Individual and contextual characteristics of indoor and outdoor falls in older residents of São Paulo, Brazil

Archives of Gerontology and Geriatrics 68 (2017) 119–125

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Individual and contextual characteristics of indoor and outdoor falls in older residents of São Paulo, Brazil Carla Ferreira do Nascimentoa,* , Yeda Aparecida Oliveira Duarteb , Maria Lúcia Lebrãoa , Alexandre Dias Porto Chiavegatto Filhoa a b

School of Public Health, University of São Paulo, Av. Dr. Arnaldo, 715, CEP: 01246-904, São Paulo – SP, Brazil, Brazil School of Nursing, University of São Paulo, Av. Dr. Enéas de Carvalho Aguiar, 419, CEP: 05403-000, São Paulo – SP, Brazil, Brazil

A R T I C L E I N F O

A B S T R A C T

Article history: Received 3 August 2016 Received in revised form 10 October 2016 Accepted 17 October 2016 Available online 23 October 2016

Purpose of the study: To analyze a representative sample of older individuals of São Paulo, Brazil, according to outdoor fallers, indoor fallers and non-fallers, and to identify biological and socioeconomic (individual and contextual) factors associated with the occurrence and place of falls. Materials and methods: A cross-sectional study was conducted using data (n = 1345) from the 2010 wave of the Health, Wellbeing and Aging (SABE) Study, a representative sample of older residents (60 years and older) of São Paulo, Brazil. Multinomial logistic analysis was performed to identify individual factors associated with the occurrence and place of falls, and multilevel multinomial analysis to identify contextual effects (green areas, violence, presence of slums and income inequality). Results: 29% had a fall in the last 12 months, with 59% occurring in indoor spaces. Individuals who had outdoor falls were overall not statistically different from non-fallers; on the other hand, those who had the last fall indoor had worse health status. Moderate homicide rate was a factor associated with increased presence of indoor falls, compared with non-fallers. Implications: Our results describe the importance of falls, a common problem in active and communitydwelling older adults of São Paulo, Brazil. Transforming outdoor spaces into walk-friendly areas is essential to allow socialization and autonomy with safety. Creating strategies that take into account the most vulnerable populations, as those who live in violent areas and the oldest older adults, will be a growing challenge among developing countries. ã 2016 Elsevier Ireland Ltd. All rights reserved.

Keywords: Outdoor falls Indoor falls Neighborhoods Multilevel analysis

1. Introduction The two most important demographic transitions of 21st century are considered to be population aging and urbanization (World Health Organization, 2016). Brazil is the most urbanized country of Latin America (ONU Habitat, 2012), and São Paulo, which is the largest urban center of the country, had a 88% increase in its older population from 1980 to 2010 (Ministério da Saúde, 2010). This age group has been consistently shown to be more vulnerable to common large cities problems, such as crime, poor building designs, urban mobility problems and lack of social interactions (World Health Organization, 2016).

* Corresponding author at: Department of Epidemiology, School of Public Health, University of São Paulo, Avenida Doutor Arnaldo, 715, 1 andar, CEP: 01246 904, Brazil. E-mail addresses: [email protected], [email protected] (C.F. do Nascimento). http://dx.doi.org/10.1016/j.archger.2016.10.004 0167-4943/ã 2016 Elsevier Ireland Ltd. All rights reserved.

Studies show that falls are the most important external cause of death among older adults (Rockett et al., 2012). In the United States, it was responsible for 52% of all external causes of death in 2009 (Rockett et al., 2012), and in São Paulo, Brazil, this percentage was around 47% in 2013 (Ministério da Saúde, 2010). According to Prince et al., in 2015, it was among the 15 most burdensome disorders in older people. Falls frequently result in hospitalization, injuries, dependency, and therefore considerably increase the costs of health, community and social care services (Hartholt et al., 2011). Falls are a multifactorial event influenced by biological, socioeconomic, environmental and behavioral risk factors (World Health Organization, 2007). Indoor falls are generally more associated with worse health conditions and outdoor falls are more common in younger and healthier individuals (Kelsey et al., 2010). Seemingly, environmental hazards are more associated with falls occurring in external places when compared to biological risk factors (Kim, 2016). Li et al. (2014), found that socioeconomic,

