Association of hemoglobin levels with bone mineral density in the thoracic and lumbar spine for adults over 18 years of age: a cross-sectional study

doi:10.21203/rs.3.rs-1456261/v1

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Research Article

Association of hemoglobin levels with bone mineral density in the thoracic and lumbar spine for adults over 18 years of age: a cross-sectional study

https://doi.org/10.21203/rs.3.rs-1456261/v1

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posted 21 Mar, 2022

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Aim:

The overall object of this study is to find out the association between hemoglobin (HGB) and bone mineral density (BMD) in the lumbar and thoracic spine among adults over the age of 18.

Methods:

The current cross-sectional study used the non-institutionalised US population from the National Health and Nutrition Survey (NHANES) as the sample source. A multiple linear regression model and smoothed curve fitting were used to show the assessment of the relationship between hemoglobin and bone mineral density in the lumbar and thoracic spine, with analysis of subgroups according to gender and race.

Results:

After accounting for relevant confounders, HGB was negatively associated with bone mineral density in multiple regression models. In subgroup analyses stratified by sex or race, however, the relationship between HGB and thoracic spine BMD was only found in women and Mexican-Americans, and the association with lumbar spine BMD was present in males and females, Mexican-American and Non-Hispanic White. Among participants in other races and those whose race was not reported, the relationship between HGB with BMD in the lumbar spine and the thoracic spine showed an inverted U-shaped curve (turning point: HGB 11.9 g/dL).

Conclusion:

HGB was negatively associated with BMD in the lumbar spine and BMD in the thoracic spine. However, this significant correlation varies by gender and race.

Hemoglobin

bone mineral density

Anemia

Osteoporosis

cross-sectional study

Osteoporosis, which most commonly occurs in the hip, spine, and wrist, not only puts people at increased risk of fragility and fracture, but also has a substantial impact on families and society(1, 2).Bone mineral density (BMD), evaluated by dual-energy x-ray assays, accurately captures bone mass and is the gold standard for diagnosing osteoporosis as well as being the best predictor of osteoporotic fracture risk(3). BMD is affected by several factors, including gender, age, genetic factors, nutrition, hormone levels, physical activity, smoking, alcohol, and more. A recent study released by Korkmaz U et al. showed anemia was an independent risk factor for low BMD among post-menopausal women(4).

Hemoglobin(HGB) is found in erythrocytes and its role is to combine with oxygen and transport it from the lungs to the tissues(5).Anemia, characterized by 'low hemoglobin concentration', is a major public health problem prevalent in the low-, middle- and high-income countries worldwide(6), affecting nearly a quarter of the world's population and predominantly mainly on pre-school children and women(7),and is recognized as a risk factor for osteoporosis, falls, fractures and physical decline(8, 9).

Zhou Y etc. conducted a study of 1238 volunteers from Anhui, China, and concluded that a U-shaped curve for the relationship between BMD and HGB in healthy men(10). On the other hand, a positive correlation was found between HGB levels and BMD in patients with chronic obstructive pulmonary disease, chronic kidney disease, sickle cell anemia, and inflammatory bowel disease(11-15). In addition, Zarei T et al. measured BMD and bone mineral content in the lumbar spine and femoral neck of 21 patients over 10 years of age with hemoglobin H disease and concluded that the prevalence of BMD in the lumbar spine and femoral neck region in patients with hemoglobin H disease was significantly lower than the expected age range compared to healthy individuals(16). Cui R et al. adjusted for age, duration of diabetes, body mass index, and alanine aminotransferase to conclude that anemia was associated with osteoporosis in patients with type 2 diabetes mellitus, irrespective of gender(17). Research on the relationship between HGB and BMD are scarce, and previous studies have had limitations in the selection of study populations and sample sizes. Furthermore, It is unclear whether HGB can be used as an indicator to assess anemia while also forecasting the risk of bone loss or osteoporosis.

Therefore, this cross-sectional study was conducted on the basis of the 2013-2018 National Health and Nutrition Survey (NHANES) as a sample source to determine the association between HGB and BMD in the lumbar and thoracic spine in adults aged 18 years and older.

