People with low aerobic and muscular fitness are nearly twice as likely to experience depression

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People with low aerobic and muscular fitness are nearly twice as likely to experience depression, finds a new study led by UCL researchers.

Low fitness levels also predicted a 60% greater chance of anxiety, over a seven-year follow-up, according to the findings published in BMC Medicine.

Lead author, Ph.D. student Aaron Kandola (UCL Psychiatry) said: “Here we have provided further evidence of a relationship between physical and mental health, and that structured exercise aimed at improving different types of fitness is not only good for your physical health, but may also have mental health benefits.”

The study involved 152,978 participants aged 40 to 69 of the UK Biobank study.

Their baseline aerobic fitness at the start of the study period was tested by using a stationary bike with increasing resistance, while their muscular fitness was measured with a grip strength test.

They also completed a questionnaire gauging depression and anxiety symptoms.

Seven years later they were tested again for depression and anxiety symptoms, and the researchers found that high aerobic and muscular fitness at the start of the study was associated with better mental health seven years later.

People with the lowest combined aerobic and muscular fitness had 98% higher odds of depression, 60% higher odds of anxiety, and 81% higher odds of having either one of the common mental health disorders, compared to those with high levels of overall fitness.

The researchers accounted for potentially confounding factors at baseline such as diet, socioeconomic status, chronic illness, and mental illness symptoms.

Previous studies have found that people who exercise more are less likely to experience mental illnesses, but most studies rely on people self-reporting their activity levels, which can be less reliable than the objective physical fitness measures used here.

Senior author Dr. Joseph Hayes (UCL Psychiatry and Camden and Islington NHS Foundation Trust) said: “Our findings suggest that encouraging people to exercise more could have extensive public health benefits, improving not only our physical health but our mental health too. Improving fitness through a combination of cardio exercise and strength and resistance training appears to be more beneficial than just focusing on aerobic or muscular fitness.”

Aaron Kandola added: “Reports that people are not as active as they used to be are worrying, and even more so now that global lockdowns have closed gyms and limited how much time people are spending out of the house. Physical activity is an important part of our lives and can play a key role in preventing mental health disorders.

“Other studies have found that just a few weeks of regular intensive exercise can make substantial improvements to aerobic and muscular fitness, so we are hopeful that it may not take much time to make a big difference to your risk of mental illness.”


Depression and, as a consequence, high suicide rates have become one of the big health problems and lead to a huge socioeconomic burden around the world1–3. South Korea also faces this problem, with its high suicide rate, and health policies have thus focused on managing depression and suicide for the last decades.

Many studies have focused on biological and psychological causes and on a variety of treatment methods such as biological approaches, cognitive and behavioural therapy, and psychotherapy4–7.

However, preventive methods for depression have not been widely established8–11. Among a variety of suggested strategies, exercise and physical activities have been hypothesized as one way of preventing depression10.

Reduced physical activity is one of the main features of depression and is also included in the diagnostic criteria12. Research has focused on reduced physical activity not only as a consequence of depressive symptoms but also as a potential target of modulating the disease.

Previous studies have indeed suggested that exercise may play a role in the reduction of depressive symptoms in patients in specific target groups13. Furthermore, various exercise types have been evaluated for differences in their efficacy in alleviating depression.

Most studies have focused on aerobic exercises, but a recent study suggested that anaerobic exercise also has the potential of reducing symptoms of depression14. These results provided the basis for many countries to include exercise in their depression guidelines, which has also happened in South Korea15.

In contrast to the obvious possibility of using exercise to treat depression, many aspects of the preventive ability of exercise remain unclear. Previous studies focused on initial physical activity and how it might lower the risk for depression16.

However, sex differences or differences between exercise types have not been clearly identified, which makes it difficult to apply such findings in the clinical practice and in specific groups of patients. Previous studies showed sex difference in type of exercise that affect to depression treatment, suggesting the possibility of analogous association of exercise and depression prevalence in general population17,18.

