Multi-Family Housing Environment and Physical Activity: A Systematic Review of the Literature

Abstract

Objective

To identify environmental features of multi-family housing (MFH) and their surrounding neighborhoods that influence residents’ physical activity (PA).

Data Source

Articles published between January 2000 and September 2023 were identified from major social science, medical, health, behavioral science, and urban studies databases.

Study Inclusion and Exclusion Criteria

Studies were included if they (a) were empirical studies published in peer-reviewed journals and written in English; (b) focused on the MFH environment or the surrounding neighborhood; and (c) had at least one PA outcome.

Data Extraction

Data was extracted regarding the study objective, location, study sample, research design, results related to MFH and neighborhood environment, and limitations.

Data Synthesis

Descriptive summary of study characteristics and analysis to identify emerging themes at three spatial scales (i.e., building, site, and neighborhood).

Results

Findings from 35 identified articles revealed factors influencing MFH residents’ PA. On the building level, typology (apartment, townhouse) and tenure (public, market rent) showed contrasting correlations with PA in different age groups. On the site level, the presence of PA facilities and safe, walking-friendly environments promoted PA. On the neighborhood level, safety, quality of PA and pedestrian infrastructure, upkeep, air quality, aesthetics, neighborhood satisfaction, street connectivity, walkability, land use mix, density, and public transport promoted PA.

Conclusion

Study findings highlight the importance of the MFH environments in promoting PA, especially in older adults and young children. With increasing housing demand, understanding diverse MFH typologies and the impact of interventions on multi-spatial scales can help promote healthy and activity-friendly communities.

Objective

Lack of physical activity (PA) is a leading public health problem in many countries. In the U.S., 25% of adults do not engage in sufficient PA to maintain their health. ¹ Globally, 81% of adolescents and 27.5% of adults fall short of the World Health Organization’s recommended PA levels. ² This deficiency not only impacts individuals and their families throughout their lifespan but also places a significant burden on health services and society as a whole.

The general influence of housing and neighborhood environment on residents’ PA is well established.^3-5 Notably, a previous systematic review ⁶ has highlighted the strong association between neighborhood environments and PA, urging for a closer examination of environmental factors within various residential settings. Factors such as pedestrian-friendly streets, access to green spaces and parks, availability and access to recreational facilities, proximity to public transit, higher residential density, and safety from crime and traffic are some of the environmental factors that promote peoples’ PA.^4,7,8 Understanding these dynamics is essential for crafting evidence-based policies and interventions that foster healthier lifestyles and contribute to the overall well-being of communities. However, previous studies have focused more on single-family housing. In contrast, not enough studies have examined the environmental features of multi-family housing (MFH) and their surrounding neighborhoods.

Considering the increasing housing demand, MFH is a potentially equitable and sustainable solution for affordable housing.^9-11 Approximately 24.75% of housing units in the U.S. are categorized as multi-family. ¹² Furthermore, the global market for MFH construction has exhibited sustained expansion in recent periods, with robust growth projected for forthcoming years. ¹³ The examination of physical environmental factors in MFH and their influences on residents’ PA is a critical area of study with profound implications for public health, urban planning, and housing design. Hence, understanding the MFH environment and its impact on population health, including residents’ PA, is essential.

As in other building types, the design and layout of residential environments vary depending on the specific type of housing arrangement. MFH is typically significantly different from single-family housing in terms of design, density, space hierarchy, and the availability of spaces.^14,15 Further variations also exist within MFH based on the typology. For example, townhomes and condominiums sometimes have a fenced-in yard, as compared to duplexes and fourplexes that have a shared yard, or apartments with outdoor spaces that are shared by more households. In general, MFHs have three spatial scales: (1) building level, which includes the individual units, the building that these units are located in, and sometimes a private yard; (2) site level, which includes the immediate outdoor surroundings that are within the property limits but shared with other residents; and (3) neighborhood level that is outside the property limits but within the neighborhood area.

The primary aim of this study is to systematically review previous studies that examined the impacts of MFH environments (built and natural) and their surrounding neighborhoods on residents’ PA. It explores (1) the correlations between housing and neighborhood environments of MFH and residents’ PA, and (2) the impacts of personal and social factors on MFH residents’ PA. At the end of the review, we discuss the importance of MFH environments and their crucial role in promoting health and healthy behaviors in its residents.

Methods

This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, which outlined a four-phase flow diagram (Figure 1). ¹⁶ The search time frame ranged from January 2000 to September 2023. The year 2000 was selected because there was a push towards understanding the influence of the built environment on lifestyle PA, marked by programs such as the Healthy People 2000 ¹⁷ by the CDC, and the establishment of the Active Living Research program ¹⁸ by Robert Wood Johnson Foundation. The search process concluded in September of 2023.

Figure 1.

