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 Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 4  |  Issue : 3  |  Page : 394-402

Bone mineral density in young adult Egyptian women and its relations to different anthropometric measures


1 Department of Internal Medicine, Faculty of Medicine for Girls, Al Azhar University, Cairo, Egypt
2 Department of Endocrinology and Metabolism, Faculty of Medicine for Girls, Al Azhar University, Cairo, Egypt

Date of Submission28-Apr-2020
Date of Decision14-May-2020
Date of Acceptance19-May-2020
Date of Web Publication2-Oct-2020

Correspondence Address:
MBBCh Noura Z Hamoda
Department of Internal Medicine, Faculty of Medicine (Girls), Al Azhar University, Cairo, 11511
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/sjamf.sjamf_52_20

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  Abstract 


Background Low bone mass often leads to osteoporosis and increased risk of bone fractures. Body composition is a new aspect that may contribute to an imbalance, leading to decreased bone mineral density (BMD) and general bone health.
Objective This study was done to evaluate the BMD in young adult Egyptian women by using dual-energy radiograph absorptiometry (DEXA) technique and to identify probable relations between different anthropometric measures and BMD.
Patients and methods This study was performed at the Internal Medicine Department of Al-Zahraa University Hospital from March 2019 to August 2019 on 80 adult Egyptian women. Their ages ranged from 18 to 40 years old. All study participants were subjected to anthropometric measurements, including weight, height, BMI, waist circumference, hip circumference, and waist/hip ratio; assessment of body composition, including fat mass, lean mass, and water volume in the body, using bioelectrical impedance by body fat analyzer 905; and assessment of BMD using dual-energy radiograph absorptiometry technique at the lumbar spine, left femoral neck, and left forearm.
Results Based on WHO diagnostic criteria, osteoporosis was present in 3.75% of samples, whereas osteopenia represented 25% of the cases. There were highly positive significant associations between BMD and each of weight, height, serum alanine transferase, and CA levels, and there was a positive significant association between BMD and each of age, BMI, waist circumference, and hip circumference.
Conclusion A significant portion of adult women are at high risk of development of osteoporosis and increased risk of bone fractures. So young women in particular need to be aware of their vulnerability to osteoporosis. They can take steps early to slow its progress and prevent complications.

Keywords: anthropometric measures, body composition, bone mineral density


How to cite this article:
Hamoda NZ, Eltokhy HM, Mohamed EF, Mohammed DS. Bone mineral density in young adult Egyptian women and its relations to different anthropometric measures. Sci J Al-Azhar Med Fac Girls 2020;4:394-402

How to cite this URL:
Hamoda NZ, Eltokhy HM, Mohamed EF, Mohammed DS. Bone mineral density in young adult Egyptian women and its relations to different anthropometric measures. Sci J Al-Azhar Med Fac Girls [serial online] 2020 [cited 2020 Oct 26];4:394-402. Available from: http://www.sjamf.eg.net/text.asp?2020/4/3/394/296947




  Introduction Top


Osteoporosis is a worldwide prevalent disease characterized by reduction of bone mass and alteration of bone architecture, resulting in increased bone fragility and increased fracture risk [1].

Osteoporosis is defined as ‘a skeletal disorder characterized by compromised bone strength leading to an increased risk of fracture.’ Moreover, according to the WHO criteria, osteoporosis is defined as a bone mineral density (BMD) that lies 2.5 SD or more below the average value for young healthy women (a T score of <2.5 SD), whereas a T score between −1 and −2.5 is diagnostic of osteopenia [2].

Postmenopausal osteoporosis (type I) and age-related osteoporosis (type II) are the most common primary forms of bone loss seen in clinical practice.

Secondary causes of osteoporosis include hypercortisolism, hyperthyroidism, hyperparathyroidism, alcohol abuse, and immobilization [3].

Osteoporosis is a silent disease without obvious symptoms and evidence until a fracture occurs [4].

The gold standard for diagnosing osteoporosis used BMD measurements, especially in the hip and lumbar spine with the dual-energy radiograph absorptiometry (DEXA) device [5].

