Population Characteristics Research Articles

Evaluation of different estimator approaches based on COVID-19 data and a simulation study

Sampling is crucial in basic statistics due to the large size of certain populations. Sampling theory focuses on selecting samples based on appropriate population characteristics and approaches to estimating population characteristics from the sample. Firstly, we use the ratio-type estimator proposed by Prasad (1989). We adapt this unbiased ratio-type estimator to two new different estimators using the Hartley-Ross and non-response approaches. Finally, we combine these approaches and propose a new estimator. The theoretical results were supported by COVID-19 data and a simulation study with various scenarios. Based on the COVID-19 data result, it was concluded that the new tN3 estimator is the most effective estimator among those proposed and compared, with the minimum MSE and maximum PRE. Upon examining the changes in the COVID-19 data set in detail, it is evident that the PRE value increases with an increase in sample size, non-response rate, and k values. As in the COVID-19 dataset, the tN3 estimator was the most effective in the simulation study results. It is also important to note that these results are not applicable to only one scenario in simulation study. The tN2 estimator was the most effective in the scenario with rho=0.90, T=1000, n=400, non-response rate=0.30 and k equal to 2, 4 and 5.

High silent prevalence of human herpesvirus 1 (HSV-1) infection affecting the indigenous reservation of the municipality of Dourados, Central-West Brazil

BackgroundThe indigenous population located in the central region of Brazil, is the second largest in terms of population size in the country. The Indigenous Reserve of Dourados has risk factors that increase the vulnerability of the indigenous population to infectious diseases, especially Human alphaherpesvirus (HSV-1), a neglected disease with high prevalence in priority populations in developing countries. The virus can also cause many more severe diseases, including widespread neonatal infections, herpetic keratitis, and herpes encephalitis, which can be fatal if left untreated. We estimated the prevalence of anti-HSV-1 antibodies and correlated it with the demographic and behavioral characteristics of the Indigenous population of the Jaguapirú and Bororó villages (Dourados, Mato Grosso do Sul (MS), Brazil).MethodsOur approach was cross-sectional. From March 2017 to November 2018. Using anti-HSV-1 (Gg1) IgM and anti-HSV-1 (gG1) IgG Euroimmun and the detection and quantification of HSV-1 viral load in plasma samples, through real-time PCR. The maps were constructed using QGIS and the statistical analyses using R Studio software.ResultsA total of 1138 individuals (> 18 years old) were enrolled. The prevalence of anti-HSV-1 IgM and IgG were 20% and 97.5%, respectively. The prevalence of anti-HSV-1 antibodies for IgG was higher in both sexes. Anti-HSV-1 IgM antibodies were present in 17.1%, 21.2%, 12.5%, and 22% of the participants with urinary problems, genital wounds, genital warts, and urethral discharge, respectively. Real-time PCR was used for confirmatory testing; HSV-1 DNA was detected in 25.6% (54/211) of anti-HSV1 IgM-positive samples. Viral loads ranged from 5.99E + 02 to 3.36E + 13.ConclusionsThe seroprevalence of HSV-1 IgM and detection of HSV-1 DNA in the Indigenous population confirmed high silent prevalence. Furthermore, the seroprevalence of HSV-1 in the Indigenous population was higher than that reported in the general adult Brazilian population. Various socioeconomic factors, drug use, and health and sexual behaviors could contribute to the facilitation of HSV-1 transmission in the Indigenous population. Our results may help develop culturally appropriate intervention programs that eliminate health access barriers and improve the implementation of public health policies aimed at promoting information regarding the prevention, treatment, and control of HSV-1 infection in Brazilian Indigenous populations.

ATAGI targeted review 2023: Vaccination for preventing influenza in Australia.