The association between types of exercise and depression therefore needs to be investigated, especially in groups of people with different demographic characteristics.

The aim of this study was to investigate the association between exercise types and depression in the Korean adult population, after adjusting for covariates assumed to affect depression levels. Furthermore, we also aimed to find sex differences in the relationship between exercise type and depression.

Results

The general characteristics of the study population separated by sex are presented in Table 1.

A total of 13,914 participants including 6010 men and 7904 women were included in the analysis. Of the participants, 2.96% of men and 6.73% of women fulfilled the depression criteria (i.e. a PHQ-9 score of 10 or higher).

Participants who reported doing strength exercise more than once in a week showed a statistically lower depression prevalence than participants reporting no strength exercise. Also, participants who had walked more than 10 min at least once during the previous week had lower depression levels than participants who reported no walking.

Educational attainment, equalized household income, marital status, smoking status, and stroke history were additionally identified as having statistically significant effects on depression.

Table 1 – Socioeconomic and health-related characteristics of all study participants according to the presence/absence of depression.

VariablesMen (N = 6010)Women (N = 7904)
Depressed (PHQ ≥ 10)Not depressed (PHQ < 10)p-valueDepressed (PHQ ≥ 10)Not depressed (PHQ < 10)p-value
N(%)N(%)N(%)N(%)
Strength exercise< 0.00010.0244
None167(4.3)3709(95.7)454(7.0)6003(93.0)
 ≥ 147(2.2)2087(97.8)78(5.4)1369(94.6)
Walking0.01250.0035
None20(6.01)313(93.99)30(11.11)240(88.89)
≥ 1193(3.40)5482(96.60)502(6.58)7132(93.42)
Physical activity0.09900.5480
Low90(3.8)2276(96.2)252(6.9)3388(93.1)
Moderate97(3.8)2454(96.2)219(6.4)3205(93.6)
High27(2.5)1066(97.5)61(7.3)779(92.7)
Age0.415< 0.0001
19–2928(3.4)798(96.6)99(9.5)945(90.5)
30–3945(4.2)1024(95.8)88(6.4)1288(93.6)
40–4934(3.1)1066(96.9)55(3.7)1439(96.3)
50–5931(2.9)1033(97.1)96(6.0)1496(94.0)
60–6937(3.5)1017(96.5)105(7.9)1222(92.1)
 ≥ 7039(4.3)858(95.7)89(8.3)982(91.7)
Educational attainment< 0.0001< 0.0001
Middle school and below65(5.6)1090(94.4)227(9.5)2171(90.5)
High school61(3.7)1572(96.3)136(6.3)2026(93.7)
University and above88(2.7)3134(97.3)169(5.1)3175(94.9)
Equalized household income< 0.0001< 0.0001
Quartile 1 (low)81(8.9)832(91.1)178(12.9)1205(87.1)
Quartile 257(4.0)1358(96.0)144(7.3)1828(92.7)
Quartile 342(2.4)1735(97.6)134(6.1)2080(93.9)
Quartile 4 (high)34(1.8)1871(98.2)76(3.3)2259(96.7)
Marital status< 0.0001< 0.0001
Married121(2.8)4253(97.2)268(4.9)5150(95.1)
Separated/divorced/widowed34(10.1)304(89.9)151(11.8)1131(88.2)
Never married59(4.5)1239(95.5)113(9.4)1091(90.6)
Smoking status0.0006< 0.0001
Non-smoker30(2.1)1402(97.9)388(5.5)6642(94.5)
Smoker184(4.0)4394(96.0)144(16.7)720(83.3)
Alcohol use0.92970.7410
No9(3.5)251(96.5)80(7.0)1070(93.0)
Yes205(3.6)5545(96.4)452(6.7)6302(93.3)
Residential area0.56470.5037
Urban96(3.4)2716(96.6)249(6.5)3561(93.5)
Rural118(3.7)3080(96.3)283(6.9)3811(93.1)
BMI0.00020.0182
Underweight15(10.4)129(89.6)40(10.0)359(90.0)
Normal weight73(3.8)1837(96.2)232(6.4)3400(93.6)
Overweight48(3.1)1490(96.9)101(6.2)1540(93.8)
Obesity66(3.1)2030(96.9)125(6.7)1735(93.3)
Severe obesity12(3.7)310(96.3)34(9.1)338(90.9)
Stroke history< 0.0001< 0.0001
No200(3.4)5663(96.6)507(6.5)7271(93.5)
Yes14(9.5)133(90.5)25(19.8)101(80.2)
Participants177(2.96)5796(97.04)532(6.73)7372(93.27)

