Non-linear Effects Of Age Research Articles

#960 Trends in eGFR and ultra-processed food intake in relationship to income among United States adults

Abstract Background and Aims Ultra-processed foods (UPF) are formulations of ingredients that are mostly of exclusive industrial use and may contain additives like artificial colors, flavors, or stabilizers. The sale and consumption of these foods has been increasing despite their associations with increased risk for several non-communicable diseases including chronic kidney disease. Ultra-processed foods are widely accessible, more shelf-stable and convenient while tending to be more affordable and lower in nutritional quality. The aim of this study was to evaluate trends in kidney function and UPF intake and temporal effect of income among United States (US) adults. Method We used dietary intake data collected with 24-hour dietary recalls from 35160 US adults across 8 cycles of the National Health and Nutrition Examination Survey (NHANES) (from 2003-2004 to 2017-2018 cycles) to categorize intake using the Nova processed food classification system. Poisson regression models were used to assess the 15-year trends in populations at risk for kidney function decline (measured by estimated glomerular filtration rate [eGFR]) and higher percentage of calories from UPF (PC-UPF) consumed along with the temporal effect of income in select subpopulations and adjusted for age and gender and non-linear effects of income and age). Results Over the past 15 years eGFR, PC-UPF, and self-reported income continue to increase among US adults. However, the associations between eGFR, PC-UPF and income are quite complex, vary by subpopulation and non-linearly depend on age. Specifically, among Black adults adjusted for age (age2) and gender, eGFR was the lowest (85 mL/min/1.73 m2, 95% CI: 84.9, 85.0 mL/min/1.73 m2) among those with the lowest ($2,500) and highest ($125,000) income (p = 0.0000000579 for a quadratic term of income), respectively. Hispanic and Mexican Americans also have similar pattern eGFR with the lowest and highest income though the eGFR is consistently higher than White and Black Americans. Across cycles, White Americans with the lowest income ($2,500) have the highest PC-UPF (range: 57-62%, p <2e-16; mean: 59.4%, 95% CI: 59.3, 59.6%) while Black Americans with the lowest ($2,500) and highest income ($125,000) have the highest PC-UPF (range: 53-58%, p <2e-16; mean: 54.8%, 95% CI: 54.3, 55.4%). Income levels does not predict PC-UPF among Mexican Americans. Overall, the PC-UPF is steadily increasing in all population subgroups. Conclusion Among Non-White US adults, higher eGFR was associated with higher income until reaching a group-specific threshold when the relationship reversed. We observed a similar threshold pattern in the association between PC-UPF and income among Black and Hispanic Americans. These complex non-linear relationships between eGFR, PC-UPF and income are driven in part by age-related association and warrant further exploration.

Meta-analysis of epigenetic aging in schizophrenia reveals multifaceted relationships with age, sex, illness duration, and polygenic risk

BackgroundThe study of biological age acceleration may help identify at-risk individuals and reduce the rising global burden of age-related diseases. Using DNA methylation (DNAm) clocks, we investigated biological aging in schizophrenia (SCZ), a mental illness that is associated with an increased prevalence of age-related disabilities and morbidities. In a whole blood DNAm sample of 1090 SCZ cases and 1206 controls across four European cohorts, we performed a meta-analysis of differential aging using three DNAm clocks (i.e., Hannum, Horvath, and Levine). To dissect how DNAm aging contributes to SCZ, we integrated information on duration of illness and SCZ polygenic risk, as well as stratified our analyses by chronological age and biological sex.ResultsWe found that blood-based DNAm aging is significantly altered in SCZ independent from duration of the illness since onset. We observed sex-specific and nonlinear age effects that differed between clocks and point to possible distinct age windows of altered aging in SCZ. Most notably, intrinsic cellular age (Horvath clock) is decelerated in SCZ cases in young adulthood, while phenotypic age (Levine clock) is accelerated in later adulthood compared to controls. Accelerated phenotypic aging was most pronounced in women with SCZ carrying a high polygenic burden with an age acceleration of + 3.82 years (CI 2.02–5.61, P = 1.1E−03). Phenotypic aging and SCZ polygenic risk contributed additively to the illness and together explained up to 14.38% of the variance in disease status.ConclusionsOur study contributes to the growing body of evidence of altered DNAm aging in SCZ and points to intrinsic age deceleration in younger adulthood and phenotypic age acceleration in later adulthood in SCZ. Since increased phenotypic age is associated with increased risk of all-cause mortality, our findings indicate that specific and identifiable patient groups are at increased mortality risk as measured by the Levine clock. Our study did not find that DNAm aging could be explained by the duration of illness of patients, but we did observe age- and sex-specific effects that warrant further investigation. Finally, our results show that combining genetic and epigenetic predictors can improve predictions of disease outcomes and may help with disease management in schizophrenia.

