Background
                Social support has been shown to be associated with various positive health outcomes among older adults but has not been previously examined in relation to falls, which are a serious health concern among older adults.
              
              
                Findings
                This study (n = 1000) uses multivariable logistic regression to evaluate the relationship between social contact and perceived availability of social support and falls among older adults. When adjusting for demographic and other covariates neither relationship was significant.
              
              
                Conclusions
                This study does not find evidence to suggest that social support could be a prevention measure for falls. Future research on this topic should focus on careful definition and precise measurement of the social support construct

Durbin, Laura

Graber, Rebecca

Kharrazi, Rebekah J.

Mielenz, Thelma J.

PubMed

Laura Durbin

Rebekah J. Kharrazi

Rebecca Graber

Thelma J. Mielenz

Springer - Publisher Connector

Social support and older adult falls

Columbia University Academic Commons

SHORT REPORT Open AccessSocial support and older adult fallsLaura Durbin1*, Rebekah J. Kharrazi1, Rebecca Graber2 and Thelma J. Mielenz1AbstractBackground: Social support has been shown to be associated with various positive health outcomes among olderadults but has not been previously examined in relation to falls, which are a serious health concern among olderadults.Findings: This study (n = 1000) uses multivariable logistic regression to evaluate the relationship between socialcontact and perceived availability of social support and falls among older adults. When adjusting for demographicand other covariates neither relationship was significant.Conclusions: This study does not find evidence to suggest that social support could be a prevention measure forfalls. Future research on this topic should focus on careful definition and precise measurement of the social supportconstruct.Keywords: Aging, Accidental falls, Social support, Risk factorsObjectiveFalls, which are frequent among older adults, are aserious concern for this population as they often causeconsequential injuries and can even be fatal (WHO2007). Nearly 1 in 3 older adults experience a fall eachyear, and half of these individuals fall more than once(CDC 2015). Although social support (including per-ceived support) has been found to be a protective factorfor depression, anxiety, and physical disability amongolder adults, it has not previously been examined expli-citly in relation to fall events (Cole and Dendukuri 2003;Vink et al. 2008; Taylor 2011).Social support has been defined as the perception orexperience that a person is cared for, valued, andesteemed by others, and is a member of a social networkthat provides mutual assistance (Wills 1991). Barrera(1986) suggested in a review of the literature that socialsupport can take the following forms: social embedded-ness, perceived support, and enacted support. Sincethen, other constructs have become accepted in thesocial support field (such as instrumental, emotional,and informational support), with perceived social sup-port continuing to be recognized as a valuable construct(Langford et al. 1997; Taylor 2011).It has been suggested that social support could act asa protective factor against falls, perhaps by encouragingolder adults to be more attentive to hazards in the envir-onment or by ensuring that at-risk individuals receivehelp for completing risky tasks, such as reaching for faraway objects or taking out the garbage (Faulkner et al.2003; Hosseini and Hosseini 2008). This study evaluatesthe relationship between social support and falls amonga community-dwelling population of older adults.MethodsThis cross-sectional study is a secondary analysis of theNew York City Housing Authority (NYCHA) SeniorSurvey, which surveyed NYCHA building residents aged65 and older via telephone interviews in June 2009.Participants were randomly selected from the more than65,100 residents meeting the age criteria, with a finalsample size of 1,036, which exceeded the prestudysample size calculation of 142 (80 % power, 5 % alpha,medium anticipated effect size). NYCHA’s publishedfindings contain further details regarding study measuresand questions (Parton et al. 2011). This secondaryanalysis study was approved by Columbia University’sInstitutional Review Board.The outcome of interest was a dichotomous measure ofself-reported falls during the past year. The primary pre-dictors of interest were social contact and perceived avail-ability of social support. Social contact is a component of* Correspondence: ld2280@cumc.columbia.edu1Department of Epidemiology, Columbia University Mailman School of PublicHealth, 722 West 168th St., Room 516, New York, NY 10032, USAFull list of author information is available at the end of the article© 2016 Durbin et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made.Durbin et al. Injury Epidemiology  (2016) 3:4 DOI 10.1186/s40621-016-0070-ysocial embeddedness, which is in turn a necessary ante-cedent of social support (Barrera 1986; Langford et al.1997). In this study, social contact was measured by thefollowing survey question: “During the past week, didyou talk with relatives, friends, or neighbors on thetelephone?” Perceived availability of social supportattempts to determine an individual’s confidence thatappropriate support would be available to them ifthey needed it (Barrera 1986). In this study thisconstruct was measured with the following question:“Is there a friend, relative, or neighbor who could as-sist you for a few days if necessary?”