Study population

Data for the analysis was obtained from the National Health and Nutrition Examination Survey (NHANES) (2013-2018)(18-20) ,a large, comprehensive and regularly updated probability sample of the non-institutionalized U.S. population.

The population of study was consisted of participants aged 18 and over who had complete data on HGB and lumbar and thoracic spine BMD. And the NCHS Ethics Review Committee has approved the implementation of the NHANES and received the informed consent of all participants. The study adhered to relevant guidelines and regulations. The encryption procedure is uniform to make it possible to link complaints belonging to the same patient in the NHANES. Detailed documentation of the ethics application and written informed consent is available on the NHANES website(21-23)

Data collection

The following information was collected by two researchers (XZH and SQL):

Demographic data [gender, age, race, annual household income and education level]

Examination data [BMD of the lumbar spine and the thoracic spine, systolic blood pressure (SBP) and diastolic blood pressure (DBP) (mmHg), weight (Kg), standing height (cm), body mass index (BMI) (Kg/m²)]

Laboratory data [HGB(g/dl), red blood cell count (UL), albumin (g/L), alkaline phosphatase (ALP)(IU/L), alanine aminotransferase (ALT)(U/L), aspartate aminotransferase (AST)(U/L), blood urea nitrogen (mmol/L), total calcium (mg/dL), iron (umol/L), creatine phosphor kinase (CPK)(IU/L), gamma glutamyl transferase(GGT) (IU/L), glucose (mmol/L), lactate dehydrogenase (LDH)(IU/L), phosphorus (mmol/L), total bilirubin (umol/L), total protein (g/L), albumin creatinine ratio (mg/g), triglyceride (mmol/L),low-density lipoprotein cholesterol (LDL-C)(mmol/L), high-density lipoprotein cholesterol (HDL-C)(mmol/L) and cholesterol level (mmol/L)]

Questionnaire data [alcohol status (average alcohol drinks/day in the past 12 months), smoking status, diabetes (has a doctor told you that you have diabetes)]

Weight value [Depending on the rules for selecting weight values offered on the NHANES website, “Full Sample Two-Year Mobile Examination Center Exam Weight (WTMEC2YR)” was Selected as representative weighting value]

Subjects younger than 18 years of age, subjects with incomplete BMD and HGB data or subjects with cancer or malignancy were excluded from the study. Treatment of missing values for other variables:1) Completing missing values of continuous variables with mean values; 2) Separating missing values in a categorical variable into a class named " Not recorded ".

Evaluation of HGB

Determination of HGB values according to the information provided on the NHANES website. The Beckman Coulter DxH 800 instrument in the NHANES mobile examination center (MEC) produced a complete blood count (CBC) on blood specimens and provided a distribution of blood cells for all participants. CBC parameter values were obtained by using the Beckman Coulter counting and calibrating method in combination with an automated dilution and mixing device for sample processing and a single beam photometer for HGB measurements. Refer to the Laboratory Method Files section for a detailed description of the measurement of HGB on the NHANES website(24).

Measurement of BMD

Participants were examined using duel energy X-ray absorptiometry (DXA) scans for BMD. The DXA scans provide bone and soft tissue measurements for the total body. We downloaded and collated data relating to the lumbar and thoracic spine from NHANES for the years 2013-2018.The whole body scans were acquired on the Hologic Discovery model A densitometers (Hologic, Inc., Bedford, Massachusetts), using software version Apex 3.2. The radiology technologists involved in DXA examinations are trained and certified. More information about the measurement of DXA examination protocol can be obtained from the NHANES website(25).

Statistical analysis

We used means (continuous variables) or proportions (categorical variables) to describe the baseline characteristics of all participants who were eventually included in the study. Weighted multivariate linear regression models were used to calculate the linear relationship between HGB and BMD. In the meantime, we calculated the unadjusted, minimally adjusted, and fully adjusted results. To further investigate the linear relationship between HGB and BMD of the thoracic and lumbar spine in different populations, a subgroup analysis was performed stratifying the subjects by age and gender. As both exposure factors and outcome indicators are continuous variables, the non-linear relationship between the two was described by a smoothed curve fitting model. All analyses were undertaken by EmpowerStats (version: 2.0. X&Y Solutions, Inc, Boston, MA. http://www. empowerstats.com) and R software, v.3.4.3 (Vienna, Austria: R Foundation for Statistical Computing, 2016 http://www.R-project.org).

