Uso misto do solo e a caminhada para fins de transporte em idosos: uma abordagem baseada em diferentes métricas do ambiente construído

Salvador, Catharina Cavasin; Lopes, Adalberto Aparecido dos Santos; Saboya, Renato Tibiriçá de; Kanashiro, Milena; d’Orsi, Eleonora

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Scientific Article • urbe, Rev. Bras. Gest. Urbana 16 • 2024 • https://doi.org/10.1590/2175-3369.016.e20220211 copiar

Uso misto do solo e a caminhada para fins de transporte em idosos: uma abordagem baseada em diferentes métricas do ambiente construído

Autoria SCIMAGO INSTITUTIONS RANKINGS

Resumo

A presença de diferentes usos do solo em um bairro tem se mostrado um aspecto importante para promover a caminhada como meio de transporte diário. No entanto, poucos estudos na área aplicaram diferentes estratégias de mensuração para testar seu efeito em modos alternativos de comportamento de viagem, como a caminhada de idosos. Aplicamos seis medidas de uso do solo em duas definições de bairro (buffers de rede de 500 e 1000m) e avaliamos suas associações com a caminhada para fins de transporte em participantes (≥ 60 anos) do estudo EpiFloripa Idoso (2013/14) de Florianópolis, Brasil. Considerando variáveis sociodemográficas e ambientais, as associações ajustadas encontraram uma relação positiva entre quatro medidas e a caminhada. O índice de entropia e três medidas alternativas de intensidade de usos não residenciais associaram-se positivamente com a caminhada para transporte, independentemente da definição de bairro. Associações positivas mais fortes foram observadas ao usar buffers menores e medidas de proporção de usos comerciais, proporção de usos não residenciais e densidade de destinos. Os resultados mostram que medidas alternativas podem superar o índice de entropia, apontando a necessidade de adaptação das métricas e da escala de vizinhança ao contexto geográfico e à faixa etária em análise.

Palavras-chave:
Caminhabilidade; Transporte Ativo; Atividade física; Buffer; Índice de entropia

Variables	Description	Measurement unity	Level	Source
Dependent variable
Walking for transport	Participants were classified through a binary variable in two groups: those that spent at least 10 minutes walking per week to access places such as stores, services, community centers, churches, and friends’ and families’ houses, and those that did not.	Binary: 1 or 0	Individual	International Physical Activity Questionnaire (IPAQ) – EpiFloripa Aging study (2013/14)
Neighbourhood perception (Control)
Commerce	Presence of supermarkets, convenience stores / mini markets / grocery stores, farmers’ markets.	Perception of destinations availability within 15 minutes walking	Individual	Adapted version of the Neighborhood Environment Walkability Scale (NEWS)(*Florindo et al., 2012*Florindo, A. A., Guimarães, V. V., de Farias Júnior, J. C., Salvador, E. P., de Sá, T. H., Reis, R. S., & Hallal, P. C. (2012). Validação de uma escala de percepção do ambiente para a prática de atividade física em adultos de uma região de baixo nível socioeconômico. Revista Brasileira de Cineantropometria e Desempenho Humano, 14(6), 647–659. https://doi.org/10.5007/1980-0037.2012v14n6p647 https://doi.org/10.5007/1980-0037.2012v1... ) – EpiFloripa Aging study (2013/14)
Commerce and services	Presence of stores, bookstores, banks, pharmacies, beauty parlors, barbershops.
Food services	Presence of restaurants, bakeries, snack bars, coffee shops.
Social and health facilites	Presence of health centers or community centers
Neighborhood Variables (Control)
Average Slope	Average of slope values for each neighborhood (buffer).	Percentage (%)	Buffer	Florianópolis digital elevation model (DEM, 2012)
Buffer area	Area of the polygon formed by the buffer, which varies according to its radius and the connectivity of the road network around the residence.	Square kilometers (Km²)	Buffer	Street network (PMF, 2012); EpiFloripa Home Addresses (2013/14)
Average per capita household income	Monthly nominal income of people aged 10 or over considering the average value of the census tracts included in the buffer.	Reais BRL (R$) Income quartiles	Buffer	IBGE Census (2010) Tabular data and census tracts
Independent Variables
Land use balance	Entropy=− $\sum_{i = 1}^{N} ($ pi×ln(pi))/ln(N), where pi is the proportion of land use category i to total land use, and N is the number of land use categories: residential, commercial, services (including buildings with mixed use), institutions (religious and educational) and public services. The reduction to five categories followed previous studies (Frank & Engelke, 2005Frank, L. D., & Engelke, P. (2005). Multiple Impacts of the Built Environment on Public Health: Walkable Places and the Exposure to Air Pollution. International Regional Science Review, 28(2), 193–216. https://doi.org/10.1177/0160017604273853 https://doi.org/10.1177/0160017604273853... ; *Brown et al., 2009Brown, B. B., Yamada, I., Smith, K. R., Zick, C. D., Kowaleski-Jones, L., & Fan, J. X. (2009). Mixed land use and walkability: Variations in land use measures and relationships with BMI, overweight, and obesity. Health and Place, 15(4), 1130–1141. https://doi.org/10.1016/j.healthplace.2009.06.008 https://doi.org/10.1016/j.healthplace.20... ; Christian et al., 2011*Christian, H. E., Bull, F. C., Middleton, N. J., Knuiman, M. W., Divitini, M. L., Hooper, P., Amarasinghe, A., & Giles-Corti, B. (2011). How important is the land use mix measure in understanding walking behaviour? Results from the RESIDE study. International Journal of Behavioral Nutrition and Physical Activity, 8. https://doi.org/10.1186/1479-5868-8-55 https://doi.org/10.1186/1479-5868-8-55... ), excluding categories of non-walkable uses (industrial uses and vacant land).	Continuous variable normalized to values from 0 to 1	Buffer	Land Use data at parcel level (PMF, 2012).
Richness	Number of different land use categories in the buffer, considering nine categories: residential, commercial, industrial, mixed use, parks, services, religious institutions, public service and educational institutions.	1 to 9 land use categories	Buffer	Land Use data at parcel level (PMF, 2012).
Retail Building Coverage Ratio – BCR	Ratio between the sum of the land area occupied by commercial buildings and the sum of the size of the parcels on which the buildings are located, considering all lots with commercial uses that touched the buffer polygon and its total area, regardless of whether they were completely inside the polygon boundary.	∑ commercial buildings area footprint (m²)/∑ commercial lots area (m²)	Buffer	Building footprint and Land Use at parcel level data (PMF, 2012).
Proportion of commercial and residential parcels	The relation between commercial and residential parcels within the buffer.	# commercial parcels/# residential parcels	Buffer	Land Use data at parcel level (PMF, 2012).
Proportion of nonresidential and residential parcels	The relation between nonresidential parcels (commercial, industrial, mixed use, parks, services, religious institutions, public service and educational institutions) and residential parcels within the buffer (Hoek, 2008Hoek, J. W. van den. (2008). The MXI (Mixed-use Index) as Tool for Urban Planning and Analysis. Corporations and Cities: Envsioning Corporate Real Estate in the Urban Future, May, 15. http://www.bk.tudelft.nl/fileadmin/Faculteit/BK/Actueel/Symposia_en_congressen/CRE_2008/Papers/doc/Paper03_vandenHoek.pdf http://www.bk.tudelft.nl/fileadmin/Facul... ).	# nonresidential parcels/# residential parcels
Destination density	Number of parcels with non-residential uses divided by the buffer area.	# nonresidential parcels/Buffer area (km²)

Variables	Categories	Total sample (n=919)		Walking for transport
		Total sample (n=919)		≥ 10 min/week
		n	%	OR	CI95%	p
Walking for transport	0 min/week	276	30,0	-	-	-
Walking for transport	≥10 min/week	643	70,0	-	-	-
Individual Variables
Sex	Female	248	38,6	1
	Male	395	61,4	1,47	1,06-2,04	0,020*
Age (years)	60-74	409	63,6	1
	75-84	207	32,2	0,68	0,48-0,94	0,022*
	≥85	27	4,2	0,49	0,24-0,98	0,045*
Marital Status	Single	279	43,4	1
	Have a partner	364	56,6	1,07	0,77-1,47	0,668
Education (years of study)	No formal education	35	5,4	1
	1-4	210	32,7	1,22	0,66-2,25	0,515
	5-8	111	17,3	1,48	0,75-2,93	0,251
	9-11	106	16,5	2,32	1,13-4,76	0,021*
	≥12	181	28,1	2,15	1,10-4,20	0,025*
Household per capita income (quartile)	R$ 80-723	145	22,6	1
	R$ 724-1,392	157	24,4	1,00	0,65-1,54	0,972
	R$ 1,400-2,900	162	25,2	1,13	0,72-1,76	0,572
	R$ 3,000-23,000	179	27,8	1,43	0,89-2,28	0,134
Type of transport	Own car/motorcycle	322	50,1	1
	Bus	307	47,7	2,85	2,01-4,04	<0,001*
	Walking/Cycling	14	2,2	1,17	0,43-3,20	0,747
Years living at current address	1 - 10	100	15,6	1
Years living at current address	≥11	543	84,4	1,02	0,66-1,58	0,907
Neighbourhood perception†
Commerce	Absent	44	6,8	1
	Present	599	93,2	2,77	1,63-4,70	<0,001*
Commerce and services	Absent	78	12,1	1
Commerce and services	Present	565	87,9	2,05	1,32-3,17	0,001*
Food services	Absent	55	8,6	1,00
	Present	588	91,4	2,73	1,69-4,42	<0,001*
Social and health facilites	Absent	165	25,7	1
Social and health facilites	Present	478	74,3	1,35	0,93-1,96	0,107

