Childhood febrile illness and the risk of myopia in UK Biobank participants

Exploring the spatial variation and associated factors of childhood febrile illness among under-five children in Ethiopia: Geographically weighted regression analysis

BACKGROUND

The global burden of febrile illness and the contribution of many fever inducing pathogens have been difficult to quantify and characterize. However, in sub-Saharan Africa it is clear that febrile illness is a common cause of hospital admission, illness and death including in Ethiopia. Therefore the major aim of this study is to explore the spatial variation and associated factors of childhood febrile illness among under-five children in Ethiopia.

METHODS

This study were based on the 2016 Ethiopian Demographic health survey data. A total weighted sample of 10,127 under- five children was included. Data management was done using Stata version-14, Arc-GIS version-10.8 and SatsScan version- 9.6 statistical software. Multi-level log binomial model was fitted to identify factors associated with childhood febrile illness. Variables with a p-value < 0.2 in the bi-variable analysis were considered for the multivariable analysis. In the multivariable multilevel log binomial regression analysis p-value< 0.05, the APR with the 95% CI was reported. Global spatial autocorrelation was done to assess the spatial pattern of childhood febrile illness. Spatial regression was done to identify factors associated with the spatial variations of childhood febrile illness and model comparison was based on adjusted R2 and AICc.

RESULT

The prevalence of febrile illness among under-five children was 13.6% (95% CI: 12.6%, 14 .7%) with significant spatial variation across regions of Ethiopia with Moran's I value of 0.148. The significant hotspot areas of childhood febrile illness were identified in the Tigray, Southeast of Amhara, and North SNPPR. In the GWR analysis, the proportion of PNC, children who had diarrhea, ARI, being 1st birth order, were significant explanatory variables. In the multilevel log binomial regression age of children 7-24 months(APR = 1.33, 95% CI: (1.03, 1.72)), maternal age 30-39 years (APR = 1.36 95% CI: 1.02, 1.80)), number of children (APR = 1.78, 95% CI: 0.96, 3.3), diarrhea(APR = 5.3% 95% CI: (4.09, 6.06)), ARI (APR = 11.5, 95% CI: (9.2, 14.2)) and stunting(APR = 1.21; 95% CI: (0.98, 1.49) were significantly associated with childhood febrile illness.

CONCLUSION

Childhood febrile illness remains public health problem in Ethiopia. On spatial regression analysis proportion of women who had PNC, proportion of children who had diarrhea, proportion of children who had ARI, and proportion of children who had being 1st birth order were associated factors. The detailed map of childhood febrile illness and its predictors could assist health program planners and policy makers to design targeted public health interventions for febrile illness.

Anxiety disorders and age-related changes in physiology

BACKGROUND

Anxiety disorders are leading contributors to the global disease burden, highly prevalent across the lifespan and associated with substantially increased morbidity and early mortality.

AIMS

The aim of this study was to examine age-related changes across a wide range of physiological measures in middle-aged and older adults with a lifetime history of anxiety disorders compared with healthy controls.

METHOD

The UK Biobank study recruited >500 000 adults, aged 37-73, between 2006 and 2010. We used generalised additive models to estimate non-linear associations between age and hand-grip strength, cardiovascular function, body composition, lung function and heel bone mineral density in a case group and in a control group.

RESULTS

The main data-set included 332 078 adults (mean age 56.37 years; 52.65% females). In both sexes, individuals with anxiety disorders had a lower hand-grip strength and lower blood pressure, whereas their pulse rate and body composition measures were higher than in the healthy control group. Case-control group differences were larger when considering individuals with chronic and/or severe anxiety disorders, and differences in body composition were modulated by depression comorbidity status. Differences in age-related physiological changes between females in the anxiety disorder case group and healthy controls were most evident for blood pressure, pulse rate and body composition, whereas this was the case in males for hand-grip strength, blood pressure and body composition. Most differences in physiological measures between the case and control groups decreased with increasing age.

CONCLUSIONS

Findings in individuals with a lifetime history of anxiety disorders differed from a healthy control group across multiple physiological measures, with some evidence of case-control group differences by age. The differences observed varied by chronicity/severity and depression comorbidity.

Frailty in individuals with depression, bipolar disorder and anxiety disorders: longitudinal analyses of all-cause mortality

BACKGROUND

Frailty is a medical syndrome that is strongly associated with mortality risk and an emerging global health burden. Mental disorders are associated with reduced life expectancy and elevated levels of frailty. In this study, we examined the mortality risk associated with frailty in individuals with a lifetime history of mental disorders compared to individuals without a history of mental disorders.