Participant selection and General characteristics

Initially, the information of 29400 participants was extracted from the NHANES database 2013-2018. After excluding subjects without HGB data (n=5211), without BMD data (n=10942), under 18 years of age (n=4133) and excluding subjects with cancer, malignancy (n=988), a total of 8126 subjects was included in this study (Figure.1).

The weighted socio-demographic and medical characteristics of the participants are described in Table 1.A total of 8126 participants were included in the original data set. The mean age of these participants was 39.3±11.4years, of which 50.8% were male and 49.2% were female, with Non-Hispanic White being the most numerous. There were significant differences in gender, age, race, annual household income, education level, BMD, SBP, DBP, weight, standing height, BMI, red blood cell count, albumin, ALP, ALT, AST, blood urea nitrogen, total calcium, iron, CPK, GGT, glucose, LDH, phosphorus, total bilirubin, total protein, albumin creatinine ratio, triglyceride, LDL-C, HDL-C, cholesterol, alcohol status, smoking status and diabetes prevalence across the different HGB groups (quartiles, Q1 to Q4).

Table 1 Weighted characteristics of the study population

Hemoglobin(g/dl)	All	Q1	Q2	Q3	Q4	P-value
Demographic and clinical characteristics
Age	39.3±11.4	39.6±10.7	39.2±11.6	39.8±11.9	38.3±11.5	0.0001
gender(%)						<0.0001
Male	50.8	6.6	26.7	65.8	94.3
Female	49.2	93.4	73.3	34.2	5.7
Weight(Kg)	82.6±22.1	78.7±23.0	79.4±22.5	83.5±21.1	89.2±20.5	<0.0001
Standing Height (cm)	167.9±10.0	162.0±7.6	165.6±9.3	170.7±9.8	174.3±8.0	<0.0001
Race(%)						<0.0001
Mexican American	16.1	10.4	9.9	10.8	12.2
Other Hispanic	10.1	7.2	7.0	7.1	6.5
Non-Hispanic White	35.2	56.2	61.1	61.9	62.7
Non-Hispanic Black	20.9	15.4	11.8	10.8	8.7
Non-Hispanic Asian	12.1	6.2	6.0	4.6	6.3
Other Race and Not recorded	5.5	4.7	4.2	4.9	3.6
Education Level(%)						<0.0001
Less than 9th grade	6.7	6.0	5.6	5.4	6.1
9-11th grade (Includes 12th grade with no diploma)	12.0	11.4	9.6	9.9	13.4
High school graduate/GED or equivalent	22.4	17.8	22.2	23.7	22.6
Some college or AA degree	32.3	34.1	32.0	33.0	31.0
College graduate or above	26.6	30.7	30.6	28.0	26.8
Annual Household Income						0.0093
$ 0 to $ 4,999	2.3	3.1	1.5	1.9	1.7
$ 5,000 to $ 9,999	2.8	3.1	2.8	3.2	2.0
$10,000 to $14,999	3.9	3.8	3.4	2.9	3.5
$15,000 to $19,999	4.9	4.8	4.2	3.9	3.5
$20,000 to $24,999	6.0	5.2	5.3	5.4	5.3
$25,000 to $34,999	9.8	9.4	9.1	9.1	8.9
$35,000 to $44,999	15.3	16.1	13.5	14.6	16.7
$45,000 to $54,999	8.2	8.6	9.0	7.1	8.7
$55,000 to $64,999	6.5	6.0	6.3	6.1	7.1
$65,000 to $74,999	5.0	5.1	5.5	5.4	5.3
$20,000 and Over	3.7	2.9	3.5	3.1	3.8
