Next Article in Journal
Explaining the Consumption Technology Acceptance in the Elderly Post-Pandemic: Effort Expectancy Does Not Matter
Previous Article in Journal
Risk Factors in Specialists and Generalists of Child-to-Parent Violence: Gender Differences and Predictors of Reactive and Proactive Reasons
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Behavioral Sciences
Volume 13
Issue 2
10.3390/bs13020086
behavsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Relationships among Depressive Symptoms, Body Weight, and Chronic Pain: A Cross-Sectional Analysis of the Shika Study

by
Shinobu Fukushima
1,
Fumihiko Suzuki
2,3,
Hiromasa Tsujiguchi
1,2,4,
Akinori Hara
1,2,4,
Sakae Miyagi
5,
Takayuki Kannon
4,6,
Keita Suzuki
2,
Yukari Shimizu
7,
Thao Thi Thu Nguyen
8,
Toru Yanagisawa
1,
Fumika Oku
1,
Kuniko Sato
9,
Masaharu Nakamura
2,
Koichiro Hayashi
1,
Aki Shibata
2,
Tadashi Konoshita
10,
Yasuhiro Kambayashi
11,
Hirohito Tsuboi
12,
Atsushi Tajima
4,6 and
Hiroyuki Nakamura
1,2,4,*
1
Department of Public Health, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University, 13-1 Takaramachi, Kanazawa 920-8640, Japan
2
Department of Hygiene and Public Health, Faculty of Medicine, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, Kanazawa 920-8640, Japan
3
Community Medicine Support Dentistry, Ohu University Hospital, Koriyama 963-8611, Japan
4
Advanced Preventive Medical Sciences Research Center, Kanazawa University, 1-13 Takaramachi, Kanazawa 920-8640, Japan
5
Innovative Clinical Research Center, Kanazawa University, 13-1 Takaramachi, Kanazawa 920-8641, Japan
6
Department of Bioinformatics and Genomics, Graduate School of Advanced Preventive Medical Sciences, Kanazawa University, 13-1 Takaramachi, Kanazawa 920-8640, Japan
7
Department of Nursing, Faculty of Health Sciences, Komatsu University, 14-1 Mukaimotorimachi, Komatsu 923-0961, Japan
8
Faculty of Public Health, Hai Phong University of Medicine and Pharmacy, Ngo Quyen, Hai Phong 180000, Vietnam
9
Department of Clinical Cognitive Neuroscience, Graduate School of Medical Science, Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan
10
Third Department of Internal Medicine, Faculty of Medical Sciences, University of Fukui, Shimoaizuki, Eiheiji-cho, Yoshida-gun, 23-3 Matsuoka, Fukui 910-1193, Japan
11
Department of Public Health, Faculty of Veterinary Medicine, Okayama University of Science, 1-3 Ikoinooka, Imabari 794-8555, Japan
12
Graduate School of Human Nursing, University of Shiga Prefecture, 2500 Hassaka-cho, Hikone 522-8533, Japan
 
add Show full affiliation list
 
remove Hide full affiliation list
*
Author to whom correspondence should be addressed.
Behav. Sci. 2023, 13(2), 86; https://doi.org/10.3390/bs13020086
Submission received: 10 December 2022 / Revised: 14 January 2023 / Accepted: 18 January 2023 / Published: 20 January 2023
Browse Figure
Review Reports Versions Notes

Abstract

:
Although depression and body weight have individually been associated with chronic pain (CP), it currently remains unclear whether the combination of depressive symptoms (DS) and being underweight/overweight is related to CP. Therefore, we herein investigated the relationships among depression, body mass index (BMI), and CP in community-dwelling middle-aged and elderly individuals. Participants comprised 2216 inhabitants of Shika town in Ishikawa prefecture, Japan, including 1003 males (mean age of 68.72 years, standard deviation (SD) of 8.36) and 1213 females (mean age of 69.65 years, SD of 9.36). CP and DS were assessed using a CP questionnaire and Geriatric Depression Scale-15, respectively. The Breslow–Day test indicated that DS positively correlated with lumbar/knee pain in the BMI < 25 group, but not in the BMI ≥ 25 group. Furthermore, lumber/knee pain was related to a higher BMI. These results were confirmed by a logistic analysis with age, sex, BMI, solitary living, the duration of education, no exercise/hobbies, smoking history, alcohol intake, and medical treatment for diabetes, hyperlipidemia, or hypertension as confounding factors. The present study indicates the importance of considering DS and BMI in the prevention of CP. Further studies are needed to clarify the causal relationships among depression, BMI, and CP.

1. Introduction

Pain is defined by the International Association for the Study of Pain (IASP) as an unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage [1]. Chronic pain (CP) is defined as pain that persists or recurs for more than three months [2]. The prevalence of CP ranges between 17.5% [3] and 40.2% [4] in Japan, and 50.2 million (20.5%) adults in the USA have CP [5]. Primary prevention that targets community residents is important because CP affects the quality of life (QOL) of adults [6].
Our previous studies reported relationships between CP and various factors, such as vitamin intake and health-related QOL (HRQoL) [7], hypertension and HRQoL [8], alcohol intake and depression [9], fatty acid intake and C-reactive protein levels [10], and hypertension and being underweight [11]. Stress caused by pain has been implicated in the development of depression [12]. A clinical study showed that up to 85% of CP patients had severe depression [13], while a cross-sectional study reported that the threshold for CP was significantly reduced in patients with depression [14]. A common mechanism in depressive disorder and CP is central hyperexcitability caused by inhibited serotonergic functions [14]. Therefore, the relationship between CP and depression warrants further study.
In addition to CP, depression is associated with body weight [15,16,17,18,19,20,21,22,23]. A cross-sectional study reported a positive relationship between being overweight or obese and depression and depression-like symptoms in both sexes [22]. In contrast, another study demonstrated that individuals with depression-like symptoms were likely to be not only obese, but also underweight [21].
Another factor related to CP is body weight. A high body mass index (BMI) was previously shown to correlate with chronic low back pain [24,25,26]. However, limited information is currently available on the relationships among depression, body weight, and CP [27]. A cross-sectional study revealed that age, BMI, and depression positively correlated with the risk and severity of CP [28]. Furthermore, a co-twin study by Pradeep et al. [18] and a cross-sectional study by Rogers et al. [29] indicated relationships among obesity, depression, and CP. Zheng et al. [30] recently suggested that a younger age, higher BMI, higher scores for Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain, dysfunction, and stiffness, a lower education level, the presence of more than one comorbidity, and two or more body sites with pain correlated with a higher incidence of depression.
Although depression and body weight have individually been associated with CP, it currently remains unclear whether the combination of depressive symptoms (DS) and being underweight/overweight are related to CP. Therefore, we herein investigated the relationships among depression, BMI, and CP in community-dwelling middle-aged and elderly individuals.

