- Academic Editor
†These authors contributed equally.
Background: Low bone mineral density (BMD) is the hallmark of
osteoporosis, postmenopausal women are more likely to have microarchitectural
deterioration and fracture risks. This study aimed to determine the relationship
between serum creatinine (sCr) levels and osteoporosis in women who are early
postmenopausal. Methods: There were 335 early postmenopausal women (age
40–60 years) in Dongguan, China, included in this cross-sectional study. BMD in
the lumbar spine, femoral neck, and trochanter was measured using dual-energy
X-ray absorptiometry (DXA) and assessed using multivariable-adjusted logistic
regression models based on sCr levels obtained during the first DXA examination.
Results: Without osteoporosis patients had significantly higher sCr
levels than osteoporosis patients. Overall, 75 (22.4%) participants (age, 51.3
Osteoporosis, characterized by low bone mineral density (BMD), microstructural deterioration, and an increased risk of fracture, is particularly prevalent in postmenopausal women [1]. The assessment of osteoporosis’ related risk factors can assist clinicians in preventing, diagnosing, and treating it. The loss of muscle mass has been linked to osteoporosis, as reported in epidemiological studies, and reduced skeletal muscle predicts fractures more accurately than BMD and other clinical risk factors [2, 3]. Consequently, ongoing studies are investigating how bone health is correlated with several less researched or novel biomarkers, including serum creatinine (sCr) [4]. sCr is one of the main metabolites of skeletal muscle [5]. In addition, since one unit of skeletal muscle contains the same amount of creatinine as one unit of creatine, sCr concentration is directly related to skeletal muscle mass [6]. A steady rate (2% of the total creatine per day) of nonenzymatic conversion has been reported between muscular creatine and sCr, which is excreted by the kidneys into the urine [7]. A person’s sCr level is an indicator of the body’s renal function and muscle mass [8]. Muscle catabolism generates creatinine, which is dependent on muscle mass [9]. Therefore, systemic muscle mass can be measured using circulating levels of creatinine [10]. Previous studies have found that patients on dialysis and those with end-stage renal disease have higher rates of low BMD and fractures and it is well known that renal function plays a key role in osteoporosis [11, 12, 13]. Considering the relationship between bones and muscles based on these findings, the decrease in sCr levels may also be associated with the decrease in BMD in individuals without renal insufficiency. In addition, early postmenopausal women undergo many physical changes due to dramatic hormonal changes in the body. However, a few researches on the association between sCr levels and osteoporosis in early postmenopausal women. For this, the data in a subsample of 335 early postmenopausal women aged 40–60 years for associations with osteoporosis were analyzed.
The current study was conducted at Dongguan Eastern Central Hospital in China in
2020 as a cross-sectional study. All subjects gave their informed consent for
inclusion before they participated in the study. The study was conducted in
accordance with the Declaration of Helsinki, and the protocol was approved by the
Ethics Committee of Dongguan Eastern Central Hospital. Participation in the study
was based on the following criteria: natural menopause; age 40–60 years;
presence of a uterus; Han nationality; no history of hypertension, diabetes,
tumors, or chronic infections related to the heart, brain, lung, kidney, liver,
or kidney and liver; not using medication (including steroid therapy, oestrogen
therapy, and other treatments); and not using other treatments. Individuals with
an estimated glomerular filtration rate (eGFR)
Participant inclusion flowchart. BMD, bone mineral density.
The bone mineral density (BMD) of the lumbar spine was assessed at the Bone
Density Testing Laboratory of the Dongguan Eastern Central Hospital using
dual-energy X-ray absorption (DXA) (Norland XR-800, Swissray Asia, Taiwan,
China). To reduce error probabilities, an experienced operator followed a
standardised procedure on the same machine. Before examining each participant,
the machine was subjected to a standard quality-control program. After
calibration of the software used by the machine, the accuracy of the instrument
for measuring BMD was 0.859, and the long-term coefficients of variation were
0.51 at the lumbar spine, femoral neck, and femoral trochanter BMD in the second,
third, and fourth lumbar vertebrae; left femoral neck; and left troch were
measured. BMD is a measure of weight per square centimetre. The BMD measurements
are expressed as grams per square centimetre and divided into the following
categories according to the World Health Organization standards [15]: normal
(T-score
During the baseline examination, each participant underwent a thorough clinical evaluation and completed a questionnaire. The menopause rating scale (MRS) is a simple and effective tool to evaluate menopausal symptoms, which includes the assessment of 11 common symptoms during menopause, such as hyperhidrosis, palpitations, and insomnia. Baseline measurements were taken without shoes while the participants wore light clothing. A body mass index is calculated by multiplying a person’s weight by his or her height. In addition to age and physical exercise, the recorded data included smoking habits (regular/never), alcohol consumption (regular/never), and menopause duration (months). As part of a regular physical activity plan, participants walked for 30 minutes four times a week or performed vigorous physical activity for at least 20 minutes three times a week. A woman was considered postmenopausal if she had amenorrhoea for six consecutive months. There were two groups of participants, osteoporosis-prone and non-osteoporosis-prone.
