Osteoporosis in Korean men over 40 years: Prevalence and risk factors

Abstract

Osteoporosis is increasingly being recognized as a significant health concern in men. However, research on male osteoporosis in Korea remains limited. This study aimed to investigate the prevalence and factors influencing osteoporosis in Korean men aged ≥40 years. Secondary analysis utilized data from the Korean Genome and Epidemiology Study urban cohort (2004–2013), focusing on 58,976 men aged ≥40 years. Variables included sociodemographic characteristics, lifestyle factors, medical history, anthropometric measurements, biometric parameters, and dietary habits. Statistical analyses included analysis of variance, Chi-square tests, and multinomial logistic regression. The prevalence of osteoporosis was 0.6% among the male participants. Risk factors significantly associated with osteoporosis included advanced age (50–59 years: odds ratio (OR) = 1.899; ≥60 years: OR = 3.119), chronic diseases including angina/myocardial infarction (OR = 2.197), fatty liver (OR = 2.297), gallstones/cholecystitis (OR = 2.176), and arthritis (OR = 8.069), poor self-rated health (OR = 3.598), and irregular meal patterns (OR = 2.884). Protective factors included normal or overweight body mass index compared with underweight, moderate total cholesterol levels (140–200 mg/dL: OR = 0.401), and moderate coffee consumption (3–4 times/day: OR = 0.555). Age, chronic diseases, poor self-rated health, and irregular dietary habits significantly increase osteoporosis risk in Korean men. Comprehensive health management strategies focusing on these factors are essential for effective osteoporosis prevention in this population.

1. Introduction

Osteoporosis is characterized by decreased bone mass or density (resulting from abnormalities in bone metabolism or calcium imbalances associated with aging). Although the chemical composition of the bone remains unchanged, osteoporosis leads to a reduction in bone quantity and density. Osteoporosis has the highest prevalence among all the skeletal diseases.^[1] Overall, 5.0% of men aged ≥30 years and 17.7% of men aged ≥70 years had osteoporosis and showed rapid progression from the age of 60 years.^[2] The Senior Citizen Survey in 2023 revealed that osteoporosis affected 11.1% of individuals aged ≥65 years, ranking it as the 5th most common chronic disease among older adults in Korea.^[3] Recent data indicate that the prevalence of osteopenia and osteoporosis among Korean men in their 40s and 50s is as high as 40.5%.^[4]

Korea transitioned to an aging society in 2023, with 19.2% of population aged ≥65 years, and is projected to become a super-aged society by 2036, when this demographic is expected to reach 30.0%.^[5] This rapid aging trend suggests a continued rise in osteoporosis prevalence and associated treatment costs for osteoporotic fractures. Data from the Health Insurance Review and Assessment Service revealed a 21.0% increase in patients with osteoporosis between 2020 and 2023, accompanied by a 41.0% increase in medical costs.^[6,7] The diagnosis rate increases with age, reaching 14.2% in those in their 50s, 36.5% in those in their 60s, and 47.6% in those aged ≥70 years.^[7] Notably, secondary osteoporosis is more common in men than in women,^[8] highlighting osteoporosis as a significant health concern in aging men. Recently, a substantial proportion of osteoporotic fractures have been reported in men, with higher associated mortality rates than in women.^[8,9]

Unlike females, males do not experience a rapid decline in sex hormones, which leads to a gradual progression of bone loss.^[10] Osteoporosis primarily occurs as a natural consequence of aging. In males, cortical bone loss typically begins after 50 years and is primarily linked to declining testosterone and estradiol levels, along with increased bone remodeling activity.^[11–13] Secondary osteoporosis refers to bone loss resulting from factors that hinder peak bone mass attainment (which is influenced by various factors, including genetics, nutrition, physical activity, and disease) or accelerated abnormal bone resorption. In Korea, secondary osteoporosis accounts for approximately 60% of osteoporosis in males.^[14] Common causes include hypogonadism, low body mass index (BMI), smoking, excessive alcohol consumption, steroid use, and physical inactivity. Although secondary osteoporosis is more prevalent in males than in females,^[15] comprehensive research focusing on male osteoporosis and its contributing factors is limited.

Osteoporosis is recognized as a major health concern among the older population, with research worldwide predominantly focusing on women, particularly postmenopausal women. This trend has also been observed in South Korea, where studies on osteoporosis in women are relatively abundant, whereas research on osteoporosis in men remains limited.

Jung et al^[4] conducted a multifaceted analysis of osteoporosis risk factors in middle-aged Korean men in their 40s and 50s, and identified advanced age, lower income and education levels, smoking, low body weight, and occupation as significant risk factors. However, this study was based on data gathered over only 3 years (2008–2011) and focused solely on men in their 40s and 50s, limiting its generalizability.

To address these limitations, the present study expands the research scope by analyzing data from the urban cohort survey (2004–2013) of the Korean Genome and Epidemiology Study (KoGES). This study aimed to examine lifestyle factors, medical history, anthropometric measurements (height, weight, waist circumference, and hip circumference), biometric parameters (blood pressure, heart rate, blood lipid levels, and blood glucose levels), and dietary intake frequencies (daily meals, milk, coffee, green tea, and carbonated beverages) to identify the factors influencing osteoporosis in men aged ≥40 years. The findings of this study are expected to serve as foundational data for the development of future strategies for the prevention and management of osteoporosis in men.

