Age and gender differences in the relationship between chronic pain and dementia amongst older Australians.

OBJECTIVES: Chronic pain is a highly debilitating condition that affects older adults and has the potential to increase their odds of experiencing cognitive impairment. The primary objective of this study was to examine the correlation between chronic pain and dementia. Additionally, this research endeavours to ascertain whether the association between chronic pain and dementia differs by age and gender. METHODS: Cross-sectional data were derived from the Survey of Disability, Ageing and Carers (SDAC). A total of 20,671 and 20,081 participants aged 65 years and older in 2015 and 2018, respectively, were included in this study. The pooled association between chronic pain and dementia was assessed using a multivariable logistic regression model. Furthermore, the study also examined the multiplicative interaction effects between chronic pain and age, as well as chronic pain and gender, with dementia. RESULTS: The pooled analysis demonstrated that chronic pain was associated with a heightened odds of dementia (Adjusted Odds Ratio [AOR]=1.95, 95%CI: 1.85-2.05) amongst older Australians than their counterparts without chronic pain. The interaction effect indicated that individuals with chronic pain across all age groups exhibited increased odds of living with dementia. Additionally, women with chronic pain had higher odds of dementia compared to their counterparts without chronic pain and being male. CONCLUSIONS: A continuous, coordinated, and tailored healthcare strategy is necessary to determine the pain management goals and explore early treatment options for chronic pain in older adults, particularly in groups with the greatest need.

Rural‒urban disparities in household catastrophic health expenditure in Bangladesh: a multivariate decomposition analysis.

BACKGROUND: Rural‒urban disparity in catastrophic healthcare expenditure (CHE) is a well-documented challenge in low- and middle-income countries, including Bangladesh, limiting financial protection and hindering the achievement of the Universal Health Coverage target of the United Nations Sustainable Development Goals. However, the factors driving this divide remain poorly understood. Therefore, this study aims to identify the key determinants of the rural‒urban disparity in CHE incidence in Bangladesh and their changes over time. METHODS: We used nationally representative data from the latest three rounds of the Bangladesh Household Income and Expenditure Survey (2005, 2010, and 2016). CHE incidence among households seeking healthcare was measured using the normative food, housing, and utilities method. To quantify covariate contributions to the rural‒urban CHE gap, we employed the Oaxaca-Blinder multivariate decomposition approach, adapted by Powers et al. for nonlinear response models. RESULTS: CHE incidence among rural households increased persistently during the study period (2005: 24.85%, 2010: 25.74%, 2016: 27.91%) along with a significant (p-value ≤ 0.01) rural‒urban gap (2005: 9.74%-points, 2010: 13.94%-points, 2016: 12.90%-points). Despite declining over time, substantial proportions of CHE disparities (2005: 87.93%, 2010: 60.44%, 2016: 61.33%) are significantly (p-value ≤ 0.01) attributable to endowment differences between rural and urban households. The leading (three) covariate categories consistently contributing significantly (p-value ≤ 0.01) to the CHE gaps were composition disparities in the lowest consumption quintile (2005: 49.82%, 2010: 36.16%, 2016: 33.61%), highest consumption quintile (2005: 32.35%, 2010: 15.32%, 2016: 18.39%), and exclusive reliance on informal healthcare sources (2005: -36.46%, 2010: -10.17%, 2016: -12.58%). Distinctively, the presence of chronic illnesses in households emerged as a significant factor in 2016 (9.14%, p-value ≤ 0.01), superseding the contributions of composition differences in household heads with no education (4.40%, p-value ≤ 0.01) and secondary or higher education (7.44%, p-value ≤ 0.01), which were the fourth and fifth significant contributors in 2005 and 2010. CONCLUSIONS: Rural‒urban differences in household economic status, educational attainment of household heads, and healthcare sources were the key contributors to the rural‒urban CHE disparity between 2005 and 2016 in Bangladesh, with chronic illness emerging as a significant factor in the latest period. Closing the rural‒urban CHE gap necessitates strategies that carefully address rural‒urban variations in the characteristics identified above.