Variables are presented as numbers and percentages.

PHQ-9 Patient health questionnaire-9, BMI body mass index, Underweight BMI < 18.5, Normal weight 18.5 ≤ BMI < 23, Overweight 23 ≤ BMI < 25, Obesity 25 ≤ BMI < 30, Severe obesity 30 ≤ BMI.

Table ​2 shows the results of the multivariate logistic regression analysis on the association between depression and exercise. In men, participants who had done strength exercise more than once in a week were less likely to be depressed after adjusting for covariates [adjusted odds ratio (OR) 0.60, 95% CI 0.40–0.92].

Walking and physical activity were not statistically related with the prevalence of depression in men. High household income, married status, underweight, and no past history of stroke were found to correlate with lower depression prevalence in men, while age, educational attainment, alcohol use, residential area, overweight, and obesity were not related to depression risk in men.

In women, walking at least once during the previous week showed an association with lower depression levels after adjustments for covariates (adjusted OR 0.54, CI 0.34–0.87). There were no association between strength exercise and prevalence of depression in women.

Older age, higher educational attainment, and higher household income were inversely correlated with depression in women, while separated/divorced/widowed marital status, smoking, underweight, and stroke history were associated with a higher depression prevalence. Never married status, alcohol use, overweight, and obesity showed no statistical association with depression in women.

Table 2 – Results of the multivariate logistic regression analysis on the association between exercise types and depression.

VariablesMenWomen
Depressed (PHQ ≥ 10)Depressed (PHQ ≥ 10)
Adjusted OR95% CIAdjusted OR95% CI
Strength exercise
None1.001.00
 ≥ 10.60(0.40–0.92)0.84(0.62–1.14)
Walking
None1.001.00
 ≥ 10.55(0.29–1.04)0.54(0.34–0.87)
Physical activity
Low1.001.00
Moderate1.13(0.80–1.60)1.04(0.82–1.32)
High1.04(0.61–1.79)1.36(0.94–1.96)
Age
19–291.001.00
30–391.72(0.92–3.19)0.64(0.39–1.05)
40–491.10(0.55–2.19)0.37(0.21–0.65)
50–590.92(0.38–2.24)0.51(0.28–0.90)
60–690.62(0.27–1.43)0.44(0.24–0.81)
 ≥ 700.48(0.19–1.20)0.25(0.13–0.48)
Educational attainment
Middle school and below1.001.00
High school0.83(0.48–1.45)0.63(0.45–0.89)
University and above0.68(0.38–1.21)0.43(0.30–0.63)
Equalized household income
Quartile 1 (low)1.001.00
Quartile 20.38(0.23–0.61)0.58(0.43–0.78)
Quartile 30.23(0.13–0.39)0.60(0.44–0.82)
Quartile 4 (high)0.25(0.14–0.43)0.38(0.26–0.54)
Marital status
Married1.001.00
Separated/divorced/widowed2.80(1.73–4.53)1.89(1.45–2.47)
Never married1.83(1.02–3.28)1.35(0.85–2.15)
Smoking status
Non-smoker1.001.00
Smoker2.03(1.21–3.39)2.89(2.24–3.73)
Alcohol use
No1.001.00
Yes1.16(0.53–2.55)0.92(0.67–1.27)
Residential area
Urban1.001.00
Rural0.95(0.68–1.32)1.01(0.80–1.27)
BMI
Underweight2.56(1.24–5.29)1.63(1.05–2.53)
Normal weight1.001.00
Overweight1.11(0.69–1.78)0.81(0.59–1.12)
Obesity1.10(0.71–1.70)0.91(0.68–1.21)
Severe obesity1.44(0.72–2.87)1.22(0.77–1.95)
Stroke history
No1.001.00
Yes2.54(1.24–5.20)3.78(2.00–7.12)