2. Materials and methods

This study, involving a secondary data analysis, was conducted after obtaining an exemption from the Institutional Review Board (IRB) (DKU 2021-11-008). The analysis utilized data from the KoGES(2004–2013), with a focusing on men aged ≥40 years. Participants completed a self-administered questionnaire that included questions about their history of physician-diagnosed diseases, including osteoporosis. The variables included sociodemographic characteristics, lifestyle, medical history, anthropometric measurements, biometric parameters, and dietary intake frequencies. Data analysis was performed using the SAS Viya software (SAS Institute Inc., Cary). Continuous variables were analyzed using means and standard deviations, whereas categorical variables were analyzed using frequencies and percentages. To compare osteoporosis prevalence based on sociodemographic, disease-related, lifestyle-related, anthropometric, and biometric factors, the study employed analysis of variance was used for continuous variables, and χ²-tests were used for categorical variables. To identify the key risk factors influencing osteoporosis in men, a binominal logistic regression analysis was conducted, with results presented as odds ratios (OR) and 95% confidence intervals.

3. Results

3.1. General characteristics of participants

Participants’ mean age was 53.9 ± 8.8 years. Regarding educational attainment, those who had graduated from junior college or higher constituted the largest proportion (42.9%). Among lifestyle characteristics, 72.3% had never consumed alcohol, the overall mean exercise time was 90.9 ± 66.1 minute per week, 51.2% of participants perceived their health as good, and 85.9% reported eating 3 meals a day. Regarding medical history, hypertension was observed in 22.6%, diabetes in 9.3%, and hyperlipidemia in 9.6% of participants, whereas arthritis (4.1%) and malignant tumors (2.2%) were relatively less prevalent. Participants’ mean height and weight were 168.6 ± 5.8 cm and 69.5 ± 9.3 kg, respectively, with mean BMI and waist circumference at 24.4 ± 2.7 kg/m² and 85.8 ± 7.5 cm, respectively. Regarding beverage intake frequency, 15.8% consumed milk 1 to 2 times per week, 38.9% consumed coffee 1 to 2 times per day, and 11.5% consumed carbonated beverages once per month (Table 1).

Table 1.

Participants’ general characteristics (N = 59,259).

