RESULTS: Important issues were identified during the data harmonisation process relating to data ownership, sharing methodologies and ethical concerns. Measures were assessed across eight domains; demographic; dietary; clinical and anthropometric; medical history; hypertension knowledge; physical activity; behavioural (smoking and alcohol); and biochemical domains. Identifying validated measures relevant across a variety of settings presented some difficulties. The resulting GACD hypertension data dictionary comprises 67 consensus measures. Of the 14 responding teams, only two teams were including more than 50 consensus variables, five teams were including between 25 and 50 consensus variables and four teams were including between 6 and 24 consensus variables, one team did not provide details of the variables collected and two teams did not include any of the consensus variables as the project had already commenced or the measures were not relevant to their study.
CONCLUSIONS: Deriving consensus measures across diverse research projects and contexts was challenging. The major barrier to their implementation was related to the time taken to develop and present these measures. Inclusion of consensus measures into future funding announcements would facilitate researchers integrating these measures within application protocols. We suggest that adoption of consensus measures developed here, across the field of hypertension, would help advance the science in this area, allowing for more comparable data sets and generalizable inferences.
Electronic Supplementary Material: Supplementary material is available for this article at 10.1007/s13770-016-9093-2 and is accessible for authorized users.
METHODS: Data collected 2001 to 2016 from PHIVA 10-19 years of age within a regional Asian cohort were analyzed using competing risk time-to-event and Poisson regression analyses to describe the nature and incidence of morbidity events and hospitalizations and identify factors associated with disease-related, treatment-related and overall morbidity. Morbidity was defined according to World Health Organization clinical staging criteria and U.S. National Institutes of Health Division of AIDS criteria.
RESULTS: A total 3,448 PHIVA contributed 17,778 person-years. Median age at HIV diagnosis was 5.5 years, and ART initiation was 6.9 years. There were 2,562 morbidity events and 307 hospitalizations. Cumulative incidence for any morbidity was 51.7%, and hospitalization was 10.0%. Early adolescence was dominated by disease-related infectious morbidity, with a trend toward noninfectious and treatment-related morbidity in later adolescence. Higher overall morbidity rates were associated with a CD4 count <350 cells/µL, HIV viral load ≥10,000 copies/mL and experiencing prior morbidity at age <10 years. Lower overall morbidity rates were found for those 15-19 years of age compared with 10-14 years and those who initiated ART at age 5-9 years compared with <5 or ≥10 years.
CONCLUSIONS: Half of our PHIVA cohort experienced a morbidity event, with a trend from disease-related infectious events to treatment-related and noninfectious events as PHIVA age. ART initiation to prevent immune system damage, optimize virologic control and minimize childhood morbidity are key to limiting adolescent morbidity.
METHODS: Malaria is a notifiable infection in Malaysia. The data used in this study were extracted from the Disease Control Division, Ministry of Health Malaysia, contributed by the hospitals and health clinics throughout Malaysia. The population data used in this study was extracted from the Department of Statistics Malaysia. Data analyses were performed using Microsoft Excel. Data used for mapping are available at EPSG:4326 WGS84 CRS (Coordinate Reference System). Shapefile was obtained from igismap. Mapping and plotting of the map were performed using QGIS.
RESULTS: Between 2000 and 2007, human malaria contributed 100% of reported malaria and 18-46 deaths per year in Malaysia. Between 2008 and 2017, indigenous malaria cases decreased from 6071 to 85 (98.6% reduction), while during the same period, zoonotic Plasmodium knowlesi cases increased from 376 to 3614 cases (an 861% increase). The year 2018 marked the first year that Malaysia did not report any indigenous cases of malaria caused by human malaria parasites. However, there was an increasing trend of P. knowlesi cases, with a total of 4131 cases reported in that year. Although the increased incidence of P. knowlesi cases can be attributed to various factors including improved diagnostic capacity, reduction in human malaria cases, and increase in awareness of P. knowlesi, more than 50% of P. knowlesi cases were associated with agriculture and plantation activities, with a large remainder proportion linked to forest-related activities.
CONCLUSIONS: Malaysia has entered the elimination phase of malaria control. Zoonotic malaria, however, is increasing exponentially and becoming a significant public health problem. Improved inter-sectoral collaboration is required in order to develop a more integrated effort to control zoonotic malaria. Local political commitment and the provision of technical support from the World Health Organization will help to create focused and concerted efforts towards ensuring the success of the National Malaria Elimination Strategic Plan.