Long-term Sedentary Behavior is Associated with Depression: A Cross-sectional Analysis from NHANSE 2017-2018

doi:10.21203/rs.3.rs-2479012/v1

Background

Lacking physical activity (PA) is an important risk factor for depression, the continuous decline of PA inevitably leads to the prolongation of sedentary behavior (SB) among adults, and limited evidence suggests that SB is also an independent risk factor associated with depression.

Objective

This study is to investigate the association between long-term sedentary behavior (LTSB) and depression in a representative sample of the American adult population using data from the National Health and Nutrition Examination Survey (NHANES).

Materials and Methods

Data from NHANES 2017–2018 were aggregated, including demographic information, degree of depression, PA, duration of sedentary behavior, body index, etc. PA was assessed by the Global Physical Activity Questionnaire (GPAQ). Depression was screened by a Patient Health Questionnaire (PHQ-9) in which includes several questions (Have little interest in doing things; Feeling down, depressed, or hopeless; Trouble sleeping or sleeping too much; etc.). Logistic regression was carried out to analyze associations between LTSB and depression.

Results

A total of 4728 adults (mean age 51.00 ± 17.49 years, 2310 males and 2418 females) were recruited in this study. The SB duration < 360 /d was negatively correlated with moderate to severe depression (r=-0.146, P = 0.029), while SB duration ≥ 720 min/d was a positive correlation with depression (r = 0.472, P = 0.001), significant correlations were not observed in other SB duration. LTSB had a significant effect on depression (OR = 1.484, 95% Cl: 1.176–1.817, P = 0.001), especially in moderate to severe depression (OR = 1.697, 95% Cl: 1.229–1.342, P = 0.001). The effects remained significant after adjusting for independent variables (OR = 1.429, 95% Cl: 1.122–1.820, P = 0.004), and this association was stronger in the occurrence of moderate to severe depression (OR = 1.586, 95% Cl: 1.139–2.210, P = 0.006). Furthermore, the detection rate of depression in females (710/2418, 29.36%) was higher than that in males (484/2310, 20.95%), and the difference was statistically significant (P < 0.001).

Conclusions

LTSB is a risk factor for depression, especially in moderate to severe depression. Middle-aged females who are not married tend to be the most likely to suffer from depression.

Depression

Long-term sedentary behavior (LTSB)

Physical activity

Sex difference

Mental disorders are the major causes of the global health-related burden, with depression being the primary contributor to this burden (1), which severely affects the quality of life in patients (2). Epidemiological investigations showed that over 350 million people had suffered from depression in 2010 (3), with an incident rate of up to 25% in females and 12% in males (3, 4). Hasin predicted that the 12-month and lifetime prevalence of depression was 10.4% and 20.6% in Americans (5). However, the situation continues to deteriorate (6); and recent surveys showed that the occurrence of depression in U.S. adults had increased (6, 7). It is urgent to discover the risk factors of depression and formulate intervention measures.

Physical activity (PA) was previously argued to be strongly associated with depression (8–12). Increasing PA was not only a crucial means to prevent depression but also an effective therapy (13). Exercise therapy has been proved to have a similar effect as drug therapy on the prognosis of patients with depression (14, 15). Activities with a metabolic equivalent of more than 1.5 METs during waking hours are PA, while those with a metabolic equivalent of less than 1.5 METs are generally classed as sedentary behavior (SB) (16, 17). The decrease of PA will inevitably lead to the increase of SB. World Health Organization suggested that adults aged 18–64 should limit the amount of time in SB and replace them with aerobic activity to prevent the occurrence of chronic conditions (18). In addition, studies have shown that the negative effect of SB was not always offset by the benefits of PA (19), and SB may be an independent risk factor for some chronic conditions. Therefore, it has started to recognize the impact of SB as an independent risk factor for depression.

Previous studies demonstrated that LTSB may lead to emotional disorders in university students (20, 21), adolescents (22–24) and senior citizens (25). However, these studies lacked a unified description of the American population, the number of samples was generally limited, and the representativeness also was weak. Therefore, a reliable large sample cross-sectional analysis in a representative sample of the American adult population is particularly essential.