Under $20,000	1.0	1.3	0.9	0.8	0.8
$75,000 to $99,999	10.4	9.4	11.1	11.0	10.9
$100,000 and Over	20.2	21.3	23.8	25.4	21.7
Alcohol Status(%)						<0.0001
<12 oz	69.8	64.7	69.5	74.2	76.3
≥12 oz	0.7	0.2	0.3	0.5	0.9
Not recorded	29.6	35.1	30.1	25.2	22.8
Smoking Status(%)						<0.0001
Every day	16.7	10.3	13.9	18.9	22.8
Some days	4.9	3.5	3.8	4.1	6.8
Not at all	16.6	11.2	15.9	19.0	18.7
Not recorded	61.8	75.0	66.3	58.1	51.7
Diabetes(%)						0.0243
Yes	7.4	7.2	6.1	6.6	5.9
No	90.6	90.1	91.9	91.5	92.1
Borderline	2.0	2.7	1.8	1.9	2.0
Not recorded	0.1	0.0	0.2	0	0.0
Laboratory measurements
BMI (Kg/m²)	29.2±7.0	29.9±8.1	28.8±7.5	28.6±6.5	29.3±6.2	<0.0001
SBP (mmHg)	119.8±14.8	117.8±14.8	117.4±14.2	119.9±14.4	122.2±14.4	<0.0001
DBP (mmHg)	71.9±10.9	70.0±10.5	70.5±10.2	72.1±10.8	73.9±10.7	<0.0001
Thoracic Spine BMD	0.8±0.1	0.8±0.1	0.8±0.1	0.8±0.1	0.8±0.1	<0.0001
Lumbar Spine BMD	1.0±0.2	1.1±0.1	1.0±0.2	1.0±0.2	1.0±0.1	<0.0001
Albumin (g/L)	42.8±3.4	41.1±3.2	42.5±3.1	43.5±3.1	44.4±3.1	<0.0001
ALP (IU/L)	68.9±23.8	66.4±23.4	66.3±22.4	67.4±22.5	70.9±23.8	<0.0001
AST (IU/L)	24.9±19.4	23.1±28.9	23.4±12.2	25.5±19.9	28.3±19.4	<0.0001
ALT (IU/L)	26.2±20.5	20.3±18.4	22.6±15.5	27.0±18.1	34.1±26.5	<0.0001
Blood Urea Nitrogen (mmol/L)	4.6±1.6	4.4±1.9	4.5±1.3	4.7±1.5	4.7±1.5	<0.0001
Total Calcium (mmol/L)	2.3±0.9	2.3±0.1	2.3±0.1	2.4±0.1	2.4±0.1	<0.0001
CPK (IU/L)	173.9±268.8	132.9±143.5	155.5±240.3	192.2±268.9	188.8±290.7	<0.0001
GGT (IU/L)	29.9±46.4	23.6±40.7	25.4±41.2	30.3±43.6	37.1±50.1	<0.0001
LDH (IU/L)	132.3±31.2	128.2±30.7	130.1±30.5	130.8±29.2	133.4±33.1	<0.0001
Phosphorus (mmol/L)	1.2±0.2	1.2±0.2	1.2±0.2	1.2±0.2	1.2±0.2	<0.0001
Total Bilirubin (umol/L)	9.6±5.1	7.8±4.1	9.2±4.5	10.3±5.1	11.8±5.8	<0.0001
Total Protein(g/L)	71.9±4.3	71.2±4.4	71.4±4.2	71.9±4.3	72.3±4.2	<0.0001
Albumin Creatinine Ratio (mg/g)	33.7±321.3	58.2±511.7	27.4±278.6	13.3±74.6	20.6±99.1	<0.0001
Red Blood Cell Count(UL)	4.8±0.5	4.4±0.4	4.6±0.3	4.9±0.3	5.2±0.3	<0.0001
HDL-C (mmol/L)	1.4±0.4	1.5±0.4	1.5±0.4	1.3±0.4	1.2±0.3	<0.0001
Total Cholesterol (mmol/L)	4.9±1.0	4.8±0.9	4.9±1.0	5.0±1.0	5.0±1.1	<0.0001
Glucose (mmol/L)	5.5±2.1	5.3±1.6	5.4±1.9	5.5±2.0	5.7±2.3	<0.0001
Iron (umol/L)	15.3±6.6	11.9±6.3	14.8±5.7	16.4±5.9	18.0±6.5	<0.0001
Triglyceride (mmol/L) (%)						<0.0001
0 to 0.677	11.9	14.6	13.7	11.2	7.2
0.678 to 1.016	11.1	10.0	11.9	11.4	10.7
1.017 to 1.569	11.6	9.8	10.6	11.8	13.3
>1.569	11.4	7.0	7.9	11.2	17.7
Not recorded	54.1	58.6	55.8	54.4	51.1
LDL-C (mmol/L) (%)						<0.0001
0 to 2.302	11.4	12.5	11.4	11.2	9.9
2.301 to 2.870	11.8	11.0	12.8	10.7	12.0
2.871 to 3.491	11.0	10.0	10.5	11.3	11.3
>3.491	11.3	7.8	9.3	11.9	14.9
Not recorded	54.6	58.7	56.0	54.9	51.8