PHQ-9 patient health questionnaire-9, BMI body mass index, Underweight BMI < 18.5, Normal weight 18.5 ≤ BMI < 23, Overweight 23 ≤ BMI < 25, Obesity 25 ≤ BMI < 30, Severe obesity 30 ≤ BMI, OR odds ratio, CI confidence interval.

The subgroup analyses were conducted to assess the combined effects of strength exercise and other sociodemographic variables on depression, as shown in Table 3 . In married men, strength exercise was statistically associated with a lower depression prevalence (adjusted OR 0.48, CI 0.27–0.84), but no relationship was found for other marital statuses.

Table ​4 shows the results from the subgroup analyses on the combined effects of walking during the past week and sociodemographic variables on the prevalence of depression. In women, walking was found to be related to depression in the youngest (19–29) and the oldest (≥ 70) age group but not in other groups. Walking also showed an association with lower prevalences of depression in subgroups using alcohol and smoking, compared to non-smokers and non-drinkers.

Table 3 – Subgroup analysis of the association between strength exercise and depression stratified by sociodemographic variables.

VariablesMenWomen
No strength exerciseStrength exercise ≥ 1No strength exerciseStrength exercise ≥ 1
Adjusted ORAdjusted OR95% CIAdjusted ORAdjusted OR95% CI
Physical activity
Low1.000.86(0.43–1.69)1.000.66(0.35–1.23)
Moderate1.000.53(0.29–0.96)1.000.85(0.54–1.33)
High1.000.53(0.22–1.27)1.001.17(0.64–21.35)
Age
19–291.001.13(0.41–3.13)1.001.47(0.80–2.70)
30–391.000.44(0.20–1.00)1.000.67(0.33–1.36)
40–491.000.63(0.28–1.43)1.000.53(0.19–1.46)
50–591.000.46(0.17–1.27)1.000.76(0.33–1.72)
60–691.000.37(0.12–1.17)1.000.63(0.33–1.22)
 ≥ 701.000.56(0.22–1.42)1.000.32(0.12–0.81)
Educational attainment
Middle school and below1.000.93(0.44–1.96)1.000.70(0.39–1.27)
High school1.000.57(0.26–1.25)1.000.84(0.48–1.46)
University and above1.000.54(0.31–0.95)1.000.94(0.58–1.54)
Equalized household income
Quartile 1 (low)1.000.94(0.48–1.84)1.001.10(0.54–2.22)
Quartile 21.000.40(0.17–0.95)1.000.68(0.41–1.13)
Quartile 31.000.37(0.16–0.8)1.000.78(0.43–1.42)
Quartile 4 (high)1.000.66(0.25–1.76)1.000.94(0.48–1.84)
Marital status
Married1.000.48(0.27–0.84)1.000.73(0.46–1.18)
Separated/divorced/widowed1.000.59(0.20–1.73)1.000.67(0.38–1.19)
Never married1.000.77(0.36–1.63)1.001.14(0.63–2.06)
Smoking status
Non-smoker1.001.01(0.40–2.54)1.000.88(0.61–0.28)
Smoker1.000.52(0.33–0.81)1.000.80(0.47–1.37)
Alcohol use
No1.000.78(0.08–8.09)1.000.64(0.27–1.51)
Yes1.000.61(0.40–0.94)1.000.87(0.63–1.20)
Residential area
Urban1.000.47(0.24–0.93)1.000.78(0.50–1.24)
Rural1.000.76(0.34–1.28)1.000.90(0.60–1.36)
BMI
Underweight1.001.44(0.16–12.68)1.000.86(0.23–3.22)
Normal weight1.000.49(0.24–0.998)1.000.89(0.48–1.362)
Overweight1.000.68(0.32–1.46)1.000.41(0.15–1.10)
Obesity1.000.39(0.17–0.92)1.001.11(0.59–2.09)
Severe obesity1.001.94(0.24–15.82)1.000.24(0.05–1.07)
Stroke history
No1.000.58(0.38–0.90)1.000.88(0.65–1.20)
Yes1.000.68(0.01–38.75)1.000.25(0.02–2.92)