2. Materials and Methods

2.1. Participants

We leveraged cross-sectional data collected from October 2013 to December 2016 in the Shika Study [7,8,9,10,31,32,33,34]. The subjects were 5013 residents [35] aged 40 years or older living in four randomly selected model districts (Horimatsu, Higashimasuho, Tsuchida, and Togi districts) in Shika town, Ishikawa prefecture in Japan, and obtained informed consent from all. Of the 4550 people who underwent physical examination, 2116 subjects (1003 males and 1213 females with mean ages of 68.72 years (SD = 8.36) and 69.65 years (SD = 9.36), respectively) were selected for analysis according to the following selection criteria. Selection criteria: answered questions related to age, education, BMI, living pattern, exercise/hobbies, smoking, alcohol consumption, and the treatment of underlying diseases; age at the time of these answers was 55 years or older; energy intake of more than 600 kcal/day and less than 4000 kcal/day; and answered the CP questionnaire and Geriatric Depression Scale-15 (GDS-15). Figure 1 shows the participant recruitment chart.

2.2. Instrumentation

2.2.1. CP

CP was evaluated using the same method as in the study by Amatsu et al. [9]. That is, participants were asked whether they had pain that lasted more than 3 months, its location, and the intensity of that pain on a scale of 1–10.

2.2.2. DS Assessment

The Japanese short version of GDS-15 for self-completed questionnaire [36,37] was used to assess depressive symptom states, and evaluated as in the study by Amatsu et al. [9].

2.2.3. BMI

BMI was calculated using current weight (kg) and height (meters).

2.3. Questionnaire on Characteristics

Participants completed a self-administered questionnaire on age, sex, the duration of education, exercise/hobbies, smoking history, and medical treatment for diabetes, hyperlipidemia, hypertension, and depression.

2.4. Statistical Analysis

Statistical analyses were conducted with IBM SPSS Statistics ver. 25 for Windows (IBM, Armonk, NY, USA). The Student’s t-test was applied to investigate the relationships between continuous variables; on the other side, the chi-square test was adopted to examine those between categorical variables. The Breslow–Day test was used to analyze the homogeneity of proportions of CP for each site by BMI and DS. Multiple logistic regression analysis was conducted for relationship assessment between DS and pain at any site, neck/shoulder/upper limb pain, and lumbar/knee pain stratified by BMI. Independent variables were age, sex, BMI, solitary living, the duration of education, no exercise/hobbies, smoking history, alcohol intake (density method), and medical treatment for diabetes, hyperlipidemia, or hypertension. The data were stratified by BMI and analyzed. Forced entry method was used to select variables. p < 0.05 was considered statistically significant.

3. Results

3.1. Participant Characteristics

Table 1 indicates the characteristics of participants by sex, including BMI, DS, and CP (Table 1). Females were significantly older than males (p < 0.001). The percentages of participants with solitary living (p < 0.001), without exercises/hobbies (p = 0.026), and undergoing treatment for hyperlipidemia (p < 0.001) were significantly lower in males than in females. In contrast, the duration of education (p = 0.006), the percentage of smokers (p < 0.001), and those undergoing treatment for diabetes (p < 0.001) and hypertension (p = 0.006) were significantly lower in females than in males. Alcohol intake (crude data and density method) was also significantly lower in females than in males (p < 0.001). On the other hand, the percentage of participants with no alcohol intake was lower in males than in females (p < 0.001). The percentages of participants with pain at any site (p = 0.005) and lumber/knee pain (p = 0.043) were significantly higher in females than in males. No significant differences were observed in the percentages of participants with DS (p = 0.064) and BMI (p = 0.272) between males and females.

3.2. Comparisons of Participants without and with DS

Table 2 presents comparisons of participants without and with DS. The mean age was significantly younger in the no DS group than in the DS group (p < 0.001). The percentages of participants with solitary living (p = 0.0289) and exercise/hobbies (without) (p < 0.001) were significantly lower in the no DS group than in the DS group. The duration of education (p = 0.013), BMI (p = 0.001), the percentage of participants with treatment for hyperlipidemia (p < 0.001), and the percentage of participants without alcohol intake (p = 0.025) were significantly lower in the DS group than in the no DS group. The percentages of participants with pain at any site (p < 0.001), neck/shoulder/upper limb pain (p = 0.016), and lumber/knee pain (p < 0.001) were significantly lower in the no DS group than in the DS group.

3.3. Comparisons of Participants with and without Lumber/Knee Pain

Table 3 shows comparisons of participants with and without lumber/knee pain. Mean age was significantly older in the no lumber/knee pain group than in the lumber/knee pain group (p < 0.001). The percentage of participants with solitary living (p = 0.003), DS (p < 0.001), no alcohol intake (p = 0.011), and BMI (p = 0.047) were significantly lower in the no lumber/knee pain group than in the lumber/knee pain group. The duration of education was significantly shorter in the lumber/knee pain group than in the no lumber/knee pain group (p < 0.001). The percentages of participants with pain at any site (p < 0.001), neck/shoulder/upper limb pain (p < 0.001), and foot pain (p < 0.001) were significantly lower in the no lumber/knee pain group than in the lumber/knee pain group.

3.4. Comparisons of CP and DS in Participants Stratified by two BMI Groups

Table 4 shows the percentage of participants with pain at any site, neck/shoulder/upper limb pain, lumber/knee pain, and foot pain with and without DS stratified by BMI < 25 and ≥ 25. Chi-square tests showed that the percentages of participants with pain at any site (p < 0.001), neck/shoulder/upper limb pain (p = 0.016), lumber/knee pain (p < 0.001), and foot pain (p = 0.010) were significantly lower in the DS with BMI < 25 group than in the no DS with BMI < 25 group, whereas no significant differences were observed between the DS and no DS with BMI ≥ 25 groups. With Breslow–Day tests, an analysis of homogeneity for the percentage of participants having lumber/knee pain with DS between the BMI groups showed a significant result (p = 0.049). Therefore, the percentage of participants having lumber/knee pain with DS was significantly higher in BMI < 25 group than in the BMI ≥ 25 group.

