Large household reduces dementia mortality: A cross-sectional data analysis of 183 populations

Background: Large households/families may create more happiness and offer more comprehensive healthcare among the members. We correlated household size to dementia mortality rate at population level for analysing its protecting role against dementia mortality. Methods: This is a retrospective cross-sectional study. Dementia specific mortality rates of the 183 member states of World Health Organization were calculated and matched with the respective country data on household size, Gross Domestic Product (GDP), urban population and ageing. Scatter plots were produced to explore and visualize the correlations between household size and dementia mortality rates. Pearson's and nonparametric correlations were used to evaluate the strength and direction of the associations between household size and all other variables. Partial correlation of Pearson's approach was used to identify that household size protects against dementia regardless of the competing effects from ageing, GDP and urbanization. Multiple regression was used to identify significant predictors of dementia mortality. Results: Household size was in a negative and moderately strong correlation (r = -0.6034, p < 0.001) with dementia mortality. This relationship was confirmed in both Pearson r (r = - 0.524, p<0.001) and nonparametric (rho = -0.579, p < 0.001) analyses. When we controlled for the contribution of ageing, socio-economic status and urban lifestyle in partial correlation analysis, large household was still in inverse and significant correlation to dementia mortality (r = -0.331, p <0.001). This suggested that, statistically, large household protect against dementia mortality regardless of the contributing effects of ageing, socio-economic status and urban lifestyle. Stepwise multiple regression analysis selected large household as the variable having the greatest contribution to dementia mortality with R2 = 0.263 while ageing was placed second increasing R2 to 0.259. GDP and urbanization were removed as having no statistically significant influence on dementia mortality. Conclusions: While acknowledging ageing, urban lifestyle and greater GDP associated with dementia mortality, this study suggested that, at population level, household size was another risk factor for dementia mortality. As part of dementia prevention, healthcare practitioners should encourage people to increase their positive interactions with persons from their neighbourhood or other fields where large household/family size is hard to achieve

Significantly different roles of economic affluence in sex-specific obesity prevalence rates: understanding more modifications within female body weight management

Socioeconomic status has been associated with obesity prevalence increase in both males and females worldwide. We examined the magnitude of the difference between the two relationships and explored the independence of both relationships. Country specific data on gross domestic product (GDP) per capita, sex-specific obesity prevalence rates, urbanisation, total calories availability and level of obesity, genetic background accumulation (measured by the Biological State Index, Ibs) were obtained for 191 countries. Curvilinear regressions, bivariate and partial correlations, linear mixed models and multivariate linear regression analyses were used to examine the relationship between GDP and obesity prevalence rates in males and females respectively. Fisher's r-to-z transformation, F-test and R2 increment in multivariate regression were used to compare results for males and females. GDP significantly correlated with sex-specific obesity prevalence rates, but significantly more strongly with male obesity prevalence in bivariate correlation analyses. These relationships remained independent of calories availability, Ibs and urbanization in partial correlation model. Stepwise multiple regression identified that GDP was a significant predictor of obesity prevalence in both sexes. Multivariate stepwise regression showed that, when adding GDP as an obesity prevalence predictor, the absolute increment of R2 in male fit model (0.046) was almost four (4) times greater than the absolute increment in female model fit (0.012). The Stepwise analyses also revealed that 68.0% of male but only 37.4% of female obesity prevalence rates were explained by the total contributing effects of GDP, Ibs, urbanization and calories availability. In both Pearson's r and nonparametric analyses, GDP contributes significantly more to male obesity than to female obesity in both developed and developing countries. GDP also determined the significant regional variation in male, but not female obesity prevalence. GDP may contribute to obesity prevalence significantly more in males than in females regardless of the confounding effects of Ibs, urbanization and calories. This may suggest that aetiologies for female obesity are much more complex than for males and more confounders should be included in the future studies when data are available

Ecological approach to investigations of noncommunicable health challenges: cancers, diabetes mellitus and obesity at the world population level

