Individuals diagnosed with Major Depression participating in an aerobic exercise intervention showed significant improvements in depression comparable to participants receiving pharmacological treatment [ 41 ]. Receptive e. In a large longitudinal study including more than 16, middle-aged individuals, cultural leisure-time activities were predictive of lower MHP at follow-up 5 years later [ 44 ].
Not all studies supported the relevance of mental activities for mental health. In a prospective study with first-year medical students, leisure-time activities such as playing music or being active in a religious community were not predictive of self-reported mental health at follow-up 1 year later [ 45 ].
As bivariate correlations and non-significant regression coefficients for cultural activities and mental health were not reported, the findings of this study should be interpreted with caution. The relationship between alcohol consumption and mental health is quite controversial. Individuals who identify themselves as alcohol abstainers show higher levels of anxiety and depression in comparison to those who do not report alcohol consumption but do not label themselves abstainers [ 47 ].
It is, however, problematic to interpret these findings to support the positive effects of moderate alcohol consumption, as many individuals who abstain from alcohol do so for a reason, such as a history of alcohol abuse or other health issues [ 47 ]. To identify the relevance of other confounding variables in the relationship between a facet of PMH, life satisfaction, a series of analyses was conducted using a large population sample in Russia [ 48 ].
The u-shaped relationship between alcohol consumption and life satisfaction that was found in men and women, was flattened when sociodemographic factors e. In other words, the positive relationship between moderate alcohol consumption and mental health is likely to be influenced by other sociodemographic characteristics or lifestyle factors and not caused by the alcohol consumption itself [ 48 ].
Smoking has been identified as a risk factor for MHP [ 49 , 50 ]. A meta-analysis of prospective studies with follow-up periods between 7 weeks and 9 years showed that individuals who quit smoking experience a significant decrease in MHP—symptoms of depression, anxiety, and stress—and an increase in PMH—psychological quality of life and positive affect—compared to continuing smokers [ 51 ].
In line with these findings, a Dutch study with more than participants showed that individuals who quit smoking do not experience a loss in life satisfaction, but rather an increase in well-being [ 52 ]. During early adolescence, smoking is associated with MPH and especially symptoms of depression [ 53 ].
The relationship between mental health and smoking is bidirectional: Young smokers with anxiety and depression are more likely to develop a nicotine addiction in early adulthood [ 54 ]. Compared to other lifestyle choices, a vegetarian diet has only rarely been investigated in the context of mental health. In a prospective study of more than young women in Australia, vegetarians and semi-vegetarians i.
In a representative study of German adults, individuals who reported a vegetarian diet were more likely to be diagnosed with depressive, anxiety, somatoform, or eating disorders [ 56 ]. These findings are in stark contrast to the proposed positive effects of a vegetarian diet on physical health e. Authors propose that these findings may be caused by psychological traits that influence both eating habits and mental health such as perfectionism.
An alternative explanation is based on the finding that mental health difficulties often precede a vegetarian diet. Individuals who experience mental health difficulties may try to modify their behavior in a way that is perceived as healthier or their mental health issues may sensitize them to the suffering of animals [ 56 ]. The relevance of a vegetarian diet for PMH and MHP has not been investigated in a prospective study including a variety of other lifestyle choices.
As prevalence of a vegetarian diet varies drastically between, for example Asian and European countries [ 57 ], the lack of cross-cultural studies including more than one country is another shortcoming in the literature [ 56 ].
The association between MHP and disturbances of circadian rhythms is documented, especially for schizophrenia, bipolar disorder, and depression [ 58 ]. Disruptions of the circadian rhythm may trigger or exaggerate manic episodes [ 59 ]. Additionally, an irregular social rhythm, which includes social contacts, are also associated with mood disorders in elderly patients [ 61 ].
In one of the first population-based studies investigating rhythm irregularity and mental health, irregular circadian and social rhythm were both associated with more MHP and lower life satisfaction in a German sample [ 33 ].
