Effects of passive smoking and its duration on the prevalence of prediabetes and type 2 diabetes mellitus in Chinese women

Wu, Juan; Pan, Gui; Huang, Yan-ting; Liu, Dengke; Zeng, Haixia; Zhou, Xiaojun; Lai, Xiulan; Liu, Jianping

doi:10.18632/aging.103217

Cited by 4 publications

(3 citation statements)

References 36 publications

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“…Behavior and lifestyle are the most important factors affecting individual health and playing an important role in the occurrence and development of DM. Studies have shown that smoking, [16,17] drinking, [18] sedentary lifestyle, lack of exercise, [19] and lack of sleep [20,21] and so on are closely related to DM. Regarding chronic disease health management, the World Health Organization states that “increasing adherence may have a greater effect on health than improvements in specific medical therapy.” [22] Therefore, early diagnosis, regular blood glucose monitoring, standardized medical treatment, appropriate exercise and other health management are effective measures to control the progress of diabetes and prevent complications.…”

Section: Discussionmentioning

confidence: 99%

The prevalence, awareness, management and influencing factors of diabetes in middle-aged and elderly in China, evidence from the CHARLS in 2015

Zhang¹,

Wu²,

Chen

et al. 2022

Medicine

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Diabetes seriously affects the health of middle-aged and elderly. What we can do is to suppress the progression and avoid complications of diabetes. The aim of this study was to evaluate the prevalence, management and influencing factors in middle-aged and elderly diabetics. The data used in our study came from the follow-up survey (2015) of China Health and Retirement Longitudinal Study. After all the questionnaire data of participants was acquired, the first screening step was conducted and the participants without blood glucose or glycosylated hemoglobin test results were excluded. In the second screening step, participants without self-reported diabetes, age <45 were excluded. After data screening, STATA 16.0 software (StataCorp, USA) was used to conduct statistical analysis. Multiple logistics regression was used to analyze the influencing factors of diabetes in middle-aged and elderly. After data screening, A total of 9738 participants were enrolled in the survey of the China Health and Retirement Longitudinal Study in 2015, including diabetes 1965 and control 7773. The prevalence of diabetes in age >60 (22.20%) was significantly higher than that in age 45 to 60 (16.60%). Age, residence, physical activity, drinking, smoking and body mass index were key influencing factors according to the results of logistics regression. 46.92% diabetics were diagnosed in hospital, 22.14% were diagnosed by community medical care. 1298 among 1965 diabetes patients had standardized medication to control blood glucose, the rate was only 66.01%. The awareness rate of diabetes was only 28.75%, and the monitoring, treatment and accepting medical advice rates were 68.32%, 66.01% and 56.99% separately. The follow-up rate of diabetes was only 14.16%. Diabetes is widely prevalent in the middle-aged and elderly with the prevalence of 16.60% in the participants with age 45 to 60. The rate of self-rated diabetics underestimated the true prevalence of diabetes. Age, residence, physical activity, drinking, smoking and body mass index are key influencing factors to diabetes. Although a national diabetes health management model has been established, the awareness of diabetes was only 28.75%. Standardized diabetes registration and regular follow up should also be strictly implemented.

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Section: Discussionmentioning

confidence: 99%

The prevalence, awareness, management and influencing factors of diabetes in middle-aged and elderly in China, evidence from the CHARLS in 2015

Zhang¹,

Wu²,

Chen

et al. 2022

Medicine

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show abstract

“…Thus, exposure to SHS can increase the levels of corticotropin releasing hormone and adrenocorticotropic hormone, and gradually affects individuals' emotions and cognitions (33)(34)(35). Previous studies indicate that passive smoking is related to endocrine and metabolic changes (36)(37)(38)(39), which may lead to sub-health status.…”

Section: Potential Biological Mechanismsmentioning

confidence: 99%

Association Between Passive Smoking and Health Among Chinese Nurses: A Cross-Sectional Study

