The prevalence of risk factors for falls increases during middle-age, but the prevalence of falls in this age-range is often overlooked and understudied. The aim was to calculate the prevalence of falls in middle-aged adults (aged 40–64 years) from four countries.
Data were from four population-based cohort studies from Australia (Australian Longitudinal Study on Women’s Health, n = 10556, 100% women, 51–58 years in 2004), Ireland (The Irish Longitudinal Study on Ageing, n = 4968, 57.5% women, 40–64 years in 2010), the Netherlands (Longitudinal Aging Study Amsterdam, n = 862, 51.6% women, 55–64 years in 2012–13) and Great Britain (MRC National Survey of Health and Development, n = 2821, 50.9% women, 53 years in 1999). In each study, falls assessment was based on recall of any falls in the past year. The prevalence of falls was calculated for the total group, for each country, for men and women separately, and for 5-year age-bands. The prevalence was higher in Australia (27.8%, women only) and the Netherlands (25.1%) than in Ireland (17.6%) and Great Britain (17.8%, p<0.001). Women (27.0%) had higher prevalences than men (15.2%, p<0.001). The prevalence increased from 8.7% in 40–44 year olds to 29.9% in 60–64 year olds in women, and from 14.7% in 45–49 year olds to 15.7% in 60–64 year olds in men. Even within 5-year age-bands, there was substantial variation in prevalence between the four cohorts. Weighting for age, sex and education changed the prevalence estimates by less than 2 percentage points.
The sharp increase in prevalence of falls in middle-age, particularly among women supports the notion that falls are not just a problem of old age, and that middle-age may be a critical life stage for preventive interventions.
Citation: Peeters G, van Schoor NM, Cooper R, Tooth L, Kenny RA (2018) Should prevention of falls start earlier? Co-ordinated analyses of harmonised data on falls in middle-aged adults across four population-based cohort studies. PLoS ONE 13(8): e0201989. https://doi.org/10.1371/journal.pone.0201989
Editor: Enrico Mossello, University of Florence, ITALY
Received: April 30, 2018; Accepted: July 25, 2018; Published: August 7, 2018
Copyright: © 2018 Peeters et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The ALSWH data contain potentially identifying and sensitive information including for example date of birth, residential location and sexual preferences. The data are owned by the Australian Government Department of Health and the ALSWH is under contractual and ethical requirements to only release de-identified data to users after each request has been approved by a data access committee. The contractual requirements are between the Australian Government Department of Health and the University of Queensland (within which the ALSWH sits). The ethical conditions are imposed by the Australian Government Department of Health Human Research Ethics Committee and the Human Research Ethics Committees at the University of Queensland and the University of Newcastle. Ethical approval of the ALSWH specifies that de-identified data are only available to collaborating researchers where there is a formal request to make use of the material, and that each request has to be approved by the ALSWH Data Access Committee. Further details can be found at http://alswh.org.au/for-researchers. Data from the Longitudinal Aging Study Amsterdam (LASA) are owned by the VU University Medical Center. The LASA data are available for use for specific research questions, provided that an agreement is made up. Research proposals should be submitted to the LASA Steering Group, using a standard analysis proposal form that can be obtained from the LASA website: www.lasa-vu.nl. Files with a data published in this publication are freely available for replication purposes and can be obtained using the same analysis proposal form. The LASA Steering Group will review all requests for data to ensure that proposals for the use of LASA data do not violate privacy regulations and are in keeping with informed consent that is provided by all LASA participants. NSHD data used in this publication are available to bona fide researchers upon request to the NSHD Data Sharing Committee. NSHD data sharing policies and processes meet the requirements and expectations of the UK Medical Research Council (MRC) policy on sharing of data from population and patient cohorts: https://www.mrc.ac.uk/publications/browse/mrc-policy-and-guidance-on-sharing-of-research-data-frompopulation-and-patient-studies/. Data requests should be submitted to firstname.lastname@example.org; further details can be found at http://www.nshd.mrc.ac.uk/data.aspx. These policies and processes are in place to ensure that the use of data from this national birth cohort study is within the bounds of consent given previously by study members, complies with MRC guidance on ethics and research governance, and meets rigorous MRC data security standards. doi: 10.5522/NSHD/Q101; doi: 10.5522/NSHD/Q102. The anonymised TILDA dataset is publicly available to researchers who meet the criteria for access, at no monetary cost, from the Irish Social Science Data Archive (ISSDA) at University College Dublin (http://www.ucd.ie/issda/data/tilda/) and the Interuniversity Consortium for Political and Social Research (ICPSR) at the University of Michigan (http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/34315). TILDA also considers applications for privileged access to the dataset.