This finding was replicated cross-culturally in representative Russian and Chinese samples [ 31 ]. While some longitudinal studies indicate the relevance of lifestyle factors for future MHP, evidence for the prediction of future PMH is much rarer. In addition, most studies focus on one or two lifestyle choices and do not investigate the relative importance of a broad range of behaviors for PMH and MHP. As many lifestyle choices are interrelated—for example, individuals who exercise regularly are less likely to be overweight or obese—those studies do not explain the individual contribution of certain lifestyle choices on mental health outcomes.
Lastly, the majority of studies only include U. American or European participants. Germany is an individualistic Western country which has undergone structural changes in the s specifically the reunification of West and East Germany [ 62 ].
In contrast, China is a collectivistic Asian country [ 63 , 64 ] in which old values and traditions interact with a rapid economical and technical development e. Thus, for this study, data from German and Chinese students were analyzed as both countries differ regarding various cultural, historical, social, and geographical conditions.
The aim of this study was to overcome these limitations by investigating the impact of seven major lifestyle factors—BMI, physical and mental activities, alcohol consumption, smoking, vegetarianism, and social rhythm irregularity—on concurrent and future PMH and MHP in two large student samples from Germany and China.
We predicted that a lower BMI, a higher frequency of physical and mental activities, a lower frequency of alcohol consumption, non-smoking, a non-vegetarian diet, and a more regular social rhythm would be predictive of better mental health at baseline, operationalized as higher PMH and fewer MHP. As longitudinal studies including a variety of lifestyle factors are lacking, no predictions about the relevance of specific lifestyle factors for the prediction of future mental health were made.
We expected, however, that mental health at baseline would predict mental health at follow-up. The present study was conducted as part of the Bochum optimism and mental health studies BOOM-studies , which aim to investigate risk and protective factors of mental health in population-based and student samples with cross-sectional and longitudinal assessments across different cultures.
Participants in both countries were sent an invitation to the study via email. They received no incentives for participation. Data were assessed through self-administered surveys i. Depending on the assessment method, participants gave their informed consent written or online after being informed about anonymity and voluntariness of the survey. Language specific versions of psychometric instruments were administered using the forward-backward-translation method [ 66 ].
In case of discrepancies, the procedure was repeated until complete agreement was achieved. All procedures were carried out in accordance with the provisions of the World Medical Association Declaration of Helsinki Since the data were anonymized from the beginning of data collection, no statement by an ethics committee was required in China.
The participating Chinese Universities were, however, informed and acknowledged the approval by the German ethics board. The Chinese sample included students below age Chinese laws grant inscribed university students of all ages the rights to decide for themselves about study-related issues including participation in studies. Thus, no consent to participate was collected from the parents or guardians. In total, 2, German and 12, Chinese participants had valid data at baseline, which was defined as having data for at least half of lifestyle predictors see Additional file 1.
Both samples included more female than male participants German sample: In the German sample, Six-hundred and thirty-six German and 8, Chinese students had at least one valid value at follow-up.
Height and weight were assessed via self-report. Self-reported measurements of height and weight have been found to be very reliable, except for highly obese individuals. For this group, a slight underestimation of weight has been reported [ 64 ]. If yes, with what intensity have you done so in the last 12 months? Single-item measures of those activities are characterized by an acceptable reliability and construct validity compared to objective measurement methods [ 67 ] and perform at least as well as longer questionnaires [ 68 ].
Research has also shown that such items show especially high criterion validity in younger and female participants [ 68 ]. While there is an on-going debate about the validity of self-reported alcohol consumption compared to objective data, recent studies conclude that self-report can reliably estimate alcohol consumption in low to moderate drinkers [ 69 ].
Such items are regularly used in epidemiological studies on alcohol consumption e. Similar items were used in previous large-scale studies on eating habits and mental health [ 56 ].
