Abstract
-
Background
The association between sleep duration and obesity risk among risky drinkers remains controversial. This study aims to investigate the relationship between adequate sleep duration and both central and overall obesity among risky drinkers in Korea, with a focus on identifying potential interventions to reduce obesity rates.
-
Methods
We analyzed data from 978 individuals, selected from 1,356 risky drinkers—as defined by the World Health Organization criteria—who participated in the 2019–2020 Korea National Health and Nutrition Examination Survey. Participants had no missing values and were engaged in economic activities. Demographic characteristics and key variables by obesity status were examined using frequency analysis and chi-square tests. Multivariable logistic regression analysis was performed to explore the association between sleep duration and obesity. To account for the stratified sampling design, we utilized complex sample analysis with weighted values.
-
Results
Risky drinkers with adequate sleep duration (7–9 hours) were less likely to be obese based on waist circumference (≥90 cm in males; ≥85 cm in females) (odds ratio [OR], 0.64; 95% confidence interval [CI], 0.48–0.86) and body mass index (≥25 kg/m2) (OR, 0.56; 95% CI, 0.41–0.76). Trend analysis revealed a significant inverse relationship between sleep duration and obesity likelihood (P for trend <0.05). Gender-stratified analysis demonstrated that the association was significant among males and more pronounced in risky drinkers compared to the general population.
-
Conclusion
This study suggests that adequate sleep duration may play a key role in reducing obesity rates among Korean male risky drinkers. Further longitudinal studies are recommended to strengthen this finding.
-
Keywords: Obesity; Abdominal Obesity; Alcohol Drinking; Sleep; Metabolic Syndrome
Graphical Abstract
Introduction
Obesity is a significant health concern, strongly associated with various diseases. It is often stigmatized due to its links with numerous chronic conditions [
1], including type 2 diabetes, dyslipidemia, hypertension, fatty liver disease, sleep apnea, and cardiovascular disorders. Obesity has been shown to increase the risk of coronary artery disease by up to two-fold, hypertension by up to four-fold, and diabetes by up to 13-fold [
2].
Alcohol consumption is particularly related to obesity. Alcohol stimulates appetite, leading to increased food intake, and inhibits fat oxidation in tissues, such as adipose tissue, thereby promoting fat accumulation and raising the risk of abdominal obesity [
3]. When alcohol is metabolized, it is prioritized as an energy source, causing other nutrients to be stored rather than utilized for energy. Additionally, the consumption of food alongside alcohol exacerbates excessive energy intake, further contributing to fat accumulation in the abdominal region.
Meanwhile, the relationship between sleep quality and obesity has been validated in numerous studies [
4-
6]. Research indicates that as sleep duration increases, the risks of obesity and abdominal obesity decrease. For instance, one study found that among Korean adult males aged 20–39, increased sleep duration reduced the likelihood of obesity by 20% and abdominal obesity by 14%. Similarly, women who slept 6–6.9 hours were 49% more likely to be obese compared to those who slept 7–7.9 hours [
7].
Moreover, studies suggest that sleep quality is closely related to individual drinking patterns. One study reported that, compared to non-drinkers, those who consumed alcohol at least once a week experienced a 44% reduction in sleep quality [
8]. Another study found that high-risk drinkers had a 25% higher risk of poor sleep quality, while monthly drinkers had a 9% higher risk. These findings suggest that persistent poor sleep quality due to alcohol consumption reduces sleep duration, thereby increasing the likelihood of obesity and chronic conditions such as metabolic syndrome.
Therefore, since alcohol consumption is directly linked to both sleep and obesity, further analysis of the relationship between sleep and obesity among risky drinkers is warranted. In contemporary society, workers are particularly vulnerable due to the culture of social drinking. Despite alcohol consumption, sufficient recovery time is necessary, making sleep a critical factor. However, workers often struggle to achieve adequate sleep due to commuting demands, even amidst risky drinking habits. This study aims to examine the impact of sufficient sleep duration on obesity risk among risky drinking workers.