Characteristics	Variables	Categories	N	%	M ± SD
Socio-demographic characteristics	Age, years	40–49	20,217	34.1	53.99 ± 8.81
		50–59	21,291	35.9
		≥60	17,751	30.0
	Educationalattainment (N = 58,207)	≤Middle school	13,697	23.5	–
		≥High school	19,544	33.6
		≥Junior college	24,966	42.9
Lifestyle	Alcohol consumption (N = 58,857)	Current drinker	11,899	20.2	–
		Former drinker	4426	7.5
		Never drinker	42,532	72.3
	Regular exercise (N = 58,794)	Yes	25,557	43.5	-
		No	33,237	56.5
	Exercise frequency (N = 31,900)	1–2/week	10,360	32.5	–
		3–4/week	10,545	33.1
		5–6/week	4994	15.7
		Everyday	6001	18.8
	Mean exercise time, min (N = 31,362)	≤49	5995	19.1	90.92 ± 66.07
		50–149	21,164	67.5
		≥150	4203	13.4
	Self-rated health status (N = 51,260)	Good	26,217	51.2	–
		Average	24,553	47.9
		Poor	490	1.0
	Daily meal frequency (N = 58,733)	1–2 times	6819	11.6	–
		3 times	50,455	85.9
		≥ 4 times	497	0.9
		Irregular	962	1.6
Medical history	Hypertension (N = 59,008)	Yes	13,346	22.6	–
		No	45,662	77.4
	Diabetes (N = 58,991)	Yes	5482	9.3	–
		No	53,509	90.7
	Hyperlipidemia (N = 58,990)	Yes	5634	9.6	–
		No	53,356	90.5
	Stroke (N = 59,001)	Yes	1058	1.8	–
		No	57,943	98.2
	Angina/myocardial infarction (n = 58,994)	Yes	2129	3.6	–
		No	56,865	96.4
	Colon polyp (n = 58,968)	Yes	3173	5.4	–
		No	55,795	94.6
	Acute liver disease (n = 58,990)	Yes	547	0.9	–
		No	58,443	99.1
	Fatty liver (N = 58,979)	Yes	5779	9.8	–
		No	53,200	90.2
	Gallstones/cholecystitis (n = 58,994)	Yes	1919	3.3	–
		No	57,075	96.8
	Thyroid disease (n = 58,997)	Yes	786	1.3	–
		No	58,211	98.7
	Arthritis (N = 58,992)	Yes	2432	4.1	–
		No	56,560	95.9
	Malignant tumor (1) (n = 58,975)	Yes	1322	2.2	–
		No	57,653	97.8
Anthropometric and biometric parameters	Height (cm) (N = 56,300)	≤164	13,152	23.4	168.62 ± 5.79
		165–174	34,663	61.6
		≥175	8485	15.1
	Weight (kg) (N = 54,946)	≤59	7218	13.1	69.46 ± 9.26
		60–70	24,116	43.9
		71–80	17,377	31.6
		≥81	6235	11.4
	BMI (n = 58,185)	<18.5 (underweight)	808	1.4	24.40 ± 2.75
		18.5–22.9 (normal)	16,229	27.9
		≥23 (overweight)	41,148	70.3
	Waist circumference (cm) (N = 56,865)	<79	10,798	20.0	85.82 ± 7.53
		80–89	28,561	50.2
		≥90	17,506	30.8
	Systolic blood pressure (mm Hg) (n = 58,644)	≤99	1059	1.8	125.89 ± 14.73
		100–119	16,879	28.8
		≥120	40,706	69.4
	Diastolic blood pressure (mm Hg) (n = 58,532)	≤59	927	1.6	78.76 ± 9.89
		60–79	26,732	45.7
		≥80	30,873	52.8
	Heart rate/min (n = 56,705)	≤64	20,369	35.9	68.54 ± 9.75
		65–8	33,347	58.8
		86–100	2711	4.8
		≥101	278	0.5
	Fasting glucose level/mg (n = 58,177)	≤69	476	0.8	99.22 ± 24.44
		70–99	37,610	65.5
		100–125	14,827	25.8
		≥126	4544	7.9
	Total cholesterol (mg/dL) (n = 59,237)	≤139	3016	5.1	193.33 ± 34.91
		140–200	32,723	55.2
		≥201	23,498	39.7
	HDL-cholesterol (mg/dL) (n = 59,235)	≤39	11,261	19.0	49.72 ± 11.96
		40–59	37,034	62.3
		≥60	10,940	18.5
Beverage intake frequency	Milk (N = 58,667)	Rarely consumed	20,185	34.4	–
		Once a month	5087	8.7
		2–3 times a month	6274	10.7
		1–2 times a week	9244	15.8
		3–4 times a week	6069	10.3
		5–6 times a week	1989	3.4
		1–2 times a day	8873	15.1
		3–4 times a day	630	1.1
		5+ times a day	316	0.5
	Coffee (N = 58,074)	Rarely consumed	7573	12.9	–
		Once a month	1085	1.9
		2–3 times a month	1791	3.1
		1–2 times a week	3116	5.3
		3–4 times a week	3216	5.5
		5–6 times a week	2287	3.9
		1–2 times a day	22,862	38.9
		3–4 times a day	12,582	21.4
		5+ times a day	4192	7.1
	Green tea (N = 58,668)	Rarely consumed	22,805	38.9	–
		Once a month	4434	7.6
		2–3 times a month	5607	9.6
		1–2 times a week	8125	13.9
		3–4 times a week	4748	8.1
		5–6 times a week	1814	3.1
		1–2 times a day	8597	14.7
		3–4 times a day	1782	3.0
		5+ times a day	756	1.3
	Carbonated beverages (N = 58,293)	Rarely consumed	37,386	64.1	–
		Once a month	6698	11.5
		2–3 times a month	5982	10.3
		1–2 times a week	5272	9.0
		3–4 times a week	1741	3.0
		5–6 times a week	427	0.7
		1–2 times a day	698	1.2
		3 or more times a day	89	0.2

BMI = body mass index, HDL = high-density lipoprotein; M ± SD = mean ± standard deviation; N = number.

3.2. Osteoporosis prevalence by sociodemographic characteristics and medical history

Of the 58,976 men aged ≥40 years included in the survey of this study, 353 (0.6%) men reported as were diagnosed with osteoporosis, accounting for 0.2% of the 173,200 male and female participants in the KoGES urban cohort (2004–2013), and 3.8% of the 9245 male and female participants aged ≥40 years who were reported to have been diagnosed with osteoporosis. Chi-square tests revealed significant associations between osteoporosis and both age (χ² = 134.90, P < .001) and education level (χ² = 27.58, P < .001). Further cross-tabulation analysis assessing the differences in osteoporosis prevalence by medical history revealed significant associations with the presence of the following conditions: hypertension (χ² = 14.93, P < .001), diabetes mellitus (χ² = 5.90, P = .02), hyperlipidemia (χ² = 28.39, P < .001), stroke (χ² = 12.21, P < .001), angina/myocardial infarction (χ² = 37.11, P < .001), intestinal polyps (χ² = 18.34, P < .001), acute liver disease (χ² = 4.38, P = .047), fatty liver disease (χ² = 64.37, P < .001), gallstones/cholecystitis (χ² = 21.87, P < .001), thyroid disorders (χ² = 6.12, P = .030), arthritis (χ² = 274.18, P < .001), and malignant tumors (χ² = 13.34, P < .001) (Table 2).

Table 2.

Osteoporosis prevalence by demographic characteristics and medical history (N = 59,259).

