Skip to main content
PMC home page
PLOS ONE logoLink to PLOS ONE
. 2022 Nov 21;17(11):e0277231. doi: 10.1371/journal.pone.0277231

Bone mineral density among virologically suppressed Asians older than 50 years old living with and without HIV: A cross-sectional study

Lalita Wattanachanya 1,2, Sarat Sunthornyothin 1,2, Tanakorn Apornpong 3, Hay Mar Su Lwin 3, Stephen Kerr 3,4,5, Sivaporn Gatechompol 3,6, Win Min Han 3,6, Thanathip Wichiansan 3, Sarawut Siwamongsatham 7, Pairoj Chattranukulchai 8, Tawatchai Chaiwatanarat 9, Anchalee Avihingsanon 3,6,*; HIV-NAT 207/006 study team
Editor: Julie A E Nelson10
PMCID: PMC9678298  PMID: 36409740

Abstract

There are limited data regarding bone health in older people living with HIV (PWH), especially those of Asian ethnicity. We aimed to determine whether BMD in well-suppressed HIV-infected men and women aged ≥ 50 years are different from HIV-uninfected controls. In a cross-sectional study, BMD by dual-energy X-ray absorptiometry and calciotropic hormones were measured. A total of 481 participants were consecutively enrolled (209 HIV+ men, 88 HIV- men, 126 HIV+ women and 58 HIV- women). PWH were on average 2.5 years younger [men: 55.0 vs. 57.5 yr; women: 54.0 vs. 58.0 yr] and had lower body mass index (BMI) [men: 23.2 vs. 25.1 kg/m2; women: 23.1 vs. 24.7 kg/m2] compared to the controls. The median duration since HIV diagnosis was 19 (IQR 15–21) years in men and 18 (IQR 15–21) years in women. Three-quarters of PWH had been treated with tenofovir disoproxil fumarate-containing antiretroviral therapy for a median time of 7.4 (IQR 4.5–8.9) years in men and 8.2 (IQR 6.1–10) years in women. In an unadjusted model, HIV+men had significantly lower BMD (g/cm2) at the total hip and femoral neck whereas there was a tend toward lower BMD in HIV+women. After adjusting for age, BMI, and other traditional osteoporotic risk factors, BMD of virologically suppressed older PWH did not differ from participants without HIV (P>0.1). PWH had lower serum 25(OH)D levels but this was not correlated with BMD. In conclusion, BMD in well-suppressed PWH is not different from non-HIV people, therefore, effective control of HIV infection and minimization of other traditional osteoporosis risk factors may help maintain good skeletal health and prevent premature bone loss in Asian PWH.

Clinical trial registration: Clinicaltrials.gov # NCT00411983.

Introduction

Longevity of people living with HIV (PWH) has dramatically improved in the last two decades, with life expectancy approaching that of the general population, predominantly due to expanded access to highly effective antiretroviral therapy (ART) [1]. The population of PWH aged ≥50 years across many world regions is expected to increase steadily to 21% by year 2030 [2]. As more PWH live longer, it is expected that medical comorbidities such as cardiovascular diseases, renal dysfunction, cancer, and bone diseases will increase [3, 4].

Low bone mineral density (BMD) has been widely documented in PWH. Prior meta-analyses indicated that the prevalence of low BMD in adults living with HIV was three times higher compared to people without HIV [5–7]. In addition, some studies suggested that fractures occurred more frequently in PWH [8–10]. Underlying mechanisms leading to reduced bone mass in PWH are believed to be multifactorial, including both traditional and HIV-specific risk factors. PWH are likely to have risk factors related to osteoporosis such as smoking, low body weight, nutritional deficiencies, and hypogonadism [11–15]. Several studies found that vitamin D deficiency, which may adversely affect calcium and skeletal homeostasis, was more prevalent in PWH compared to people without HIV [16–18]. In addition, HIV itself and chronic inflammation/immune activation may negatively affect bone mass by altering osteoblast and/or osteoclast function [19, 20]. Specific antiretroviral drugs such as tenofovir disoproxil fumarate (TDF) may also lead to a reduction of bone mass and increased risk of fracture [21].