The Neurobiology of Life Course Socioeconomic Conditions and Associated Cognitive Performance in Middle to Late Adulthood.

Despite major advances, our understanding of the neurobiology of life course socioeconomic conditions is still scarce. This study aimed to provide insight into the pathways linking socioeconomic exposures-household income, last known occupational position, and life course socioeconomic trajectories-with brain microstructure and cognitive performance in middle to late adulthood. We assessed socioeconomic conditions alongside quantitative relaxometry and diffusion-weighted magnetic resonance imaging indicators of brain tissue microstructure and cognitive performance in a sample of community-dwelling men and women (N = 751, aged 50-91 years). We adjusted the applied regression analyses and structural equation models for the linear and nonlinear effects of age, sex, education, cardiovascular risk factors, and the presence of depression, anxiety, and substance use disorders. Individuals from lower-income households showed signs of advanced brain white matter (WM) aging with greater mean diffusivity (MD), lower neurite density, lower myelination, and lower iron content. The association between household income and MD was mediated by neurite density (B = 0.084, p = 0.003) and myelination (B = 0.019, p = 0.009); MD partially mediated the association between household income and cognitive performance (B = 0.017, p < 0.05). Household income moderated the relation between WM microstructure and cognitive performance, such that greater MD, lower myelination, or lower neurite density was only associated with poorer cognitive performance among individuals from lower-income households. Individuals from higher-income households showed preserved cognitive performance even with greater MD, lower myelination, or lower neurite density. These findings provide novel mechanistic insights into the associations between socioeconomic conditions, brain anatomy, and cognitive performance in middle to late adulthood.

The Effectiveness of the Third Dose of COVID-19 Vaccine: When Should It Be Performed?

COVID-19 vaccination is the most significant step toward the long-term mitigation of SARS-CoV-2-related complication, avoiding disease and death and decreasing virus spread. This study aimed to evaluate, in a real-world setting, booster dose effectiveness to reduce COVID-19 risk considering the amount of time after the end of the two-dose vaccination cycle. A sub-analysis was conducted to adjust the booster dose effect for occupational and demographic factors. About 16,000 COVID-19-vaccinated HCWs of three University Hospital Networks in Milan (HN1/HN2/HN3) were included in the study. Data were collected by Occupational Health Physicians of the HNs within specific computerized databases. In univariable analysis, booster dose administration displayed a slightly higher risk of infection with respect to not receiving it, OR = 1.18, with 95% confidence interval (C.I) [0.99, 1.41]. When the model was adjusted with the modulating effect of time from the completion of the vaccination cycle on booster dose administration, the latter resulted in strong protective effect against infection, OR = 0.43, 95% CI [0.26, 0.74]. However, considering the modifying influence of time from the vaccination cycle's completion, the administration of booster doses appeared to have a protective effect against infection. In HN1, students and resident physicians displayed lower odds of infection with respect to physicians. Lastly, a non-linear effect of age was reported. Our findings suggest that the correct timing in vaccine scheduling and administration is critical to vaccine effectiveness. These findings, applicable to all vaccinations, should help in setting up more effective vaccination strategies.

Lifespan development of thalamic nuclei and characterizing thalamic nuclei abnormalities in schizophrenia using normative modeling.