Globally, cancers, diabetes mellitus and obesity have emerged as the major health and development challenges which are responsible for millions of deaths annually. Population-based prevention strategies have been advocated and adopted as a public health approach. However, unfortunately, no country has achieved their expected results in the past 30 years. An important way to control cancers, diabetes mellitus and obesity is to focus on reducing the risk factors associated with these non-communicable diseases. However, previous case or cohort studies into the risk factors associated with the three epidemics have controversial findings which may be the results of circumstantial study designs. It may be necessary to use broadly based ecological study to obtain new insights into the associations between risk factors and epidemic at population level. The international health organizations, such as the WHO and the International Diabetes Federation (IDF) monitor and publish country specific health data in relation to the cancer, diabetes and obesity. These data have been helping governments, policy-makers, funders and researchers track and investigate the priorities of health research and development based on public health needs and ensure that funds and resources are used to meet the priorities. In terms of tracking and investigating the risk factors of the epidemics, ecological studies have several advantages in study designs over case or cohort researches: 1) More risk factors can be included in the data analysis. 2) Cumulative/ prolonged effects of risk factors on epidemics can be considered in the studies through backdating the risk data. 3) The data on risk variables used in ecological studies are objective because they are collected independent from epidemiological data. In patient-based surveys or anonymised clinical records people with any disease tend to exaggerate negative life events in comparison to people with average or good health. For instance, obese people may misinform how much sugar they have consumed trying to appear more cautious in their dietary choices than they really are. With the advantages of ecological studies, this thesis seeks to show that reduced natural selection, nutrition/diet and birth behaviour may be independent predictors of the modern noncommunicable epidemics. To achieve this, we collected and analysed data from 191 countries across over 30 years in ten investigations: Natural selection is considered a force of evolution that adapts populations to their environments. However, humans manipulated their environments and supplemented natural properties of their bodies by medical procedures and technologies, so that natural selection no longer is a force of adaptation. Its operation as a force differentiating reproductive success of individuals has been seriously relaxed. This allows practically any person to pass their genes to the next generation, thus leading to accumulation of deleterious mutations whose effects are controlled by artificial means. In Investigations 1-3, it is proposed that modern humans may not be naturally well adapted to the current environment because their survival capacity and “fitness” have been maintained by application of high levels of medical services, nutrition and public health advocacy. The studies were conducted through analysing correlations between relaxed natural selection indexed by the Biological State Index (Is) with incidence rates of cancers and Type 1 diabetes mellitus, and prevalence rates of sex-specific obesity. Meat has been advocated as one of the major contributors to obesity prevalence because it contains high energy component of fat. It is a fact that selective breeding, butchery and cooking which aim for leanness (more protein) have minimized the fat intake in our daily diet. However, meat is still reported as a contributor to body weight increase significantly because of its protein content. Investigation 4 hypothesized that meat protein in modern diet may have been providing energy surplus to our daily life which contributes to obesity. The hypothesis was examined through analysing the correlations between obesity prevalence and total meat and meat protein consumption respectively. Both meat and sugar (sucrose) in our daily diet contain the slower digested component and cause insulin resistance. However, it is widely accepted that sugar has been a major contributor to obesity. The role of meat in this regard has not been widely recognised. Investigation 5 compared the use of sugar and meat to predict obesity prevalence worldwide showing that meat availability predicts increase of obesity to the same extent as sugar availability. Red meat and processed meat have been proposed as the major predictors of prostate cancer, but those studies are circumstantial, and the findings are controversial. Total meat (flesh) has not been associated with prostate cancer. Investigation 6 postulated that total meat (flesh) may be an independent predictor of prostate cancer. This postulation was examined using country specific data, from a global perspective, that population with more total meat consumption, may have higher incidence rate of prostate cancer, with empirical, macro-level data collected from the major international organizations. Gluten has been considered as the trigger of a number of diseases. Worldwide, incidence of gluten-related diseases is increasing. Wheat, the storage proteins, is the main source of gluten, but the adverse effects of wheat on obesity have not been tested. Investigation 7 analysed and compared the associations between obesity prevalence and wheat, rice and maize, and identified that wheat is the hidden risk factor of obesity. Contrarily, consumption of maize and rice showed the protective role in obesity prevalence. Therefore, the adverse effects of wheat on increasing body weight may have been covered by maize and rice when cereals consumption is advocated as the healthy diet component. Previous studies into the relationship between low parity and risk of cancers revealed that the decreasing number of children born into a family was associated with the risk of cancers of the mother and a few other cancers of family members. However, these studies did not identify that parity may be the most influential predictor of breast cancer and ovarian cancer. Neither did these studies show that greater parity has the protecting effects on developing site cancers of family members. Investigation 8 hypothesized that greater family size may protect the whole family from developing cancers. The hypothesis was examined through analysing relationships between total fertility rate, indexing family size and incidence rates of male and female cancers. Investigations 9 and 10 analysed and compared the contributing effects of multiple risk factors of female breast cancer and ovarian cancer and identified that low parity (indexed by birth rate) may be the most influential risk factor of female breast cancer and ovarian cancers respectively. The information gathered from the ten studies reveals that 1) Reduced natural selection may be the significant predictor of cancer, Type 1 diabetes and obesity; 2) Meat consumption may be the risk predictor of obesity and prostate cancer; 3) Wheat may be a hidden contributor to obesity prevalence worldwide. 4) The number of children born into a family may be the strong predictor of female breast cancer and ovarian cancer and it may be associated with the cancer risk of all family members. In general terms, the investigations presented in this thesis show that “ecological analyses” of worldwide data confirm known relationships between some risk factors and incidence/prevalence of non-communicable diseases and can reveal new, hitherto unknown relationships, that are interpretable in the context of human biology.Thesis (Ph.D.) -- University of Adelaide, Adelaide Medical School, 201