Mean ± SD for continuous variables: P-value was calculated by weighted linear regression model.

% for categorical variables: P-value was calculated by weighted chi-square test.

Relationship between HGB and BMD

In exploring the relationship between HGB and BMD, we constructed three weighted univariate and multivariate linear regression models: model 1, unadjusted; model 2, adjusted for gender, age, and race; and in model 3, adjusted for the covariates in Table 1.

In Model 1, HGB levels displayed a negative association with lumbar spine BMD (β=-0.0082, P<0.000001), in contrast, HGB levels were positively correlated (β=0.0061, P<0.000001) with thoracic spine BMD. After fully adjusting for confounding factors, HGB showed a negative correlation with both thoracic spine BMD (β=-0.0031, P=0.021831) and lumbar spine BMD (β=-0.0086, P=0.000003) (Table 2, Figure 2 and 3).

TABLE 2 Relationship between HGB and BMD

	Non-adjusted	Adjust I	Adjust II
Thoracic Spine BMD	0.0061 (0.0044, 0.0078) <0.000001	-0.0068 (-0.0090, -0.0046) <0.000001	-0.0031 (-0.0058, -0.0005) 0.021831
Lumbar Spine BMD	-0.0082 (-0.0104, -0.0059) <0.000001	-0.0136 (-0.0164, -0.0107) <0.000001	-0.0086 (-0.0122, -0.0050) 0.000003

Expose variable HGB (g/dl), ending variable lumbar spine BMD, the results in the table are expressed as β (95%CI).

Model 1, no covariates were adjusted.

Model 2, age, sex, race were adjusted.

Model 3, gender, age, race, annual household income, education level, SBP, DBP, weight, standing height, BMI, red blood cell count, albumin, ALP, ALT, AST, blood urea nitrogen, total calcium, iron, CPK, GGT, glucose, LDH, phosphorus, total bilirubin, total protein, albumin creatinine ratio, triglyceride, LDL-C, HDL-C, cholesterol, alcohol status, smoking status and diabetes were adjusted.

In fully adjusted subgroup analyses stratified by gender, the negative association between HGB and thoracic spine BMD was only significant in female subjects [-0.0040 (-0.0075, -0.0004)]. While the negative correlation between HGB and lumbar spine BMD was significantly present in both male [-0.0097 (-0.0154, -0.0039)] and female subjects [-0.0083 (-0.0129, -0.0037)] (Table 3). Table 4 shows the subgroup analyses performed after grouping for race. We discovered that the negative association between HGB and thoracic spine BMD was only significant in Mexican-Americans [-0.0097 (-0.0155, -0.0039)]. And HGB levels exhibited a negative association with lumbar spine BMD in Mexican-American [-0.0201 (-0.0282, -0.0119)] and Non-Hispanic White [-0.0065 (-0.0128, -0.0002)]. In addition, fully adjusted smoothed plots showed a non-linear relationship between HGB and BMD in the lumbar and thoracic spine after stratification by gender or race (Figure 4 and 5). Among participants in other races and those whose race was not reported, BMD in the thoracic spine increased with HGB until the turning point (turning point: HGB 11.9 g/dL) (Table 5, Figure 4). Similarly, there was an identical turning point between HGB and BMD in the lumbar spine (turning point: HGB 11.9 g/dL) (Table 5, Figure 4). Overall, the relationship between HGB and BMD in the lumbar spine and with BMD in the thoracic spine for other races and not recorded showed an inverted U-shaped curve.

