Ambient ultraviolet radiation as a cardioprotective factor: A global and regional analysis.

Background: Ambient ultraviolet radiation (UVR) has been found to have a greater cardioprotective effect than previously believed. This study aimed to quantitatively measure the role of UVR in protecting against the progression of cardiovascular disease (CVD) in general on a global and regional scale. Methods: Population-level data on UVR, CVD incidence, aging, economic affluence, CVD genetic background (indexed with the Biological State Index, Ibs), obesity prevalence, and urbanization were collected and analysed. The correlation between UVR and CVD was examined using bivariate correlations, partial correlation, and stepwise multiple linear regression. Countries were grouped to investigate regional correlations between UVR and CVD, and Fisher's r-to-z transformation was used to compare correlation coefficients. Results: UVR showed a significant inverse correlation with CVD incidence rates in bivariate correlation analyses globally (r = - 0.775 and r = - 0.760, p < 0.001), as well as within high-income (r = -0.704, p < 0.001) and low- and middle-income countries (LMIC) (r = -0.851, p < 0.001). These correlations remained significant even after controlling for confounding variables (r = -0.689 to -0.812, p < 0.001). In stepwise regression models, UVR was found to be the most significant predictor of CVD incidence. The inverse correlation between UVR and CVD was stronger in LMICs compared to high-income countries (z = -1.96, p < 0.050). Conclusions: Low ambient UVR may be a significant risk factor for the progression of CVD worldwide. The protective effect of UVR appears to be stronger in LMICs than in high-income countries, suggesting a greater impact of UVR on CVD prevention in these regions. These findings emphasize the need for further research into the mechanisms underlying the cardioprotective effects of UVR and the development of public health strategies to mitigate CVD risk associated with low UVR exposure.

A greater nurse and midwife density protects against infant mortality globally.

PURPOSE: As the largest profession within the health care workforce, nurses and midwives play a critical role in the health and wellness of families especially children and infants. This study suggests those countries with higher nurse and midwife densities (NMD) had lower infant mortality rates (IMR). DESIGN AND METHODS: With affluence, low birthweight and urbanization incorporated as potential confounders, this ecological study analyzed the correlations between NMD and IMR with scatterplots, Pearson r correlation, partial correlation and multiple linear regression models. Countries were also grouped for analysing and comparing their Pearson's coefficients. RESULTS: NMD inversely and significantly correlated to IMR worldwide. This relationship remained significant independent of the confounders, economic affluence, low birthweight and urbanization. Explaining 57.19% of IMR variance, high NMD was implicated in significantly reducing the IMR. PRACTICE IMPLICATIONS: Countries with high NMD had lower IMRs both worldwide and with special regard to developing countries. This may interest healthcare policymakers, especially those from developing countries, to consider the impacts of global nursing and midwifery staffing shortages. Nurses and midwives are the group of healthcare professionals who spend most with infants and their carers. This may be another alert for the health authorities to extend nurses and midwives' practice scope for promoting infant health.

Nursing workforce plays a significant role in reducing COVID-19 deaths worldwide: A cross-sectional analysis of data from 178 countries.

Worldwide, the role of nursing workforce in reducing COVID-19 case fatality ratio (CFR) is analyzed with scatter plots, Pearson's r and nonparametric, partial correlation and multiple linear regression models. The potential confounders, median age, health expenditure, physician density, and urbanization were incorporated for calculating the independent role of nursing workforce in protecting against COVID-19 CFR. The study findings suggested that (1) the nursing workforce inversely and significantly correlates with COVID-19 CFR; (2) this relationship remained independent of the confounding effects of each individual confounder or their combination; (3) Nursing workforce was the only variable identified as a significant contributor for reducing COVID-19 CFR, when it was incorporated into stepwise regression model with health expenditure, median age, physician density, and urbanization for analyzing their individual predicting effects on COVID-19 CFR. A strong message for the health authorities is that, although in shortage, nursing workforce showed their significant role in reducing COVID-19 deaths worldwide. This study highlights that the role of nursing workforce should be incorporated into population health research.

Modern medical services, a double-edged sword manages symptoms, but accumulates genetic background of cardiovascular diseases: A cross populational analysis of 217 countries.