Most of the data mentioned above are from studies conducted in western countries. Data regarding bone health in Asians living with HIV, especially in persons over 50 years old, are currently limited. Therefore, we sought to determine whether BMD in PWH over 50 years old are different from people without HIV. This study also compared the levels of calciotropic hormones, including 25-dihydroxyvitamin D (25(OH)D), and bone turnover markers (BTMs) between PWH and people without HIV.

Methods

Study population and settings

This cross-sectional study was conducted between January 2016 and June 2017. Three hundred and fifty-eight PWH over 50 years of age who were virologically suppressed (HIV-RNA <50 copies/mL) in a long-term cohort (HIV-NAT 006: clinical trial number NCT00411983) at the HIV Netherlands Australia Thailand Research Collaboration (HIV-NAT), Bangkok, Thailand, were asked to participate in this study. Age (within 10-year age bands) and sex-matched controls were recruited from those visiting the King Chulalongkorn Memorial Hospital for their annual medical checkup during the study period. Participants with known history of metabolic bone diseases, multiple myeloma, cancer, inflammatory bowel disease, currently on glucocorticoids or anticonvulsant agents, and/or currently admitted to the hospital were excluded. These criteria applied to both people living with and without HIV. Three hundred thirty-five out of 358 PWH and 146 healthy controls who met the inclusion criteria were enrolled (Fig 1).

Fig 1. Participants recruitment and investigation flow diagram.

Fig 1

Open in a new tab

Demographic and medical data of all participants were extracted from the clinic’s electronic health database and chart review: reproductive history, physical activity, current medications, medical illness, traditional risks for osteoporosis and fracture history. For PWH, the following data were collected: ART history, nadir CD4 cell count, and duration of HIV infection. Whole blood samples were drawn on the day of the clinic visit after at least 8 hours of fasting and plasma was stored at -80°C until assayed. CD4 cell counts, HIV-RNA viral load, creatinine, calciotropic hormones, and BTMs, including calcium, phosphorus, albumin, intact parathyroid hormone (ICMA; intact PTH assays Roche Elecsys®), serum 25(OH)D levels (CLIA; DiaSorin LIAISON®), serum procollagen type 1 N-terminal propeptide (P1NP), and C-terminal cross-linking telopeptide of type I collagen (CTX) (CLIA; Roche Diagnostics, Mannheim, Germany) were measured. Inflammatory markers, high sensitivity C-reactive protein (hs-CRP; Roche Diagnostics GmbH, Mannheim, Germany), and Interleukin 6 (IL-6; ECLIA; Roche Diagnostics GmbH, Mannheim, Germany) were also measured. The intra- and inter-assay coefficients of variations for 25(OH)D assay were less than 6%. Vitamin D deficiency and insufficiency were defined as a serum 25(OH)D below 20 ng/mL and within 20–29 ng/mL, respectively [22]. The same tests, with the exception of viral load and CD4 count, were ordered for people without HIV.

BMD at the lumbar spine (L1 to L4), total hip, and femoral neck, as well as the percentage of body fat were measured using dual-energy X-ray absorptiometry on a QDR 4500 bone densitometer (Hologic, Inc., Bedford, MA). BMD T-scores were analyzed using Asian population reference databases, supplied by the manufacturer. Osteoporosis was defined as a T-score of ≤ -2.5 standard deviation (SD) and osteopenia, or low BMD, was defined as a T-score between -1 and -2.5 SD below the young adult mean value, as per World Health Organization (WHO) criteria [23, 24]. A subset of PWH underwent lateral thoraco-lumbar (T-L) X-ray radiographs at the left lateral position centered at L1 level. Radiographic vertebral fracture was diagnosed using the Genant’s semi-quantitative method [25]. Vertebral bodies from T4 to L4 levels were assessed to identify vertebral fracture.

This study was reviewed and approved by the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. HIV-NAT 207 IRB approval No. 442/58 and HIV-NAT 006 study IRB approval No. 589/2007; REC. No. 161/45. Written informed consent was obtained from all of the participants.

