Relaxed natural selection contributes to global obesity increase more in males than in females due to more environmental modifications in female body mass

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 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, I_bs) 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, I_bs 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, I_bs, 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 I_bs, 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.

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 (I_s), 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, I_s 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 I_s is the significant predictor of dementia incidence among all ages and 15-49 years old. Subsequently, I_s was selected as the variable having the greatest influence on dementia incidence in stepwise multiple linear regression. The I_s 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.

Phenotypic variation in urban environments: mechanisms and implications

In the past decade, numerous studies have explored how urbanisation affects the mean phenotypes of populations, but it remains unknown how urbanisation impacts phenotypic variation, a key target of selection that shapes, and is shaped by, eco-evolutionary processes. Our review suggests that urbanisation may often increase intraspecific phenotypic variation through several processes; a conclusion aligned with results from our illustrative analysis on tit morphology across 13 European city/forest population pairs. Urban-driven changes in phenotypic variation will have immense implications for urban populations and communities, particularly through urbanisation's effects on individual fitness, species interactions, and conservation. We call here for studies that incorporate phenotypic variation in urban eco-evolutionary research alongside advances in theory.

Genetics of psychic ability - A pilot case-control exome sequencing study

INTRODUCTION

It is commonly believed that psychic ability, like many mental and physical traits, runs in families. This suggests the presence of a genetic component. If such a component were found, it would constitute a biological marker of psychic ability and inform environmental or pharmacologic means of enhancing or suppressing this ability.

METHODS

A case-control study design was used to evaluate differences between psychic cases and non-psychic controls. Over 3,000 candidates globally were screened through two online surveys to locate people who claimed they and other family members were psychic. Measures of relevance to the claimed abilities (e.g., absorption, empathy, schizotypy) were collected and based on those responses, individuals with indications of psychotic or delusional tendencies were excluded from further consideration. Eligible candidates were then interviewed and completed additional screening tests. Thirteen individuals were selected as the final "psychic cases," and ten age-, sex-, and ethnicity-matched individuals with no claims of psychic ability were selected as controls. DNA from the saliva of these 23 participants was subjected to whole-exome sequencing. Two independent bioinformatics analyses were blindly applied to the sequenced data, one focusing exclusively on protein-coding sequences and another that also included some adjacent noncoding sequences.

RESULTS

Sequencing data were obtained for all samples, except for one in the control group that did not pass the quality controls and was not included in further analyses. After unblinding the datasets, none of the protein-coding sequences (i.e., exons) showed any variation that discriminated between cases and controls. However, a difference was observed in the intron (i.e., non-protein-coding region) adjacent to an exon in the TNRC18 gene (Trinucleotide Repeat-Containing Gene 18 Protein) on chromosome 7. This variation, an alteration of GG to GA, was found in 7 of 9 controls and was absent from all psychic cases.

DISCUSSION

The most conservative interpretation of these results is that they result from random population sampling. However, when the results are considered in relation to other lines of evidence, the results are more provocative. Further research is justified to replicate and extend these findings.

Gluten consumption may contribute to worldwide obesity prevalence

Gluten consumption has been controversially associated with obesity in previous studies. We sought to examine this association at the worldwide level.

Country specific data were obtained from 168 countries. Scatter plots, bivariate, partial correlation and multiple linear regression models were used to explore and compare the coincidence between obesity prevalence and consumption of gluten, non-gluten cereal protein and total cereal protein respectively. The established risk factors of obesity: caloric intake, sedentary lifestyle, urbanization, socioeconomic status, meat protein intake and sugar consumption were included in analyses as potential confounders. The 168 countries were also stratified into developing and developed country groupings for further examination of the relationships.

Worldwide, bivariate correlation analyses revealed that the strength and direction of correlations between all variables (independent, dependent and potential confounders) were at similar levels. Obesity prevalence was positively correlated to gluten consumption but was negatively correlated to consumption of non-gluten cereal protein, and was in almost nil correlation to total cereal protein consumption. These relationships were similar across all countries (n= 168), developed country grouping (N=44) and developing country grouping (n=124). When caloric intake, Gross Domestic Product at Purchasing Power Parity, sedentary lifestyle and urbanization were kept statistically constant in the partial correlation analysis, obesity was significantly correlated to gluten consumption in all countries, developed country grouping and developing country grouping, and was significantly but inversely and weakly correlated to non-gluten cereal protein in all countries and developing countries, and was in almost nil correlation to total cereal protein in all country groupings. Globally, stepwise multiple regression analysis, when all the independent variables and potential confounding factors were included, selected consumption of sugar as the variable having the greatest influence on obesity with R2 = 0.510, while gluten was placed second increasing R2 to 0.596. Gluten consumption may have been emerging as an inconspicuous, but significant cause of obesity. While Westernization has driven the diet patterns worldwide to incorporate more gluten crops, obesity prevalence projection methods may estimate future obesity rates poorly if gluten consumption is not considered.

Long Non-Coding RNAs in Brown Adipose Tissue

Obesity has become a widespread disease that is harmful to human health. Fat homeostasis is essentially maintained by fat accumulation and energy expenditure. Studies on brown adipose tissue (BAT) represent a promising opportunity to identify a pharmaceutical intervention against obesity through increased energy expenditure. Long non-coding RNAs (lncRNAs) were thought to be critical regulators in a variety of biological processes. Recent studies have revealed that lncRNAs, including ones that are BAT-specific, conserved, and located at key protein-coding genes, function in brown adipogenesis, white adipose browning (ie, beige adipogenesis), and brown thermogenesis. In this review, we describe lncRNA properties and highlight functional lncRNAs in these biological processes, with the goal of establishing links between lncRNAs and BAT. Based on the advances of lncRNAs in the regulation of BAT, we discussed the advantages of potential lncRNA-based obesity drugs. Further BAT lncRNA-based drug development may provide new exciting approaches to defend obesity by regulation of fat homeostasis.

Genome-wide identification and characterization of long non-coding RNAs during postnatal development of rabbit adipose tissue

Background

The rabbit is widely used as an important experimental model for biomedical research, and shows low adipose tissue deposition during growth. Long non-coding RNAs (lncRNAs) are associated with adipose growth, but little is known about the function of lncRNAs in the rabbit adipose tissue.

Methods

Deep RNA-sequencing and comprehensive bioinformatics analyses were used to characterize the lncRNAs of rabbit visceral adipose tissue (VAT) at 35, 85 and 120 days after birth. Differentially expressed (DE) lncRNAs were identified at the three growth stages by DESeq. The cis and trans prediction ways predicted the target genes of the DE lncRNAs. To explore the function of lncRNAs, Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed on the candidate genes.

Results

A total of 991,157,544 clean reads were generated after RNA-Seq of the three growth stages, of which, 30,353 and 107 differentially expressed (DE) lncRNAs were identified. Compared to the protein-coding transcripts, the rabbit lncRNAs shared some characteristics such as shorter length and fewer exons. Cis and trans target gene prediction revealed, 43 and 64 DE lncRNAs respectively, corresponding to 72 and 20 protein-coding genes. GO enrichment and KEGG pathway analyses revealed that the candidate DE lncRNA target genes were involved in oxidative phosphorylation, glyoxylate and dicarboxylate metabolism, and other adipose growth-related pathways. Six DE lncRNAs were randomly selected and validated by q-PCR.

Conclusions

This study is the first to profile the potentially functional lncRNAs in the adipose tissue growth in rabbits, and contributes to our understanding of mammalian adipogenesis.

Electronic supplementary material

The online version of this article (10.1186/s12944-018-0915-1) contains supplementary material, which is available to authorized users.

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.