PRISMA flow diagram showing the process of literature review. ¹⁶

The study team consisted of three researchers. Two lead researchers first reviewed three randomly selected articles to reach inter-rater agreements in their understanding of the screening criteria, study quality assessment tool, and data extraction process; a third researcher was involved to discuss and resolve conflicts in case of inconsistencies between the two reviewers. These two lead researchers also independently assessed the study quality of all identified articles using a standard quality assessment tool. More detailed data extraction for each article was conducted by one of the two lead researchers after they had reached inter-rater agreements.

Data Sources and Keywords

We searched for original studies that reported the impacts of MFH and its surrounding neighborhood environment on residents’ PA. Various keyword combinations were used to search online databases in the domains of (1) general health and PA - Web of Science, PubMED, Embase (OVID), CINAHL Ultimate, Academic Search Ultimate, Medline, Medline Ultimate; (2) health and PA in children - ERIC, Child Development and Adolescent Studies; (3) health and PA in older adults - AgeLine, Abstracts in Social Gerontology; (4) health and sports - Alt HealthWatch, SPORTDiscus; (5) healthy behavior - APA PsycInfo, Psychology and Behavioral Sciences Collection; and (6) environment and transportation - Environment Complete, Urban Studies Abstracts, Transport Research Information Services-TRIS. Studies with people of all ages were included. Search terms for MFH included “multi-family,” “apartment,” “flat,” “townhouse/townhome,” “terraced housing,” “condominium,” “duplex,” and “fourplex.” Keywords related to housing tenure included “public housing,” “social housing,” “cooperative housing,” and “affordable housing.” For environment, “neighborhood,” “built environment,” “natural environment,” “nature,” “greenery,” “green space,” or “outdoor space” were used. Finally for PA, “physical activity,” “MVPA,” “walking,” “biking,” “cycling,” “exercise,” “active living,” “sports,” or “physical fitness” were used. Literature review articles and citation and reference lists of the identified articles were also reviewed for additional relevant studies.

Inclusion and Exclusion Criteria

The screening process involved reviewing titles, abstracts, and full text using Covidence – a web-based application that supports a collaborative systematic literature review. ¹⁹ Studies were eligible for inclusion in the final data extraction if they were (1) published in peer-reviewed journals; (2) written in English; (3) empirical studies; (4) focused on populations living in MFH; (5) focused on the built/natural environmental factors of MFH or its surrounding neighborhood; and (6) had at least one PA outcome.

Data Extraction and Synthesis

Data were extracted from the identified articles using a template that included: (1) study title; (2) study objective(s); (3) research design (e.g., observational, natural experimental, pre-post intervention); (4) intervention details whenever applicable (e.g., type of intervention, duration, assessment time) (5) study location(s); (5) sample size and type; (6) study timeline; (7) data collection and analysis methods; (8) MFH (building and site) factors; (9) MFH type discussed in the study (e.g., apartment/flat, townhouse/townhome/terraced house, duplex, triplex, fourplex, condominium, row housing); (10) other MFH attributes(e.g., public housing, affordable housing, social housing, cooperative housing, commodity housing, intermediate housing [including affordable rent, shared ownership, and shared equity], market-rent housing); (11) neighborhood factors; (12) sociodemographic factors; (13) association between each independent/confounding variable and the dependent variable and their significance; and (14) conclusions and study limitations. The findings from the extracted studies were further reviewed and synthesized to provide summaries related to MFH and its neighborhood environment and their impact on residents’ PA. Three spatial scales, building, site, and neighborhood were used to organize the findings as each spatial scale provides distinctive opportunities in understanding the built environment and its impact on PA outcomes. A summary of key results is presented under each spatial scale to provide relevant details.

Study Quality Assessments

The Joanna Briggs Institute (JBI) Critical Appraisal Tool for cross-sectional studies ²⁰ was used to assess the methodological quality of the study and determine the extent to which the study has addressed the possibility of bias in its design, implementation, and analysis. The appraisal checklist consists of seven questions regarding (1) well-defined inclusion criteria, (2) clear descriptions of study settings and samples, (3) outcome measure validity and reliability, (4) use of objective and standard measures of independent variables, (5) identifying confounding variables, (6) strategies used to deal with confounders, and (7) use of appropriate statistical analysis methods.

Results

The initial search yielded 1070 records, from which 578 were retained after excluding duplicates. After the screening process, 23 articles were identified for final data extraction. An additional 12 articles were added after reviewing reference lists of the retained studies, bringing the total number of studies ready for data extraction to 35 (Figure 1). We report findings from 35 studies about their study sample and design, study quality, PA-related outcome variables, MFH and neighborhood factors, any significant associations between the environmental and PA outcomes, and the sociodemographic confounders.

Study Design, Time, and Quality

Of the 35 studies, 83% (n = 30) used a cross-sectional study design. The remaining 17% included four natural experiment studies and one pre-post intervention design. In terms of years of publication (Figure 2), the distribution is consistent between 2006 and 2023 except for the 2018 – 2020 year range, which has the highest number (n = 11) of relevant studies.