Statistical analysis

Descriptive data were reported as median (IQR), mean (SD), or number (percentage). Formal comparisons of the continuous demographic data and BMD covariates between the study groups were made using Student’s t-test or non-parametric equivalents where appropriate; categorical comparisons were made using a Chi-square or Fisher’s exact test as appropriate. Univariate analyses were developed for factors associated with BMD, including demographic and anthropometric data, in all participants. In addition to age, sex, alcohol and smoking status, which were well known factors affecting BMD, all variables with p-values ≤ 0.20 were included in the multivariable regression model. Separate models incorporating HIV-disease-related characteristics were developed for PWH for BMD. Collinearity was tested, and nonoverlapping covariates were retained for inclusion in the final models. Subgroup analyses of multivariate linear regression models were developed for serum 25(OH)D and BTMs. Potential determinants with a p-value less than 0.05 were considered statistically significant. Data analysis was performed using Stata version 15.1 (StataCorp LLC, College Station, TX, USA).

Results

Characteristics of the study population

From January 2016 to June 2017, a total of 481 patients were consecutively recruited into the study and analysed (209 men living with HIV (HIV+men), 88 men living without HIV (HIV-men), 126 women living with HIV (HIV+women) and 58 women living without HIV: HIV- women). Demographic and clinical characteristics of the study population classified by sex are summarized in Table 1.

Table 1. Demographic and clinical characteristics of the study population stratified by sex.

Characteristics Men (n = 297) Women (n = 184)
HIV- (n = 88) HIV+ (n = 209) P-value HIV- (n = 58) HIV+ (n = 126) P-value
Age (years) 57.5 (54.0–62.0) 55.0 (52.0–60.0) 0.001 58.0 (54.0–62.0) 54.0 (52.0–59.0) 0.001
Weight (kg) 67.6 (60.1–73.8) 66.0 (57.5–72.3) 0.12 60.6 (53.2–64.8) 55.1 (51.1–62.0) 0.004
BMI (kg/m2) 25.1 (22.4–27.3) 23.2 (21.0–25.3) <0.001 24.7 (22.2–28.2) 23.1 (20.8–25.4) 0.001
Body fat (%) 22.6 (18.8–25.5) 19.2 (15.2–23.2) 0.001 34.3 (31.9–36.8) 31.2 (26.3–35.3) 0.001
Current residential location (% Bangkok) 11.7 48.9 <0.001 33.3 49.5 0.12
History of all fractures, n (%) 15 (17.0) 44 (21.0) 0.47 7 (12.1) 18 (14.3) 0.75
History of fragility fracture, n (%) 3 (3.4) 4 (1.9) 0.42 3 (5.2) 6 (4.8) 0.86
FH of osteoporosis/fracture, n (%) 20 (22.7) 40 (19.1) 0.48 5 (8.6) 21 (16.7) 0.15
Current smoking, n (%) 15 (17.1) 46 (22.0) 0.33 0 (0) 2 (1.6) 1.00
Alcohol use (>1 drink /day), n (%) 19 (21.6) 25 (12.0) 0.033 2 (3.5) 5 (4.0) 1.00
Reproductive history (women) 0.28
Regular menstruation, n (%) 7 (12.1) 26 (20.6)
Bilateral ovaries resection, n (%) 5 (8.6) 14 (11.1)
• Year since bilateral ovaries resection 9 (5–29) 12 (7–20)
• Menstruation exhausted, n (%) 46 (79.3) 89 (68.3)
• Years since menopause 10 (5–14) 6 (2–12)
Chronic medical conditions, n (%)
• Hypertension 34 (38.6) 115 (55.0) 0.01 13 (22.4) 36 (28.6) 0.38
• Dyslipidemia 22 (25.0) 129 (61.7) <0.001 10 (17.2) 79 (62.7) <0.001
• Type 2 diabetes 12 (13.6) 47 (22.5) 0.08 10 (17.2) 13 (10.3) 0.19
• Cardiovascular diseases 3 (3.4) 6 (2.9) 0.73 0 (0) 1 (0.8) 1.00
• Others 2 (2.3) 5 (2.4) 1.00 3 (5.2) 2 (1.6) 0.18
Hepatitis C seropositive, n (%) 2 (2.3) 24 (11.5) 0.012 1 (1.8) 7 (5.6) 0.44
Hepatitis B seropositive, n (%) 6 (6.9) 32 (15.3) 0.049 2 (3.5) 9 (7.1) 0.51
Medications, n (%)
• Calcium supplements 4 (4.6) 12 (5.7) 0.79 14 (24.1) 11 (8.7) 0.005
• Multivitamins 9 (10.2) 14 (6.7) 0.30 10 (17.2) 13 (10.3) 0.19
• Insulin 0 (0) 8 (3.8) 0.11 0 (0) 2 (1.6) 1.00
• Oral hypoglycemic agents 8 (9.1) 40 (19.1) 0.032 9 (15.5) 13 (10.3) 0.31
• Statins 21 (23.9) 110 (52.6) <0.001 9 (15.5) 77 (61.1) <0.001
• Steroids (ever) 0 (0) 1 (0.5) 1.00 0 (0) 0 (0) N/A
• Proton pump inhibitors 0 (0) 4 (1.9) 0.32 2 (3.5) 0 (0) 0.09
HIV and ART characteristics
Presumptive transmission route, n (%)
• Men who have sex with men 43 (20.6) N/A
• Heterosexuals 140 (67.0) 110 (87.3)
• Injecting drugs use 2 (0.9) 0 (0)
• Unknown 22 (10.5) 14 (11.1)
Years since HIV diagnosis 19 (15–21) 18 (15–21)
History of AIDS-defined illness (%) 147 (70.3) 59 (46.8)
Nadir CD4 cell count (cells/mm3) 183 (67–256) 174 (120–252)
Current CD4 cell count (cells/mm3) 599 (444–791) 685 (527–814)
HIV-1 RNA before ARV initiation (log10 copies/mL) 4.72 (4.22–5.20) 4.61 (4.09–5.12)
Duration of ART (year) 16.2 (13.3–19.1) 16.1 (12.6–18.9)
Current ART, n (%)a
• NNRTI-based 110 (52.6) 78 (61.9)
• PI-based 72 (34.5) 36 (28.6)
• PI and NNRTI 15 (7.2) 8 (6.4)
• PI- Integrase inhibitor 12 (5.7) 4 (3.2)
• EFV 58 (27.8) 31 (24.6)
• Non TDF-based 59 (27.7) 32 (24.4)
• TDF-based 152 (72.7) 94 (74.6)
    TDF full dose (300 mg/day) 104 (68.4) 58 (61.7)
    TDF reduced dose (150 mg/day) 48 (31.6) 36 (38.2)
• TDF exposure (year) 7.4 (4.5–8.9) 8.2 (6.1–10)
Open in a new tab

