Dataset Information

Managing more than the mean: using quantile regression to identify factors related to large elk groups.

ABSTRACT: Animal group size distributions are often right-skewed, whereby most groups are small, but most individuals occur in larger groups that may also disproportionately affect ecology and policy. In this case, examining covariates associated with upper quantiles of the group size distribution could facilitate better understanding and management of large animal groups.We studied wintering elk groups in Wyoming, where group sizes span several orders of magnitude, and issues of disease, predation and property damage are affected by larger group sizes. We used quantile regression to evaluate relationships between the group size distribution and variables of land use, habitat, elk density and wolf abundance to identify conditions important to larger elk groups.We recorded 1263 groups ranging from 1 to 1952 elk and found that across all quantiles of group size, group sizes were larger in open habitat and on private land, but the largest effect occurred between irrigated and non-irrigated land [e.g. the 90th quantile group size increased by 135 elk (95% CI = 42, 227) on irrigation].Only upper quantile group sizes were positively related to broad-scale measures of elk density and wolf abundance. For wolf abundance, this effect was greater on elk groups found in open habitats and private land than those in closed habitats or public land. If we had limited our analysis to mean or median group sizes, we would not have detected these effects. Synthesis and applications. Our analysis of elk group size distributions using quantile regression suggests that private land, irrigation, open habitat, elk density and wolf abundance can affect large elk group sizes. Thus, to manage larger groups by removal or dispersal of individuals, we recommend incentivizing hunting on private land (particularly if irrigated) during the regular and late hunting seasons, promoting tolerance of wolves on private land (if elk aggregate in these areas to avoid wolves) and creating more winter range and varied habitats. Relationships to the variables of interest also differed by quantile, highlighting the importance of using quantile regression to examine response variables more completely to uncover relationships important to conservation and management.

SUBMITTER: Brennan A

PROVIDER: S-EPMC5016784 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Managing more than the mean: using quantile regression to identify factors related to large elk groups.

Brennan Angela A Cross Paul C PC Creel Scott S

The Journal of applied ecology 20150827 6

Animal group size distributions are often right-skewed, whereby most groups are small, but most individuals occur in larger groups that may also disproportionately affect ecology and policy. In this case, examining covariates associated with upper quantiles of the group size distribution could facilitate better understanding and management of large animal groups.We studied wintering elk groups in Wyoming, where group sizes span several orders of magnitude, and issues of disease, predation and pr ...[more]

PMID: 27660373

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Project description:Background and aimsDiabetes mellitus, characterized by high blood glucose, is an overwhelming public health concern globally, including in Bangladesh. The implication of this trend may pose a significant challenge to the health systems due to the lack of awareness and improper management of this chronic disease. To formulate strategies for public health planning, this study aims to explore the potential risk factors for elevated blood glucose levels among Bangladeshi individuals using advanced statistical methods and a nationally representative data set.MethodsThis study utilized data from the 2017-18 Bangladesh Demographic and Health Survey and included 11,863 individuals. A nonparametric Kruskal-Wallis test assessed the significant association between fasting plasma glucose levels and various risk factors. Additionally, a robust quantile regression model was applied to examine the net effects of each risk factor at different quantiles of the distribution.ResultsThe prevalence of diabetes is 8.1% among individuals in the study population, with variations observed across different administrative divisions in the country. Respondents from the Dhaka division respondents had a higher likelihood (24.1%) of having elevated plasma glucose and the Rangpur division had a lower risk (10.3%) of developing diabetes disease. This study identified several potential risk factors associated with elevated blood glucose levels, including hypertensive disease, overweight and obese body mass index, higher economic status, reduced physical activities, and older age, significantly contributing to develop diabetes mellitus.ConclusionThis study recommends promoting healthy lifestyles, increased physical activity, effective hypertension management, obesity reduction, and nationwide screening programs to control diabetes and noncommunicable diseases in Bangladesh. These preventive measures are crucial for reducing the existing prevalence of diabetes and working toward achieving the Sustainable Development Goals by 2030.

Project description:BackgroundThe analysis of disease-free survival and related factors leads to a better understanding of the patient's condition and recurrence-related characteristics and provides a basis for more appropriate treatment guidance. In this study, we aimed to investigate the role of prognostic factors on disease-free survival in breast cancer with a quantile regression model.MethodsThis retrospective study was conducted by reviewing data obtained from 2056 breast cancer patients. Age at diagnosis and education status, tumor size, lymph node ratio, tumor grade, estrogen receptor and progesterone receptor, type of surgery, use of radiotherapy, chemotherapy, and hormone therapy were the prognosis factors considered in this study. A quantile regression model was used to investigate prognostic factors of disease-free survival in breast cancer.ResultsDisease recurrence was verified in 251 (13.9%) women, and 39 (0.02%) women died before experience recurrence. The 10th percentile of disease-free survival for patients with the hormone therapy was 23.85 months greater than patients who did not receive this treatment (P value < .001). In the examination of the tumor size, the 10th and 20th percentiles of disease-free survival for patients with tumor size > 5 cm were 31.06 and 27 months less than patients with the tumor size < 2 cm, respectively (P value = .006 and .021, respectively). Compared with grade 1 tumors, the 10th and 20th percentiles of disease-free survival for patients with grade 3 tumors decreased 30.11 and 38.32 months, respectively (P value < .001 and .038, respectively). The 10th and 20th percentiles of disease-free survival decreased 28.16 and 45.32 months with a 1 unit increase in lymph node ratio, respectively (P value = .032 and .032, respectively).ConclusionsAmong the prognostic factors, tumor size, grade, and lymph node ratio showed a close relationship with disease-free survival in breast cancer. The findings indicated that developing public screening and educational programs through the health care system with more emphasis on low-educated women is needed among Iranian women.

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Managing more than the mean: using quantile regression to identify factors related to large elk groups.

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Managing more than the mean: using quantile regression to identify factors related to large elk groups.

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