Figure 2.

Number of reviewed studies by year of publication.

Study Setting and Sample

Studies identified were from across the world (Figure 3). The country with the highest number of studies (16 studies) is the U.S., followed by China (5 studies), Singapore (4 studies), UK (3 studies), and other countries.

Figure 3.

Number of studies included by study locations.

Study samples included individual residents such as older adults, adults, and children as well as others such as individual trips (Figure 4). Of the studies with individual resident participants, twenty studies included adults (average sample size = 1967, range = 11 to 26 767)^21-40; twelve studies included older adults (average sample size = 1644, range = 26 to 13 468)^41-52; and two studies included children (average sample size = 1122, range = 422 to 1822).^53,54 Of the twelve studies with older adult participants, one study ⁴⁶ also had a qualitative component that examined 820 photographs of the built environment. Additionally, one study used individual trips as the unit of analysis (sample size = 223,232). ⁵⁵

Figure 4.

Sample type and size by number of studies.

Outcome Measures

PA was measured objectively or through subjective self-report. Objective measures used included the Actigraph GT3X + accelerometer (n = 5)^{22,30,38,39,51} and pedometers (n = 2).^21,28 Self-reported subjective measures included surveys (n = 24),^21-53,55 interviews (n = 11),^{29,34,35,41,42,44-46,49,50,52} and focus groups (n = 3).^37,43,49 Survey instruments included International Physical Activity Questionnaire (IPAQ) (n = 8),^{22,23,28,31,34,36,40,42} Global Physical Activity Questionnaire (GPAQ), ³³ Recent Physical Activity Questionnaire (RPAQ), ³³ 7-day activity diary, ⁵⁴ 2-items about walking from the National Health Interview Survey, ²⁴ PA measures from the Behavioral Risk Factor Surveillance System, ²⁵ Transportation Tomorrow Survey, ⁵⁵ Canada National Household Survey, ⁵⁵ and the Hong Kong Travel Characteristics Survey.^29,52

The PA outcomes examined can be classified based on purpose, PA type, and measure. In terms of the purpose of PA, one study looked at recreational PA, ⁵³ seven studies examined transportation-related PA,^{22,25-27,44,52,55} two studies examined recreation- and transportation-related PA,^40,42 one study examined work-, recreation-, and transportation-related PA, ³³ while the other twenty-four studies examined PA for all purposes. Types of PA examined included walking^{22,24-42,44,48,50,52,55}; biking^26,27,33,55; outdoor play in children^33,53; climbing stairs^33,37; exercises such as yoga, aerobics, cardio, strength training, dance, and physical therapy^37,43,48; and playing sports such as swimming, golf, shuffleboard, bowling, and others.^34,46,48 Measures of PA varied based on the type. Walking was captured as mean steps per day,^{21,28,30,38,39} minutes per day of walking in a typical week,^{22,24,25,28,29,31,33,40,42,52} number of walking trips per week,^26,27,52 odds and frequency of walking,^{29,38,44,52,55} and participation.^41,48 Biking/cycling measures included the number and percentage of biking trips.^26,27,33,55 Sports, outdoor play, and other forms of exercise were measured using participation,^{35,37,41,43,48} minutes per week of the reported activity,^33,53 and weekly frequency. ⁴⁷ Intensity of PA was measured using minutes of moderate and vigorous PA (MVPA),^{22-24,28,30,32,34,36,38,42,51,54} and percentage of residents meeting MVPA guidelines of at least 75 minutes per week of vigorous PA (VPA) or 150 minutes per week of moderate PA (MPA), or an equivalent combination.^24,25 Finally, three studies measured total weekly minutes of PA,^28,31,45 and one study examined the weekly frequency of MPA. ³²

Sedentary behaviors (SB) were examined in four studies.^33,34,36,39 Sitting was the primary SB, captured as the number of driving trips,^26,27 minutes per week of sitting, ³³ and daily sedentary minutes in a typical week. ³⁹ Secondary outcomes impacted by PA were also measured such as body-mass index (BMI) (n = 3),^30,33,36 fat mass percentage (n = 1), ³⁹ obesity (n = 1), ³² waist-hip circumference ratio (WHR) change (n = 1), ³³ and social interaction (n = 1). ⁵⁰

Physical Environmental Factors as Independent Variables

The physical environmental factors examined in the reviewed studies are categorized into three spatial scales, including building, site, and neighborhood scales as defined previously. At the building level, factors related to MFH typology, tenure, and design were identified. At the site level, presence and maintenance of PA amenities were reported as significant correlates of PA. At the neighborhood level, factors related to safety, presence and quality of PA infrastructure, neighborhood upkeep and satisfaction, neighborhood aesthetics, street connectivity, walkability, land use mix, density, and public transport were identified.