Data are reported as median (IQR), mean (SD), or number (percentage). The difference between PWH and people without HIV were compared using Student t-test, Mann-Whitney test, Chi-square test or Fisher’s Exact test, where appropriate. HIV-, people living without HIV; HIV+, PWH; BMI, body mass index; FH, family history; ART, antiretroviral therapy; NNRTI, non-nucleoside reverse transcriptase inhibitors; PI, protease Inhibitor; EFV, efavirenz; TDF, tenofovir disoproxil fumarate; N/A, not assessed. aMen, n = 173; Women, n = 112.

Men living with HIV were 2.5 years younger, had lower BMI and percentages of body fat compared to the HIV-men. Regarding factors associated with osteoporosis and/or fracture, HIV+men had higher prevalence of hepatitis B and hepatitis C co-infection. Current smoking, history of low-trauma fracture, family history of osteoporosis/fracture were comparable between the two groups. The median (IQR) duration since HIV diagnosis was 19 (15–21) years with median (IQR) nadir and current CD4 cell counts of 183 (67–256) and 599 (444–791) cells/mm3, respectively.

Likewise, HIV+women were 4 years younger, but they had lower BMI and percentages of body fat than HIV-women. Other risk factors for osteoporosis and/or fractures were similar in both groups. However, HIV+women consumed calcium supplements more than HIV- women. The median (IQR) duration since HIV diagnosis was 18 (15–21) years with median (IQR) nadir and current CD4 cell counts of 174 (120–252) and 685 (527–814) cells/mm3, respectively. The proportion of women who has regular menstruation was higher among HIV+women with shorter years since menopause. Three-quarters of PWH have been treated with TDF-containing ART. Among these, 35% used TDF at half dose. Of note, since this is an observational study, all ART regimens and doses were based on the physician’s decision and local guidelines, and the reason behind it may probably because of reduced creatinine clearance or low body weight of the patients.