Annual seasonal influenza epidemics cause substantial disease and economic burden worldwide. During the coronavirus disease 2019 (COVID-19) pandemic in 2020 and 2021, influenza activity significantly declined. However, influenza resurged in Australia following the relaxation of non-pharmaceutical interventions, with increased influenza virus circulation in early 2022 coinciding with the SARS-CoV-2 Omicron BA.2 variant wave. Together with other respiratory virus diseases, these disease impacts on the Australian population and healthcare system have re-emphasised the importance of influenza vaccination and control. We aim to provide an overview of the current seasonal influenza vaccination program in Australia and summarise evidence and considerations underpinning potential future immunisation strategies. Influenza causes disproportionately higher morbidity and mortality in young children and older adults. Other populations at elevated risk from influenza include Aboriginal and Torres Strait Islander peoples, pregnant women, and people with certain underlying medical conditions. All Australians aged ≥ 6 months are recommended to receive influenza vaccine every year. The National Immunisation Program (NIP) provides free vaccine for eligible at-risk populations. While approximately 70% of older adults had received influenza vaccine in 2022, coverage in other age groups remains suboptimal. There are several key unmet needs and challenges, but also potential strategies for enhancing the influenza vaccination program in Australia. Improved monitoring and evaluation, including the use of relevant linked datasets for such purposes, is imperative to better understand variations in coverage and vaccination impact in specific populations. Adoption of evidence-based strategies, such as culturally appropriate resources that consider the characteristics of diverse Australian populations, may also help to achieve higher vaccine coverage rates. Additionally, greater vaccine uptake across the population could be facilitated by expanding the NIP-eligible population where cost-effective, and adopting the use of more effective and different types of vaccines when available.

Genome-wide association analysis reveal candidate genes and haplotypes related to root weight in cucumber (Cucumis sativus L.).

The plant root system is critical for the absorption of water and nutrients, and have a direct influence on growth and yield. In cucumber, a globally consumed crop, the molecular mechanism of root development remains unclear, and this has implications for developing stress tolerant varieties. This study sought to determine the genetic patterns and related genes of cucumber root weight. A core cucumber germplasms population was used to do the GWAS analysis in three environments. Here, we investigated four root-weight related traits including root fresh weight (RFW), root dry weight (RDW), ratio of root dry weight to root fresh weight (RDFW) and the comprehensive evaluation index, D-value of root weight (DRW) deduced based on the above three traits for the core germplasm of the cucumber global repository. According to the D-value, we identified 21 and 16 accessions with light and heavy-root, respectively. We also found that the East Asian ecotype accessions had significantly heavier root than other three ecotypes. The genome-wide association study (GWAS) for these four traits reveals that 4 of 10 significant loci (gDRW3.1, gDRW3.2, gDRW4.1 and gDRW5.1) were repeatedly detected for at least two traits. Further haplotype and expression analysis for protein-coding genes positioned within these 4 loci between light and heavy-root accessions predicted five candidate genes (i.e., Csa3G132020 and Csa3G132520 both encoding F-box protein PP2-B1 for gDRW3.1, Csa3G629240 encoding a B-cell receptor-associated protein for gDRW3.2, Csa4G499330 encodes a GTP binding protein for gDRW4.1, and Csa5G286040 encodes a proteinase inhibitor for gDRW5.1). We conducted a systematic analysis of the root genetic basis and characteristics of cucumber core germplasms population. We detected four novel loci, which regulate the root weight in cucumber. Our study provides valuable candidate genes and haplotypes for the improvement of root system in cucumber breeding.

Ultrastructure of the mesonephros of whitefishes from the Lake Baikal basin.

The article presents a study of the mesonephros ultrastructure of Baikal omul Coregonus migratorius, Baikal whitefish Coregonus baicalensis, and a cross between Baikal whitefish and humpback whitefish (C. baicalensis × Coregonus pidschian). The mesonephros ultrastructure was studied using electron microscopy methods. The results of the study show that the number of mature granulocytes is a systematic feature and does not depend on the ecology of fish. The quantitative characteristics of blood cells and the ultrastructural features of leukocytes in the mesonephros are associated with the functioning of the nonspecific defence system in fish. Morphological diversity of epithelial cells in nephron tubules is the ancestral characteristic of the modern omul population, associated with geological and climatic events in the history of Lake Baikal. The development of haematopoietic tissue in the mesonephros, the ultrafine structure of ion-transporting interstitial cells, as well as some ultrastructural features found in the nephron, reflect the adaptive capabilities of the species to live in the ultra-deep Lake Baikal.