Categories			Diagnosed		Non-diagnosed		${\mathit{\chi }}^{\mathbf{2}}$(P)
			N	%	N	%
Socio-demographic characteristics	Age (yr) (N = 58,976)	40–49	47	0.2	20,065	99.8	134.90 (<.001***)
		50–59	105	0.5	21,080	99.5
		≥60	201	1.1	17,478	98.9
	Educational attainment (N = 58,141)	≤Middle school	124	0.9	13,558	99.1	27.58 (<.001***)
		≥High school	104	0.5	19,417	99.5
		≥Associate degree	123	0.5	24,815	99.5
Medical history	Hypertension (N = 58,968)	Yes	110	0.8	13,210	99.2	14.93 (<.001***)
		No	243	0.5	45,405	99.5
	Diabetes (N = 58,964)	Yes	46	0.8	5431	99.2	5.90 (.02*)
		No	307	0.6	53,180	99.4
	Hyperlipidemia (N = 58,959)	Yes	63	1.1	5562	98.9	28.39 (<.001***)
		No	290	0.5	53,044	99.5
	Stroke (N = 58,971)	Yes	15	1.4	1041	98.6	12.21 (<.001***)
		No	338	0.6	57,577	99.4
	Angina/myocardial infarction (N = 58,965)	Yes	34	1.6	2092	98.4	37.11 (<.001***)
		No	319	0.6	56,520	99.4
	Colon polyp (N = 58,947)	Yes	37	1.2	3133	98.8	18.34 (<.001***)
		No	315	0.6	55,462	99.4
	Acute liver disease† (N = 58,966)	Yes	7	1.3	538	98.7	4.38 (0.047*)
		No	345	0.6	58,076	99.4
	Fatty liver (N = 58,952)	Yes	79	1.4	5686	98.6	64.37 (<.001***)
		No	273	0.5	52,914	99.5
	Gallstones/cholecystitis (N = 58,971)	Yes	27	1.4	1889	98.6	21.87 (<.001***)
		No	326	0.6	56,729	99.4
	Thyroid disease† (N = 58,970)	Yes	10	1.3	774	98.7	6.12 (.030*)
		No	343	0.6	57,843	99.4
	Arthritis (N = 58,968)	Yes	76	3.1	2350	96.9	274.18 (<.001***)
		No	276	0.5	56,266	99.5
	Malignant tumor (N = 58,958)	Yes	18	1.4	1303	98.6	13.34 (<.001***)
		No	334	0.6	57,303	99.4

N = number.

^†Fisher exact test.

^*P < 0.05.

^***P < 0.001.

3.3. Osteoporosis prevalence by lifestyle and dietary habits

Analysis of lifestyle and dietary habits revealed significant associations between osteoporosis prevalence and alcohol consumption (χ² = 16.66, P < .001), self-rated health status (χ² = 75.70, P < .001), daily meal frequency (χ² = 13.55, P = .004), and coffee consumption (χ² = 39.04, P < .001) (Table 3).

Table 3.

Osteoporosis prevalence by lifestyle and dietary habits (N = 59,259).

Categories			Diagnosed		Non-diagnosed		${\mathit{\chi }}^{\mathbf{2}}$(P)
			N	%	N	%
Lifestyle	Alcohol consumption (N = 58,788)	Current drinker	87	0.7	11,794	99.3	16.66 (<.001***)
		Former drinker	42	1.0	4375	99.0
		Never drinker	223	0.5	42,267	99.5
	Regular exercise (N = 58,728)	Yes	193	0.6	33,007	99.4	0.34 (.558)
		No	158	0.6	25,370	99.4
	Exercise frequency (N = 31,866)	1–2/week	55	0.5	10,293	99.5	4.06 (.255)
		3–4/week	58	0.6	10,477	99.4
		5–6/week	39	0.8	4949	99.2
		Every day	37	0.6	5958	99.4
	Mean exercise time, min (N = 31,332)	≤49	39	0.7	5955	99.4	0.68 (.713)
		50–149	125	0.6	21,015	99.4
		≥150	22	0.5	4176	99.5
	Self-rated health status (N = 51,199)	Good	99	0.4	26,094	99.6	75.70 (<.001***)
		Average	138	0.6	24,379	99.4
		Poor	15	3.1	474	96.9
	Daily meal frequency (N = 58,661)	1–2 times	28	0.4	6781	99.6	13.55 (0.004**)
		3 times	308	0.6	50,088	99.4
		≥4 times	8	1.6	489	98.4
		Irregular	8	0.8	951	99.2
Beverage intake frequency	Milk (N = 58,574)	Rarely consumed	117	0.6	20,041	99.4	8.06 (.427)
		Once a month	28	0.6	5054	99.4
		2–3 times a month	31	0.5	6237	99.5
		1–2 times a week	51	0.6	9177	99.4
		3–4 times a week	45	0.7	6015	99.3
		5–6 times a week	9	0.5	1966	99.5
		1–2 times a day	62	0.7	8799	99.3
		3–4 times a day	6	1.0	620	99.0
		5+ times a day	3	0.9	313	99.1
	Coffee (N = 58,612)	Rarely consumed	76	1.0	7488	99.0	39.04 (<.001***)
		Once a month	6	0.6	1078	99.4
		2–3 times a month	17	1.0	1771	99.0
		1–2 times a week	21	0.7	3087	99.3
		3–4 times a week	21	0.7	3187	99.3
		5–6 times a week	19	0.8	2263	99.2
		1–2 times a day	124	0.5	22,698	99.5
		3–4 times a day	49	0.4	12,520	99.6
		5+ times a day	19	0.5	4168	99.5
	Green tea (N = 58,575)	Rarely consumed	149	0.7	22,608	99.3	9.35 (.314)
		Once a month	32	0.7	4398	99.3
		2–3 times a month	30	0.5	5571	99.5
		1–2 times a week	46	0.6	8070	99.4
		3–4 times a week	25	0.5	4714	99.5
		5–6 times a week	14	0.8	1798	99.2
		1–2 times a day	37	0.4	8548	99.6
		3–4 times a day	14	0.8	1765	99.2
		5+ times a day	4	0.5	752	99.5
	Carbonated beverages (N = 58,208)	Rarely consumed	232	0.6	37,094	99.4	11.84 (.106)
		Once a month	47	0.7	6645	99.3
		2–3 times a month	23	0.4	5952	99.6
		1–2 times a week	26	0.5	5238	99.5
		3–4 times a week	13	0.7	1724	99.3
		5–6 times a week	3	0.7	424	99.3
		1–2 times a day	4	0.6	694	99.4
		3–4 times a day	2	2.2	87	97.8