Bone mineral density at the lumbar spine, total hip and femoral neck

Unadjusted BMD (grams per square centimeter) of the total hip and femoral neck were significantly lower in HIV+men than HIV- men, while differences among women were not statistically significant (Table 2). No difference in the vertebral BMD was observed in either men or women. According to WHO criteria, both HIV+men and HIV+women had a higher proportion of low BMD (T-score ≤ -1.0) at the femoral neck (men: 62% in HIV+ vs. 44% in HIV-, P = 0.047; women: 72% in HIV+ vs. 52% in HIV-, P = 0.024).

Table 2. Unadjusted BMD and T-score at the lumbar spine, total hip and femoral neck.

Men Women
HIV- (n = 88) HIV+ (n = 209) P-value HIV- (n = 58) HIV+ (n = 126) P-value
Lumbar spine
BMD (g/cm2) 0.96 (0.14) 0.94 (0.16) 0.11 0.88 (0.18) 0.85 (0.16) 0.22
T-score, mean (SD) -0.48 (1.18) -0.68 (1.35) 0.09 -1.5 (3.64) -1.37 (1.37) 0.29
T-score, n (%) 0.40 0.28
>-1.0 56 (64.37) 122 (58.65) 28 (49.12) 45 (36.59)
-2.5 to -1.0 29 (33.33) 74 (35.58) 20 (35.09) 53 (43.09)
≤-2.5 2 (2.30) 12 (5.77) 9 (15.79) 25 (20.33)
Total hip
BMD (g/cm2) 0.91 (0.13) 0.86 (0.13) 0.002 0.81 (0.17) 0.79 (0.13) 0.14
T-score, mean (SD) -0.21 (0.92) -0.58 (0.95) 0.002 -0.25 (1.15) -0.53 (1.10) 0.11
T-score, n (%) 0.047 1.00
>-1.0 68 (77.27) 135 (64.59) 42 (72.41) 89 (70.63)
-2.5 to -1.0 20 (22.73) 68 (32.54) 15 (25.86) 34 (26.98)
≤-2.5 0 (0.00) 6 (2.87) 1 (1.72) 3 (2.38)
Femoral neck
BMD (g/cm2) 0.74 (0.12) 0.71 (0.11) 0.023 0.66 (0.21) 0.64 (0.12) 0.060
T-score, mean (SD) -0.86 (0.93) -1.13 (0.92) 0.020 -1.13 (1.18) -1.48 (1.08) 0.023
T-score, n (%) 0.016 0.024
>-1.0 49 (55.68) 80 (38.28) 28 (48.28) 35 (27.78)
-2.5 to -1.0 37 (42.05) 117 (55.98) 22 (37.93) 73 (57.94)
≤-2.5 2 (2.27) 12 (5.74) 8 (13.79) 18 (14.29)
Open in a new tab

In men, univariate analysis revealed that age was negatively correlated with BMD at the femoral neck, while BMI and current smoking, were negatively correlated with BMD at all sites. These variables remained significant in the multivariate analyses. HIV infection was a risk factor for low BMD at the total hip and femoral neck, but only in the univariate model (Table 3). In women, age and lower BMI were negatively correlated with BMD at all sites in both univariate and multivariate analysis. Still menstruating was positively correlated with BMD at the lumbar spine. Similar to men, HIV status was not correlated with BMD in women (Table 4). As for PWH, the years since HIV diagnosis, duration of antiretroviral exposure, type of ART and the presence of AIDS defining illness were not associated with BMD in both men and women (P>0.2).

Table 3. Univariate and multivariate analysis of factors associated with BMD at the lumbar spine, total hip, and femoral neck in men.