The red blood cell count, mean platelet volume, serum uric acid level, and sCr
level (biochemical indicators) were evaluated in the laboratory. During 8:30 AM
and 10:00 AM, blood samples were collected from participants that had
fasted overnight for at least 8 hours. Testing was performed on all
blood samples at Dongguan Eastern Central Hospital’s Clinical Laboratory (XT4000i
System, Sysmex, Foshan, Guangdong, China; C16000 Integrated System, Architct,
Abbott Park, IL, USA). The reference measurement ranges of the red blood cell
count and mean platelet volume were 2.3–6.5
In continuous variables, the mean is expressed as the mean
As shown in Table 1, the baseline characteristics of the 335 early
postmenopausal women are summarized. Their mean age was 49.0
Early postmenopausal women | |||||
Total (n = 335) | No Osteoporosis (n = 119) | Osteopenia (n = 147) | Osteoporosis (n = 69) | p-value | |
Age (years) | 49.0 |
46.9 |
49.68 |
51.2 |
|
MT (months) | 23.7 |
13.52 |
25.2 |
38.38 |
|
MRS | 13.4 |
13.1 |
13.8 |
13.0 |
0.674 |
BMI (kg/m |
23.9 |
23.8 |
23.9 |
24.0 |
0.715 |
Smoking, n (%) | 52 (15.5%) | 17 (14.3%) | 27 (18.4%) | 8 (11.6%) | 0.083 |
Alcohol consumption, n (%) | 163 (48.7%) | 53 (44.5%) | 73 (49.7%) | 37 (53.6%) | 0.395 |
Activity, n (%) | 122 (36.4%) | 49 (41.2%) | 53 (36.1%) | 20 (29.0%) | 0.244 |
RBC (×10 |
4.4 |
4.5 |
4.5 |
4.3 |
0.040 |
MPV (fL) | 9.7 |
9.9 |
9.6 |
9.3 |
0.046 |
sCr (µmol/L) | 55.9 |
56.4 |
57.1 |
52.2 |
0.002 |
UA (µmol/L) | 300.9 |
304.9 |
305.4 |
284.6 |
0.176 |
BUN (mmol/L) | 5.0 |
4.5 |
4.7 |
4.5 |
0.470 |
L2–L4 BMD (g/cm |
0.9 |
1.1 |
0.9 |
0.7 |
|
L-Total BMD (g/cm |
1.0 |
1166.5 |
987.0 |
751.6 |
|
Fem neck BMD (g/cm |
0.8 |
0.9 |
0.7 |
0.7 |
|
Troch BMD (g/cm |
0.6 |
0.7 |
0.6 |
0.5 |
|
L-hip Total BMD (g/cm |
0.8 |
972.1 |
815.3 |
716.8 |
The data are expressed as a mean
In Table 2, we performed linear regression analysis and found no linear
correlation between creatinine levels and BMD site values (p
β | SE | p-value | |
L2–L4 BMD | 6.943 | 0.118 | 0.524 |
L-Total BMD | 0.001 | 0.019 | 0.913 |
Fem neck BMD | –5.099 | –0.071 | 0.630 |
Troch BMD | 0.747 | 0.009 | 0.952 |
L-hip Total BMD | 0.001 | 0.021 | 0.924 |
L2–L4 BMD, total bone mineral density of the second to the fourth lumbar vertebrae; L-Total BMD, total bone mineral density of the lumbar vertebrae; Fem neck BMD, the bone mineral density of the left femoral neck; Troch BMD, the bone mineral density of the left femoral trochanter; L-hip total BMD, total bone mineral density of the left hip. SE, standard error
In Table 3, we summarize the analyses of logistic regression. Both models showed
an association between sCr levels and osteoporosis. In the non-adjusted model
(Model 1), sCr levels increased by 1 µmol/L, while the risk of osteoporosis
decreased by 5% (odds ratio [OR], 0.95; 95% confidence interval [95% CI],
0.92–0.98; p
Variable | Model 1 | Model 2 |
OR (95% CI) | OR (95% CI) | |
sCr (µmol/L) | 0.95 (0.92–0.98) | 0.96 (0.93–0.99) |
Binary variable | ||
Quartile 1 (29.00–52.68) | Ref. | Ref. |
Quartile 2 (52.90–64.00) | 0.42 (0.22–0.78) | 0.42 (0.21–0.86) |
Quartile 3 (64.22–94.00) | 0.44 (0.23–0.83) | 0.46 (0.22–0.94) |
p-value | 0.009 | 0.027 |
Model 1: non-adjusted Model. Model 2: adjusted for age, MT, MRS, BMI, smoking habits, alcohol consumption, activity, UA, and BUN. BMD, bone mineral density; BMI, body mass index; BUN, serum blood urea nitrogen; MRS, menopause rating scale; MT, menopause time; OR, odds ratio; 95% CI, 95% confidence interval; sCr, serum creatinine; UA, serum uric acid.