Influence of non-pharmaceutical interventions on epidemiological characteristics of Mycoplasma pneumoniae infection in children during and after the COVID-19 epidemic in Ningbo, China.

Since the outbreak of COVID-19, China has implemented a series of non-pharmaceutical interventions (NPIs), effectively containing the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as well as various respiratory pathogens. With the continuous relaxation of restrictions, China has entered a new phase of the post-pandemic era. However, the epidemiological differences of Mycoplasma pneumoniae (MP) between the two phases in Ningbo and even in China remain unclear. Data of children aged 0-14 years who visited the Ningbo Medical Center LiHuiLi Hospital due to acute respiratory tract infections from January 2020 to December 2023 were collected. PCR was used to detect 13 respiratory pathogens and the macrolide-resistance of Mycoplasma pneumoniae. Among 10,206 children, 2,360 were infected with MP (23.12%). Among the total, the MP positive rate during the NPI phase (6.35%) was significantly lower than that during the non-NPI phase (34.28%), while the macrolide resistance rate increased from 62.5% (NPI phase) to 81.1% (non-NPI phase). The rate of MP co-infection increased from 11.2% (NPI phase) to 30.3% (non-NPI phase). MP infection exhibited obvious seasonality, with the highest prevalence in autumn (30.0%) followed by summer (23.6%). There were differences in MP positivity rates among different age groups, with the highest among school-age children at 39.5%. During the NPI phase, all age groups were less susceptible to MP, while during the non-NPI phase, the susceptible age for MP was 4-12 years, with 8 years being the most susceptible. The susceptible age for MP co-infection was 0-6 years. MP exhibited antagonistic effects against numerous pathogens. Compared to MP single infection, the proportion of pneumonia was higher in MP co-infection cases. The removal of NPIs significantly impacted the spread of MP, altering population characteristics including age, seasonality, macrolide resistance, and MP co-infection rates.

The evaluation of the General Health Questionnaire (GHQ-12) reliability generalization: A meta-analysis.

The General Health Questionnaire (GHQ-12) is widely used for detecting psychiatric disorders, but its reliability across different populations remains to be determined. This meta-analysis aims to evaluate the reliability of GHQ-12 across varied cultural and demographic settings. This meta-analysis evaluates the reliability of General Health Questionnaire [GHQ-12]' across diverse populations, employing a systematic search strategy and rigorous inclusion criteria. This meta-analysis evaluates the General Health Questionnaire (GHQ-12) using a pre-registered protocol (CRD42023488436) to ensure unbiased results. Data from 20 studies published between 2016-2023 were analysed using a random-effects model, with quality assessment guided by COSMIN Risk of Bias and QUADAS-2. This study enhances our understanding of GHQ-12's psychometric properties. For the GHQ-12 subscales, Cronbach's alpha coefficients were 0.72 (90% CI [0.68, 0.75]) for anxiety and depression, 0.82 (90% CI [0.79, 0.86]) for social dysfunction, and 0.72 (90% CI [0.68, 0.76]) for loss of confidence. However, the analysis showed substantial heterogeneity (I2 = 90.04%), with significant variability in reliability estimates across different studies. The overall Cronbach's alpha was 0.84 (95% Cl [0.810, 0.873]) with SE = 0.016 (90% CI [0.68, 0.82], p < .05), indicating moderate to high internal consistency. Quantifying heterogeneity revealed a substantial level (se = 0.0016, I2 = 96.7%), signifying considerable variability in the reliability estimate among the studies. Results further show Cronbach's alpha coefficients range from 0.82 to 0.85 (95% Cl [0.77, 0.86 to 0.81, 0.90]) for the GHQ 12 items. While reaffirming the GHQ-12's utility in mental health assessment, our findings urge a more cautious and context-aware application of the questionnaire. The substantial heterogeneity and variability in reliability scores indicate a need for further research. Future studies should explore the reasons behind this variability, focusing on cultural, socio-economic, and methodological factors that might influence the GHQ-12's reliability. This critical analysis underscores the need for a deeper understanding of the GHQ-12's applicability and the importance of tailoring mental health assessment tools to specific population characteristics.

