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      Risk factor analysis of insufficient fluid intake among urban adults in Wuxi, China: a classification and regression tree analysis

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          Abstract

          Background

          Dehydration due to insufficient fluid intake (IFI) is detrimental to health. This cross-sectional study aimed to assess the fluid intake of urban adults in Wuxi, China, and to identify potential risk factors contributing to IFI.

          Methods

          Adults were selected from the urban area of Wuxi, China, using a multiple-stage random sampling method. The fluid intake information was obtained with a 24-h self-reported diary over seven consecutive days in both summer and winter of 2015. A classification and regression tree (CART) analysis was conducted to detect the potential risk factors associated with IFI. CART is a machine-learning algorithm that portions the data into subsets by threshold.

          Results

          A total of 584 adults aged 18–87 years were included. The results showed that the median (P25–P75) values of daily fluid intake of the participants were 1100 (800–1550) mL in summer and 1000 (750–1300) mL in winter. Women had a higher prevalence of IFI than men in both summer (odds ratio (OR) = 2.683, 95% confidence interval (CI): 1.830–3.934) and winter (OR = 2.636, 95% CI: 1.677–4.142). The results of CART analysis showed that, in summer, BMI < 25 kg/m 2 (probability: 64.2%) and age < 64 years (probability: 67.4%) were main risk factors of IFI for men, and BMI < 29 kg/m 2 (probability: 81.6%) and living in C Community (probability: 86.7%) were main risk factors for women. In winter, age < 40 years (probability: 81.8%) and BMI < 20 kg/m 2 (probability: 94.5%) were identified as main risk factors of IFI for men and women, respectively.

          Conclusions

          Most of the participants living in the study site had IFI. The fluid consumption varied by gender, age, location, and BMI. The findings could be useful for the implementation and optimization of intervention programs by identifying the individuals who may at greater risk of dehydration.

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          Most cited references40

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          Water as an essential nutrient: the physiological basis of hydration.

          How much water we really need depends on water functions and the mechanisms of daily water balance regulation. The aim of this review is to describe the physiology of water balance and consequently to highlight the new recommendations with regard to water requirements. Water has numerous roles in the human body. It acts as a building material; as a solvent, reaction medium and reactant; as a carrier for nutrients and waste products; in thermoregulation; and as a lubricant and shock absorber. The regulation of water balance is very precise, as a loss of 1% of body water is usually compensated within 24 h. Both water intake and water losses are controlled to reach water balance. Minute changes in plasma osmolarity are the main factors that trigger these homeostatic mechanisms. Healthy adults regulate water balance with precision, but young infants and elderly people are at greater risk of dehydration. Dehydration can affect consciousness and can induce speech incoherence, extremity weakness, hypotonia of ocular globes, orthostatic hypotension and tachycardia. Human water requirements are not based on a minimal intake because it might lead to a water deficit due to numerous factors that modify water needs (climate, physical activity, diet and so on). Water needs are based on experimentally derived intake levels that are expected to meet the nutritional adequacy of a healthy population. The regulation of water balance is essential for the maintenance of health and life. On an average, a sedentary adult should drink 1.5 l of water per day, as water is the only liquid nutrient that is really essential for body hydration.
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            Classification and regression tree analysis in public health: methodological review and comparison with logistic regression.

            Audience segmentation strategies are of increasing interest to public health professionals who wish to identify easily defined, mutually exclusive population subgroups whose members share similar characteristics that help determine participation in a health-related behavior as a basis for targeted interventions. Classification and regression tree (C&RT) analysis is a nonparametric decision tree methodology that has the ability to efficiently segment populations into meaningful subgroups. However, it is not commonly used in public health. This study provides a methodological overview of C&RT analysis for persons unfamiliar with the procedure. An example of a C&RT analysis is provided and interpretation of results is discussed. Results are validated with those obtained from a logistic regression model that was created to replicate the C&RT findings. Results obtained from the example C&RT analysis are also compared to those obtained from a common approach to logistic regression, the stepwise selection procedure. Issues to consider when deciding whether to use C&RT are discussed, and situations in which C&RT may and may not be beneficial are described. C&RT is a promising research tool for the identification of at-risk populations in public health research and outreach.
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              Overweight and obesity in China.

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                Author and article information

                Contributors
                zhenghao@jscdc.cn
                853127075@qq.com
                zl67672004@sina.com
                wxcdczwj@163.com
                jscdc@126.com
                w2.hu@qut.edu.au
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                4 March 2020
                4 March 2020
                2020
                : 20
                : 286
                Affiliations
                [1 ]ISNI 0000 0000 8803 2373, GRID grid.198530.6, Department of Environmental Health, , Jiangsu Provincial Center for Disease Control and Prevention, ; No. 172 Jiangsu Road, Nanjing, 210009 China
                [2 ]ISNI 0000 0000 8803 2373, GRID grid.198530.6, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, ; No. 29 Nanwei Road, Beijing, 100050 China
                [3 ]Department of Public Health, Wuxi Center for Disease Control and Prevention, No. 499 Jincheng Road, Wuxi, 214023 China
                [4 ]ISNI 0000000089150953, GRID grid.1024.7, School of Public Health and Social Work, Institute of Health and Biomedical Innovation, , Queensland University of Technology, ; Brisbane, Queensland 4059 Australia
                Article
                8380
                10.1186/s12889-020-8380-y
                7057576
                32131783
                d73ddfa7-e39f-4af2-a8b2-125752ab305d
                © The Author(s). 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 19 December 2018
                : 20 February 2020
                Funding
                Funded by: Key Talent Project for Medical Young Scholar of Jiangsu Province
                Award ID: QNRC2016551
                Award Recipient :
                Funded by: Foundation of Jiangsu Commision of Health
                Award ID: H2018094
                Award Recipient :
                Funded by: National Water Pollution Control and Management Foundation of China
                Award ID: (2014ZX07405001)
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Public health
                fluid intake,risk factors,adults,cart
                Public health
                fluid intake, risk factors, adults, cart

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