The aim of the present study was to explore the impact of LTSB on depression through rigorous analysis and evaluation with the samples from a larger population. We found that LTSB was significantly associated with depression, especially with moderate to severe depression; depression is related to various demographic factors, and there are gender differences; middle aged non-married females are more likely to present depression.

Study Population

The National Health and Nutrition Examination Survey (NHANES) is a population-based cross-sectional survey designed to collect information about the health and nutrition situation of the U.S. household population (26). A stratified multistage sampling design was used to obtain a representative sample of U.S. residents of two months or older; the two-year survey cycle covers about 5000 families. The NHANES protocol was approved by the National Center for Health Statistic's research ethics review board; all adult participants provided written notice of consent (27). The present study extracted and aggregated data on physical activity, depression, and demographic characteristics from the NHANES 2017–2018, and the current sample is restricted to adults aged 20 and older.

Depression Assessment

The Patient Health Questionnaire (PHQ-9), a nine-item depression screening instrument, was used to assess the frequency of depression symptoms in the sample over the past 2 weeks. The questions were asked at the Mobile Examination Center (MEC) by trained interviewers using the Computer-Assisted Personal Interview (CAPI) system, which is programmed with built-in consistency checks to reduce data entry errors as part of the MEC interview. For each item, points ranging from 0 to 3, are associated with the response categories "not at all," "several days," "more than half the days," and "nearly every day.” (28, 29). A total score, ranging from 0 to 27, can be calculated for persons with complete responses to the symptom questions. Those who scored less than 5 were considered to have no depression; those who scored 5–9 were classed as mild depression; those who scored 9–19 were classed as moderate depression; and those who scored more than 19 were classed as severe depression (29). Moreover, the last question: “Over the last 2 weeks, how often have you been bothered by the following problem: Thoughts that you would be better off dead or of hurting yourself in some way?” was used to assess participants’ self-injury tendency (26).

Sedentary Behavior and Physical Activity Assessments

PA was self-reported by participants using questions based on the Global Physical Activity Questionnaire (GPAQ) (30). SB was assessed through one question: “The following question is about sitting at school, at home, getting to and from places, or with friends, including time spent sitting at a desk, traveling in a car or bus, reading, playing cards, watching television, or using a computer. Do not include time spent sleeping. How much time do you usually spend sitting on a typical day?” Participants report time in minutes. “10 hours” was well recognized as one of the critical points of sedentary duration time. Stay sedentary for more than 10 hours could be devastating to human health. An authoritative review demonstrated that SB more than 10 h/d had a significant negative impact on the human body, increasing the risk of chronic diseases as well as all-cause mortality (31). And another study showed that SB for more than 10 h/d could age females’ biological age up to 8 years (32). Thus, we took > 600 minutes as the classification standard of LTSB. The levels of Occupational physical activity (OPA) and leisure-time physical activity (LTPA) were calculated through the number of minutes that participants reported participating in moderate to vigorous work physical activities and recreational physical activities per week. There was vigorous PA as 2 or 0, and whether there was moderate PA as 1 and 0, and added these values, with 0, 1, and 3 representing inactive, moderate, and vigorous PA, respectively.

Demographic Characteristics Adjustments

Demographic variables include gender, age, race/ethnicity, education, marital status, smoking status (33), and body mass index (BMI). A total of 4728 participants were divided into three age groups: <40, 40–64, and > 60. Race/ethnicity was divided into Hispanic, Non-Hispanic white, Non-Hispanic black, Non-Hispanic Asian, and Other. The level of education was divided into < 12th grade, high school, some college, college graduate, or above. Marital status was classed into married and not married (living with a partner, widowed, divorced, separated, never married). Smoking status was defined as smoking (smoked 100 cigarettes in life) and non-smoking (did not smoke 100 cigarettes in life) (26). Weight and height were measured by trained technicians using standardized equipment during MEC physical examination; BMI was classed into two standard categories: general weight (≤ 28.0 kg/m²) and obese (> 28.0 kg/m²) (34).