3.5. Multiple Logistic Regression Analysis of DS and CP in Participants Stratified by Two BMI Groups

Table 5 shows the results of a multiple logistic regression analysis of the relationship between CP and DS in participants stratified by BMI. The independent variable was DS adjusted for the following covariates: age, sex, BMI, solitary living, the duration of education, exercise/hobbies (without), smoking, alcohol intake (density method), DS, and treatment for diabetes, hyperlipidemia, and hypertension. DS were a significant independent variable for pain at any site (OR: 2.191; 95%CI: 1.526, 3.144; p < 0.001), neck/shoulder/upper limb pain (OR: 2.040; 95%CI: 1.156, 3.600; p = 0.014), and lumber/knee pain (OR: 2.195; 95%CI: 1.437, 3.353; p < 0.001) in participants with BMI < 25, but not in those with BMI ≥ 25. Furthermore, age was a significant independent variable for pain at any site (OR: 1.030; 95%CI: 1.008, 1.052; p = 0.007), neck/shoulder/upper limb pain (OR: 0.952; 95%CI: 0.918, 0.987; p = 0.008), and lumber/knee pain (OR: 1.059; 95%CI: 1.033, 1.086; p < 0.001), sex was a significant independent variable for pain at any site (OR: 2.231; 95%CI: 1.411, 3.527; p = 0.001), neck/shoulder/upper limb pain (OR: 2.180; 95%CI:1.030, 4.612; p = 0.042), and lumber/knee pain (OR: 1.766; 95%CI: 1.054, 2.957; p = 0.031), and BMI was a significant independent variable for lumber/knee pain (OR: 1.122; 95%CI: 1.013, 1.243; p = 0.027) in participants with BMI < 25, but not in those with BMI ≥ 25. The duration of education was a significant variable for pain at any site (OR: 0.874; 95%CI: 0.771, 0.992; p = 0.037) and smoking was a significant variable for pain at any site (OR: 2.736; 95%CI: 1.258, 5.952; p = 0.011) and lumber knee pain (OR: 4.950; 95%CI: 2.102, 11.656; p < 0.001) in participants with BMI ≥25, but not in those with BMI < 25. These results suggest that CP is associated with DS only in participants with BMI < 25.

4. Discussion

The main result of the present study was that DS positively correlated with lumbar/knee pain in the BMI < 25 group, but not in the BMI ≥ 25 group. Furthermore, lumber/knee pain was related to a higher BMI. Previous studies indicated that individuals with a high BMI are more likely to have CP. A cross-sectional study by Lee et al. showed that weight gain correlated with low back pain [24]. A meta-analysis by Shiri et al. [25] revealed that being overweight or obese correlated with chronic low back pain. In addition, a Mendelian randomized trial by Elgaeva et al. [26] demonstrated the causal effect of BMI on chronic low back pain. A cross-sectional study with a multivariate model by Dong et al. [38] indicated that a BMI of 30 or higher was a modifiable factor in older adults, whereas a BMI lower than 30 was not. The present results showed that BMI was significantly higher in the lumbar/knee pain group than in the non-lumbar/knee pain group. Therefore, BMI appears to be a risk factor for CP. On the other hand, a two-way ANCOVA of the interaction between BMI groups and DS groups for CP revealed that CP was more frequent among participants in the BMI < 25 group with DS. The discrepancy between the findings of Lee et al. [24] and the present results may be attributed to the inclusion of DS in the analysis; we examined the involvement of not only BMI, but also DS in CP. We considered a high BMI to be directly associated with chronic low back pain; however, it is important to note that even a low BMI was associated with chronic low back pain in the presence of DS.
A review by Sheng et al. on the relationship between CP and depression reported that 85% of CP patients had severe depression [13]. A cross-sectional study by Klausenberg et al. [14] demonstrated that the threshold for CP was significantly reduced in patients with depression. The present study also showed that participants with DS were more likely to have CP, but that this relationship was linked to BMI. Regarding the relationship between depression and BMI, a longitudinal study by Kim et al. [39] indicated that depression contributed to weight loss rather than obesity, and also that being underweight appeared to result in the development of DS in middle-aged and elderly Asian populations. On the other hand, a cross-sectional study by Badillo et al. [20] suggested a positive relationship between being overweight or obese and depression and depression-like symptoms in both sexes. In the present study, BMI was lower in the DS group than in no DS group. Therefore, in consideration of the different results obtained on the relationship between CP and DS and CP and BMI, further studies are needed to concurrently examine the relationships among CP, DS, and BMI. The relationships among CP, depression, and BMI have only been examined in a cross-sectional analysis by Häuser et al. [27], and the findings obtained showed that age, BMI, and depression independently predicted disabling chronic low back pain. The present results demonstrated that DS correlated with chronic lumber/knee pain in the BMI < 25 group, but not in the BMI ≥ 25 group. Therefore, we speculate that DS are related to CP in non-obese individuals.
As a mechanism for low back pain, obesity with a BMI ≥ 25 is speculated to be related to weight compression of the discs in the joints [40] and anterior abdominal curvature of the lumbar spine [41]. In addition, cytokines secreted from adipose tissue and an increased adipocyte size, which is a characteristic of obesity, cause pain-mediated changes in the neurophysiological properties of peripheral nociceptors and central neurons [24,42]. On the other hand, in subjects with BMI < 25, central hyperexcitation due to decreased serotonin-producing function is involved in pain [14], and reduced serotonin/noradrenaline activates descending circuits at the spinal level to reduce the pain threshold [43], suggesting that blocked descending inhibitory pathways are associated with CP, even in subjects who are not overweight. Therefore, the mechanisms of CP development are different for obesity and DS. On the other hand, our results showed that DS is a factor involved in lumbar/knee pain in non-obese subjects, whereas the presence or absence of DS does not make a difference in the prevalence of lumbar/knee pain in obese subjects. Our findings showed that although obesity and DS are associated with CP, the presence of both factors does not additively or synergistically increase their prevalence. It is considered unique to this study since it has not been shown in previous studies. However, the involvement of these mechanisms requires further detailed investigation.
The present results showed that sex, the duration of education, and smoking were also associated with CP and BMI. Although a cross-sectional study by Hattori [44] demonstrated that sex was not associated with CP, the results obtained herein revealed that in the BMI < 25 group, women were more likely to have pain at any site, neck/shoulder/upper limb, and lumbar/knee pain than men. This difference may be related to the lower mean age in Hattori’s study [45] than in the present study and a different mechanism for the development of CP. Regarding the relationship between the duration of education and CP, a cross-sectional study reported that a lower level of education correlated with a higher prevalence of chronic low back and knee pain [44]. The present results also showed that the duration of education was lower in the CP group than in the non-CP group. Regarding smokers and CP, smokers report more severe pain and functional impairment than non-smokers [46,47,48]. The cessation of smoking and weight loss are used in combination to treat CP [49]. The present results were consistent with previous findings because CP was more likely to occur in participants with BMI ≥ 25 and a smoking history, but not in those with BMI < 25. These differences were significant for lumbar/knee pain. Our results show that solitary living is relevant in both CP and DS. Previous studies have reported an association between CP and loneliness [50,51,52]. A cross-sectional study of older adults [50] and a prospective longitudinal study of middle-aged [51] have demonstrated the correlation between pain and loneliness with depression. Furthermore, a longitudinal study by Emerson et al. [52] reported that at both the onset of the study and four years later, those in pain had 1.58 times higher levels of loneliness than those who were not. Therefore, our results seem to support the findings of previous studies.

