Neighborhood disadvantage, individual-level socioeconomic position and physical function: A cross-sectional multilevel analysis

Loh, Venurs; Rachele, Jerome N.; Brown, Wendy J.; Washington, Simon

doi:10.1016/j.ypmed.2016.05.007

Cited by 30 publications

(16 citation statements)

References 54 publications

(46 reference statements)

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“…For example, women living in the most disadvantaged neighborhoods had on average (and with the exception of women with a household income greater than $130,000) the highest BMI. This “double disadvantage” phenomenon, where lower individual-level socioeconomic characteristics add together with neighborhood-level disadvantage to yield a greater overall disadvantage, is not uncommon in social epidemiology, with Australian studies yielding similar results (Loh et al, 2016; McPhedran, 2010).…”

Section: Discussionmentioning

confidence: 97%

A multilevel study of neighborhood disadvantage, individual socioeconomic position, and body mass index: Exploring cross-level interaction effects

Rachele

Schmid

Brown

et al. 2019

Preventive Medicine Reports

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This study examined associations between neighborhood disadvantage and body mass index (BMI), and tested whether this differed by level of individual socioeconomic position (SEP). Data were from 9953 residents living in 200 neighborhoods in Brisbane, Australia in 2007. Multilevel linear regression analyses were undertaken by gender to determine associations between neighborhood disadvantage, individual SEP (education, occupation and household income) and BMI (from self-reported height and weight); with cross-level interactions testing whether the relationship between neighborhood disadvantage and BMI differed by level of individual SEP. Both men (Quintile 4, where Quintile 5 is the most disadvantaged β = 0.66 95%CI 0.20, 1.12) and women (Quintile 5 β = 1.32 95%CI 0.76, 1.87) from more disadvantaged neighborhoods had a higher BMI. BMI was significantly higher for those with lower educational attainment (men β = 0.71 95%CI 0.36, 1.07 and women β = 1.66 95%CI 0.78, 1.54), and significantly lower for those in blue collar occupations (men β = −0.67 95%CI −1.09, −0.25 and women β = −0.71 95%CI −1.40, −0.01). Among men, those with a lower income had a significantly lower BMI, while the opposite was found among women. None of the interaction models had a significantly better fit than the random intercept models. The relationship between neighborhood disadvantage and BMI did not differ by level of education, occupation, or household income. This suggests that individual SEP is unlikely to be an effector modifier of the relationship between neighborhood disadvantage and BMI. Further research is required to assist policy-makers to make more informed decisions about where to intervene to counteract BMI-inequalities.

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Section: Discussionmentioning

confidence: 97%

A multilevel study of neighborhood disadvantage, individual socioeconomic position, and body mass index: Exploring cross-level interaction effects

Rachele

Schmid

Brown

et al. 2019

Preventive Medicine Reports

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“…First, this is the first study that has examined the potential effect of the neighborhood environment on muscle mass and function in more than 2000 older adults (≥ 60 years old) as well as in males and females separately, using a longitudinal study design. Most previous studies on neighborhood environments and physical function included middle age adults, such as 40 or 50 years old together with older adults and most studies were cross-sectional [10][11][12][13][14][15][42][43][44][45]. Second, our study objectively measured both neighborhood environmental factors as well as muscle mass and function specific to sarcopenia.…”

Section: Discussionmentioning

confidence: 99%

“…One study from the US found that living in neighborhoods with high physical disorder, low social cohesion and low safety was associated with higher incidence of limitations in activities of daily living, such as getting across the room, bathing, eating and shopping for groceries [14]. Other studies from the UK and Australia have found that living in neighborhoods with low socioeconomic status is associated with poorer physical function measured by self-reported functional limitations in different daily activities [10][11][12]15]. One study from the US assessed physical function objectively and found that self-reported neighborhood disorder was associated with lower physical function [13].…”

Section: Introductionmentioning

confidence: 99%

Neighborhood environment and muscle mass and function among rural older adults: a 3-year longitudinal study

et al. 2020

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Background Sarcopenia, resulting from loss of muscle mass and function, is highly prevalent in the ageing societies and is associated with risk of falls, frailty, loss of independence, and mortality. It is important to identify environmental risk factors, so that evidence-based interventions to prevent sarcopenia can be implemented at the population level. This study aimed to examine the potential effect of several objectively measured neighborhood environmental factors on longitudinal change of muscle mass and function among older adults living in rural Japanese towns where the population is ageing. Methods This study was based on data from the Shimane CoHRE Study conducted by the Center for Community-based Healthcare Research and Education (CoHRE) at Shimane University in 3 rural towns in the Shimane Prefecture, Japan. Subjects older than 60 years, who participated in an annual health examination in 2016 and any follow-up years until 2019, i.e., 4 possible time points in total, were included (n = 2526). The skeletal muscle mass index (SMI) and grip strength were assessed objectively for each year as a measure of muscle mass and function, respectively. Neighborhood environmental factors, i.e., hilliness, bus stop density, intersection density, residential density, and distance to a community center were measured by geographic information systems (GIS). Linear mixed models were applied to examine the potential effect of each neighborhood environmental factor on the change of SMI and grip strength over time. Results Males living far from community centers had a less pronounced decline in SMI compared to those living close to community centers. Females living in areas with higher residential density had a less pronounced decline in grip strength compared to those living in areas with lower residential density. Conclusions Neighborhood environmental factors had limited effects on change of SMI and grip strength among rural older adults within the 3 years follow up. Further long-term follow up studies are necessary by also taking into account other modifiable neighborhood environmental factors.

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“…Lower socioeconomic status may be associated with unequal opportunities for access to physical activity promoting environments (23,24) . Another study carried out with data from Brazil's 2015 National Household Sample Survey also found a positive association between physical activity and income (25) .…”

Section: Discussionmentioning

confidence: 99%

Influence of sociodemographic and economic factors on physical activity among university students

Chamberlem

Ferreira

Rodrigues

et al. 2020

RBPS

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Objective: To estimate the influence of socioeconomic factors on the variation in time spent by university students on physical activity after the first academic year. Methods: Quantitative longitudinal study of 348 full-time university students aged 16-25 years from the capital of Mato Grosso, Brazil. Change in time spent on moderate and vigorous physical activity was assessed in minutes per week through the short version of the International Physical Activity Questionnaire (IPAQ). The following independent variables were analyzed: gender, age, race/skin color, economic class, students’ housemates and field of study. Multinomial regression analysis was used to check for associations between physical activity time variation in tertiles and the independent variables. Results: The overall change in median physical activity time in one year was -90.0 minutes/week. Students of higher socioeconomic status maintained the same physical activity time, while those in other socioeconomic classes showed a decrease in such time after the first year at university. After adjustments, lower economic class (OR=2.85; 95%CI= 1.26-6.43) and living in a shared house (OR=2.84; 95%CI= 1.26-6.38) were associated with decrease in time spent on physical activity. Conclusion: There was a decrease in time spent on physical activity among students belonging to the lower economic classes who lived in a shared house after the first year at university.

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Neighborhood disadvantage, individual-level socioeconomic position and physical function: A cross-sectional multilevel analysis

Cited by 30 publications

References 54 publications

A multilevel study of neighborhood disadvantage, individual socioeconomic position, and body mass index: Exploring cross-level interaction effects

A multilevel study of neighborhood disadvantage, individual socioeconomic position, and body mass index: Exploring cross-level interaction effects

Neighborhood environment and muscle mass and function among rural older adults: a 3-year longitudinal study

Influence of sociodemographic and economic factors on physical activity among university students

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