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behavioral and neighborhood aspects could influence the incidence of outdoor falls and that some environmental modifications, such as improvements in curbs, walkways, streets, sidewalks and recreational places design, could prevent it (Li et al., 2006). Researchers consider outdoor falls a relatively neglected public health problem since they represent almost 50% of total falls (Li et al., 2006). A qualitative study analyzed the emotional consequences of outdoor falls in the United Kingdom and found that several outdoor falls were associated with feelings of embarrassment and anxiety about falling again, and that the presence of bystanders could intensify these feelings (Nyman, Ballinger, Phillips, & Newton, 2013). Results of a recent study about differences in injuries from falls in outdoor and indoor places found that, although injury severity score was higher in indoor fallers and that the body region affected was different, the consciousness level due the injury and the percentage of severe injury were not statistically different between the two groups (Kim, 2016). The objective of this study was to analyze a representative sample of older individuals from a very large and diverse city of Brazil. As the number of older individuals rapidly increase in developing countries, identifying the determinants of falls can help with public health interventions. We therefore aim to identify the individual and contextual (area of residence) differences between outdoor fallers, indoor fallers and non-fallers. 2. Material and methods We use data from the Health, Well-Being and Aging Study (SABE), a representative sample of community-dwelling older adults (60 years and older) of the municipality of São Paulo. The original project of the SABE Study was multicentered, coordinated by Pan-American Health Organization and implemented by Epidemiology Department of University of São Paulo. From an initial sample of 72 census tracts from the municipality of São Paulo, subjects were selected by clustered sampling, using a probability proportional to size approach. Further details of the sampling approach can be found elsewhere (Lebrão & Duarte, 2003). The SABE Study received approval from the Human Research Ethics Committee of the Public Health School of the University of São Paulo, in accordance with Declaration of Helsinki (protocol number 2044). All subjects gave informed consent and individual anonymity was preserved. We performed a cross-sectional analysis of the 1345 older adults of the last wave of the study (2010). Individuals were nested within 31 local administrative regions known as subprefeituras (a proxy for neighborhood), the smallest areas for which health and social contextual data are available. Area-level data were obtained from the public statistics department of the municipality of São Paulo (“Prefeitura do Município de São Paulo,” 2015), and the Informatics Department of Brazilian Public Health (DATASUS) (Ministério da Saúde, 2010). For each of the 31 areas, we calculated the homicide rate adjusted by age as a proxy for local violence, the Gini coefficient, the total green area per resident (m2) and the percentage of residences living in favelas (slums). The dependent variable was the occurrence and place of last fall. It is a qualitative variable divided into 3 factors: “non-fallers”, “indoor fallers” and “outdoor fallers”. The variable was assessed by the questions: “Have you had any fall in the last 12 months (last year)?” followed by “Where did you have the last fall?” in case of an affirmative answer. We considered as “indoor” the falls that occurred inside the house or any other building, and as “outdoor” the falls occurred anywhere outside a building. For our analyses, we excluded individuals who were not able to walk independently (as indicated by not being able to complete the Time Up and Go Test, TUGT) and who did not inform the place of falls (n = 157, 11.7%). Fig. 1 summarizes these results.

n =153 (not able to perform TUGT)

n=4 (did not give informaon about the place of fall)

Excluded (n=157)

n = 1,345 (Overall sample)

Included (n=1188) n = 224 (Indoor fall)

n = 141 (outdoor fall)

n = 823 (no fallers)

Fig. 1. Flow chart of the sample considered for the study.

