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      Testing lipid markers as predictors of all-cause morbidity, cardiac disease, and mortality risk in captive western lowland gorillas ( Gorilla gorilla gorilla)

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      Primate Biology
      Copernicus GmbH

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          Abstract

          Great apes and humans develop many of the same health conditions, including cardiac disease as a leading cause of death. In humans, lipid markers are strong predictors of morbidity and mortality risk. To determine if they similarly predict risk in gorillas, we measured five serum lipid markers and calculated three lipoprotein ratios from zoo-housed western lowland gorillas (aged 6–52 years, n = 61 , subset with routine immobilizations only: n = 47 ): total cholesterol (TC), triglycerides (TGs), high-density lipoprotein (HDL), low-density lipoprotein (LDL), apolipoprotein A1 (apoA1), TC / HDL , LDL / HDL , and TG / HDL . We examined each in relation to age and sex, then analyzed whether they predicted all-cause morbidity, cardiac disease, and mortality using generalized linear models (GLMs). Older age was significantly associated with higher TG, TC / HDL , LDL / HDL , and TG / HDL , and lower HDL and apoA1. With all ages combined, compared to females, males had significantly lower TG, TC / HDL , LDL / HDL , and TG / HDL , and higher HDL. Using GLMs, age, sex, and lower LDL / HDL were significant predictors of all-cause morbidity; this is consistent with research demonstrating lower LDL in humans with arthritis, which was the second most prevalent condition in this sample. In contrast to humans, lipid markers were not better predictors of cardiac disease and mortality risk in gorillas, with cardiac disease best predicted by age and sex alone, and mortality risk only by age. Similar results were observed when multimodel inference was used as an alternative analysis strategy, suggesting it can be used in place of or in addition to traditional methods for predicting risk.

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          Null hypothesis significance testing (NHST) is the dominant statistical approach in biology, although it has many, frequently unappreciated, problems. Most importantly, NHST does not provide us with two crucial pieces of information: (1) the magnitude of an effect of interest, and (2) the precision of the estimate of the magnitude of that effect. All biologists should be ultimately interested in biological importance, which may be assessed using the magnitude of an effect, but not its statistical significance. Therefore, we advocate presentation of measures of the magnitude of effects (i.e. effect size statistics) and their confidence intervals (CIs) in all biological journals. Combined use of an effect size and its CIs enables one to assess the relationships within data more effectively than the use of p values, regardless of statistical significance. In addition, routine presentation of effect sizes will encourage researchers to view their results in the context of previous research and facilitate the incorporation of results into future meta-analysis, which has been increasingly used as the standard method of quantitative review in biology. In this article, we extensively discuss two dimensionless (and thus standardised) classes of effect size statistics: d statistics (standardised mean difference) and r statistics (correlation coefficient), because these can be calculated from almost all study designs and also because their calculations are essential for meta-analysis. However, our focus on these standardised effect size statistics does not mean unstandardised effect size statistics (e.g. mean difference and regression coefficient) are less important. We provide potential solutions for four main technical problems researchers may encounter when calculating effect size and CIs: (1) when covariates exist, (2) when bias in estimating effect size is possible, (3) when data have non-normal error structure and/or variances, and (4) when data are non-independent. Although interpretations of effect sizes are often difficult, we provide some pointers to help researchers. This paper serves both as a beginner's instruction manual and a stimulus for changing statistical practice for the better in the biological sciences.
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              To establish a unified working diagnostic tool for the metabolic syndrome (MetS) that is convenient to use in clinical practice and that can be used world-wide so that data from different countries can be compared. An additional aim was to highlight areas where more research into the MetS is needed. The International Diabetes Federation (IDF) convened a workshop held 12-14 May 2004 in London, UK. The 21 participants included experts in the fields of diabetes, public health, epidemiology, lipidology, genetics, metabolism, nutrition and cardiology. There were participants from each of the five continents as well as from the World Health Organization (WHO) and the National Cholesterol Education Program-Third Adult Treatment Panel (ATP III). The workshop was sponsored by an educational grant from AstraZeneca Pharmaceuticals. The consensus statement emerged following detailed discussions at the IDF workshop. After the workshop, a writing group produced a consensus statement which was reviewed and approved by all participants. The IDF has produced a new set of criteria for use both epidemiologically and in clinical practice world-wide with the aim of identifying people with the MetS to clarify the nature of the syndrome and to focus therapeutic strategies to reduce the long-term risk of cardiovascular disease. Guidance is included on how to compensate for differences in waist circumference and in regional adipose tissue distribution between different populations. The IDF has also produced recommendations for additional criteria that should be included when studying the MetS for research purposes. Finally, the IDF has identified areas where more studies are currently needed; these include research into the aetiology of the syndrome.
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                Author and article information

                Contributors
                Journal
                Primate Biol
                Primate Biol
                PB
                Primate Biology
                Copernicus GmbH
                2363-4707
                2363-4715
                17 December 2020
                2020
                : 7
                : 2
                : 41-59
                Affiliations
                [1 ]Center for Species Survival, Smithsonian Conservation Biology Institute, 1500 Remount Rd., Front Royal, VA 22630, USA
                [2 ]North of England Zoological Society, Chester Zoo, Upton by Chester, CH2 1LH, UK
                [a ]currently at: Department of Reproductive and Behavioral Sciences, Saint Louis Zoo, St. Louis, MO 63110, USA
                Author notes
                [*] Correspondence: Ashley N. Edes ( aedes@ 123456stlzoo.org )
                Article
                01021829
                10.5194/pb-7-41-2020
                7852406
                fcdc92bb-beb5-440a-9a44-c8dbab5d4702
                Copyright: © 2020 Ashley N. Edes et al.

                This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/

                History
                : 25 March 2020
                : 19 October 2020
                Categories
                Research Article

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