Psychosocial Stress Over the Lifespan, Psychological Factors, and Cardiometabolic Risk in the Community.

OBJECTIVE: The complex relationship between psychosocial stress over the lifetime, psychological factors, and cardiometabolic risk is still poorly understood. Accordingly, our aims were (1) to independently assess the associations between childhood adversity, life-event stress in remote (earlier than the last 5 years), and recent adulthood and cardiometabolic risk, and (2) to determine the role of psychological factors including personality, coping, and depression in these associations. METHODS: The sample included 2674 adults, aged 35 to 66 years, randomly selected from urban area. Participants underwent a physical examination including the assessment of obesity markers, blood pressure, and blood lipid and glucose levels. Stress during adulthood was determined using the severity scores of 52 stressful life events. Information on adverse childhood experiences and major depressive disorders was collected using semistructured interviews, whereas personality traits and coping mechanisms were evaluated through questionnaires. RESULTS: Both childhood adversity and stress in remote adulthood were associated with elevated body mass index (ß [95% confidence interval {CI}] = 0.249 [0.029 to 0.468]; 0.020 [0.006 to 0.034]), waist circumference (ß [95% CI] = 0.061 [0.024 to 0.099]; 0.08 [0.04 to 0.11]), and the global cardiometabolic risk score (ß [95% CI] = 0.278 [0.017 to 0.540]; 0.017 [0.001 to 0.033]) after adjustment for sociodemographic, lifestyle, and psychological factors. In addition, childhood adversity was associated with low high density lipoprotein levels (ß [95% CI] = -0.021 [-0.042 to 0.000]), as well as increased fat mass and systolic blood pressure levels (ß [95% CI] = 0.506 [0.165 to 0.846]; 0.952 [0.165 to 1.740]) and stress in remote adulthood with apolipoprotein B levels (ß [95% CI] = 0.607 [0.312 to 0.901]). Psychological factors did not account for these associations and were not effect modifiers. CONCLUSIONS: Our data demonstrate that psychosocial stress during childhood and remote adulthood favor adiposity and abnormal lipid metabolism.

The plasma separation card as a novel solution for enhancing central laboratory capability for HIV-1 viral load monitoring in limited-access settings.

Measurement of HIV-1 viral load (VL) is essential for monitoring antiretroviral treatment (ART) efficacy. The preferred specimen type for VL is plasma, but in remote settings where collection and preservation of plasma many not be possible, dried blood spots (DBS) are often used instead. A new specimen collection matrix, the cobas plasma separation card (PSC, Roche Diagnostics Solutions), enables specimen preparation from a finger prick or venous blood, using a multi-layer absorption and filtration design that results in a specimen similar to dried plasma. We sought to confirm the correlation between VL results obtained using PSC prepared from venous blood to those from plasma or DBS, as well as PSC prepared with capillary blood from a finger prick. PSC, DBS and plasma were prepared with blood from HIV-1 infected persons attending a primary care clinic in Kampala, Uganda. VL in PSC and plasma was measured using cobas HIV-1 (Roche Diagnostics), while VL in DBS was measured with RealTime HIV-1 (Abbott Diagnostics). The correlation between VL from plasma and PSC made from capillary or venous blood was high (regression coefficient of determination r2 between 0.87 and 0.91), and there was good agreement based on mean bias (-0.14 to 0.24 log10 copies/mL) and classification of VL above or below 1000 copies/mL (91.4% agreement). In contrast, VL from DBS was lower than plasma or PSC (mean bias 0.51 to 0.63 log10 copies/mL) and not as well correlated (r2 0.78 to 0.81, 75.1-80.5% agreement). These results confirm the utility of PSC as an alternative specimen type for HIV-1 viral load measurement in areas where preparation and optimal storage or shipment of plasma is an obstacle to provision of treatment and care of HIV-1 infected people.

Spatial air pollution modelling for a West-African town.

Land use regression (LUR) modelling is a common approach used in European and Northern American epidemiological studies to assess urban and traffic related air pollution exposures. Studies applying LUR in Africa are lacking. A need exists to understand if this approach holds for an African setting, where urban features, pollutant exposures and data availability differ considerably from other continents. We developed a parsimonious regression model based on 48-hour nitrogen dioxide (NO2) concentrations measured at 40 sites in Kaédi, a medium sized West-African town, and variables generated in a geographic information system (GIS). Road variables and settlement land use characteristics were found to be important predictors of 48-hour NO2 concentration in the model. About 68% of concentration variability in the town was explained by the model. The model was internally validated by leave-one-out cross-validation and it was found to perform moderately well. Furthermore, its parameters were robust to sampling variation. We applied the model at 100 m pixels to create a map describing the broad spatial pattern of NO2 across Kaédi. In this research, we demonstrated the potential for LUR as a valid, cost-effective approach for air pollution modelling and mapping in an African town. If the methodology were to be adopted by environmental and public health authorities in these regions, it could provide a quick assessment of the local air pollution burden and potentially support air pollution policies and guidelines.