Thalamic abnormalities have been repeatedly implicated in the pathophysiology of schizophrenia and other neurodevelopmental disorders. Uncovering the etiology of thalamic abnormalities and how they may contribute to illness phenotypes faces at least two obstacles. First, the typical developmental trajectories of thalamic nuclei and their association with cognition across the lifespan are largely unknown. Second, modest effect sizes indicate marked individual differences and pose a significant challenge to personalized medicine. To address these knowledge gaps, we characterized the development of thalamic nuclei volumes using normative models generated from the Human Connectome Project Lifespan datasets (5-100+ years), then applied them to an independent clinical cohort to determine the frequency of thalamic volume deviations in people with schizophrenia (17-61 years). Normative models revealed diverse non-linear age effects across the lifespan. Association nuclei exhibited negative age effects during youth but stabilized in adulthood until turning negative again with older age. Sensorimotor nuclei volumes remained relatively stable through youth and adulthood until also turning negative with older age. Up to 18% of individuals with schizophrenia exhibited abnormally small (i.e., below the 5th centile) mediodorsal and pulvinar volumes, and the degree of deviation, but not raw volumes, correlated with the severity of cognitive impairment. While case-control differences are robust, only a minority of patients demonstrate unusually small thalamic nuclei volumes. Normative modeling enables the identification of these individuals, which is a necessary step toward precision medicine.

Effects of gene dosage and development on subcortical nuclei volumes in individuals with 22q11.2 copy number variations.

The 22q11.2 locus contains genes critical for brain development. Reciprocal Copy Number Variations (CNVs) at this locus impact risk for neurodevelopmental and psychiatric disorders. Both 22q11.2 deletions (22qDel) and duplications (22qDup) are associated with autism, but 22qDel uniquely elevates schizophrenia risk. Understanding brain phenotypes associated with these highly penetrant CNVs can provide insights into genetic pathways underlying neuropsychiatric disorders. Human neuroimaging and animal models indicate subcortical brain alterations in 22qDel, yet little is known about developmental differences across specific nuclei between reciprocal 22q11.2 CNV carriers and typically developing (TD) controls. We conducted a longitudinal MRI study in a total of 385 scans from 22qDel (n = 96, scans = 191, 53.1% female), 22qDup (n = 37, scans = 64, 45.9% female), and TD controls (n = 80, scans = 130, 51.2% female), across a wide age range (5.5-49.5 years). Volumes of the thalamus, hippocampus, amygdala, and anatomical subregions were estimated using FreeSurfer, and the linear effects of 22q11.2 gene dosage and non-linear effects of age were characterized with generalized additive mixed models (GAMMs). Positive gene dosage effects (volume increasing with copy number) were observed for total intracranial and whole hippocampus volumes, but not whole thalamus or amygdala volumes. Several amygdala subregions exhibited similar positive effects, with bi-directional effects found across thalamic nuclei. Distinct age-related trajectories were observed across the three groups. Notably, both 22qDel and 22qDup carriers exhibited flattened development of hippocampal CA2/3 subfields relative to TD controls. This study provides novel insights into the impact of 22q11.2 CNVs on subcortical brain structures and their developmental trajectories.

Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.

Spatial inequalities and non-linear association of continuous variables with mortality risk of liver transplantation in Iran: a retrospective cohort study

Liver transplantation is the second most common solid organ transplant and the best option for liver failure. Of course, patient survival after transplantation depends on many risk factors. The aim of this study was to investigate the spatial and non-linear effects of continuous risk factors on patient survival after liver transplantation. This retrospective cohort study (n = 3148) used data on liver transplantation in Iran (2004–2019). A generalized additive model with spatial effects and non-linear effects of age and Model for End-Stage Liver Disease (MELD) score variables by penalized spline was used. The majority of patients were male (63.3%), with a mean (SD) age of 42.65 (13.31) and a mean (SD) MELD score of 24.43 (6.72). The 1, 5, and 10-year survival rates were 88.2%, 84.6%, and 82.5% respectively. The non-linear effect showed a steeper slope of the age effect on the hazard of death after the age of 50 (p < 0.05), and the MELD score had a direct but non-linear relationship with the hazard of death (p < 0.05). In the spatial pattern, the provinces with a greater distance from the transplant center had significantly fewer old patients than other provinces. Also, more distant provinces with an older transplant age had higher post-transplant mortality rates. Our study showed that it is better to take age and MELD score into account in postoperative care. The spatial pattern of mortality risk reflects inequalities in access to transplantation and public health services after transplantation.

Individualised prediction of major bleeding in patients with atrial fibrillation treated with anticoagulation.