Table 3 Association between HGB and BMD stratified by gender

		Non-adjusted	Adjust I	Adjust II
Thoracic Spine BMD	Male	-0.0056(-0.0089,-0.0024) 0.000759	-0.0026(-0.0059,0.0006) 0.113653	-0.0019(-0.0060, 0.0022) 0.354982
Thoracic Spine BMD	Female	-0.0097(-0.0127,-0.0068) <0.000001	-0.0088 (-0.0117,-0.0058) <0.000001	-0.0040 (-0.0075, -0.0004) 0.028075
Lumbar Spine BMD	Male	-0.0157(-0.0201,-0.0113) <0.000001	-0.0148(-0.0192, -0.0103) <0.000001	-0.0097 (-0.0154, -0.0039) 0.001023
Lumbar Spine BMD	Female	-0.0129 (-0.0166,-0.0091) <0.000001	-0.0129 (-0.0166,-0.0091) <0.000001	-0.0083 (-0.0129, -0.0037) 0.000397

Expose variable HGB (g/dl), ending variable lumbar spine BMD, the results in the table are expressed as β (95%CI).

Model 1, no covariates were adjusted.

Model 2, age, sex, race were adjusted.

In the subgroup analysis stratified by gender, the model is not adjusted for the stratification variable itself.

Table 4 Association between HGB and BMD stratified by race

		Non-adjusted	Adjust I	Adjust II
Thoracic Spine BMD	Mexican American	0.0065 (0.0028, 0.0102) 0.000575	-0.0069 (-0.0117,-0.0021) 0.005205	-0.0097 (-0.0155, -0.0039) 0.001060
	Other Hispanic	0.0106 (0.0049, 0.0163) 0.000280	-0.0048 (-0.0122, 0.0025) 0.198142	-0.0047 (-0.0138, 0.0044) 0.310054
	Non-Hispanic White	0.0070 (0.0040, 0.0100) 0.000004	-0.0057 (-0.0095,-0.0018) 0.003646	-0.0004 (-0.0051, 0.0043) 0.867754
	Non-Hispanic Black	0.0054 (0.0017, 0.0092) 0.004840	-0.0122 (-0.0169,-0.0075) <0.000001	-0.0040 (-0.0098, 0.0018) 0.172235
	Non-Hispanic Asian	0.0061 (0.0011, 0.0111) 0.016835	-0.0075 (-0.0139,-0.0010) 0.023639	-0.0040(-0.0115,0.0036) 0.304728
	Other Race and Not recorded	0.0030 (-0.0041, 0.0100) 0.410772	-0.0093 (-0.0184,-0.0003) 0.044208	-0.0081 (-0.0192, 0.0030) 0.154452
Lumbar Spine BMD	Mexican American	-0.0070 (-0.0120,-0.0019) 0.007095	-0.0147 (-0.0214,-0.0080) 0.000019	-0.0201 (-0.0282, -0.0119)
	Other Hispanic	-0.0031 (-0.0106, 0.0045) 0.427725	-0.0118 (-0.0217,-0.0019) 0.019337	-0.0073 (-0.0195, 0.0048)
	Non-Hispanic White	-0.0079 (-0.0117,-0.0041) 0.000043	-0.0124 (-0.0173,-0.0076) <0.000001	-0.0065 (-0.0128, -0.0002) 0.044215
	Non-Hispanic Black	-0.0080 (-0.0130,-0.0031) 0.001528	-0.0195 (-0.0258,-0.0131) <0.000001	-0.0060 (-0.0139, 0.0018) 0.133322
	Non-Hispanic Asian	-0.0055 (-0.0117, 0.0007) 0.084751	-0.0107 (-0.0189,-0.0024) 0.011710	-0.0089 (-0.0188, 0.0010)
	Other Race and Not recorded	-0.0124 (-0.0214, -0.0034) 0.007041	-0.0175 (-0.0292,-0.0057) 0.003764	-0.0154 (-0.0304, -0.0004)

Expose variable HGB (g/dl), ending variable lumbar spine BMD, the results in the table are expressed as β (95%CI).

