May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension

Aims Raised blood pressure (BP) is the biggest contributor to mortality and disease burden worldwide and fewer than half of those with hypertension are aware of it. May Measurement Month (MMM) is a global campaign set up in 2017, to raise awareness of high BP and as a pragmatic solution to a lack of formal screening worldwide. The 2018 campaign was expanded, aiming to include more participants and countries. Methods and results Eighty-nine countries participated in MMM 2018. Volunteers (≥18 years) were recruited through opportunistic sampling at a variety of screening sites. Each participant had three BP measurements and completed a questionnaire on demographic, lifestyle, and environmental factors. Hypertension was defined as a systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg, or taking antihypertensive medication. In total, 74.9% of screenees provided three BP readings. Multiple imputation using chained equations was used to impute missing readings. 1 504 963 individuals (mean age 45.3 years; 52.4% female) were screened. After multiple imputation, 502 079 (33.4%) individuals had hypertension, of whom 59.5% were aware of their diagnosis and 55.3% were taking antihypertensive medication. Of those on medication, 60.0% were controlled and of all hypertensives, 33.2% were controlled. We detected 224 285 individuals with untreated hypertension and 111 214 individuals with inadequately treated (systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg) hypertension. Conclusion May Measurement Month expanded significantly compared with 2017, including more participants in more countries. The campaign identified over 335 000 adults with untreated or inadequately treated hypertension. In the absence of systematic screening programmes, MMM was effective at raising awareness at least among these individuals at risk

Soil apparent conductivity measurements for planning and analysis of agricultural experiments: A case study from Western-Thailand

In experimental trials, the success or failure of agricultural improvements is commonly evaluated on the agronomic response of crops, using proper experimental designs with sufficient statistical power. Since fine-scale variability of the experimental site can reduce statistical power, efficiency gains in the experimental design can be achieved if this variation is known and used to design blocking, or some proxy variable is used as a covariate. Near-surface geophysical techniques such as electromagnetic induction (EMI), which describes subsurface properties non-invasively by measuring soil apparent conductivity (ECa), may be one source of this information. The motivation of our study was to investigate the effectiveness of EMI-derived ECa measurements for planning and analysis of agricultural experiments. ECa and plant height measurements (the response variable) were taken from an agroforestry experiment in Western Thailand, and their variability was quantified to simulate multiple realizations of ECa and the residuals of the response variable from treatment means. These were combined to produce simulated data from different experimental designs and treatment effects. The simulated data were then used to evaluate the statistical power by detecting three orthogonal contrasts among the treatments in the original experiment. We considered three experimental designs, a simple random design (SR), a complete randomized block design (CRB), and a complete randomized block design with spatially adjusted blocks on plot means of ECa (CRBECa). Using analysis of variance (ANOVA), the smallest effect sizes could be detected with the CRBECa design, which indicates that ECa measurements could be used in the planning phase of an experiment to achieve efficiencies by improved blocking. In contrast, analysis of covariance (ANCOVA) demonstrated that substantial power improvements could be gained when ECa was considered as a covariate in the analysis. We therefore recommend that ECa measurements should be used to characterize subsurface variability of experimental sites and to support the statistical analysis of agricultural experiments

Towards sustainable food systems: the concept of agroecology and how it questions current research practices. A review

Introduction. Multiple environmental and socio-economic indicators show that our current agriculture and the organization of the food system need to be revised. Agroecology has been proposed as a promising concept for achieving greater sustainability. This paper offers an overview and discussion of the concept based on existing literature and case studies, and explores the way it questions our current research approaches and education paradigms. Literature. In order to improve the sustainability of agriculture, the use of external and chemical inputs needs to be minimized. Agroecological farming practices seek to optimize ecological processes, thus minimizing the need for external inputs by providing an array of ecosystem services. Implementing such practices challenges the current structure of the food system, which has been criticized for its lack of social relevance and economic viability. An agroecological approach includes all stakeholders, from field to fork, in the discussion, design and development of future food systems. This inclusion of various disciplines and stakeholders raises issues about scientists and their research practices, as well as about the education of the next generation of scientists. Conclusions. Agroecology is based on the concept that agricultural practices and food systems cannot be dissociated because they belong to the same natural and socio-economic context. Clearly, agroecology is not a silver-bullet, but its principles can serve as avenues for rethinking the current approaches towards achieving greater sustainability. Adapting research approaches in line with indicators that promote inter- and transdisciplinary research is essential if progress is to be made