Machine learning models for prediction of double and triple burdens of non-communicable diseases in Bangladesh.

Increasing prevalence of non-communicable diseases (NCDs) has become the leading cause of death and disability in Bangladesh. Therefore, this study aimed to measure the prevalence of and risk factors for double and triple burden of NCDs (DBNCDs and TBNCDs), considering diabetes, hypertension, and overweight and obesity as well as establish a machine learning approach for predicting DBNCDs and TBNCDs. A total of 12,151 respondents from the 2017 to 2018 Bangladesh Demographic and Health Survey were included in this analysis, where 10%, 27.4%, and 24.3% of respondents had diabetes, hypertension, and overweight and obesity, respectively. Chi-square test and multilevel logistic regression (LR) analysis were applied to select factors associated with DBNCDs and TBNCDs. Furthermore, six classifiers including decision tree (DT), LR, naïve Bayes (NB), k-nearest neighbour (KNN), random forest (RF), and extreme gradient boosting (XGBoost) with three cross-validation protocols (K2, K5, and K10) were adopted to predict the status of DBNCDs and TBNCDs. The classification accuracy (ACC) and area under the curve (AUC) were computed for each protocol and repeated 10 times to make them more robust, and then the average ACC and AUC were computed. The prevalence of DBNCDs and TBNCDs was 14.3% and 2.3%, respectively. The findings of this study revealed that DBNCDs and TBNCDs were significantly influenced by age, sex, marital status, wealth index, education and geographic region. Compared to other classifiers, the RF-based classifier provides the highest ACC and AUC for both DBNCDs (ACC = 81.06% and AUC = 0.93) and TBNCDs (ACC = 88.61% and AUC = 0.97) for the K10 protocol. A combination of considered two-step factor selections and RF-based classifier can better predict the burden of NCDs. The findings of this study suggested that decision-makers might adopt suitable decisions to control and prevent the burden of NCDs using RF classifiers.

Genome mining for ribosomally synthesized and post-translationally modified peptides (RiPPs) in Streptomyces bacteria.

Ribosomally synthesized post-translationally modified peptides (RiPPs) are a novel category of bioactive natural products (NPs). Streptomyces bacteria are a potential source of many bioactive NPs. Limited opportunities are available to characterize all the bioactive NP gene clusters. In this study, 410 sequences of Streptomyces were analyzed for RiPPs through genome mining using the National Center for Biotechnology Information (NCBI), by combining BAGEL and anti-SMASH. A total of 4098 RiPPs were found; including both classified (lanthipeptide, RiPP-like, bacteriocin, LAPs, lassopeptide, thiopeptides) and nonclassified RiPPs. Soil was identified as a rich habitat for RiPPs. These data may offer alternative future remedies for various health issues.

A Systematic Literature Review of Substance-Use Prevention Programs Amongst Refugee Youth.

This paper aims at exploring existing literature on substance use prevention programs, focusing on refugee youth. A comprehensive search for relevant articles was conducted on Scopus, PubMed, and EBSCOhost Megafile databases including Academic Search Ultimate, APA PsycArticles, APA PsycInfo, CINAHL with Full Text, E-Journals, Humanities Source Ultimate, Psychology and Behavioural Sciences Collection, and Sociology Source Ultimate. Initially, a total of 485 studies were retrieved; nine papers were retained for quality assessment after removing duplicates. Of the nine studies that met the inclusion criteria, only three are found to partially addressed substance use prevention programs. The two substance use prevention programs that emerge from the study are Adelante Social and Marketing Campaign (ASMC), and Screening and Brief Intervention (SBI). Six others explored protective factors and strategies for preventing substance use. The study findings show that refugee youth held negative attitudes toward institutions that provide substance use prevention programs. This review concluded that refugee youth often experience persistent substance use as they are not aware of prevention programs that may reduce the prevalence and/or severity of such misuse.

Impact of prenatal maternal dietary exclusion on childhood obesity and overweight risk.