Model 1, no covariates were adjusted.

Model 2, age, sex, race were adjusted.

In the subgroup analysis stratified by race, the model is not adjusted for the stratification variable itself.

Table 5 Threshold effect analysis of HGB on Thoracic Spine BMD and Lumbar Spine BMD using two-piecewise linear regression in the Other Race and Not recorded group

	Hemoglobin(g/dl)	Adjusted β (95%CI)，p-value
Thoracic Spine BMD	<11.9(g/dl)	0.0215 (-0.0059, 0.0488) 0.1246
Thoracic Spine BMD	>11.9(g/dl)	-0.0176 (-0.0313, -0.0040) 0.0119
Lumbar Spine BMD	<11.9(g/dl)	0.0196 (-0.0175, 0.0567) 0.3005
Lumbar Spine BMD	>11.9(g/dl)	-0.0268 (-0.0453, -0.0082) 0.0049

Gender, age, annual household income, education level, SBP, DBP, weight, standing height, BMI, red blood cell count, albumin, ALP, ALT, AST, blood urea nitrogen, total calcium, iron, CPK, GGT, glucose, LDH, phosphorus, total bilirubin, total protein, albumin creatinine ratio, triglyceride, LDL-C, HDL-C, cholesterol, alcohol status, smoking status and diabetes were adjusted.

The main goal of the study was to clarify whether HGB was correlated with BMD in the lumbar and thoracic spine. In our comprehensive adjusted model multiple linear regression analysis, we found that HGB was negatively correlated with both lumbar and thoracic BMD, in addition, the complete adjusted smoothed curve fits showed a non-linear correlation. When stratified by gender and race, HGB was negatively correlated with thoracic spine BMD significantly in females and Mexican-American, and with lumbar spine BMD significantly in males, females, Mexican-American and Non-Hispanic White. Among participants in other races and those whose race was not reported, the relationship between HGB with BMD in the lumbar spine and the thoracic spine showed an inverted U-shaped curve.

Similar to our conclusion, a cross-sectional study involving 3626 Korean participants found that HGB levels were inversely associated with low BMD in lumbar spine among non-anemic adults(26). Furthermore, in a recently published study, BMD was negatively correlated with HGB levels in younger and older women(27). Similar results were obtained by Cesari M et al. in a survey of 950 older people(28). Nevertheless, a study examining the association between serum HGB levels, BMD and fracture risk using estimated scores from the Fracture Risk Assessment Tool (FRAX) in 662 male patient, concluded that HGB was positively associated with BMD, but negatively associated with risk of hip fracture and risk of major osteoporotic fracture(29). It is possible that age and ethnic differences in the study population or limited sample size may have influenced the results. Based on this, the cross-sectional study has a broad and large sample size, targeting both males and females aged 18 years and over, and providing subgroup analysis across gender and race.

The mechanism of the link between HGB and BMD is not yet clear, but based on the theory that both osteoblasts and cells of the hematopoietic microenvironment responsible for maintaining hematopoietic tissue have a common progenitor, namely mesenchymal stem cells (MSC)(30), Gurevitch, O et al. propose a hypothesis that the differentiation pathways of osteogenesis and the hematopoietic microenvironment are in competition with each other, with osteogenic stimulation predominating during the growth phase of the organism, while during After maturation, there is a gradual increase in differentiation of MSCs towards cells of the hematopoietic microenvironment and a decrease in intraosseous differentiation. This subsequently leads to a reduction in bone mass and an enlargement of the bone marrow cavity inhematopoietically active cancellous bone(31).They speculated that the continuous overproduction of blood cells leads to excessive depletion of the hematopoietic system and is a non-negligible component in the etiology of osteoporosis. Blood loss promotes the proliferation of hematopoietic progenitor cells, leading to an increase in the number of hematopoietic cells, including osteoblasts, which enhances the resorption of bone tissue. In addition, a reduction in blood volume stimulates bone development and an increase in the number of osteoblasts, thus promoting new bone formation(32). It has also been shown that acute bleeding stimulates the secretion of bone morphogenetic protein 2 and BMP6 by hematopoietic stem cells, thereby driving MSC differentiation along the osteogenic pathway(33).