Statistical Analyses

We first aggregated the extracted information and excluded missing and useless (refused, don’t know) data using Microsoft Excel 2010. NHANES adults aged 20 years and older with complete information on SB, PA, depression, and other characteristics were included in the analyses. We analyzed the descriptive characteristics separately in the depression group and non-depression group due to the purpose of this study. Weighted means and standard errors were calculated for continuous variables, while weighted proportions were summarized for categorical variables. T-test and variance analysis were carried out compared to continuous data between groups, while χ²-tests and Kruskal-Wallis-tests were carried out in comparison to counting data. We analyzed the correlation between SB duration and depression score by Spearman correlation analysis. Logistic regression was carried out to analyze associations between LTSB and depression. All data were analyzed using Statistical Package for Social Sciences (SPSS) version 23.0. P-values of less than 0.05 were considered statistically significant (2-sided tests).The equations should be inserted in editable format from the equation editor. SPSSAU was used as the plotting tool.

3.1 Demographic Characteristics

This study included a total of 4728 adults aged 20 years or older in the NHANES cycle 2017–2018 who have completed data on duration of SB, degree of depression, and demographic information. Mean age of participants was 51.00 ± 17.49 years at the time of examination, including 2310 males and 2418 females, with a mean SB duration of 330.61 ± 119.67 minutes. Significant statistical differences were observed in different gender (P < 0.001), age (P = 0.021), race (P = 0.043), marital status (P < 0.001), smoking status (P < 0.001), LTSB (P = 0.001), SB (P = 0.043), BMI (P < 0.001), self injury tendency (P < 0.001), OPA (P = 0.007) and LTPA (P < 0.001) between the depression group and the non-depression group. The differences in military service (P = 0.335) and education (P = 0.068) were not statistically significant. (See Table 1)

Table 1

Sample demographic characteristics by depression
Characteristics	sample capacity (%) N = 4728	Depression group n = 1194(26.6%)	Non-depression group n = 3534(73.4%)	test statistic	p
Gender Male Female	2310(48.86) 2418(51.14)	484 710	1826 1708	44.273^a	< 0.001^***
Age group < 40 40–60 > 60	1443(30.52) 1646(34.81) 1639(34.67)	351 455 388	1092 1192 1251	7.741^a	0.021*
Race Hispanic Non-Hispanic white Non-Hispanic black Non-Hispanic Asian Other	1060(22.42) 1675(35.43) 1112(23.52) 644(13.62) 237(5.01)	280 477 269 89 79	780 1198 843 555 158	-2.023^b	0.043^*
Military service Yes No	482(10.19) 4246(89.81)	113 1081	369 3165	0.931^a	0.335
Education < 12th grade High school Some college College graduate or above	871(18.42) 1145(24.22) 1552(32.83) 1160(24.53)	275 315 424 180	596 830 1128 980	-1.826^b	0.068
Marital status Married Not married	2377(50.27) 2351(49.73)	457 737	1920 1614	92.017^a	< 0.001^***
Smoking status Smoking Non-smoking	2009(42.49) 2719(57.51)	628 566	1381 2153	66.747^a	< 0.001^***
LTSB > 600min ≤ 600min	355(7.51) 4373(92.49)	116 1078	239 3295	11.202^a	0.001^**
SB < 360 ≥ 360,<480 ≥ 480,<600 ≥ 600,<720 ≥ 720	2726(68.42) 693(14.53) 619(9.54) 373(4.76) 317(2.75)	667 183 151 88 105	2059 510 468 285 212	-2.203^b	0.043^*
BMI(kg/m²) ≤ 28.0 > 28.0	2173(45.96) 2555(54.04)	461 733	1712 1822	34.750^a	< 0.001^***
Self-injury tendency Yes No	173(3.66) 4555(96.34)	160 1034	13 3521	430.000^a	< 0.001^***
OPA Inactive Moderate Vigorous	2489(52.64) 1069(22.61) 1170(24.75)	582 295 317	1907 774 853	9.821^a	0.007^**
LTPA Inactive Moderate Vigorous	2486(52.58) 1102(23.31) 1140(24.11)	767 227 200	1719 875 940	89.835^a	< 0.001^***
^aχ²-test, ^bKruskal-Wallis-test, ^*p < 0.05, ^**p < 0.01, ^***p < 0.001, same as below