Use of Population Weighted Density Index for Coronavirus Spread in the United States

Background: Understanding how population density affected the transmission of COVID-19 is vitally important, since crowded cities were the epicenters for the disease. Since human contact was the main cause of the spread, population-weighted densities have been shown to be a better measure than conventional densities, since the variation in density across subareas matters more than the density in the total area. Objectives: This study investigates the impact of population-weighted density and other demographics on the rate of COVID-19 spread in the United States. Methods: The study considers population-weighted density and many other demographics. The population-weighted density index is the weighted average of density across the tracts, where tracts are weighted by population. Multivariate analysis has been used to determine the elasticity of the spread. Results: Using U.S. county-level data, we calculated the elasticity of COVID-19 spread with respect to population-weighted density to be 0.085 after controlling for other factors. In addition to the density, the proportion of people over 65 years of age, the number of total healthcare workers, and average temperature in each county positively contributed to the case numbers, while education level and income per capita had a negative effect. Discussion: For the spread, understanding the population characteristics and dynamics is as important as understanding the infectious disease itself. This will help policy makers to utilize and reallocate the resources more effectively. If the spread is successfully contained early, there will be less stress placed upon the healthcare system, resulting in better healthcare access for those who are sick. Conclusions: Our analysis suggests that population-weighted density can be a useful tool to control and manage outbreaks, especially within the early stage of the spread. We presented the early dynamics of the spread and recommended a policy measure on how to transfer healthcare workers from low-spread-risk areas to high-spread-risk areas to utilize resources better.

Validation of a Demography-Based Adaptive QTc Formula using Pediatric and Adult Datasets Acquired from Humans and Guinea Pigs.

A variety of QT rate-correction (QTc) formulae have been utilized for both clinical and research purposes. However, these formulae are not universally effective, likely due to significant influences of demographic diversity on the QT-HR relationship. To address this limitation, we proposed an adaptive QTc (QTcAd) formula that adjusts to subject demographics (i.e., age). Further, we compared the efficacy and accuracy of the QTcAd formula to other widely used alternatives. Using age as a demographic parameter, we tested the QTcAd formula across diverse age groups with different heart rates (HR) in both humans and guinea pigs. Utilizing retrospective human (n=1360) and guinea pig electrocardiogram (ECG) data from in-vivo (n=55) and ex-vivo (n=66) settings, we evaluated the formula's effectiveness. Linear regression fit parameters of HR-QTc (slope and R²) were utilized for performance assessment. To evaluate the accuracy of the predicted QTc, we acquired epicardial electrical and optical voltage data from Langendorff-perfused guinea pig hearts. In both human subjects and guinea pigs, the QTcAd formula consistently outperformed other formulae across all age groups. For instance, in a 20-year-old human group (n=300), the QTcAd formula successfully nullified the inverse HR-QT relationship (R²=5.1E-09, slope=-3.5E-05), while the Bazett formula (QTcB) failed to achieve comparable effectiveness (R²= 0.20, slope=0.91). Moreover, the QTcAd formula exhibited better accuracy than the age-specific Benatar formula (QTcBe), which overcorrected QTc (1-week human QT: 263.8±14.8 ms, QTcAd: 263.8±7.3 ms, p=0.62; QTcBe: 422.5±7.3 ms, p<0.0001). The optically measured pseudo-QT interval (143±22.5 ms, n=44) was better approximated by QTcAd (180.6±17.0 ms) compared to all other formulae. Furthermore, we demonstrated that the QTcAd formula was not inferior to individual-specific QTc formulae. The demography-based QTcAd formula showed superior performance across human and guinea pig age groups, which may enhance the efficacy of QTc for cardiovascular disease diagnosis, risk stratification, and drug safety testing. Corrected QT (QTc) is a well-known ECG biomarker for cardiovascular disease risk stratification and drug safety testing. Various QT rate-correction formulae have been developed, but these formulae do not perform consistently across diverse datasets (e.g., sex, age, disease, species). We introduce a novel QTc formula (QTcAd) that adapts to demographic variability, as the parameters can be modified based on the characteristics of the study population. The formula (QTcAd = QT + (|m|*(HR-HR mean )) - includes the absolute slope (m) of the linear regression of QT and heart rate (HR) and the mean HR of the population (HR mean ) as population characteristics parametersˍUsing datasets from both pediatric and adult human subjects and an animal model, we demonstrate that the QTcAd formula is more effective at eliminating the QT-HR inverse relationship, as compared to other commonly used correction formulae.