Based on their urinary creatinine levels, the participants were divided into
triplets. During quartile 1 (Q1), 52.90–64.00 µmol/L in Q2, 64.22–94.00 µmol/L
in Q3, creatinine in each quartile ranged from 29.00–52.68 µmol/L. No
significant trends were observed in Age, MRS, Drinking, Smoking, Activity, menopause
time (MT), RBC, and MPV levels as the quantile increased, while there were significant
differences in BMI (p
Graph comparing bone mineral density in the lumbar spine. In the L-Total (A), in the fem neck (B) and in the Troch (C), the L2–L4 (D), and the L-hip Total (E).
Q1 (n = 134) | Q2 (n = 148) | Q3 (n = 53) | p-value | |
Age (years) | 49.100 |
48.670 |
49.700 |
0.412 |
BMI (months) | 23.620 |
24.100 |
23.920 |
0.043 |
MRS (kg/m |
12.490 |
14.000 |
14.060 |
0.195 |
Drinking, n (%) | 69.000 (51.500) | 63.000 (42.600) | 31.000 (58.500) | 0.096 |
Smoking, n (%) | 21.000 (15.700) | 21 (14.200) | 10 (18.900) | 0.721 |
Activity, n (%) | 42.000 (31.300) | 59.000 (39.900) | 21.000 (39.600) | 0.289 |
MT (months) | 23.820 |
23.260 |
24.890 |
0.908 |
RBC (×10 |
4.470 |
4.430 |
4.450 |
0.763 |
MPV (fL) | 9.610 |
9.740 |
9.630 |
0.797 |
eGFR | 118.060 |
96.360 |
78.360 |
|
UA (µmol/L) | 281.350 |
305.370 |
337.960 |
|
BUN | 4.730 |
4.950 |
5.700 |
|
L2–L4 BMD (g/cm |
0.920 |
0.950 |
0.950 |
0.158 |
L-Total BMD (g/cm |
977.970 |
1019.560 |
1015.450 |
0.167 |
Fem neck BMD (g/cm |
0.770 |
0.780 |
0.780 |
0.778 |
Troch BMD (g/cm |
0.640 |
0.650 |
0.640 |
0.619 |
L-hip Total BMD (g/cm |
842.280 |
855.420 |
858.890 |
0.630 |
The data are expressed as a mean
In this study, we determined whether sCr levels are associated with osteoporosis in early postmenopausal women. According to our findings, sCr negatively correlated with osteoporosis risk among early postmenopausal Chinese women aged 40–60. Additionally, this association remained negative in subgroups stratified by age, menopause duration, hyperuricemia, smoking habits, and alcohol consumption.