Lumbar spine Total hip Femoral neck
Univariate analysis Multivariate analysis Univariate analysis Multivariate analysis Univariate analysis Multivariate analysis
Coef (95%CI) P-value Coef (95%CI) P-value Coef (95%CI) P-value Coef (95%CI) P-value Coef (95%CI) P-value Coef (95%CI) P-value
HIV -0.02 (-0.06, 0.02) 0.23 -0.002 (-0.04, 0.04) 0.93 -0.05 (-0.08, -0.02) 0.002 -0.03 (-0.06, 0.003) 0.076 -0.03 (-0.06, -0.005) 0.023 -0.02 (-0.04, 0.01) 0.26
Age by 10 years -0.003 (-0.03, 0.03) 0.82 0.0003 (-0.03, 0.03) 0.99 -0.02 (-0.04, 0.01) 0.13 -0.02 (-0.04, 0.01) 0.14 -0.02 (-0.04, -0.001) 0.038 -0.02 (-0.04,-0.0004) 0.045
BMI 0.01 (0.01, 0.02) <0.001 0.01 (0.01, 0.01) <0.001 0.02 (0.01, 0.02) <0.001 0.01 (0.01, 0.02) <0.001 0.01 (0.01, 0.02) <0.001 0.01 (0.01, 0.01) <0.001
Current smoking -0.05 (-0.10, -0.01) 0.018 -0.04 (-0.09,-0.0002) 0.049 -0.06 (-0.09, -0.02) 0.002 -0.04 (-0.08, -0.01) 0.016 -0.05 (-0.08, -0.02) 0.001 -0.04 (-0.07, -0.01) 0.007
Alcohol use 0.01 (-0.04, 0.06) 0.73 0.02 (-0.03, 0.07) 0.48 0.003 (-0.04, 0.04) 0.89 0.01 (-0.03, 0.05) 0.72 0.005 (-0.03, 0.04) 0.81 0.01 (-0.02, 0.05) 0.53
HCV -0.04 (-0.10, 0.03) 0.27 -0.001 (-0.05, 0.05) 0.97 0.01 (-0.04, 0.06) 0.71
HBV 0.01 (-0.04, 0.06) 0.70 -0.01 (-0.06, 0.03) 0.61 -0.01 (-0.05, 0.03) 0.62
FH of osteoporosis -0.002 (-0.05, 0.04) 0.92 0.015 (-0.022,0.052) 0.43 0.018 (-0.015, 0.05) 0.29
Open in a new tab

*Coef = coefficient, BKK, residential location in Bangkok.

All variables with p-value <0.20 in the univariate analysis together with age, BMI, current smoking and alcohol use status were adjusted in the multivariate model. BMI: body mass index; HCV: hepatitis C; HBV: hepatitis B; FH: family history.

Table 4. Univariate and multivariate analysis of factors associated with BMD at the lumbar spine, total hip, and femoral neck in women.

Lumbar spine Total hip Femoral neck
Univariate analysis Multivariate analysis Univariate analysis Multivariate analysis Univariate analysis Multivariate analysis
Coef (95%CI) P-value Coef (95%CI) P-value Coef (95%CI) P-value Coef (95%CI) P-value Coef (95%CI) P-value Coef (95%CI) P-value
HIV -0.03 (-0.08, 0.02) 0.22 -0.04 (-0.08, 0.01) 0.12 -0.02 (-0.06, 0.03) 0.48 -0.01 (-0.05, 0.03) 0.56 -0.01 (-0.06, 0.04) 0.65 -0.02 (-0.06, 0.02) 0.32
Age by 10 years -0.10 (-0.14, -0.06) <0.001 -0.11 (-0.15, -0.06) <0.001 -0.09 (-0.13, -0.06) <0.001 -0.10 (-0.14, -0.07) <0.001 -0.12 (-0.15, -0.08) <0.001 -0.13 (-0.17, -0.09) <0.001
BMI 0.01 (0.01, 0.02) <0.001 0.02 (0.01, 0.02) <0.001 0.01 (0.01, 0.02) <0.001 0.01 (0.01, 0.02) <0.001 0.01 (0.005, 0.02) <0.001 0.01 (0.01, 0.02) <0.001
Current smoking 0.02 (-0.21, 0.25) 0.85 0.03 (-0.17, 0.23) 0.79 0.04 (-0.17, 0.26) 0.68
Alcohol use 0.04 (-0.09, 0.16) 0.55 0.02 (-0.09, 0.12) 0.77 0.02 (-0.09, 0.14) 0.69
HCV -0.03 (-0.15, 0.09) 0.62 -0.01 (-0.11, 0.09) 0.80 -0.01 (-0.11, 0.10) 0.92
HBV 0.07 (-0.05, 0.18) 0.24 0.04 (-0.05, 0.12) 0.41 0.03 (-0.07, 0.12) 0.59
FH of osteoporosis -0.04 (-0.11, 0.03) 0.27 -0.07 (-0.12, -0.01) 0.029 -0.05 (-0.10, 0.002) 0.059 -0.04 (-0.10, 0.02) 0.23
Still menstruation 0.09 (0.04, 0.14) 0.001 0.05 (0.004, 0.10) 0.035 0.05 (0.01, 0.10) 0.018 0.01 (-0.03, 0.05) 0.59 0.06 (0.01, 0.11) 0.012 0.01 (-0.04, 0.05) 0.79
Open in a new tab

