Results From the Epidemiology of Chronic Diseases Cohort Study 3

Introduction: The public health problem of food insecurity also affects the elderly population. This study aimed to estimate the prevalence of household food insecurity and its associations with chronic disease and health-related quality of life characteristics in individuals ≥65 years of age living in the community in Portugal. Methods: The data were collected from the Epidemiology of Chronic Diseases Cohort Study 3 (EpiDoC3)-Promoting Food Security Study (2015-2016), which was the third evaluation wave of the EpiDoC and represented the Portuguese adult population. Food insecurity was assessed using a psychometric scale adapted from the Brazilian Food Insecurity Scale. The data on sociodemographic variables, chronic disease, and management of chronic disease were self-reported. Health-related quality of life were assessed using the European Quality of Life Survey (version validated for the Portuguese population). Logistic regression models were used to determine crude and adjusted odds ratios (for age group, gender, region, and education). The dependent variable was the perceived level of food security. Results: Among older adults, 23% were living in a food-insecure household. The odds of living in a food-insecure household were higher for individuals in the 70-74 years age group (odds ratio (OR) = 1.405, 95% confidence interval (CI) 1.392-1.417), females (OR = 1.545, 95% CI 1.534-1.556), those with less education (OR = 3.355, 95% CI 3.306-3.404), low income (OR = 4,150, 95% CI 4.091-4.210), and those reporting it was very difficult to live with the current income (OR = 16.665, 95% CI 16.482-16.851). The odds of having a chronic disease were also greater among individuals living in food-insecure households: diabetes mellitus (OR = 1.832, 95% CI 1.818-1.846), pulmonary diseases (OR = 1.628, 95% CI 1.606-1.651), cardiac disease (OR = 1.329, 95% CI 1.319-1.340), obesity (OR = 1.493, 95% CI 1.477-1.508), those who reduced their frequency of medical visits (OR = 4.381, 95% CI 4.334-4.428), and who stopped taking medication due to economic difficulties (OR = 5.477, 95% CI 5.422-5.532). Older adults in food-insecure households had lower health-related quality of life (OR = 0.212, 95% CI 0.210-0.214). Conclusions: Our findings indicated that food insecurity was significantly associated with economic factors, higher values for prevalence of chronic diseases, poor management of chronic diseases, and decreased health-related quality of life in older adults living in the community.publishersversionpublishe

Accurate strain measurements in highly strained Ge microbridges

Ge under high strain is predicted to become a direct bandgap semiconductor. Very large deformations can be introduced using microbridge devices. However, at the microscale, strain values are commonly deduced from Raman spectroscopy using empirical linear models only established up to 1.2% for uniaxial stress. In this work, we calibrate the Raman-strain relation at higher strain using synchrotron based microdiffraction. The Ge microbridges show unprecedented high tensile strain up to 4.9 % corresponding to an unexpected 9.9 cm-1 Raman shift. We demonstrate experimentally and theoretically that the Raman strain relation is not linear and we provide a more accurate expression.Comment: 10 pages, 4 figure

Food Insecurity in Older Adults: Results From the Epidemiology of Chronic Diseases Cohort Study 3

Introduction: The public health problem of food insecurity also affects the elderly population. This study aimed to estimate the prevalence of household food insecurity and its associations with chronic disease and health-related quality of life characteristics in individuals ≥65 years of age living in the community in Portugal.Methods: The data were collected from the Epidemiology of Chronic Diseases Cohort Study 3 (EpiDoC3)—Promoting Food Security Study (2015–2016), which was the third evaluation wave of the EpiDoC and represented the Portuguese adult population. Food insecurity was assessed using a psychometric scale adapted from the Brazilian Food Insecurity Scale. The data on sociodemographic variables, chronic disease, and management of chronic disease were self-reported. Health-related quality of life were assessed using the European Quality of Life Survey (version validated for the Portuguese population). Logistic regression models were used to determine crude and adjusted odds ratios (for age group, gender, region, and education). The dependent variable was the perceived level of food security.Results: Among older adults, 23% were living in a food-insecure household. The odds of living in a food-insecure household were higher for individuals in the 70–74 years age group (odds ratio (OR) = 1.405, 95% confidence interval (CI) 1.392–1.417), females (OR = 1.545, 95% CI 1.534–1.556), those with less education (OR = 3.355, 95% CI 3.306–3.404), low income (OR = 4,150, 95% CI 4.091–4.210), and those reporting it was very difficult to live with the current income (OR = 16.665, 95% CI 16.482–16.851). The odds of having a chronic disease were also greater among individuals living in food-insecure households: diabetes mellitus (OR = 1.832, 95% CI 1.818–1.846), pulmonary diseases (OR = 1.628, 95% CI 1.606–1.651), cardiac disease (OR = 1.329, 95% CI 1.319–1.340), obesity (OR = 1.493, 95% CI 1.477–1.508), those who reduced their frequency of medical visits (OR = 4.381, 95% CI 4.334–4.428), and who stopped taking medication due to economic difficulties (OR = 5.477, 95% CI 5.422–5.532). Older adults in food-insecure households had lower health-related quality of life (OR = 0.212, 95% CI 0.210–0.214).Conclusions: Our findings indicated that food insecurity was significantly associated with economic factors, higher values for prevalence of chronic diseases, poor management of chronic diseases, and decreased health-related quality of life in older adults living in the community