Methods
Participants and procedures
This study utilized the Korea National Health and Nutrition Examination Survey (KNHANES) to investigate the relationship between obesity and risky drinking among workers. KNHANES, based on the Korean National Health Promotion Act, surveys health behaviors and the prevalence of chronic diseases in the population. Conducted annually by the Korea Disease Control and Prevention Agency since its inception in 1998 [
9], KNHANES employs stratified sampling, enabling complex sample analysis with weighted values that enhance the data’s representativeness [
10].
This study analyzed the correlation between sleep duration and obesity prevalence among risky drinkers who participated in the 2019 and 2020 KNHANES (
Figure 1). It aimed to identify the general characteristics of risky drinkers, evaluate their overall health behaviors, and examine their relationship with sleep. From the KNHANES data, we selected adults aged 20 years and older who met the World Health Organization (WHO) criteria for risky drinking (drinking at least twice a week, with men consuming seven or more shots of alcohol per session and women consuming five or more shots). Data from 2021 were excluded due to differences in sleep duration measurement methods. Of the 1,356 individuals initially identified, respondents with missing values in covariates and those not engaged in economic activities were excluded, resulting in a final sample of 978 risky drinking workers.
We compared obesity status, categorized into abdominal obesity based on waist circumference and body mass index (BMI)- defined overall obesity, by sleep duration and gender. Abdominal obesity was defined as a waist circumference of 90 cm or more for men and 85 cm or more for women, following the guidelines of the Korean Society for the Study of Obesity [
11]. BMI-defined overall obesity was classified as a BMI of 25 kg/m
2 or higher. Normal sleep duration was defined as 7 to 9 hours, in accordance with WHO recommendations.
The requirement for informed consent was waived because the participants’ consent was obtained from the KNHANES. The dataset is stored in a public domain and does not include individually identifiable information.
Statistical analysis
This study analyzed demographic characteristics (gender, age, education level, smoking status, physical activity including days of walking and strength training) and their association with obesity, using waist circumference and BMI as measures. Comparisons were made based on sleep duration and gender. Descriptive statistics were employed to analyze the demographic and clinical characteristics of the participants. To focus on high-risk drinking employees, participants with missing values or those not engaged in economic activities were excluded from the analysis.
A three-step multidimensional approach was used to explore factors influencing obesity among high-risk drinking employees. First, chi-squared tests were conducted to identify demographic and clinical factors affecting obesity. Second, multiple logistic regression analysis was performed to examine the influence of variables, including sleep duration, on obesity in high-risk drinkers. Lastly, tables were generated based on multidimensional multiple logistic regression analysis. To account for the stratified sampling design of the KNHANES, complex sample analysis was conducted. This method allowed us to examine the significance of various factors through multivariate analysis within the stratified framework. Additionally, trend analysis was performed to determine the association between sleep duration and obesity among risky drinkers by calculating the P-value for trend. Further subgroup analyses were conducted by gender, focusing on the correlation between sleep duration and obesity in males. For this analysis, a significance level of 0.05 was established as the criterion for determining statistical significance, where P-values less than 0.05 were considered statistically significant. To confirm the difference in coefficients between risky and non-risky drinkers, a separate calculation formula was utilized. In this analysis, B represents the unstandardized coefficient, and SE denotes the standard error associated with each coefficient. Assuming b1 as the effect of 7–9 hours of sleep on risky drinkers and b2 as the effect on the general group, the Z-value was calculated by taking the difference between b1 and b2 divided by the square root of the sum of the squared standard errors associated with each coefficient (SEb12 and SEb22). A Z-value of 1.96 or higher indicates significance at the 95% confidence level, while a Z-value of 1.65 or higher indicates significance at the 90% confidence level. This Zvalue allowed us to determine whether the impact of sleep duration significantly differed between the two groups.
Results
Demographic and clinical characteristics
The demographic and clinical characteristics of the participants are summarized in
Table 1. Chi-square test results revealed that, regarding abdominal obesity, only gender, age, and sleep duration showed statistically significant differences. Similarly, for overall obesity, gender and sleep duration were the only characteristics significantly associated with obesity.