*Coef = coefficient, BKK, residential location in Bangkok.

All variables with p-value <0.20 in the univariate model together with age and BMI were adjusted in the multivariate model. BMI: body mass index; HCV: hepatitis C; HBV: hepatitis B; FH: family history.

Fractures

The percentage of participants with a history of fractures, either all fractures or low-trauma fractures, was similar between PWH and the controls (Table 1). A lateral thoraco-lumbar (T-L) X-ray radiograph was done in 154 PWH (87 men and 67 women). Of these, six men and one woman had morphometric vertebral fractures. There were no significant differences in baseline characteristics, laboratory testing, and the WHO BMD classifications between PWH with and without T-L X ray radiograph.

Calciotropic hormones, vitamin D levels, and bone turnover markers

Serum 25(OH)D levels were lower in HIV+men [23.3 (IQR 17.9–28.8) vs 25.5 (IQR 23.1–31.5) ng/mL, P = 0.001] and HIV+women [21.9 (IQR 17.9–26.8) vs 24.2 (IQR 21.5–28.65) ng/mL, P = 0.035]. Both HIV+men and HIV+women had higher proportion of vitamin D deficiency (men: 33.5% in HIV+ vs. 13.1% in HIV-, P = 0.002; women: 37.6% in HIV+ vs. 20% in HIV-, P = 0.04). c Serum iPTH levels were also significantly higher in PWH compared to the healthy controls (Table 5).

Table 5. Calciotropic hormones, and markers of bone turnover and inflammation.

Laboratory results Men Women
HIV- (n = 61) HIV + (n = 209) P-value HIV- (n = 41) HIV + (n = 126) P-value
Calcium (mg/dL) 9.2 (8.9–9.5) 8.9 (8.5–9.2) <0.001 8.8 (8.3–9.3) 8.9 (8.5–9.3) 0.83
Phosphate (mg/dL) 2.9 (2.7–3.2) 3.3 (2.9–3.7) <0.001 3.4 (3.2–3.6) 3.7 (3.4–4.1) <0.001
Albumin (g/dL) 4.1 (3.9–4.3) 4.4 (4.1–4.6) 0.001 3.9 (3.7–4.1) 4.4 (4.0–4.6) <0.001
iPTH (pg/mL) 34.9 (29.1–46.7) 42.0 (31.1–58.7) 0.010 33.7 (25.4–42.9) 44.8 (36.5–55.3) <0.001
Creatinine (mg/dL) 0.93 (0.84–1.02) 0.97 (0.84–1.13) 0.14 0.72 (0.68–0.77) 0.76 (0.70–0.84) 0.005
Serum 25(OH)D (ng/mL) 25.5 (23.1–31.5) 23.3 (17.9–28.8) 24.2 (21.5–28.7) 21.9 (17.9–26.8)
<20, n (%) 8 (13.1) 70 (33.5) 0.001 8 (20.0) 47 (37.6) 0.035
≥20, n (%) 53 (86.9) 139 (66.5) 0.002 32 (80.0) 78 (62.4) 0.04
P1NP (ng/mL) 41.3(34.9–53.7) 48.6(37.7–58.9) 0.016 49.3(40.5–58.8) 58.9(46.6–79.7) 0.008
CTX (ng/mL) 0.34 (0.24–0.41) 0.39 (0.29–0.51) 0.005 0.35 (0.31–0.44) 0.48 (0.36–0.65) 0.001
hs-CRP (mg/L) 1.32 (0.46–2.32) 1.29 (0.59–2.56) 0.68 1.44 (0.67–2.82) 1.15 (0.58–2.54) 0.61
IL-6 (pg/mL) 6.0 (3.4–10.2) 6.3 (4.3–9.0) 0.64 6.5 (4.5–12.2) 5.9 (4.1–7.4) 0.10
Open in a new tab