3.2 Depression Percentage in This Study

More than a quarter of the samples were detected as depression individuals in this study. In a total of 4278 samples, 3534 (74.75%) participants with a PHQ-9 score < 5 were classed as no depression individuals; 1194 (25.25%) participants with a PHQ-9 score > 5 were classed as depression individuals, among which 777 (16.43%) had mild depression, and 417 (8.82%) had moderate to severe depression [378 (8.00%) for moderate, and 39 (0.82%) for severe, respectively] which were generally believed to require professional psychiatric treatments. (See Table 2 and Fig. 1)

Table 2

Sample depression status
Depression score	Assignment	Depression level	n(%)
0–4	0	no depression	3534(74.75)
5–9	1	mild depression	777(16.43)
10–19	3	moderate depression	378(8.00)
20–27	4	severe depression	39(0.82)

3.3 Comparison of Sedentary Duration and Depression

We plotted clusters of sedentary hours with depression scores (See Fig. 2). Where sedentary duration are the horizontal coordinate and the mean depression scores are the vertical coordinate. The results showed that the mean depression scores started a significant increasing trend starting from more 600 minutes of sedentary duration. Among them, the mean depression scores at 720, 900, 960 and 1020 minutes exceeded the depression threshold (> 4) of the PHQ-9. We plotted violin plots of sedentary duration and depression rating (See Fig. 3), in order to exhibit the distribution characteristics of depression rating in different sedentary duration. The values of the vertical coordinates indicate each of the four depression levels in the PHQ-9. The results showed that, as in the cluster plot, there was a tendency for the depression levels to expand from more than 600 minutes onwards.

3.4 Logistic Regression Analysis

LTSB were taken as the independent variable (0 = none, 1 = yes), depression (0 = non-depression, 1 = depression), and moderate to severe depression (0 = non-moderate to severe depression, 1 = moderate to severe depression) as the dependent variable, respectively. Variables with statistical significance in univariate analysis were included in logistic stepwise regression analysis. An a-entry = 0.05 and a-exit = 0.10 was used to select and eliminate the independent variables. Finally, gender, race, marital status, smoking LTPA, and BMI were included in the regression model. The two predictors are not maximally correlated (r < 0.7). To eliminate the interference of other variables, we have established the following four models: Model I: Primary model, adjusted for independent variable LTSB only. Model II: Adjusted for the independent variable in Model I plus gender, race and marital status. Model III: Adjusted the independent variable in Model II plus smoking. Model IV: Adjusted for the independent variable in Model III plus LTPA. Model V: Adjusted the for independent variable in Model IV plus BMI. Table 3 showed that in the first Logistic regression analysis, Model I (without excluding confounding factors) showed that the odds ratio (OR) of LTSB to depression was 1.484 (95% Cl: 1.176–1.817); Model II (adjusted variables of gender, race, and marine status) showed that the OR was 1.531 (95% Cl: 1.208–1.939), Model III (adjusted smoking variable) showed that the OR was 1.478 (95% Cl: 1.164–1.877); Model IV (adjusted LTPA variable) showed that the OR was 1.464 (95%Cl: 1.151–1.864); and Model V (adjusted BMI variable) showed that the OR was 1.429 (95% Cl: 1.122–1.820). Results showed that, after adjusting for confounding factors, LTSB was still a risk factor for depression. Participants with LTSB were 1.429 times more likely to develop depression than those without LTSB. Similar results were observed in another Logistic regression analysis, which Model I-V showed OR was 1.697 (95% Cl: 1.229–1.342), 1.727 (95% Cl: 1.246–2.393), 1.661 (95% Cl:1.196–2.307), 1.633 (95% Cl: 1.173–2.273), 1.586 (95% Cl: 1.139–2.210), respectively. (All P < 0.01). (See Table 3)

Table 3

Results from Logistic progressive regression analysis of LTSB and depression
Depressive division	Mode	b	SE	Wald	p	OR(95%Cl)
Depression (> 4)	I^c	0.394	0.118	11.084	0.001^**	1.484(1.176–1.817)
	II^d	0.426	0.121	12.414	< 0.001^***	1.531(1.208–1.939)
	III^e	0.391	0.122	10.278	0.001^**	1.478(1.164–1.877)
	IV^f	0.381	0.123	9.620	0.002^**	1.464(1.151–1.864)
	V^g	0.357	0.123	8.376	0.004^**	1.429(1.122–1.820)
Moderate to severe depression (> 9)	I^c	0.529	0.164	10.330	0.001^**	1.697(1.229–1.342)
	II^d	0.546	0.166	10.787	0.001^**	1.727(1.246–2.393)
	III^e	0.507	0.168	9.165	0.002^**	1.661(1.196–2.307)
	IV^f	0.490	0.169	8.451	0.004^**	1.633(1.173–2.273)
	V^g	0.461	0.169	7.434	0.006^**	1.586(1.139–2.210)

^c Primary model, adjusted for independent variable LTSB only. ^d Adjusted for the independent variable in Model I plus gender, race, and marital status. ^e Adjusted for the independent variable in Model II plus smoking. ^f Adjusted for the independent variable in Model III plus LTPA. ^g Adjusted for the independent variable in Model IV plus BMI.

4.1 Comparison of Demographic Characteristics

Demographic correlations are roughly consistent with previous surveys; however, there are some differences among PA.

A large number of studies have consisted that depression is more common among females; the results of this study support previous studies. This may be related to social factors, including gender discrimination, adversity exposure in childhood or adulthood, sexual abuse, etc (35), as well as biological factors, including exposure to developmental tissue risk factors, biological stress response, gonadal hormone concentrations, etc.

Significant differences were observed in depression among participants of different ages and presented a normal distribution, depression is more common in middle-aged participants. However, in previous studies, participants were mostly restricted, such as only with the elderly (25), university students (20,21), or patients with chronic conditions (36). Although failed to receive sufficient attention in previous studies, there was still evidence supporting that the middle-aged population is a high-risk group for depression (37). This may be due to the continuous downturn of the U.S. economic situation, the rising cost of living, the high unemployment rate and other factors related to greater stress among the middle-aged population. A study suggested that stress is an important risk factor for depression (38), and several other studies support this view (39-41).

Differences were also observed in depression levels among adults of different races, which is not particularly significant (P=0.043). Non-Hispanic whites are still the high incidence group. The depression incidence rates of non-Hispanic blacks and Hispanics are roughly similar, while non-Hispanic Asians are below the average level. The influencing factors of racial/ethnic differences in depression are complex, which may include complex mechanisms such as social, economic, cultural, biological factors and their interactions. The reasons for these differences are not clear yet, but does not reduce the importance of attention to minorities, in which treatment differences still exist (35).

The Highly educated population is less likely to present depression. There were no significant differences in depression between military personnel and non-military personnel and among different educational backgrounds. These two results support previous studies. However, an easily overlooked detail showed that the prevalence of depression among participants with college and above was significantly lower than those with other educational levels, which provides evidence for the perspective that the highly educated population is less likely to present depression. People with higher education tend to occupy more social resources, are better paid and less unemployed, which also leads to lower stress. Although previous studies suggested that the prevalence of depression among the highly educated population, especially master's and doctoral students, is significantly higher than the average level (42), but combined with the higher lifetime incidence rate of depression and long-term social facts, gaining a higher degree is still necessary.

A significant difference was also observed between married and non-married participants; that is, depression among married participants is significantly lower than that of non-married participants. In this regard, we suggest the following explanation: 1) marital status may directly affect depression, happy marriage may improve mental health. Psychological studies showed that intimate actions such as touching, kissing, hugging and intercourse can significantly reduce the incidence of depression (43,44). Intimate actions lead to the greater secretion of positively emotional catecholamines such as dopamine, which have been proved to significantly resist depression (45). 2) Depression may directly affect the marital status; those with depressive syndrome or already diagnosed with depression shall take more effort into attracting the opposite sex as well as maintaining a marriage.