Limitations and Future Directions

The strength of the present study is that it is an almost all-inclusive survey. On the other hand, it was a cross-sectional analysis; therefore, causal relationships regarding DS, BMI, and CP cannot be elucidated. In addition, no objective measurements were conducted for BDHQ, GDS, and CP because they are all self-administered surveys.

5. Conclusions

The present study indicated that DS positively correlated with lumbar/knee pain in the BMI < 25 group, but not in the BMI ≥ 25 group. Furthermore, lumber/knee pain was related to a higher BMI. The present study indicates the importance of considering DS and BMI in the prevention of CP.

Author Contributions

Conceptualization, S.F. and H.N.; Data curation, T.K. (Takayuki Kannon) and A.T.; Formal analysis, H.T. (Hiromasa Tsujiguchi) and M.N.; Funding acquisition, H.N.; Investigation, S.F., F.S., H.T. (Hiromasa Tsujiguchi), A.H., S.M., K.S. (Keita Suzuki), Y.S., T.T.T.N., T.Y., F.O., K.S. (Kuniko Sato), M.N., K.H., A.S. and H.T. (Hirohito Tsuboi); Methodology, H.N.; Project administration, H.N.; Resources, H.N.; Supervision, T.K. (Tadashi Konoshita) and H.N.; Validation, H.T. (Hiromasa Tsujiguchi) and M.N.; Visualization, F.S.; Writing—original draft preparation, S.F. and F.S.; Writing—review and editing, H.T. (Hiromasa Tsujiguchi), A.H., S.M., T.K. (Takayuki Kannon), K.S. (Keita Suzuki), Y.S., T.T.T.N., T.Y., F.O., K.S. (Kuniko Sato), M.N., K.H., A.S., T.K. (Tadashi Konoshita), Y.K., H.T. (Hirohito Tsuboi), A.T. and H.N. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by Grants-in-Aid for Scientific and Technology-Japan (Research project/Area number: 19H03882) and Health Labour Sciences Research Grant (2019–2021, 19FG2001).

Institutional Review Board Statement

This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving research study participants were approved by the Ethics Committee of Kanazawa University (No. 1491).

Informed Consent Statement

Written informed consent was obtained from all participants prior to their participation.

Data Availability Statement

Data in the present study are available upon request from the corresponding author. Data are not publicly available due to privacy and ethical policies.