Independent variables included on the models were years of education (none, 1–3, 4–7, 8 or more years), marital status (married, divorced, widower and unmarried), race (white, mixed, black and others), perception of income sufficiency (“Do you consider you have enough money to cover your needs for daily life?: yes or no”), gender, age group (60–69, 70–79, 80 and older), cognitive impairment, number of self-reported noncommunicable diseases (hypertension, diabetes, stroke, pulmonary, heart or joint disease) and functional mobility. Cognitive status was measured by the modified version of Mini-Mental State Examination (Icaza & Albala, 1999), where the cutoff of 12 points indicates cognitive impairment. To assess functional mobility we used the Timed Up and Go Test (TUGT) result, which quantifies the time in seconds that took for the elderly to stand up from a standardized chair, with arms and trunk supported, walk 3 m at usual pace, return, walk back and sit down (Podsiadlo & Richardson, 1991). The individuals used their usual footwear and their gait-assistance device if needed, but did not received physical assistance throughout the test. Longer results on the TUGT is an indicator of poorer functional mobility (Podsiadlo & Richardson, 1991). 2.1. Statistical analysis We first performed descriptive and bivariate analyses. We estimated the relative frequency and the Rao-Scott test to compare differences within independent variables according to the dependent variable (Rao & Scott, 1987). For the TUGT we estimate the mean and confidence intervals (95%) for each factor of the dependent variable. Results with p-value  0.05 were considered significant. We performed multinomial logistic regression with non-fallers as the reference factor. We included variables in the models by following conceptual criteria. Biological risk factors were added first, followed by race, and lastly by socioeconomics variables. For all of the analyses we considered the sampling weight using the svy mode of Stata 13.1 software. To analyze the potential effect of neighborhoods we performed multinomial logistic multilevel models, with individual factors as the first level and the contextual factors as the second. We first adjusted the null models without the inclusion of independent variables. We then included all individual variables to the models, followed by the contextual factors. Results are presented in terms of prevalence ratios (PR) along with 95% confidence intervals (CI). We used the Akaike information criteria (AIC) to identify models with better fit. The GLLAMM program in Stata 13.1 was used for the multinomial multilevel analysis (Rabe-Hesketh, Skrondal, & Pickles, n.d.).

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3. Results The distribution of the individual characteristics for the total sample is shown in Table 1. About 17.4% of the total sample had the last fall indoor and 11.9% outdoor. Considering only the fallers, approximately 41% had the last fall in outdoor spaces. Table 2 shows the sample distribution according to individual variables and the occurrence and place of last fall. Women had higher probability to have an indoor fall than men, when compared to non-fallers. The oldest old also had higher prevalence of indoor falls than the younger group. The group without self-reported noncommunicable diseases (NCD) had lower percentage of indoor falls, in contrast to the group with 2 or more NCD. Socioeconomic variables did not show significant differences according to place of fall. The TUGT time was significantly different between indoor fallers and non-fallers. There was not a statistically significant difference in TUGT between outdoor fallers and non-fallers (Table 3). Table 4 presents the multinomial logistic analysis results. Model 1, which includes biological risk factors, indicates a higher probability of indoor falls for women (PR = 1.65) and for those with 2 or more NCD (PR = 2.23), when compared to non-fallers. According to the same model, each 1 s added in TUGT increases

Table 1 Sample characteristcs (n = 1.188). São Paulo, 2010. Variables

Total (%)