Funding: The Australian Longitudinal Study on Women’s Health was supported by the Australian Government Department of Health. The MRC National Survey of Health and Development is funded Longitudinal Aging Study Amsterdam is supported by a grant from the Netherlands Ministry of Health Welfare and Sports, Directorate of Long-Term Care. The data collection [in 2012-2013 and 2013-2014] was financially supported by the Netherlands Organization for Scientific Research (NWO) in the framework of the project “New Cohorts of young old in the 21st century” (file number 480-10-014). The Irish Longitudinal Study on GP was supported by a Global Brain Health Institute fellowship, University of California San Francisco, and Trinity College Dublin. RC was supported by the UK Medical Research Council (programme code: MC_UU_12019/4). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: Ageing (TILDA) is funded by the Irish Government and the Atlantic Philanthropies, along with support from Irish Life PLC in the form of a charitable gift. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
The high prevalence and burden of falls in older adults has been widely described [1, 2]. Meta-analyses suggest that interventions targeting adults aged 65+ could lower the risk of falls by up to 30% . But despite this, population injury rates for falls and injuries from falls continue to rise independent of the ageing of the population [4, 5], suggesting a failure of intervention strategies and/or a change in risk factor profiles of those who fall. The rising rates in injuries from falls and the ageing of the population has led to calls for new approaches to falls prevention . Current falls prevention guidelines predominantly focus on adults over the age of 65 with a high falls risk based on presence of risk factors [7, 8]. While this approach is sensible from the point of view of providing care to those with the highest need, it ignores the opportunity for early preventive interventions.
A past fall is the strongest predictor of a future fall , suggesting that primary prevention is important. The second strongest predictor of falls is abnormality of gait or balance . At the population-level, onset of declines in balance ability and other measures of physical functioning are typically observed between ages 40 and 60 [10, 11]. The prevalence of other risk factors for falls, such as syncope, dizziness and chronic conditions, also increase after the age of 50 [12, 13], particularly in women after menopause. These findings suggest that middle-age may be a critical life stage for early interventions for falls prevention.
A first step in exploring opportunities for preventive strategies at younger ages is to establish the prevalence of falls in middle-aged adults. To date, few population-based studies have examined the prevalence of falls in this age group. However, those studies that have reported on this, report prevalences ranging from 11 to 30% [4, 14]. For example, in the 2008 U.S. National Health Interview Survey, the prevalence of falls in the past year among adults aged 45–64 years was 11.4% . In the middle-aged cohort of the Australian Longitudinal Study on Women’s Health, the prevalence of falls varied between 21 and 31% between ages 53–58 and 62–67 . Studies in older adults suggest that country differences exist in the prevalence of falls [2, 16–18], indicating that published prevalences cannot be automatically extrapolated to other countries. Moreover, these studies do not show how the prevalence changes during middle-age.
The aim of this study is to calculate the prevalence of falls in middle-aged adults (aged 40–64 years) from four countries, and to examine how the prevalence changes during middle-age. Data were used from population-based cohort studies from Australia, the Netherlands, Great Britain and Ireland. These studies were selected based on the availability of falls data measured using similar methods in the relevant age-range. Previous publications from these cohort studies reported on the prevalence of falls in older adults only (e.g. [19, 20]) or reported the prevalence for the 50–64 year old group as a whole .
Materials and methods
The Australian Longitudinal Study on Women’s Health (ALSWH) is a prospective study of the health and well-being of four generations of women [22, 23]. Samples were randomly drawn from the national Medicare health insurance database, which includes all Australian citizens and permanent residents, with intentional over-representation of women from rural and remote areas . The study was approved by Ethics Committees of the Universities of Newcastle and Queensland. All participants provided informed consent. In 1996, 13714 participants from the mid-age cohort (born 1946–51) returned the baseline survey (response rate 54%). Follow-up surveys have been completed at approximately 3-year intervals. Falls data were available from the 2004 survey onward. For the current analysis, data were used from 10556 women aged 51–58 years in 2004, 9547 women aged 53–61 years in 2007 and 8995 women aged 57–64 years in 2010 with complete data on age, education and falls.