Prevalence of Belching Disorders and Their Characteristics in the General Adult Population.

Excessive bothersome belching is clinically problematic and the Rome IV classification categorizes belching disorders as gastroduodenal disorders. A total of 10,000 Japanese adults participated in this web-based survey. We aimed to examine the prevalence of belching disorders and their characteristics. Belching disorders were found in 151 (1.5%) adults. The presence of reflux esophagitis, thyroid diseases, gastroesophageal reflux disease, functional dyspepsia, full eaters, or a small or large number of mastication was significantly associated with an increased odds ratio of belching disorders. A detailed epidemiology of belching disorders in adults was clarified.

CD147 TagSNP is associated with the vulnerability to lung cancer in the Chinese population: a case–control study

BackgroundLung cancer, with its high morbidity and mortality, presents a major significant public health challenge. CD147, linked to cancer progression and metastasis, is a promising therapeutic target, including for lung cancer. The genetic variation may influence the expression of the gene and consequently the risk of lung cancer. This study aims to investigate single nucleotide polymorphisms (SNPs) in CD147 to understand their association with the risk of developing lung cancer in the Han Chinese population.MethodsA hospital-based case–control investigation was conducted, enrolling 700 lung cancer patients and 700 cancer-free controls. TagSNPs were selected using Haploview v4.2, and genotype data from the 1000 Genomes Project database were utilized. The selected SNPs (rs28992491, rs67945626, and rs79361899) within the CD147 gene were evaluated using the improved multiple ligation detection reaction method. Statistical analysis included chi-square tests, logistic regression models, and interaction analyses.ResultsBaseline characteristics of the study population showed no significant differences in gender distribution between cases and controls, but there was a notable difference in smoking rates. No significant associations were found between the three TagSNPs and lung cancer susceptibility in the codominant model. However, stratification analyses revealed interesting findings. Among females, the rs79361899 AA/AG genotype was associated with an increased risk of lung cancer. In individuals aged ≥ 65 years old, the rs28992491 GG and rs79361899 AA genotypes were linked to a higher susceptibility. Furthermore, an interaction analysis demonstrated significant genotype × gender interactions in the rs79361899 recessive model, indicating an increased lung cancer risk in female carriers of the heterozygous or homozygous polymorphic genotype.ConclusionsCD147 polymorphisms play an important role in lung cancer development, particularly in specific subgroup of age and gender. These findings highlight the significance of incorporating genetic variations and their interactions with demographic factors in comprehending the intricate etiology of lung cancer.

Interacting with the farthest neighbor promotes cohesion and polarization in collective motion

The collective behavior generated from self-organization is one of the most prominent characteristics of animal populations. Typically, it is assumed that the interactions between individuals are average and synchronous. However, recent empirical studies have shown that interactions between individuals are selective and update their positions and directions asynchronously. Especially the feature factor of distance is widely used in theoretical modeling, but there is no detailed analysis and discussion on it in pairwise interaction. In this work, the effect of pairwise interactions on group motion is investigated under three distance features: nearest, medium, and farthest, based on a self-propelled particle model and combined with an asynchronous update scheme. The research results indicate that simple pairwise interaction can achieve group-level cohesion, especially by selecting the farthest neighbor instead of only interacting with the nearest neighbor, and the proportion of topological neighbors required to achieve cohesion is independent of the group size. In addition, we found that there is a visual angle range that is conducive to achieving cohesion and consistent movement in the group. This study provides insight into selective interaction, especially the great significance of the distance factor in pairwise interaction.