Building Level Environmental Factors Influencing Residents’ PA

Fourteen studies^{23,30,33,36-39,44,46,50,51,53-55} examined building level environmental factors and their influences on PA. At the building level, MFH design typology and housing tenure were the most studied factors (n = 14). Table 1 provides detailed descriptions of different housing typologies and tenures.

Table 1.

Definitions of MFH Types by Design Typology and Housing Tenure.

MFH typology
Apartment/flat	Self-contained, private living units within a larger multi-unit residential structure(s) with shared amenities and communal spaces. 56 Residents typically rent these units
Condominium	Individual housing units within a multi-unit complex. Residents here either own their individual unit or rent from independent landlords. Feature shared amenities and spaces maintained through shared responsibilities
Townhouse/townhome/terraced housing/row houses	Residential units characterized by multiple floors and shared walls with adjacent units. They are part of row or attached grouping of similar homes with a small private outdoor space. They are individually owned with private entrances. They sometimes have shared amenities
Duplex, triplex, quadplex	Residential building divided into either two, three, or four separate units. Duplex features separate entrance to individual units. They may be owned by a single individual who rents out the units or by different owners for each unit. They typically have shared outdoor spaces
Multiplex	Residential dwelling in South Korea with a total floor area not exceeding 660 square meters and a total of no more than 3-4 stories. They are also known as “multi-unit house” or “multi-household house” 57
Housing tenure
Public/social housing	Government-subsidized housing programs designed to provide affordable rental housing for low-income individuals and families. These programs may be administered by national, state, or local housing authorities. Housing tenure, typology, and other associated policies may vary in different countries.58,59
Intermediate housing	Affordable housing in the UK that sits between social and market housing and caters to individuals that disqualify for social housing and are not able to afford the high costs of market rent housing 60
Market rent housing	Residential properties in the private sector that are rented out at market rates, determined by the prevailing demand and supply conditions in the local housing market. 61

Correlations between the housing factors and PA varied significantly (Table 2). Living in apartments had mixed associations with PA. Compared to single-family or other housing types, apartments and townhouses were negatively associated with outdoor play in children ⁵³ and apartment dwellers had fewer bike trips for transportation. ⁵⁵ Conversely, apartment, townhouse/terraced house, and condominium dwellers had a higher chance of walking for transportation,^44,55 meeting MVPA recommendations, and had higher levels of MVPA compared to single-family residents.^51,54 Residents of bigger apartments with four-to-five rooms had a higher chance of participating in regular PA than residents of smaller apartment with three or less rooms.^46,47 Living in a rental or a stand-alone apartment was associated with increased perception of neighborhood disadvantage, lower proximity to recreational areas, and decreased perception of neighborhood safety. ⁴⁶ Additionally, three studies observed that active design elements such as well-lit stairwells, stairwells with artwork, non-prominent elevators with delayed speeds, and onsite gyms increased minutes of recreational VPA per week, steps per day, stair use frequency, and regular use of gym for PA.^23,33,37 The U.S. public housing was positively associated with outdoor play in children compared to children not residing in public housing. ⁵³ In the UK, social housing was negatively associated with daily steps and daily minutes of MVPA^30,39 compared to intermediate and market-rent housing, which had positive correlations with the outcome.^38,39

Table 2.

Relationship Between Building-Level Environmental Factors and PA.

Variable	Association with [a]	Outcome variable
Housing typology
Apartment (compared to single-family and other MSH types)	+	Walking trips 55 ; meeting MVPA recommendations 51
	−	Weekday outdoor play 53 ; biking trips 55 ; MPA 54
	NS	Transportation walking frequency 44 ; MVPA 51 ; MPA 54
Apartment (with 4-5 rooms) (compared to 3 rooms or smaller)	+	Participation in regular exercise 46
Townhouse (compared to single-family and other MSH types)	+	Walking trips 55
	−	Biking trips 55
	NS	Weekday outdoor play 53 ; met MVPA recommendations 51 ; MVPA 51
Condominium (compared to single-family and other MSH types)	NS	Transportation walking frequency 44 ; MPA 54
Detached or semi-detached houses (compared to other MSH types)	+	MVPA 51 ; met MVPA recommendations 51
	NS	MPA 54
Housing tenure
Public/social housing (compared to non-public/non-social housing)	+	Weekday outdoor play 53
	−	Daily steps 30 ; MVPA 30 ; MVPA in bouts of >=10 mins 30
	NS	Daily steps 39 ; MVPA 39 ; MVPA in bouts of >=10 mins 39
Intermediate housing	+	Daily steps [b] 38 ; MVPA [b] 38
	NS	Daily steps 39 ; MVPA 39 ; MVPA in bouts of >=10 mins 39
Market rent housing	+	Daily steps [b] 38 ; MVPA [b] 38
	NS	Daily steps30,39; MVPA30,39; MVPA in bouts of >=10 mins30,39
Design features and maintenance
Staircase design
Well-lit	+ [c]	Stair usage 37
	+	Stair usage 23
	NS	Stairs climbed/day [d] 33 ; steps/day [d] 33 ; stair use frequency [d] 33
Dark	− [c]	Stair usage 37
Artwork and music present	+ [c]	Stair usage 37
	+	Stair usage 23
	NS	Stairs climbed/day [d] 33 ; steps/day [d] 33 ; stair use frequency [d] 33
Point-of-decision stair prompts	+ [c]	Stair usage 37
	+	Stair usage 23
	NS	Stairs climbed/day [d] 33 ; steps/day [d] 33 ; stair use frequency [d] 33
Poor ventilation	− [c]	Stair usage 37
No handrails	− [c]	Recreation walking frequency 50
Centrally located staircase	+ [c]	Stair usage 37
	+	Stair usage 23
Delayed and slow elevator speeds	+ [c]	Stair usage 37
	+	Stair usage 23
Other factors
PA equipment present at home	+	VPA 36 ; MPA in men 36
Indoor gym present	NS	Recreation VPA [d] 33 ; MPA 54 ; steps/day [d] 33