Depression is more common among smokers (who have smoked 100 cigarettes in life), and may be strongly associated with addictions. The results from this study support previous studies; i.e. anxiety and depression were the most common emotional disorders, which have been proved to be important factors for drug, alcohol and tobacco as well as Internet addictions (46,47). However, whether participants’ smoking behavior causes depression or depression made them smoke has not been confirmed, but we prefer the latter view. In addition, depression is more common in obese participants. We believe this may as well be related to the mechanism of addiction. Except for a few patients with congenital obesity [such as leptin deficiency (48)], obesity was believed strongly related to uncontrolled diet (49), and quite a number of common chemicals in food, such as sucrose, sodium chloride, fat and caffeine, are addictive (50-52).

Patients with depression have a stronger tendency to self-injury (53). Another conclusion in this study supports this view, that is, depression is more common among participants with a tendency to self-injury. Depression is not a fatal or disabling disease, but it is an important risk factor leading to suicide and self-injury.

There were significant differences in depression between OPA and LTPA of different intensities, but the effects on depression were opposite: participants with greater intensity of OPA are more likely to present depression, while participants with greater intensity of LTPA were opposite. Previous studies normally believed that depression was significantly related to PA, and the more PA, the better. WHO did not make an upper limit recommendation for PA (18). However, the conclusion of this study found that depression is not only related to PA, but also may be related to the variety of PA. OPA may be a risk factor for depression, and LTPA may be a protective factor. Greater intensity of OPA may be related to greater stress, leading to boredom, anxiety and depression, while recreational PA may enhance positive emotions against stress. In addition, the conclusion of this study also enlightens us that there may be many complex interactions in the interior of PA. different physical activities may have different effects, and some of them could be negative.

4.2 Depression Situation

Middle-aged females who are not married tend to be the most likely to suffer from depression and may be accompanied by worse smoking status and physically less active. Middle-age is a high incidence period of chronic conditions in females (54), among which physical conditions, such as chronic pain, cancer, cardiovascular conditions, diabetes and hormone disorders, are the leading factors of depression in the middle-aged population (55). As presented physical disorders while presented indifferent and fail to commend basic physiological needs independently, one should contact a doctor immediately, for these symptoms may be related to emotional and subjective reactions, which is easy to trigger depression. When females entered the middle-age period, their endocrine situation changes sharply (56), which may lead to neurotransmitter disorders and unstable emotions. Patients with depressive disorder were believed to lack some chemicals called neurotransmitters (57) in their brains, and it is believed that the imbalance between serotonin and nor-epinephrine may lead to depression and/or anxiety. Lacking serotonin and nor-epinephrine often lead to depressive emotions, decreased motivation and changes in appetite and sexuality, which is also factors of depression in the middle-aged female population. On the other hand, emotional factors such as non-marriage and divorce may further deteriorate their depression situation.

In this study, 25.75% of participants were considered to have depressive symptoms, of which moderate to severe depression was 8.82%, which means that treatment is acquired. Differences in the incidence rate of depression were observed in different countries and regions. (58) The representative sample has a high risk of depression, which are therefore a cause for general alarm in U.S. residents. The United States is one of the most developed countries in the world, but its conditions of depression is as well among the highest (5). To our knowledge, we believe that the following three social factors are to be deeply concerned: 1) People are experiencing more stress events. Stress events are required high-intensity centralized attention to deal with. These kinds of stuffs need careful planning, which requires more time and attention than usual, which naturally increases the psychological burden. 2) Abuse and bullying occur frequently. Victims who have experienced some physical and mental abuse, or campus bullying, are often more likely to increase the risk of depression. In particular, one's self-esteem and sense of security could be seriously affected by the long-term insulting and abusing in childhood, or being in an abusive relationship in adulthood and being subjected to the control and malicious attack of one’s partner. Currently, various cases of depression and even suicide events caused by campus bullying has been reported. 3) People may be experiencing more interpersonal disharmony. Studies confirmed that people's happiness is not about their income or social status but the harmony of important interpersonal relationships (59), especially intimate ones. Disharmonious important interpersonal relationships and frequent family conflicts could lead to negative emotions. One cannot live without these important relationships, and they are fixed with problems, leading to long-term emotional distress. If these relationships are not improved and emotions are not adjusted, depression may take its advantage.