Background and Aims: Through reduced natural selection, measured with Biological State Index (I bs), modern medicine enables most people to survive well beyond the reproductive lifespan leading to deleterious gene accumulation in population. This study explored the role of reduced natural selection in increasing cardiovascular disease (CVD) incidence worldwide. Methods: Country-specific estimates of CVD incidence and the index of reduced natural selection were captured for analysis of their correlation. Aging, affluence, obesity prevalence, and urbanization were considered as the potential confounders in the analyses. Results: Worldwide, I bs was significantly correlated with CVD incidence in the bivariate correlation analyses. This relationship remains when the contributing effects from aging, affluence, obesity prevalence, and urbanization are removed in partial correlation model. Multiple linear regression (enter) shows that I bs is a significant predictor of CVD incidence. Stepwise multiple linear regression selects I bs as the variable having the second greatest influence on CVD incidence after ageing. I bs showed a significantly greater correlation with CVD incidence in low- and middle-income countries (LMICs) than in high-income countries. Conclusion: Worldwide, through reducing natural selection, the side effects of healthcare services may have been partially contributing to the increase of CVD incidence worldwide with special regard to LMICs.

A cross-sectional study quantifies the independent contribution of nurses and midwives in child health outcomes.

INTRODUCTION: As the largest profession within the healthcare industry, nursing and midwifery workforce (NMW) provides comprehensive healthcare to children and their families. This study quantified the independent role of NMW in reducing under-5 mortality rate (U5MR) worldwide. DESIGN: A retrospective, observational and correlational study to examine the independent role of NMW in protecting against U5MR. METHODS: Within 266 "countries", the cross-sectional correlations between NMW and U5MR were examined with scatter plots, Pearson's r, nonparametric, partial correlation and multiple regression. The affluence, education and urban advantages were considered as the potential competing factors for the NMW-U5MR relationship. The NMW-U5MR correlations in both developing and developed countries were explored and compared. RESULTS: Bivariate correlations revealed that NMW negatively and significantly correlated to U5MR worldwide. When the contributing effects of economic affluence, urbanization and education were removed, the independent NMW role in reducing U5MR remained significant. NMW independently explained 9.36% U5MR variance. Multilinear regression selected NMW as a significant factor contributing an extra 3% of explanation to U5MR variance when NMW, affluence, education and urban advantage were incorporated as the predicting variables. NMW correlated with U5MR significantly more strongly in developing countries than in developed countries. CONCLUSION: NMW, indexing nursing and midwifery service, was a significant factor for reducing U5MR worldwide. This beneficial effect explained 9.36% of U5MR variance which was independent of economic affluence, urbanization and education. The NMW may be a more significant risk factor for protecting children from dying under 5 years old in developing countries. As a strategic response to the advocacy of the United Nations to reduce child mortality, it is worthy for health authorities to consider a further extension of nurses and midwives' practice scope to enable communities to have more access to NMW healthcare services.

Greater nurse density correlates to higher level of population ageing globally, but is more prominent in developed countries.

BACKGROUND: Representing over 50% of the healthcare workforce, nurses provide care to people at all ages. This study advances, at a population level, that high levels of nursing services, measured by nurse density may significantly promote population ageing measured by the percentage of a population over 65 years of age (65yo%). METHODS: Population level data was examined to explore the correlation between nurse density and 65yo%. The confounding impacts on ageing such as the effects of economic affluence, physician density, fertility rate, obesity and urban advantages were also considered. Scatter plots, bivariate correlation, partial correlation and multiple linear regression analyses were performed for examining the correlations. RESULTS: Nurse density correlated to 65yo%; this relationship was independent of other influences such as fertility rate, economic affluence, obesity prevalence, physician density and urban advantages. Second to fertility rate, nursing density had the greatest influence on 65yo%. The predicting and confounding variables explain 74.4% of the total 65yo% variance. The universal correlations identified in country groupings suggest that low nurse density may be a significant global concern. CONCLUSIONS: While nurse density might contribute significantly to 65yo% globally, the effect was more prominent in developed countries. Ironically, countries with higher nurse densities and therefore greater levels of 65yo%, were countries with an increased need for more nursing staff. To highlight the profound implications for the role the nursing profession plays especially at a time of global nursing shortage, further study into the effects of long-run elasticity of nurse staffing level on population ageing may be needed. For instance, what percentage of nursing staff increase would be required to meet every 1% increase of an ageing population.