[a] +: positive association/impact, −: negative association/impact, NS: not significant; [b] positive correlations but higher PA in market rent compared to intermediate housing; [c] qualitative study; [d] intervention study with change in PA from T0 to T1.

Site Level Environmental Factors Influencing Residents’ PA

Eleven studies examined site level factors (Table 3) and their influences on PA.^{26,27,32,33,35,37,41,43,45,48,50} Factors such as pedestrian-friendly environments, presence of well-maintained walking paths, looped walking paths, presence of onsite PA facilities, apartment site liveliness, well-connected developments, and secure outdoor areas were positively associated with the percentage or number of walking or biking trips to shopping or other destinations^26,27; participation in PA^41,43,48; initiating, regulating, and maintaining PA ³⁵ ; and outdoor play in children. ³⁷ Liveliness is defined as “the prediction of population movement between the selected origins and the destinations.” ³⁵ Subsequently, the absence of outdoor areas, unoccupied houses, and signs of disorder were negatively associated with children’s outdoor play, ³⁷ minutes per week of MPA, ⁵⁴ and total PA. ³²

Table 3.

Relationship Between Site-Level Environmental Factors and PA.

Variable	Association with [a]	Outcome variable
Liveliness of the apartment site	+	PA initiation 35
	+ [c]	Initiate, maintain, and regulate PA 35
Presence of PA facilities and amenities on site	+	PA participation41,48
	+ [c]	PA participation37,43
	NS	Recreation VPA [d] 33 ; steps/day [d] 33
Poor maintenance and disorder in building and site	− [c]	Total PA 45 ; recreation walking frequency 50
	NS	MPA 54 ; MPA frequency 32
Walkability and pedestrian friendly environment	+	Biking/walking trips to shopping area 26
	+ [c]	PA participation43,48; total PA 45
	NS	Biking/walking trips to shopping area 26
Proximity to destinations	+	Maintaining PA (older adults) 35
	−	Maintaining PA (middle-aged adults) 35
	NS	Biking/walking trips 27
Safety	+ [c]	PA participation 37

[a] +: positive association/impact, −: negative association/impact, NS: not significant; [c] qualitative study; [d] intervention study with change in PA from T0 to T1.

Neighborhood Level Environmental Factors Influencing Residents’ PA

Twenty-six studies^{21,22,24,28-32,34-36,38,40-44,46,47,49-55} focused on the neighborhood scale. Factors related to safety from crime and traffic, other traffic hazards, neighborhood amenities and characteristics, walkability, land use mix and density, neighborhood satisfaction, and others such as air quality and thermal comfort were examined. The correlations between these factors and the PA outcome varied significantly.

Night-time safety and overall neighborhood safety were associated with higher mean steps per day in women ²¹ and PA participation in older adults. ⁴⁹ Traffic hazards and volume were negatively associated with PA participation ⁴⁹ and weekly minutes of walking for transportation. ²² Higher speed limits, more number of lanes, and shorter crossing light duration resulted in lower PA participation, ⁴³ and fewer weekly minutes of VPA, total PA, and walking. ²⁸ Presence and perceived quality of PA amenities had mixed correlations. Perceptions of neighborhood quality, and presence of PA resources and pedestrian infrastructure was positively associated with participation in PA,^41,46 daily steps, ³⁰ and weekly minutes of MVPA.^30,34 However, quality and presence of PA resources was negatively associated with weekly minutes of MVPA in men. ³¹ Incivilities such as litter and graffiti, poor upkeep and cleanliness were negatively associated with PA participation,^49,50 and weekly minutes of walking. ²⁴ Whereas physical disorder was positively associated with hours of weekday outdoor play in children. ⁵³ Neighborhood aesthetics, presence of neighborhood greenery, and outdoor space (e.g. park) were positively associated with odds and minutes of walking,^29,52 walking frequency for leisure and transportation,^44,50 weekly minutes of MVPA,^22,34 and PA participation.^41,43,49,50 Neighborhood satisfaction was positively associated with weekly minutes of MPA. ³⁶

