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

Birth Rate as a Determinant of Dementia Incidence: A Comprehensive Global Analysis

BACKGROUND

The role of parity in predicting dementia risk in women is debated. This study examines how birth rate affects global dementia incidence.

METHODS

Country-specific data on birth rate and dementia incidence rate were analyzed using bivariate analysis, partial correlation, and multiple linear regression. Confounding factors such as aging, affluence, genetic predisposition (Ibs), and urbanization were considered.

RESULTS

Pearson's r and nonparametric analyzes showed a significant inverse correlation between birth rate and dementia incidence. This relationship remained significant after controlling for aging, affluence, Ibs, and urbanization. Multiple linear regression identified birth rate as a significant predictor of dementia incidence, and as the strongest predictor. Affluence and urbanization were not significant predictors. The correlation was stronger in developing countries.

CONCLUSIONS

Lower birth rate is an independent risk factor for dementia, particularly in developed countries. These findings highlight the importance of considering birth rate in dementia studies.

Smaller household size and higher prevalence of serious psychological distress in younger people and never-married people: a nationwide cross-sectional survey in Japan

Background

Small-member households are increasing worldwide. However, most previous studies have focused on older people and living alone. Using the latest national survey data, we investigated a dose-response relationship between household size and serious psychological distress (SPD).

Methods

We analyzed data from the 2019 Comprehensive Survey of Living Conditions in Japan. The study participants were 405,560 community-dwelling adults aged 20 or older. Household size was classified into 5 or more, 3 or 4, two, and one (i.e., living alone). SPD was defined as ≥13 points based on the Kessler 6-item Psychological Distress Scale. We used multivariable logistic regressions and included age, education, equivalent household expenditures, housing tenure, employment contract, smoking, and illness under treatment as covariates.

Results

After stratified analyses by age and gender, a dose-response relationship between smaller household size and more common SPD was significant for younger, but not for older people (p-trend was <0.001 in men aged 20-59 and women aged 20-39). After stratified analyses by gender and marital status, a dose-response relationship was significant only for the never-married group in both genders (p-trend was <0.001 in never-married men and women).

Conclusion

Smaller households were associated with higher prevalence of SPD in younger adults and in never-married individuals, regardless of gender. Our findings suggest a need to focus on younger people and never-married people to reduce the mental health risks due to small household sizes.

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.

Identifying the Environmental Determinants of Lung Cancer: A Case Study of Henan, China

Lung cancer has become one of the most prevalent cancers in the last several decades. Studies have documented that most cases of lung cancer are caused by inhaling environmental carcinogens while how external environmental factors lead to individual lung cancer is still an open issue as the pathogenesis may come from the combined action of multiple environmental factors, and such pathogenic mechanism may vary from region to region. Based on the data of lung cancer cases from hospitals at the county level in Henan from 2016 to 2020, we analyzed the response relationship between lung cancer incidence and physical ambient factors (air quality, meteorological conditions, soil vegetation) and socioeconomic factors (occupational environment, medical level, heating mode, smoking behavior). We used a Bayesian spatio-temporal interaction model to evaluate the relative risk of disease in different regions. The results showed that smoking was still the primary determinant of lung cancer, but the influence of air quality was increasing year by year, with meteorological conditions and occupational environment playing a synergistic role in this process. The high-risk areas were concentrated in the plains of East and Central Henan and the basin of South Henan, while the low-risk areas were concentrated in the hilly areas of North and West Henan, which were related to the topography of Henan. Our study provides a better understanding of the environmental determinants of lung cancer which will help refine existing prevention strategies and recognize the areas where actions are required to prevent environment and occupation related lung cancer.

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.

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.

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.

Socio-Demographic Determinants of Mortality from Chronic Noncommunicable Diseases in Women of Reproductive Age in the Republic of Georgia: Evidence from the National Reproductive Age Mortality Study (2014)

Purpose

Worldwide, noncommunicable diseases (NCDs) are the leading cause of premature death of women, taking the highest toll in developing countries. This study aimed to identify key socio-demographic determinants of NCD mortality in reproductive-aged women (15-49 years) in Georgia.

Materials and Methods

The study employed the verbal autopsy data from the second National Reproductive Age Mortality Survey 2014. Univariate and multivariate logistic regression models were fitted to explore the association between each risk factor and NCD mortality, measured by crude and adjusted odds ratio (AOR) with respective 95% confidence intervals (95% CI).

Results

In the final sample of 843 women, 586 (69.5%) deaths were attributed to NCDs, the majority of which occurred outside a hospital (72.7%) and among women aged 45-49 years (46.8%), ethnic Georgians (85.2%), urban residents (60.1%), those being married (60.6%), unemployed (75.1%) or having secondary and higher education (69.5%), but with nearly equal distribution across the wealth quintiles. After multivariate adjustment, the odds of dying from NCDs were significantly higher in women aged 45-49 years (AOR=17.69, 95% CI= 9.35 to 33.50), those being least educated (AOR=1.55, 95% CI= 1.01 to 2.37) and unemployed (AOR=1.47, 95% CI= 1.01 to 2.14) compared, respectively, to their youngest (15-24 years), more educated and employed counterparts. Strikingly, the adjusted odds were significantly lower in "other" ethnic minorities (AOR=0.29, 95% CI= 0.14 to 0.61) relative to ethnic Georgians. Contrariwise, there were no significant associations between NCD mortality and women's marital or wealth status, place of residence (rural/urban) or place of death.

Conclusion

Age, ethnicity, education, and employment were found to be strong independent predictors of young women's NCD mortality in Georgia. Further research on root causes of inequalities in mortality across the socioeconomic spectrum is warranted to inform equity- and life course-based multisectoral, integrated policy responses that would be conducive to enhancing women's survival during and beyond reproduction.