Validity evidence comes from data indicating that the full scale is related to physical health, consistent with past research on rhythmicity and certain aspects of mental health [ 31 , 33 ]. The PMH-scale is a self-report instrument consisting of nine non-specific judgments and was developed to measure eudaimonic and hedonic aspects of well-being.
Targeted at general psychological functioning, subjects were asked to indicate their agreement on a 4-point Likert scale ranging from 0 do not agree to 3 agree. High internal consistency, good retest- reliability as well as good and discriminant validity were confirmed in a series of six studies comprising samples of students, patients, and general populations [ 12 ]. The DASS consists of 21 items, 7 for each subscale, rated on a 4-point Likert scale ranging from 0 did not apply to me at all to 3 applied to me very much, or most of the time.
Summing across the complete scale yields a total score ranging from 0 to The DASS is a widely used instrument with good psychometric properties [ 73 ]. Three percent of participants had missing values for MHP, 6. Missing values were not replaced.
For the primary hypotheses, path analysis was used to examine whether the lifestyle factors explained current and predicted future PMH and MHP.
To evaluate whether the proposed model would fit the data of German and Chinese students equally well, a multi group path analysis was conducted. To control for differences in sample size, a case-control sample of the Chinese students, matched for age and gender, was randomly drawn and included in this analysis.
To assess whether the proposed model would fit the data, three fit indices were inspected [ 77 ]. For an acceptable fit, CFI values above. For the standardized root-mean-square residual SRMR , values smaller than. Table 1 shows the sample characteristics regarding lifestyle variables and mental health outcomes for Chinese and German participants.
This group difference, however, was very small. For descriptive purposes, Table 2 shows non-parametric bivariate correlations between all predictor and outcome variables. Explained outcome variance by lifestyle factors at baseline was Baseline lifestyle explained Table 3 shows the results of the regression paths of the path analysis for the prediction of current and future mental health by lifestyle choices in German students.
Female gender, a higher body mass index, smoking, vegetarian diet, and social rhythm irregularity were predictive of lower PMH at baseline. Higher frequency of physical activity, mental activity, and alcohol consumption were positive predictors of baseline PMH. Effects were mostly small. In addition, only social rhythm irregularity was a negative predictor of future PMH.
Male gender, a higher body mass index, smoking, a vegetarian diet, and an irregular social rhythm were positive, physical and mental activity were negative predictors of baseline MHP. In addition, being female and having a more irregular social rhythm at baseline were positive predictors of future MHP. Baseline lifestyle explained 6. Table 4 shows the results of the regression paths of the path analysis for the prediction of current and future mental health in Chinese students.
At baseline, a higher frequency of alcohol consumption, smoking, and a higher social rhythm irregularity were predictive of lower PMH. Being older and reporting a higher frequency of physical and mental activities were positive predictors of PMH.
In addition, male gender, older age, and higher frequency of physical and mental activities were positive predictors of future PMH. Vegetarian diet and a more irregular social rhythm were negative predictors of future PMH.
All effects of lifestyle factors on future PMH were small. At baseline, female gender, a higher body mass index, more frequent alcohol consumption, smoking, a vegetarian diet, and an irregular social rhythm were positive, frequency of physical and mental activities as well as higher age were negative predictors of MHP.
In addition, younger and female participants, those with fewer mental activities, more frequent alcohol consumption, smokers, vegetarians, and those having a more irregular social rhythm reported higher MHP at follow-up.
All effects of lifestyle factors on future MHP were small. While correlations between PMH and MHP, intercepts, and residual variances were allowed to differ, all regression paths were set equal between countries.
In German and Chinese students, explained outcome variance by lifestyle factors at baseline was Lifestyle at baseline explained 5. Table 5 shows the results of the regression paths of the path analysis for the prediction of current and future mental health in our multi-group model of German and Chinese students. At baseline, female gender, a higher body mass index, smoking, a vegetarian diet, and a more irregular social rhythm were predictive of lower PMH.
In addition, higher frequencies of physical and mental activities were positive predictors of PMH. In addition, reporting higher frequency of physical activities was a positive predictor, while a more irregular social rhythm was a negative predictor of future PMH.
At baseline, female gender, higher body mass index, more frequent alcohol consumption, smoking, a vegetarian diet, and an irregular social rhythm were positive, older age and a higher frequency of physical and mental activities were negative predictors of MHP. In addition, female gender, younger age, smoking, and having a more irregular social rhythm at baseline were positive predictors of future MHP.
The primary objective of this study was to evaluate the predictive value of a broad range of lifestyle choices for PMH and MHP in a cross-cultural study using two longitudinal student samples from Germany and China. In both samples, the lifestyle factors under investigation explained a substantial amount of variance in mental health outcomes at baseline and at follow-up.
A good fit of this multi-group model indicated that, overall, the impact of lifestyle on PMH and MHP was comparable across countries. These findings suggest that choosing healthier lifestyle behaviors can increase psychological well-being and reduce symptoms of depression, anxiety, and stress.
We found, however, some differences in lifestyle between German and Chinese students as well as a differential impact of certain lifestyle choices on the mental health of the two groups. In the following section, we will first describe differences in lifestyle and mental health between the two student samples and proceed to discuss which hypotheses were supported cross-culturally or within one of our samples.
German and Chinese students lead different lifestyles. Medium to large group differences were found for BMI and alcohol consumption, with higher values for German compared to Chinese students. Despite increasing levels of overweight and obesity in Asian children, adolescents, and adults, high BMI [ 80 ] are still much more prevalent in Europe than in Asia [ 81 ].
In addition, Germany is among the countries with the highest alcohol consumption rates worldwide [ 82 ]. China has undergone substantial social and economic changes with increasing urbanization, changes to traditional family structure, and developments towards a free market which have been accompanied by an increase in alcohol consumption [ 83 ] and changed dietary habits shifting away from high-carbohydrate foods toward high-fat, high-energy density foods [ 84 ].
Our findings, however, suggest that on an absolute level, German students still surpass their Chinese counterparts with respect to these two lifestyle factors.
The remaining differences, even though statistically significant, were minimal. Chinese students reported engaging in mental and physical activities more frequently, as well as having a more regular social rhythm. Fewer Chinese students were smokers. Overall, Chinese students lead a somewhat healthier lifestyle than German students except for more Chinese participants indicating a vegetarian diet. It may, however, be an oversimplification to devaluate a meat-free diet as an unhealthy lifestyle choice as positive effects of a vegetarian diet on physical health are well documented [ 85 ] and research on the relationship between vegetarianism and mental health is still in its infancy see the following section for more information.
When comparing these findings to a previous study that included three population-based samples in Germany, Russia, and the United States, both student samples scored significantly lower than all of these samples [ 31 ]. This finding can not only be explained by the small, but significant correlation between age and PMH. In other words, these findings support the notion that college students report higher mental disorder prevalence rates than the general population [ 86 ].
Regarding birth cohorts, psychopathology among college students increased [ 87 ]. Again, German students showed values that were substantially higher than those reported in a representative study in Germany [ 31 ].
A potential explanation could be the face-to-face assessment method used in our Chinese sample, which might lead to more socially desirable responding and lower levels of MHP compared to online surveys [ 89 ]. Effect sizes were comparable to those found in another cross-sectional study that investigated a similar set of predictors of life satisfaction and MHP in a population-based sample of German adults [ 33 ].
Lifestyle choices explained a small amount of variance in PMH and MHP at follow-up even when controlling for baseline mental health. Thus, other variables, that were not included in the study such as socioeconomic factors, could explain more variance. Next to lifestyle choices that are manifested in behaviors, internal factors, like personality e. While all effect sizes were small, the predictive value of BMI for mental health at both time-points was somewhat higher in German than in Chinese students.
