Sage Journals: Discover world-class research

Abstract

Risk factors for hip fracture in Japanese older populations are understudied compared with Western countries arguably due to the relatively lower prevalence rates in Japan. Nationally representative data from the Nihon University Japanese Longitudinal Study of Aging were analyzed using logistic regression to examine possible risk factors of hip fractures, separately for older women (n = 2,859) and older men (n = 2,108). Results showed that older Japanese women with difficulty bending their knees (OR = 1.9), with diabetes (OR = 1.7 times), and/or with more activity of daily living limitations (OR = 1.1) had higher risks of hip fracture. Older Japanese men with difficulty bending their knees (OR = 2.6), who use more external prescription drugs (OR = 1.9), and with cancer (OR = 2.0 times) had higher risks of hip fracture. Further considerations of gender- and culture-specific factors along with the identified risk factors may provide insights into future intervention programs for hip fracture in Japanese older populations.

Keywords

falls gender-specific risk factors injury geriatrics

Introduction

Older adults experiencing hip fractures may find their lives irrevocably changed. The estimated number of new cases of hip fracture in Japan was 117,900 in 2002, doubling from the 53,000 cases reported in 1987. Hip fracture is the third leading cause of becoming bedridden following stroke and frailty due to advanced old age in Japan (Ministry of Health Labour and Welfare, 2005). Furthermore, the risk of mortality increases due to the severe injury and complications after hip fracture (Hasegawa, Suzuki, & Wingstrand, 2007). Even in cases of successful recovery, increased needs for extensive care and institutionalization are often reported (Alexander, Rivara, & Wolf, 1992; Yoshimura, Suzuki, Hosoi, & Orimo, 2005).

Preventing hip fracture is a public health priority in the Japanese society given the ongoing transition to the super-aging society. By 2050, the population age 65 years and older is expected to reach 40% of the total Japanese population (Cabinet Office, 2007). Even if the age-specific incidence rates of hip fractures stay constant, the total number of individuals experiencing hip fracture is likely to follow the number of older adults (Cummings & Melton, 2002). Hip fracture is known to be an expensive injury due to intensive medical treatment and follow-up care (Cummings & Melton, 2002; Rizzo et al., 1998). In addition to the current pension budget crisis, further medical expense would be tremendous burden on the Japanese society (Kunieda, 2002).

More than 90% of hip fractures are attributable to falls in the older population (Youm, Koval, Kummer, & Zuckerman, 1999). Constructing hip fracture prevention strategies requires an understanding of the risk factors for falls. Thus, sources of potential risk factors for hip fracture will be identified from the literature about falls risk factors. Many studies have identified risk factors of hip fracture in Western countries (Otaka, Riu, Uzawa, & Chino, 2003). Given the known gender differences in hip fracture risk factors (Cummings et al., 1995), this study conducts analyses of risk factors separately for women and men. Although some Japanese studies investigated risk factors of hip fracture using the large samples (Suzuki et al., 1997), further population-level research is necessary for developing higher quality intervention programs from public health perspectives. The purpose of this study is to identify the risk factors of hip fracture in the relatively understudied population of Japanese older adults using nationally representative data.

Materials and Method

Study Population

This study used data from the first wave of the Nihon University Japanese Longitudinal Study of Aging (NUJLSOA) initiated by the Nihon University Center for Information Networking in 1999. NUJLSOA used a multistage probability sampling method to collect nationally representative data of Japanese older adults age 65 and older. Trained interviewers conducted face-to-face interviews using a structured questionnaire. Those who were 75 years and older were oversampled for the purpose of detailed analysis of the oldest old population. The NUJLSOA survey included a wide range of questions such as demographic information, socioeconomic status, medical history, lifestyle, and health/disability status of Japanese older adults. For this study, only community-dwelling older adults (N = 4,967) were analyzed after excluding those who were institutionalized (n = 30).

Response Variable

The respondents who answered yes to the question, “Have you ever experienced or are currently experiencing fractures fissures (femur, hips)?” were coded 1 and others were coded 0 for the variable hip fracture.

Predictor Variables

Risk factors of falls and hip fracture were selected as predictor variables. A collection of potential risk factors along with relevant references are displayed in Table 1. Potentially related factors and available variables in the NUJLSOA Wave 1 including demographic and socioeconomic factors, medical conditions, functional limitations and physical health, and environmental factors are also identified in this table.

Table 1.

Risk Factors of Falls and Hip Fractures in Older Population

Category	Fall and fracture risk factors	Reference
Demographic and socioeconomic	Age	Wei, Hu, Wang, and Hwang, 2001 ^a; Tromp et al., 2001 ^b
	Female gender	Tromp et al., 2001 ^b
	Education	Pluijm et al., 2006 ^b,c
Medical conditions	Stroke	Suzuki et al., 1997 ^a; Lau et al., 2001 ^a; Wei et al., 2001 ^a
	Dementia	Rubenstein and Josephson, 2002 ^b
	Cataract	Wei et al., 2001 ^a
	Osteoporosis	Lau, Woo, Leung, and Swaminthan, 1993 ^b; Kanis, Johnell et al., 1999 ^b,c
	Use of medication	Lau et al., 2001 ^a,c; Grisso et al., 1997 ^a
	Sleep disturbance	Suzuki et al., 1997 ^a
	Hormone therapy	Cummings et al., 1995 ^a
	History of falls	Lau et al., 2001 ^a; Cummings et al., 1995 ^a; Tromp et al., 2001 ^b; Pluijm et al., 2006 ^b
	History of fracture	Fujiwara, Kasagi, Yamada, and Kodama, 1997 ^a; Wei et al., 2001 ^a
	Knee osteoarthritis	Wei et al., 2001 ^a,c
	Incontinence	Tromp et al., 2001 ^b
Functional limitation and physical health	Lower body weight	Suzuki et al., 1997 ^a
	BMI	Suzuki et al., 1997 ^a,c; Fujiwara et al., 1997 ^a,c; Kanis et al., 1999 ^a,c; Wei et al., 2001 ^a,c
	Alcohol intake	Suzuki et al., 1997 ^a,c; Fujiwara et al., 1997 ^a; Lau et al., 2001 ^a,c; Cummings et al., 1995 ^a,c; Pluijm et al., 2006 ^b,c
	Visual impairment	Tromp et al., 2001 ^b; Dargent-Molina and Favier, 1996 ^b
	Giving birth to five or more children A	Fujiwara et al., 1997 ^a,c
	Weight	Grisso et al., 1997 ^a,c; Cummings et al., 1995 ^a,c
	Height	Grisso et al., 1997 ^a; Tromp et al., 2001b,^c
	Lower limb dysfunction	Grisso et al., 1997 ^a
	Functional limitations	Cummings et al., 1995 ^a; Tromp et al., 2001 ^b; Dargent-Molina and Favier, 1996 ^b
Lifestyle	Calcium intake	Lau et al., 2001 ^a,c; Kanis et al., 1999 ^a,c
	Coffee/tea consumption	Suzuki et al., 1997 ^a; Kanis et al., 1999 ^a
	Eating fish	Suzuki et al., 1997 ^a,c
	Milk intake	Fujiwara et al., 1997 ^a,c
	Physical activity	Lau et al., 2001 ^a,c; Grisso et al., 1997 ^a,c; Kanis et al., 1999 ^a,c
	Smoking	Lau et al., 2001 ^a; Kanis et al., 1999 ^a; Cummings et al., 1995 ^a
	Alcohol intake	Suzuki et al., 1997 ^a,c; Fujiwara et al., 1997 ^a; Lau et al., 2001 ^a,c; Kanis et al., 1999 ^a,c
Environment	Living in rural areas	Suzuki et al., 1997 ^a
	Use of Western style bed	Suzuki et al., 1997 ^a
	Direct hip impact when fall	Wei et al., 2001 ^a
	Presence of dogs/cats in the house	Pluijm et al., 2006

Note: BMI = body mass index. This table included the risk factors only from major Japanese studies and comparatively recent studies.

Risk factors of falls/recurrent falls.

Risk factor of fracture.

Protective factors.

Demographic and socioeconomic factors

Age and education were included in the analyses. Age is a continuous variable. Education was reported as the respondent’s last education level completed and has six levels: (a) junior high school, (b) high school, (c) schools for specialized studies, (d) junior college, (e) university, and (f) graduate school. The education variables were dichotomized into (0) less than high school or (1) higher than high school education due to the highly skewed distribution showing that the majority of respondents had high school or less education completed.

Medical conditions and history

The indicators of dementia, heart problem, cancer, diabetes, cataracts, glaucoma, arthritis, osteoporosis, and back pain were included in the analysis. Each variable was coded whether the respondents had the condition (1) or not (0). For medication use, the total number of internal prescribed medications and nonprescribed medications used were separately taken into account. The external prescribed medications variable was dichotomized into the respondents who used at least one external prescribed medication (1) and those who did not (0) given the highly skewed distribution. When female respondents gave birth to more than five children, they were coded 1 and others 0.

Functional limitation and physical health characteristic

Activity of daily living (ADL) and instrumental activity of daily living (IADL) were included as variables to assess functional limitations. The ADL variable corresponded to the number of ADL problems associated with eating, dressing, showering, getting out of bed, walking across room, going outside of house, and toileting experienced by an individual. The IADL variable corresponded to the number of IADL problems, including difficulty with preparing meals, shopping, taking care of bills, using telephone, cleaning, taking a bus, and managing medications. Body mass index (BMI) was calculated as weight (kg)/height (m)². The variable height (cm) was also taken into account. Variables measuring physical ability included walking 200 to 300 m; grasping with fingers and bending knee were coded 1 if the respondents had difficulty performing or 0 if they did not, respectively. A self-rated variable of overall health was coded 1 if the respondents reported positive health as very healthy, healthier than average, or average health, and the other was coded 0.

Environmental factor

The variable rural was coded 1 if the respondents reported living in farming or fishing village and was coded 0 if they reported living in city or suburb areas. This variable accounts for the geographical difference in diet. Japanese people living in rural areas are more likely to have higher salt intake than those in urban areas (Yamaguchi, 1995). Higher salt intake is associated with lower bone density among postmenopausal women (Devine, Criddle, Dick, Kerr, & Prince, 1995); therefore, it may be a relevant factor of hip fracture (Suzuki et al., 1997).

Statistical Methods

Summary statistics for the predictor variables were computed for the respondents with hip fracture and those without hip fracture, separately for women and men. Means and standard deviations for continuous variables, and percentages for dichotomous variables were computed. Independent t tests were used to assess differences in means between those with hip fracture and those without for continuous variables, and chi-square tests were used to assess differences for categorical variables. Logistic regression was used to model the odds of hip fracture on demographic and socioeconomic factors, medical condition, functional limitation and physical health, lifestyle, and environmental factors (Hosmer & Lemeshow, 2004). All analyses were performed with the Statistical Analysis System (SAS) software version 9.1 (SAS Institute, Cary, North Carolina).

Results

Table 2 shows a comparison of predictor variables between individuals with and without hip fracture stratified by gender: women (n = 2,859) and men (n = 2,108). Overall, 349 out of 4,967 or 7% of the respondents had at least one hip fracture. The respondents with hip fracture were, on average, 1 year older than individuals not experiencing a hip fracture (76.6 vs. 75.3), and their prevalence rates of diabetes (13% vs. 8%), osteoporosis (13% vs. 7%), the number of internal prescription drugs (2.5 vs. 2.1), and use of external prescription drugs (37% vs. 25%) were higher compared with those without. In addition, the respondents with hip fracture reported more difficulty bending their knee (45% vs. 24%), higher mean number of difficulty with ADLs (1.0 vs. 0.4) or IADLs (1.4 vs. 0.90), and lower self-rated health (54% vs. 67% for positive self-rated health) compared with those without, respectively.

Table 2.

Summary Statistics for Japanese Older Adults by Gender. Means (SD) Reported for Numeric Variables and Percentages for Dichotomous Variables

	Female (n = 2,859)		Male (n = 2,108)		Total (N = 4,967)
	With hip fracture n = 200	No hip fracture n = 2,659	With hip fracture n = 149	No hip fracture n = 1,959	With hip fracture n = 349	No hip fracture n = 4,618
Demographic and socioeconomic factors
Female	—	—	—	—	57%	57%
Age	77.4 (6.58)**	75.8 (6.47)	75.6 (6.07)*	74.5 (6.39)	76.6 (6.42)***	75.3 (6.47)
More than high school education	2%	2%	9%	10%	5%	5%
Medical condition
Dementia	4%	2%	3%	2%	3%	2%
Cancer	2%	4%	8%*	4%	5%	4%
Heart problem	17%	17%	20%	16%	18%	16%
Diabetes	15%***	7%	10%	9%	13%***	8%
Cataracts	35%	30%	25%	19%	31%	25%
Glaucoma	5%	3%	1%	2%	3%	2%
Back pain	25%**	17%	11%	12%	19%	15%
Arthritis	23%	19%	14%	10%	19%	15%
Osteoporosis	20%***	11%	4%*	1%	13%***	7%
Prescription drug (internal)	2.7 (2.57)**	2.1 (2.20)	2.44 (2.58)	2.11 (2.36)	2.59 (2.57)**	2.13 (2.27)
Prescription drug (external)^a	41.5% ***	29.0%	31.5%***	19.1%	37.3%***	24.8%
Nonprescribed drug	0.4 (0.81)	0.3 (0.81)	0.32 (0.72)	0.32 (0.82)	0.40 (0.78)	0.35 (0.81)
Functional limitation and physical health
Difficulty to grasp with fingers	9%*	5%	4%	5%	7%	5%
Difficulty to bend knee	54%***	29%	33%***	18%	45%***	24%
ADL	1.3 (2.22)***	0.5 (1.45)	0.5 (1.56)	0.4 (1.34)	1.0 (2.01)***	0.4 (1.40)
IADL	1.7 (2.37)***	0.9 (1.80)	1.0 (1.78)	0.9 (1.74)	1.46 (2.1)***	0.9 (1.77)
Positive self-rated health	46%***	65%	64%	69%	54%***	67%
Height (cm)	149.2 (6.73)	149.3 (5.67)	161.0 (6.61)	161.3 (6.417)	154.3 (8.86)	154.4 (8.40)
BMI	21.8 (3.65)	22.0 (3.46)	21.9 (3.20)	22.0 (2.96)	21.9 (3.46)	22.0 (3.26)
Five or more natural children*	8%	8%	—	—	—	—
Lifestyle
Drinking	15%	16%	53%	54%	31%	32%
Smoking	6%	5%	33%	29%	18%	15%
Environmental factors
Living in rural areas	40%	40%	42%	39%	41%	40%

Note: ADL = activity of daily living; IADL = instrumental activity of daily living; BMI = body mass index. Bivariate tests: t test for continuous variables, chi-square test for categorical variables.

Use at least one external prescription drug versus use no external prescription drug.

p < .05. **p < .01. ***p < .001.

Among older women, those with hip fracture were older (77.4 vs. 75.8) and reported higher prevalence of diabetes (15% vs. 7%), back pain (25% vs. 17%), osteoporosis (20% vs. 11%), higher average number of internal (2.7 vs. 2.1) prescription drugs, and more use of external prescription drugs (42% vs. 29%) than those without. In addition, women who had a hip fracture were more likely to report difficulty with grasping with fingers (9% vs. 5%), bending their knee (54% vs. 29%), along with more ADL (1.3 vs. 0.5) and IADL (1.7 vs. 0.9) difficulties, and lower self-rated health (46% vs. 65%) compared with those without, respectively.

Among older men, those who had hip fracture were older (75.6 vs. 74.5) and had higher prevalence rates of cancer (13% vs. 8%) and use of external prescribed drugs (32% vs. 19%) when compared with those men without hip fracture. In addition, older men who had a hip fracture were more likely to report difficulty to bend knee (33% vs. 15%).

Table 3 shows the results of logistic regression analyses for women and men. Among older Japanese women, diabetics had 1.7 times the odds of hip fracture (95% confidence interval [CI] = [1.1, 2.6]) than those nondiabetics holding all other risk factors constant. Whereas older women with difficulty bending their knee and more difficulty with ADLs had 1.9 (95% CI = [1.3, 2.7]) times and 1.2 (95% CI = [1.1, 1.4]) times the odds of hip fracture than those without, respectively, women with difficulty grasping with their fingers had 47% lower odds of hip fracture than those without.

Table 3.

Estimated Coefficients and Odds Ratios From Logistic Regression Predicting Hip Fracture As a Function of Various Risk Factors.

	Female				Male
	Estimated	SE	p value	Odds ratio [95% CI]	Estimated	SE	p value	Odds ratio [95% CI]
Demographic and socioeconomic factors
Age	0.01	0.01	.361	1.01 [0.99, 1.04]	0.01	0.02	.369	1.01 [0.98, 1.05]
More than high school education	0.03	0.49	.954	1.03 [0.39, 2.71]	−0.04	0.31	.895	0.96 [0.53, 1.75]
Medical condition
Diabetes	0.52	0.23	.023*	1.68 [1.07, 2.62]	0.03	0.29	.906	1.04 [0.59, 1.82]
Osteoporosis	0.39	0.20	.054	1.48 [0.99, 2.20]	0.79	0.49	.108	2.21 [0.84, 5.81]
Glaucoma	0.38	0.35	.279	1.46 [0.74, 2.89]	−1.12	0.74	.131	0.33 [0.80, 1.40]
Prescription drug (external)	0.29	0.17	.093	1.31 [0.95, 1.87]	0.66	0.22	.003*	1.93 [1.26, 2.97]
Nonprescribed drug	0.11	0.08	.188	1.12 [0.95, 1.87]	0.00	0.11	1.000	1.00 [0.80, 1.25]
Back pain	0.08	0.19	.680	1.08 [0.75, 1.56]	−0.57	0.29	.049*	0.57 [0.32, 1.01]
Prescription drug (internal)	0.03	0.04	.425	1.03 [0.96, 1.10]	−0.03	0.04	.535	0.98 [0.90, 1.06]
Cataracts	−0.06	0.17	.706	0.94 [0.67, 1.31]	0.12	0.22	.582	1.13 [0.73, 1.72]
Dementia	−0.04	0.42	.929	0.96 [0.43, 2.19]	0.38	0.53	.474	1.46 [0.52, 4.12]
Arthritis	−0.16	0.19	.418	0.86 [0.59, 1.25]	−0.05	0.27	.848	0.95 [0.56, 1.61]
Heart problem	−0.34	0.21	.117	0.72 [0.47, 1.09]	0.33	0.23	.145	1.40 [0.89, 2.19]
Cancer	−0.67	0.47	.159	0.51 [0.20, 1.30]	0.69	0.33	.037*	2.00 [1.04, 3.83]
Functional limitation and physical health
Difficulty to bend knee	0.62	0.19	.001*	1.85 [1.29, 2.67]	0.96	0.23	.001*	2.61 [1.66, 4.12]
ADL	0.18	0.07	.005*	1.20 [1.06, 1.37]	0.08	0.09	.396	1.08 [0.90, 1.29]
Height (cm)	0.00	0.01	.994	1.00 [0.98, 1.03]	0.00	0.01	.830	1.00 [0.98, 1.03]
BMI	0.00	0.02	.875	1.00 [0.95, 1.04]	0.00	0.03	.956	1.00 [0.94, 1.06]
IADL	−0.01	0.06	.930	0.99 [0.88, 1.13]	−0.07	0.08	.338	0.93 [0.80, 1.08]
Five or more natural children*	−0.20	0.29	.496	0.82 [0.47, 1.45]	—	—	—	—
Positive self-rated health	−0.29	0.18	.106	0.75 [0.53, 1.06]	0.10	0.22	.645	1.11 [0.71, 1.72]
Difficulty to grasp with fingers	−0.63	0.31	.042*	0.53 [0.29, 0.98]	−0.88	0.49	.076	0.42 [0.16, 1.10]
Lifestyle
Drinking	0.11	0.21	.607	1.12 [0.74, 1.69]	0.06	0.18	.746	1.06 [0.74, 1.52]
Smoking	0.27	0.32	.392	1.31 [0.71, 2.43]	0.31	0.19	.103	1.37 [0.94, 1.99]
Environmental factors
Living in rural areas	0.01	0.16	.924	1.02 [0.75, 1.38]	0.21	0.18	.246	1.24 [0.86, 1.77]

Note: CI = confidence interval; ADL = activity of daily living; BMI = body mass index; IADL = instrumental activity of daily living.

p < .05.

Among older Japanese men, individuals who used at least one external prescribed medication had 1.9 (95% CI = [1.3, 3.0]) times the odds of hip fracture than those who did not. Those with cancer had 2.0 (95% CI = [1.04, 3.8]) times the odds of hip fracture than those without. Older men with difficulty bending their knee had 2.6 (95% CI = [1.7, 4.1]) times the odds of hip fracture than those who did not. However, the individuals with back pain had 43% lower odds of hip fracture than those without.

Discussion

This study examined the risk factors of hip fracture for older Japanese women and men separately using the nationally representative Japanese data set, NUJLSOA. In older Japanese women, diabetes, difficulty bending their knee, and more ADL limitations were associated with increased risk of hip fracture, whereas difficulty to grasp with fingers was associated with lower risk. In addition, in older Japanese men, cancer, use of external prescription drugs, and difficulty bending their knee were associated with increased risk of hip fracture, whereas back pain was associated with lower risk.

In this study, age and education were not associated with hip fracture unlike some of the past studies (Wei, Hu, Wang, & Hwang, 2001). However, one Japanese study reported that age was not a risk factor of hip fracture (Yamanashi et al., 2005). Although age was not independently associated with risk of hip fracture in this study, a number of factors that tend to increase with age seemed to be associated with increased risk of hip fracture. For example, ADL limitations, back pain, and use of prescription drugs generally increase with ages. Indeed, these factors were independently associated with risk of hip fracture in the current study. Education may influence the variables considered in this study but did not seem to be a direct risk factor of hip fracture.

Two chronic illnesses, diabetes and cancer, were associated with increased risk of hip fracture in women and men, respectively. This finding supports some of the previous studies. Schwartz et al. (2001) found that diabetics had a greater risk of hip and proximal humerus fracture after adjusting for bone mineral density and demographic factors. In addition, Mexican American older adults with diabetes were at higher risks of hip fracture after adjusting for covariates such as demographic factors and BMI (Ottenbacher, Ostir, Peek, Goodwin, & Markides, 2002). Although the occurrence mechanism of how particular chronic illnesses influence hip fracture risk is still unclear, complications from diabetes such as diabetes-related visual impairment, and/or cancer treatments including hormone therapy and androgen deprivation therapy for particular cancers seem to indirectly increase risk of hip fracture (Kanis, McCloskey, et al., 1999; Lopez et al., 2005; Ottenbacher et al., 2002; Schwartz et al., 2001). On a relevant note, more attention should be paid to other drugs (e.g., benzodiazepine) known to be associated with fall risks, which may reflect existence of illnesses or other physical conditions along with particular chronic illnesses in addition to those examined in this study (Cummings et al., 1995; Grisso et al., 1997).

Difficulty bending a knee was associated with increased risk of hip fracture among older Japanese women and men. There are two potential mechanisms that might explain this association. First, difficulty bending the knee presumably works as a mediator of the relationship between falls and hip fracture (Nguyen, Pongchaiyakul, Center, Eisman, & Nguyen, 2005). That is to say, not being able to bend the knee comfortably could result in instability of posture that may lead to falls (Lord et al., 1994). Second, difficulty bending knee may have an influence on the trauma of one’s hip when a fall occurs. Indeed, hitting the knee first on the ground and changing direction of the fall can alleviate the impact on hip and avoid hip fracture (Pinilla, Boardman, Bouxsein, Myers, & Hayes, 1996; Runge, Rehfeld, & Resnicek, 2000). This finding suggests that educating older adults about how to fall safely along with potential consequences of hip fracture may be a reasonable strategy as a future public health intervention. In addition, such findings could help understand possible etiological explanations about the associations between ADL, physical fitness, and falls (Lau, Woo, Leung, & Swaminthan, 1993). Two protective factors, difficulty grasping with fingers in women and back pain in men, are arguably related to lower activities levels, which may indicate lower risk of falls and, in turn, hip fracture.

It should be noted that osteoporosis was not associated with risk of hip fracture in this study. In general, osteoporosis or lower bone mineral density is a definitive indicator of bone fragility (Cummings & Melton, 2002). Whereas osteoporosis is reported as a risk factor of hip fracture (Lau et al., 2001; Lau et al., 1993), it is a protective factor in other studies (Kanis, Johnell, et al., 1999). It may be possible that osteoporosis would be a risk factor only when there was a significant impact on one’s hip like when one falls.

There are several important contributions from the findings in this study. First, this study examined hip fracture risk factors in the understudied older Japanese population. Given the lower prevalence of hip fracture comparing with Western nations, only a few studies have focused on hip fracture at the population level in Japan while it still is a serious public health problem. Second, this study identified different risk factors of hip fracture for older Japanese women and men. Most previous studies considered gender as a risk factor or focused only on either women or men. Last, no previous study examined risk factors of hip fracture with NUJLSOA, which is one of a few publicly available large data sets of Japanese older adults. Secondary data analysis using nationally representative data in aging population is not yet common in Japanese hip fracture studies.

Some limitations in this study should be noted. First, Japanese specific cultural aspects were not taken into account. Although not examined in this study, typical but distinctive Japanese diets such as fish, tofu, and natto (fermented soybeans), and use of Japanese traditional futon are possible protective factors of fracture (Suzuki et al., 1997). Second, although we identified risk factors for hip fracture, the predictive accuracy of logistic regression models in this study may not be sufficient for routine use. Follow-up analyses using the area under the receiver operating characteristic curve (AUC) showed the moderate predictive accuracy, AUC (women, men) = (0.71, 0.67); the models could improve by incorporating omitted risk factors of hip fracture (DeMaris, 2004; Swets, 1988). Third, the finding regarding back pain requires caution as the estimated odds ratio was small although statistically significant. Finally, the NUJLSOA does not include information about timing of hip fracture and possible consequences (e.g., functional limitations). Therefore, any causal inference or examination of hip fracture treatment outcomes was not possible. However, the respondents were community-dwelling older adults who are still at risk of hip fracture. In this regard, identification of risk factors regardless of previous hip fracture experience is meaningful. Although this study included a single wave of data, as further consecutive waves of NUJLSOA become available, longitudinal analyses may allow for the inclusion of additional risk factors including a previous history of falls.

In conclusion, this study identified risk factors of hip fracture by developing hip fracture prediction models separately for older Japanese women and men using the nationally representative data. Diabetes, difficulty to bend knee, difficulty to grasp with fingers (protective factor), and ADL limitations were associated with risk of hip fracture among older Japanese women. Cancer, use of external prescribed drugs, back pain (protective factor), and difficulty to bend knee were associated with increased risk of hip fracture among older Japanese men. These identified risk factors including physical impairments and functional limitations, and their causal pathways to hip fracture need to be further examined with consideration of gender difference and specific cultural aspects of study populations in future research.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research and/or authorship of this article.

Bios

Takashi Yamashita, Ph.D is assistant professor of sociology at University of Nevada, Las Vegas, USA. His primary research focus is on social determinants of health, health resource access and health literacy. He completed his post-doctoral training (2011-2012) at the Scripps Gerontology Center, Miami University in Oxford, Ohio, USA.

A. John Bailer, Ph.D is University Distinguished Professor and Chair of the Department of Statistics at Miami University in Oxford, Ohio, USA. He also serves as a Scripps Research Fellow in the Scripps Gerontology Center and as an affiliate member of the Department of Sociology and Gerontology, both at Miami University. He joined Miami University in 1988 after completing a PhD in biostatistics from the University of North Carolina and a staff fellowship at the National Institute of Environmental Health Sciences.

References

Alexander

B. H.

Rivara

F. P.

Wolf

M. E.

(1992). The cost and frequency of hospitalization for fall-related injuries in older adults. American Journal of Public Health, 82, 1020-1023. doi:10.2105/AJPH.82.7.102010.2105/AJPH.82.7.1020

Cabinet Office. (2007). Annual report on the aging society 2007. Tokyo, Japan: Japanese Government.

Cummings

S. R.

Melton

L. J.

(2002). Epidemiology and outcomes of osteoporotic fractures. Lancet, 359, 1761-1767. doi:10.1016/S0140-6736(02)08657-910.1016/S0140-6736(02)08657-9

Cummings

S. R.

Nevitt

M. C.

Browner

W. S.

Stone

Fox

K. M.

Ensrud

K. E.

. . . Vogt

T. M.

(1995). Risk factors for hip fracture in white women. Study of Osteoporotic Fractures Research Group. New England Journal of Medicine, 332, 767-774. doi:10.1056/NEJM19950323332120210.1056/NEJM199503233321202

Dargent-Molina

Favier

(1996). Fall-related factors and risk of hip fracture: The EPIDOS prospective study. Lancet, 348, 145-149. doi:10.1016/S0140-6736(96)01440-710.1016/S0140-6736(96)01440-7

DeMaris

(2004). Regression with social data: Modeling continuous and limited response variables. Hoboken, NJ: Wiley-Interscience.

Devine

Criddle

R. A.

Dick

I. M.

Kerr

D. A.

Prince

R. L.

(1995). A longitudinal study of the effect of sodium and calcium intakes on regional bone density in postmenopausal women. American Journal of Clinical Nutrition, 62, 740-745.

Fujiwara

Kasagi

Yamada

Kodama

(1997). Risk factors for hip fracture in a Japanese cohort. Journal of Bone and Mineral Research, 12, 998-1004.

Grisso

J. A.

Kelsey

J. L.

O’Brien

L. A.

Miles

C. G.

Sidney

Maislin

. . . Peters

(1997). Risk factors for hip fracture in men. Hip Fracture Study Group. American Journal of Epidemiology, 145, 786-793.

10.

Hasegawa

Suzuki

Wingstrand

(2007). Risk of mortality following hip fracture in Japan. Journal of Orthopaedic Science, 12, 113-117.

11.

Hosmer

D. W.

Lemeshow

(2004). Applied logistic regression. New York, NY: Wiley-Interscience.

12.

Kanis

J. A.

Johnell

Gullberg

Allander

Elffors

Ranstam

. . . Ribot

(1999). Risk factors for hip fracture in men from southern Europe: The MEDOS study. Mediterranean Osteoporosis Study. Osteoporosis International, 9, 45-54.

13.

Kanis

J. A.

McCloskey

E. V.

Powles

Paterson

A. H. G.

Ashley

Spector

(1999). A high incidence of vertebral fracture in women with breast cancer. British Journal of Cancer, 79, 1179-1181. doi:10.1038/sj.bjc.669018810.1038/sj.bjc.6690188

14.

Kunieda

(2002). Japanese pension reform: Can we get out of intergenerational exploitation? Hitotsubashi Journal of Economics, 43, 57-72.

15.

Lau

E. M. C.

Suriwongpaisal

Lee

J. K.

Das De

Festin

M. R.

Saw

S. M.

. . . Sambrook

(2001). Risk factors for hip fracture in Asian men and women: The Asian osteoporosis study. Journal of Bone and Mineral Research, 16, 572-580. doi::jbmr.2001.16.3.572jbmr.2001.16.3.572

16.

Lau

E. M. C.

Woo

Leung

P. C.

Swaminthan

(1993). Low bone mineral density, grip strength and skinfold thickness are important risk factors for hip fracture in Hong Kong Chinese. Osteoporosis International, 3, 66-70. doi:10.1007/BF0162337510.1007/BF01623375

17.

Lopez

A. M.

Pena

M. A.

Hernandez

Val

Martin

Riancho

J. A.

(2005). Fracture risk in patients with prostate cancer on androgen deprivation therapy. Osteoporosis International, 16, 707-711. doi:10.1007/s00198-004-1799-710.1007/s00198-004-1799-7

18.

Lord

S. R.

Sambrook

P. N.

Gilbert

Kelly

P. J.

Nguyen

Webster

I. W.

Eisman

J. A.

(1994). Postural stability, falls and fractures in the elderly: Results from the Dubbo Osteoporosis Epidemiology Study. Medical Journal of Australia, 160, 684.

19.

Ministry of Health Labour and Welfare. (2005). Kokumin seikatsu kiso tyousa. Tokyo, Japan: Author.

20.

Nguyen

N. D.

Pongchaiyakul

Center

J. R.

Eisman

J. A.

Nguyen

T. V.

(2005). Identification of high-risk individuals for hip fracture: A 14-year prospective study. Journal of Bone and Mineral Research, 20, 1921-1928. doi:10.1359/JBMR.05052010.1359/JBMR.050520

21.

Otaka

Riu

Uzawa

Chino

(2003). The effectiveness of fall prevention programs: A review-2. Fall-related issues and future perspectives on fall related research. Japanese Journal of Rehabilitation Medicine, 40, 389-397.

22.

Ottenbacher

K. J.

Ostir

G. V.

Peek

M. K.

Goodwin

J. S.

Markides

K. S.

(2002). Diabetes mellitus as a risk factor for hip fracture in Mexican American older adults. Journals of Gerontology Series A: Biological and Medical Sciences, 57, 648-653. doi: 10.1093/gerona/57.10.M64810.1093/gerona/57.10.M648

23.

Pinilla

T. P.

Boardman

K. C.

Bouxsein

M. L.

Myers

E. R.

Hayes

W. C.

(1996). Impact direction from a fall influences the failure load of the proximal femur as much as age-related bone loss. Calcified Tissue International, 58, 231-235. doi:10.1007/s00223990004010.1007/s002239900040

24.

Pluijm

S. M. F.

Smit

J. H.

Tromp

E. A. M.

Stel

V. S.

Deeg

D. J. H.

Bouter

L. M.

Lips

(2006). A risk profile for identifying community-dwelling elderly with a high risk of recurrent falling: Results of a 3-year prospective study. Osteoporosis International, 17, 417-425. doi:10.1007/s00198-005-0002-010.1007/s00198-005-0002-0

25.

Rizzo

J. A.

Freidkin

Williams

C. S.

Nabors

Acampora

Tinetti

M. E.

(1998). Health care utilization and costs in a Medicare population by fall status. Medical Care, 36, 1174-1188.

26.

Rubenstein

L. Z.

Josephson

K. R.

(2002). Risk factors for falls: A central role in prevention. Generations, 26, 15.

27.

Runge

Rehfeld

Resnicek

(2000). Balance training and exercise in geriatric patients. Journal of Musculoskeletal and Neuronal Interactions, 1, 54-58.

28.

Schwartz

A. V.

Sellmeyer

D. E.

Ensrud

K. E.

Cauley

J. A.

Tabor

H. K.

Schreiner

P. J.

, . . . Study of Osteoporotic Features Research Group. (2001). Older women with diabetes have an increased risk of fracture: A prospective study. Journal of Clinical Endocrinology & Metabolism, 86, 32-38. doi:10.1210/jc.86.1.3210.1210/jc.86.1.32

29.

Suzuki

Yoshida

Hashimoto

Yoshimura

Fujiwara

Fukunaga

. . . Orimo

(1997). Case-control study of risk factors for hip fractures in the Japanese elderly by a Mediterranean osteoporosis study (MEDOS) questionnaire. Bone, 21, 461-467. doi:10.1016/S8756-3282(97)00179-810.1016/S8756-3282(97)00179-8

30.

Swets

J. A.

(1988). Measuring the accuracy of diagnostic systems. Science, 240, 1285-1293.

31.

Tromp

A. M.

Pluijm

S. M.

Smit

J. H.

Deeg

D. J.

Bouter

L. M.

Lips

(2001). Fall-risk screening test: A prospective study on predictors for falls in community-dwelling elderly. Journal of Clinical Epidemiology, 54, 837-844. doi:10.1016/S0895-4356(01)00349-310.1016/S0895-4356(01)00349-3

32.

Wei

T. S.

C. H.

Wang

S. H.

Hwang

K. L.

(2001). Fall characteristics, functional mobility and bone mineral density as risk factors of hip fracture in the community-dwelling ambulatory elderly. Osteoporosis International, 12, 1050-1055. doi:10.1007/PL0000418410.1007/PL00004184

33.

Yamaguchi

(1995). Nutritional factors relating to cardiovascular diseases and cancer. Journal of Epidemiology (in Japanese), 5, 42-43.

34.

Yamanashi

Yamazaki

Kanamori

Mochizuki

Okamoto

Koide

. . . Nagano

(2005). Assessment of risk factors for second hip fractures in Japanese elderly. Osteoporosis International, 16, 1239-1246. doi:10.1007/s00198-005-1835-210.1007/s00198-005-1835-2

35.

Yoshimura

Suzuki

Hosoi

Orimo

(2005). Epidemiology of hip fracture in Japan: Incidence and risk factors. Journal of Bone and Mineral Metabolism, 23, 78-80. doi:10.1007/BF0302632810.1007/BF03026328

36.

Youm

Koval

K. J.

Kummer

F. J.

Zuckerman

J. D.

(1999). Do all hip fractures result from a fall? American Journal of Orthopedics, 28, 190-194.

Risk Factors for Hip Fracture in Japanese Older Adults

Abstract

Keywords

Introduction

Materials and Method

Study Population

Response Variable

Predictor Variables

Demographic and socioeconomic factors

Medical conditions and history

Functional limitation and physical health characteristic

Environmental factor

Statistical Methods

Results

Discussion

Footnotes

Declaration of Conflicting Interests

Funding

Bios

References