The Longitudinal Ageing Study Amsterdam (LASA) is an ongoing interdisciplinary cohort study on predictors and consequences of changes in physical, cognitive, emotional, and social functioning in men and women aged 55–85 years at baseline in 1992–93. A random sample stratified for age, sex, and expected 5-year mortality was drawn from the population registries of 11 municipalities in the Netherlands . In 2012–13, the original sample was replenished with 1023 participants aged 55–65 years. The VU University Medical Centre Ethical Review Board approved the study. All participants provided informed consent. As falls data were available in the correct age-range for participants in the 2012–13 cohort only, data from this cohort were used for the current analyses. In total, 862 participants aged 55–64 years with complete data on age, sex, education and falls were included.
The MRC National Survey of Health and Development (NSHD) is an ongoing cohort study of a nationally representative sample of 5,362 males and females born in England, Scotland and Wales during one week in March 1946 [25, 26]. The sample have now been followed up 24 times since birth. Falls data for these analyses were ascertained from nurse interviews during two of the most recent waves of data collection. In 1999, at age 53, 3035 participants were successfully contacted, of whom 2984 received a home visit from a trained nurse. In 2006–2010, at age 60–64, 2856 eligible participants (those known to be alive, living in England, Scotland or Wales and who had not permanently refused to participate) were invited for assessment at one of six clinical research facilities or to be visited by a research nurse at home of whom 2229 were assessed. Relevant ethical approval has been received from the North Thames Multi-Centre Research Ethics Committee (MREC 98/1/121) for the 1999 assessment and from the Central Manchester Local Research Ethics Committee (07/H1008/245) and the Scottish A Research Ethics Committee (08/MRE00/12) for the 2006–2010 assessment. All participants provided informed consent. In total, 2821 participants had complete data on age, sex, educational level attained and falls at age 53 and 2094 had falls data at age 60–64.
The Irish Longitudinal Study on Ageing (TILDA) is an ongoing cohort study designed to achieve a representative sample of community-dwelling people aged 50 years or older in Ireland. A random sample of 25600 residential addresses in Ireland were selected with stratification for socioeconomic status, age and geography. Each address was provided with study information and visited by field staff. All persons aged 50 years and over (primary respondents) and their spouses or partners of any age (secondary respondents) were eligible. Enrolled participants completed a computer-assisted questionnaire, self-completion questionnaire and a health assessment. All participants signed informed consent. Ethical approval has been obtained from the Trinity College Dublin Research Ethics Committee. Baseline data from the 8504 primary and secondary participants were collected between October 2009 and July 2011. For the current analyses, data were used from 4968 participants aged 40–64 years with complete data on age, sex, education and falls.
In ALSWH, participants were asked “In the last 12 months, have you: (a) had a fall to the ground?, (b) been injured as a result of a fall?, and (c) needed to seek medical attention for an injury from a fall?”. Participants with a positive response to any one of these three questions were classified as having had a fall. In LASA and TILDA, participants were asked “Have you fallen in the last year?” In the NSHD, participants were asked “Have you fallen at all in the past 12 months?”. Participants who responded ‘yes’ were classified as having had a fall.
Socio-economic and health variables.
Age, sex, level of education and self-rated health were included to describe the sample. In each cohort, level of education was based on the highest level of qualification attained. The cohort-specific response options were harmonised to match the categories of ‘none or primary education’, ‘secondary education’ and ‘tertiary education’. Although slight variations in wording were used, all cohorts assessed self-rated health with a question similar to “In general, would you say your health is: excellent, very good, good, fair or poor?” The response options were collapsed into ‘excellent-good’ and ‘fair-poor’. The wording of the response options varied slightly in LASA, but were also collapsed into the highest three (excellent-fair) versus the lowest two categories (sometimes good and sometimes bad-poor). BMI was calculated based on height and weight (kg/cm2) self-reported in ALSWH and measured in LASA, NSHD and TILDA. Diabetes and arthritis were based on self-report.