Screening by DEXA is important to obtain an early diagnosis and to avoid fractures [6].

Several studies have attempted to discover associations between anthropometric measures such as weight, height, and fat mass and BMD. A low body weight is shown to be associated with low bone mass and increase risk of fractures [7]. It has also been shown that body height is positively associated with higher calcium absorption. It has also been postulated that some anthropometric factors like patient’s weight could be used to increase the diagnostic value of BMD in women at risk of osteoporotic fractures [8].


  Aim Top


The aim was to evaluate BMD in young adult Egyptian women and to identify probable relations between it and different anthropometric measures.

Inclusion criteria

Young adult Egyptian women with age ranged between 18 and 40 years were included.

Exclusion criteria

Women under the age of 18 years with early menopause, chronic kidney disease, diabetes mellitus, vitamin D or CA supplementation in the past 6 months, pregnant women, and patients wearing pacemaker were excluded.


  Patients and methods Top


This study was conducted on 80 adult Egyptian women at the Internal Medicine Department of Al-Zahraa University Hospital from January 2019 to June 2019 after obtaining local medical ethics committee approval and consent from all the patients in the study.

Methods

All participants were subjected to the following: full medical history taking, complete clinical examination, and laboratory investigations, including complete blood count, serum CA, phosphorus, creatinine, albumin, alanine transferase (ALT), and aspartate transferase (AST) levels.

Anthropometric measurements

Height was recorded without shoes using a wall stadiometer to the nearest 1 mm. Patients were weighed using a clinical balance, wearing light clothing and without shoes, to the nearest 0.1 kg. BMI was calculated as weight (kg)/height (m2) [9]. The waist circumference was measured at a level midway between the lowest rib and the iliac crest. The hip circumference may likewise be measured at its widest part of the buttocks or hip.

Assessment of body composition

Body composition, including fat mass, lean mass, and water volume in the body, was assessed using bioelectrical impedance by body fat analyzer 905. Maltron body fat analyzer measures the flow of electrical signals as they pass through fat mass, lean mass, and water volume in the body. When the amount of body fat mass, lean body mass, or body water changes, so does the signals, giving a highly reliable and accurate measure of the amounts of each of these components that make up the total body weight [10].

Assessment of bone mineral density

BMD was measured by using DEXA (en CORE 2010) device, model 8743, manufactory Lunar (Wisconsin, USA) [7]. It is the preferred technique for measuring BMD. Diane [11] reported that a normal BMD is not more than −1 SD below the mean value of peak bone mass in young adult women. Osteopenia is indicated by a BMD of between −1 and −2.5 SD below the mean value. The BMD of a patient with osteoporosis is −2.5 SD below the mean value of peak bone mass. BMD was measured at the lumbar spine L1–L4, left femoral neck, and left forearm.

Statistical analysis

Data were collected, coded, revised, and entered to the statistical package for social science version 20 (SPSS Inc., version 20) (IBM Corp. Released 2011. IBM SPSS statistics for windows, version 20.0. Armonk, NY: IBM Corp). The data were presented as number and percentages for the qualitative data, and as mean, SD and ranges, median, and interquartile range for quantitative data with parametric distribution. Statistical presentation and analysis of the present study was conducted using the mean, SD, analysis of variance test, c2 test, and Kruskal–Wallis test by SPSS, version 20.[Inline 1]

Where ∑=sum and n=number of observations.

x=independent variable.

SD[Inline 2]

P value more than 0.05 was considered nonsignificant, P less than 0.05 as significant, and <0.001 as highly significant.


  Results Top


This study was conducted on 80 female participants. Their ages ranged from 18 to 40 years, with mean of 26.04±3.89 years. Based on the WHO diagnostic criteria, they were classified according to the result of DEXA study into three groups:
  1. Normal DEXA group: this comprised 57 (71.25%) patients whose T score was more than or equal to 1.
  2. Osteopenic group: this comprised 20 (25%) patients whose T score ranged from −1 to −2.5
  3. Osteoporotic group: this comprised three (3.75) patients whose T score was less than
  4. −2.5, as shown in [Figure 1].
    Figure 1 Diagnosis of participants according to the results of DEXA scan. DEXA, dual-energy radiograph absorptiometry.