Sex Women Men

60.12 39.88

Age, years 60–69 70–79 80 and older

55.36 30.38 14.26

Marital Status Married Divorced Widower Unmarried

56.06 9.55 31.05 3.35

Income is enough Yes No

56.98 43.02

Years of schooling None 1–3 4–7 8 or over

11.37 23.18 38.30 27.15

Race White Mixed race Black Others

58.30 29.73 6.66 5.31

Number of non-communicable diseases None 1 2 or more

16.24 27.85 55.91

Cognitive impairment Yes No

8.87 91.13

Falls None Indoor Outdoor

70.77 17.35 11.87

121

the probability of indoor falls by 3%. These results were similar to the other models, even after the inclusion of socioeconomic variables. None of these factors was significantly associated with outdoor falls. In Model 2 we included race, but the variable was not associated with any of the factors of the dependent variable. Income sufficiency, schooling, and marital status, which were introduced in Model 3, also did not present statistically significant associations. On the other hand, after the inclusion of these variables, mixed race individuals had a significant reduced prevalence ratio of indoor falls (PR = 0.64) and individuals 80 years or more had a higher prevalence of outdoor falls (PR = 1.99). Table 5 presents the results for the contextual variables obtained by the multinomial multilevel analyses. Model 1, which included all individual variables, had a significant lower AIC in comparison with the Null Model, which indicates better fit. The following models, which included contextual variables, found a significant association only for the homicide rate (Model 3), indicating that moderate homicide neighborhoods increased the prevalence of indoor falls by 57% compared with low homicide rate areas. Nevertheless, the inclusion of contextual variables did not contribute to model fit, as it increased the AIC value. 4. Discussion Among fallers, our results revealed that 41% of the falls occurred in outdoor spaces. This result is only slightly lower than previous studies, for which the amount of outdoor fallers was around 46% (Kelsey et al., 2010; Kelsey, Procter-Gray, Hannan, & Li, 2012; Li et al., 2014). Only one study found a higher prevalence of outdoor falls (58%), but its sample was younger, from individuals with 45 years and more (Li et al., 2006). Broadly, our results show that individuals who had outdoor falls were not statistically different from non-fallers. On the other hand, those who had the last fall indoors seem to have worst health status. We observed that having two or more non-communicable diseases was an independent factor associated with indoor falls, but not with outdoor. These results reinforce the idea that indoor falls are associated with worse health status and that outdoor falls are more common in more physically active individuals (Kelsey et al., 2010, 2012; Kim, 2016; Wijlhuizen, Jong, & Hopman-Rock, 2007). We also found that indoor fallers had worse functional mobility than outdoor fallers and non-fallers. This result corroborate the findings of Kelsey et al., in 2010, who described worse physical performance in indoor group if compared with outdoor fallers using the Balance Berg Scale, the Short Physical Performance Battery and gait speed. In our analysis, we used the TUGT as functional mobility measure, which is recommended by American Geriatrics Society and British Geriatrics Society to identify risk of falling in older adults (American Geriatrics Society and British Geriatrics Society, 2011). According to our results, the test was not sufficiently able to detect outdoor fallers, probably because these falls are frequently more associated with environmental and behavioral aspects than with individual health status (Kim, 2016; Li et al., 2014). The multiple analyses found a higher prevalence ratio (RP) for indoor falls among women, even after the inclusion of socioeconomic variables. Other studies also show that women have more indoor falls than men (Kelsey et al., 2010; Kim, 2016). This could be influenced by the fact that women have a higher probability to become frail (Fried et al., 2001), and that women are more exposed to household activities, an important behavioral risk factor for falls (Perracini & Ramos, 2002). Regarding the age groups, previous studies show a decreased probability to have outdoor falls and an increased probability to

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Table 2 Sample distribution according individual dependent and independent variables and p values corresponding to Rao-Scott test. São Paulo, 2010. Fallers

Non-fallers (%)

p

–

Indoor (%)

Outdoor (%)

Total

17.35

11.87

70.77

Sex Women Men

20.94 11.95

11.98 11.70

67.08 76.35

Age, years 60–69 70–79 80 and older

14.50 19.10 24.71

11.15 12.26 13.85

74.35 68.64 61.44

Marital status Married Divorced Widower Unmarried

15.40 19.97 20.11 17.07

11.78 11.97 10.47 20.40

72.82 68.06 69.42 62.53

Income is enough Yes No

17.11 17.24

10.43 13.94

72.46 68.82

Years of schooling None 1–3 4–7 8 or over

23.99 16.12 18.75 13.96

12.63 12.06 10.77 11.90

63.39 71.82 70.48 74.14

Race White Mixed race Black Others

19.21 14.43 13.53 16.20

11.60 12.07 14.00 10.95

69.18 73.50 72.46 72.85

Number of non-communicable diseases None 1 2 or more

9.32 13.10 21.80

10.67 9.55 13.38

80.00 77.35 64.82

Cognitive impairment Yes No

23.76 16.73

13.89 11.68

62.35 71.59

0.0050

0.0270

0.3026

0.1973

0.2415

0.6527

0.0001

0.0816

Table 3 TUG average time (seconds) and confidence intervals (CI) according dependent variable factors. São Paulo, 2010. Factors

