Prevalence of chronic obstructive pulmonary disease and variation in risk factors across four geographically diverse resource-limited settings in Peru

Background

It is unclear how geographic and social diversity affects the prevalence of chronic obstructive pulmonary disease (COPD). We sought to characterize the prevalence of COPD and identify risk factors across four settings in Peru with varying degrees of urbanization, altitude, and biomass fuel use.

Methods

We collected sociodemographics, clinical history, and post-bronchodilator spirometry in a randomly selected, age-, sex- and site-stratified, population-based sample of 2,957 adults aged ≥35 years (median age was 54.8 years and 49.3% were men) from four resource-poor settings: Lima, Tumbes, urban and rural Puno. We defined COPD as a post-bronchodilator FEV₁/FVC < 70%.

Results

Overall prevalence of COPD was 6.0% (95% CI 5.1%–6.8%) but with marked variation across sites: 3.6% in semi-urban Tumbes, 6.1% in urban Puno, 6.2% in Lima, and 9.9% in rural Puno (p < 0.001). Population attributable risks (PARs) of COPD due to smoking ≥10 pack-years were less than 10% for all sites, consistent with a low prevalence of daily smoking (3.3%). Rather, we found that PARs of COPD varied by setting. In Lima, for example, the highest PARs were attributed to post-treatment tuberculosis (16% and 22% for men and women, respectively). In rural Puno, daily biomass fuel for cooking among women was associated with COPD (prevalence ratio 2.22, 95% CI 1.02–4.81) and the PAR of COPD due to daily exposure to biomass fuel smoke was 55%.

Conclusions

The burden of COPD in Peru was not uniform and, unlike other settings, was not predominantly explained by tobacco smoking. This study emphasizes the role of biomass fuel use, and highlights pulmonary tuberculosis as an often neglected risk factor in endemic areas.     

Analysis of Longitudinal Clinical Trials with Missing Data Using Multiple Imputation in Conjunction with Robust Regression

Summary In a typical randomized clinical trial, a continuous variable of interest (e.g., bone density) is measured at baseline and fixed postbaseline time points. The resulting longitudinal data, often incomplete due to dropouts and other reasons, are commonly analyzed using parametric likelihood‐based methods that assume multivariate normality of the response vector. If the normality assumption is deemed untenable, then semiparametric methods such as (weighted) generalized estimating equations are considered. We propose an alternate approach in which the missing data problem is tackled using multiple imputation, and each imputed dataset is analyzed using robust regression (M‐estimation; Huber, 1973 , Annals of Statistics 1, 799–821.) to protect against potential non‐normality/outliers in the original or imputed dataset. The robust analysis results from each imputed dataset are combined for overall estimation and inference using either the simple Rubin (1987 , Multiple Imputation for Nonresponse in Surveys, New York: Wiley) method, or the more complex but potentially more accurate Robins and Wang (2000 , Biometrika 87, 113–124.) method. We use simulations to show that our proposed approach performs at least as well as the standard methods under normality, but is notably better under both elliptically symmetric and asymmetric non‐normal distributions. A clinical trial example is used for illustration.     

Simple cannulation procedure for serial blood sampling through cutaneous ulnar vein in chickens

The objective of the study was to collect repeated, low-stress blood samples from the ulnar vein of chickens required for pharmacokinetic studies or hormonal assays. The study used 5 apparently healthy, unsexed, commercial broiler chickens about 6 weeks old and weighing 1.7-1.9 kg for serial sampling of blood. The study prepared the birds prior to cannulation and penetrated the catheter through the skin and into the lumen of the ulnar vein. The study successfully carried out serial blood samplings in 4 of 5 cannulated birds. Heparin (10%) solution maintained patency and prevented blood clot formation inside the cannula. However, the study found repeated clotting occurring in 1 bird. Cannula failed to maintain patency; the study could not carry out blood sampling properly, which was attributed to air embolism that might have occurred during catheter manipulation or repeated filling of cannula with heparin solution. The study observed no hematoma or inflammation at the site of cannulation. Owing to the advantages and to facilitate compliance with nonhuman animal welfare, this technique seems simple and efficient, allowing adoption for serial blood collection in chickens.     