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The results and data were collected and analyzed and are presented in [Table 1],[Table 2],[Table 3],[Table 4],[Table 5],[Table 6],[Table 7] and [Figure 1],[Figure 2],[Figure 3],[Figure 4],[Figure 5],[Figure 6],[Figure 7].
Table 1 Demographic data of all studied participants

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Table 2 Anthropometric measures and body composition of all studied participants

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Table 3 Dual-energy radiograph absorptiometry scan (T score) in all studied participants

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Table 4 Laboratory data in all studied participants

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Table 5 Correlation of bone mineral density of AP spine, left femur, and left forearm with age and different anthropometric measures of the studied participants

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Table 6 Correlation of bone mineral density of AP spine, left femur, and left forearm with different body composition of the studied participants

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Table 7 Correlation of bone mineral density of AP spine, left femur, and left forearm with different laboratory data of the studied participants

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Figure 2 Correlation of BMD of AP spine and body weight of the studied participants. BMD, bone mineral density. AP, antro-posterior.

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Figure 3 Correlation of BMD of AP spine and height of the studied participants. BMD, bone mineral density. AP, antro-posterior.

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Figure 4 Correlation of BMD of left femur with body weight of the studied participants. BMD, bone mineral density.

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Figure 5 Correlation of BMD of left femur with body height of the studied participants. BMD, bone mineral density.

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Figure 6 Correlation of BMD of left femur with fat mass of the studied participants. BMD, bone mineral density.

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Figure 7 Correlation of BMD of left femur with muscle mass of the studied participants. BMD, bone mineral density.

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Descriptive data

[Table 1] are descriptive tables that show mean±SD and range of demographic data ([Table 1]), anthropometric measures and body composition ([Table 2]), results of DEXA scan (T score) ([Table 3]), and laboratory data in all studied participants ([Table 4]).

Correlative data

[Table 5] shows no significant positive correlations of age with BMD of antro-posterior (AP) spine, left femur, and left forearm.

There were highly significant positive correlations of BMD of AP spine and left femur with weight and height of the studied participants ([Table 5] and [Figure 2],[Figure 3],[Figure 4],[Figure 5]). Moreover, there were significant positive correlations of BMD of AP spine and BMI.

[Table 5] also shows highly significant positive correlations of BMD of left femur and the BMI, whereas there were no significant correlations of BMD of left forearm with the different anthropometric measures (weight, height, and BMI) of the studied participants ([Table 5]).

[Table 6] shows that there were no significant correlations of BMD of AP spine and left forearm with muscle mass, fat mass, and total body water of the studied participants.

However, there was a significant negative correlation of BMD of left femur with muscle mass% ([Figure 6]) and a significant positive correlation with fat mass% of the studied groups.

[Figure 7] shows there was no significant negative correlation of BMD of left femur with total body water of the studied participants.

There were significant positive correlations of hemoglobin and mean corpuscular volume (MCV) levels and a highly significant positive correlation of serum ALT level with BMD of AP spine of the studied participants ([Table 7].

[Table 7] also shows a significant positive correlation of BMD of left femur with serum ALT level and highly significant positive correlation with serum CA level of the studied participants.


  Discussion Top


Our results revealed that there was a highly positive significant correlation between BMD of AP spine and each of weight, height, BMI, and ALT level, and a significantly positive correlation with hemoglobin and MCV levels. Meanwhile, femur BMD showed a highly significant positive correlation with each of weight, height, BMI, and CA level; a significant positive correlation with fat mass% and ALT level; and a significant negative correlation with muscle mass%. However, forearm BMD had no correlation with any parameter.

Our results revealed that no significant positive correlations of the age with BMD of AP spine, left femur, and left forearm.