N = number.

^**P < 0.01.

^***P < 0.001.

3.4. Osteoporosis prevalence by anthropometric and biometric parameters

Chi-square tests were used to examine the association between osteoporosis prevalence and the anthropometric and biometric parameters. Height (χ² = 29.82, P < .001), weight (χ² = 51.04, P < .001), BMI (χ² = 52.05, P < .001), diastolic blood pressure (χ² = 13.25, P = .001), total cholesterol (χ² = 26.27, P < .001), and high-density lipoprotein cholesterol (χ² = 10.53, P < .001) were identified as statistically significant factors (Table 4).

Table 4.

Osteoporosis prevalence by anthropometric and biometric parameters (N = 59,259).

Variables	Categories	Diagnosed		Non-diagnosed		${\mathit{\chi }}^{\mathbf{2}}$(P)
		N	%	N	%
Height (cm) (N = 56,116)	≤164	121	0.9	12,988	99.1	29.82 (<.001***)
	165–174	185	0.5	34,363	99.5
	≥175	35	0.4	8422	99.6
Weight (kg) (N = 54,762)	≤59	83	1.2	7108	98.8	51.04 (<.001***)
	60–70	150	0.6	23,890	99.4
	71–80	77	0.4	17,239	99.6
	≥81	21	0.3	6194	99.7
BMI (N = 57,997)	<18.5 (underweight)	19	2.4	785	97.6	52.05 (<.001***)
	18.5–22.9 (normal)	117	0.7	16,065	99.3
	≥23 (overweight)	209	0.5	40,802	99.5
Waist circumference (cm) (N = 56,748)	<79	72	0.7	10,710	99.3	1.15 (.564)
	80–89	161	0.6	28,337	99.4
	≥90	103	0.6	17,365	99.4
Systolic blood pressure (mm Hg) (N = 58,484)	≤99	6	0.6	1051	99.4	3.87 (.144)
	100–119	118	0.7	16,719	99.3
	≥120	228	0.6	40,362	99.4
Diastolic blood pressure (mm Hg) (N = 58,372)	≤59	10	1.1	916	98.9	13.25 (.001**)
	60–79	187	0.7	26,480	99.3
	≥80	154	0.5	30,625	99.5
Heart rate/min (N = 56,568)	≤64	139	0.7	20,176	99.3	5.07 (.167)
	65–85	181	0.5	33,089	99.5
	86–100	13	0.5	2693	99.5
	≥101	1	0.4	276	99.6
Fasting glucose level/mg (N = 57,234)	≤69	2	0.4	473	99.6	2.62 (.454)
	70–99	238	0.6	37,227	99.4
	100–125	77	0.5	14,691	99.5
	≥ 126	26	0.6	4500	99.4
Total cholesterol (mg/dL) (N = 58,954)	≤139	39	1.3	2963	98.7	26.27 (<.001***)
	140–200	182	0.6	32,390	99.4
	≥201	131	0.6	23,249	99.4
HDL-cholesterol (mg/dL) (N = 58,952)	≤39	50	0.5	11,168	99.6	10.53 (<.001***)
	40–59	218	0.6	36,635	99.4
	≥60	85	0.8	10,796	99.2

BMI = body mass index; HDL = high-density lipoprotein; N = number.

^**P < 0.01.

^***P < 0.001.

3.5. Risk factors for osteoporosis in Korean men

The model fit of this study was statistically significant at χ² of 3189.395 (df = 23, P < .0001, Nagelkerke R² = 0.776). The analysis identified age, angina/myocardial infarction, fatty liver, gallstones/cholecystitis, arthritis, self-rated health status, irregular meal frequency, coffee consumption (3–4 times/day), BMI, and total cholesterol levels (140–200 mg/dL) as significant factors influencing osteoporosis in men (P < .05) (Table 5).

Table 5.