The results of the multivariate logistic regression analysis are presented in
Table 2. Being male was positively associated with both abdominal obesity (odds ratio [OR], 2.13; 95% confidence interval [CI], 1.44–3.15) and overall obesity (OR, 2.64; 95% CI, 1.77–3.95). Conversely, having a sleep duration of 7–9 hours was negatively associated with abdominal obesity (OR, 0.64; 95% CI, 0.48–0.86) and overall obesity (OR, 0.56; 95% CI, 0.41–0.76). Interestingly, smoking was negatively associated with the prevalence of overall obesity (OR, 0.68; 95% CI, 0.50–0.92).
Multivariable logistic regression models were stratified by gender to explore potential differences. The results are presented in
Table 3 and
Figure 2. Chi-square test results indicated that longer sleep duration was associated with reduced abdominal and overall obesity, while sleeping 5–6 hours was significantly associated with a higher risk of obesity. When categorizing sleep duration into less than 5 hours, 5–6 hours, 7–9 hours (normal), and over 9 hours, trend analysis revealed a statistically significant P-value for trend (<0.01), suggesting that longer sleep duration was associated with lower abdominal obesity in men (
Table 3). Specifically, a sleep duration of 5–6 hours was found to significantly increase the risk of abdominal obesity (OR, 1.69; 95% CI, 1.20–2.36). Multivariate regression analysis results showed that, for abdominal obesity in women, being aged 19–39 years was significantly associated with a lower risk (OR, 0.05; 95% CI, 0.01–0.48). However, other factors such as education level, smoking, days of walking, strength training, and sleep duration were not statistically significant. Additionally, trend analysis for women, with a P-value for trend of 0.53, did not demonstrate a significant association between sleep duration and abdominal obesity. For men, multivariate regression analysis results indicated that being aged 19–39 years (OR, 2.54; 95% CI, 1.19–5.62), current smoking status (OR, 0.68; 95% CI, 0.49–0.95), and walking three or more times per week (OR, 0.70; 95% CI, 0.50–0.99) were significantly associated with abdominal obesity. Similar to abdominal obesity, when sleep duration was categorized into less than 5 hours, 5–6 hours, 7–9 hours (normal), and over 9 hours, trend analysis revealed a P-value for trend of 0.01. This result supports the hypothesis that the probability of obesity decreases with increasing sleep duration among male risky drinkers, indicating statistical significance. Specifically, a sleep duration of 5–6 hours was significantly associated with an increased risk of obesity (OR, 2.32; 95% CI, 1.65–3.29). Multivariate regression analysis results for women showed that being aged 19–39 years was significantly associated with a reduced risk of obesity (OR, 0.15; 95% CI, 0.03–0.91), consistent with findings for abdominal obesity. Unlike abdominal obesity, however, walking three or more times per week emerged as a significant factor in reducing obesity risk (OR, 0.70; 95% CI, 0.50–0.99). Similar to abdominal obesity in women, the trend analysis, with a P-value for trend of 0.45, did not demonstrate a significant association between sleep duration and overall obesity. In contrast, trend analysis provided statistically significant evidence of an association between longer sleep duration and both abdominal and overall obesity in male risky drinkers (
Figure 2).
This cross-sectional study aimed to identify the relationship between adequate sleep duration and both central and overall obesity among risky drinkers in Korea. Additionally, a comparative analysis was conducted on the entire experimental group participating in the NHANES to assess whether the association between adequate sleep duration and reductions in abdominal and overall obesity was greater in risky drinkers than in non-risky drinkers (
Supplement 1). According to the analysis, the incidence of abdominal obesity among risky drinkers who get 7–9 hours of sleep is 0.66 times that of those who do not get adequate sleep. In comparison, the abdominal obesity rate among non-risky drinkers who get 7–9 hours of sleep is 0.79 times that of those who do not get adequate sleep (
Supplement 2). These findings suggest that adequate sleep duration reduces the probability of abdominal obesity more significantly in risky drinkers (0.66 times) than in non-risky drinkers (0.79 times). Further comparison of the unstandardized coefficients (B) indicates values of 0.41 for risky drinkers and 0.23 for non-risky drinkers, with CI validating the results. This demonstrates that the reduction in abdominal obesity associated with adequate sleep duration is greater in risky drinkers than in non-risky drinkers. Therefore, it can be concluded that the relationship between sleep duration and abdominal obesity is more significant in risky drinkers compared to non-risky drinkers.