The cohorts were described using descriptive statistics. Cohort characteristics were compared using ANOVA for continuous variables and chi-squared test for categorical variables. Crude and weighted prevalence estimates and 95% confidence intervals were calculated for the total sample within each of the cohorts as well as for men and women separately. The weighted prevalence estimates accounted for deviations in the samples from the underlying population at the year of data collection in the distribution of age, sex and level of education. Weights were used to ensure the prevalence estimates were representative of the general population the sample was drawn from. As the Australian cohort included women only, weights were based on age and level of education. In the British cohort, the weights were based on age, sex and fathers occupational status at birth (i.e. manual vs non-manual and agricultural workers) due to lack of availability of comparable census data on education. Finally, prevalence was calculated for each 5-year age-band within each of the cohorts to depict the trend in prevalence with age. Sensitivity analyses were done for 4- and 6-year age-bands to examine the influence of using different age-band widths. Changes in prevalence with age were examined using chi-squared tests. Differences in prevalence by country and sex were examined using chi-squared tests.
Each cohort has unique features (Table 1). The ALSWH cohort includes a large sample (n = 10556) of women only. The TILDA cohort covers the full age-range of 40–64 years. The LASA cohort includes the most recent data (collected in 2012/13). The ALSWH and NSHD cohorts each have falls data collected at 3 and 2 time points spanning 6 and 10 years of follow-up, respectively.
Across the cohorts, the crude prevalence of falls in the previous year varied from 12.8% in 53 year old men in Great Britain (NSHD) to 31.4% in 53–61 year old women in Australia (ALSWH) (Table 2). Weighting for age, sex and education had little influence on the prevalence estimates (i.e. less than 2 percentage points). Overall, the prevalence was higher in Australia (27.8%, women only) and the Netherlands (25.1%) than in Ireland (17.6%) and Great Britain (17.8%, p<0.001). Women (27.0%) had higher prevalences than men (15.2%, p<0.001). In women, the prevalence of falls increased with age from 8.7% in 40–44 year olds, 19.1% in 45–49 year olds, 20.9% in 50–54 year olds, 27.3% in 55–59 year olds, to 29.9% in 60–64 year olds (p<0.001). In men, the prevalence of falls increased with age from 14.7% in 45–49 year olds, 13.4% in 50–54 year olds, 19.3% in 55–59 year olds, to 15.7% in 60–64 year olds (p<0.001). However, there is substantial variation in prevalence between the cohorts within any specific age-band (Fig 1). For example, in 60–64 year old women, the prevalence ranged from 20% in TILDA to 31.4% in ALSWH. Sensitivity analyses estimating the prevalence in 4- and 6-year age-bands strengthen the observation that the prevalence of falls increased with age in women, but less so in men (S2 Fig).
Prevalence of falls per 5-year age band in middle-aged women (top) and men (bottom). Presented are the prevalence of falls per 5-year age bands based on the harmonised data across the four cohorts, and the number of participants providing data in each 5-year age band. Note that ALSWH and NSHD participants could be included more than once if they provided data at multiple data collection waves while still falling within the defined age bands.
Across the four cohorts, the prevalence of falls ranged from 8.7% to 31.1%, and varied by age-group, sex and country. On average, the prevalence was markedly higher than the 11.4% found in 45–64 year old adults in the 2008 U.S. National Health Interview Survey and the 2-year prevalence of 21% in 45–64 your old adults in the Baltimore Longitudinal Study of Aging . In addition to age and sex, factors that explain this variation in prevalence between countries include variations in prevalence of key fall risk factors and the measurement of falls. This will be discussed in the following paragraphs. Regardless of the differences in absolute prevalences between the countries, there is consistent evidence of an increase in prevalence of falls across mid-life, particularly in women.
Age is the factor most likely to explain the variation in prevalence between the countries. As shown in the current and previous studies, falls risk increases with age [1, 28]. One would therefore expect the prevalence to be higher in cohorts with older average age. Indeed, the prevalence was higher in cohorts that were older at the time of assessment (Table 2). However, even within 5-year age-bands, substantial variation in prevalence was found between the cohorts. For example, within the 60–64 year old women, the prevalences were 20.1% in Ireland, 22.7% in Great Britain, 28.7% in The Netherlands and 31.1% in Australia (Fig 1). This suggests that other factors also play a role, such as socio-demographic, health and lifestyle factors.
In adults over the age of 65, women typically have a higher prevalence of falls than men [2, 28]. For example, a meta-analyses of observational studies showed that women have a 1.3 times higher odds of falls than men . The current study also confirms this for 40–64 year olds. The sex-differences in prevalence were more pronounced in the Netherlands and Great Britain than in Ireland (Table 2). The Australian cohort included women only and also reported the highest prevalence. It therefore seems likely that differences in sex distribution contribute to the variation in prevalence between countries. A potential explanation for the stronger increase in prevalence of falls during midlife in women than men may be explained by the concurrent stronger increase in prevalence of risk factors for falls, such as arthritis and cardiovascular diseases, post menopause in women.
The four cohorts were designed to be nationally representative and included mainly Western-Europeans. The Australian cohort included mostly women born in Australia of British or Irish descendency (77.8%). Few studies have examined ethnic differences in falls risk of older adults and the findings are inconsistent, but there is some evidence that falls risk may be lower in African Americans than in White Americans [16, 18] and lower in Asians than in Caucasians globally [16, 17]. Hence the current results may not be generalizable to other populations with different ethnic backgrounds.
Many risk factors for falls have been identified in older adults. It is yet unclear whether the same risk factors are important in middle-aged adults. In older adults, some of the strongest risk factors include mobility limitations and chronic conditions such as diabetes and arthritis . Indeed, the prevalence of diabetes and arthritis were higher in the Dutch cohort than in the British and Irish cohorts (Table 1) and could partly explain the higher prevalence of falls in this cohort. In contrast, the prevalence of arthritis was lower in the Australian cohort than in the Dutch cohort, while the prevalence of falls was higher in the Australian cohort. A previous study by our group found that, diabetes was not identified as a risk factor of falls in Australian middle-aged women, but presence of joint symptoms was . That study also found that different factors were associated with falls at early, middle and later midlife, highlighting the complexity of falls risk at this life stage . For example, high levels of alcohol intake and hearing problems were significant predictors of falls at ages 59–67, but not at earlier ages . The differences found by age, sex and country could be explained by variations by age, sex and country in risk factors for falls. Further research is required to identify key risk factors of falls in middle-age.
Finally, the variation in prevalence between the cohorts may also be partially explained by differences in measurement of falls. While there was little variation in the wording used to ask participants about falls in the past year, there were variations in how the questions were presented. The Irish, British and Dutch cohorts use a conditional approach whereby follow-up questions about the consequences of a fall are only asked if the participant responds positively to the first question about a fall in the past year. In the Australian cohort, the question specifically asked about ‘falls to the ground’ and the follow-up questions about the consequences of a fall are visible in the survey to all participants. It may be that the specific wording and these follow-up questions facilitate the recall of falls. Moreover, in the Australian cohort, some participants responded ‘yes’ to either ‘having had an injury from a fall’ or ‘seeking medical attention after a fall’, but not to the actual falls question. As one cannot have an injury from a fall without actually having a fall, these participants were classified as fallers. This resulted in a 2–2.6 percentage point increase in the prevalence of fallers at each survey. Follow-up questions about the consequences of falls may help improve recall and reduce misclassification.
Falls are currently perceived as a major problem in older adults, but receive little attention in middle-age. While the prevalence of falls is lower in middle-aged adults than in older adults, the current findings show that the prevalence is not low. Previous studies have suggested a U-shaped association between age and fall risk, in which the fall risk is highest in children and seniors . This may result in the misperception that falls are not of concern in middle-aged adults. While falls that result in injuries have the greatest impact on health services use, any fall, with or without injury, can result in fear of falling and avoidance of physical or social activities [20, 30]. Therefore all falls have the potential to influence wellbeing . Repeating the analyses for ‘falls requiring medical attention’ (S2 Fig) showed similar trends as for all falls (Fig 1). However, data were available only for the Irish and Australian cohorts, and for the 2006–2010 assessment in the British cohort. On average, a third of all reported falls (32%) required medical attention,which is similar to the proportion reported for older adults [14, 30]. Moreover, the current data show a marked increase in prevalence from 8.7% at age 40–45 to 19.1% at age 45–50 in Irish women (Fig 1). The timing of this increase in falls coincides with the onset of menopause , decline in balance performance  and increase in prevalence of syncope and vertigo [12, 13]. These collective findings warrant further research to inform preventive strategies in middle-aged adults. A better understanding of the factors that drive this increase in fall risk in middle-age may be the key to effective preventive interventions earlier in life with potential sustained benefits into older age.
Strengths and limitations
Strengths of this study include the use of data from four population-based cohort studies with a total of 19207 participants. The large sample enabled subgroup comparisons by age and sex and provided insight into variations in prevalence estimates across countries. As is common in cohort studies, participants included in the analyses are likely healthier than those who refused to participate or dropped out . The current prevalence estimates may therefore underestimate the true prevalence of falls in 40–64 year old adults. By weighting the prevalence estimates for age, sex and education, we compensated for potential selective drop-out or deviations in the cohorts from the national distribution. The weighted prevalence estimates were slightly lower (<2 percentage points) than the crude prevalence rates. This is likely to be explained by the underrepresentation of participants at the lower end of the age-range. Another limitation of this study is that the falls data were based on self-report. All cohorts used a 12-month recall, which has 89% agreement with medical records data . Although calendar-based methods are preferred, underreporting of falls is an issue with all methods used .
Across the four cohorts, the annual prevalence of falls ranged from 8.7% to 31.1% depending on age-group, sex and country. The prevalence was higher in women than in men and increased with age. There was substantial variation in the prevalence of falls between the four countries, even within 5-year age-bands, which are likely explained by differences in sample characteristics such as age, sex, ethnicity and chronic conditions. The sharp increase in prevalence of falls in middle-age, particularly among women, supports the notion that falls are not just a problem of old age, and that middle-age may be a critical life stage for preventive interventions. Further research to inform preventive strategies in middle-aged adults is warranted.
Prevalence of falls per 4- and 6-year age bands in middle-aged women (top) and men (bottom). Presented are the prevalence of falls per 4-year age bands (left panels) and 6-year age bands (right panels) based on the harmonised data across the four cohorts, and the number of participants providing data in each age band. ALSWH participants could be included more than once if they provided data at multiple data collection waves while still falling within the defined age bands.
Prevalence of falls requiring medical attention per 5-year age band in middle-aged women (top) and men (bottom). Presented are the prevalence of falls requiring medical attention per 5-year age bands based on the harmonised data across the four cohorts, and the number of participants providing data in each 5-year age band. Note that data were available for ALSWH, NSHD (wave 2006–2010 only) and TILDA, but not for LASA. ALSWH participants could be included more than once if they provided data at multiple data collection waves while still falling within the defined age bands.
We are grateful to NSHD study members for their continuing support. We are grateful to all of the LASA and TILDA respondents for participating in the study. Some of the research on which this article is based was conducted as part of the Australian Longitudinal Study on Women’s Health by The University of Newcastle and The University of Queensland. We are grateful to the women who provided the survey data.
- 1. Cigolle CT, Ha J, Min LC, Lee PG, Gure TR, Alexander NB, et al. The epidemiologic data on falls, 1998–2010: More older americans report falling. JAMA Internal Medicine. 2015. pmid:25599461
- 2. Morrison A, Fan T, Sen SS, Weisenfluh L. Epidemiology of falls and osteoporotic fractures: a systematic review. Clinicoecon Outcomes Res. 2013;5:9–18. Epub 2013/01/10. pmid:23300349; PubMed Central PMCID: PMCPMC3536355.
- 3. Gillespie LD, Robertson MC, Gillespie WJ, Sherrington C, Gates S, Clemson LM, et al. Interventions for preventing falls in older people living in the community. The Cochrane database of systematic reviews. 2012;9:CD007146. Epub 2012/09/14. pmid:22972103.
- 4. Verma SK, Willetts JL, Corns HL, Marucci-Wellman HR, Lombardi DA, Courtney TK. Falls and Fall-Related Injuries among Community-Dwelling Adults in the United States. PLoS One. 2016;11(3):e0150939. Epub 2016/03/16. pmid:26977599; PubMed Central PMCID: PMCPMC4792421.
- 5. AIHW: Pointer S. Trends in hospitalised injury, Australia 1999–00 to 2010–11. Canberra: Australian Institute of Health and Welfare, 2013 30 Nov 2012. Report No.: Cat. no. INJCAT 145.
- 6. Watson WL, Li Y, Mitchell RJ. Projections of hospitalised fall-related injury in NSW, Australia: impacts on the hospital and aged care sectors. J Safety Res. 2011;42(6):487–92. Epub 2011/12/14. pmid:22152266.
- 7. Preventing Falls and Harm From Falls in Older People—Best Practice Guidelines for Australian Community Care 2009: Australian commission on safety and quality in health care; 2009. 202 p.
- 8. National Steering Group on the Prevention of Falls in Older People and the Prevention and Management of osteoporosis throughout life. Strategy to Prevent Falls and Fractures in Ireland's Ageing Population. Dublin: Health Service Executive, 2008.
- 9. Ganz DA, Bao Y, Shekelle PG, Rubenstein LZ. Will my patient fall? JAMA. 2007;297(1):77–86. Epub 2007/01/04. pmid:17200478.
- 10. Peeters G, Dobson AJ, Deeg DJ, Brown WJ. A life-course perspective on physical functioning in women. Bull World Health Organ. 2013;91(9):661–70. Epub 2013/10/09. pmid:24101782; PubMed Central PMCID: PMCPMC3790225.
- 11. Choy NL, Brauer S, Nitz J. Changes in postural stability in women aged 20 to 80 years. J Gerontol A Biol Sci Med Sci. 2003;58(6):525–30. Epub 2003/06/17. pmid:12807923.
- 12. Ruwald MH, Hansen ML, Lamberts M, Hansen CM, Hojgaard MV, Kober L, et al. The relation between age, sex, comorbidity, and pharmacotherapy and the risk of syncope: a Danish nationwide study. Europace. 2012;14(10):1506–14. Epub 2012/05/17. pmid:22588456.
- 13. Neuhauser HK, Lempert T. Vertigo: epidemiologic aspects. Semin Neurol. 2009;29(5):473–81. Epub 2009/10/17. pmid:19834858.
- 14. Talbot LA, Musiol RJ, Witham EK, Metter EJ. Falls in young, middle-aged and older community dwelling adults: perceived cause, environmental factors and injury. BMC Public Health. 2005;5:86. Epub 2005/08/20. pmid:16109159; PubMed Central PMCID: PMC1208908.
- 15. White AM, Tooth LR, Peeters GMEE. Fall risk factors in mid-age women: the Australian Longitudinal Study on Women's Health. Am J Prev Med. 2018;54(1):51–63. Epub Accepted 6 Sept 2017. pmid:29254554
- 16. Geng Y, Lo JC, Brickner L, Gordon NP. Racial-Ethnic Differences in Fall Prevalence among Older Women: A Cross-Sectional Survey Study. BMC Geriatr. 2017;17(1):65. Epub 2017/03/13. pmid:28284206; PubMed Central PMCID: PMCPMC5346231.
- 17. Han BH, Ferris R, Blaum C. Exploring ethnic and racial differences in falls among older adults. J Community Health. 2014;39(6):1241–7. Epub 2014/03/04. pmid:24585104.
- 18. Nicklett EJ, Taylor RJ. Racial/Ethnic predictors of falls among older adults: the health and retirement study. J Aging Health. 2014;26(6):1060–75. Epub 2014/07/10. pmid:25005171; PubMed Central PMCID: PMCPMC4227632.
- 19. Tromp AM, Smit JH, Deeg DJ, Bouter LM, Lips P. Predictors for falls and fractures in the Longitudinal Aging Study Amsterdam. J Bone Miner Res. 1998;13(12):1932–9. Epub 1998/12/09. pmid:9844112.
- 20. Peeters GM, Jones M, Byles J, Dobson AJ. Long-term Consequences of Noninjurious and Injurious Falls on Well-being in Older Women. J Gerontol A Biol Sci Med Sci. 2015;70(12):1519–25. pmid:26273020.
- 21. Bhangu J, King-Kallimanis BL, Donoghue OA, Carroll L, Kenny RA. Falls, non-accidental falls and syncope in community-dwelling adults aged 50 years and older: Implications for cardiovascular assessment. PLoS One. 2017;12(7):e0180997. Epub 2017/07/22. pmid:28732008; PubMed Central PMCID: PMCPMC5521793.
- 22. Lee C, Dobson AJ, Brown WJ, Bryson L, Byles J, Warner-Smith P, et al. Cohort Profile: the Australian Longitudinal Study on Women's Health. Int J Epidemiol. 2005;34(5):987–91. Epub 2005/05/17. pmid:15894591.
- 23. Dobson AJ, Hockey R, Brown WJ, Byles JE, Loxton DJ, McLaughlin D, et al. Cohort Profile Update: Australian Longitudinal Study on Women's Health. Int J Epidemiol. 2015;44(5):1547,a-f. Epub 2015/07/02. pmid:26130741.
- 24. Huisman M, Poppelaars J, van der Horst M, Beekman AT, Brug J, van Tilburg TG, et al. Cohort profile: the longitudinal aging study amsterdam. Int J Epidemiol. 2011;40(4):868–76. Epub 2011/01/11. pmid:21216744.
- 25. Kuh D, Pierce M, Adams J, Deanfield J, Ekelund U, Friberg P, et al. Cohort Profile: Updating the cohort profile for the MRC National Survey of Health and Development: a new clinic-based data collection for ageing research. Int J Epidemiol. 2011;40(1):e1–e9. pmid:21345808
- 26. Wadsworth M, Kuh D, Richards M, Hardy R. Cohort Profile: The 1946 National Birth Cohort (MRC National Survey of Health and Development). Int J Epidemiol. 2006;35(1):49–54. Epub 2005/10/06. pmid:16204333.
- 27. Kearney PM, Cronin H, O'Regan C, Kamiya Y, Savva GM, Whelan B, et al. Cohort profile: the Irish Longitudinal Study on Ageing. Int J Epidemiol. 2011;40(4):877–84. Epub 2011/08/04. pmid:21810894.
- 28. Deandrea S, Lucenteforte E, Bravi F, Foschi R, La Vecchia C, Negri E. Risk factors for falls in community-dwelling older people: a systematic review and meta-analysis. Epidemiology. 2010;21(5):658–68. Epub 2010/06/30. pmid:20585256.
- 29. Granacher U, Muehlbauer T, Gollhofer A, Kressig RW, Zahner L. An intergenerational approach in the promotion of balance and strength for fall prevention—a mini-review. Gerontology. 2011;57(4):304–15. Epub 2010/08/20. pmid:20720401.
- 30. Stel VS, Smit JH, Pluijm SM, Lips P. Consequences of falling in older men and women and risk factors for health service use and functional decline. Age Ageing. 2004;33(1):58–65. Epub 2003/12/30. pmid:14695865.
- 31. Schoenaker DAJM Jackson CA, Rowlands JV Mishra GD. Socioeconomic position, lifestyle factors and age at natural menopause: a systematic review and meta-analyses of studies across six continents. Int J Epidemiol. 2014;43(5):1542–62. WOS:000343972200028. pmid:24771324
- 32. Brilleman SL, Pachana NA, Dobson AJ. The impact of attrition on the representativeness of cohort studies of older people. BMC Med Res Methodol. 2010;10:71. Epub 2010/08/07. pmid:20687909; PubMed Central PMCID: PMC2927605.
- 33. Hale WA, Delaney MJ, Cable T. Accuracy of patient recall and chart documentation of falls. J Am Board Fam Pract. 1993;6(3):239–42. Epub 1993/05/01. pmid:8503294.
- 34. Ganz DA, Higashi T, Rubenstein LZ. Monitoring falls in cohort studies of community-dwelling older people: effect of the recall interval. J Am Geriatr Soc. 2005;53(12):2190–4. Epub 2006/01/10. pmid:16398908.