Neighborhood Beauty and the Brain in Older Japanese Adults
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Participants
2.2. Brain Imaging Measures
2.3. Subjective Neighborhood Beauty
2.4. Objective Neighborhood Indicators (Green Spaces, Blue Spaces, and Plant Diversity)
2.5. Covariates
2.6. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Thompson, C.W. Linking landscape and health: The recurring theme. Landsc. Urban Plan. 2011, 99, 187–195. [Google Scholar] [CrossRef]
- Vanaken, G.J.; Danckaerts, M. Impact of Green Space Exposure on Children’s and Adolescents’ Mental Health: A Systematic Review. Int. J. Environ. Res. Public Health 2018, 15, 2668. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Yuan, Y.; Huang, F.; Lin, F.; Zhu, P.; Zhu, P. Green space exposure on mortality and cardiovascular outcomes in older adults: A systematic review and meta-analysis of observational studies. Aging Clin. Exp. Res. 2020, 33, 1783–1797. [Google Scholar] [CrossRef] [PubMed]
- Wendelboe-Nelson, C.; Kelly, S.; Kennedy, M.; Cherrie, J.W. A Scoping Review Mapping Research on Green Space and Associated Mental Health Benefits. Int. J. Environ. Res. Public Health 2019, 16, 2081. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kawabata, H.; Zeki, S. Neural correlates of beauty. J. Neurophysiol. 2004, 91, 1699–1705. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Di Dio, C.; Macaluso, E.; Rizzolatti, G. The golden beauty: Brain response to classical and renaissance sculptures. PLoS ONE 2007, 2, e1201. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zaidel, D.W. Neuroesthetics is Not Just about Art. Front. Hum. Neurosci. 2015, 9, 80. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ishizu, T.; Zeki, S. Toward a brain-based theory of beauty. PLoS ONE 2011, 6, e21852. [Google Scholar] [CrossRef] [Green Version]
- Ishizu, T.; Zeki, S. The brain’s specialized systems for aesthetic and perceptual judgment. Eur. J. Neurosci. 2013, 37, 1413–1420. [Google Scholar] [CrossRef] [Green Version]
- Tsukiura, T.; Cabeza, R. Shared brain activity for aesthetic and moral judgments: Implications for the Beauty-is-Good stereotype. Soc. Cogn. Affect. Neurosci. 2011, 6, 138–148. [Google Scholar] [CrossRef]
- Shobugawa, Y.; Murayama, H.; Fujiwara, T.; Inoue, S. Cohort Profile of the NEIGE Study in Tokamachi City, Japan. J. Epidemiol. 2020, 30, 281–287. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tamiya, N.; Noguchi, H.; Nishi, A.; Reich, M.R.; Ikegami, N.; Hashimoto, H.; Shibuya, K.; Kawachi, I.; Campbell, J.C. Population ageing and wellbeing: Lessons from Japan’s long-term care insurance policy. Lancet 2011, 378, 1183–1192. [Google Scholar] [CrossRef] [PubMed]
- Niigata Prefectural Tokamachi Hospital. List of Main Equipment. Available online: http://www.tokamachi-hosp-niigata.jp/section/radiation.html (accessed on 26 December 2022).
- Fischl, B. FreeSurfer. Neuroimage 2012, 62, 774–781. [Google Scholar] [CrossRef] [Green Version]
- Deutsch, D.; Sainani, K.L. Q&A: David Deutsch. Objective beauty. Nature 2015, 526, S16. [Google Scholar] [PubMed]
- Gardiner, J. Fibonacci, quasicrystals and the beauty of flowers. Plant Signal. Behav. 2012, 7, 1721–1723. [Google Scholar] [CrossRef] [Green Version]
- Atiyeh, B.S.; Hayek, S.N. Numeric expression of aesthetics and beauty. Aesthetic Plast. Surg. 2008, 32, 209–216; discussion 217–219. [Google Scholar] [CrossRef] [PubMed]
- Tucker, C.J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 1979, 8, 127–150. [Google Scholar] [CrossRef] [Green Version]
- Ministry of the Environment Biodiversity Center of Japan. Available online: http://www.biodic.go.jp/index_e.html (accessed on 22 June 2021).
- Tokamachi Tourist Association TANADA-Rice Field Terraces. Available online: https://www.tokamachishikankou.jp/en/special/special-tanada/ (accessed on 2 September 2021).
- Simpson, E.H. Measurement of diversity. Nature 1949, 163, 688. [Google Scholar] [CrossRef]
- Kringelbach, M.L. The human orbitofrontal cortex: Linking reward to hedonic experience. Nat. Rev. Neurosci. 2005, 6, 691–702. [Google Scholar] [CrossRef]
- Grabenhorst, F.; Rolls, E.T. Value, pleasure and choice in the ventral prefrontal cortex. Trends Cogn Sci 2011, 15, 56–67. [Google Scholar] [CrossRef]
- Kühn, S.; Gallinat, J. The neural correlates of subjective pleasantness. Neuroimage 2012, 61, 289–294. [Google Scholar] [CrossRef] [PubMed]
- Craig, A.D. How do you feel—Now? The anterior insula and human awareness. Nat. Rev. Neurosci. 2009, 10, 59–70. [Google Scholar] [CrossRef]
- Critchley, H.D.; Harrison, N.A. Visceral influences on brain and behavior. Neuron 2013, 77, 624–638. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lewis, G.J.; Kanai, R.; Rees, G.; Bates, T.C. Neural correlates of the ‘good life’: Eudaimonic well-being is associated with insular cortex volume. Soc. Cogn. Affect. Neurosci. 2014, 9, 615–618. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Armstrong, N.M.; An, Y.; Shin, J.J.; Williams, O.A.; Doshi, J.; Erus, G.; Davatzikos, C.; Ferrucci, L.; Beason-Held, L.L.; Resnick, S.M. Associations between cognitive and brain volume changes in cognitively normal older adults. Neuroimage 2020, 223, 117289. [Google Scholar] [CrossRef]
- Qing, Z.; Gong, G. Size matters to function: Brain volume correlates with intrinsic brain activity across healthy individuals. Neuroimage 2016, 139, 271–278. [Google Scholar] [CrossRef]
- Raz, N.; Rodrigue, K.M. Differential aging of the brain: Patterns, cognitive correlates and modifiers. Neurosci. Biobehav. Rev. 2006, 30, 730–748. [Google Scholar] [CrossRef]
- Pettemeridou, E.; Kallousia, E.; Constantinidou, F. Regional Brain Volume, Brain Reserve and MMSE Performance in Healthy Aging From the NEUROAGE Cohort: Contributions of Sex, Education, and Depression Symptoms. Front. Aging Neurosci. 2021, 13, 711301. [Google Scholar] [CrossRef]
- Gourley, S.L.; Zimmermann, K.S.; Allen, A.G.; Taylor, J.R. The Medial Orbitofrontal Cortex Regulates Sensitivity to Outcome Value. J. Neurosci. 2016, 36, 4600–4613. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Dadvand, P.; Pujol, J.; Macià, D.; Martínez-Vilavella, G.; Blanco-Hinojo, L.; Mortamais, M.; Alvarez-Pedrerol, M.; Fenoll, R.; Esnaola, M.; Dalmau-Bueno, A.; et al. The Association between Lifelong Greenspace Exposure and 3-Dimensional Brain Magnetic Resonance Imaging in Barcelona Schoolchildren. Environ. Health Perspect. 2018, 126, 027012. [Google Scholar] [CrossRef]
- Bratman, G.N.; Hamilton, J.P.; Hahn, K.S.; Daily, G.C.; Gross, J.J. Nature experience reduces rumination and subgenual prefrontal cortex activation. Proc. Natl. Acad. Sci. USA 2015, 112, 8567–8572. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tokamachi Tourist Association Japan Niigata Tokamachi City. Available online: https://www.tokamachishikankou.jp/en/spot/category/view-en/ (accessed on 22 June 2021).
- Brandt, K. Kingdom of Beauty: Mingei and the Politics of Folk Art in Imperial Japan; Duke University Press: Durham, NC, USA, 2007. [Google Scholar]
- Na, K.S.; Ham, B.J.; Lee, M.S.; Kim, L.; Kim, Y.K.; Lee, H.J.; Yoon, H.K. Decreased gray matter volume of the medial orbitofrontal cortex in panic disorder with agoraphobia: A preliminary study. Prog. Neuropsychopharmacol. Biol. Psychiatry 2013, 45, 195–200. [Google Scholar] [CrossRef] [PubMed]
- Wang, Y.M.; Zou, L.Q.; Xie, W.L.; Yang, Z.Y.; Zhu, X.Z.; Cheung, E.F.C.; Sørensen, T.A.; Møller, A.; Chan, R.C.K. Altered grey matter volume and cortical thickness in patients with schizo-obsessive comorbidity. Psychiatry Res. Neuroimaging 2018, 276, 65–72. [Google Scholar] [CrossRef] [PubMed]
- Lee, B.; Bennett, L.L.; Bernick, C.; Shan, G.; Banks, S.J. The Relations Among Depression, Cognition, and Brain Volume in Professional Boxers: A Preliminary Examination Using Brief Clinical Measures. J. Head Trauma Rehabil. 2019, 34, E29–E39. [Google Scholar] [CrossRef] [PubMed]
- Grieve, S.M.; Korgaonkar, M.S.; Koslow, S.H.; Gordon, E.; Williams, L.M. Widespread reductions in gray matter volume in depression. Neuroimage Clin. 2013, 3, 332–339. [Google Scholar] [CrossRef] [Green Version]
- Sprengelmeyer, R.; Steele, J.D.; Mwangi, B.; Kumar, P.; Christmas, D.; Milders, M.; Matthews, K. The insular cortex and the neuroanatomy of major depression. J. Affect. Disord. 2011, 133, 120–127. [Google Scholar] [CrossRef]
Total | Subjective Environmental Beauty | ||||||
---|---|---|---|---|---|---|---|
Low | Moderately Low | Moderately High | High | p Value a | |||
n = 476 | n = 81 | n = 95 | n = 100 | n = 200 | |||
n | % | % | % | % | % | ||
Age (years) | |||||||
65–69 | 153 | 32.1 | 23.5 | 38.9 | 34.0 | 31.5 | 0.45 |
70–74 | 129 | 27.1 | 25.9 | 29.5 | 23.0 | 28.5 | |
75–79 | 109 | 22.9 | 28.4 | 16.8 | 23.0 | 23.5 | |
≥80 | 85 | 17.9 | 22.2 | 14.7 | 20.0 | 16.5 | |
Sex | |||||||
Male | 230 | 48.3 | 50.6 | 44.2 | 53.0 | 47.0 | 0.61 |
Female | 246 | 51.7 | 49.4 | 55.8 | 47.0 | 53.0 | |
Education (years) | |||||||
Low (≤9) | 178 | 37.4 | 38.3 | 27.4 | 34.0 | 43.5 | 0.13 |
Moderate (10–12) | 203 | 42.6 | 37.0 | 49.5 | 45.0 | 40.5 | |
High (≥13) | 95 | 20.0 | 24.7 | 23.2 | 21.0 | 16.0 | |
Annual income (million yen) | |||||||
Low (<2.00) | 190 | 39.9 | 44.4 | 34.7 | 35.0 | 43.0 | 0.06 |
Moderate (2.00–3.99) | 206 | 43.3 | 42.0 | 44.2 | 46.0 | 42.0 | |
High (≥4.00) | 51 | 10.7 | 3.7 | 17.9 | 10.0 | 10.5 | |
Missing | 29 | 6.1 | 9.9 | 3.2 | 9.0 | 4.5 | |
Marital status | |||||||
Married | 387 | 81.3 | 82.7 | 82.1 | 74.0 | 84.0 | 0.70 |
Widowed | 73 | 15.3 | 13.6 | 14.7 | 20.0 | 14.0 | |
Divorced | 9 | 1.9 | 2.5 | 2.1 | 3.0 | 1.0 | |
Not married | 7 | 1.5 | 1.2 | 1.1 | 3.0 | 1.0 | |
Age first lived in current location | |||||||
≤15 years old | 182 | 38.2 | 43.2 | 33.7 | 39.0 | 38.0 | 0.09 |
16–24 years old | 153 | 32.1 | 23.5 | 31.6 | 28.0 | 38.0 | |
25–39 years old | 93 | 19.5 | 19.8 | 25.3 | 26.0 | 13.5 | |
≥40 years old | 48 | 10.1 | 13.6 | 9.5 | 7.0 | 10.5 | |
Residential area | |||||||
Matsunoyama (mountain) | 174 | 36.6 | 25.9 | 15.8 | 30.0 | 54.0 | <0.001 |
Central Tokamachi (downtown) | 302 | 63.4 | 74.1 | 84.2 | 70.0 | 46.0 | |
Childhood exposure to neighborhood nature | |||||||
High | 389 | 81.7 | 71.6 | 66.3 | 85.0 | 91.5 | <0.001 |
Moderately high | 45 | 9.5 | 4.9 | 17.9 | 12.0 | 6.0 | |
Medium | 18 | 3.8 | 7.4 | 5.3 | 2.0 | 2.5 | |
Moderately low | 18 | 3.8 | 12.3 | 7.4 | 1.0 | 0.0 | |
Low | 6 | 1.3 | 3.7 | 3.2 | 0.0 | 0.0 |
Neighborhood Variables | Mean | SD | Median | Min | Max | 1 | 2 | 3 | 4 | 5 | |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | Subjective beauty (range: 1–4) | 2.88 | 1.14 | 3 | 1 | 4 | 1.00 | ||||
2 | Objective green space (NDVI, range: −1 to 1) | 0.34 | 0.11 | 0.37 | 0.19 | 0.48 | 0.31 | 1.00 | |||
3 | Objective blue space (km2) | 0.029 | 0.038 | 0.024 | 0 | 0.32 | −0.13 | −0.33 | 1.00 | ||
4 | Objective blue space including paddy fields (km2) | 0.65 | 0.43 | 0.62 | 0 | 1.94 | 0.28 | 0.59 | −0.05 | 1.00 | |
5 | Objective plant diversity (range: 0–1) | 0.60 | 0.18 | 0.67 | 0.31 | 0.85 | 0.29 | 0.83 | −0.29 | 0.61 | 1.00 |
mOFC (mm3) | Insula (mm3) | |||
---|---|---|---|---|
Left | Right | Left | Right | |
Coef. (95% CI) | Coef. (95% CI) | Coef. (95% CI) | Coef. (95% CI) | |
Model 1 | ||||
Subjective beauty | ||||
Low | referent | referent | referent | referent |
Middle-low | 211 (69 to 354) | 129 (−8.1 to 266) | 127 (−32 to 286) | 173 (−4.9 to 352) |
Middle-high | 232 (91 to 373) | 143 (7.7 to 279) | 222 (65 to 379) | 253 (76 to 429) |
High | 242 (118 to 366) | 166 (47 to 286) | 218 (79 to 356) | 317 (162 to 472) |
p for trend | 0.001 | 0.01 | 0.002 | <0.0001 |
Model 2 | ||||
Subjective beauty | ||||
Low | referent | referent | referent | referent |
Middle-low | 155 (14 to 296) | 89 (−50 to 227) | 110 (−53 to 273) | 118 (−63 to 298) |
Middle-high | 205 (67 to 342) | 134 (−1.2 to 268) | 219 (60 to 378) | 227 (51 to 403) |
High | 204 (82 to 326) | 148 (28 to 268) | 210 (69 to 351) | 294 (137 to 450) |
p for trend | 0.003 | 0.02 | 0.003 | <0.0001 |
Model 3 | ||||
Subjective beauty | ||||
Low | referent | referent | referent | referent |
Middle-low | 158 (15 to 301) | 90 (−50 to 230) | 112 (−54 to 277) | 125 (−58 to 308) |
Middle-high | 207 (66 to 349) | 117 (−21 to 255) | 215 (52 to 379) | 232 (51 to 413) |
High | 202 (73 to 331) | 126 (0.4 to 252) | 203 (54 to 352) | 295 (130 to 460) |
p for trend | 0.005 | 0.07 | 0.007 | <0.0001 |
Objective Neighborhood Variables | mOFC (mm3) | Insula (mm3) | ||
---|---|---|---|---|
Left | Right | Left | Right | |
Coef. (95% CI) | Coef. (95% CI) | Coef. (95% CI) | Coef. (95% CI) | |
Model 1 | ||||
Green space (NDVI, −1 to 1) | 37 (−349 to 424) | 203 (−165 to 572) | 211 (−217 to 640) | 264 (−220 to 747) |
p value | 0.85 | 0.28 | 0.33 | 0.28 |
Blue space (km2) | −561 (−1712 to 590) | −986 (−2081 to 110) | −44 (−1321 to 1234) | −644 (−2084 to 797) |
p value | 0.34 | 0.08 | 0.95 | 0.38 |
Blue space including paddy fields (km2) | −55 (−157 to 46) | −30 (−126 to 67) | 74 (−38 to 186) | 58 (−68 to 185) |
p value | 0.28 | 0.55 | 0.20 | 0.37 |
Species diversity index (0–1) | 47 (−203 to 297) | 105 (−134 to 344) | 95 (−184 to 373) | 99 (−214 to 413) |
p value | 0.71 | 0.39 | 0.50 | 0.53 |
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Tani, Y.; Fujiwara, T.; Sugihara, G.; Hanazato, M.; Suzuki, N.; Machida, M.; Amagasa, S.; Murayama, H.; Inoue, S.; Shobugawa, Y. Neighborhood Beauty and the Brain in Older Japanese Adults. Int. J. Environ. Res. Public Health 2023, 20, 679. https://doi.org/10.3390/ijerph20010679
Tani Y, Fujiwara T, Sugihara G, Hanazato M, Suzuki N, Machida M, Amagasa S, Murayama H, Inoue S, Shobugawa Y. Neighborhood Beauty and the Brain in Older Japanese Adults. International Journal of Environmental Research and Public Health. 2023; 20(1):679. https://doi.org/10.3390/ijerph20010679
Chicago/Turabian StyleTani, Yukako, Takeo Fujiwara, Genichi Sugihara, Masamichi Hanazato, Norimichi Suzuki, Masaki Machida, Shiho Amagasa, Hiroshi Murayama, Shigeru Inoue, and Yugo Shobugawa. 2023. "Neighborhood Beauty and the Brain in Older Japanese Adults" International Journal of Environmental Research and Public Health 20, no. 1: 679. https://doi.org/10.3390/ijerph20010679