Analyzing pain patterns in the emergency department: Leveraging clinical text deep learning models for real-world insights

ObjectiveTo determine the incidence of patients presenting in pain to a large Australian inner-city emergency department (ED) using a clinical text deep learning algorithm. Materials and methodsA fine-tuned, domain-specific, transformer-based clinical text deep learning model was used to interpret free-text nursing assessments in the electronic medical records of 235,789 adult presentations to the ED over a three-year period. The model classified presentations according to whether the patient had pain on arrival at the ED. Interrupted time series analysis was used to determine the incidence of pain in patients on arrival over time. We described the changes in the population characteristics and incidence of patients with pain on arrival occurring with the start of the Covid-19 pandemic. Results55.16% (95%CI 54.95%–55.36%) of all patients presenting to this ED had pain on arrival. There were differences in demographics and arrival and departure patterns between patients with and without pain. The Covid-19 pandemic initially precipitated a decrease followed by a sharp, sustained rise in pain on arrival, with concurrent changes to the population arriving in pain and their treatment. DiscussionApplying a clinical text deep learning model has successfully identified the incidence of pain on arrival. It represents an automated, reproducible mechanism to identify pain from routinely collected medical records. The description of this population and their treatment forms the basis of intervention to improve care for patients with pain. The combination of the clinical text deep learning models and interrupted time series analysis has reported on the effects of the Covid-19 pandemic on pain care in the ED, outlining a methodology to assess the impact of significant events or interventions on pain care in the ED. ConclusionApplying a novel deep learning approach to identifying pain guides methodological approaches to evaluating pain care interventions in the ED, giving previously unavailable population-level insights.

Evaluating flood hazards in data-sparse coastal lowlands: highlighting the Ayeyarwady Delta (Myanmar)

Coastal lowlands and river deltas worldwide are increasingly exposed to coastal, pluvial and fluvial flooding as well as relative sea-level rise (RSLR). However, information about both single and multiple flood-type hazards, their potential impact and the characteristics of areas, population and assets at risk is often still limited as high-quality data either does not exist or is not accessible. This often constitutes a main barrier for generating sound assessments, especially for scientific and public communities in the so-called Global South. We provide a standardised, integrative approach for the first-order assessment of these single and multiple flood-type hazards and show how this can be conducted for data-sparse, hardly accessible and inaccessible coastal lowlands such as the Ayeyarwady Delta in Myanmar by using only open accessible and freely available datasets of satellite imagery, global precipitation estimates, satellite-based river discharge measurements, elevation, land use, and population data. More than 70% of the delta, mainly used for agriculture, and about 40% of its present population are prone to flooding due to either monsoon precipitation and runoff, storm surge, and RSLR, or their combination, jeopardising food security and economic development in the region. The approach allows for the integration and combination of various datasets, combined in a highly flexible workflow that performs at low computational capacities, supporting the evaluation of flood-prone areas on regional and local scale for data-sparse coastal lowlands worldwide. It thereby allows to attribute different types of flood hazards, complements concepts of vulnerability and risk, and supports risk-informed decision making and development of effective multi-flooding adaptation strategies.

Considering pregnancies as repeated vs independent events: an empirical comparison of common approaches across selected perinatal outcomes