Healthcare services relaxing natural selection may contribute to increase of dementia incidence

Ageing and genetic traits can only explain the increasing dementia incidence partially. Advanced healthcare services allow dementia patients to survive natural selection and pass their genes onto the next generation. Country-specific estimates of dementia incidence rates (all ages and 15-49 years old), Biological State Index expressing reduced natural selection (Is), ageing indexed by life expectancy e(65), GDP PPP and urbanization were obtained for analysing the global and regional correlations between reduced natural selection and dementia incidence with SPSS v. 27. Worldwide, Is significantly, but inversely, correlates with dementia incidence rates for both all ages and 15-49 years old in bivariate correlations. These relationships remain inversely correlated regardless of the competing contributing effects from ageing, GDP and urbanization in partial correlation model. Results of multiple linear regression (enter) have shown that Is is the significant predictor of dementia incidence among all ages and 15-49 years old. Subsequently, Is was selected as the variable having the greatest influence on dementia incidence in stepwise multiple linear regression. The Is correlated with dementia incidence more strongly in developed population groupings. Worldwide, reduced natural selection may be yet another significant contributor to dementia incidence with special regard to developed populations

Meat consumption providing a surplus energy in modern diet contributes to obesity prevalence: an ecological analysis

Background: Excessive energy intake has been identified as a major contributor to the global obesity epidemic. However, it is not clear whether dietary patterns varying in their composition of food groups contribute. This study aims to determine whether differences in per capita availability of the major food groups could explain differences in global obesity prevalence. Methods: Country-specific Body Mass Index (BMI) estimates (mean, prevalence of obesity and overweight) were obtained. BMI estimates were then matched to mean of three year-and country-specific availability of total kilocalories per capita per day, major food groups (meat, starch, fibers, fats and fruits). The per capita Gross Domestic Product (GDP) and prevalence of physical inactivity for each country were also obtained. SPSS was used for log-transformed data analysis. Results: Spearman analyses of the different major food groups shows that meat availability is most highly correlated with prevalence of obesity (r = 0.666, p < 0.001) and overweight (r = 0.800, p < 0.001) and mean BMI (r = 0.656, p < 0.001) and that these relationships remain when total caloric availability, prevalence of physical inactivity and GDP are controlled in partial correlation analysis. Stepwise multiple linear regression analysis indicates that meat availability is the most significant predictors of prevalence of obesity and overweight and mean BMI among the food groups. Scatter plot diagrams show meat and GDP adjusted meat are strongly correlated to obesity prevalence. Conclusion: High meat availability is correlated to increased prevalence of obesity. Effective strategies to reduce meat consumption may have differential effects in countries at different stages of the nutrition transition