This relationship is more pronounced in BMI-defined overall obesity than in abdominal obesity. The incidence of overall obesity among risky drinkers who get 7–9 hours of sleep is 0.63 times that of those who do not get adequate sleep. In contrast, the obesity rate among non-risky drinkers who get 7–9 hours of sleep is 0.83 times that of those who do not get adequate sleep (
Supplement 3). These findings indicate that adequate sleep duration reduces the probability of overall obesity more significantly in risky drinkers (0.63 times) than in non-risky drinkers (0.83 times). Comparison of the unstandardized coefficients (B) reveals values of 0.45 for risky drinkers and 0.18 for non-risky drinkers, with the CI validating the results. This demonstrates that the relationship between sleep duration and overall obesity is more significant in risky drinkers than in non-risky drinkers.
Therefore, it is necessary to recommend adequate sleep duration as a strategy to reduce overall obesity rates among risky drinkers. Although the waist circumference results were not statistically significant, the unstandardized coefficient was consistently higher in the risky drinking group compared to the general group. This underscores the need for targeted interventions focusing on sleep and obesity among risky drinkers and highlights the importance of further in-depth studies on this topic.
Discussion
Current research has explored various aspects of the relationships between sleep duration and obesity, alcohol consumption and obesity, and the impact of alcohol on sleep quality. Findings indicate that insufficient sleep can lead to hormonal imbalances that increase the risk of obesity, while excessive alcohol consumption may exacerbate obesity through its negative impact on sleep quality. However, there is a lack of direct research examining the effect of sleep duration on obesity specifically in risky drinkers. This gap makes it challenging to accurately assess the obesity risk factors associated with inadequate sleep in this population. Therefore, this study is significant in addressing this gap by investigating the interaction between sleep duration and obesity within this specific group.
The relationship between risky drinking, poor sleep, and obesity involves multiple physiological and behavioral factors. Risky alcohol consumption can lead to liver damage, resulting in fat accumulation in the liver and insulin resistance [
12]. This resistance impairs glucose metabolism, potentially leading to metabolic diseases such as diabetes and obesity. Additionally, alcohol-induced liver inflammation can disrupt the balance of appetite-regulating hormones such as leptin and ghrelin, increasing appetite and promoting overeating or late-night snacking. Previous studies have demonstrated that short sleep duration is associated with reduced leptin levels, elevated ghrelin levels, and increased BMI, highlighting the critical role of adequate sleep in hormonal regulation [
13]. Given these established findings, adequate sleep becomes particularly important for supporting hormonal balance and aiding liver detoxification, making it essential for risky drinkers to effectively manage obesity.
Risky drinkers often exhibit irregular lifestyles and unhealthy eating habits [
14], which contribute to obesity. Adequate sleep can mitigate these behaviors by reducing fatigue and stress, thereby lowering the desire and consumption of alcohol [
15]. Furthermore, sufficient sleep improves energy levels, encouraging greater physical activity. Collectively, better sleep hygiene promotes healthier lifestyle choices, reduces alcohol intake, and decreases obesity rates among risky drinkers more effectively than among non-drinkers.
Furthermore, alcohol is often used for stress relief, and adequate sleep plays a crucial role in reducing stress levels, which can impact both sleep quality and obesity risk [
16]. Good sleep helps alleviate stress and may contribute to obesity reduction more effectively [
17]. Risky drinkers, who may use alcohol to manage stress, could experience temporarily lower stress levels and potentially better sleep conditions compared to non-drinkers. Therefore, with adequate sleep, risky drinkers may significantly reduce stress and obesity more effectively than non-drinkers who do not use alcohol as a stress relief tool. These findings suggest that risky drinkers might experience greater obesity reduction from the combined benefits of alcohol-induced stress relief and sufficient sleep.