This is in agreement with Nicholas et al. [12], who found that in the proximal femur, age was not an independent predictor of BMD at any site.

This is in disagreement with Ahmet et al. [13]. Their study was conducted on 30–39-year age group of women and 20–29 year age group of men as a reference group. They revealed that BMD decreases rapidly with age for both sexes and in all races.

Our results revealed that there was a highly significant positive correlation of BMD of AP spine and left femur with weight of the studied participants.

This is in agreement with Eslam et al. [14], who conducted a study on 100 adult women. Women’s ages ranged from 19 to 45 years old. Their results revealed that weight was significantly decreased for osteoporotic cases as compared with osteopenia and normal cases.

Gourlay et al. [15] reported that weight was the most important determinants of a BMD at all sites. Their study was conducted on 109 community-dwelling postmenopausal women aged 50–64 years of mixed race and ethnicity who self-reported postmenopausal status, had no prior treatment for osteoporosis, and had weight less than 139 kg.

Lloyd et al. [16] also agreed with our results, as they concluded that a 10 U increase in BMI (e.g. from normal BMI to obese) would result in moving an individual from an osteoporotic BMD level to a normal BMD level. They also demonstrated a protective cross-sectional association between obesity and osteoporosis in a sample of US older adults.

Our results revealed that there was a highly significant positive correlation of BMD of AP spine and left femur with height of the studied participants.

This is in agreement with AghaeiMeybodi et al. [17]. The data of their study were collected from 4445 participants, who were sampled from healthy men and women with age 20–70 years old. The participants comprised 1900 (42.7%) males and 2545 (57.3%) women, residing in various regions of Iran using randomized clustered sampling. They reported that BMD was significantly correlated to height.

This is in disagreement with Eslam et al. [14], who revealed that height had no significant effect on BMD of Saudi adult young women.

This difference may be owing to the difference in the genetic background of their patients and ours.

Our results revealed that there was a significant positive correlation of BMD of AP spine and left femur with BMI.

This is in agreement with Isabel et al. [18]. Their study was conducted on 4106 participants at 18 years of age (follow-up rate: 81.3%), whereas at 22 years of age, 3810 individuals were interviewed (follow-up rate: 76.3%). Body composition data were available for 2968 of the participants assessed at both follow-ups, of whom 1560 (52.6%) were women. They reported that BMI had a positive effect on bone mass at age of 18–22 years.

Moreover, the results were in agreement with Eslam et al. [14], who revealed that there was a highly positive significant correlation between BMD and BMI.

Moreover, Arimatsu et al. [19] in a study of correlation between body composition and BMD of the forearm in young Japanese women aged 18 through 40 years who had undergone an Annual Women’s Health Examination showed a positive correlation between BMD and BMI.

Nicholas et al. [12] found that muscle strength was an independent predictor of BMD at all three sites in the proximal femur as well as in the lumbar spine and forearm; proximal femur BMD was also predicted by physical fitness. BMI was a positive predictor of bone mass at all sites.

Our study revealed that there were no significant correlations of BMD of AP spine and left forearm with muscle mass%, fat mass%, and total body water% of the studied participants.

Moreover, there were significant negative correlations of BMD of left femur with muscle mass% (P=0.010) and a significant positive correlation with fat mass% (P=0.010) and no significant negative correlation of BMD of left femur with total body water% of the studied groups.

Eslam et al. [14] revealed that there was a highly positive significant relationship at level (1%) between BMD and each of fat%, fat weight, lean weight, dry lean, and body water with a negative significant correlation at the same level between it and water% in the body.

Moreover, Isabel et al. [18] observed positive effects of fat mass index and lean mass index on bone density at 22 years, with the largest effect observed for lean mass.

These results were in agreement with Sowers et al. [20] who reported that BMD of the proximal femur was similar and significantly greater in the thigh muscle/low fat and thigh muscle/high fat body composition subgroups compared with BMD in the seven other groups, whereas Aloia et al. [21] disagreed with our results, as they reported that they found no evidence that adiposity plays a major role in protecting against bone loss.