Built environment measures	Unit	500m Network Buffer			1000m Network Buffer
Built environment measures	Unit	Mean	SD	Min-Max	Mean	SD	Min-Max
Built environment and sociodemographic
Buffer area	Km2	0,249	0,107	0,026 - 0,512	1,153	0,391	0,355 - 2,167
Average slope (%)	%	10,968	7,034	1,317 - 41,310	12,300	6,622	2,161 - 40,025
Neighborhood income †	Brazilian Real (R$)	1.859,42	813,47	525,87 - 4.561,88	1.887,13	807,71	805,36 - 3.906,94
Land use mix ‡
Land use balance - Entropy	0 - 1	0,214	0,120	0 - 0,512	0,368	0,155	0,087- 0,791
Richnessb	1 - 9	5,15	1,325	1-8	6,20	0,972	3-8
Retail Building Coverage Ratio – BCR (n=909)	commercial buildings area (m²)/commercial lots area (m²)	0,292	0,197	0,005 - 1,165	0,303	0,159	0,010 - 0,927
Proportion of commercial parcels	# commercial parcels/	0,213	0,366	0 - 3,658	0,180	0,237	0,018- 1,247
Proportion of commercial parcels	# residential parcels	0,213	0,366	0 - 3,658	0,180	0,237	0,018- 1,247
Proportion of non-residential parcels	# non-resid. parcels/	0,391	0,717	0 - 6,28	0,323	0,472	0,03 - ,54
Proportion of non-residential parcels	# residential parcels	0,391	0,717	0 - 6,28	0,323	0,472	0,03 - ,54
Destination density	# non-resid. parcels/	229,968	218,16	0 - 1.217,82	178,993	166,010	15,695 - 766,060
Destination density	buffer area (km²)	229,968	218,16	0 - 1.217,82	178,993	166,010	15,695 - 766,060

Spearman Correlation Coefficient	500-m Network Buffer					1000-m Network Buffer
Spearman Correlation Coefficient	1	2	3	4	5	1	2	3	4	5
1.Entropy	1,00					1,00
2. Retail BCR	0,12*	1,00				0,24*	1,00
3.Richness	0,53*	0,21*	1,00			0,26*	-0,02	1,00
4.Commercial Proportion	0,82*	-0,002	0,24*	1,00		0,91*	0,16*	0,04	1,00
5.Non-residential Prop.	0,94^* * p < 0,05; 4. Commercial Proportion is represented by the Proportion of commercial and residences.	0,06	0,39*	0,95*	1,00	0,99*	0,22*	0,22*	0,94*	1,00
6.Destination Density	0,81*	0,26*	0,65*	0,68*	0,77*	0,77*	0,39*	0,44*	0,60*	0,75*

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[1] CCS is Architect and Urbanist, MSc. in Architecture and Urbanism, PhD student, e-mail: catharinacavasin@gmail.com AASL is Research Assistant, PhD in Physical Activity & Health and Geoprocessing Specialist, e-mail: aadalberto@hotmail.com RTS is Architect and Urbanist, Associate Professor, PhD in Civil Engineering, e-mail: renato.saboya@ufsc.br MK is Architect and Urbanist, Associate Professor, PhD in Environmental and Development, e-mail: milena@uel.br ED’O, Titular professor, Medicine, PhD in Epidemiology and Quantitative Methods in Health, e-mail: eleonora.dorsi@ufsc.br