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      Prevalence of Suboptimal Health Status and the Relationships between Suboptimal Health Status and Lifestyle Factors among Chinese Adults Using a Multi-Level Generalized Estimating Equation Model

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          Abstract

          This study examined the prevalence of suboptimal health among Chinese adults based on a large-scale national survey and clarified the relationship between suboptimal health and lifestyle factors. We used multi-level generalized estimating equation models to examine the relationships between suboptimal health and lifestyle factors. Of the 48,978 respondents, 34,021 reported one or more suboptimal health symptoms, giving a suboptimal health status prevalence of 69.46%. After controlling for the cluster effect of living areas and confounding effect of demographic characteristics, factors associated with suboptimal health were: current smoking (odds ratio (OR) = 1.083, 95% confidence interval (CI): 1.055–1.111), drinking alcohol (OR = 1.075, 95% CI: 1.025–1.127), family history of disease (OR = 1.203, 95% CI: 1.055–1.111), sleeping <6 h per day (OR = 1.235, 95% CI: 1.152–1.256), poor sleep quality (OR = 1.594, 95% CI: 1.515–1.676), stress (OR = 1.588, 95% CI: 1.496–1.686), negative life events (OR = 1.114, 95% CI: 1.045–1.187), unhealthy diet choices (OR = 1.093, 95% CI: 1.033–1.156), and not regularly having meals at fixed hours (OR = 1.231, 95% CI: 1.105–1.372). Respondents who exercised regularly had lower odds of having suboptimal health status (OR = 0.913, 95% CI: 0.849–0.983). Suboptimal health has become a serious public health challenge in China. The health status of the population could be effectively improved by improving lifestyle behaviors.

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          Sex and gender-related differences in alcohol use and its consequences: Contemporary knowledge and future research considerations.

          To review the contemporary evidence reflecting male/female differences in alcohol use and its consequences along with the biological (sex-related) and psycho-socio-cultural (gender-related) factors associated with those differences.
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            Tobacco smoking and cancer: a brief review of recent epidemiological evidence.

            This report summarises the epidemiological evidence on the association between tobacco smoking and cancer, which was reviewed by an international group of scientists convened by IARC. Studies published since the 1986 IARC Monograph on "Tobacco smoking" provide sufficient evidence to establish a causal association between cigarette smoking and cancer of the nasal cavities and paranasal sinuses, nasopharynx, stomach, liver, kidney (renal cell carcinoma) and uterine cervix, and for adenocarcinoma of the oesophagus and myeloid leukaemia. These sites add to the previously established list of cancers causally associated with cigarette smoking, namely cancer of the lung, oral cavity, pharynx, larynx, oesophagus, pancreas, urinary bladder and renal pelvis. Other forms of tobacco smoking, such as cigars, pipes and bidis, also increase risk for cancer, including cancer of the lung and parts of the upper aerodigestive tract. A meta-analysis of over 50 studies on involuntary smoking among never smokers showed a consistent and statistically significant association between exposure to environmental tobacco smoke and lung cancer risk. Smoking is currently responsible for a third of all cancer deaths in many Western countries. It has been estimated that every other smoker will be killed by tobacco.
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              Effect of body mass index on all-cause mortality and incidence of cardiovascular diseases--report for meta-analysis of prospective studies open optimal cut-off points of body mass index in Chinese adults.

              To verify the optimal cut-off points for overweight and obesity in Chinese adults based on the relationship of baseline body mass index (BMI) to all-cause mortality, and incidence of cardiovascular diseases from pooled data of Chinese cohorts. The prospective study data of existing cohort studies in China were collected, and the age-adjusted all-cause mortality stratified by BMI were estimated. The similar analysis was repeated after excluding deaths within the first three years of follow-up and after excluding smokers. The incidence of age-adjusted coronary heart disease (CHD) and stroke stratified by BMI were also analyzed. Multiple Cox regression coefficients of BMI for the incidence of CHD and stroke after controlling other risk factors were pooled utilizing the methods of weighting by inverse of variance to reveal whether BMI had independent effect and its strength on the incidence of CHD and stroke. The data of 4 cohorts including 76,227 persons, with 745,346 person-years of follow-up were collected and analyzed. The age-adjusted all-cause mortality stratified by BMI showed a U-shaped curve, even after excluding deaths within the first three years of follow-up and excluding smokers. Age-adjusted all-cause mortality increased when BMI was lower than 18.5 and higher than 28. The incidence of CHD and stroke, especially ishemic stroke increased with increasing BMI, this was consistent with parallel increasing of risk factors. Cox regression analysis showed that BMI was an independent risk factor for both CHD and stroke. Each amount of 2 kg/m2 increase in baseline BMI might cause 15.4%, 6.1% and 18.8% increase in relative risk of CHD, total stroke and ischemic stroke. Reduction of BMI to under 24 might prevent the incidence of CHD by 11% and that of stroke by 15% for men, and 22% of both diseases for women. BMI or = 28 (kg/m2) is the appropriate cut-off points for underweight, overweight and obesity in Chinese adults.
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                25 January 2020
                February 2020
                : 17
                : 3
                : 763
                Affiliations
                [1 ]Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing 100005, China; hansm1@ 123456vip.sina.com
                [2 ]Department of Physiopathology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing 100005, China; zgj_1942@ 123456tom.com
                Author notes
                [* ]Correspondence: xutaosd@ 123456126.com
                Author information
                https://orcid.org/0000-0002-0799-8630
                Article
                ijerph-17-00763
                10.3390/ijerph17030763
                7038125
                31991741
                eac8d26f-c8b1-467d-a9d2-022380a65c25
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 02 January 2020
                : 22 January 2020
                Categories
                Article

                Public health
                suboptimal health,prevalence,lifestyle,generalized estimating equation model
                Public health
                suboptimal health, prevalence, lifestyle, generalized estimating equation model

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