4.3 Sedentary Behavior Duration Situation

The factors affecting SB are diverse, including but not limited to personal and social factors. Studies revealed that educational level, age, employment status, gender, BMI, income, smoking status, moderate to vigorous PA, attitude, depressive symptoms and quality of life were related to sedentary behavior (35). Our study has not explored the factors of SB and the impact of the environment on it, which is also the directions of future research. However, we discovered that the average length of SB of participants was 330.61 ± 119.67, which may be due to the wide demographic distribution of the included participants, which led to significant differences.

4.4 Findings Support or Supplement to Previous Studies

This study found in a large representative sample of the adult population in the U.S. that with the length of LTSB, the risk of depression increased, especially the risk of moderate to severe depression. The study found a significant positive correlation between LTSB and depression only in the LTSB population of 720 min and above. In contrast, there was no correlation between SB and depression in other periods, except that SB less than 360 min showed a significant negative correlation with depression. Previous studies have shown that sedentary behavior in all its form was a risk factor for depression in different populations. Lee found that as sitting hours increased, university students' stress, anxiety, and depression significantly increased, and suggested intervention programs that reduce SB and improve PA were necessary (60). Xu found that the total sedentary time and time spent on school assignments on weekends were significantly associated with depression (20). Results from Meta-analyses suggested that mentally passive SB, such as watching television, could increase the risk of depression, interventions that reduce mentally passive SB may prevent depression (61). While screening time-based sedentary behavior was also approved to be associated with depression risk and the effects varied in different populations (62). Other Meta-analyses also contribute to this conclusion (24). Eriksson pointed out that in the 70-years and older population a greater percentage of the day spent sedentary and the longest average length of sedentary bouts increased the risk of depression (63). In addition, this study is also a supplement to previous studies, which confirms that SB, as an independent risk factor, contributes to the occurrence of depression. A previous study on the combined effect of SB and PA showed that although reducing PA could cause an increase in depression symptoms, a combined effect on changes in depression was not observed. Researchers hold doubt as to whether reduced PA or increased SB were driving the changes in psychological function (19). Another study suggested that evidence highlights the importance of maintaining physical activity and reducing sedentary screen-use to promote mental health (64). The conclusion of this study supports previous studies, i.e. SB is still an independent risk factor for depression, excluding the influence of PA and other variables, and adds to the confusion about the impact of depression under the mixed influence of PA and SB in previous studies.

4.5 New Findings from This Study

PA and SB are a pair of relative concepts. Generally, the intensity of activity during the awake time was used as the division basis and took 1.5 MET as the boundary value between SB and PA (16). Once the length of PA increases, it will inevitably lead to the shortening of SB duration. An interesting result showed that SB less than 360 min was negatively correlated with depression. This conclusion had never been mentioned in previous studies. To our knowledge, this conclusion is related to the length of PA: the reduction of SB will inevitably lead to an increase in PA, and there was evidence that the length of PA should also be within a certain time range (65,66). Previous studies have always emphasized the negative psychological effects of insufficient physical activity, but few studies provided evidence that excessive PA can also bring negative psychological effects. Previous studies found that excessive exercise may lead to a series of physical conditions (67,68), and chronic physical symptoms were one of the important factors leading to depression (69). Therefore, we believe that SB is also a resting behavior to some extent and should be within a reasonable period, just like PA and sleep (70). Thus, one of future research directions is to determine the best SB range through large-scale epidemiological investigation and analysis, to supplement various suggestions on PA in previous studies.