.Bivariable analyses were conducted between falls andboth predictors, as well as between falls and each of thecovariates, using the Chi-squared test. Two logistic re-gression models, one for each social support construct,were used to conduct multivariable analyses. Covariates,selected among available measures that have previouslybeen shown to be associated with falls among olderadults, are reported in Table 1. All covariates wereinitially included in the logistic regression models. Thecovariates that were nonsignificant at the bivariate levelwere removed first, followed by the significant variables.The change-in-estimate method with a 10 % changecriterion was used to remove covariates (Walter andTiemeier 2009).FindingsThe overall response rate for the NYCHA study was34.7 %, with a cooperation rate of 93.4 % for individualsreached by phone. Thirty-six individuals were excludedfor missing data on falls or social support constructs,resulting in a study population of 1,000. The mean agewas 74, with a maximum age of 95. Participants repre-sented several races (57.4 % black, 28.8 % Hispanic,9.5 % white, 4.3 % Asian/Pacific Islander) and weremostly female (75.6 %). A large percentage of partici-pants reported social contact (89.8 %) and a perceivedavailability of social support (72.1 %). Nearly one inthree participants (28 %) reported falling in the pastyear. A comparison between fallers and non-fallers isoutlined in Table 1. In bivariate analyses, neither socialcontact nor perceived availability of social support wassignificantly associated with falls.Variables adjusted for in both final social supportmodels included age, gender, race/ethnicity, visiondifficulties, self-described health, dizziness, osteoporosis,arthritis, stroke, heart attack, diabetes, depression, andphysical activity. Table 2 presents only the point esti-mates for the social support exposure. In both finalmodels, the variables that were significant include:gender, self-described health, dizziness, arthritis, stroke,diabetes, depression, and physical activity. Gender wasnot originally significant in bivariate analyses, but wasTable 1 Characteristics of fallers and non fallers, NYCHAresidents, New York City, 2009Fallers (n = 280) Non Fallers (n = 720)N (%) N (%)Social Support (n = 1000)Perceived availability 195 (69.64) 526 (73.06)Social contact 251 (89.64) 647 (89.86)Age (n = 1000)65-74 161 (57.50) 401 (55.69)75-84 95 (33.93) 264 (36.67)85+ 24 (8.57) 55 (7.64)Ethnicity/Racea (n = 1000)Black 144 (51.43) 430 (59.72)White 33 (11.79) 62 (8.61)Hispanic 95 (33.93) 193 (26.81)Asian/Pacific Islander 8 (2.86) 35 (4.86)Gender (n = 1000)Male 75 (26.79) 169 (23.47)Female 205 (73.21) 551 (76.53)Type of Household (n = 1000)Single 163 (58.21) 380 (52.78)Multiple 117 (41.79) 340 (47.22)Type of Development (n = 1000)Family 226 (80.71) 585 (81.25)Mixed 13 (4.64) 42 (5.83)Senior Only 41 (14.64) 93 (12.92)Vision Difficultiesa (n = 975b)No Difficulty 49 (18.35) 218 (30.79)Low Difficulty 137 (51.31) 338 (47.74)High Difficulty 81 (30.34) 152 (21.47)Self-Described Healtha (n = 994b)Good 69 (24.73) 328 (45.87)Not Good 210 (75.27) 387 (54.13)Presence of Health IssueDizzinessa (n = 990b) 172 (62.32) 218 (30.53)Strokea (n = 993b) 32 (11.51) 28 (3.92)Heart Attacka (n = 995b) 37 (13.26) 36 (5.03)Diabetesa (n = 995b) 135 (48.39) 229 (31.98)Osteoporosisa (n = 978b) 86 (32.09) 171 (24.08)Arthritisa (n = 988b) 211 (77.01) 404 (56.58)Depressiona (n = 988b) 88 (32.35) 77 (10.75)Physical Activitya (n = 996b)Active 175 (62.72) 542 (75.59)Inactive 104 (37.28) 175 (24.41)NYCHA New York City Housing AuthorityaChi-square values significant at p < .05bN values smaller than 1000 reflect missing data for specific covariatesDurbin et al. Injury Epidemiology  (2016) 3:4 Page 2 of 4significant in the final model. Age, ethnicity/race, visiondifficulties, heart attack, and osteoporosis were not sig-nificant covariates. Without adjustment, both perceivedavailability of social support (OR = 0.846, 95 % CI:0.620,1.146) and social contact (OR = 0.976, 95 % CI:0.620,1.538) had odds ratios below 1.00, with no indica-tion of significant effects. When adjusting for the covari-ates, perceived availability of social support still reportedan odds ratio below 1.00 (OR = 0.948, 95 % CI:0.650,1.384), while the odds ratio for social contactchanged direction to above 1.00 (OR = 1.320, 95 % CI:0.746,2.338), though neither of these adjusted effects wassignificant (Table 2).DiscussionThis study found no significant association between per-ceived availability of social support or social contact andfalls among older adults. The null finding indicates thatthere is not currently evidence to support focusing onsocial support as a prevention measure for falls. It isworth noting, however, that in the unadjusted model, so-cial contact originally had an odds ratio below 1.00, butthe directionality of the finding changed to an odds ratioabove 1.00 after covariates were added to the model. Itis possible that substantial confounding occurred, butthe close proximity of the odds ratio to 1.00 suggeststhat directionality may have changed simply due tochance. Perceived availability of social support had anodds ratio below 1.00 both before and after adjustment.In addition to being one of the first studies to examinesocial support and its relationship to fall events amongolder adults, a primary strength of this study is its popu-lation. Studies of falls among older adults have tended tofocus on sociodemographically homogenous, and par-ticularly white, populations (Chan and Fong 2013; Choiet al. 2014). Other study strengths include a large samplesize and nearly complete reporting for most variables.A major limitation of this study is the cross-sectionaldesign, which is unable to establish a temporal order be-tween fall events and the social support constructs. Thetiming mentioned in the questions is an importantlimitation as well. The falls question asks if individualsfell during the past 12 months, whereas the social con-tact variable references the “past week” and the per-ceived availability of social support variable asksindividuals to reference their perceptions about whatcould happen in the future, presumably based in part ontheir past and recent experiences. For the purposes ofthis analysis, we have treated these social support vari-ables as relatively constant variables without variationover time. However, it is very possible that after experi-encing a major event, such as a fall, that an individual’ssocial contact and perceived availability of social supportcould change dramatically, with relatives, neighbors, andothers close to the individual providing more social sup-port since the event. Individuals who were receiving lim-ited social contact and support before a fall, may havereported receiving much more contact and support atthe time of the survey’s administration.Further limitations include self-reported data and theuse of a dichotomous falls variables, which does not pro-vide as much information as would the exact number offall events experienced (Parton et al. 2011). Questionsthat were used to determine social contact and perceivedavailability of social support were not originally writtento measure these specific social support subdomains.This lack of precision in measuring each subdomaincould be the cause of the null findings. Additionally, thedataset utilized did not include many other factors that,when combined with social support, could have apositive impact on falls (medications and fall riskassessed by physician, home assessments, etc.).Future studies should thus consider using longitudinaldesigns, monthly falls calendars and the National Insti-tutes of Health (NIH) Patient Reported Outcomes Meas-urement Information System (PROMIS) measures, whichcurrently cover seven subdomains of social support pre-cisely, as they were constructed using modern measure-ment theory (Hannan et al. 2010). It is possible that whenoperationalized in a more appropriate way, social supportwill indeed be found to be associated with falls. However,it is also possible that social support does not hold anyrelevance for falls among older adults.AbbreviationsNIH: National Institutes of Health; NYCHA: New York City Housing Authority;PROMIS: Patient Reported Outcomes Measurement Information System.Competing interestsThe authors declare that they have no competing interests.Authors’ contributionsLD conducted the analysis, interpreted the results, and wrote the first draftof the manuscript. TJM helped to procure the dataset, supervised theanalysis, contributed to the results, oversaw the development of themanuscript, and provided critical revisions to the manuscript. RJK and RGcontributed to the interpretation of the results and to critical revisions of themanuscript. All authors read and approved the final manuscript.Table 2 Logistic regression models predicting fall eventsamong NYCHA residents, New York City, 2009Primary predictor(two models)Unadjusted OR(95 % confidenceInterval) (n = 1000)Adjusted OR(95 % confidenceInterval) (n = 912b)Social Contact 0.976 (0.620-1.538) 1.320a (0.746-2.338)Perceived availabilityof social support0.846 (0.625-1.146) 0.948a (0.650-1.384)NYCHA New York City Housing AuthorityaAdjusted for age, self-described health, race/ethnicity, gender, dizziness, visiondifficulties, arthritis, osteoporosis, heart attack, stroke, diabetes, depression, andphysical activitybAn n value smaller than 1000 reflects missing data for the covariates thatwere used during adjustmentDurbin et al. Injury Epidemiology  (2016) 3:4 Page 3 of 4Authors’ informationLD presented a first draft of the results in the form of a Master’s studentthesis for Columbia University’s Mailman School of Public Health. TJM actedas her first reader at the Mailman School.AcknowledgementsThis research is supported in part by Grant 1 R49 CE002096-01 from theNational Center for Injury Prevention and Control, Centers for Disease Controland Prevention to the Center for Injury Epidemiology and Prevention atColumbia University. Its contents are solely the responsibility of the authorsand do not necessarily represent the official views of the Centers for DiseaseControl and Prevention.The authors would like to thank the following contributors to this manuscript:1) a co-investigator: Hilary B. Parton, MPH, Division of Epidemiology, New YorkCity Department of Health and Mental Hygiene; 2) a co-investigator: Anne-MarieFlatley, MCP, Vice-President for Research & Management Analysis, Departmentof Research & Management Analysis, New York City Housing Authority; 3) theprincipal investigator: Lorna Thorpe, PhD, Professor, Director, Epidemiology andBiostatistics Program CUNY School of Public Health and Hunter College.Author details1Department of Epidemiology, Columbia University Mailman School of PublicHealth, 722 West 168th St., Room 516, New York, NY 10032, USA.2Department of Social Sciences, University of Alabama at Birmingham, 17202nd Ave. S, Birmingham, AL 35233, USA.Received: 24 November 2015 Accepted: 23 January 2016ReferencesBarrera M. Distinctions between social support concepts, measures, and models.Am J Clin Pathol. 1986;14(4):413–45.CDC. Home and recreational safety: important facts about falls. 2015. http://www.cdc.gov/homeandrecreationalsafety/falls/adultfalls.html. Accessed 5 Jan 2016.Chan KS, Fong KNK. Accidental falls among community-dwelling people withchronic stroke in Hong Kong. Asian J Gerontol Geriatr. 2013;8(2):61–7.Choi EJ, Kim SA, Kim NR, Rhee J, Yun Y, Shin M. Risk factors for falls in olderadults: the 2011 community health survey. J Korean Med Sci. 2014;29(11):1482–7.Cole MG, Dendukuri N. Risk factors for depression among elderly communitysubjects: a systematic review and meta-analysis. Am J Psychiatry. 2003;160:1147–56.Faulkner KA, Cauley JA, Zmuda JM, Griffin JM, Nevitt MC. Is social integrationassociated with the risk of falling in community-dwelling women? J GerontolA Biol Sci Med Sci. 2003;58A(10):954–9.Hannan MT, Gagnon MM, Aneja J, Jones RN, Cupples LA, Lipsitz LA, et al.Optimizing the tracking of falls in studies of older participants: comparison ofquarterly telephone recall with monthly falls calendars in the MOBILIZEBoston Study. Am J Epidemiol. 2010;171(9):1031–6.Hosseini H, Hosseini N. Epidemiology and prevention of fall injuries among theelderly. Hosp Top. 2008;86(3):15–20.Langford CPH, Bowsher J, Maloney JP, Lillis PP. Social support: a conceptualanalysis. J Adv Nurs. 1997;25:95–100.Parton HB, Greene R, Flatley AM, Viswanathan N, Wilensky L, Berman J, et al.Health of older adults in New York City public housing: findings from theNew York City Housing Authority Senior Survey. 2011. A joint report by theNew York City Housing Authority, the New York City Housing Authority, theNew York City Departments of Health and Mental Hygiene and for theAging, and the City University of Public Health at Hunter College.Taylor SE. Social support: a review. In: Friedman HS, editor. The Oxford Handbookof Health Psychology. New York: Oxford University Press; 2011. p. 189–214.Vink D, Aartsen MJ, Schoevers RA. Risk factors for anxiety and depression in theelderly: a review. J Affect Disord. 2008;106:29–44.Walter S, Tiemeier H. Variable selection: current practice in epidemiologicalstudies. Eur J Epidemiol. 2009;24:733–6.WHO. WHO global report on falls prevention in older age. Department of Ageingand Life Course (ALC). Geneva: WHO Press; 2007.Wills TA. Social support and interpersonal relationships. In: Clark MS, editor.Prosocial Behavior. Newbury Park, CA: Sage; 1991. p. 265–89.Submit your manuscript to a journal and benefi t from:7 Convenient online submission7 Rigorous peer review7 Immediate publication on acceptance7 Open access: articles freely available online7 High visibility within the fi eld7 Retaining the copyright to your article    Submit your next manuscript at 7 springeropen.comDurbin et al. Injury Epidemiology  (2016) 3:4 Page 4 of 4

https://academiccommons.columbia.edu/doi/10.7916/wh2z-6s21/download

Social support and older adult falls

Abstract

Similar works

Full text

Available Versions

Springer - Publisher Connector

Columbia University Academic Commons