Anticoagulation in atrial fibrillation (AF) increases the risk of major bleeding. No predictive model has hitherto provided estimates of the absolute risk for individual patients. To predict the individual 1-year risk of major bleeding in patients with AF taking anticoagulants and evaluate the importance of individual risk factors. A nationwide register-based cohort study. Danish patients with first-time non-valvular AF who redeemed anticoagulants within 7 days after diagnosis. The individual absolute risk of major bleeding was estimated from a logistic regression model (the Calculator of Absolute Bleeding Risk/CABS model) utilising the same risk factors as HAS-BLED, except allowing non-linear age effects, and allowing effect modification of all factors according to history of bleeding. The logistic regression was assessed in term of discrimination using the Area Under the ROC curve (AUC) and calibration. Among 76,102 patients with AF redeeming anticoagulants, 2,406 suffered a major bleeding within 1 year. History of bleeding was the strongest predictor, and age significantly modified the risk. The CABS model superseded HAS-BLED score with regards to discrimination (AUC 0.646 vs 0.615, p<0.001) and calibrated well. A typical male patient was 70-years old without any risk factors and he had a 1-year bleeding risk of 1.4% (1.2; 1.6) while a typical female patient was 73-years old, had hypertension and a 1-year bleeding risk of 2.2% (1.9;2.6). We propose CABS as a tool for prediction of individual absolute risks of major bleeding in patients with AF taking anticoagulant. The predicted absolute risk can be used for patient counselling.

Does functional system segregation mediate the effects of lifestyle on cognition in older adults?

Healthy aging is typically accompanied by cognitive decline. Previous work has shown that engaging in multiple, non-work activities during midlife can have a protective effect on cognition several decades later, rendering it less dependent on brain structural health; the definition of “cognitive reserve”. Other work has shown that increasing age is associated with reduced segregation of large-scale brain functional networks. Here we tested the hypothesis that functional segregation (SyS) mediates this effect of middle-aged lifestyle on late-life cognition. We used fMRI data from three tasks in the CamCAN dataset, together with cognitive data on fluid intelligence, episodic memory, and retrospective lifestyle data from the Lifetime of Experiences Questionnaire (LEQ). In all three tasks, we showed that SyS related to fluid intelligence even after adjusting for the (nonlinear) age effects. However, we found no evidence that SyS in late-life mediated the relationship between non-specific (non-occupation) midlife activities and either measure of cognition in late-life. Thus, the brain correlates of cognitive reserve arising from mid-life activities remain to be discovered.

Regression-based normative data for the D-KEFS Color-Word Interference Test in Norwegian adults ages 20–85

Objective: The Delis-Kaplan Executive Function System (D-KEFS) Color-Word-Interference Test (CWIT; AKA Stroop test) is a widely used measure of processing speed and executive function. While test materials and instructions have been translated to Norwegian, only American age-adjusted norms from D-KEFS are available in Norway. We here develop norms in a sample of 1011 Norwegians between 20 and 85 years. We provide indexes for stability over time and assess demographic adjustments applying the D-KEFS norms. Method: Participants were healthy Norwegian adults from Center for Lifespan Changes in Brain and Cognition (LCBC) (n = 899), the Dementia Disease Initiation (n = 77), and Oslo MCI (n = 35). Using regression-based norming, we estimated linear and non-linear effects of age, education, and sex on the CWIT 1-4 subtests. Stability over time was assessed with intraclass correlation coefficients (ICC). The normative adjustment of the D-KEFS norms was assessed with linear regression models. Results: Increasing age was associated with slower completion on all CWIT subtests in a non-linear fashion (accelerated lowering of performance with older age). Women performed better on CWIT-1&3. Higher education predicted faster completion time on CWIT-3&4. The original age-adjusted norms from D-KEFS did not adjust for sex or education. Furthermore, we observed significant, albeit small effects of age on all CWIT subtests. ICC analyses indicated moderate to good stability over time. Conclusion: We present demographically adjusted regression-based norms and stability indexes for the D-KEFS CWIT subtests. US D-KEFS norms may be inaccurate for Norwegians with high or low educational attainment, especially women.

Age and postoperative opioid use in women undergoing pelvic organ prolapse surgery.

