The emergence of critical incidents in Rugby Union matches using Markov chain analysis

Marino, Thomas Kisil; Ferreira, André Rebêlo; Morgans, Ryland; Schildberg, Walter Tenório; Aoki, Marcelo Saldanha; Corrêa, Umberto César; Moreira, Alexandre

doi:10.1080/24733938.2022.2135758

Cited by 3 publications

(3 citation statements)

References 21 publications

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“…These sex and race differences in weight change are concordant with previous epidemiological studies that studied sex‐ and race‐based differences in gradual weight gain. These overall trends in weight gain match other analyses of both NHANES data and other cohorts of the United States population 14–22 …”

Section: Discussionsupporting

confidence: 80%

“…These overall trends in weight gain match other analyses of both NHANES data and other cohorts of the United States population. 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 …”

Section: Discussionmentioning

confidence: 99%

“…These overall trends in weight gain match other analyses of both NHANES data and other cohorts of the United States population. [14][15][16][17][18][19][20][21][22] Many past obesity studies have observed age-related weight gain in population cohorts. [23][24][25][26] These studies showed significant weight gain in the populations (greater than 3 kg per decade) and were found to have significant racial and sex-based disparities.…”

Section: Model Construction and Statistical Analysismentioning

confidence: 99%

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Stochastic modeling of obesity status in United States adults using Markov Chains: A nationally representative analysis of population health data from 2017–2020

Huang

2023

Obesity Science & Practice

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ImportanceThe prevalence of obesity among United States adults has increased from 34.9% in 2013–2014 to 42.8% in 2017–2018. Developing methods to model the increase of obesity over‐time is a necessity to know how to accurately quantify its cost and to develop solutions to combat this national public health emergency.MethodsA cross‐sectional cohort study using the publicly available National Health and Nutrition Examination Survey (NHANES 2017–2020) was conducted in individuals who completed the weight questionnaire and had accurate data for both weight at the time of survey and weight 10 years ago. To model the dynamics of obesity, a Markov transition state matrix was created, which allowed for the analysis of weight transitions over time. Bootstrap simulation was incorporated to account for uncertainty and generate multiple simulated datasets, providing a more robust estimation of the prevalence and trends in obesity within the cohort.ResultsOf the 6146 individuals who met the inclusion criteria, 3024 (49%) individuals were male and 3122 (51%) were female. There were 2252 (37%) White individuals, 1257 (20%) Hispanic individuals, 1636 (37%) Black individuals, and 739 (12%) Asian individuals. The average BMI was 30.16 (SD = 7.15), the average weight was 83.67 kilos (SD = 22.04), and the average weight change was a 3.27 kg (SD = 14.97) increase in body weight. A total of 2411 (39%) individuals lost weight, and 3735 (61%) individuals gained weight. 87 (1%) individuals were underweight (BMI <18.5), 2058 (33%) were normal weight (18.5 ≤ BMI <25), 1376 (22%) were overweight (25 ≤ BMI <30) and 2625 (43%) were in the obese category (BMI >30).ConclusionUnited States adults are at risk of transitioning from normal weight to the overweight or obese category. Markov modeling combined with bootstrap simulations can accurately model long‐term weight status.

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Section: Discussionsupporting

confidence: 80%

“…These overall trends in weight gain match other analyses of both NHANES data and other cohorts of the United States population. 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 …”

Section: Discussionmentioning

confidence: 99%