Under normal renal function conditions, several steps were taken to analyse the
relationship between sCr and osteoporosis. First, participants with heart, brain,
lung, kidney, rheumatoid, or liver diseases; those with hypertension, diabetes,
tumour, or chronic infection; those using hormone replacement therapy; and those
with an eGFR
In previous studies, abnormal renal function was associated with reduced bone mass [17, 18]. sCr is an important measure of kidney function. A high sCr level indicates impaired kidney function. The relationship between high sCr levels and BMD in patients with chronic kidney disease has been reported by several studies [17, 19]. A certain amount of creatinine is metabolised by the body when renal function is abnormal. However, renal function impairs sCr excretion, and high sCr levels are not associated with muscle mass [20]. Patients with abnormal renal function also lose bone because of altered calcium and vitamin D metabolism [21, 22]. As a result, individuals with renal dysfunction are at risk for osteoporosis when they have high sCr levels. Contrary to previous studies, our study consistently found a positive correlation between sCr and body mass index among patients with normal renal function. This difference is possibly attributable to the difference in renal function affecting sCr. Creatinine is normally metabolised and excreted by individuals with normal renal function. For participants with high sCr responses, muscle mass and physical activity were higher, and sCr was a stable indicator of human muscle metabolism [23]. Consequently, higher sCr levels correspond to greater muscle mass, which protects against osteoporosis in a normal population.
Osteoporosis and sarcopenia are common health problems among postmenopausal
women [24]. Reduced muscle mass and sarcopenia are known risk factors for
osteoporosis [25]. As muscle mass decreases, falls and fractures are more likely
to occur [26]. Increased morbidity and mortality can result from the gradual
deterioration of bone and muscle (osteoporosis and sarcopenia) [27]. Sarcopenia
is associated with a decrease in BMD and a greater risk of osteoporosis [28, 29, 30].
Muscle accounts for 40% of body mass, thereby making it the largest organ of the
body [31]. Sarcopenia causes the loss of muscle mass and strength [32]. Several
studies have shown that combining sarcopenia and osteoporosis as “movement
disorder syndrome” is more inclusive of cases; furthermore, their combination
integrates their pathogenesis and unifies them as one therapeutic target [33].
Several strategies can be implemented to improve bone health and reduce
fractures. These strategies include early diagnosis and prevention. A protective
or risk factor assessment determines whether a particular characteristic or
exposure increases the likelihood of developing osteoporosis. A risk assessment
may assist in preventing osteoporosis-related fractures by detecting osteoporosis
at an early stage [34]. Despite the clarity of the definition of osteoporosis,
sarcopenia remains a mystery [35]. The DXA measurement of body composition,
including bone density and muscle mass, is currently the gold standard for
evaluating body composition [36]; however, because of financial and time
constraints, it is not readily accessible by the general population. An increase
or decrease in muscle mass may affect the sCr concentration [37]. sCr is a stable
marker of skeletal muscle quality, which may be related to bone health [38].
Despite this, there is little evidence of a correlation between the sCr level and
BMD, especially during early menopause. Based on the Fourth Korea National Health
and Nutrition Examination Survey data, Huh et al. [39] conducted a
cross-sectional study to investigate the relationship between sCr and BMD in
older adults with good renal function and provided the first clinical evidence
indicating that low sCr is associated with low BMD. These findings provide a
basis for further research. In our study, the sCr level was linearly associated
with BMD levels of early postmenopausal women, which is consistent with the
research results observed during studies performed in South Korea [39]. The sCr
level was affected by the eGFR, but we excluded cases of kidney-related diseases
from the study population and participants with an eGFR
This study has some limitations. First, because cross-sectional studies only measure once at one point in time and cannot be used to analyze behavior over time or establish long-term trends, the results of this study do not yet establish causal inferences about the association between sCr and osteoporosis in early postmenopausal women. Therefore, a longitudinal study is necessary to clarify the role of creatinine metabolism in bone health. Second, although we considered the effects of medicines and diseases that can affect BMD, unidentified confounders exist. Third, dietary variables including protein, calcium and vitamin D supplements were not measured in this study. Among them, since protein intake can significantly affect sCr levels, we need to reduce the influence of this confounder in further studies.
In conclusion, this cross-sectional analysis found an inverse association between sCr levels and BMD among early postmenopausal women. sCr levels can be used to indirectly assess bone and muscle health and to further treat and prevent sarcopenia and low BMD. The relationship between sCr levels and BMD among early postmenopausal women also provide evidence for future markers of osteoporosis.
In accordance with the authors’ obligations, raw data supporting the article’s conclusions will be made available to the public without undue delay.
All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by YHC and SGZ. The manuscript was written by SHC and RJL. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript.
All subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Dongguan Eastern Central Hospital approved the study (approval number: 2020033).
The research team acknowledges all the investigators’ contributions to the study.
This research was funded by the Dongguan Science & Technology Bureau (project no. 202050715035199).
The authors declare no conflict of interest.
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