A global comparison of nursing and midwifery's and medical efficacy in preventing COVID-19 deaths 2019-2022.

AIM: Compare roles of nurses and midwives and physicians in reducing COVID-19 deaths measured with a case fatality ratio. BACKGROUND: The roles and responsibilities of different health disciplines to the COVID-19 pandemic vary. While more difficult to measure, objective assessments of discipline contributions of nurses and midwives and physicians can be viewed through statistical analysis. METHODS: Population-level data are analysed with scatter plots, bivariate correlations, partial correlation and multiple linear regression models to illustrate the contributions of nurses and midwives and physicians in reducing COVID-19 deaths. The role of nurses and midwives and physicians in protecting the community against COVID-19 deaths is explored and compared using competing effects of affluence, age and urbanization. Data analysis software programs include Excel v.2016, SPSS v.28 and Fisher r-to-z transformation. RESULTS: Nurses and midwives reduce COVID-19 deaths significantly more than physicians. This difference remains while controlling for physician care, economic affluence, median age and urbanization individually or in combination. In contrast, the role of physicians in reducing COVID-19 deaths is less independent than nurses and midwives. Linear regression results insinuate when nursing and physician care are collated together with other predicting factors, physicians' contribution to community protection against COVID-19 case fatality ratio is statistically explained by nursing and midwifery care. DISCUSSION: Unlike physicians, the nursing and midwifery workforce is bigger and located throughout all healthcare system levels and, therefore, is more accessible to the community. This is an important point in explaining the contribution of nurses and midwives to reducing COVID-19 deaths when compared with physicians. CONCLUSION: This study suggests that, worldwide, the nursing and midwifery workforce may play a more significant role in protecting the community against COVID-19 deaths than physicians. IMPLICATIONS FOR HEALTH POLICY, NURSING AND MIDWIFERY PRACTICE: The findings from this study offer a unique perspective for health authorities to further understand the complementary and independent role of the nursing and midwifery workforce in respect of the healthcare team. This study suggests the importance of a broader range of healthcare services, especially during the pandemic, for example, COVID-19. With the permission of health authorities, the nursing and midwifery workforce should have further extension of their scope of practice in situations such as pandemics due to their broader access to the community.

A lack of nurse autonomy impacts population health when compared to physician care: an ecological study.

This study highlights that the contribution of nursing is secondary to physicians in overall population health (indexed with life expectancy at birth, e(0)). Scatter plots, bivariate correlation and partial correlation models were performed to analyse the correlations between e(0) and physician healthcare and nursing healthcare respectively. Affluence, urbanization and obesity were incorporated as the potential confounders. The Fisher's r-to-z transformation was conducted for comparing the correlations. Multiple linear regression analyses were implemented for modelling that physicians' contributions to e(0) explain nurses'. Nursing healthcare correlated to e(0) significantly less strongly than physician healthcare in simple regressions. Nursing healthcare was in weak or negligible correlation to e(0) when physician healthcare was controlled individually or together with the three confounders. Physician healthcare remains significantly correlational to e(0) when nursing healthcare alone was controlled or when the three confounders were controlled. Linear regression revealed that nursing healthcare was a significant predictor for e(0) when physician healthcare was "not added" for modelling, but this predicting role became negligible when physician healthcare was "added". Our study findings suggested that nurses still work under the direction of physicians due to lack of autonomy. Without correction, health services will continue to transmit the invisibility of nursing healthcare from one generation of nurses to another.

Total meat (flesh) supply may be a significant risk factor for cardiovascular diseases worldwide.