BackgroundIn population-based research, pregnancy may be a repeated event. Despite published guidance on how to address repeated pregnancies to the same individual, a variety of approaches are observed in perinatal epidemiological studies. While some of these approaches are supported by the chosen research question, others are consequences of constraints inherent to a given dataset (eg, missing parity information). These decisions determine how appropriately a given research question can be answered and overall generalizability. ObjectiveTo compare common cohort selection and analytic approaches used for perinatal epidemiological research by assessing the prevalence of two perinatal outcomes and their association with a clinical and a social independent variable. Study DesignUsing vital records linked to maternal hospital discharge records for singleton births, we created four cohorts: (1) all-births (2) randomly selected one birth per individual (3) first-observed birth per individual (4) primiparous-births (parity 1). Sampling of births was not conditional on cluster (ie, we did not sample all births by a given mother, but rather sampled individual births). Study outcomes were severe maternal morbidity (SMM) and preeclampsia/eclampsia, and the independent variables were self-reported race/ethnicity (as a social factor) and systemic lupus erythematosus. Comparing the four cohorts, we assessed the distribution of maternal characteristics, the prevalence of outcomes, overall and stratified by parity, and risk ratios (RR) for the associations of outcomes with independent variables. Among all-births, we then compared RR from three analytic strategies: with standard inference that assumes independently sampled births to the same mother in the model, with cluster-robust inference, and adjusting for parity. ResultsWe observed minor differences in the population characteristics between the all-birth (N=2736,693), random-selection, and first-observed birth cohorts (both N=2284,660), with more substantial differences between these cohorts and the primiparous-births cohort (N=1054,684). Outcome prevalence was consistently lowest among all-births and highest among primiparous-births (eg, SMM 18.9 per 1000 births among primiparous-births vs 16.6 per 1000 births among all-births). When stratified by parity, outcome prevalence was always the lowest in births of parity 2 and highest among births of parity 1 for both outcomes. RR differed for study outcomes across all four cohorts, with the most pronounced differences between the primiparous-birth cohort and other cohorts. Among all-births, robust inference minimally impacted the confidence bounds of estimates, compared to the standard inference, that is, crude estimates (eg, lupus-SMM association: 4.01, 95% confidence intervals [CI] 3.54–4.55 vs 4.01, 95% CI 3.53–4.56 for crude estimate), while adjusting for parity slightly shifted estimates, toward the null for SMM and away from the null for preeclampsia/eclampsia. ConclusionResearchers should consider the alignment between the methods they use, their sampling strategy, and their research question. This could include refining the research question to better match inference possible for available data, considering alternative data sources, and appropriately noting data limitations and resulting bias, as well as the generalizability of findings. If parity is an established effect modifier, stratified results should be presented.

Effectiveness of behavioural interventions with motivational interviewing on physical activity outcomes in adults: systematic review and meta-analysis

ObjectiveTo evaluate the effectiveness of behavioural interventions that include motivational interviewing on physical activity outcomes in adults.DesignSystematic review and meta-analysis.Study selectionA search of seven databases for randomised controlled trials published...

Characteristics and survival of advanced untreated hepatocellular carcinoma of non-viral etiology.

Hepatocellular carcinoma (HCC) is an aggressive tumor and presents late. The underlying etiology of HCC is changing rapidly. HCC in Sri Lanka is unique due to its predominant non-viral etiology (nvHCC) but lacks survival data. Data was collected from patients who presented with HCC from 2011 to 2018. There were 560/568 (98.6%) nvHCC. The patients who were not candidates for tumor-specific treatment (149/560 [26.7%]) were selected. Population characteristics, demographic data, tumor characteristics, survival and factors affecting survival were analyzed. The median age was 64years (range 30-88) and 86% (n = 129) were males. As many as124 (83%) were cirrhotic. The overall performance score was 80%.Nearly 21/124 tumors were detected in cirrhotic screening. Tumors were single nodular in 32 (21%), up to three nodules in 28 (18%), more than three nodules in 33 (22%) and diffusely infiltrating in 56 (37%). The major venous invasions were present in 78 (52.3%). Extra-hepatic tumor spread was seen in 19 (12.7%) (lungs 13[72.2%], bones 2 [11.1%]). The median survival of patients receiving palliative care was three months (1-43months). Tumor size and cirrhotic status were significant predictors in univariate analysis. A quarter of nvHCCs were not amenable to treatment at presentation as they had dismal survival. P/126/09/2021.