Neighborhoods with better walkability, street connectivity and access, intersection density, and higher destination density were positively associated with weekly minutes of MVPA,^22,38 percentage of participants meeting MVPA guidelines, ²⁴ weekend steps, ³⁸ weekly minutes of walking,^24,44 number of walking and biking trips, ⁵⁵ and PA participation.^43,49 Distance to destination was negatively associated with frequency of PA⁴⁷ and number of biking/walking trips. ⁵⁵ Land use mix was positively associated with weekly minutes of walking^36,44,52 and MPA ³⁶ but negatively associated with walking for transportation and recreation in older adults. ⁴² Presence of public transport was associated with more walking but fewer biking trips. ⁵⁵ Easy public transport access and closer proximity was positively associated with PA participation,^43,49 daily steps, ³⁸ weekly minutes of walking,^36,52 odds of walking, ²⁹ and weekly minutes of MVPA. ³⁸ Higher residential and population density promoted frequency and odds of walking.^44,55 However, higher population density was associated with fewer biking trips. ⁵⁵ Finally, (Table 4) poor air quality discouraged participation in PA ³⁵ whereas better thermal comfort encouraged it. ⁵⁰

Table 4.

Relationship Between Neighborhood-Level Environmental Factors and PA.

Variable	Association with [a]	Outcome variable
Safety
Day-time safety	NS	Steps/day 21
Night-time safety	+	Steps/day in women 21
	+ [c]	PA participation 49
	NS	MVPA [d] 22 ; walking for transportation [d] 22 ; walking for leisure and transportation 40
Perceptions of crime	NS	Daily steps 30 ; MVPA 30 ; MVPA in bouts of >=10 mins 30 transportation walking frequency 44
Traffic related factors
Safety from traffic	NS	Transportation walking frequency 44
Traffic hazard and volume	−	Walking for transportation [d] 22
	− [c]	PA participation 43
	NS	MPA 54
Speed limits and number of lanes	−	VPA 28 ; total PA 28 ; walking 28
	NS	MVPA 28 ; total PA 28 ; walking 28 ; steps/week 28 ; MPA 54
Shorter crossing light duration, missing crossing aid/traffic control devices	− [c]	PA participation 43
	NS	MVPA 28 ; total PA 28 ; walking 28 ; steps/week 28 ; MPA 54
Neighborhood amenities and characteristics
Quality of PA amenities	+	Daily steps 30 ; MVPA 30 ; MVPA [d] 22
	−	MPA in men 31
	NS	Walking24,31; % meeting MPA guidelines 24 ; VPA24,31; MVPA in bouts of >=10 mins 30 ; MPA 31
Incivilities (e.g., litter, vandalized buildings, graffiti, dog waste), physical disorder, poor order and upkeep, lack of cleanliness	+	Weekday outdoor play 53
	−	Walking 24 ; PA participation 46
	− [c]	PA participation49,50
	NS	VPA 24 ; MPA 54 ; % meeting MPA guidelines 24 ; MPA frequency 32 ; walking 40
Presence of PA amenities and pedestrian infrastructure (e.g., benches, trash cans, street vendors)	+	MVPA 34
	−	VPA in men 31
	+ [c]	PA participation 41
	NS	Walking24,28,29,31,42; % meeting MPA guidelines 24 ; VPA24,28,31; MPA28,31,54; total PA28,31; steps/week 28
Neighborhood aesthetics (e.g., trees, interesting things, attractive sights)	+	Walking frequency for transportation 44 ; MPA [d] 22
	+ [c]	PA participation 49
Presence of outdoor spaces (e.g., park, garden, public open space)	+ [c]	PA participation41,43,50; walking for leisure 50
	NS	MVPA 51 ; % meeting MVPA guidelines 51
Proximity to outdoor spaces (local park)	+	Weekend steps 38 ; weekend MVPA 38
Proximity to outdoor spaces (metropolitan park)	−	Weekday steps 38 ; weekday MVPA 38
Proximity to outdoor spaces	NS	Steps/week 38 ; MVPA 38
Parking lot space and configuration (parallel parking)	+	MPA 54
Neighborhood greenery (e.g., green view index, street greenness, streetscape greenery, or urban greenness)	+	Odds of walking29,52; walking29,52; MVPA 34
	NS	Walking (elderly) 52
Walkability
Street connectivity and walkability	+	MVPA [d] 22 ; walking 24 ; % meeting MPA guidelines 24 ; weekend steps 38 ; weekend MVPA 38
	−	MPA 28
	NS	VPA24,28; total PA 28 ; walking28,44; steps/week 28 ; weekend steps 38 ; MVPA38,51; % meeting MPA guidelines 51
	+ [c]	PA participation 49
Access to services and facilities	+	Transportation walking 44
	+ [c]	PA participation43,49
	NS	Walking 24
Destination density	+	Walking and biking trips 55
	+ [c]	PA participation 49
Distance to destination	−	Walking and biking trips 55 ; PA frequency 47
Intersection density	+	Transportation biking/walking 55
	NS	Transportation/recreation walking29,42; MPA 54
Sidewalk infrastructure (e.g., presence, quality, buffer)	−	MPA 28
	+ [c]	PA participation 43 ; recreation walking frequency 50
	NS	VPA 28 ; total PA 28 ; walking28,44; steps/week 28
Others
Land use mix, diversity, and density	+	Walking36,44,52; MPA 36
	−	Transportation/recreation walking (older adults) 42
	NS	Walking29,31,44,52; MVPA 31 ; total PA 31 ; MPA 54
Bicycle infrastructure density	NS	MPA28,54; VPA 28 ; walking28,44,55; total PA 28 ; steps/week 28
Public transport (presence of service and number of bus stops)	+	Walking trips 55
	−	Biking trips 55
	NS	MVPA 42 ; walking29,42; walking odds 29
Public transport (proximity and access)	+	Walking odds 29 ; walking 36 ; weekday steps 38 ; weekday MVPA 38
	−	Walking trips (older adults) 52
	+ [c]	PA participation43,49
	NS	Walking odds 52 walking29,52 steps/week 38 ; MVPA 38
Residential density	+	Walking frequency 44
	NS	MPA 54
Population density	+	Walking odds52,55
	−	Biking 55
	NS	Walking odds52,55
Neighborhood satisfaction	+	MPA 36
Retail shops and retail food environment	+	Walking odds29,52; walking 52
	NS	Walking29,42; walking odds 29
Poor air quality	− [c]	PA participation 35
Thermal comfort	+ [c]	PA participation 50