Our study revealed that there were significant positive correlations of hemoglobin and MCV levels with BMD of AP spine of the studied participants (P=0.034 and 0.049, respectively), whereas white blood cells and platelet show no association with BMD.

This is in agreement with Yoon et al. [22] who revealed that those with low BMD had lower hemoglobin levels. The explanation may be related to that healthy women loose about 70 ml of blood every month, and this blood loss intensifies hematopoiesis by increasing the level of hematopoietic growth factors, while stimulating proliferation of osteogenic progenitor cells. Blood loss creates developmental pressure on the hematopoietic system, augments production of hematopoietic growth factors with subsequent intensified proliferation of hematopoietic progenitor cells, and increases the number of hematopoietic cells including osteoclasts, thus intensifying resorption of bone tissue and extension of hematopoietic territories [23].

Our study disagrees with Valderrábano et al. [24]. Their study was done on older men and women (ages 65 or older). They found that neither a single hemoglobin measurement nor longitudinal change in hemoglobin would be useful as a marker of low bone density in the short-term in older community. They added also that anemia was not associated with low bone density by T score. White blood cell or platelet counts were also not observed to be associated with BMD.

Our study revealed that there was a highly significant positive correlation of serum ALT level with BMD of AP spine (P=0.000) and no significant positive correlation of serum AST with BMD of AP spine of the studied participants.

This is in disagreement with Ho Jeong et al. [25], who revealed an association between liver enzyme levels and BMD in Korean adults aged 19 or older using KNHANES data. ALT generally displayed a negative relationship with the lumbar spine and whole body BMD, whereas AST showed a negative relationship with lumbar BMD.

Our study revealed that there was a significant positive correlation of BMD of left femur with serum ALT level (P=0.013) and no significant correlation with serum AST level of the studied groups.

In a previous study by Breitling [26] using a comparable study design and model, that was conducted on 13 849 adult participants of the Third National Health and Nutrition Examination Survey, a weak negative association was perceived between ALT and femoral neck BMD, whereas AST failed to reach statistical significance in associations with femoral neck BMD.

Compared with the previous study, Ho Jeong et al. [25] revealed stronger negative relationships between both gamma glutamyle transferase (GGT) and ALT and BMD and did not show the U-shaped relationships with BMD commonly seen at lower values.

Breitling [26] noted a U-shaped association between ALT and femoral neck BMD, and similar U-shaped associations were observed for ALT and mortality, suggesting that very low ALT levels indicate decrepitude. These results, however, are highly disparate from the findings of Ho Jeong et al. [25], where the lowest ALT quartile was linked with high bone mass. These findings may be a result of the difference in BMD measurement region, or alternately be a characteristic of ethnic divergence.Our study revealed that there was a highly significant positive correlation of BMD of left femur with serum CA level (P=0.009) of the studied participants.

Our result is in agreement with Sasmita et al. [27]. Their study patients were between the age group of 25 and 65 years. The study patients were divided into two groups. Group 1 comprised apparently normal postmenopausal women (within age group of 45–65 years). Group 2 comprised apparently normal premenopausal women (between the age group of 25–50 years). They showed that serum CA level is significantly lower in postmenopausal women when compared with premenopausal women. Calcium level also had a positive correlation with T score in both the groups, which explains the role of calcium in osteoporosis.

Our study revealed that there was no significant correlation of BMD of all sites with serum phosphorus level of the studied participants.

However, Sasmita et al. [27] reveled that there was no significant difference of phosphorus level in their patients (premenopausal and postmenopausal) group, but there is a significant positive correlation between the T score and phosphorus level in both the groups [27].


  Conclusion Top


A significant portion of adult women are at high risk of development of osteopenia and later on increased risk of osteoporosis. Young women are in particular need to be aware of their vulnerability to osteoporosis. They can take steps early to slow its progress and prevent complications. High calcium foods and correction of anemia is very important to their bone health and to minimize the risk of osteoporosis.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]



 

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