Acknowledgments

The authors thank all the participants in the Shika Town study, as well as collaborators including the field survey staff and experimental staff.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Raja, S.N.; Carr, D.B.; Cohen, M.; Finnerup, N.B.; Flor, H.; Gibson, S.; Keefe, F.J.; Mogil, J.S.; Ringkamp, M.; Sluka, K.A.; et al. The Revised International Association for the Study of Pain Definition of Pain: Concepts, Challenges, and Compromises. Pain 2020, 161, 1976–1982. [Google Scholar] [CrossRef] [PubMed]
  2. Treede, R.D.; Rief, W.; Barke, A.; Aziz, Q.; Bennett, M.I.; Benoliel, R.; Cohen, M.; Evers, S.; Finnerup, N.B.; First, M.B.; et al. Chronic Pain as a Symptom or a Disease: The IASP Classification of Chronic Pain for the International Classification of Diseases (ICD-11). Pain 2019, 160, 19–27. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Kasai, Y.; Sakakibara, T.; Wang, Z.; Paholpak, P.; Kosuwon, W.; Oo, M. Cross-Sectional Study A Comparison of Chronic Pain Prevalence in Japan, Thailand, and Myanmar. Pain Physician 2013, 16, 603–608. [Google Scholar] [CrossRef]
  4. Imai, R.; Imaoka, M.; Nakao, H.; Hida, M.; Tazaki, F.; Omizu, T.; Ishigaki, T.; Nakamura, M. Association between Chronic Pain and Pre-Frailty in Japanese Community-Dwelling Older Adults: A Cross-Sectional Study. PLoS ONE 2020, 15, e0236111. [Google Scholar] [CrossRef] [PubMed]
  5. Yong, R.J.; Mullins, P.M.; Bhattacharyya, N. Prevalence of Chronic Pain among Adults in the United States. Pain 2022, 163, e328–e332. [Google Scholar] [CrossRef]
  6. Geneen, L.J.; Moore, R.A.; Clarke, C.; Martin, D.; Colvin, L.A.; Smith, B.H. Physical Activity and Exercise for Chronic Pain in Adults: An Overview of Cochrane Reviews. Cochrane Database Syst. Rev. 2017, 4. [Google Scholar]
  7. Mitoma, J.; Kitaoka, M.; Asakura, H.; Anyenda, E.O.; Hori, D.; Tao, N.T.T.; Hamagishi, T.; Hayashi, K.; Suzuki, F.; Shimizu, Y.; et al. Prevalence of Chronic Pain, Especially Headache, and Relationship with Health-Related Quality of Life in Middle-Aged Japanese Residents. Health 2016, 8, 116–124. [Google Scholar] [CrossRef] [Green Version]
  8. Kitaoka, M.; Mitoma, J.; Asakura, H.; Anyenda, O.E.; Nguyen, T.T.T.; Hamagishi, T.; Hori, D.; Suzuki, F.; Shibata, A.; Horii, M.; et al. The Relationship between Hypertension and Health-Related Quality of Life: Adjusted by Chronic Pain, Chronic Diseases, and Life Habits in the General Middle-Aged Population in Japan. Environ. Health Prev. Med. 2016, 21, 193–214. [Google Scholar] [CrossRef]
  9. Amatsu, T.; Tsujiguchi, H.; Hara, A.; Miyagi, S.; Kannon, T.; Suzuki, K.; Shimizu, Y.; Nguyen, T.T.T.; Pham, K.O.; Suzuki, F.; et al. Relationship between Alcohol Intake and Chronic Pain with Depressive Symptoms: A Cross-Sectional Analysis of the Shika Study. Int. J. Environ. Res. Public Health 2022, 19, 2024. [Google Scholar] [CrossRef]
  10. Asai, A.; Suzuki, F.; Tsujiguchi, H.; Hara, A.; Miyagi, S.; Kannon, T.; Suzuki, K.; Nakamura, M.; Shimizu, Y.; Nguyen, T.T.T.; et al. Relationship between Fatty Acid Intake and Chronic Neck/Shoulder/Upper Limb Pain without Elevated CRP in a Japanese Population: A Cross-Sectional Analysis of the Shika Study. J. Nutr. Sci. 2022, 11, e38. [Google Scholar] [CrossRef]
  11. Yanagisawa, T.; Suzuki, F.; Tsujiguchi, H.; Hara, A.; Miyagi, S.; Kannon, T.; Suzuki, K.; Shimizu, Y.; Nguyen, T.T.T.; Oku, F.; et al. Hypertension and Low Body Weight Are Associated with Depressive Symptoms Only in Females: Findings from the Shika Study. Behav. Sci. 2022, 12, 413. [Google Scholar] [CrossRef] [PubMed]
  12. Leeuw, M.; Goossens, M.E.J.B.; Linton, S.J.; Crombez, G.; Boersma, K.; Vlaeyen, J.W.S. The Fear-Avoidance Model of Musculoskeletal Pain: Current State of Scientific Evidence. J. Behav. Med. 2007, 30, 77–94. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Sheng, J.; Liu, S.; Wang, Y.; Cui, R.; Zhang, X. The Link between Depression and Chronic Pain: Neural Mechanisms in the Brain. Neural Plast. 2017, 2017, 9724371. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Klauenberg, S.; Maier, C.; Assion, H.J.; Hoffmann, A.; Krumova, E.K.; Magerl, W.; Scherens, A.; Treede, R.D.; Juckel, G. Depression and Changed Pain Perception: Hints for a Central Disinhibition Mechanism. Pain 2008, 140, 332–343. [Google Scholar] [CrossRef] [PubMed]
  15. Jéquier, E. Leptin Signaling, Adiposity, and Energy Balance. Ann. N. Y. Acad. Sci. 2002, 967, 379–388. [Google Scholar] [CrossRef]
  16. Luppino, F.S.; de Wit, L.M.; Bouvy, P.F.; Stijnen, T.; Cuijpers, P.; Penninx, B.W.J.H.; Zitman, F.G. Overweight, Obesity, and Depression: A Systematic Review and Meta-Analysis of Longitudinal Studies. Arch. Gen. Psychiatry 2010, 67, 220–229. [Google Scholar] [CrossRef]
  17. Jung, S.J.; Woo, H.T.; Cho, S.; Park, K.; Jeong, S.; Lee, Y.J.; Kang, D.; Shin, A. Association between Body Size, Weight Change and Depression: Systematic Review and Meta-Analysis. Br. J. Psychiatry 2017, 211, 14–21. [Google Scholar] [CrossRef] [Green Version]
  18. Mannan, M.; Mamun, A.; Doi, S.; Clavarino, A. Prospective Associations between Depression and Obesity for Adolescent Males and Females—A Systematic Review and Meta-Analysis of Longitudinal Studies. PLoS ONE 2016, 11, e0157240. [Google Scholar] [CrossRef] [Green Version]
  19. Yu, N.W.; Chen, C.Y.; Liu, C.Y.; Chau, Y.L.; Chang, C.M. Association of Body Mass Index and Depressive Symptoms in a Chinese Community Population: Results from the Health Promotion Knowledge, Attitudes, and Performance Survey in Taiwan. Chang. Gung Med. J. 2011, 34, 620–627. [Google Scholar]
  20. Badillo, N.; Khatib, M.; Kahar, P.; Khanna, D. Correlation Between Body Mass Index and Depression/Depression-Like Symptoms Among Different Genders and Races. Cureus 2022, 14, e21841. [Google Scholar] [CrossRef]
  21. Hidese, S.; Asano, S.; Saito, K.; Sasayama, D.; Kunugi, H. Association of Depression with Body Mass Index Classification, Metabolic Disease, and Lifestyle: A Web-Based Survey Involving 11,876 Japanese People. J. Psychiatr. Res. 2018, 102, 23–28. [Google Scholar] [CrossRef] [PubMed]
  22. Myles, D.Y.; Ryan, J.D.; Frances, K.-L.; Clare, E.C.; Robin, C.; Brian, J.K.; Caitlin, B.; Philip, J.M. Supplemental Material for Impact of a Self-Guided, EHealth Program Targeting Weight Loss and Depression in Men: A Randomized Trial. J. Consult. Clin. Psychol. 2021, 89, 682–694. [Google Scholar] [CrossRef]
  23. Grigolon, R.B.; Trevizol, A.P.; Gerchman, F.; Bambokian, A.D.; Magee, T.; McIntyre, R.S.; Gomes, F.A.; Brietzke, E.; Mansur, R.B. Is Obesity A Determinant of Success with Pharmacological Treatment for Depression? A Systematic Review, Meta-Analysis and Meta-Regression. J. Affect. Disord. 2021, 287, 54–68. [Google Scholar] [CrossRef] [PubMed]
  24. Lee, C.A.; Jang, H.D.; Moon, J.E.; Han, S. The Relationship between Change of Weight and Chronic Low Back Pain in Population over 50 Years of Age: A Nationwide Cross-Sectional Study. Int. J. Environ. Res. Public Health 2021, 18, 3969. [Google Scholar] [CrossRef]
  25. Shiri, R.; Karppinen, J.; Leino-Arjas, P.; Solovieva, S.; Viikari-Juntura, E. The Association between Obesity and Low Back Pain: A Meta-Analysis. Am. J. Epidemiol. 2010, 171, 135–154. [Google Scholar] [CrossRef] [Green Version]
  26. Elgaeva, E.E.; Tsepilov, Y.; Freidin, M.B.; Williams, F.M.K.; Aulchenko, Y.; Suri, P. ISSLS Prize in Clinical Science 2020. Examining Causal Effects of Body Mass Index on Back Pain: A Mendelian Randomization Study. Eur. Spine J. 2020, 29, 686–691. [Google Scholar] [CrossRef]