Consumption of red meat instead of white meat has typically been associated with cardiovascular diseases (CVDs). Reflecting actual diet patterns, this study explored the role of total meat (red + white) in predicting CVD incidence. Data from 217 countries were extracted from United Nations agencies for the analyses in five steps. Bivariate correlations were applied to examine the relationship between total meat and CVD incidence globally and regionally. Partial correlation was applied to identify that total meat was an independent predictor of CVD incidence while socioeconomic status, obesity, and urbanization were statistically constant. Stepwise linear regression was conducted for selecting the significant predictor of CVD incidence. SPSS 28 and Microsoft Excel were used for correlation analyses. Globally, total meat correlated to CVD incidence strongly and significantly in bivariate correlation models. This relationship remained significant in partial correlation when socioeconomic status, obesity, and urbanization were statistically kept constant. Stepwise multiple regression identified that, second to socioeconomic status, total meat was a significant predictor of CVD incidence. Total meat correlated to CVD incidence in different country groupings. However, the correlations between total meat and CVD incidence were significantly stronger in developing countries than in developed countries. Worldwide, total meat (flesh) consumption correlated to CVD incidence independently, but significantly stronger in developing countries than in developed countries. This correlation is worth exploring further in longitudinal cohort studies.

Although in shortage, nursing workforce is still a significant contributor to life expectancy at birth.

OBJECTIVES: Previous studies have not fully reported the strength and independency of the correlation of nursing workforce to life expectancy. This study advances that nursing workforce is a major independent contributor to life expectancy at birth (LEB) globally and regionally. DESIGN: A cross-sectional study was conducted at population level. SAMPLE: Ecological data were extracted from the United Nations agencies for 215 populations. Each population is considered a research subject. MEASUREMENTS: The correlation between nursing workforce and LEB was analyzed with scatter plots, bivariate correlation, partial correlation, and multiple linear regression analyses, Analysis of Variance post hoc and independent T-test. Economic affluence, urban lifestyle and obesity were included as the potential confounders in this study. INTERVENTION: Not applicable RESULTS: Nursing workforce correlated to LEB and this relationship remained regardless of the competition of economic affluence, urbanization, and obesity. Second to economic affluence, nursing workforce showed the greatest influence on LEB. In total, 64.50% of LEB was explained in this study. Nursing workforce was a determinant of regional variations of LEB. CONCLUSIONS: Nursing workforce may be a significant contributor to LEB globally and regionally. This contribution was independent of the potential confounding effects of economic affluence, urbanization, and obesity.

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.

Physician care access plays a significant role in extending global and regional life expectancy.

BACKGROUND: Previous cross-sectional studies generally did not fully consider the potential confounding factors associated with physician impact on overall population health. This ecological study controlled for health, demographic and socioeconomic confounders while using total physician density for predicting overall population health globally and regionally. METHODS: Ecological data were extracted from the United Nations agencies for 215 populations. Considering the competing effects of economic affluence, urban advantages and obesity, correlations between physician density and life expectancy at birth (LEB) were analysed with scatter plots, bivariate correlation, partial correlation and multiple linear regression analyses. Countries are also grouped for exploring the regional correlations between physician density and LEB. RESULTS: Physician density correlates to LEB and this relationship remains regardless of the competition of the individual confounders, economic affluence, urbanization and obesity, or their combination. Physician density has the greatest influence on LEB, while economic affluence is second. Physician density explains 64.89% of LEB in this study. Together with constant bivariate correlations in country groupings, power correlation without a plateau or U shape in the trendline of the scatterplots, suggests that a shortage of physicians is a worldwide issue. CONCLUSIONS: Physician density is a major independent contributor for LEB both globally and with special regard to the developing world. Telehealth may be an alternative to increase physicians' capacity while funding for increasing physician employment is desirable.

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.

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.

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.

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.

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

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.

Greater family size is associated with less cancer risk: an ecological analysis of 178 countries.

BACKGROUND: Greater family size measured with total fertility rate (TFR) and with household size, may offer more life satisfaction to the family members. Positive psychological well-being has been postulated to decrease cancer initiation risk. This ecological study aims to examine the worldwide correlation between family size, used as the measure of positive psychological well-being, and total cancer incidence rates. METHODS: Country specific estimates obtained from United Nations agencies on total cancer incidence rates (total, female and male rates in age range 0-49 years and all ages respectively), all ages site cancer incidence (bladder, breast, cervix uteri, colorectum, corpus uteri, lung, ovary and stomach), TFR, household size, life expectancy, urbanization, per capita GDP PPP and self-calculated Biological State Index (Ibs) were matched for data analysis. Pearson's, non-parametric Spearman's, partial correlations, independent T-test and multivariate regressions were conducted in SPSS. RESULTS: Worldwide, TFR and household size were significantly and negatively correlated to all the cancer incidence variables. These correlations remained significant in partial correlation analysis when GDP, life expectancy, Ibs and urbanization were controlled for. TFR correlated to male cancer incidence rate (all ages) significantly stronger than it did to female cancer incidence rate (all ages) in both Pearson's and partial correlations. Multivariate stepwise regression analysis indicated that TFR and household size were consistently significant predictors of all cancer incidence variables. CONCLUSIONS: Countries with greater family size have lower cancer risk in both females, and especially males. Our results seem to suggest that it may be worthwhile further examining correlations between family size and cancer risk in males and females through the cohort and case-control studies based on large samples.