PHQ-9 patient health questionnaire-9, BMI body mass index, Underweight BMI < 18.5, Normal weight 18.5 ≤ BMI < 23, Overweight 23 ≤ BMI < 25, Obesity 25 ≤ BMI < 30, Severe obesity 30 ≤ BMI, OR odds ratio, CI confidence interval.

Table 4 – Subgroup analysis of the association between walking and depression stratified by sociodemographic variables.

VariablesMenWomen
No walkingWalking ≥ 1No walkingWalking ≥ 1
Adjusted ORAdjusted OR95% CIAdjusted ORAdjusted OR95% CI
Physical activity
Low1.000.49(0.21–1.18)1.000.59(0.33–1.06)
Moderate1.001.54(0.51–4.68)1.000.50(0.21–1.17)
High1.000.20(0.05–0.75)1.000.37(0.05–2.70)
Age
19–291.000.90(0.12–6.86)1.000.27(0.12–0.63)
30–391.000.29(0.11–0.78)1.000.64(0.17–2.34)
40–491.001.05(0.35–3.20)1.000.93(0.18–4.84)
50–591.003.34(0.16–69.82)1.000.53(0.17–1.60)
60–691.000.56(0.10–3.17)1.000.41(0.15–1.09)
 ≥ 701.000.23(0.08–0.71)1.000.27(0.18–0.63)
Educational attainment
Middle school and below1.000.42(0.13–1.36)1.000.35(0.18–0.65)
High school1.000.58(0.25–1.34)1.000.70(0.26–1.90)
University and above1.000.55(0.20–1.51 )1.000.66(0.24–1.81)
Equalized household income
Quartile 1 (low)1.000.45(0.11–1.86)1.000.41(0.19–0.86)
Quartile 21.000.70(0.24–1.98)1.000.38(0.15–0.95)
Quartile 31.000.31(0.12–0.83)1.000.45(0.17–1.20)
Quartile 4 (high)1.000.62(0.14–2.76)1.002.61(0.59–11.48)
Marital status
Married1.000.65(0.30–1.43)1.000.59(0.33–1.08)
Separated/divorced/widowed1.000.12(0.02–0.57)1.000.59(0.21–1.70)
Never married1.000.64(0.13–3.26)1.000.48(0.11–2.23)
Smoking status
Non-smoker1.000.36(0.07–1.92)1.000.69(0.40–1.19)
Smoker1.000.59(0.29–1.20)1.000.28(0.11–0.73)
Alcohol use
No1.000.08(0.01–0.44)1.000.37(0.13–1.12)
Yes1.000.59(0.30–1.15)1.000.56(0.32–0.95)
Residential area
Urban1.001.40(0.42–4.68)1.000.50(0.22–1.13)
Rural1.000.39(0.17–0.86)1.000.60(0.33–1.08)
BMI
Underweight1.00*(*–*)1.001.28(0.12–13.11)
Normal weight1.000.50(0.22–1.14)1.000.72(0.32–1.59)
Overweight1.000.52(0.08–3.24)1.000.22(0.10–0.49)
Obesity1.000.71(0.22–2.25)1.000.52(0.20–1.35)
Severe obesity1.000.21(0.01–5.61)1.000.33(0.04–2.56)
Stroke history
No1.000.20(0.02–2.51)1.000.53(0.33–0.87)
Yes1.000.54(0.28–1.04)1.000.16(0.01–2.35)

PHQ-9 patient health questionnaire-9, BMI body mass index, Underweight BMI < 18.5, Normal weight 18.5 ≤ BMI < 23, Overweight 23 ≤ BMI < 25, Obesity 25 ≤ BMI < 30, Severe obesity 30 ≤ BMI, OR odds ratio, CI confidence interval.