These findings might be related to the, on average, higher level of BMI and its greater variance in Germany. To reduce complexity, a quadratic polynomial of BMI was not added to our analyses. In order to further investigate the impact of underweight, normal weight, and overweight on PMH and MHP in Chinese college students future studies should include different BMI variables i.
As hypothesized, both physical and mental activities were independently predictive of higher PMH and fewer MHP at baseline. Both variables were also predictive of future PMH in Chinese students above and beyond baseline mental health. In our multi-group model, physical activity was associated with increases in PMH from baseline to follow-up.
Our findings underline the importance of exercise, sports, and cultural or mental leisure-time activities [ 33 , 39 , 43 ] for psychological well-being as well as for the prevention of mental disorders. Effects were small but compared to other lifestyle choices, the impact of both variables on PMH and MHP was the second and third largest in size.
Although previous evidence concerning alcohol consumption and mental health was mixed [ 25 , 46 ], we assumed that more frequent alcohol consumption would be associated with more MHP and lower PMH in our student samples.
Our hypothesis was supported only in the Chinese sample. In other words, German students who reported more frequent drinking, showed greater psychological well-being. Previous studies indicated that positive associations between alcohol intake and mental health are moderated by other confounding variables [ 48 ]. Thus, it seems unlikely that the alcohol intake itself is responsible for improved mental health.
A possible explanation might be that German students who consume alcohol on a regular basis, exhibit other social or trait characteristics e. Using longitudinal data, smoking was a positive predictor of MHP in Chinese students as well as our multi-group model. In other words, students who were smokers at baseline, reported an increase in symptoms of depression, anxiety, and stress from baseline to follow-up.
Other evidence suggests that consuming a fully plant-based diet can even reverse chronic, diet-related conditions, including advanced heart disease.
This diet eliminates meat, dairy and eggs and includes whole foods such as vegetables, whole grains, legumes and fruits. It is the most compassionate and the most sustainable diet, Dr. Golubic says, and the one he recommends most. Start by preparing one new plant-based meal a week. Experts recommend minutes of moderate-intensity activity each week. If that seems daunting, Dr.
Golubic recommends starting small. So start with a minute walk. If walking is not an option, any physical activity will do. Simply move more and sit less. Shoot for seven to nine hours of restful sleep each night.
Try mindfulness, meditation and gratitude to relieve stress and improve your physical and mental health. There are many temptations and distractions that can steer you away from positive and healthy daily habits. This is where we can help. Our MyClinic team can give you the tools to help you succeed. At MyClinic, we are here to support and guide you in the right direction.
We can assist you with the following things:. Exercise Regularly. But sticking with a workout routine is easier said than done. As you may be aware, exercising brings many physical and mental benefits that affect our daily lives. To get the benefits, you should plan to do strength training three times per week and do cardio two times per week. You should also actively rest two days a week!
Maintain a Healthy Body Weight. Weight is also an important measure that can determine the development of future disease and illness and also affect existing health concerns. Sitting in a chair for too long can be the source of many illnesses. Simply standing up for a few minutes can reduce the risks. So for those of you that work at a desk all day, if you can take a couple minutes to walk and stretch. Adding simple stretching while you stand up can further improve blood circulation and metabolism.
Avoid Sugar. Like many experts say, sugar is not beneficial and is bad for your health. Processed sugar can lead to weight gain, which could be the source of certain illness. Sugar has no essential nutrients and is bad for your teeth. Fructose in sugar can lead to liver damage and can cause insulin resistance, which can cause type 2 diabetes. Recognising how much sugar you eat helps you determine how much sugar you need to cut out of your diet.
Choose Healthier Fats. Not all fats are created equal. Healthy fats can help lower bad cholesterol and help lose excessive weight. You can find the healthy fats in avocados, coconut oil, butter, extra virgin oil, and omega-3s. Eat more Vegetables and Fruits.
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