BACKGROUND: Child birthweight is a measure of fetal nutrition that is primarily determined by prenatal maternal (PM) diet. Child birthweight and child obesity/overweight risk are well established to be linked. Nevertheless, no studies have investigated the impact of PM dietary exclusion on child obesity/overweight risk or body mass index z-score (BMIz). OBJECTIVES: The study aimed to determine whether PM dietary exclusion affected the child's BMIz, obesity/overweight risk, whether child birthweight serves as a mediator of this, and whether PM use of dietary supplements can protect against this. METHODS: Waves within the years 2004-2019 from the Longitudinal Study of Australian Children, a population-based cohort study, were analyzed. The participants were aged 0 to 15 years during these waves of the study. Analysis was conducted using logistic and linear models. A total of 5,107 participants were involved in the first wave of the study. RESULTS: The PM exclusion of fish was associated with a higher risk of being underweight at age 14 or 15 years and mild-to-moderate obesity at age 6 or 7 years. The PM exclusion of egg was associated with a higher risk of being overweight at age 14 or 15 years. The exclusion of dairy was associated with more mixed effects. Mediation effects did not reach statistical significance. Moderation effects involving PM dietary supplement use, when they did occur, were associated with higher child BMIz and usually a higher risk of obesity/overweight. CONCLUSIONS: Fish and eggs are likely important parts of PM diets for preventing childhood obesity and overweight. Further studies will be needed to determine reasons for this and the apparent adverse effects of dietary supplements on overweight/obesity risk.

Socio-demographic factors and mental health trajectories in Australian children and primary carers: Implications for policy and intervention using latent class analysis.

Children's mental health status (MHS) is frequently influenced by their primary carers (PCs), underscoring the significance of monitoring disparities longitudinally. This research investigated the association between socio-demographic clusters and mental health trajectories among children and their PCs over time. Data from waves 6-9c2 of the Longitudinal Study of Australian Children (LSAC) were analyzed using Latent Class Analysis (LCA) to identify four socio-demographic classes among children aged 10-11 years at wave 6. Multinomial logistic regression and predictive marginal analysis explored associations between classes and mental health outcomes. PCs in Class 4 (disadvantaged and separated families with indigenous children) exhibited higher odds of borderline and abnormal MHS compared to Class 1 (prosperous and stable working families) across all waves. However, while MHS of PCs' impacted children consistently, the association with socio-demographic classes was significant only in wave 6. Class 4 children had elevated risks of mental illness compared to Class 1, while Class 3, characterized by educated working mothers, had lower risks. Reducing mental health risks entails addressing socio-economic disparities, supporting stable family structures, and offering tailored interventions like counseling and co-parenting support. Longitudinal monitoring and culturally sensitive approaches are crucial for promoting mental well-being across diverse groups.

Can digital innovation transform rural primary health care? A systematic review protocol.

INTRODUCTION: Digital technology is increasingly being adopted within primary healthcare services to improve service delivery and health outcomes; however, the scope for digital innovation within primary care services in rural areas is currently unknown. This systematic review aims to synthesise existing research on the use and integration of digital health technology within primary care services for rural populations across the world. METHODS AND ANALYSIS: A systematic approach to the search strategy will be conducted. Relevant medical and healthcare-focused electronic databases will be searched using key search terms between January 2013 and December 2023. Searches will be conducted using specific inclusion and exclusion criteria. A systematic study selection and data extraction process will be implemented, using standardised templates. Outcomes will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-analyses- Protocol statement guidelines. Quality assessment and risk of bias appraisal will be conducted using the Mixed Methods Appraisal Tool. ETHICS AND DISSEMINATION: Ethical approval will not be required because there is no individual patient data collected or reviewed. The finding of this review will be disseminated through peer-reviewed publications and conference presentations. Outcomes will help to understand existing knowledge and identify gaps in delivering digital healthcare services, while also providing potential future practice and policy recommendations. PROSPERO REGISTRATION NUMBER: CRD42023477233.