*Due to the sparsity of the data, OR was > 999,999 which does not represent a proper value.

Table 5 shows the results from subgroup analyses among somatic symptom items of PHQ-9 and exercise. Walking was associated with sleep disturbance (item 3), low energy level (item 4), poor appetite (item 5) in men and low energy level, agitation/retardation (item 8) in women. Strength exercise was only associated with low energy level in men. The results of subgroup analyses among exercise and cognitive/affective symptoms were shown in Table 6 .

Poor concentration (item 7) was not associated with any type of exercise. Other cognitive/affective items except item 7 were associated with walking in women. Item 1 (little interest or pleasure in doing things) was associated with strength exercise in men. Suicidal or self-mutilating ideation (item 9) was associated with walking in both sexes.

Table 5 – Dependent subgroup analysis of the association among strength exercise , walking and somatic symptoms items of PHQ-9.

VariablesPHQ-9 Item-3 ≥ 1PHQ-9 Item-4 ≥ 1PHQ-9 Item-5 ≥ 1PHQ-9 Item-8 ≥ 1
Adjusted OR95% CIAdjusted OR95% CIAdjusted OR95% CIAdjusted OR95% CI
MenStrength exercise
None1.001.001.001.00
≥ 11.07(0.83–1.37)0.71(0.55–0.92)0.73(0.50–1.07)0.50(0.24–1.03)
Walking
None1.001.001.001.00
≥ 10.53(0.34–0.82)0.47(0.31–0.73)0.43(0.24–0.76)0.67(0.28–1.64)
WomenStrength exercise
None1.001.001.001.00
≥ 11.00(0.81–1.23)0.87(0.71–1.07)0.82(0.61–1.09)0.59(0.29–1.18)
Walking
None1.001.001.001.00
≥ 11.21(0.81–1.82)0.65(0.46–0.93)0.78(0.49–1.25)0.23(0.11–0.50)

PHQ-9 patient health questionnaire-9, OR odds ratio, CI confidence interval.

Table 6 – Dependent subgroup analysis of the association among strength exercise , walking and cognitive/affective items of PHQ-9.

VariablesPHQ-9 Item-1 ≥ 1PHQ-9 Item-2 ≥ 1PHQ-9 Item-6 ≥ 1PHQ-9 Item-7 ≥ 1PHQ-9 Item-9 ≥ 1
Adjusted OR95% CIAdjusted OR95% CIAdjusted OR95% CIAdjusted OR95% CIAdjusted OR95% CI
MenStrength exercise
None1.001.001.001.001.00
≥ 10.55(0.40–0.76)0.77(0.50–1.17)0.71(0.45–1.12)0.58(0.31–1.08)0.73(0.27–1.98)
Walking
None1.001.001.001.001.00
≥ 10.69(0.39–1.23)0.88(0.41–1.88)0.59(0.31–1.13)0.59(0.26–1.32)0.23(0.07–0.83)
WomenStrength exercise
None1.001.001.001.001.00
≥ 11.05(0.79–1.38)0.94(0.67–1.33)0.62(0.41–0.95)0.80(0.48–1.34)0.61(0.34–1.10)
Walking
None1.001.001.001.001.00
≥ 10.50(0.32–0.79)0.50(0.30–0.84)0.54(0.32–0.90)0.70(0.37–1.33)0.44(0.23–0.86)

PHQ-9 patient health questionnaire-9, OR odds ratio, CI confidence interval.

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More information: Aaron A. Kandola et al, Individual and combined associations between cardiorespiratory fitness and grip strength with common mental disorders: a prospective cohort study in the UK Biobank, BMC Medicine (2020). DOI: 10.1186/s12916-020-01782-9

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