Latitude does not influence cavity entrance orientation of South American avian excavators

In the Northern Hemisphere, several avian cavity excavators (e.g., woodpeckers) orient their cavities increasingly toward the equator as latitude increases (i.e., farther north), and it is proposed that they do so to take advantage of incident solar radiation at their nests. If latitude is a key driver of cavity orientations globally, this pattern should extend to the Southern Hemisphere. Here, we test the prediction that cavities are oriented increasingly northward at higher (i.e., colder) latitudes in the Southern Hemisphere and describe the preferred entrance direction(s) of 1501 cavities excavated by 25 avian species (n = 22 Picidae, 2 Trogonidae, 1 Furnariidae) across 12 terrestrial ecoregions (15°S ? 55°S) in South America. We used Bayesian projected normal mixed-effects models for circular data to examine the influence of latitude, and potential confounding factors, on cavity orientation. Also, a probability model selection procedure was used to simultaneously examine multiple orientation hypotheses in each ecoregion, to explore underlying cavity-orientation patterns. Contrary to predictions, and patterns from the Northern Hemisphere, birds did not orient their cavities more toward the equator with increasing latitude, suggesting that latitude may not be an important underlying selective force shaping excavation behavior in South America. Moreover, unimodal cavity-entrance orientations were not frequent among the ecoregions analyzed (infour ecoregions), whereas bimodal (in five ecoregions) or uniform (in three ecoregions) werealso common, although many of these patterns were not very sharp. Our results highlight the need to include data from under-studied biotas and regions to improve inferences at macroecology scales. Furthermore, we suggest a re-analysis of Northern Hemisphere cavity orientation patterns using a multimodel approach, and a more comprehensive assessment of the role of environmental factors as drivers of cavity orientation at different spatial scales in both hemispheres.Fil: Ojeda, Valeria Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; ArgentinaFil: Schaaf, Alejandro Alberto. Universidad Nacional de Jujuy. Instituto de Ecorregiones Andinas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Ecorregiones Andinas; ArgentinaFil: Altamirano, Tatiana Edith. University of British Columbia; CanadáFil: Bonaparte, Eugenia Bianca. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; ArgentinaFil: Bragagnolo, Laura Araceli. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Chazarreta, L.. Secretaría de Ambiente y Desarrallo Sustentable de la Nación; ArgentinaFil: Cockle, Kristina Louise. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; ArgentinaFil: Dias, R.. Universidade do Brasília; BrasilFil: Di Sallo, Facundo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; ArgentinaFil: Ibarra, T.. Pontificia Universidad Católica de Chile; ChileFil: Ippi, Silvina Graciela. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Jauregui, Adrian. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Área Zoología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Jimenez, Jaime E.. Universidad de Magallanes; ChileFil: Lammertink, J. Martjan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; ArgentinaFil: Lopez, F.. Universidad Nacional de La Pampa; ArgentinaFil: Nuñez Montellano, Maria Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; ArgentinaFil: de la Peña, Martín. No especifíca;Fil: Rivera, Luis Osvaldo. Universidad Nacional de Jujuy. Instituto de Ecorregiones Andinas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Ecorregiones Andinas; ArgentinaFil: Vivanco, Constanza Guadalupe. Universidad Nacional de Jujuy. Instituto de Ecorregiones Andinas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Ecorregiones Andinas; ArgentinaFil: Santillán, Miguel. Museo de Historia Natural de La Pampa; ArgentinaFil: Soto, G.. Cornell University; Estados UnidosFil: Vergara, P.. Universidad de Santiago de Chile; ChileFil: Politi, Natalia. University of North Texas; Estados Unido

Measurements of CO2 exchange over a woodland savanna (Cerrado Sensu stricto) in southeast Brasil

The technique of eddy correlation was used to measure the net ecosystem exchange over a woodland savanna (Cerrado Sensu stricto) site (Gleba Pé de Gigante) in southeast Brazil. The data set included measurements of climatological variables and soil respiration using static soil chambers. Data were collected during the period from 10 October 2000 to 30 March 2002. Measured soil respiration showed average values of 4.8 molCO2 m-2s-1 year round. Its seasonal differences varied from 2 to 8 molCO2 m-2s-1 (Q10 = 4.9) during the dry (April to August) and wet season, respectively, and was concurrent with soil temperature and moisture variability. The net ecosystem CO2 flux (NEE) variability is controlled by solar radiation, temperature and air humidity on diel course. Seasonally, soil moisture plays a strong role by inducing litterfall, reducing canopy photosynthetic activity and soil respiration. The net sign of NEE is negative (sink) in the wet season and early dry season, with rates around -25 kgC ha-1day-1, and values as low as 40 kgC ha-1day-1. NEE was positive (source) during most of the dry season, and changed into negative at the onset of rainy season. At critical times of soil moisture stress during the late dry season, the ecosystem experienced photosynthesis during daytime, although the net sign is positive (emission). Concurrent with dry season, the values appeared progressively positive from 5 to as much as 50 kgC ha-1day-1. The annual NEE sum appeared to be nearly in balance, or more exactly a small sink, equal to 0.1 0.3 tC ha-1yr-1, which we regard possibly as a realistic one, giving the constraining conditions imposed to the turbulent flux calculation, and favourable hypothesis of succession stages, climatic variability and CO2 fertilization

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks