Effect of nulliparity, Body Mass Index and residency on bone mineral density in women between 40 and 50 years in Al-Medina, KSA

Introduction 30

Low bone mineral density (BMD) represents a significant risk factor for 31

osteoporosis and its associated fractures (1). Over the past decade, 32

osteoporosis has been considered a large-scale health issue by both the 33

public and the medical profession (2). Osteoporosis is a skeletal disease 34

characterized by low BMD and microarchitectural deterioration of bone tissue, 35

which leads to increase in bone fragility and its susceptibility to fractures (2,3). 36

osteopenia is low BMD grade which ends with osteoporosis. 37

Bone tissue remodels itself continuously throughout life, through bone 38

resorption and bone formation (4). As we grow older, bone resorption exceeds 39

bone formation. As a result, bones become osteopenic due to decrease in the 40

stored calcium and minerals in the bones and makes them less dense, lighter 41

in weight and more fragile (1). 42

Bone strength can be assessed by measuring the BMD. (1,5) Currently, dual- 43

energy x-ray absorptiometry (DEXA) is used widely to measure BMD and is 44

considered the gold standard (6). This wide use has enabled specialists to 45

assess BMD in many skeletal sites (7,8), a technique that is verified widely (7) 46

BMD is regulated mainly by genetics, but it is influenced by many	47
environmental factors too, such as pregnancy, period of lactation, body mass,	48
nutrition, physical activity, smoking, alcohol consumption, and Follicle	49
Stimulating Hormone (FSH) deficiency. (3,8,9) Many studies have reported the	50
significant variation in BMD levels by gender, age group, geographical area	51
and ethnicity/race (1). Values of BMD also differ widely between different local	52
regions of one country or nearby countries, such as the Gulf States. (8)	53
Low BMD is a main public health problem around the world, but, in most of the	54
Middle East countries, the epidemiology of osteoporosis is not well known	55
yet.(1,5) osteoporosis also is an important cause of fracture which may keep	56
The person bedridden.These complications	57
could be life-threatening specially among elderly people. (7)	58
Ito et al. reported that the maximum BMD among females is in the mid-30s,	59
and then it tends to decrease with a particularly drastic decrease around	60
menopause(10). According to the WHO, osteoporosis is defined as a BMD that	61
lies 2.5 standard deviations or more below the average value for young	62
healthy women (a T-score of <-2.5 SD)(7). While, Osteopenia is defined as	63
below normal bone density and the precursor to osteoporosis, with a T-score	64
−1 to −2.5(11). Based on global estimates around the world, there are about	65
200 million women have osteoporosis (12). In the USA, osteoporosis affects	66
about 30% of postmenopausal white women, and the ratio rises to 70%	67
among the women over 80 years old (13). While in Saudi Arabia, low BMD is a	68
public health issue as AlQuaiz et al. (2014) reported that 58.6 % of Saudi	69
women >40 years old have a low BMD (12) .	70

Low BMD adversely affects the public health and country's economy in	71
general due to the high medical cost. In addition, almost all previous	72
osteoporosis studies focused on postmenopausal females and some focused	73
on young females, or children (13,14). Therefore, there is still a need to study	74
risk factors related to osteoporosis among women aged 40-50 years, because	75
women at this age are either at early menopause or not reaching menopause,	76
so the hormonal effect will be minimal. Hence, this study aimed to evaluate	77
the effect of nulliparity, body mass index (BMI), and location of residency on	78
BMD in woman aged 40-50 years at king Fahad hospital in medina.	79
MATERIALS AND METHODS	80
Study design and setting:	81
A cross sectional study was conducted in King Fahad hospital in	82
Almadinah Almunwwarah from February to April 2018.	83
Study population and sampling:	84
Inclusion criteria and Exclusion criteria	85
Women whose age is 40-50 years, who had abnormal DEXA scan while they	86
visited King Fahd Hospital for a DEXA scan purpose between the first of	87
January 2015 until the end of August 2017, as a new case or had a previous	88
scan with an abnormal result, whether she had a complaint or not.	89
Study tools:	90
Specialized questionnaire was designed for data collection. Pilot study was	91
done for 50 persons and modification of the form was done by removing items	92

that were hard to collect, and items that were not clear were revised. It covers	93
the socio-demographic data, site of abnormality and its severity (osteoporosis	94
or osteopenia) as well as the data needed to assess the risk factors of	95
osteoporosis as nulliparity, BMI, location of residency, hormone levels,	96
calcium level, previous Gastrointestinal (GI) surgery, medications, chronic	97
diseases.	98
Methods:	99
Mainly the data were obtained from the patients' files and by contacting them	100
through their mobile phones. Ethical approval was obtained from King Fahad	101
Hospital in Medina and from Taibah University. Consent was taken verbally	102
after ensuring the confidentiality of data.	103
Statistical Analysis	104
The Statistical Package for Social Studies (SPSS 22; IBM Corp., New York,	105
NY, USA) was used for data analysis. Chi-square test was used for	106
categorical data and the t- test was used for the quantitative data analysis and	107
p < 0.05 was considered significant.	108
	109
	110
Results:	111
Table 1: participants distribution according to BMI, marital status,	112
residency location, and null- parity.	113
Frequency (n= 271)	Percentage %

Class of BMI	Normal BMI <25 kg/𝑚2 Overweight BMI <30 kg/𝑚2	2 0.7 125 46.1
Obese BMI ≥30 kg/𝑚2	144 53.1
		Frequency (n= 145)	Percentage %
Marital status	Married	120	82.8
	Single	20	13.8
	Divorced	3	2.1
	Widow	2	1.4
		Frequency (n= 245)	Percentage %
Location of Residency	Urban	218	89.0
	Rural	27	11.0

		Frequency (n= 153)	Percentage %
Null parity	Yes	116	75.9
No	37	24.1

114

The mean age of participants is 45.43 years with a standard deviation of 2.879, 115

BMI is calculated through equation: weight in kilograms divided by square of 116

the person's height in meters. the mean BMI of participants' is 30.43 Kg/m2 with 117

a standard deviation of 5.614. Most of participants are married (82.8%), live in 118

urban area (89.0%) and null- parous (75.9%). Table 1 119

120

Table 2: participants' distribution according to DEXA diagnosis for the 121 spine, right femur, and left femur. 122
			Frequency (n=271)	Percentage %
DEXA diagnosis for spine	osteoporosis		62	22.9
	osteopenia		189	69.7
	normal		20	7.4
DEXA diagnosis for right femur	osteoporosis		16	5.9
	osteopenia	86	31.7
	normal	169	62.4
DEXA diagnosis for left femur	osteoporosis	18	6.6
osteopenia	99	36.5
	normal	154	56.8

123

The table shows the participants' distribution according to the diagnosis based 124 on DEXA done for the spine, right femur, and left femur, and shows that, the 125 most affected area was spine with 69.7% osteopenia and 22.9% osteoporosis. 126

127

None 227 91.9

Chronic diseases IBD 1 0.4

Kidney 5

disease 2.0

liver disease 3 1.2

None 238 96.4

GI surgery Yes 5 2.0

No 242 98.0

Previous calcium level High 2 0.8

normal 93 37.7

Low 3 1.2

None 149 60.3

Parathyroid level High 7 2.8

normal 78 31.6

Low 6 2.4

	None	156	63.2
	Missing	24	9.7
Thyroid level	High	4	1.6
	normal	87	35.2
	Low	34	13.8
	None	122	49.4
FSH hormone level	High	9	3.6
	normal	2	0.8
	Low	9	3.6
	None	227	91.9
Serum corticosteroid level	normal	12	4.9
Low	2	0.81%
	None	233	94.33%

131

The participants' distribution according to steroids use, chronic diseases, GI 132 surgery, previous calcium level, parathyroid level, thyroid level, FSH hormone 133 level, and corticosteroid level is shown in table 3, and most of factors were not 134

Table 3: Shows the participants distribution according to steroid use, 128 chronic diseases, GI surgery, previous calcium level, parathyroid level, 129 thyroid level, sex hormone level, and corticosteroid level. 130

		Frequency (n=247)	Percentage %
Steroids use	No	2	0.8
	Yes	18	7.3

available for all patients and majority of them had no history of GI surgery	135
(98.0%).	136
	137
	138
Relations test	139
	140
There is a relationship between DEXA diagnosis for spine, right femur and left femur	141
and BMI, but there is no relationship between DEXA diagnosis and residency location	142
or nulliparity (Table 4).	143
Table 4: The relationship between DEXA diagnosis and (BMI, residency,	144
and nulliparity)	145
		BMI		Residency	Nulliparity
overwei ght	normal	obese	urban	rural	Yes	No
DEXA diagnosis for spine	osteoporosis	36	1	25	47	5	18	7
osteopenia	79	0	110	153	21	83	20
Normal	10	1	9	18	1	7	3
	Chi-Square	12.786		0.942	1.303
	P-value	0.012		0.624	0.521
	osteoporosis	15	0	1	12	2	3	4
DEXA diagnosis for right femur	osteopenia	51	1	34	72	5	26	11
Normal	59	1	109	134	20	79	55
	Chi-Square	29.808			2.369		8.393
	P-value	0.000			0.306		0.015
DEXA diagnosis for left femur	osteoporosis	12	0	6	13	2	5	3
osteopenia	54	2	43	86	5	37	12
Normal	59	0	95	119	20	66	15
	Chi-Square	13.883			4.524		1.880
	P-value	0.008			0.104		0.391

146

Discussion. 147

The current study showed that there is a high prevalence of osteoporosis and 148 osteopenia among the women in the study population. The analysis of DEXA 149 diagnosis for our participants revealed significant differences among 150

measurements of spine and femurs (figure 1). 151

Figure 1. participants distribution for DEXA diagnosis.	153
This difference of BMD among different human body parts could be due to the	154
variation of bone loss velocities between these different parts (16). The	155
presence of BMD differences between different body parts is one of the	156
reasons for measuring BMD in several body sites, which can affect the	157
diagnosis and therapeutic plan in an individual person (17).	158
In the present study, the BMD in the spine was less than the femurs. The	159
spine had the highest prevalence of osteoporosis and osteopenia (22.9% and	160
69.7% respectively). Our findings here are consistent with Moayyeri et al.,	161
finding that lower BMD values were reported in the lumbar spine (17). The	162
literature showed that the vertebral fractures are the most common clinical	163
manifestation of osteoporosis (16). Otherwise, most of the etiologies of the	164
secondary osteoporosis affect the spinal column first (18). In general, the	165
health status and history of our participants were not totally accessible due to	166
change from paper record to electronic one, but we can say that there was no	167
widespread prevalence of chronic diseases or previous surgeries among the	168
participants.	169

High BMI is one of the strongest risk factors for osteoporosis (19). Almost all	170
participants in this study ranged from overweight to obese, our results here	171
revealed an inverse relationship between BMD and BMI. Studies differed in	172
their results regarding the relationship between BMD and BMI as some	173
studies found that increased BMI reduces BMD (19,20), which is consistent with	174
our results. While other studies have found that increased BMI increases BMD	175
and thus reduces osteoporosis (21,22). Differences in results can be explained	176
by the fact that there is a negative genetic correlation between fat mass and	177
weight-adjusted bone mass (19), so fat mass has a negative effect on bone	178
mass in contrast with the positive effect of weight-bearing itself (23) Obesity,	179
therefore, has negative effect on BMD (20).	180
Lifestyles particularly physical activity levels and dietary patterns, generally	181
vary between rural and urban areas. In the current study, the majority of	182
women (89%) were living in Urban areas. There is no relationship between	183
BMD and location of residence. Since the study was in Saudi Arabia, which is	184
a high-income country, our results here are consistent with Matsuzaki et al.,	185
study, which found that in some low and middle-income countries, BMD was	186
higher in urban areas. While in high-income countries, the urban areas didn't	187
show higher BMD (24). While in Norway, Meyer et al., found higher BMD in	188
rural areas compared with urban areas (25). Also, In Thailand, Pongchaiyakul	189
et al., found that BMD of the femoral neck was higher in rural men and women	190
than their counterparts in urban areas (26). This may be because the rural	191
areas are usually having higher level of physical activity, high serum vitamin D	192
level, and lower levels of air pollution. The difference in the results between	193

our study and these studies may be due to the difference of the target group	194
in the studies in terms of age, gender, sample size and time of the study.	195
During pregnancy, the rise in body-weight, multi-vitamin supplement and	196
increasing estrogen hormone are thought to have positive effects on BMD.	197
Otherwise, mothers' inability to compensate for the calcium loss with diet	198
during pregnancy and lactation is thought to exert a negative effect on BMD	199
(27). So, differences appeared in the results of studies about the relationship	200
between nulliparity and BMD. In the present study, about 75.9% of women	201
were null-parous. Our results, showed that there is no relationship between	202
BMD in spine or left femur and nulliparity, but there is an inverse relationship	203
between BMD in the right femur and nulliparity. Terzi et al.; Hillier et al. and	204
Lenorav et al., found that there was no effect of nulliparity on the BMD among	205
women (27,28). While Cure‐Cure et al., found that pregnancies appear to be a	206
protective factor against the development of osteoporosis (29). However,	207
Ozdemir et al., findings indicate that the increased number of pregnancies and	208
abortions and higher age at first pregnancy increases the risk of	209
osteoporosis(30). As well as, Gur, Ali et al., who found that among the group of	210
40-59-year women, the BMD of the spine in both the null-parous and one-to-	211
two-parity groups was significantly higher than that of the more-than-five-	212
parity group. No significant differences were found among the groups with	213
respect to the BMD values at any femur sites (31).	214
Conclusion	215
The study revealed that BMD in the spine is less than femurs. The study	216
showed that there is an inverse relationship between BMD and BMI. There is	217

relationship between BMD on right femur and nulliparity, but not with left.	218
There is no relationship between BMD and residence location.	219
Limitations of the study	220
This study included only females aged 40-50, therefore the results cannot be	221
generalized to males and females at other ages. Also, participants were	222
selected from King Fahd Hospital in Almadinah Almunawwarah only and may	223
not be representative of the general population in Saudi Arabia.	224
	225
Recommendations	226
People should avoid obesity by regular exercise and healthy diet.	227
Factors that were not tested because it was unavailable like FSH level should	228
be tested.	229
There is Need for further studies to consider all factors affecting BMD.	230
Use mass media and lectures to increase awareness and then reduce	231
osteoporosis.	232
	233
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