METHODS

The UK Biobank study recruited > 500,000 adults, aged 37-73, between 2006 and 2010. We derived the two most common albeit distinctive measures of frailty, the frailty phenotype and the frailty index. Individuals with lifetime depression, bipolar disorder or anxiety disorders were identified from multiple data sources. The primary outcome was all-cause mortality. We have also examined differences in frailty, separately by sex and age.

RESULTS

Analyses included up to 297,380 middle-aged and older adults with a median follow-up of 12.19 (interquartile range = 1.31) years, yielding 3,516,706 person-years of follow-up. We observed higher levels of frailty in individuals with mental disorders for both frailty measures. Standardised mean differences in the frailty index ranged from 0.66 (95% confidence interval [CI] 0.65-0.67) in individuals with anxiety disorders to 0.94 (95% CI 0.90-0.97) in individuals with bipolar disorder, compared to people without mental disorders. For key comparisons, individuals with a mental disorder had greater all-cause mortality hazards than the comparison group without mental disorders. The highest hazard ratio (3.65, 95% CI 2.40-5.54) was observed among individuals with bipolar disorder and frailty, relative to non-frail individuals without mental disorders.

CONCLUSIONS

Our findings highlight elevated levels of frailty across three common mental disorders. Frailty and mental disorders represent potentially modifiable targets for prevention and treatment to improve population health and life expectancy, especially where both conditions coexist.

Sex and age as determinants of the seroprevalence of anti-measles IgG among European healthcare workers: A systematic review and meta-analysis

INTRODUCTION

The international literature shows good evidence of a significant rate of measles susceptibility among healthcare workers (HCWs). As such, they are an important public health issue.

METHODS

We conducted a systematic review and meta-analysis to estimate the prevalence of susceptible HCWs in EU/EEA countries and in the UK and to explore the characteristics (sex and age differences) and management of those found to be susceptible.

RESULTS

Nineteen studies were included in the meta-analysis. The prevalence of measles-susceptible HCWs was 13.3% (95 %CI: 10.0-17.0%). In a comparison of serosusceptible female vs. male HCWs, the RR was 0.92 (95 %CI = 0.83-1.03), and in a comparison of age classes (born after vs. before 1980) the RR was 2.78 (95 %CI = 2.20-3.50). The most recent studies proposed the mandatory vaccination of HCWs.

DISCUSSION

According to our meta-analysis, the prevalence of serosusceptible European HCWs is 13%; HCWs born in the post-vaccination era seem to be at higher risk. Healthcare professionals susceptible to measles are a serious epidemiological concern. Greater efforts should therefore be made to identify those who have yet to be vaccinated and actively encourage their vaccination.

Cross-classification between self-rated health and health status: longitudinal analyses of all-cause mortality and leading causes of death in the UK

Risk stratification is an important public health priority that is central to clinical decision making and resource allocation. The aim of this study was to examine how different combinations of self-rated and objective health status predict all-cause mortality and leading causes of death in the UK. The UK Biobank study recruited > 500,000 participants between 2006 and 2010. Self-rated health was assessed using a single-item question and health status was derived from medical history, including data on 81 cancer and 443 non-cancer illnesses. Analyses included > 370,000 middle-aged and older adults with a median follow-up of 11.75 (IQR = 1.4) years, yielding 4,320,270 person-years of follow-up. Compared to individuals with excellent self-rated health and favourable health status, individuals with other combinations of self-rated and objective health status had a greater mortality risk, with hazard ratios ranging from HR = 1.22 (95% CI 1.15-1.29, P_Bonf. < 0.001) for individuals with good self-rated health and favourable health status to HR = 7.14 (95% CI 6.70-7.60, P_Bonf. < 0.001) for individuals with poor self-rated health and unfavourable health status. Our findings highlight that self-rated health captures additional health-related information and should be more widely assessed. The cross-classification between self-rated health and health status represents a straightforward metric for risk stratification, with applications to population health, clinical decision making and resource allocation.

Exploring health in the UK Biobank: associations with sociodemographic characteristics, psychosocial factors, lifestyle and environmental exposures

BACKGROUND

A greater understanding of the factors that are associated with favourable health may help increase longevity and healthy life expectancy. We examined sociodemographic, psychosocial, lifestyle and environmental exposures associated with multiple health indicators.