The study indicated that while adequate sleep reduces abdominal and overall obesity in risky drinking men, it is less effective for women. This difference is primarily attributed to distinct hormonal responses between genders. In men, adequate sleep may enhance testosterone levels [
18], which promotes muscle mass and fat loss [
19]. For women, alcohol affects estrogen and progesterone levels differently, potentially disrupting sleep patterns and appetite control [
20]. Alcohol-induced increases in estrogen and decreases in progesterone [
21,
22] alter sleep quality and structure [
23,
24], further influenced by the menstrual cycle [
25]. These hormonal fluctuations can impair sleep and exacerbate sleep disorders [
26,
27], contributing to obesity development. Additionally, women’s lower metabolic rate during sleep results in fewer calories burned, reducing sleep’s effectiveness in combating obesity. More research is needed to fully explore these gender-specific dynamics.
Also, the study also highlights how sleep’s effect on obesity varies by gender due to differences in body structure and metabolic rate. Men generally have a higher basal metabolic rate [
28] and greater muscle mass compared to women, enabling them to burn more calories even at rest. Adequate sleep in men supports better muscle recovery, which not only increases their metabolic rate but also aids in muscle growth and repair, primarily during deep non-rapid eye movement sleep stages. This process is facilitated by the higher secretion of growth hormone [
29] and peak testosterone levels during sleep, creating an optimal environment for muscle development and enhanced metabolic function [
30]. Consequently, this leads to more significant weight loss and better obesity prevention in men compared to women.
Additionally, social and cultural factors contribute significantly to the gender differences observed in the relationship between sleep and obesity among risky drinkers. Men and women differ in lifestyle, health behaviors, and eating habits due to societal expectations, which also influence their sleep patterns and drinking behaviors. According to the study, men typically consume more alcohol per drinking session than women. This higher prevalence of binge drinking among men may alter the impact of adequate sleep on obesity reduction, leading to gender-specific differences. These physiological, physical, and socio-cultural distinctions underscore the importance of considering multiple factors when understanding how sleep influences obesity in risky drinkers and highlight the need for further detailed research.
The primary limitation of this study is the difficulty of establishing causal relationships due to its cross-sectional design. While the study concludes that adequate sleep duration reduces obesity rates among risky drinkers, particularly men, it does not clearly establish the temporal sequence between sleep duration and obesity. Thus, it remains unclear whether inadequate sleep duration contributes to obesity or whether obesity among risky drinkers affects their sleep duration. Additionally, while the study confirms the impact of adequate sleep duration on obesity rates, it does not clearly present a dose-response relationship between sleep duration and obesity reduction among risky drinkers. Future research should focus on longitudinal studies to address these limitations and establish a more robust understanding of the interactions between sleep, alcohol consumption, and obesity.
A major strength of this study is the utilization of data from a well-established, nationally representative sample. The study focuses on Korean risky drinkers who are actively participating in the workforce, making the results highly representative of the national population. Furthermore, the study addresses real-world issues faced by contemporary Korean workers, such as the social drinking culture and long commuting times. These factors ensure that the findings are not only academically significant but also practically applicable to solving societal problems. The study provides important implications for public health policy and workplace health program development. For example, the findings can inform policy interventions or programs aimed at improving sleep among workers to reduce obesity. By focusing on male risky drinkers, the study offers valuable insights for developing health management and prevention strategies that account for gender-specific characteristics. Finally, the use of multivariate regression analysis to control for multiple confounding variables enhances the study’s rigor and clarifies the direct relationship between sleep and obesity, thereby contributing to the accuracy and reliability of its findings.
In conclusion, risky drinkers with normal sleep duration (7–9 hours) were less likely to be obese based on waist circumference and BMI criteria. This trend was particularly pronounced among male risky drinkers. Further longitudinal studies are recommended to validate these findings and establish causal relationships.
Notes
Supplementary materials
Supplement 2.
Multidimensional multivariate regression analysis of abdominal obesity comparing risky drinker vs non-risky drinker.