Risk factors for osteoporosis in Korean men.

Independent variables (characteristics)		B	SE	Wald	P	OR	95% CI
							LLCI	ULCI
Age, years	50–59	0.641	0.228	7.898	.005**	1.899	1.214	2.970
	≥60	1.138	0.228	24.925	<.001***	3.119	1.996	4.874
Educational attainment	High school diploma	−0.217	0.176	1.520	.218	0.805	0.570	1.136
	≥Associate degree	−0.088	0.171	0.266	.606	0.916	0.655	1.280
Hypertension	Yes	0.113	0.161	0.494	.482	1.120	0.817	1.536
Diabetes	Yes	−0.307	0.230	1.783	.182	0.735	0.469	1.155
Hyperlipidemia	Yes	0.239	0.201	1.404	.236	1.270	0.855	1.884
Stroke	Yes	0.233	0.402	0.334	.563	1.262	0.574	2.777
Angina/myocardial infarction	Yes	0.731	0.239	9.375	.002**	2.078	1.301	3.318
Colon polyp	Yes	0.418	0.219	3.647	.056	1.519	0.989	2.334
Acute liver disease	Yes	0.444	0.482	0.846	.358	1.558	0.606	4.010
Fatty liver	Yes	0.790	0.183	18.633	<.001***	2.203	1.539	3.152
Gallstones/cholecystitis	Yes	0.702	0.246	8.154	.004**	2.017	1.246	3.265
Thyroid disease	Yes	0.673	0.399	2.839	.092	1.960	0.896	4.287
Arthritis	Yes	1.379	0.181	58.344	<.001***	3.970	2.787	5.654
Malignant tumor	Yes	0.387	0.314	1.524	.217	1.473	0.797	2.722
Alcohol consumption	Former drinker	−0.241	0.263	0.834	.361	0.786	0.469	1.318
	Never drinker	−0.185	0.164	1.271	.260	0.831	0.603	1.146
Self-rated health status	Average	0.289	0.142	4.158	.041	1.335	1.011	1.762
	Poor	1.280	0.336	14.555	<.001***	3.598	1.864	6.946
Meal frequency (no. of meals per day)	3	0.371	0.273	1.854	.173	1.450	0.849	2.474
	4	0.976	0.650	2.257	.133	2.654	0.743	9.482
	Irregular	1.059	0.495	4.575	.032*	2.884	1.093	7.612
Coffee	Once a month	−0.442	0.526	0.707	.400	0.643	0.229	1.802
	2–3 times a month	0.105	0.340	0.095	.758	1.111	0.570	2.165
	1–2 times a week	−0.187	0.295	0.400	.527	0.830	0.465	1.479
	3–4 times a week	−0.313	0.319	0.961	.327	0.731	0.391	1.367
	5–6 times a week	−0.288	0.371	0.602	.438	0.750	0.363	1.551
	1–2 times a day	−0.318	0.185	2.953	.086	0.728	0.506	1.046
	3–4 times a day	−0.809	0.250	10.496	.001***	0.445	0.273	0.726
	5+ times a day	−0.656	0.371	3.132	.077	0.519	0.251	1.073
Height (cm)	165–174	−0.078	0.170	0.210	.647	0.925	0.663	1.291
	≥175	0.060	0.288	0.043	.836	1.062	0.604	1.868
Weight (kg)	60–70	−0.237	0.245	0.937	.333	0.789	0.488	1.275
	71–80	−0.545	0.327	2.785	.095	0.580	0.306	1.100
	≥81	−0.654	0.416	2.477	.116	0.520	0.230	1.174
BMI	18.5–22.9 (normal)	−0.914	0.359	6.474	.011*	0.401	0.198	0.811
	≥23 (overweight)	−0.847	0.421	4.056	.044*	0.429	0.188	0.978
Diastolic blood pressure (mm Hg)	60–79	0.450	0.593	0.576	.448	1.568	0.491	5.014
	≥80	0.028	0.598	0.002	.963	1.028	0.318	3.321
Total cholesterol (mg/dL)	140–200	−0.513	0.243	4.458	.035*	0.599	0.372	0.964
	≥201	−0.340	0.257	1.745	.187	0.712	0.430	1.178
HDL-cholesterol (mg/dL)	40–59	0.363	0.202	3.225	.073	1.438	0.967	2.137
	≥60	0.417	0.245	2.902	.089	1.517	0.939	2.449

BMI = body mass index, CI = confidence intervals, HDL = high-density lipoprotein, LLCI = lower limit confidence interval, N = number, OR = odds ratio, SE = standard error of mean, ULCI = upper limit confidence interval.

^*P < 0.05.

^**P < 0.01.

^***P < 0.001.

4. Discussion

This study investigated the factors associated with osteoporosis prevalence in Korean men using KoGES data and analyzed sociodemographic characteristics, lifestyle factors, medical history, anthropometric measurements, and biometric parameters. Logistic regression analysis identified age, angina/myocardial infarction, fatty liver, gallstones/cholecystitis, arthritis, self-rated health status, daily meal frequency, coffee consumption frequency, BMI, and total cholesterol levels as significant factors associated with osteoporosis prevalence.