Non-fallers Indoor fallers Outdoor fallers Total

TUG (sec) Mean

CI (95%)

13.26 16.24 13.72 13.83

(12.74;13.77) (14.77;17.71) (12.82;14.62) (13.28;14.38)

have indoor falls with advancing age, which is mainly explained by the higher frequency of outside walks in younger and healthier individuals (Kelsey et al., 2010). Our multivariate analysis, after inclusion of socioeconomic variables, found a significant higher prevalence of outdoor falls, but not indoor falls, among the oldest old group (80 + ). Weather characteristics could help to explain these findings, as the climate in Brazil is less extreme and more conductive to walking than other places where similar studies were conducted (Kelsey et al., 2012). Even so, this finding indicates the necessity to investigate other individual characteristics that could influence this relationship such as dual task capability, cognitive aspects (such as executive function) and medication use (Muir, Gopaul, & Montero Odasso, 2012; Quach et al., 2013).

Social and behavioral aspects could also influence this result, even though we did not find significant associations with socioeconomic variables. A previous study conducted in São Paulo found that individuals aged 80 years and more had higher odds of living alone than younger individuals. The same study found that individuals who lived alone had lower odds of having a strong social support network, thus they could be more susceptible to external activities (Rosa, Benício, Alves, & Lebrão, 2007). A recent study showed that outdoor falls are influenced by socioeconomic disparities, probably due to behavioral factors (Li et al., 2014). Individuals in disadvantaged areas present a higher habit to walk for utilitarian proposes, which could be more associated with outdoor fall risk than recreational walking. The same authors suggest that these falls could be explained by unmeasured urban environmental characteristics (Li et al., 2014). In our multinomial analysis, after the inclusion of socioeconomic variables, we found a reduced PR for indoor falls in the mixed race group compared to whites. This result is in contrast with Silva et al., in 2012, that showed higher prevalence of falls among blacks, followed by mixed races, when compared with whites. The same study did not find significant differences by race and place of falls. Results from Faulkner et al., in 2005 did not show differences in the incidence of falls according to ethnicity, but found it for the circumstances of falls. They observed that white elderly female residents of Pennsylvania, United States, had a

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Table 4 Results of multinomial logistic regression models: Prevalence ratios (PR) and confidence intervals (CI) for indoor and outdoor fallers, with non-fallers as reference factor. São Paulo, 2010. Indoor fallers:

Model 1

Model 2

PR Female sex

1.65

Age, years (ref: 60–69) 70–79 80 and older

1.19 1.29

Number of non-communicable diseases (ref: none) 1 2 or more

1.30 2.23

TUG (seconds)

1.03

Cognitive impairment

1.03

*

*

*

CI (95%)

PR

(1.07;2.53)

1.61

(0.75;1.90) (0.75;2.24)

1.15 1.20

(0.69;2.44) (1.22;4.04)

1.28 2.30

(1.01;1.05)

1.03

(0.63;1.69)

Race (ref: white) Mixed Black Others

Model 3 CI (95%)

PR

(1.05;2.49)

1.65

(0.69;1.91) (0.66;2.19)

1.19 1.32

(0.68;2.42) (1.26;4.19)

1.29 2.35

(1.01;1.05)

1.03

1.13

(0.66;1.93)

1.09

0.71 0.60 0.92

(0.47;1.08) (0.29;1.23) (0.38;2.21)

0.64 0.54 0.99

*

*

*

CI (95%) *

(1.01;2.69)

(0.71;1.99) (0.70;2.52)