  27. Häuser, W.; Schmutzer, G.; Brähler, E.; Schiltenwolf, M.; Hilbert, A. SPINE SECTION Original Research Articles the Impact of Body Weight and Depression on Low Back Pain in a Representative Population Sample. Pain Med. 2014, 15, 1316–1327. [Google Scholar] [CrossRef] [Green Version]
  28. Suri, P.; Boyko, E.J.; Smith, N.L.; Jarvik, J.G.; Williams, F.M.K.; Jarvik, G.P.; Goldberg, J. Modifiable Risk Factors for Chronic Back Pain: Insights Using the Co-Twin Control Design. Spine J. 2017, 17, 4–14. [Google Scholar] [CrossRef]
  29. Rogers, A.H.; Kauffman, B.Y.; Garey, L.; Asmundson, G.J.; Zvolensky, M.J. Pain-Related Anxiety among Adults with Obesity and Chronic Pain: Relations with Pain, Opioid Misuse, and Mental Health. Behav. Med. 2022, 48, 198–206. [Google Scholar] [CrossRef]
  30. Zheng, S.; Tu, L.; Cicuttini, F.; Zhu, Z.; Han, W.; Antony, B.; Wluka, A.E.; Winzenberg, T.; Aitken, D.; Blizzard, L.; et al. Depression in Patients with Knee Osteoarthritis: Risk Factors and Associations with Joint Symptoms. BMC Musculoskelet. Disord. 2021, 22, 22–40. [Google Scholar] [CrossRef]
  31. Suzuki, F.; Morita, E.; Miyagi, S.; Tsujiguchi, H.; Hara, A.; Nguyen, T.T.T.; Shimizu, Y.; Hayashi, K.; Suzuki, K.; Kannon, T.; et al. Protein Intake in Inhabitants with Regular Exercise Is Associated with Sleep Quality: Results of the Shika Study. PLoS ONE 2021, 16, e0247926. [Google Scholar] [CrossRef] [PubMed]
  32. Nguyen, T.T.T.; Miyagi, S.; Tsujiguchi, H.; Kambayashi, Y.; Hara, A.; Nakamura, H.; Suzuki, K.; Yamada, Y.; Shimizu, Y.; Nakamura, H. Association between Lower Intake of Minerals and Depressive Symptoms among Elderly Japanese Women but Not Men: Findings from Shika Study. Nutrients 2019, 11, 389. [Google Scholar] [CrossRef] [PubMed]
  33. Narukawa, N.; Tsujiguchi, H.; Hara, A.; Miyagi, S.; Kannon, T.; Suzuki, K.; Shimizu, Y.; Nguyen, T.T.T.; Pham, K.O.; Suzuki, F.; et al. Relationship between Vitamin Intake and Health-Related Quality of Life in a Japanese Population: A Cross-Sectional Analysis of the Shika Study. Nutrients 2021, 13, 1023. [Google Scholar] [CrossRef] [PubMed]
  34. Tsujiguchi, H.; Hori, D.; Kambayashi, Y.; Hamagishi, T.; Asakura, H.; Mitoma, J.; Kitaoka, M.; Anyenda, E.O.; Nguyen, T.T.T.; Yamada, Y.; et al. Relationship between Screen Time and Nutrient Intake in Japanese Children and Adolescents: A Cross-Sectional Observational Study. Environ. Health Prev. Med. 2018, 23, 34. [Google Scholar] [CrossRef] [Green Version]
  35. Population of Shika Town (September 2020). Available online: https://www.town.shika.lg.jp/jyuumin/shika_town_pop/reiwa2/shikatown_pop_202009.html (accessed on 9 November 2022).
  36. Shin, C.; Park, M.H.; Lee, S.H.; Ko, Y.H.; Kim, Y.K.; Han, K.M.; Jeong, H.G.; Han, C. Usefulness of the 15-Item Geriatric Depression Scale (GDS-15) for Classifying Minor and Major Depressive Disorders among Community-Dwelling Elders. J. Affect. Disord. 2019, 259, 370–375. [Google Scholar] [CrossRef]
  37. Sugishita, K.; Sugishita, M.; Hemmi, I.; Asada, T.; Tanigawa, T. A Validity and Reliability Study of the Japanese Version of the Geriatric Depression Scale 15 (GDS-15-J). Clin. Gerontol. 2017, 40, 233–240. [Google Scholar] [CrossRef]
  38. Dong, H.J.; Larsson, B.; Levin, L.Å.; Bernfort, L.; Gerdle, B. Is Excess Weight a Burden for Older Adults Who Suffer Chronic Pain? BMC Geriatr. 2018, 18, 270. [Google Scholar] [CrossRef] [Green Version]
  39. Kim, J.; Noh, J.W.; Park, J.; Kwon, Y.D. Body Mass Index and Depressive Symptoms in Older Adults: A Cross-Lagged Panel Analysis. PLoS ONE 2014, 9, e114891. [Google Scholar] [CrossRef] [Green Version]
  40. Brady, S.R.E.; Mamuaya, B.B.; Cicuttini, F.; Wluka, A.E.; Wang, Y.; Hussain, S.M.; Urquhart, D.M. Body Composition Is Associated with Multisite Lower Body Musculoskeletal Pain in a Community-Based Study. J. Pain 2015, 16, 700–706. [Google Scholar] [CrossRef]
  41. Ando, K.; Kobayashi, K.; Nakashima, H.; Machino, M.; Ito, S.; Kanbara, S.; Inoue, T.; Hasegawa, Y.; Imagama, S. Poor Spinal Alignment in Females with Obesity: The Yakumo Study. J. Orthop. 2020, 21, 512–516. [Google Scholar] [CrossRef]
  42. Ray, L.; Lipton, R.B.; Zimmerman, M.E.; Katz, M.J.; Derby, C.A. Mechanisms of Association between Obesity and Chronic Pain in the Elderly. Pain 2011, 152, 53–59. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Ossipov, M.H.; Dussor, G.O.; Porreca, F. Central Modulation of Pain. J. Clin. Investig. 2010, 120, 3779–3787. [Google Scholar] [CrossRef]
  44. Takahashi, A.; Kitamura, K.; Watanabe, Y.; Kobayashi, R.; Saito, T.; Takachi, R.; Kabasawa, K.; Oshiki, R.; Tsugane, S.; Iki, M.; et al. Epidemiological Profiles of Chronic Low Back and Knee Pain in Middle-Aged and Elderly Japanese from the Murakami Cohort. J. Pain Res. 2018, 11, 3161–3169. [Google Scholar] [CrossRef] [Green Version]
  45. Hattori, S. The prevalence of chronic pain in Japan. Nihon Yakurigaku Zasshi. 2006, 127, 176–180. [Google Scholar] [CrossRef] [PubMed]
  46. Arvidsson, S.; Arvidsson, B.; Fridlund, B.; Bergman, S. Health Predicting Factors in a General Population over an Eight-Year Period in Subjects with and without Chronic Musculoskeletal Pain. Health Qual. Life Outcomes 2008, 6, 98. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Weingarten, T.N.; Moeschler, S.M.; Ptaszynski, A.E.; Hooten, W.M.; Beebe, T.J.; Warner, D.O. An Assessment of the Association Between Smoking Status, Pain Intensity, and Functional Interference in Patients with Chronic Pain. Pain Physician 2008, 11, 643–653. [Google Scholar] [CrossRef] [PubMed]
  48. Audet, M.A.; Benedick, A.; Vallier, H.A. Tobacco Smoking Is Associated with More Pain and Worse Functional Outcomes after Torsional Ankle Fracture. OTA Int. 2022, 5, e175. [Google Scholar] [CrossRef]
  49. Aronoff, G. Chronic Pain, Smoking, and Obesity: A Pain Physician’s Perspective on Patient Selection. Pain Med. 2009, 10, 962–965. [Google Scholar] [CrossRef] [Green Version]
  50. Sipowicz, K.; Podlecka, M.; Mokros, Ł.; Pietras, T. Lonely in the City–Sociodemographic Status and Somatic Morbidities as Predictors of Loneliness and Depression among Seniors–Preliminary Results. Int. J. Environ. Res. Public Health 2021, 18, 7213. [Google Scholar] [CrossRef]
  51. Wilson, J.M.; Colebaugh, C.A.; Meints, S.M.; Mikayla Flowers, K.; Edwards, R.R.; Schreiber, K.L. Loneliness and Pain Catastrophizing Among Individuals with Chronic Pain: The Mediating Role of Depression. J. Pain Res. 2022, 15, 2939–2948. [Google Scholar] [CrossRef]
  52. Emerson, K.; Boggero, I.; Ostir, G.; Jayawardhana, J. Pain as a Risk Factor for Loneliness Among Older Adults. J. Aging Health 2018, 30, 1450–1461. [Google Scholar] [CrossRef] [PubMed]
Behavsci 13 00086 g001 550
Figure 1. Participant recruitment chart. Abbreviations: BMI, Body Mass Index; BDHQ, Brief-type self-administered Diet History Questionnaire; GDS, Geriatric Depression Scale.
Figure 1. Participant recruitment chart. Abbreviations: BMI, Body Mass Index; BDHQ, Brief-type self-administered Diet History Questionnaire; GDS, Geriatric Depression Scale.
Behavsci 13 00086 g001
Table
Table 1. Participant characteristics.
Table 1. Participant characteristics.
Male (n = 1003)Female (n = 1213)p-Value a
Age, years, mean (SD)68.728.3669.659.36<0.001
Solitary living, n (%)757.4815012.37<0.001
Education, years, mean (SD)11.403.0210.882.500.006
Exercise/hobbies (without), n (%)59759.5277864.140.026
Smoking history, n (%)28328.22433.54<0.001