First, of the 58,976 men aged ≥40 years included in the survey of this study, 353 (0.6%) men self-reported as were medical diagnosed with osteoporosis. In this study, the prevalence of osteoporosis in men was 0.6%, which was significantly lower than the global male prevalence of 11.7%^[16] and the 40.5% prevalence of osteopenia and osteoporosis in middle-aged Korean men.^[4] The study by Salari et al^[16] was based on a large-scale meta-analysis of the global male population, while Jung et al^[4] examined both osteopenia and osteoporosis. These differences in prevalence can be attributed to variations in the scope and diversity of the sample population. Discrepancies in osteoporosis diagnostic criteria, examination methods, lifestyle factors, and health-related conditions may also contribute to the differences in the prevalence rates.^[17] Also, osteoporosis is often asymptomatic and underdiagnosed, particularly in men. Therefore, participants in this study may have been unaware of their condition, leading to an underestimation of the true prevalence.^[8,13] Furthermore, the absence of objective bone mineral density (BMD) measurements limits the ability to identify subclinical or undiagnosed cases. As such, the low prevalence observed in this study should be interpreted with caution. Since these findings likely reflect osteoporosis prevalence within a specific study population,^[2] further research is needed to validate these findings by comparing various sample populations and diagnostic methods and to determine a more accurate prevalence rate in Korean men.

The odds of developing osteoporosis in men aged 50 to 59 and ≥60 years were 1.899 and 3.119 times higher, respectively, than those in men in their 40s. These findings align with those of previous studies,^[4,18] which identified age as a key factor in osteoporosis development, thus emphasizing the negative effect of aging on bone health. Aging disrupts the bone remodeling processes, resulting in decreased BMD. The cumulative effects of lifestyle habits on bone health, along with the increasing prevalence of chronic diseases with age, may further increase the risk of osteoporosis. Unlike women, men do not undergo abrupt hormonal changes; however, the gradual decline of testosterone and growth hormone with age may contribute to an increased risk of osteoporosis.^[19] Further research is needed to explore these associations and to develop age-specific health management programs, including potential hormone therapy interventions.

Chronic diseases are also strongly associated with osteoporosis in men. In this study, the presence of angina/myocardial infarction, fatty liver, gallstones, and arthritis increased the OR for osteoporosis by more than 2-fold. Choi and Kim,^[20] reported that individuals with 2 or 3 chronic diseases had an osteoporosis OR of 1.442 compared with those without chronic conditions. Jankowska et al,^[21] indicated that men with heart failure exhibited reduced BMD and bone mineral content. These results correlate with the findings of the present study, and suggest that chronic diseases may affect bone metabolism and contribute to osteoporosis development. This underscores the importance of chronic disease management as a key strategy in osteoporosis prevention. Identifying and monitoring high-risk individuals with chronic conditions are crucial, reinforcing the need for enhanced screening and preventive programs for early detection and management. Additionally, osteoporosis-related education and intervention programs should be implemented to support effective disease management and prevention strategies.

This study also confirms the importance of self-rated health status and dietary habits. Participants who perceived their health as poor had 3.598 times higher odds of developing osteoporosis than those who perceived their health as good. Self-rated health status influences health behaviors,^[22] and differences in lifestyle habits based on self-rated health status have been reported.^[23] Men who perceive themselves as unhealthy are generally less likely to maintain healthy lifestyle habits, which can negatively impact their bone health. Therefore, fostering a positive health perceptions and promoting proactive health management behaviors are essential for osteoporosis prevention. Identifying individuals with negative self-rated health and providing targeted education and counseling programs may help them adopt healthier habits. Irregular daily meal patterns also increased the odds of osteoporosis by a factor of 2.884 times. Dietary habits play a critical role in determining overall health status,^[24] and a balanced diet is a key determinant of bone health.^[25] Regular meals support the stable intake of essential nutrients, contributing to better bone health. Therefore, osteoporosis prevention strategies should emphasize the importance of regular meals and a nutrient-rich diet, along with the implementation of dietary intervention programs.

Notably, consuming coffee 3 to 4 times per day was associated with a 44.5% reduction in the odds of osteoporosis. Although caffeine is generally known to increase calcium excretion and potentially negatively affect BMD,^[26,27] this study suggests that moderate coffee consumption may have a protective effect against osteoporosis. This finding aligns with those of previous studies by Zeng et al,^[28] who reported that both high and low coffee consumption were associated with lower odds of osteoporosis, and by Asoudeh et al,^[29] which found that higher coffee intake was linked to a reduced fracture risk in men. Coffee contains various bioactive compounds, including caffeine (mental alertness effects), chlorogenic acid (antioxidant and anti-inflammatory properties), and trigonelline (improved glucose tolerance in obesity-related diabetes). These compounds may exert synergistic effects that positively influence bone health.^[30] This study suggests that the potential benefits of coffee consumption could contribute to osteoporosis prevention in men, providing evidence to support its inclusion in health management strategies for men. However, it is important to consider the individual variability in coffee metabolism and avoid relying solely on coffee intake for osteoporosis prevention. A comprehensive approach that integrates healthy lifestyle habits, regular physical activity, and balanced nutrition is essential to achieve optimal bone health.