*

*

(0.66;2.52) (1.27;4.38) (1.02;1.06) (0.63;1.91)

*

(0.41;0.98) (0.25;1.14) (0.40;2.46)

Income is enough

0.98

(0.69;1.39)

Years of schooling (ref: none) 1–3 4–7 8 and over

0.76 0.91 0.74

(0.43;1.35) (0.55;1.49) (0.39;1.43)

Marital status (ref.: married) Divorced Widower Unmarried

1.39 0.85 1.28

(0.82;2.34) (0.58;1.25) (0.55;2.98)

Outdoor fallers:

Model 1 PR

CI (95%)

Model 2 PR

CI (95%)

Model 3 PR

CI (95%)

Female sex

1.07

(0.67;1.70)

1.06

(0.67;1.68)

1.14

(0.69;1.88)

Age, years (ref: 60–69) 70–79 80 and older

1.11 1.37

(0.70;1.77) (0.86;2.17)

1.14 1.38

(0.72;1.79) (0.87;2.19)

1.39 1.99

Number of non-communicable diseases (ref: none) 1 2 or more

0.90 1.47

(0.47;1.72) (0.87;2.48)

0.91 1.44

(0.48;1.71) (0.86;2.42)

0.78 1.32

(0.41;1.50) (0.75;2.33)

TUG (seconds)

1.00

(0.97;1.03)

1.00

(0.97;1.03)

0.99

(0.96;1.03)

Cognitive impairment

1.17

(0.62;2.23)

1.23

(0.63;2.41)

1.05

(0.51;2.15)

1.01 1.06 0.90

(0.65;1.57) (0.57;1.99) (0.24;3.20)

0.92 0.95 0.93

(0.56;1.53) (0.47;1.91) (0.25;3.52)

Income is enough

0.70

(0.46;1.07)

Years of schooling (ref: none) 1–3 4–7 8 and over

0.89 0.91 1.03

(0.43;1.84) (0.48;1.74) (0.50;2.13)

Marital status (ref.: married) Divorced Widower Unmarried

1.14 0.74 1.95

(0.58;2.23) (0.44;1.23) (0.76;4.98)

Race (ref: white) Mixed Black Others

*

*

(0.89;2.16) (1.23;3.22)

p  0,05.

higher risk of falls on the street, when compared to African elderly women. In our study, most contextual variables did not present a significant association with outdoor falls. Only moderate homicide rate was a factor associated with increased prevalence of indoor

falls, when compared with non-fallers. Although we have not detected other studies using the same analysis, our result is in accordance with the assumption that individuals who live in violent regions have lower likelihood to walk away from home and to practice regular physical activity (Chiavegatto Filho, Lebrão, &

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Table 5 Prevalence ratios and confidence intervals of second level of multilevel analysis. The reference factor is non-fallers group. São Paulo, 2010. Models

Contextual variables

CI (95%)

PR

CI (95%)

–

–

–

2216.563

–

–

–

–

1856.596

Green area (m2/resident) (reference: 0.35–3.30 low) 3.90–6.65 (moderate) >10.00 (high)

0.93 0.92

(0.61;1.42) (0.64;1.31)

0.76 0.79

(0.46;1.26) (0.52;1.21)

Homicide rate (/100.000 hab) Ref.: (2.1–10.0 low) 10.1–13.4 (moderate) >13.5 (high)

1.57 1.33

(1.06;2.31) (0.89;1.97)

1.31 1.06

(0.83;2.06) (0.66;1.71)

Gini index ref.: (0.45–0.51 low) 0.52–0.57 (moderate) 0.58 (high)

1.01 1.37

(0.70;1.48) (0.90;2.07)

0.74 1.16

(0.47;1.16) (0.71;1.90)

% residences in slums (ref.: 0.25–5.00) 6.00–14.00 >15.00

1.05 1.37

(0.70;1.56) (0.92;2.06)

0.73 0.70

(0.47;1.14) (0.43;1.15)

Model 1

Model 4

Model 5

AIC

PR

a

Model 3

Outdoor falls

–

Null model

Model 2

Indoor falls

1862.827

1858.570 *

1858.986

1858.220

a In Model 1 only the individual variables (sex, age group, number of non-communicable disease, TUG time, cognitive impairment, race, income sufficiency and marital status) were included. The other models were adjusted by these variables.