Xia

Xiao

et al. 2021

Front. Public Health

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This study aimed to investigate the association between passive smoking and physical and psychological health in Chinese nurses. Participants of this cross-sectional study comprised 2,484 non-smoking nurses. Passive smoking and demographic information were assessed using a self-administered questionnaire. Physical, psychological, and overall health status of nurses were measured using the Cornell Medical Index (CMI) health questionnaire. Multivariate-adjusted odds ratio (OR) and 95% confidence interval (CI) for nurses' health were estimated by exposure to passive smoking using unconditional logistic regression models. A total of 1,219 nurses (49.07%) were exposed to passive smoking. Of these, 609 (24.52%), 160 (6.44%), and 587 (23.63%) nurses had poorer physical, mental, and overall health, respectively. After adjusting for other confounding factors, compared with the non-passive smoking group, passive smoking was associated with poor physical (OR = 1.51, 95% CI: 1.25–1.83), mental (OR = 1.48, 95% CI: 1.07–2.07), and overall (OR = 1.58, 95% CI: 1.30–1.93) health of nurses, respectively. We also carried out subgroup analyses stratified by age, department, and professional title, which showed that most findings supported the main results. This study demonstrated that exposure to passive smoking was a risk factor for overall decreased physical and mental health status among Chinese nurses.

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“…Several associating factors of glycemic status have been proposed in clinical guidelines worldwide, including older age, obesity, family history of diabetes, history of gestational diabetes mellitus (GDM), hypertension, antihypertensive therapy, dyslipidemia, physical inactivity, and passive smoking. 3 , 4 , 8–10 The association between glycemic status and other unhealthy behaviors, such as low consumption of vegetables and fruits, is partially understood. The consumption of vegetables and fruits is related to better glycemic status among women in the US 11 and China.…”

Section: Introductionmentioning

confidence: 99%

Factors Associated with Hemoglobin A1c Level Among Women Without Prior Diabetes Diagnosis in Rural Areas of Central South China: A Cross-Sectional Study

Jiang¹,

Jiang²,

Qin³

et al. 2022

IJWH

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Background Women in rural areas of China face the unique risk of developing diabetes, but data on the glycemic status among women without prior diabetes diagnosis in rural areas are lacking which may limit the decision-making for diabetes screening or prevention. This study was aimed to describe the glycemic status of women determined by hemoglobin A1c (HbA1c) and explore its associating factors. Methods A cross-sectional survey was conducted among women without prior diabetes diagnosis from two counties of rural areas in Central South China from July to October 2018. On the basis of the life course framework, data on socio-demographic, environmental health, genetic, biological (blood pressure, weight and height, lipids), psychosocial, and healthy behavioral factors were collected on site either through questionnaires or field measurements. The questionnaires included social-demographic sheet, Perceived Stress Scale, Self-efficacy scales for health-related diet and exercise behaviors, and Chinese Diabetes Risk Questionnaire. Generalized linear model analysis was performed to determine the associating factors of glycemic status, which was measured by HbA1c level. Results A total of 647 women were included in the study. The median age of women was 51.00 years (range 35–65 years). The median HbA1c level was 5.1% (interquartile range 4.6%-5.5%, range 4–13.6%), and 8.7% (n=56) of women were identified as elevated glycemic status (HbA1c>6%). Environmental health factors (eg, living in less-developed county [ β =0.206, p =0.027]), biological factors (eg, higher body mass index [ β =0.201, p =0.036], higher total cholesterol [ β =0.097, p =0.040], history of gestational diabetes mellitus [ β =0.722, p <0.001]), and psychosocial factors (eg, higher perceived stress [ β =0.247, p =0.002]) were associated with higher HbA1c level. Conclusion This study reported 8.7% of elevated glycemic status among women without prior diabetes diagnosis in rural Hunan Province, China. After a comprehensive investigation based on a theoretical framework, living in a less-developed county of rural areas, having larger body mass index, higher total cholesterol, higher perceived stress, and a gestational diabetes mellitus history were identified as associating factors of higher HbA1c level. Professional support regarding weight control, blood lipid control, stress management, and the prevention of gestational diabetes mellitus should be recommended among this population, especially for women from less-developed counties.

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Effects of passive smoking and its duration on the prevalence of prediabetes and type 2 diabetes mellitus in Chinese women

Cited by 4 publications

References 36 publications

The prevalence, awareness, management and influencing factors of diabetes in middle-aged and elderly in China, evidence from the CHARLS in 2015

The prevalence, awareness, management and influencing factors of diabetes in middle-aged and elderly in China, evidence from the CHARLS in 2015

Association Between Passive Smoking and Health Among Chinese Nurses: A Cross-Sectional Study

Factors Associated with Hemoglobin A1c Level Among Women Without Prior Diabetes Diagnosis in Rural Areas of Central South China: A Cross-Sectional Study

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