Prostate Cancer Incidence is Correlated to Total Meat Intake­ a Cross-National Ecologic Analysis of 172 Countries

Objective: To examine the association of total meat (animal flesh) consumption to prostate cancer incidence (PC61) at population level. Subjects and Methods: Data from 172 countries were extracted for analysis. Associations between country specific per capita total meat intake and PC61 incidence at country level were examined using Pearson's r and Spearman rho, partial correlation, stepwise multiple linear regression analyses with ageing, GDP, Is (index of magnitude of prostate cancer gene accumulation at population level), obesity prevalence and urbanization included as the confounding factors. Countries were also grouped for regional association analysis. The data were log-transformed for analysis in SPSS. Microsoft Excel, and ANOVA Post hoc Scheffe tests were applied to calculate and compare mean differences between country groupings. Results: Worldwide, total meat intake was strongly and positively associated with PC61 incidence in Pearson's r (r= 0.595, p<0.001) and Spearman rho (r= 0.637, p<0.001) analyses. This relationship remained significant in partial correlation (r= 0.295, p<0.001) when ageing, GDP, Is, obesity prevalence and urbanization were kept statistically constant. GDP was weakly and insignificantly associated with PC61 when total meat intake was kept statistically constant. Stepwise multiple linear regression identified that total meat was a significant predictor of PC61 with total meat intake and all the five confounders included as the independent variables (R2=0.417). Post hoc Scheffe tests revealed nine significant mean differences of PC61 between the six WHO regions, but all disappeared when the contributing effect of total meat on PC61 incidence rate was removed. GDP was not identified as the statistically significant predictor of PC61 in either of the models including or excluding total meat as the independent variable. Conclusions: Total meat intake is an independent predictor of PC61 worldwide, and the determinant of regional variation of PC61. The longitudinal cohort studies are proposed to explore the association further.

Low fertility may be a significant determinant of ovarian cancer worldwide: an ecological analysis of cross- sectional data from 182 countries.

BACKGROUND: Ageing, socioeconomic level, obesity, fertility, relaxed natural selection and urbanization have been postulated as the risk factors of ovarian cancer (OC56). We sought to identify which factor plays the most significant role in predicting OC56 incidence rate worldwide. METHODS: Bivariate correlation analysis was performed to assess the relationships between country-specific estimates of ageing (measured by life expectancy), GDP PPP (Purchasing power parity), obesity prevalence, fertility (indexed by the crude birth rate), opportunity for natural selection (Ibs) and urbanization. Partial correlation was used to compare contribution of different variables. Fisher A-to-Z was used to compare the correlation coefficients. Multiple linear regression (Enter and Stepwise) was conducted to identify significant determinants of OC56 incidence. ANOVA with post hoc Bonferroni analysis was performed to compare differences between the means of OC56 incidence rate and residuals of OC56 standardised on fertility and GDP respectively between the six WHO regions. RESULTS: Bivariate analyses revealed that OC56 was significantly and strongly correlated to ageing, GDP, obesity, low fertility, Ibs and urbanization. However, partial correlation analysis identified that fertility and ageing were the only variables that had a significant correlation to OC56 incidence when the other five variables were kept statistically constant. Fisher A-to-Z revealed that OC56 had a significantly stronger correlation to low fertility than to ageing. Stepwise linear regression analysis only identified fertility as the significant predictor of OC56. ANOVA showed that, between the six WHO regions, multiple mean differences of OC56 incidence were significant, but all disappeared when the contributing effect of fertility on OC56 incidence rate was removed. CONCLUSIONS: Low fertility may be the most significant determining predictor of OC56 incidence worldwide.