[a] +: positive association/impact, −: negative association/impact, NS: not significant; [c] qualitative study; [d] intervention study.

Sociodemographic Factors Influencing Residents’ PA

We also reviewed the confounding factors (see Supplemental Material) related to residents’ PA such as participants’ sociodemographic factors (e.g., age, sex, race and ethnicity, income, education); employment status; occupation type; physical, mental, and social health variables; household structure type and size; and travel behaviors. As expected, age, sex, race and ethnicity, education, income, and employment status had significant impacts on the PA outcome.

Age and sex had mixed associations with the outcome depending on the type of PA. Older residents had lower levels of MVPA and initiating PA but higher daily steps and walking for recreation and transportation.^29,30,55 Additionally, higher BMI, and poor health were negatively associated with participation in PA, daily steps, and MVPA.^{22,35,36,46,51} On the contrary, one of the studies found that having multiple ailments was positively associated with PA regulation. ³⁵ Similarly, being on regular medical checkup was positively associated with PA participation. ⁴⁶ Black and Asian adult residents had negative correlations with daily minutes of MVPA and daily steps ³⁰ whereas White residents showed positive correlations with walking and biking. ²⁶ Subsequently, Hispanic and Asian children had fewer hours of weekday outdoor play. ⁵³ Being unemployed, employed part-time, or employed in manufacturing, clerical, or retail jobs was negatively associated with walking and biking. ⁵⁵ Education showed contrasting correlations^36,44 with walking and a positive correlation with total PA. ⁴⁷ A study ⁵⁵ noted that trips from home to school positively correlated with biking and walking whereas trips to other destinations and non-home-based trips negatively correlated with biking and walking. Other personal factors such as poor mental health, and social isolation were negatively associated with frequency of walking, ²⁵ change in PA,^22,47 and participation in PA. ⁴⁶

Conclusion

Key Findings and Implications

This systematic review examined the importance of multi-scale physical environments of MFH, including building-, site-, and neighborhood-scale features, illustrating how they promote or inhibit residents’ PA, with an overarching goal of promoting health and healthy behaviors. While the influence of neighborhood environments on health is well studied, the housing environment (i.e., building- and site-scale features) is understudied. In this literature review, we address important knowledge gaps as revealed by previous reviews.^62-64 Two reviews focused on architecture interventions that promote PA by summarizing results from forty ⁶⁴ and eighty-eight ⁶² articles respectively. However, design, prompts, and usage of stairs and presence of PA equipment, were the only factors examined at the housing level. Similarly, another 2021 review ⁶³ examined the aspects of housing environments, such as housing design, type, condition, and location on residents’ physical and mental health. While the study investigates the impact of apartment-type housing on residents’ social interaction and physical and mental well-being, the overall discussion is mostly focused on detached housing. Despite these examinations, the literature highlights the significant gaps in the research, particularly MFH building and site level features, which the current review attempts to address.