BMI, kg/m2, mean (SD)23.402.9622.643.230.064
Treatment for diabetes, n (%)13113.06937.67<0.001
Treatment for hyperlipidemia, n (%)11010.9721717.89<0.001
Treatment for hypertension, n (%)36236.0937130.590.006
DS, n (%)34834.7039432.480.272
Alcohol (crude data), g, mean (SD)19.9225.112.016.29<0.001
Alcohol (density method), % energy, mean (SD)3.814.540.5031.54<0.001
No alcohol intake, n (%)32232.1090674.69<0.001
Alcohol intake, n (%)68167.9030725.31
CP
Any, n (%)737.2813010.720.005
Head, n (%)0-40.3300.090
Neck/shoulder/upper limb, n (%)272.69463.790.149
Lumbar/knee, n (%)565.58947.750.043
Foot, n (%)151.50231.900.470
a For p-values, Student’s t-test was used for mean ± standard deviation, and the chi-square test was used for n numbers and percentages. Abbreviations: SD, standard deviation; BMI, body mass index; DS, depressive symptoms; CP, chronic pain.
Table
Table 2. Characteristics of hypertension and GDS according to sex.
Table 2. Characteristics of hypertension and GDS according to sex.
Without DS(n = 1474)With DS(n = 742)p-Value a
Sex (female), n (%)81955.5639453.100.272
Age, years, mean (SD)68.688.1870.3210.18<0.001
Solitary living, n (%)1359.169012.130.029
Education, years, mean (SD)11.222.8410.912.580.012
Exercise/hobbies (without), n (%)82155.7055474.66<0.001
Smoking history, n (%)21314.4511315.230.625
BMI, kg/ m2, mean (SD)23.113.0022.743.370.001
Treatment for diabetes, n (%)1479.977710.380.766
Treatment for hyperlipidemia, n (%)24916.897810.51<0.001
Treatment for hypertension, n (%)50033.9223331.400.234
Alcohol (crude data), g, mean (SD)10.4319.569.4919.850.288
Alcohol (density method), % energy, mean (SD)2.043.571.933.810.492
No alcohol intake, n (%)79253.7343658.760.025
Alcohol intake, n (%)68246.2730641.24
CP
Any, n (%)1047.069913.34<0.001
Head, n (%)10.0730.400.112
Neck/shoulder/upper limb, n (%)392.65344.580.016
Lumbar/knee, n (%)765.16749.97<0.001
Foot, n (%)191.29192.560.030
a For p-values, Student’s t-test was used for mean ± standard deviation, and the chi-square test was used for n numbers and percentages. Abbreviations: DS, depressive symptoms; SD, standard deviation; BMI, body mass index; CP, chronic pain.
Table
Table 3. Characteristics of body weight and GDS according to sex.
Table 3. Characteristics of body weight and GDS according to sex.
Non-CP (Lumbar/Knee)
(n = 2066)		CP (Lumbar/Knee)
(n = 150)		p-Value a
Sex (female), n (%)111954.169462.670.043
Age, years, mean (SD)68.888.7573.9910.00<0.001
Solitary living, n (%)1999.632617.330.003
Education, years, mean (SD)11.192.7710.112.36<0.001
Exercise/hobbies (without), n (%)127261.5710368.670.084
Smoking history, n (%)29914.472718.000.239
BMI, kg/ m2, mean (SD)22.953.1223.483.330.047
Treatment for diabetes, n (%)20710.021711.330.606
Treatment for hyperlipidemia, n (%)31015.001711.330.221
Treatment for hypertension, n (%)68433.114932.670.912
DS, n (%)66832.337449.33<0.001
Alcohol (crude data), g, mean (SD)10.3119.817.5317.310.062
Alcohol (density method), % energy, mean (SD)2.033.661.583.560.147
No alcohol intake, n (%)113054.709865.330.011
Alcohol intake, n (%)93645.305234.67
CP
Any, n (%)532.57150100.00<0.001
Head, n (%)30.1510.670.245
Neck/shoulder/upper limb, n (%)371.793624.00<0.001
Foot, n (%)120.582617.33<0.001
a For p-values, Student’s t-test was used for mean ± standard deviation, and the chi-square test was used for n numbers and percentages. Abbreviations: SD, standard deviation; BMI, body mass index; DS, depressive symptoms; CP, chronic pain.
Table
Table 4. Breslow–Day test on CP location and DS stratified by BMI.
Table 4. Breslow–Day test on CP location and DS stratified by BMI.
Non-CPCPChi-Square ValueP1P2
n (%)n (%)
BMI < 25AnyNDS1048 (93.9%)68 (6.1%)25.806<0.0010.084
DS490 (86.6%)76 (13.4%)
Neck/shoulder/
upper limb		NDS1089 (97.6%)27 (2.4%)5.8180.0160.523
DS540 (95.4%)26 (4.6%)
Lumber/kneeNDS1069 (95.8%)47 (4.2%)22.225<0.0010.049
DS509 (89.9%)57 (10.1%)
FootNDS1106 (99.1%)10 (0.9%)6.6440.0100.193
DS552 (97.5%)14 (2.5%)
BMI ≥ 25AnyNDS322 (89.9%)36 (10.1%)1.0890.2970.084
DS153 (86.9%)23 (13.1%)
Neck/shoulder/
Upper limb		NDS346 (96.6%)12 (3.4%)0.4660.4950.523
DS168 (95.5%)8 (4.5%)
Lumber/kneeNDS329 (91.9%)29 (8.1%)0.3640.5460.049
DS159 (90.3%)17 (9.7%)
FootNDS349 (97.5%)9 (2.5%)0.0490.8240.193
DS171 (97.2%)5 (2.8%)
P1: Chi-square test, P2: Breslow–Day test. Abbreviations: CP, chronic pain; BMI, body mass index; NDS, non-depressive symptoms; DS, depressive symptoms.
Table
Table 5. Relationship between CP location and DS stratified by BMI.
Table 5. Relationship between CP location and DS stratified by BMI.
AnyNeck/Shoulder/Upper LimbLUMBAR/KNEE
Exp (B)95%CI
(Lower,
Upper)		p-ValueExp (B)95%CI
(Lower,
Upper)		p-ValueExp (B)95%CI
(Lower,
Upper)		p-Value a
BMI < 25
(n = 1682)		Age1.0301.008,
1.052		0.0070.9520.918,
0.987		0.0081.0591.033,
1.086		<0.001
Sex2.2311.411,
3.527		0.0012.1801.030,
4.612		0.0421.7661.054,
2.957		0.031
BMI1.0560.969,
1.151		0.2130.9710.848,
1.112		0.6711.1221.013,
1.243		0.027
Solitary living1.3300.809,
2.186		0.2611.2410.541,
2.849		0.6101.2890.725,
2.292		0.388
Duration of
education		0.9290.857,
1.008		0.0780.8740.771,
0.991		0.0350.9510.865,
1.046		0.304
Exercise/
hobbies (without)		1.0660.722,
1.576		0.7470.8210.457,
1.478		0.5111.1570.724,
1.850		0.541
Smoking
history		1.3880.786,
2.451		0.2591.1060.465,
2.630		0.8201.6070.831,
3.110		0.159
Alcohol
(density method)		1.0410.983,
1.101		0.1681.0520.969,
1.142		0.2240.9970.925,
1.074		0.931
DS2.1911.526,
3.144		<0.0012.0401.156,
3.600		0.0142.1951.437,
3.353		<0.001
Treatment for
diabetes		1.0460.564,
1.942		0.8860.4930.117,
2.075		0.3351.1590.590,
2.279		0.668
Treatment for
hyperlipidemia		0.5580.289,
1.079		0.0830.7630.288,
2.020		0.5860.5840.270,
1.262		0.171
Treatment for
hypertension		0.8160.539,
1.235		0.3360.7760.382,
1.574		0.4820.8080.502,
1.302		0.381
BMI ≥ 25
(n = 534)		Age1.0240.985,
1.065		0.2241.0020.939,
1.070		0.9511.0400.996,
1.086		0.078
Sex1.3820.696,
2.746		0.3551.0810.359,
3.258		0.8901.7070.761,
3.830		0.195
BMI1.0070.886,
1.145		0.9160.8830.682,
1.144		0.3471.0490.913,
1.205		0.501
Solitary living1.6150.716,
3.642		0.2480.5110.064,
4.050		0.5252.1730.932,
5.068		0.072
Duration of
education		0.8740.771,
0.992		0.0370.9550.791,
1.153		0.6340.8930.778,
1.024		0.104
Exercise/
hobbies (without)		0.9740.528,
1.796		0.9331.4050.501,
3.943		0.5180.7610.386,
1.501		0.431
Smoking
history		2.7361.258,
5.952		0.0112.4250.741,
7.940		0.1434.9502.102,
11.656		<0.001
Alcohol
(density method)		1.0080.930,
1.093		0.8450.9910.863,
1.137		0.8921.0090.923,
1.104		0.844
DS1.2530.697,
2.251		0.4511.3480.518,
3.506		0.5411.1450.586,
2.236		0.692
Treatment for
diabetes		1.2600.583,
2.724		0.5561.7230.565,
5.253		0.3390.8980.347,
2.321		0.824
Treatment for
hyperlipidemia		0.9230.436,
1.951		0.8331.8830.623,
5.690		0.2621.0500.456,
2.419		0.908
Treatment for
hypertension		1.0340.575,
1.860		0.9100.8040.300,
2.159		0.6651.0620.549,
2.058		0.857
a Multiple logistic regression analysis. Abbreviations: Exp (B), Exponentiation of the B coefficient; CI, confidence interval; CP, chronic pain; BMI, body mass index; DS, depressive symptoms.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Fukushima, S.; Suzuki, F.; Tsujiguchi, H.; Hara, A.; Miyagi, S.; Kannon, T.; Suzuki, K.; Shimizu, Y.; Nguyen, T.T.T.; Yanagisawa, T.; et al. Relationships among Depressive Symptoms, Body Weight, and Chronic Pain: A Cross-Sectional Analysis of the Shika Study. Behav. Sci. 2023, 13, 86. https://doi.org/10.3390/bs13020086