METHODS

UK Biobank recruited > 500,000 participants, aged 37-73, between 2006 and 2010. Health indicators examined were 81 cancer and 443 non-cancer illnesses used to classify participants' health status; long-standing illness; and self-rated health. Exposures were sociodemographic (age, sex, ethnicity, education, income and deprivation), psychosocial (loneliness and social isolation), lifestyle (smoking, alcohol intake, sleep duration, BMI, physical activity and stair climbing) and environmental (air pollution, noise and residential greenspace) factors. Associations were estimated using logistic and ordinal logistic regression.

RESULTS

In total, 307,378 participants (mean age = 56.1 years [SD = 8.07], 51.9% female) were selected for cross-sectional analyses. Low income, being male, neighbourhood deprivation, loneliness, social isolation, short or long sleep duration, low or high BMI and smoking were associated with poor health. Walking, vigorous-intensity physical activity and more frequent alcohol intake were associated with good health. There was some evidence that airborne pollutants (PM2.5, PM10 and NO2) and noise (Lden) were associated with poor health, though findings were not consistent across all models.

CONCLUSIONS

Our findings highlight the multifactorial nature of health, the importance of non-medical factors, such as loneliness, healthy lifestyle behaviours and weight management, and the need to examine efforts to improve the health outcomes of individuals on low incomes.

IMI Risk Factors for Myopia

Risk factor analysis provides an important basis for developing interventions for any condition. In the case of myopia, evidence for a large number of risk factors has been presented, but they have not been systematically tested for confounding. To be useful for designing preventive interventions, risk factor analysis ideally needs to be carried through to demonstration of a causal connection, with a defined mechanism. Statistical analysis is often complicated by covariation of variables, and demonstration of a causal relationship between a factor and myopia using Mendelian randomization or in a randomized clinical trial should be aimed for. When strict analysis of this kind is applied, associations between various measures of educational pressure and myopia are consistently observed. However, associations between more nearwork and more myopia are generally weak and inconsistent, but have been supported by meta-analysis. Associations between time outdoors and less myopia are stronger and more consistently observed, including by meta-analysis. Measurement of nearwork and time outdoors has traditionally been performed with questionnaires, but is increasingly being pursued with wearable objective devices. A causal link between increased years of education and more myopia has been confirmed by Mendelian randomization, whereas the protective effect of increased time outdoors from the development of myopia has been confirmed in randomized clinical trials. Other proposed risk factors need to be tested to see if they modulate these variables. The evidence linking increased screen time to myopia is weak and inconsistent, although limitations on screen time are increasingly under consideration as interventions to control the epidemic of myopia.

Detecting Genotype-Population Interaction Effects by Ancestry Principal Components

Heterogeneity in the phenotypic mean and variance across populations is often observed for complex traits. One way to understand heterogeneous phenotypes lies in uncovering heterogeneity in genetic effects. Previous studies on genetic heterogeneity across populations were typically based on discrete groups in populations stratified by different countries or cohorts, which ignored the difference of population characteristics for the individuals within each group and resulted in loss of information. Here, we introduce a novel concept of genotype-by-population (G × P) interaction where population is defined by the first and second ancestry principal components (PCs), which are less likely to be confounded with country/cohort-specific factors. We applied a reaction norm model fitting each of 70 complex traits with significant SNP-heritability and the PCs as covariates to examine G × P interactions across diverse populations including white British and other white Europeans from the UK Biobank (N = 22,229). Our results demonstrated a significant population genetic heterogeneity for behavioral traits such as age at first sexual intercourse and academic qualification. Our approach may shed light on the latent genetic architecture of complex traits that underlies the modulation of genetic effects across different populations.

Geographical Variation in Likely Myopia and Environmental Risk Factors: A Multilevel Cross Classified Analysis of A UK Cohort

Purpose: Previous studies have demonstrated positive associations between myopia and environmental risk factors such as urbanization. However, these have failed to account for the clustering of individuals within geographical areas, opening analyses to theoretical and statistical limitations. We demonstrate how a multilevel modelling approach can provide a more nuanced understanding of the relationship between geography and myopia. We examined longitudinal associations between onset of myopia and urban/rural status or population density.

Methods: Data were collected over 5 visits during an 8-year period for a UK cohort of 3,512 children. Associations between incident myopia (spherical equivalent ≤ −1.00 diopters) and both urban/rural status and population density were examined using discrete time multilevel hazard models which allow the partitioning of variance into different neighborhood and school areas.

Results: There was evidence for an association between myopia and higher population density (Hazard Ratio = 1.14; 95% CI = 1.032 to 1.26) after adjustment for a range of risk factors. There was no strong evidence that urban/rural status was associated with incident myopia. Only a minor amount of variation in myopia was attributable to geographical areas (<2.2%), and this was not explained by rurality or population density.