Managing private,commercial rangelands for agricultural production and wildlife diversity in Namibia and Zambia

The private game industry has grown across Africa since the mid-20th century. While considerable research has documented wildlife production on commercial land in many eastern and southern African countries, few studies have focused specifically on the integration of livestock and game production in Namibia and Zambia. This paper reports a survey of 43 commercial conservancy members in Namibia and 23 game farmers in Zambia conducted between September 2004 and June 2005. The survey was based on inductive sampling theory and queried farmers on how they have integrated wildlife production into their management practices. Farmers in each country reported considerable integration of wildlife conservation and agricultural production. Namibian farmers reported substantial problems with bush encroachment, whereas none of their Zambian counterparts raised similar complaints. This paper describes the state of rangeland management on commercial farms in Namibia and Zambia and identifies important areas where further research can contribute to the enhancement of this conservation-production system.     

Informing conservation by identifying range shift patterns across breeding habitats and migration strategies

A species distribution combines the resources and climatic tolerances that allow an individual or population to persist. As these conditions change, one mechanism to maintain favorable resources is for an organism to shift its range. Much of the research examining range shifts has focused on dynamic distribution boundaries wheras the role of species breeding habitat or migration strategies on shift tendencies has received less attention. We expand on previous research by using a large suite of avian species (i.e., 277), analyzing observed abundance-weighted average latitudes, and categorizing species by breeding environment and migration strategy. We used the North American Breeding Bird Survey dataset to address two questions: (1) Has the center of observed abundance for individual species shifted latitudinally? (2) Is there a relationship between migration strategy or breeding habitat and range shifts? Results indicate the majority of species have experienced poleward range shifts over the last 43 years, and birds breeding in all habitat showed trends of poleward shift but only those species breeding in scrub-shrub and grassland environments were different from zero. Additionally, species that are short distance migrants are experiencing significant poleward shifts while Neotropical and permanent residents had shifts that were not different from zero. Our findings do support the general trend expected from climate driven changes (i.e., > 52 % shifting poleward), however, the proportion of species exhibiting equatorial shifts (24 %) or no significant shifts (23 %) illustrates the complex interplay between land cover, climate, species interactions, and other forces that can interact to influence breeding ranges over time. Regardless of the mechanisms driving range shifts, our findings emphasize the need for connecting and expanding habitats for those species experiencing range shifts. This research describes the patterns of breeding birds through central North America and we encourage future research to focus on the mechanisms driving these patterns.     

B cell genomics behind cross-neutralization of SARS-CoV-2 variants and SARS-CoV

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Assessment of a livestock GPS collar based on an open‐source datalogger informs best practices for logging intensity

Ecologists have used Global Positioning Systems (GPS) to track animals for 30 years. Issues today include logging frequency and precision in estimating space use and travel distances, as well as battery life and cost. We developed a low‐cost (~US$125), open‐source GPS datalogger based on Arduino. To test the system, we collected positions at 20‐s intervals for several 1‐week durations from cattle and sheep on rangeland in North Dakota. We tested two questions of broad interest to ecologists who use GPS collars to track animal movements: (1) How closely do collared animals cluster in their herd? (2) How well do different logging patterns estimate patch occupancy and total daily distance traveled? Tested logging patterns included regular logging (one position every 5 or 10 min), and burst logging (positions recorded at 20‐s intervals for 5 or 10 min per hour followed by a sleep period). Collared sheep within the same pasture spent 75% of daytime periods within 51 m of each other (mean = 42 m); collared cattle were within 111 m (mean = 76 m). In our comparison of how well different logging patterns estimate space use versus constant logging, the proportion of positions recorded in 1‐ and 16‐ha patches differed by 2%–3% for burst logging and 1% for regular logging. Although all logging patterns underestimated total daily distance traveled, underestimations were corrected by multiplying estimations by regression coefficients estimated by maximum likelihood. Burst logging can extend battery life by a factor of 7. We conclude that a minimum of two collars programmed with burst logging robustly estimate patch use and spatial distribution of grazing livestock herds. Research questions that require accurately estimating travel of individual animals, however, are probably best addressed with regular logging intervals and will thus have greater battery demands than spatial occupancy questions across all GPS datalogger systems.