The cost of living crisis – how does it impact the health and life of individuals? A survey exploring perceptions in Italy, Germany, Sweden and the United Kingdom

BackgroundThe Cost of Living Crisis (CoLC), a real term reduction in basic income, risks individuals being unable to afford essentials such as heat, food and clothing. The impact of the CoLC is disproportionate – with different population sub-groups more likely to be negatively affected. The objective of this survey was to evaluate the perceived impact of the CoLC on the life and health of participants across four European countries.MethodsA survey housing two questions to investigate the relationship between the CoLC and its perceived impact on life and health was developed. Four European countries (U.K., Sweden, Italy and Germany) took part via the YouGov platform. Logistic regression models were created for each country and question to evaluate which population characteristics were associated with a negative reported impact of the CoLC.ResultsA total of 8,152 unique individuals responded between 17th March and 30th March 2023. Each country was equally represented. Those aged 36–64 were more likely to report a negative impact of the CoLC on their life and health than younger participants (p < 0.001, p = 0.02 respectively). Across all countries, females were significantly more likely to report a negative impact on their life and health, however, when analysed according to country, in Sweden females were less likely to report a negative impact (p < 0.001). Those in lower income families or who reported poor health in the preceding 12 months were significantly more likely to report a negative impact of the CoLC on their life and health. There was no difference within the participant group on the reported impact of the CoLC based on location (rural vs. urban).ConclusionsWe demonstrate the disproportionate negative impact of the CoLC on both life and health in different population subgroups. Germany and Sweden appeared to be more resilient to the effects of the CoLC, particularly for certain population subgroups. It is important to understand the differing effects of a CoLC, and to learn from successful health and economic strategies in order to create targeted policy and create a population resilient to economic shocks.

Psychosocial characteristics of the general population who habitually use hypnotics: Results from a national survey on drug use among the Japanese.

The aim of this study was to examine the characteristics of habitual hypnotic users in Japan. This nationwide, cross-sectional survey used self-administered questionnaires. Data were collected from four national surveys conducted every 2 years between 2015 and 2021. The participants were Japanese individuals who had taken prescription hypnotics in the past year or had never taken them. We divided 13,396 participants into three groups to compare the social background and status of taking medication and controlled drugs, drinking, and smoking among the three groups: people who use hypnotics habitually daily (habitual hypnotic users [HUs]), people who use them only occasionally (occasional hypnotic users [OUs]), and people who do not use them (hypnotic non-users [NUs]). We compared the perception of using hypnotics between the HU and OU groups. HUs were more likely to be older, unemployed, and to habitually use anxiolytics and analgesics than NUs. The main reasons for taking anxiolytics in HUs were alleviating insomnia and reducing anxiety, whereas the main reason for taking analgesics was improving joint pain. Additionally, the HU group had a higher proportion of habitual smokers than the OU group. There was no difference in drinking status or taking of controlled drugs among the three groups. HUs were more likely to use hypnotics and to have concerns about their side-effects than OUs. HUs were more likely to be unemployed, habitually use anxiolytics and analgesics, smoke heavily, and take hypnotic drugs with concerns regarding side-effects. These results may help encourage the appropriate use of hypnotics.

Blastocystis colonization and associations with population parameters in Thai adults.

Blastocystis is a unicellular eukaryote commonly found in the intestinal tract of humans and other animals. The prevalence of Blastocystis has been investigated in both developed and developing countries, yet its occurrence and distribution in rural locations has been less studied. Herein, we aimed to examine the distribution of Blastocystis colonization in Thai adults representing background populations along a rural/peri-urban gradient, as well as associations between colonization and personal characteristics. A total of 238 participants were recruited from rural and peri-urban areas situated in three provinces. The presence of Blastocystis in feces was evaluated using PCR and qPCR. Information on gender, age, region (province), rural/peri-urban location, and body mass index (BMI) was collected. The overall rate of Blastocystis carriage was 67.2%. Univariate analysis revealed significant associations between Blastocystis carriage and region (p<0.05), location (p<0.001) and age group (p<0.05). Logistic regression analysis revealed that rural/peri-urban location and BMI were significantly associated with Blastocystis carriage. Nine subtypes (ST1-ST7, ST10 and ST23) were identified with ST3, ST7 and ST1 as the most abundant ones, in this order. The greatest diversity of subtypes, in terms of numbers, was found in the middle aged group (nine subtypes), while the least diversity was found in the young adult and obese (three subtypes each) groups. This study increases the understanding of the epidemiology of Blastocystis colonization and its association with population parameters and characteristics in middle-income countries.