Our objective was to explore the relation between patient age and postoperative opioid use up to 24 hours following pelvic organ prolapse (POP) surgery. We conducted a prospective cohort study following 335 women ranging in age from 26 to 82 years who underwent surgery for multi-compartment POP at a tertiary center in Alberta, Canada. Patient characteristics were measured using baseline questionnaires. Perioperative data were collected from medical chart review during and up to 24 hours following surgery. We used logistic regression to analyze the odds of being opioid-free and linear regression to analyze mean differences in opioid dose, measured as total morphine equivalent daily dose, exploring for a potential non-linear effect of age. Adjusted models controlled for preoperative pain, surgical characteristics and patient health factors. Overall, age was positively associated with greater odds of being opioid-free in the first 24 hours after surgery (adjusted odds ratio per increasing year of age = 1.07, 95% confidence interval [CI] 1.04-1.09, n = 332 women). Among opioid users, age was inversely associated with total opioid dose (adjusted mean difference per increasing year of age = 0.71 mg morphine equivalent daily dose, 95% CI -0.99 to -0.44, n = 204 women). There was no evidence of a non-linear relation between age and postoperative opioid use or dose. In the context of POP surgery, we found that younger women were more likely to use opioids after surgery and to use a higher dose in the first 24 hours when compared with older women. These findings support physicians to consider age when counseling POP patients regarding pain management after surgery, and to direct resources aimed at opioid-free pain control towards younger patients.

Why Do the Public Participate in Community Regeneration Co-production? The Case of He Ping, Tianjin

The public’s co-production behaviors are influenced by individual and organizational factors. This article analyzes these factors using 2110 questionnaire data from He Ping, Tianjin. Results show that self-efficacy, solidarity incentives, spiritual incentives and inclusive administrative culture have a statistically significant positive correlation with public coproduction behaviors, while the impact of material incentives is limited. In addition to the nonlinear effect of age, middle-aged women, homeowners, middle-income people, and the public with bachelor’s degree are more likely to participate in community regeneration coproduction. The findings provide theoretical and practical implications for the existing co-production theory and public administration practitioners.

The evolution of the adolescent growth spurt: Urinary biomarkers of bone turnover in wild chimpanzees (Pan troglodytes)

Life history theory addresses how organisms balance development and reproduction. Mammals usually invest considerable energy into growth in infancy, and they do so incrementally less until reaching adult body size, when they shift energy to reproduction. Humans are unusual in having a long adolescence when energy is invested in both reproduction and growth, including rapid skeletal growth around puberty. Although many primates, especially in captivity, experience accelerated growth in mass around puberty, it remains unclear whether this represents skeletal growth. Without data on skeletal growth in nonhuman primates, anthropologists have often assumed the adolescent growth spurt is uniquely human, and hypotheses for its evolution have focused on other uniquely human traits. The lack of data is largely due to methodological difficulties of assessing skeletal growth in wild primates. Here, we use two urinary markers of bone turnover-osteocalcin and collagen-to study skeletal growth in a large, cross-sectional sample of wild chimpanzees (Pan troglodytes) at Ngogo, Kibale National Park, Uganda. For both bone turnover markers, we found a nonlinear effect of age, which was largely driven by males. For male chimpanzees, values for osteocalcin and collagen peaked at age 9.4 years and 10.8 years, respectively, which corresponds to early and middle adolescence. Notably, collagen values increased from 4.5 to 9 years, suggesting faster growth during early adolescence compared to late infancy. Biomarker levels plateaued at 20 years in both sexes, suggesting skeletal growth continues until then. Additional data, notably on females and infants of both sexes, are needed, as are longitudinal samples. However, our cross-sectional analysis suggests an adolescent growth spurt in the skeleton of chimpanzees, especially for males. Biologists should avoid claiming that the adolescent growth spurt is uniquely human, and hypotheses for the patterns of human growth should consider variation in our primate relatives.

Age, period and cohort effects in depression prevalence among Canadians 65+, 1994 to 2018: A multi-level analysis.