Kawachi, 2012; Latham & Williams, 2015), which could increase the probability to have a fall at home. Although outdoor falls frequently lead to less severe injuries than indoor falls (Duckham et al., 2013; Kim, 2016), it is important to take into consideration that the first fall is a potential risk to have another fall (Tinetti & Kumar, 2010). Despite the exposure to urban environment caused by social and physical activity, this practice is important to a successful and healthy aging. Therefore, transforming these spaces into walk-friendly places is essential to allow socialization and autonomy with safety. It is also important to create strategies that take into account the more vulnerable populations, as those who live in more violent spaces and the oldest older adults. Our study has a few limitations that need to be mentioned. First, occurrence of falls was self-reported, which could be subject to memory bias, an important problem among the elderly. To address this problem, we considered exclusively the last 12 months and only the last fall, but memory bias could still be an issue here. Second, it was not possible to take into account previous falls that occurred in different places, if it even occurred. Third, the crosssectional design does not allow for causal inferences, since we do not know the temporal association between the factors. Fourth, the size of the neighborhoods may have underestimated some of the associations, which would be better measured if we could collect local data from smaller clusters. Fifth, we found a higher association for moderate homicide than for higher homicide rate, which could be an indication that another proxy for violence is a more adequate measure, but unfortunately the homicide rate is the only reliable proxy for violence currently available for the neighborhood-level (Chiavegatto Filho, Lebrão, & Kawachi, 2012). Our results present important elements to consider when forming preventive policies and strategies to prevent falls among the elderly in a very large and socioeconomically diverse urban area of Latin America. This study reinforces the necessity of investments in preventive strategies that promote not only mobility and physical performance, but also home environment interventions. Our results also point out the problem of outdoor

falls, which are quite common in active and community-dwelling older residents of São Paulo, Brazil. Funding This work was supported by the São Paulo Research Foundation (grant number 2014/06721-4). Declaration of conflicting interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Acknowledgment The authors thank the São Paulo Research Foundation (FAPESP) for the grant (number: 2014/06721-4). References American Geriatrics Society & British Geriatrics Society (2011). Summary of the updated American Geriatrics Society/British Geriatrics Society clinical practice guideline for prevention of falls in older persons. Journal of the American Geriatrics Society, 59(1), 148–157. http://dx.doi.org/10.1111/j.15325415.2010.03234.x. Chiavegatto Filho, A. D. P., Lebrão, M. L., & Kawachi, I. (2012). Income inequality and elderly self-rated health in São Paulo, Brazil. Annals of Epidemiology, 22(12), 863–867. http://dx.doi.org/10.1016/j.annepidem.2012.09.009. Duckham, R. L., Procter-Gray, E., Hannan, M. T., Leveille, S. G., Lipsitz, L., & Li (2013). Sex differences in circumstances and consequences of outdoor and indoor falls in older adults in the MOBILIZE Boston cohort study. BMC Geriatrics, 13(1), 133. http://dx.doi.org/10.1186/1471-2318-13-133. Faulkner, K., Cauley, J., Zmuda, J. M., Landsittel, D. P., Nevitt, M. C., Newman, A. B., . . . Redfern, M. S. (2005). Ethnic differences in the frequency and circumstances of falling in older community-dwelling women. Journal of the American Geriatrics Society, 53, 1774–1779. http://dx.doi.org/10.1111/j.15325415.2005.53514.x. Fried, L. P., Tangen, C. M., Walston, J., Newman, A. B., Hirsch, C., Gottdiener, J., . . . McBurnie, M. A. (2001). Frailty in older adults: Evidence for a phenotype. Journal of Gerontology: Biological Sciences, 56(3), 808–813.

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