This study analyzed data from NHANES 2013-2018 conducted by the U.S. Centers for Disease Control and Prevention. NHANES 2013-2018 has a rigorous design and accurate data, which is the advantage of this study. However, the restrictions ought to be noted. The adjusted variables during this study square measure restricted, and it's unknown whether or not alternative unadjusted variables can have a major impact on the results. It is also regrettable that this study relied on a cross-sectional style and therefore it was not possible to ascertain a causal relationship between BMD and HGB.

In conclusion, this study found that HGB was negatively correlated with BMD in the thoracic and lumbar spine. Stratified analyses showed that the negative correlation between HGB and BMD of the thoracic spine was more significant in women and Mexican Americans, and the negative correlation between HGB and BMD of the lumbar spine was more significant in Mexican Americans and non-Hispanic whites and was not affected by gender. the association between HGB and BMD in the thoracic and lumbar spine followed an inverted U-shaped curve.

HGB: Hemoglobin; BMD: bone mineral density; NHANES: National Health and Nutrition Survey; SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; ALP: alkaline phosphatase; ALT: alanine aminotransferase; AST: aspartate aminotransferase; CPK: creatine phosphor kinase; GGT: gamma glutamyl transferase; LDH: lactate dehydrogenase; LDL-C: low-density lipoprotein cholesterol; HDL-C: high-density lipoprotein cholesterol; MEC: mobile examination center; CBC: complete blood count; DXA: duel energy X-ray absorptiometry; FRAX: Fracture Risk Assessment Tool; MSC: mesenchymal stem cell

Ethics approval

All analyses were based on data of the National Health and Nutrition Examination Survey (NHANES). And all procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the ethics review board of the National Center for Health Statistics. The National Center for Health Statistics Ethics Review Board protocol numbers are Protocol #2011-17 (NHANES 2013-2014), Continuation of Protocol #2011-17 (NHANES 2015-2016), Continuation of Protocol #2011-17 and #2018-01(NHANES 2017-2018), respectively. The detailed information located on the NHANES website.

Consent for publication

All participating authors give their consent for this work to be published.

Availability of data and materials

The datasets obtained and analysed during the current study are available in the NHANES [https://www.cdc.gov/nchs/nhanes/index.htm]

Competing interest

The authors declare no conflict of interest in the research.

Funding

This work was supported by grants from the Shandong University of Chinese Medicine Research and Innovation Team (No.220318); the Shandong Province Famous Old Chinese Medicine Experts Inheritance Studio Construction Project (No.22201906).

Authors’ contributions

All authors made a significant contribution to the work reported and agreed to be accountable for all aspects of the work. H.J. and L.E.Q. designed the experiments. L.E.Q., H.X.Z., and L.S.Q. collected and analyzed data. L.E.Q. and H.X.Z. prepared the initial draft of the manuscript. L.H, L.E.Q. and H.J. gave critical feedback during the study or during the submission of the manuscript. All authors provided final approval of the version to be submitted and agreed on the journal for publication.

Acknowledgements

We would like to acknowledge the following financial support: the Shandong University of Chinese Medicine Research and Innovation Team (No.220318); the Shandong Province Famous Old Chinese Medicine Experts Inheritance Studio Construction Project (No.22201906). We thank the NHANES database for sharing the data.

Authors' information

¹College of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Shandong 250355, China. Email,[email protected]

²College of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Shandong 250355, China.Email,[email protected]

³ Acupuncture and massage rehabilitation department, Qingdao Traditional Chinese Medicine Hospital, 4 Renmin Road, Qingdao city 266033, Shandong Province, china.Email,[email protected]

⁴ Acupuncture Department, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, 16369 Jingshi Road, Jinan City 250014, Shandong Province, China. Email, [email protected]

⁵ Pediatric Orthopaedics, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, 16369 Jingshi Road, Jinan City 250014, Shandong Province, China. Email, [email protected]

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No competing interests reported.

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Association of hemoglobin levels with bone mineral density in the thoracic and lumbar spine for adults over 18 years of age: a cross-sectional study

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