Figure. 1.Participant selection process. a)Definition of risky drinking: drinking at least twice a week, with men consuming seven or more shots of alcohol per session and women consuming five or more shots.
Figure. 2.Correlation plot between abdominal obesity/overall obesity and sleep duration among male risky drinkers. (A) This plot illustrates the relationship between sleep duration (h) and abdominal obesity measured by waist circumference (cm). Each data point represents individual subjects. A negative correlation suggests that shorter sleep durations are associated with higher waist circumferences, indicating increased abdominal obesity. Statistical analysis confirms the significance of this relationship (P<0.05). (B) The plot illustrates the relationship between sleep duration (h) and obesity measured by body mass index (BMI). Data points represent individual subjects. A negative correlation suggests that shorter sleep durations are associated with higher BMI, indicating increased levels of obesity. Statistical analysis confirms the significance of this relationship (P<0.05).
Table 1.Demographic characteristics of risky drinkers
|
Characteristic |
Abdominal obesitya)
|
Obesityb)
|
|
Yes |
No |
P-value |
Yes |
No |
P-value |
|
Gender |
|
|
<0.01 |
|
|
<0.01 |
|
Men |
351 (46.8) |
400 (53.2) |
|
380 (50.7) |
370 (49.3) |
|
|
Women |
62 (29.0) |
149 (71.0) |
|
65 (30.2) |
146 (69.8) |
|
|
Age (y) |
|
|
0.01 |
|
|
0.27 |
|
<50 |
220 (38.8) |
351 (61.2) |
|
264 (45.5) |
307 (54.5) |
|
|
≥50 |
193 (52.4) |
198 (47.6) |
|
181 (49.8) |
209 (50.2) |
|
|
Education |
|
|
0.77 |
|
|
0.26 |
|
≥College |
190 (44.2) |
244 (55.8) |
|
211 (49.2) |
222 (50.8) |
|
|
<High school |
223 (43.1) |
305 (56.9) |
|
234 (45.0) |
294 (55.0) |
|
|
Smoking |
|
|
0.25 |
|
|
0.10 |
|
Smoker |
177 (41.4) |
247 (58.6) |
|
187 (43.5) |
236 (56.5) |
|
|
Non-smoker |
236 (45.4) |
302 (54.6) |
|
258 (49.9) |
280 (50.1) |
|
|
Walking (time/wk) |
|
|
0.25 |
|
|
0.32 |
|
≥3 |
247 (41.8) |
339 (58.2) |
|
271 (45.5) |
315 (54.5) |
|
|
<3 |
166 (46.4) |
210 (53.6) |
|
174 (49.3) |
201 (50.7) |
|
|
Strength training (time/wk) |
|
|
0.26 |
|
|
0.86 |
|
≥3 |
334 (44.6) |
432 (55.4) |
|
251 (46.8) |
413 (53.2) |
|
|
<3 |
79 (39.5) |
117 (60.5) |
|
93 (47.7) |
103 (52.3) |
|
|
Sleep duration (h) |
|
|
0.01 |
|
|
<0.01 |
|
7–9 |
209 (38.4) |
334 (61.6) |
|
225 (40.8) |
318 (59.2) |
|
|
Others |
204 (50.3) |
215 (49.7) |
|
220 (55.1) |
198 (44.9) |
|
Table 2.Multidimensional multivariate regression analysis of abdominal obesity and overall obesity
|
Variable |
Abdominal obesity |
Obesity |
|
Odds ratio (95% CI) |
P-value |
Odds ratio (95% CI) |
P-value |
|
Gender |
|
|
|
|
|
Men |
2.13 (1.44-3.15) |
<0.01 |
2.64 (1.77-3.95) |
<0.01 |
|
Women |