The nature of the Canadian population 65+ has changed considerably over the past several decades. They comprise a larger proportion of the population, are better educated, and are wealthier than previous generations. We estimate the contributions of chronological aging, temporal periods, and birth cohort effects on the trends in the major depressive episode (MDE) prevalence among Canadian seniors from 1994/1995 to 2017/2018. Using data from two sets of national health surveys, the National Population Health Survey (NPHS) and the Canadian Community Health Survey (CCHS). Pooled data on 150,246 survey respondents aged 65+ from 16 repeated cross-sectional surveys are included. Hierarchical regression age-period-cohort models were used to visualize the linear and non-linear effects of age, period, and cohort trends in late-life depression. We found that: the prevalence of MDE in later life fluctuated non-significantly during the study time period; the probability of developing MDE declined with increasing age from 65 to 80+ (β = -.32, p = .027). The significant quadratic birth cohort predictor showed a non-linear increasing association with the prevalence of MDE from the earlier to later-born cohorts (β = .01, p = .049). We also found that females 65+ were consistently more likely to be depressed than males 65+ (β = .47, p = .007). The significantly negative "age × female" interaction shows that age exerts a greater effect on females' probability of developing MDE than males (β = -.09, p = .011). There were no consistent significant period effects but there were peaks in prevalence around 2001, 2008, and 2012 which corresponded to some recent historical events. Our moderation analysis documents that lower levels of education significantly contributed to the higher rates of depression among cohorts born earlier in the 20th century. Our findings show the presence of strong chronological age and cohort effects and weaker period effects on the prevalence of late-life depression in Canadian seniors.

Age-associated sex and asymmetry differentiation in hemispheric and lobar cortical ribbon complexity across adulthood: A UK Biobank imaging study.

Cortical morphology changes with ageing and age-related neurodegenerative diseases. Previous studies suggest that the age effect is more pronounced in the frontal lobe. However, our knowledge of structural complexity changes in male and female brains is still limited. We measured cortical ribbon complexity through fractal dimension (FD) analysis at the hemisphere and lobe level in 7010 individuals from the UK Biobank imaging cohort to study age-related sex differences (3332 males, age ranged 45-79 years). FD decreases significantly with age and sexual dimorphism exists. With correction for brain size, females showed higher complexity in the left hemisphere and left and right parietal lobes whereas males showed higher complexity in the right temporal and left and right occipital lobes. A nonlinear age effect was observed in the left and right frontal, and right temporal lobes. Differential patterns of age effects were observed in both sexes with relatively more age-affected regions in males. Significantly higher rightward asymmetries at hemisphere, frontal, parietal, and occipital lobe level and higher leftward asymmetry in temporal lobe were observed. There was no age-by-sex-by asymmetry interaction in any region. When controlling for brain size, the leftward hemispheric, and temporal lobe asymmetry decreased with age. Males had significantly lower asymmetry between hemispheres and higher asymmetry in the parietal and occipital lobes than females. This work provides distinct patterns of age-related sex and asymmetry differences that can aid in the future development of sex-specific models of the normal brain to ascribe cognitive functional significance of these patterns in ageing.

Spatiotemporal Variation and Predictors of Unsuppressed Viral Load among HIV-Positive Men and Women in Rural and Peri-Urban KwaZulu-Natal, South Africa.

Unsuppressed HIV viral load is an important marker of sustained HIV transmission. We investigated the prevalence, predictors, and high-risk areas of unsuppressed HIV viral load among HIV-positive men and women. Unsuppressed HIV viral load was defined as viral load of ≥400 copies/mL. Data from the HIV Incidence District Surveillance System (HIPSS), a longitudinal study undertaken between June 2014 to June 2016 among men and women aged 15–49 years in rural and peri-urban KwaZulu-Natal, South Africa, were analysed. A Bayesian geoadditive regression model which includes a spatial effect for a small enumeration area was applied using an integrated nested Laplace approximation (INLA) function while accounting for unobserved factors, non-linear effects of selected continuous variables, and spatial autocorrelation. The prevalence of unsuppressed HIV viral load was 46.1% [95% CI: 44.3–47.8]. Predictors of unsuppressed HIV viral load were incomplete high school education, being away from home for more than a month, alcohol consumption, no prior knowledge of HIV status, not ever tested for HIV, not on antiretroviral therapy (ART), on tuberculosis (TB) medication, having two or more sexual partners in the last 12 months, and having a CD4 cell count of <350 cells/μL. A positive non-linear effect of age, household size, and the number of lifetime HIV tests was identified. The higher-risk pattern of unsuppressed HIV viral load occurred in the northwest and northeast of the study area. Identifying predictors of unsuppressed viral load in a localized geographic area and information from spatial risk maps are important for targeted prevention and treatment programs to reduce the transmission of HIV.