This study identified factors related to MFH and its surrounding environment and their impact on residents’ PA. Living in apartments and townhomes instead of condominiums, and single-family homes had a statistically significant positive correlation with walking and taking public transit for transportation. However, a negative correlation was observed with bicycle usage as a transportation choice. This could be location specific or due to the availability of bike infrastructure, all of which needs further investigation. The review also notes that MFH factors related to housing conditions and maintenance significantly influenced residents’ PA. A lively atmosphere in the apartment site positively impacted the initiation of PA, whereas inadequate maintenance and disorderliness in the building and site had a negative effect on both the engagement and level of PA participation. Finally, like previous reviews,^62,64 we found that staircase location, design, and PA promoting prompts positively influenced stair usage and MPA.

This review also included studies with populations of all age groups. We found that apartments were negatively associated with outdoor play in children, but public housing showed a positive correlation. A more in-depth understanding of children’s recreational PA, the micro-scale physical and social environment, and the housing typologies of public housing may provide a clearer picture. One study ³¹ observed a negative correlation between presence and quality of PA resources and MVPA in men which could be because men in this neighborhood performed MVPA outside their neighborhood. Similarly, another study ²⁸ observed a negative correlation between sidewalk connectivity and men’s MPA which could be because of perceived safety issues such as high crime rate and traffic. Studies with older adults suggest that providing pedestrian-friendly environments with more recreational facilities that are onsite or within shorter walking distance, public transit stops, safety from traffic and crime, socially interactive environment, and better health status positively impacted their overall PA. However, one study found a negative correlation between land use mix and recreational and transportation walking in older adults which could be because of the much higher land use mix and diversity in Hong Kong compared to other countries. ⁴²

The limitations of this review are largely related to the limited number of studies examining MFH environment, insufficiently explored site and building level environment, choice of metrics, and study design. Only twenty-three studies examined MFH environment, with contrasting correlations with PA outcomes. Additionally, housing typologies and the variations within site level outdoor areas are not sufficiently explored. Further studies that examine diverse site level outdoor areas and the PA amenities within are needed to better understand the interactions between the environment and residents’ PA. Variations in correlations with PA were observed depending on the population type and study location. Since local policy guidelines highly influence the design and structure of MFH and its neighborhood, conducting studies with a targeted focus can provide a comprehensive understanding of its impact on PA. Only seven studies used objective measures of PA which is considered more robust and reliable. While using these types of PA measures are not feasible in larger samples, studies that examine PA using the Actigraph GT3X + accelerometer, and pedometers can provide accurate understanding of the impacts of multi-spatial environments on residents’ PA. Finally, 87% of the studies (n = 30) included are cross-sectional and hence the causal relationships are unclear. Adopting longitudinal and intervention study designs can provide more robust understanding of this topic.

Conclusion and Suggestions for Future Research and Practice

MFH and its immediate surrounding environment have crucial influences on its residents’ health and healthy behaviors. This is especially true in low-income and vulnerable communities with limited access to paid subscriptions and dependence on the building and site level environments. Hence, it is necessary to understand the varying typologies of MFH and how the design of multi-scale environments can promote or inhibit residents’ PA. For future research, more intervention studies, focus groups, and interview-style studies are needed for an improved understanding of these environments. Design strategies such as incorporating smaller green spaces with well-lit walking paths, outdoor fitness zones with exercise equipment, interactive public art and installations, resident-maintained community gardens, seating and shade, and health promoting signages or prompts can encourage residents to participate in healthy behaviors. Policy recommendations such as incentivizing active design through tax incentives for developers and partnering with local fitness programs or trainers to provide on-site fitness classes are helpful. Implementing zoning regulations that promote mixed-use development, establishing inclusive design standards to create an environment that is safe for all ages and abilities, and collaborating with local schools to establish safe walking and biking routes for children have shown to promote healthy behaviors. Finally, implementing education programs to raise awareness about the importance of PA and the available facilities within the community can promote a healthier and more vibrant community.

So What? Implication for Health Promotion Practitioners and Researchers

What is already known?

Neighborhood environment has a significant influence on residents’ health and healthy behaviors. But the roles of MFH and their surrounding neighborhoods have been understudied although MFH residents, especially those in low-income housing, are more likely to depend on the housing environments to stay active.

What does this article add?

This review explored the correlations between housing and neighborhood environments of MFH and residents’ PA, and the impacts of the underlying sociodemographic factors. We identify the gaps and need for further research in understanding building, site, and neighborhood level environments of MFH and their influence on residents’ healthy behaviors. The review also identifies the need for studies with objective measures of PA and more intervention, focus groups, and interview study designs.

What are the implications for health promotion practice or research?

MFH and its immediate surrounding environment is a very crucial environment that highly influences its residents’ health and healthy behaviors. This is especially true in low-income and vulnerable communities with limited access to paid subscriptions and dependence on the building and site level environments, highlighting the importance of understanding the varying typologies of MFH and how the design of multi-scale environments can promote or inhibit residents’ PA.

ORCID iD

Manasa Vigneshwar Hegde https://orcid.org/0000-0002-0401-0922