increased from 7.3 to 29 points). The Uniformity procedure increased the homogeneity of the sample characteristics (e.g., − 58.4% in geographical variability). The procedures selected hospitals with higher data quality, especially the Probability procedure (lower QS in 100% of bootstrap simulations). The Distance procedure produced lower HAI prevalence estimates (6.98% compared to 7.44% in the convenience sample), more in line with the European median. Conclusions The QS and the subsampling procedures proposed in this study could represent effective tools to improve the quality of prevalence studies, decreasing the biases that can arise due to non-probabilistic sample collection.

[This corrects the article DOI: 10.1371/journal.pone.0305558.].

Background Fecal incontinence is highly prevalent among nursing home residents. Previous nursing home studies have identified co-morbidity associated with fecal incontinence, but as this population is increasingly old and frail, we wanted to see if the rate of fecal incontinence had increased and to investigate correlates of fecal incontinence further. Methods Cross-sectional study of the entire nursing home population in one Norwegian municipality. Registered nurses filled in a questionnaire for all residents in the municipality (980 residents aged ≥65). Statistical methods used are descriptive statistics, binary logistic regression and multivariable logistic regression. Results The response rate of the study was 90.3%. The prevalence of fecal incontinence was 42.3%. In multivariable analysis of FI, residents with diarrhea (OR 7.33, CI 4.39-12.24), urinary incontinence (OR 2.77, CI 1.73-4.42) and dementia (OR 2.17, CI 1.28-3.68) had higher odds of having fecal incontinence compared to those without the condition. Residents residing in a nursing home between 4–5 years had higher odds of having fecal incontinence compared to residents who had stayed under a year (OR 2.65, CI 1.20-5.85). Residents with deficiency in feeding (2.17, CI 1.26-3.71), dressing (OR 4.03, CI 1.39-11.65), toilet use (OR 7.37, CI 2.65-20.44) and mobility (OR 2.54, CI 1.07-6.00) had higher odds of having fecal incontinence compared to residents without deficiencies in activities of daily living (ADL). Needing help for transfer between bed and chair was a protective factor for fecal incontinence compared to residents who transferred independently (OR 0.49, CI 0.26-0.91). Conclusions Fecal incontinence is a prevalent condition in the nursing home population and is associated with ADL decline, frailty, diarrhea and quality of care. This knowledge is important for staff in nursing home in order to provide the best treatment and care for residents with fecal incontinence.

Background Estimation of prevalence of Strongyloides stercoralis infection is required in endemic areas, in order to identify areas in need of control programmes. Data on prevalence of strongyloidiasis in Madagascar are scant. Aim of this work was to estimate prevalence of S. stercoralis in four districts of Madagascar. Methods Fecal and serum samples collected in the context of a previous study on schistosomiasis were tested with S. stercoralis real-time PCR and serology, respectively. A multiplex real-time PCR for Ascaris lumbricoides , Ancylostoma duodenalis , Necator americanus , and Trichuris trichiura was done on fecal samples collected in the areas demonstrating higher prevalence of strongyloidiasis. Comparisons between proportions were made using Fisher exact test, with false discovery rate correction used for post-hoc comparisons. A multivariable Firth logistic regression model was used to assess potential risk factors for S. stercoralis infection. Results Overall, 1775 serum samples were tested, of which 102 of 487 (20.9%) and 104 of 296 (35.2%) were serological-positive in Marovoay and in Vatomandry districts (both coastal areas), respectively, compared to 28 of 496 (5.6%) and 30 of 496 (6.1%) in Tsiroanomandidy and in Ambositra districts (both highlands), respectively (adj. p  < 0.001). PCR for S. stercoralis was positive in 15 of 210 (7.1%) and in 11 of 296 (3.7%) samples from Marovoay from Vatomandry, respectively, while was negative for all samples tested in the other two districts. High prevalence of A. lumbricoides (45.9%), hookworm (44.6%) and T. trichiura (32.1%) was found in Vatomandry. In the multivariable analysis, strongyloidiasis was associated with hookworm infection. Hookworm infection was also associated with male sex and lower education level. Conclusions S. stercoralis prevalence proved higher in coastal areas compared to highlands. Different climatic conditions may explain this distribution, along with previous rounds of anthelminthics distributed in the country, which may have reduced the parasite load in the population. The high prevalence of the other soil-transmitted helminths (STH) in Vatomandry was unexpected, given the good coverage with benzimidazole in control campaigns. Further studies are needed to explore the risk factors for STH and S. stercoralis infections in Madagascar, in order to align with the WHO recommendations.