1 (reference) |
|
1 (reference) |
|
|
Age (y) |
|
|
|
|
|
19-39 |
0.57 (0.28-1.19) |
0.13 |
1.87 (0.86-4.07) |
0.12 |
|
40-64 |
0.84 (0.42-1.66) |
0.61 |
1.70 (0.80-3.60) |
0.17 |
|
≥65 |
1 (reference) |
|
1 (reference) |
|
|
Education |
|
|
|
|
|
≥College |
1.05 (0.77-1.44) |
0.75 |
1.04 (0.77-1.42) |
0.79 |
|
<High school |
1 (reference) |
|
1 (reference) |
|
|
Smoking |
|
|
|
|
|
Smoker |
0.81 (0.62-1.07) |
0.13 |
0.68 (0.50-0.92) |
0.01 |
|
Non-smoker |
1 (reference) |
|
1 (reference) |
|
|
Walking (time/wk) |
|
|
|
|
|
≥3 |
0.87 (0.62-1.21) |
0.41 |
0.86(0.64-1.16) |
0.33 |
|
<3 |
1 (reference) |
|
1 (reference) |
|
|
Strength training (time/wk) |
|
|
|
|
|
≥3 |
1.34 (0.89-2.02) |
0.16 |
1.03 (0.69-1.55) |
0.88 |
|
<3 |
1 (reference) |
|
1 (reference) |
|
|
Sleep duration (h) |
|
|
|
|
|
7–9 |
0.64 (0.48-0.86) |
<0.01 |
0.56 (0.41-0.76) |
<0.01 |
|
Others |
1 (reference) |
|
1 (reference) |
|
Table 3.Multidimensional multivariate regression analysis of abdominal obesity and overall obesity analyzed by gender
|
Variable |
Abdominal obesity |
Obesity |
|
Men |
Women |
Men |
Women |
|
OR (95% CI) |
P for trenda)
|
OR (95% CI) |
P for trend |
OR (95% CI) |
P for trend |
OR (95% CI) |
P for trend |
|
Age (y) |
|
|
|
|
|
|
|
|
|
19-39 |
0.71 (0.33-1.52) |
|
0.05 (0.01-0.48) |
|
2.54 (1.19-5.62) |
|
0.15 (0.03-0.91) |
|
|
40-64 |
0.83 (0.40-1.69) |
|
0.16 (0.02-1.37) |
|
1.73 (0.82-3.65) |
|
0.40 (0.08-2.10) |
|
|
≥65 |
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
|
Education |
|
|
|
|
|
|
|
|
|
≥College |
1.18 (0.83-1.67) |
|
0.55 (0.25-1.21) |
|
1.12 (0.80-1.57) |
|
0.71 (0.33-1.55) |
|
|
<High school |
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
|
Smoking |
|
|
|
|
|
|
|
|
|
Smoker |
0.82 (0.60-1.12) |
|
0.74 (0.34-1.60) |
|
0.68 (0.49-0.95) |
|
0.70 (0.33-1.48) |
|
|
Non-smoker |
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
|
Walking (time/wk) |
|
|
|
|
|
|
|
|
|
≥3 |
0.74 (0.51-1.06) |
|
2.15 (0.92-5.00) |
|
0.70 (0.50-0.99) |
|
2.22 (1.05-4.69) |
|
|
<3 |
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
|
Strength training (time/wk) |
|
|
|
|
|
|
|
|
|
≥3 |
1.54 (0.99-2.39) |
|
0.37 (0.12-1.16) |
|
1.11 (0.71-1.75) |
|
0.48 (0.16-1.45) |
|
|
<3 |
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
|
Sleep duration (h) |
|
<0.01 |
|
0.53 |
|
<0.01 |
|
0.45 |
|
<5 |
2.66 (0.90-7.87) |
|
2.01 (0.40-10.17) |
|
2.45 (0.98-6.13) |
|
0.627 (0.136-2.901) |
|
|
5–6 |
1.69 (1.20-2.36) |
|
1.19 (0.37-3.90) |
|
2.33 (1.65-3.29) |
|
0.637 (0.298-1.361) |
|
|
≥9 |
0.74 (0.25-2.24) |
|
1.17 (0.37-3.71) |
|
0.72 (0.24-2.19) |
|
0.633 (0.210-1.908) |
|
|
7–9 |
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
1 (reference) |
|
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