4.6 Limitations of This Study

This study has several limitations, including in data selections and reference cites related to this study. Depression situations were changing sharply (6), we performed cross-sectional analysis extracted only one cycle of data, which failed to reflect the changes in depression situations among U.S. residents. The outbreak of corona-virus disease 2019 (COVID-19) pandemic in late 2019 significantly impacted on daily routine. However, the 2017-2018 data we selected excluded entirely the impact of the pandemic on various key factors. Given above circumstances, we propose the following solutions: 1) we will combine data of different cycles and weight them to establish a complete database for further analyses. 2) Based on the fact that the NHANES program suspended field operations in March 2020 due to the pandemic, data collection for the NHANES 2019-2020 cycle was not completed, and the collected data are not nationally representative, it is necessary to conduct another epidemiological survey to explore the impact of SB on depression under the influence of COVID-19 pandemics in the future. There were few studies similar to this study, which was another main limitation. Due to this concern, we summarized the following possibilities: first, current studies were mainly focused on the impact of PA on depression or the harm of sedentary conditions in depressive patients. Second, whether SB leads to depression or patients presented SB due to their depressive syndrome is still uncertain and needs further discussion. Third, increasing PA through interventions is essentially the same as reducing SB. Although the lack of similar studies leads to some limitations in ideas and references it also indicates that this study is unique. The results support that SB is an independent risk factor for depression; thus, in future studies, we will continue to verify the reliability of this conclusion by increasing the sample size as well as switching investigation areas. In addition, this study also had certain limitations in the exclusion of interference factors. Some common risk factors of SB, together with depression related to disabilities and chronic conditions, were not excluded. Due to the insufficient original investigation, data on some factors cannot be directly obtained. Additionally, the number of these samples is limited, which may have an impact on the reliability of study results. Thus, future research designed should avoid these interference factors and rigorously exhibit the impact of SB to public.

In summary, depression is a global public health burden that needs to be solved urgently, and the U.S. is among one of the most serious. Depression has been proved to be strongly related to PA, and most of the current studies have focused on such topics as "increasing PA to relieve depression" or "increasing PA to prevent depression". However, little attention has been paid to the concept of SB as opposed to PA. The harm of LTSB may not be offset by PA. Therefore, this study took U.S. adults as the research object, aiming to explore the influence of LTSB as an independent risk factor on depression.

As the research has demonstrated, LTSB is an independent risk factor for depression. This study first conducted a correlation analysis between SB and depression for different duration of time, aiming to establish the significance of "long term" in LTSB while exploring the correlation between the two. The results showed that LTSB for more than 720 min was significantly related to depression, which proved the role of time in the formation of SB harm to the human body. In this study, regression models were carried out in the analysis to exclude the influence of complex interference factors. Since factors affecting depression are varied and complicated, it is necessary to analyze LTSB independently. The results show that LTSB had a significant effect on depression after adjusting for significant independent variables, and these associations were stronger in the occurrence of moderate to severe depression, which verifies the core idea of this study.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The datasets generated and/or analysed during the current study are available in the [NHANES] repository, [NHANES Questionnaires, Datasets, and Related Documentation (cdc.gov)]. Raw data supporting the obtained results are available at the corresponding author.

Author Contributions

HM and YL conceived and designed the study. HM organized the database, performed the statistical analysis and wrote the manuscript. YL and GW contributed to the discussion. HM, YL, MZ, JP, JX and GW revised the manuscript. All authors edited, revised, and certified the final version of this manuscript.

Funding

This study were supported by the High-end Foreign Experts Introduction Program (Grants No.HNGD2022025) and the 2021 Henan Key R&D and Promotion (tackling key scientific and technological problems) Project (Grants No.212102310022) of the Department of Science and Technology of Henan Province.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to thank all the staff and participants of the National Health and Nutrition Examination Survey 2017-2018 cycle for their valuable contributions. Any interpretation or conclusion related to this manuscript does not represent the views of the CDC or the NHANES. We would also like to thank the editors and reviewers for their valuable and constructive comments to help us improve the manuscript. And we especially thank Dr. JH for his constructive suggestions.

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No competing interests reported.

Long-term Sedentary Behavior is Associated with Depression: A Cross-sectional Analysis from NHANSE 2017-2018

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