Impact of Age and Gender on Entrepreneurial Self-Efficacy and Fear of Entrepreneurial Failure

This study applies life-stage theory to investigate the still ill-understood effects of age on the behavioral tendencies of male and female entrepreneurs. Hypotheses for effects on entrepreneurial self-efficacy and fear of entrepreneurial failure are tested in a gender-stratified cross-sectional random sample using U.S. Global Entrepreneurship Monitor data (2013 – 2018). Results support strong non-linear age effects and challenge the dominant assumptions in the established entrepreneurship literature that what we know about middle-aged entrepreneurs will more or less also hold for the increasingly important cohorts of junior and senior entrepreneurs. Age effects also differ substantially across gender. Taken together, these findings outline highly complex age effects and suggest the urgent need to account explicitly for both age and gender effects in models theorizing about entrepreneurial behavior and outcomes.

Bayesian Spatial Modeling of Diabetes and Hypertension: Results from the South Africa General Household Survey

Determining spatial links between disease risk and socio-demographic characteristics is vital in disease management and policymaking. However, data are subject to complexities caused by heterogeneity across host classes and space epidemic processes. This study aims to implement a spatially varying coefficient (SVC) model to account for non-stationarity in the effect of covariates. Using the South Africa general household survey, we study the provincial variation of people living with diabetes and hypertension risk through the SVC model. The people living with diabetes and hypertension risk are modeled using a logistic model that includes spatially unstructured and spatially structured random effects. Spatial smoothness priors for the spatially structured component are employed in modeling, namely, a Gaussian Markov random field (GMRF), a second-order random walk (RW2), and a conditional autoregressive (CAR) model. The SVC model is used to relax the stationarity assumption in which non-linear effects of age are captured through the RW2 and allow the mean effect to vary spatially using a CAR model. Results highlight a non-linear relationship between age and people living with diabetes and hypertension. The SVC models outperform the stationary models. The results suggest significant provincial differences, and the maps provided can guide policymakers in carefully exploiting the available resources for more cost-effective interventions.

Developing PHarmacie-R: A bedside risk prediction tool with a medicines management focus to identify risk of hospital readmission.

The imperative to identify patients at risk of medication-related harm has never been greater. Hospital clinicians cannot easily predict risk of readmission or harm. Candidate variables associated with medication-related harm derived from the literature or significantly represented in a complex patient cohort have been previously described by PHarmacie-4. With a focus on polypharmacy and high-risk medicines in vulnerable patient cohorts, PHarmacie-4 was easy to use and highlighted risks. However it over-estimated risk, reducing its usefulness in stratifying risk of readmission. Develop a risk prediction tool built into a smart phone app, enabling clinicians to identify and refer high-risk patients for an early post-discharge medicines review. Demonstrate usability, real world application and validity in an independent dataset. A retrospective, observational study was conducted with 1201 randomly selected patients admitted to Sir Charles Gairdner Hospital between June 1, 2016 to December 31, 2016. Patient characteristics and outcomes of interest were reported, including unplanned hospital utilisation at 30, 60 and 90 days post-discharge. Using multivariable logistic regression modelling, an algorithm was developed, built into a smart phone app and used and validated in an independent dataset. 738 patients (61%) were included in the derivation sample. The best predictive performance was achieved by PHarmacie-R (C-statistic 0.72, 95% CI 0.68-0.75) which included PHarmacie-4 risk variables, a non-linear effect of age, unplanned hospital utilisation in the preceding six months and gender. The independent validation dataset had a C-statistic of 0.64 (95% CI 0.56-0.72). PHarmacie-R is the first readmission risk prediction tool, built into a smart phone app, focussing on polypharmacy and high-risk medicines in vulnerable patients. It can assist clinical pharmacists to identify medical inpatients who may benefit from early post-discharge medication management services. External validation is needed to enable application in other clinical settings.