AMA Style

Fukushima S, Suzuki F, Tsujiguchi H, Hara A, Miyagi S, Kannon T, Suzuki K, Shimizu Y, Nguyen TTT, Yanagisawa T, et al. Relationships among Depressive Symptoms, Body Weight, and Chronic Pain: A Cross-Sectional Analysis of the Shika Study. Behavioral Sciences. 2023; 13(2):86. https://doi.org/10.3390/bs13020086

Chicago/Turabian Style

Fukushima, Shinobu, Fumihiko Suzuki, Hiromasa Tsujiguchi, Akinori Hara, Sakae Miyagi, Takayuki Kannon, Keita Suzuki, Yukari Shimizu, Thao Thi Thu Nguyen, Toru Yanagisawa, and et al. 2023. "Relationships among Depressive Symptoms, Body Weight, and Chronic Pain: A Cross-Sectional Analysis of the Shika Study" Behavioral Sciences 13, no. 2: 86. https://doi.org/10.3390/bs13020086

APA Style

Fukushima, S., Suzuki, F., Tsujiguchi, H., Hara, A., Miyagi, S., Kannon, T., Suzuki, K., Shimizu, Y., Nguyen, T. T. T., Yanagisawa, T., Oku, F., Sato, K., Nakamura, M., Hayashi, K., Shibata, A., Konoshita, T., Kambayashi, Y., Tsuboi, H., Tajima, A., & Nakamura, H. (2023). Relationships among Depressive Symptoms, Body Weight, and Chronic Pain: A Cross-Sectional Analysis of the Shika Study. Behavioral Sciences, 13(2), 86. https://doi.org/10.3390/bs13020086

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop