Factors associated with osteoporosis among older patients at the Geriatric Centre in Nigeria: a cross-sectional study South African Family Practice is co-published by Medpharm Publications, NISC (Pty) Ltd and Taylor & Francis, and Informa business. S Afr Fam Pract ISSN 2078-6190 EISSN 2078-6204 © 2017 The Author(s) RESEARCH South African Family Practice 2017; 59(3):87–93 https://doi.org/10.1080/20786190.2016.1272248 Open Access article distributed under the terms of the Creative Commons License [CC BY-NC 3.0] http://creativecommons.org/licenses/by-nc/3.0 Factors associated with osteoporosis among older patients at the Geriatric Centre in Nigeria: a cross-sectional study TO Alongea, LA Adebusoyeb*, AM Ogunbodec, OO Olowookereb, MM-A Ladipoc  , WO Balogund and V Okoje-Adesomojue aDepartment of Orthopaedics and Trauma, University College Hospital, Ibadan, Nigeria b Chief Tony Anenih Geriatric Centre, University College Hospital, Ibadan, Nigeria c Department of Family Medicine, University College Hospital, Ibadan, Nigeria d Department of Medicine, College of Medicine, University of Ibadan, Nigeria e Department of Oral and Maxillofacial Surgery, University College Hospital, Ibadan, Nigeria *Corresponding author, email: larrymacsoye@yahoo.com Background: Osteoporosis is a silent disabling clinical condition often attributed to ageing. It is of public health importance because of its complications and attendant morbidity and mortality. Methods: A cross-sectional study was undertaken of 2401 older patients (60 years and above) at the Geriatric Centre, University College Hospital, Ibadan. Candidate variables such as socio-demographic characteristics, anthropometric indices, physical and lifestyle habits were assessed. Bivariate and multivariate analyses were carried out using SPSS 17®. Results: The point prevalence of osteoporosis was 56.9% (males  =  43.7% and females  =  65.8%). The most significant factors associated with osteoporosis on logistics regression analyses were increasing age, female sex, lack of formal education, lack of engagement in occupational activities and living with relatives/friends. Receiving social support from relatives/friends, non- participation in sporting activities at younger ages, prolonged use of medications for peptic ulcer disease, hospitalisation on or after the age of 60  years and asthenic build were also found to be significant. Yearly increase in age shows a 6.9% (95% CI 5.4–8.4%) increase in the odds of having osteoporosis. Conclusion: The high prevalence of osteoporosis among older persons in this study calls for concerted efforts by the healthcare workers to prevent osteoporosis among older patients. Keywords: Geriatric centre, Nigeria, older patients, osteoporosis Background Osteoporosis is a progressive disease with loss of bone mass which leaves the skeleton vulnerable to fracture.1 It is a systemic skeletal disease in which there is micro-architectural deterioration of bone tissue.2 Osteoporosis is operationally defined using the World Health Organization (WHO) criteria as a bone mineral density (BMD) that lies 2.5 standard deviations or more below the average value for young healthy women (a T-score of < –2.5 SD).3,4 Dual-energy X-ray absorptiometry (DXA) is commonly used to measure BMD.3 The WHO scientific group on the assessment of osteoporosis at the primary healthcare level in the report of the meeting held in Brussels, Belgium in 2004 noted that osteoporosis is a disease that has to be prevented in view of its severe morbidities and associated fragility fractures among the elderly because these cause a huge impact, financial and social, on the health of the community.3,5 Osteoporosis is also known to affect the quality of life and independence of the elderly.3 With increasing life expectancy in Nigeria, the population of the elderly being hospitalised following fractures of the head of the femur is on the rise.1 The vertebral bodies, distal radius, neck of femur, proximal femur and proximal humerus are the areas of highest prevalence of fractures.4 Osteoporosis can be divided into primary osteoporosis, which includes age-related and idiopathic osteoporosis, and secondary osteoporosis.6 The causes of secondary osteoporosis include but are not restricted to hypogonadism such as arises from hormonal treatment of prostate cancer, lifestyle choices such as a sedentary lifestyle, alcohol and cigarette consumption, gastrointestinal disorders, systemic illnesses and medications such as glucocorticoids.6 In the United Kingdom (UK), more than 200,000 fractures are reported each year secondary to osteoporosis.4 In America, the prevalence rate of osteoporosis is 10.3%, which translates to 28 million people, of which 10 million have osteoporosis and 18 million have low BMD.7 In Australia, 1.2 million people are reported to have osteoporosis,8 whilst in India postmenopausal women commonly suffer from osteoporosis,9 although osteoporosis is as important in men as it is in women.6 The risk factors associated with osteoporosis include a positive family history of osteoporosis, lack of exercise, vitamin D deficiency and a low-calcium diet.9 Prolonged amenorrhoea and a history of anorexia or bulimia are also implicated in the development of osteoporosis.9 Significant increase in total homocysteine (tHcy) with corresponding decreases in folic acid, vitamins B12 and B6 were identified as the risk factors causing a decrease in BMD in osteoporotic Nigerian adults using DXA measurement.10 In a case-control study conducted at the National Orthopaedic Hospital Igbobi, Lagos, Nigeria over a 12-month period, 31 patients ranging from 67 to 100  years with a mean age of 79.6  years were recruited.1 The majority of those in the study group with osteoporosis were female and most were post- menopausal; also virtually all the patients were above 70 years of age.1 Similarly, in a cross-sectional study among 208 Nigerian women, broadband ultrasound attenuation (BUA) and speed of sound velocity (SOS) were used to calculate the stiffness index http://orcid.org/0000-0001-9897-3473 mailto:larrymacsoye@yahoo.com 88 S Afr Fam Pract 2017; 59(3):87–93 (SI) of the calcaneus.11 In this total study group, 9% had T-scores indicative of osteoporosis, based on United States (US) reference data.11 Among Nigerians living with the human immunodeficiency virus (HIV), the BMD values revealed osteoporosis in 31.9% and osteopenia in 46.6%.12 To our knowledge, there is a paucity of data on osteoporosis in Nigeria using DXA measurement, as osteoporosis has been sparingly studied. Furthermore, the few studies available were carried out in young and pregnant women. This has left a knowledge gap in the frequency of the condition among elderly patients and the effects of the interventions used in managing this condition. Most healthcare workers and elderly patients become aware of osteoporosis when a fracture has occurred, most often after an innocuous injury. The aim of healthcare workers should be to prevent fractures from occurring in elderly patients as studies have shown high morbidity and mortality following fractures in older persons. This study will increase the knowledge of healthcare workers and increase their awareness of the public health impact of osteoporosis among elderly patients. Additionally, it will serve as a reference point for policy- makers in the health sector to understand the magnitude and modifiable factors to be urgently and properly addressed to prevent osteoporosis in elderly people. Methods Study site This study was carried out at the Chief Tony Anenih Geriatric Centre (CTAGC) of University College Hospital (UCH), Ibadan. Ibadan is the capital city of Oyo State in South-Western Nigeria and it has a population of 3.6 million inhabitants, while Oyo State as a whole has 5.6 million people.13 University College Hospital, Ibadan is the premier teaching hospital in Nigeria with 850-bed capacity. CTAGC was the first purpose-built geriatric centre in West Africa, established on November 17, 2012, to give holistic care to elderly patients seeking care at UCH. CTAGC has recreational facilities, a dietetics unit, a medical social work unit, a physiotherapy unit, a one-stop-shop outpatient clinic, and two operating theatre suites as well as inpatient (ward) services. This study was carried out at the outpatient unit of the CTAGC, UCH. Aim of the study The aim of this study was too determine the prevalence of osteoporosis and its associated factors among older patients aged ≥ 60 years in a first-contact care setting. Study population Male and female patients aged 60  years and above who presented consecutively at the CTAGC, UCH between February 2013 and August 2014 were included in the study. Those who did not consent or were too ill to participate were excluded. Their ages were determined by direct recall and the use of the table of historical events by Ajayi-Igun.14 Study design This was a cross-sectional study of 2401 older patients aged  ≥  60  years who were selected consecutively as they presented in the clinic. An assumed prevalence of 50%, because there were no local data on prevalence of osteoporosis in older Nigerians, and a precision of 2% were used in calculating the sample size to arrive at 2401 respondents. Table 1: Socio-demographic characteristics Factor Males = 964, n (%) Females = 1437, n (%) Total = 2401,  n (%) Age groups (years) 60–64 204 (21.2) 312 (21.7) 516 (21.5) 65–69 233 (24.2) 374 (26.0) 607 (25.3) 70–74 233 (24.2) 335 (23.3) 568 (23.7) 75–79 171 (17.7) 260 (18.1) 431 (18.0) ≥ 80 123 (12.8) 156 (10.9) 279 (11.6) Marital status Married 819 (85.0) 634 (44.1) 1435 (60.5) Widowed 131 (13.6) 782 (54.4) 913 (38.0) Separated 7 (0.7) 11 (0.8) 18 (0.7) Single 5 (0.5) 5 (0.3) 10 (0.4) Divorced 2 (0.2) 5 (0.3) 7 (0.3) Religious groups Christianity 618 (64.1) 957 (66.6) 1575 (65.6) Islam 339 (35.2) 473 (32.9) 812 (33.8) Traditional and others 7 (0.7) 7 (0.5) 14 (0.6) Educational attainment None 177 (18.4) 669 (46.6) 846 (35.2) Primary school 163 (16.9) 228 (15.9) 391 (16.3) Secondary school 276 (28.6) 202 (14.1) 478 (19.9) Tertiary school 348 (36.1) 338 (23.5) 686 (28.6) Occupational status Not engaged in occupational activities 636 (66.0) 925 (64.4) 1561 (65.0) Still engaged in occupational activities 328 (34.0) 512 (35.6) 840 (35.0) Living arrangements Alone 117 (12.1) 264 (18.4) 381 (15.9) With spouse 771 (80.0) 599 (41.7) 1370 (57.1) With chil- dren/grandchil- dren 70 (7.3) 548 (38.1) 618 (25.7) With relatives/ friends 6 (0.6) 26 (1.8) 32 (1.3) Financial support Self 383 (39.7) 269 (18.7) 652 (27.2) Spouse 67 (7.0) 131 (9.1) 198 (8.2) Children/grand- children 487 (50.5) 1020 (71.0) 1507 (62.8) Relatives/friends 27 (2.8) 17 (1.2) 44 (1.8) Social support None 15 (1.6) 23 (1.6) 38 (1.6) Spouse 580 (60.2) 364 (25.3) 944 (39.3) Children/grand- children 360 (37.3) 1021 (71.1) 1381 (57.5) Relatives/friends 9 (0.9) 29 (2.0) 38 (1.6) Number of children 0–5 487 (50.5) 903 (62.8) 1390 (57.9) > 5 477 (49.5) 534 (37.2) 1011 (42.1) Factors associated with osteoporosis among older patients at the Geriatric centre in Nigeria: A cross sectional study 89 Procedure A semi-structured interviewer-administered questionnaire which was pre-tested before the actual study was used. The BMD was measured in the right wrist (radial and ulnar bones) using a Dual Energy X-ray Absorptiometry (DXA) OsteoSys machine (EXA 3000®) (Mmedical ECONET GmbH, Oberhausen, Germany).15 It provides BMD in g/cm3 (gold standard) and the T-score within five seconds. This ensures speed, maximum reduction in patients’ radiation dose, detailed imaging and analysis as well as excellent precision.15 Osteoporosis was defined based on the quantitative assessment of BMD using the WHO operational definition of osteoporosis by DXA machine.16 Respondents with a T-score of < –2.5 were classified as having osteoporosis.16 Table 2: Socio-demographic characteristics by prevalence of osteoporosis *Significant at 5% level of significance. Factor Osteoporosis Yes = 1366, n (%) No = 1035, n (%) Total = 2401, n (%) Age groups (years) 60–64 205 (39.7) 311 (60.3) 516 (100.0) χ2 = 156.500 65–69 300 (49.4) 307 (50.6) 607 (100.0) 70–74 341 (60.0) 227 (40.0) 568 (100.0) p < 0.0001*75–79 309 (71.7) 122 (28.3) 431 (100.0) ≥ 80 211 (75.6) 68 (24.4) 279 (100.0) Sex Males 421 (43.7) 543 (56.3) 964 (100.0) χ2 = 114.800 Females 945 (65.8) 492 (34.2) 1437 (100.0) p < 0.0001* Marital status Not currently married 640 (67.5) 308 (32.5) 948 (100.0) χ2 = 72.008 Currently married 726 (50.0) 727 (50.0) 1453 (100.0) p < 0.0001* Religious groups Christianity 851 (54.0) 724 (46.0) 1575 (100.0) χ2 = 17.488 Islam 509 (62.7) 303 (37.3) 812 (100.0) Traditional and others 6 (42.9) 8 (57.1) 14 (100.0) p < 0.0001* Educational attainment None 610 (72.1) 236 (27.9) 846 (100.0) χ2 = 139.800 Primary school 220 (56.3) 171 (43.7) 391 (100.0) Secondary school 237 (49.6) 241 (50.4) 478 (100.0) p < 0.0001* Tertiary school 299 (43.6) 387 (56.4) 686 (100.0) Occupational status Not engaged in occupational activities 933 (59.8) 628 (40.2) 1561 (100.0) χ2 = 15.053 Still engaged in occupational activities 433 (51.5) 407 (48.5) 840 (100.0) p < 0.0001* Living arrangements Alone 223 (58.5) 158 (41.5) 381 (100.0) χ2 = 69.283 With spouse 689 (50.3) 681 (49.7) 1370 (100.0) With children/grandchildren 431 (69.7) 187 (30.3) 618 (100.0) p < 0.0001* With relatives/friends 23 (71.9) 9 (28.1) 32 (100.0) Financial support Self 251 (38.5) 401 (61.5) 652 (100.0) χ2 = 155.200 Spouse 93 (47.0) 105 (53.0) 198 (100.0) Children/grandchildren 1001 (66.4) 506 (33.6) 1507 (100.0) p < 0.0001* Relatives/friends 21 (47.7) 23 (52.3) 44 (100.0) Social support None 17 (44.7) 21 (55.3) 38 (100.0) χ2 = 48.115 Spouse 465 (49.3) 479 (50.7) 944 (100.0) Children/grandchildren 868 (62.9) 513 (37.1) 1381 (100.0) p < 0.0001* Relatives/friends 16 (42.1) 22 (57.9) 38 (100.0) Number of children 0–5 802 (57.7) 588 (42.3) 1390 (100.0) χ2 = 0.872 > 5 564 (55.8) 447 (44.2) 1011 (100.0) p = 0.350 90 S Afr Fam Pract 2017; 59(3):87–93 45,000], Z = 11.098, p < 0.0001). The majority of the men (85.0%) were still married while the majority of the women (54.4%) were widowed. A higher proportion of the men (81.6%) had formal education compared with the women (53.5) (Table 1). The Detailed information on the risk factors for osteoporosis such as socio-demographic characteristics, lifestyle habits, family functionality, previous hospitalisation (age at first hospital admission and number of hospital admission), healthcare utilisation, morbidities and pattern of medications used in the past one year prior to this study were obtained. Comprehensive physical examination and anthropometric measurements of height, weight, waist and hip circumferences were carried out by the researchers. Body mass index (BMI) was calculated by dividing weight (kilogrammes) by height in meters squared and this was graded using the WHO anthropometric classification.15 Underweight was defined as BMI < 18.4 kg/m2 with 18.5–24.9 kg/ m2 as normal. Overweight was a BMI of 25.0–29.9  kg/m2 and obesity a BMI ≥ 30.0 kg/m2.17 The average distance walked by the respondents was estimated from the number of electric poles they walk daily (50 metres between two poles). The administration of the questionnaire was carried out in the English language and Yoruba language (the local dialect of most respondents) and it took about 45 minutes to be administered to each respondent. Consent for the study Approval for the study was obtained from the University of Ibadan/University College Hospital Institutional Ethical Review Board. Informed consent of each respondent was obtained before administration of questionnaires. Respondents’ follow-up: Those who were diagnosed with osteoporosis were treated with bisphosphonate (alendronate or ibandronate) and calcium supplement. The administered questionnaires were cleaned and analysed using SSPS® version 17 (SPSS Inc, Chicago, IL, USA). Chi-square statistics was used to test the association between categorical variables and Student’s t-test to test the association between continuous variables. The level of significance was set at p  ≤  0.05. Logistic regression was used to explore relationships between significant variables and osteoporosis. Results There were 2401 respondents in this study with a male to female ratio of 1:1.49. The mean  ±  SD age of the respondents was 70.8 ± 7.7 years (males > females = 71.1 ± 7.9 > 70.6 ± 7.5 years) without a statistical difference (t = 1.533, p = 0.125). The median income of the respondents was 40,000 Naira (IQR 35,000 – 60,000) with the men significantly earning more than the women (45,000 Naira [IQR 40,000–70,000] vs. 40,000 Naira [IQR 30,000– 25.7% 11.3% 17.1% 30.6% 22.9% 26.0% 43.7% 65.8% 56.9% Males Females Total Normal Osteopenia Osteoporosis 10 20 30 40 50 60 70 80 90 PR EV A LE N C E (% ) Figure 1: Point prevalence of osteopenia and osteoporosis using Dual Energy X-ray Absorptiometry (DXA). Table 3: Medical history and lifestyle habits by prevalence of osteoporosis *Significant at 5% level of significance. †Fisher’s exact test. Factor Osteoporosis Yes = 1366, n (%) No = 1035, n (%) Total = 2401, n (%) Do you engage in physical activities now? Yes 908 (54.1) 769 (45.9) 1677 (100.0) χ2 = 17.132 No 456 (63.3) 266 (36.7) 724 (100.0) p < 0.0001* Do you take alcohol? Yes 9 (45.0) 11 (55.0) 20 (100.0) χ2 = 1.163 No 1357 (57.0) 1024 (43.0) 2381 (100.0) p = 0.281 Do you take tobacco Yes 0 (0.0) 5 (100.0) 5 (100.0) p = 0.010† No 1366 (57.0) 1030 (43.0) 2396 (100.0) Do you take vitamins and mineral supplements? Yes 443 (59.2) 305 (40.8) 748 (100.0) χ2 = 2.408 No 923 (55.8) 730 (44.2) 1653 (100.0) p = 0.121 Did you engage in sporting activities when you were in school or young? Yes 381 (44.0) 485 (56.0) 866 (100.0) χ2 = 91.878 No 985 (64.2) 550 (35.8) 1535 (100.0) p < 0.0001* Are you on steroid therapy? Yes 27 (69.2) 12 (30.8) 39 (100.0) χ2 = 2.851 No 1315 (56.8) 1001 (43.2) 2316 (100.0) Can’t remember 24 (52.2) 22 9 (47.8) 46 (100.0) p = 0.240 Do you have thyroid disease? Yes 8 (88.9) 1 (11.1) 9 (100.0) No 1358 (56.8) 1034 (43.2) 2392 (100.0) p = 0.052† Do you have any form of cancer? Yes 8 (72.7) 3 (27.3) 11 (100.0) No 1358 (56.8) 1032 (43.2) 2390 (100.0) p = 0.288† Do you have family history of fracture? Yes 5 (71.4) 2 (28.6) 7 (100.0) p = 0.437† No 1361 (56.9) 1033 (43.1) 2394 (100.0) Are you on anticonvulsant medications? Yes 10 (47.6) 11 (52.4) 21 (100.0) χ2 = 0.743 No 1356 (57.0) 1024 (43.0) 2380 (100.0) p = 0.389 Are you on peptic ulcer disease medications? Yes 104 (66.7) 52 (33.3) 156 (100.0) χ2 = 6.498 No 1262 (56.2) 983 (43.8) 2245 (100.0) p = 0.011* Do you have chronic joint pains? Yes 662 (57.2) 496 (42.8) 1158 (100.0) χ2 = 0.069 No 704 (56.6) 539 (43.4) 1243 (100.0) p = 0.793 Your first admission to a hospital Never been admitted 857 (59.3) 588 (40.7) 1445 (100.0) χ2 = 32.544 Before the age of 60 years 198 (44.8) 244 (55.2) 442 (100.0) p < 0.0001* After the age of 60 years 311 (60.5) 203 (39.5) 514 (100.0) Factors associated with osteoporosis among older patients at the Geriatric centre in Nigeria: A cross sectional study 91 (OR  =  1.410 [95% CI 1.130–1.805], p  =  0.006), normal waist circumference (OR  =  1.953 [95% CI 1.495–2.551], p  <  0.0001), having no formal education (OR  =  1.376 [95% CI 1.088–1.740], p = 0.008) and not being obese (OR = 3.310 [95% CI 2.647–4.141], p  <  0.0001). Each increase of one year in age produced a 6.9% (95% CI 5.4–8.4%) increase in the odds of having osteoporosis. Discussion Osteoporosis is a common metabolic bone disease that has attracted little attention and even less action in many developing countries including Nigeria and there are several reasons for this state of neglect.18 These include the erroneous belief that osteoporosis is a disease limited to the developed countries and the acceptance of osteoporosis as an inevitable consequence of ageing.18 This was a large study carried out among elderly respondents in the premier Geriatric Centre established in Nigeria. Osteoporosis was found in more than half of the older patients in our setting. The prevalence of osteoporosis varies widely due to the differences in instruments used in measuring and the bones measured. Our prevalence was higher than that of adults aged 50 years and older in the US/European reference (38.3–47.7%),19 Saudi Arabia (30.5–49.6%),19 China (31%)20 and India studies (20.3%).21 Differences in the cut-off ages of adults in these studies could account for the disparities in prevalence values. average distance walked daily by the respondent was 483 metres (males > females = 559.5 metres > 430 metres). A total of 1366 respondents were diagnosed with osteoporosis, giving a point prevalence of osteoporosis of 56.9%. This is described in Figure 1. The socio-demographic characteristics by prevalence of osteoporosis are shown in Table 2. The prevalence of osteoporosis increases significantly with the age group from 39.7% in the 60– 64  years age group to 75.6% in those above 80  years of age (χ2  =  156.500, p  <  0.0001). The prevalence of osteoporosis was higher among the female respondents compared with their male counterparts (65.8% vs. 43.7%; χ2  =  114.800, p  <  0.0001). The prevalence of osteoporosis was significantly associated with respondents who were not currently married, and had no formal education, non-engagement in occupational activities and were living with relatives/friends and being supported socially as well as financially by children or grandchildren. Table 3 shows the medical history and lifestyle habits by prevalence of osteoporosis. The prevalence of osteoporosis was significantly associated with non-engagement in physical activities (χ2 = 17.132, p < 0.0001), non-participation in sporting activities during school years (χ2 = 91.878, p < 0.0001), usage of peptic ulcer medications (χ2  =  6.498, p  =  0.011) and being admitted to the hospital for the first time at or after the age of 60 years (χ2 = 32.544, p < 0.0001). Anthropometric measurements showed that the males were significantly taller than females (163.6 ± 7.4 cm > 153.2 ± 6.5 cm; t  =  36.649, p  <  0.0001) and significantly heavier (68.1  ±  14.9  kg  >  66.4  ±  15.8  kg; t  =  2.648, p  =  0.008) than the females. However, the female respondents had higher mean ± SD waist circumference (98.6 ± 13.1 cm vs. 95.2 ± 12.4 cm; t = 6.530, p < 0.0001), hip circumference (106.1 ± 12.9 cm vs. 100.0 ± 30.5 cm; t = 6.739, p < 0.0001) and body mass index (28.3 ± 6.5 vs. 25.4 ± 5.0; t = 11.848, p < 0.0001) compared with the male respondents. Table 4 shows the anthropometric measurements by prevalence of osteoporosis. In both sexes, osteoporosis was significantly associated with having normal waist circumference (p  <  0.0001) and being non-obese (p < 0.0001). The prevalence of osteoporosis was observed to have an inverse association with different categories of body mass index (BMI). This is shown in Figure 2. Logistic regression analysis was carried out on significant variables associated with osteoporosis and this is shown in Table 5 (effect of age, sex, marital status, occupational activities, living arrangements, social and financial support, sporting activities while in school, first hospital admission, waist circumference, educational status, obesity and physical activities on the likelihood that the participants have osteoporosis). The logistic model was statistically significant, χ2 (19) = 598.702, p < 0.0001. The model explained 29.6% (Nagelkerke R2) of the variance in osteoporosis and correctly classified 72.3% of cases. The most significant variables associated with osteoporosis were age (OR  =  1.069 [95% CI 1.054–1.084] p  <  0.0001), female sex (OR  =  4.061 [95% CI 3.133 – 5.263], p  <  0.0001), not engaged in occupational activities (OR  =  1.246 [95% CI 1.018–1.526], p = 0.033), living with relatives/friends (OR = 2.705 [95% CI 1.060– 6.908], p  =  0.037), receiving social support from relatives and friends (OR  =  2.712 [95% CI 1.254–5.864), p  =  0.011], receiving social support from children or grandchildren (OR = 3.482 [95% CI 1.553–7.805], p = 0.002), non-participation in sporting activities while at school (OR  =  1.453 [95% CI 1.168–1.808], p  =  0.001), using peptic ulcer disease medications (OR  =  1.780 [95% CI 1.212–2.613], p = 0.003), hospitalisation after the age of 60 years Table 4: Anthropometric measurements by prevalence of osteoporosis *Significant at 5% level of significance. Factor Osteoporosis Yes = 1366, n (%) No = 1035, n (%) Total = 2401, n (%) Waist–hip Ratio (WHR) Males < 1.00 334 (45.1) 406 (54.9) 740 (100.0) ≥ 1.00 87 (38.8) 137 (61.2) 224 (100.0) χ2 = 2.771 df = 1; p = 0.096 Females < 0.85 90 (65.7) 47 (34.3) 137 (100.0) ≥ 0.85 855 (65.8) 445 (34.2) 1300 (100.0) χ2 = 0.000 df = 1; p = 0.986 Body mass index (BMI) Males Non-obese (< 30 kg/m2) 385 (47.7) 422 (52.3) 807 (100.0) Obese (≥ 30 kg/m2) 36 (22.9) 121 (77.1) 157 (100.0) χ2 = 32.801 df = 1; p < 0.0001* Females Non-obese (< 30 kg/m2) 710 (78.1) 199 (21.9) 909 (100.0) Obese (≥ 30 kg/m2) 235 (44.5) 293 (55.5) 528 (100.0) χ2 = 167.500 df = 1; p < 0.0001* Waist circumference (WC) Males Normal (< 94 cm) 259 (55.3) 209 (44.7) 468 (100.0) Above normal (≥ 94 cm) 162 (32.7) 334 (67.3) 496 (100.0) χ2 = 50.354 df = 1; p < 0.0001* Females Normal (< 80 cm) 66 (88.0) 9 (12.0) 75 (100.0) Above normal (≥ 80 cm) 879 (64.5) 483 (35.5) 1362 (100.0) χ2 = 17.380 df = 1; p < 0.0001* 92 S Afr Fam Pract 2017; 59(3):87–93 Globally, osteoporosis has been reported to be more prevalent among older females compared with males due to their postmenopausal state. We found female sex to be an independent risk factor for developing osteoporosis with a fourfold risk among the older women. This was also reported in a Nigerian study in which a majority of those in the study group with osteoporosis were female.1 The prevalence of osteoporosis among the female respondents (65.8%) was higher than that reported among the Moroccan older women (35.7%).22 We found a 6.9% increase in the risk of developing osteoporosis with each one-year increase in age. The association between age and osteoporosis was similarly reported in a hospital study in South-Western Nigeria.1 Generally, bone formation and bone resorption processes are well balanced with no net change in the bone mass; however, bone formation exceeds bone resorption in the childhood and early adulthood periods. Between the ages of 30 and 40 years, the BMD plateaus, after which bone resorption exceeds bone formation with a decline in BMD throughout the rest of life, which in turn may lead to osteoporosis.9 Low education has been reported as an independent risk factor for the development of osteoporosis23 and this was not different in our study as respondents without formal education had 1.4 times the risk of developing osteoporosis. Lifestyle habits of tobacco smoking and alcohol consumption in the respondents were not independently associated with osteoporosis. We could not draw any conclusion on this as few of the respondents engaged in these lifestyle habits. Also, the amount of alcohol consumed by the respondents was not ascertained. Studies have shown a dose–response relationship between tobacco smoking and osteoporosis.24 However, the relationship between alcohol consumption and osteoporosis is unclear.25 Body size has been found to strongly influence bone mineral density and by extension the development of osteoporosis. Generally, obesity was thought to be protective against osteoporosis and fragility fracture, but a recent review has challenged this assumption.26 Obesity causes increased mechanical loading from bodyweight and increases pancreatic secretion of hormones promoting bone homeostasis and formation.26 In our study, however, obese respondents were at three times less risk of developing osteoporosis compared with those with normal body mass index. Table 5: Logistic regression analysis of significant variables associate with osteoporosis *Significant at 5% level of significance. Factor B Wald p OR 95% CI for OR Lower Upper Age 0.066 84.789 0.001* 1.069 1.054 1.084 Sex (females) 1.401 112.076 0.001* 4.061 3.133 5.263 Currently married −0.297 2.257 0.133 0.743 0.505 1.095 Not engaged in occupation- al activities 0.220 4.554 0.033* 1.246 1.018 1.526 Living ar- rangement 4.909 0.179 With spouse 0.053 0.058 0.809 1.054 0.687 1.618 With chil- dren/grand- children −0.052 0.110 0.740 0.949 0.697 1.293 With relatives and friends 0.995 4.330 0.037* 2.705 1.060 6.908 Social support 11.475 0.009* From spouse 0.654 1.449 0.229 1.924 0.663 5.582 From chil- dren/grand- children 1.247 9.173 0.002* 3.482 1.553 7.805 From relatives and friends 0.998 6.432 0.011* 2.712 1.254 5.864 Did no sporting ac- tivities while in school 0.374 11.252 0.001* 1.453 1.168 1.808 Using med- ication for peptic ulcer disease 0.576 8.656 0.003* 1.780 1.212 2.613 First hospital admission 7.651 0.022* Before the age of 60 years 0.128 1.125 0.289 1.138 0.897 1.441 After the age of 60 years 0.344 7.482 0.006* 1.410 1.103 1.805 Waist cir- cumference (normal) 0.669 24.075 0.001* 1.953 1.495 2.551 Had no formal education 0.319 7.077 0.008* 1.376 1.088 1.740 Financially supported by others 0.511 20.954 0.001* 1.667 1.339 2.075 Not obese (BMI < 30 kg/m2) 1.197 109.909 0.001* 3.310 2.647 4.141 Not engaged in physical activities 0.083 0.602 0.438 1.087 0.881 1.341 Constant −5.632 72.056 0.000 0.004 Figure 2: Body mass index by prevalence of osteoporosis. Factors associated with osteoporosis among older patients at the Geriatric centre in Nigeria: A cross sectional study 93 12. Alonge TO, Okoje-Adesomoju VN, Atalabi OM, et al. Prevalence of abnormal bone mineral density in HIV-positive patients in Ibadan, Nigeria. J West Afr Coll Surg. 2013 Oct;3(4):1–14. 13. National Population Commission of Nigeria. National and states population and housing tables. 2006 population and housing census of the Federal Republic of Nigeria. 2009. [cited 2011 Feb 14] Available from: www.population.gov.ng 14. Ogunniyi A, Osuntokun BO. Determination of ages of elderly Nigerians through historical events: validation of Ajayi-Igun 1963 listing. West Afr J Med. 1993 Oct–Dec;12(4):189–90. 15. EXA 3000-OsteoSys. Medical econet GmbH. [cited 2015 Sep 12] Available from: www.medical-econet.com 16. National Osteoporosis Guideline Group. Guideline for the diagnosis and management of osteoporosis in postmenopausal women and men from the age of 50 years in the UK. [cited 2013 Nov 13] Available from: www.shef.ac.uk/NOGG/NOGG_pocket_guide_for_healthcare_ professionals 17. World Health Organization. Physical status: the use and interpretation of anthropometry. Technical Report Series no. 854. Geneva: Author; 1995. 18. Haida R, Kalla AA, Mahlouf G. Osteoporosis in developing countries. Best Practice & Research Clinical Rheumatology 2008;22(14):693–708. 19. Maalouf G, Gannagé-Yared MH, Ezzedine J, et al. Middle East and North Africa consensus on osteoporosis. J Musculoskelet Neuronal Interact. 2007 Apr–Jun;7(2):131–43. 20. Cheng XG, Yang DZ, Zhou Q. Age-related bone mineral density, bone loss rate, prevalence of osteoporosis, and reference database of women at multiple centers in China. J Clin Densitom. 2007;10:276–84. https://doi.org/10.1016/j.jocd.2007.05.004 21. Sharma S, Tandon VR, Mahajan A. Preliminary screening of osteoporosis and osteopenia in urban women from Jammu using calcaneal QUS. Indian J Med Sci. 2006;60:183–9. https://doi.org/10.4103/0019-5359.25679 22. Elmaataoui A, Elmachtani Idrissi S, Dami A, et al. Association between bone turnover markers, bone mineral density and vitamin D in Moroccan postmenopausal women. Pathol Biol (Paris). 2014 Feb;62(1):49–54. https://doi.org/10.1016/j.patbio.2013.11.001 23. Allali F, Rostom S, Bennani L, et al. Educational level and osteoporosis risk in postmenopausal Moroccan women: a classification tree analysis. Clin Rheumatol. 2010 Nov;29(11):1269–75. https://doi.org/10.1007/s10067-010-1535-y 24. Ayo-Yusuf OA, Olutola BG. Epidemiological association between osteoporosis and combined smoking and use of snuff among South African women. Niger J Clin Pract. 2014 Mar-Apr;17(2):174–7. https://doi.org/10.4103/1119-3077.127542 25. El Maghraoui A, Ghazi M, Gassim S, et al. Risk factors of osteoporosis in healthy Moroccan men. BMC Musculoskelet Disord. 2010;11:148– 53. https://doi.org/10.1186/1471-2474-11-148 26. Patel R, Rodriguez A, Yasmeen T, et al. Impact of obesity on osteoporosis: limitations of the current modalities of assessing osteoporosis in obese subjects. Clinic Rev Bone Mineral Metab. 2015;13:36–42. https://doi.org/10.1007/s12018-015-9179-8 27. O’Connell MB, Borgelt L, Bowles SK, et al. Drug-induced osteoporosis in the older adult. Aging Health. 2010;6(4):501–18. https://doi.org/10.2217/ahe.10.42 Received: 10-08-2016 Accepted: 05-12-2016 Certain medications have been associated with the development of osteoporosis. We found a 1.8 increased risk of developing osteoporosis in respondents taking anti-peptic ulcer medications, which include antacids and proton pump inhibitors (PPIs), for long periods of time. Though studies varied on the pathogenesis of osteoporosis among persons taking PPIs, data have suggested a direct inhibitory effect on bone metabolism.27 Conclusions The prevalence of osteoporosis was high among older patients in our settings with risk factors such as age, female sex, low education and prolonged use of peptic ulcer disease medications. Further longitudinal and community-based studies are needed to evaluate the predictive factors for developing osteoporosis. Limitations This study was hospital based, thus it is difficult to generalise its findings. Authors’ contributions – TA, LA and AO conceived the study. LA, OO and AO drafted the manuscript. ML, WB, VOA and TA critically reviewed the manuscript and made conceptual constructs. The final version of the manuscript was read and approved by all the authors. References 1. Jimoh OR, Onabowale BO, Musa OI. 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Building healthy bones throughout life: an evidence-informed strategy to prevent osteoporosis in Australia. Med J Aust. 2013;199(7 suppl):S1–4. 9. Indumati V, Vidya S, Rama J. Hospital based preliminary study on osteoporosis in postmenopausal women. Indian J Clin Biochem. 2007;22(2):96–100. https://doi.org/10.1007/BF02913323 10. Ebesunun MO, Umahoin KO, Alonge TO, et al. Plasma homocysteine, B vitamins and bone mineral density in osteoporosis: a possible risk for bone fracture. Afr J Med Med Sci. 2014 Mar;43(1):41–7. 11. VanderJagt DJ, Bond B, Dulai R, et al. Assessment of the bone status of Nigerian women by ultrasound and biochemical markers. Calcif Tissue Int. 2001;68(5):277–84. https://doi.org/10.1007/BF02390834 http://www.population.gov.ng http://www.medical-econet.com http://www.shef.ac.uk/NOGG/NOGG_pocket_guide_for_healthcare_professionals http://www.shef.ac.uk/NOGG/NOGG_pocket_guide_for_healthcare_professionals http://www.rightdiagnosis.com/o/osteoporosis/stats-country.htm http://www.rightdiagnosis.com/o/osteoporosis/stats-country.htm Background Methods Study site Aim of the study Study population Study design Procedure Consent for the study Results Discussion Conclusions Limitations Authors’ contributions References