BMI and total cholesterol levels are closely associated with the risk of osteoporosis. Both the normal and overweight BMI categories were associated with lower odds of osteoporosis than the underweight category. These findings align with previous studies reporting that individuals with lower BMI have a higher risk of osteoporosis and osteopenia^[31,32] and that BMD declines more significantly in underweight individuals than in those with normal or overweight BMI.^[33] Since being underweight increases osteoporosis risk due to reduced mechanical loading on bones, nutritional deficiencies, and decreased sex hormone production. Maintaining a healthy weight is crucial for osteoporosis prevention. A better understanding of the relationship between weight and BMD considering the physiological and metabolic characteristics of men is essential for developing targeted prevention and management strategies for underweight men.

Individuals with total cholesterol levels, within the 140 to 200 mg/dL range had 59.9% lower odds of developing osteoporosis than those with higher levels. This finding is consistent with previous research indicating that higher total cholesterol and triglyceride levels are increase osteoporosis risk^[34] and that total cholesterol levels are inversely correlated with lumbar spine BMD.^[35] These results suggest that maintaining optimal cholesterol levels may help prevent osteoporosis. While cholesterol plays a key role in hormone and vitamin D synthesis, prolonged hypercholesterolemia can accelerate bone loss by promoting osteoclast activity and inhibiting osteoblast function, leading to reduced BMD.^[36] Maintaining total cholesterol within the 140 to 200 mg/dL range may support bone health by preventing BMD reduction and lowering osteoporosis risk. Achieving this requires regular health checkups and lifestyle modifications for cholesterol management. Further studies should explore the relationship between cholesterol levels and osteoporosis in men, particularly by examining the effects of testosterone and cholesterol fluctuations in different age groups. Identifying optimal strategies for maintaining bone health in men with both high and low cholesterol levels is also necessary.

Among the analyzed variables, some were found to have no significant impact on osteoporosis risk, including alcohol consumption, physical activity, and dietary intake frequency. Alcohol consumption and exercise habits did not have a significant effects on osteoporosis. This suggests that the influence of alcohol on osteoporosis risk may vary depending on factors, such as drinking patterns, alcohol consumption, and metabolic interactions. Therefore, more detailed data are required to assess its impact accurately. Although regular physical activity is generally recognized for its health benefits, exercise frequency and type were not significant risk factors for osteoporosis in this study. This finding indicates that the relationship between exercise and bone health may depend on individual bone metabolism, highlighting the need for more precise studies on the effects of exercise type, intensity, and duration on BMD.

Similarly, dietary intake frequency was not significantly associated with osteoporosis risk. The frequency of consumption of various food groups, such as milk, coffee, and soft drinks, did not exhibit a meaningful correlation with osteoporosis. This suggests that the effects of diet on bone health cannot be explained by the intake frequency or quantity alone. Future research should consider the overall quality of the diet and the interactions between various nutrients.

As a cross-sectional study, this research was limited in its ability to establish causal relationships between the risk factors and osteoporosis. Also, this study has several limitation. First, osteoporosis diagnosis was based on self-reported history of prior physician diagnosis rather than clinical BMD criteria. Variables relied on self-reported data, which may have introduced measurement errors. Second, the low number of diagnosed cases (N = 353, 0.6%) may have affected the statistical power of the logistic regression model and increased the risk of type I error. Although the number of events per variable (EPV) met the minimum recommended threshold, cautious interpretation of marginally significant findings is warranted. Future studies should consider incorporating objective diagnostic data and employing statistical methods specifically designed for rare event analysis.

5. Conclusions and recommendations

This study on the prevalence of osteoporosis in Korean men identified advanced age, presence of chronic diseases, poor self-rated health, and irregular meal intake as key factors for osteoporosis in men aged ≥40 years. Notably, men aged ≥50 years had a higher odds of developing osteoporosis than those in their 40s, emphasizing the negative impact of aging on bone health.

Furthermore, chronic diseases double the risk of osteoporosis, underscoring the importance of chronic disease management in osteoporosis prevention. Men who perceived their health as poor had higher odds of developing osteoporosis than those who rated their health as good, demonstrating the influence of health perception on lifestyle behaviors.

These findings can serve as foundational data for the development of tailored health management programs to prevent osteoporosis. In particular, regular health screenings and educational programs are recommended for men aged ≥50 years, who are at a higher risk.

Future research should incorporate a broader population and conduct longitudinal studies to examine the complex interactions between risk factors in greater depth. This will contribute to a more accurate understanding of osteoporosis in Korean men and will support the development of effective preventive strategies.

Author contributions

Conceptualization: Seunghee Lee, Su Jeong Yi.

Data curation: Seunghee Lee, Hyunjung Lee.

Formal analysis: Seunghee Lee.

Funding acquisition: Hyunjung Lee.

Methodology: Hyunjung Lee.

Project administration: Hyunjung Lee.

Supervision: Hyunjung Lee.

Writing – original draft: Seunghee Lee, Su Jeong Yi.

Writing – review & editing: Hyunjung Lee.