Conclusion: Our findings contrast with previous studies and raise the possibility that some of the results reported may have been driven by confounding bias whereby geographical differences in myopia are driven by lifestyle factors that are correlated with geographical setting.

Comparison of peripapillary retinal nerve fiber layer thickness between myopia severity groups and controls

AIM

To compare the peripapillary retinal nerve fiber layer (RNFL) thickness measured via optical coherence tomography (OCT) between different groups of myopia severity and controls.

METHODS

This was a prospective cross-sectional study. All subjects underwent a full ophthalmic examination, refraction, visual field analysis and A-scan biometry. Myopic patients were classified as low myopia (LM) [spherical equivalent (SE) from greater than -0.5 D, up to -3.0 D], moderate myopia (MM; SE greater than -3.0 D, up to -6.0 D) and high myopia (HM; SE greater than -6.0 D). The control group consisted of emmetropic (EM) patients (SE from +0.5 D to -0.5 D). A Zeiss Cirrus HD-OCT machine was used to measure the peripapillary RNFL thickness of both eyes of each subject. The mean peripapillary RNFL thickness between groups was compared using both analysis of variance and analysis of covariance.

RESULTS

A total of 403 eyes of 403 subjects were included in this study. The mean age was 31.48±10.23y. There were 180 (44.7%) eyes with EM, 124 (30.8%) with LM, 73 (18.1%) with MM and 26 (6.5%) with HM. All groups of myopia severity had a thinner average RNFL than the EM group, but after controlling for gender, age, and axial eye length, only the HM group differed significantly from the EM group (P=0.017). Likewise, the superior, inferior and nasal RNFL was thinner in all myopia groups compared to controls, but after controlling for confounders, only the inferior quadrant RNFL was significantly thinner in the HM group, when compared to the EM group (P=0.017).

CONCLUSION

The average and inferior quadrant RNFL is thinner in highly myopic eyes compared to emmetropic eyes. Refractive status must be taken into consideration when interpreting the OCT of myopic patients, as RNFL thickness varies with the degree of myopia.

Genotype-environment interaction on human cognitive function conditioned on the status of breastfeeding and maternal smoking around birth

We estimated genotype by environment interaction (G × E) on later cognitive performance and educational attainment across four unique environments, i.e. 1) breastfed without maternal smoking, 2) breastfed with maternal smoking, 3) non-breastfed without maternal smoking and 4) non-breastfed with maternal smoking, using a novel design and statistical approach that was facilitated by the availability of datasets with the genome-wide single nucleotide polymorphisms (SNPs). There was significant G × E for both fluid intelligence (p-value = 1.0E-03) and educational attainment (p-value = 8.3E-05) when comparing genetic effects in the group of individuals who were breastfed without maternal smoking with those not breastfed without maternal smoking. There was also significant G × E for fluid intelligence (p-value = 3.9E-05) when comparing the group of individuals who were breastfed with maternal smoking with those not breastfed without maternal smoking. Genome-wide significant SNPs were different between different environmental groups. Genomic prediction accuracies were significantly higher when using the target and discovery sample from the same environmental group than when using those from the different environmental groups. This finding demonstrates G × E has important implications for future studies on the genetic architecture, genome-wide association studies and genomic predictions.

Environmental Factors and Myopia: Paradoxes and Prospects for Prevention

The prevalence of myopia in developed countries in East and Southeast Asia has increased to more than 80% in children completing schooling, whereas that of high myopia has increased to 10%-20%. This poses significant challenges for correction of refractive errors and the management of pathological high myopia. Prevention is therefore an important priority. Myopia is etiologically heterogeneous, with a low level of myopia of clearly genetic origins that appears without exposure to risk factors. The big increases have occurred in school myopia, driven by increasing educational pressures in combination with limited amounts of time spent outdoors. The rise in prevalence of high myopia has an unusual pattern of development, with increases in prevalence first appearing at approximately age 11. This pattern suggests that the increasing prevalence of high myopia is because of progression of myopia in children who became myopic at approximately age 6 or 7 because age-specific progression rates typical of East Asia will take these children to the threshold for high myopia in 5 to 6 years. This high myopia seems to be acquired, having an association with educational parameters, whereas high myopia in previous generations tended to be genetic in origin. Increased time outdoors can counter the effects of increased nearwork and reduce the impact of parental myopia, reducing the onset of myopia, and this approach has been validated in 3 randomized controlled trials. Other proposed risk factors need further work to demonstrate that they are independent and can be modified to reduce the onset of myopia.