Cutaneous malignant melanoma incidence is strongly associated with European depigmented skin type regardless of ambient ultraviolet radiation levels: evidence from Worldwide population-based data

Current public health advice is that high ultraviolet radiation (UVR) exposure is the primary cause of Malignant Melanoma of skin (CMM), however, despite the use of sun-blocking products incidence of melanoma is increasing. To investigate the UVR influence on CMM incidence worldwide WHO, United Nations, World Bank databases and literature provided 182 country-specific melanoma incidence estimates, daily UVR levels, skin colour (EEL), socioeconomic status (GDP PPP), magnitude of reduced natural selection (Ibs), ageing, urbanization, percentage of European descendants (Eu%), and depigmentation (blonde hair colour), for parametric and non-parametric correlations, multivariate regressions and analyses of variance. Worldwide, UVR levels showed negative correlation with melanoma incidence ("rho" = -0.515, p < 0.001), remaining significant and negative in parametric partial correlation (r = -0.513, p < 0.001) with other variables kept constant. After standardising melanoma incidence for Eu%, melanoma correlation with UVR disappeared completely ("rho" = 0.004, p = 0.967, n = 127). The results question classical views that UVR causes melanoma. No correlation between UVR level and melanoma incidence was present when Eu% (depigmented or light skin type) was kept statistically constant, even after adjusting for other known variables. Countries with lower UVR levels and more Eu% (depigmented or light skin people) have higher melanoma incidence. Critically, this means that individual genetic low skin pigmentation factors predict melanoma risk regardless of UVR exposure levels, and even at low-UVR levels. Keywords: UV levels; adaptation; cutaneous malignant melanoma (CMM); depigmentation; incidence; world-wide data

Total Meat Intake is Associated with Life Expectancy: A Cross-Sectional Data Analysis of 175 Contemporary Populations

Background: The association between a plant-based diet (vegetarianism) and extended life span is increasingly criticised since it may be based on the lack of representative data and insufficient removal of confounders such as lifestyles. Aim: We examined the association between meat intake and life expectancy at a population level based on ecological data published by the United Nations agencies. Methods: Population-specific data were obtained from 175 countries/territories. Scatter plots, bivariate, partial correlation and linear regression models were used with SPSS 25 to explore and compare the correlations between newborn life expectancy (e(0)), life expectancy at 5 years of life (e(5)) and intakes of meat, and carbohydrate crops, respectively. The established risk factors to life expectancy - caloric intake, urbanization, obesity and education levels - were included as the potential confounders. Results: Worldwide, bivariate correlation analyses revealed that meat intake is positively correlated with life expectancies. This relationship remained significant when influences of caloric intake, urbanization, obesity, education and carbohydrate crops were statistically controlled. Stepwise linear regression selected meat intake, not carbohydrate crops, as one of the significant predictors of life expectancy. In contrast, carbohydrate crops showed weak and negative correlation with life expectancy. Conclusion: If meat intake is not incorporated into nutrition science for predicting human life expectancy, results could prove inaccurate. Keywords: agriculture; ecological study; evolution; life expectancy; meat intake; vegetaria

Genghis Khan's death (AD 1227): An unsolvable riddle or simply a pandemic disease?

Abstract The article examines Genghis Khan's death from the historico-medical perspective. Although several etiologies have been proposed over the years, most of these at a closer look appear to be later inventions by historians. A reassessment of the available evidence suggests instead bubonic plague as the most likely clinical scenario. Genghis Khan's death is also a reflection on the impact of pandemic diseases on leadership in ancient times as well as nowadays

Adding power of artificial intelligence to situational awareness of large interconnections dominated by inverter‐based resources

Large-scale power systems exhibit more complex dynamics due to the increasing integration of inverter-based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide-Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large-scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra-high density synchrophasor and point-on-wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)-based advanced applications are introduced, including AI-based inertia estimation, AI-based disturbance size and location estimation, AI-based system stability assessment, and AI-based data authentication