Data are reported as median (IQR) or number (percentage). The difference between the people with and without HIV was compared using t-test, and Mann-Whitney two-sample statistic, where appropriate. HIV-, people living without HIV; HIV+, PWH; iPTH, intact parathyroid hormone; 25(OH)D, 25-hydroxyvitamin D; P1NP, procollagen type 1 N-terminal propeptide; and CTX, C-terminal cross-linking telopeptide of type I collagen.

The level of BTMs, serum P1NP and serum CTX, were significantly higher in both HIV+men and HIV+women tPWH compared to healthy controls (Table 5). Only serum P1NP remained significantly higher in HIV+men in the adjusted model (Table 6). There were no differences in the plasma levels of the inflammatory biomarkers, hs-CRP and IL-6, between men and women with and without HIV.

Table 6. Comparison of unadjusted and adjusted bone turnover markers between people living with and without HIV of both sexes.

Bone turnover markers HIV status Unadjusted P-valueⱡ Adjusted P-value
Mean difference 95% CI Mean difference 95% CI
Men (n = 270)
P1NP (ng/mL) Uninfected ref - ref -
Infected 7.15 (1.63, 12.66) 0.011 7.14 (1.52, 12.76) 0.013
CTX (ng/mL) uninfected ref - ref -
infected 0.07 (0.02, 0.12) 0.008 0.04 (-0.02, 0.10) 0.20
25(OH)D (ng/mL) Uninfected ref - ref -
Infected -3.97 (-6.44, -1.49) 0.002 -3.59 (-6.12, -1.06) 0.006
Women (n = 167)
P1NP (ng/mL) uninfected ref - ref -
infected 12.72 (2.92, 22.52) 0.011 10.10 (-2.73, 22.94) 0.122
CTX (ng/mL) uninfected ref - ref -
infected 0.13 (0.04, 0.22) 0.004 0.10 (-0.02, 0.21) 0.097
25(OH)D (ng/mL) Uninfected ref - ref -
Infected -2.49 (-4.80, -0.18) 0.035 -2.97 (-6.18, 0.25) 0.07
Open in a new tab

P-values were estimated by linear regression mode.

All variables with p-value <0.20 in the univariate model together with age, BMI, current smoking and alcohol use status were adjusted in the multivariate model for P1NP and CTX. All variables with p-value <0.20 in the univariate model together with age, BMI, and living in Bangkok were adjusted in the multivariate model for serum 25(OH)D. P1NP: serum procollagen type 1 N-terminal propeptide; CTX: C-terminal cross-linking telopeptide of type I collagen; 25(OH)D:25-dihydroxyvitamin D (25(OH)D).

Being infected with HIV among males was an independent predictor for lower levels of 25(OH)D in the adjusted model containing age, BMI and current residential location. However, serum 25(OH)D level and iPTH were not correlated with BMD results (p-values >0.2). Among PWH, the exposure to TDF or efavirenz did not affect serum 25(OH)D level. Estimated glomerular filtration rates were comparable between the participants with and without HIV for both sexes, and none of them had hypophosphatemia.

Discussion

In the current study, we assessed the BMD and vitamin D status in virologically suppressed PWH aged over 50 years compared to healthy controls. We found that PWH had lower BMD at the total hip and femoral neck. PWH had more clinical risk factors for osteoporosis and/or fracture, such as smoking, and co-infection with either chronic hepatitis B or hepatitis C than their respective controls. In men, BMI and smoking were independent factors that affected the BMD results at all sites, while age was an independent factor affecting BMD at the femoral neck. In women, age and BMI were independent factors affecting BMD at all sites, while still menstruating was an independent factor affecting BMD at the lumbar spine. After adjusting for clinical risk factors listed above, there were no differences in BMD at any sites between PWH and people living without HIV (Tables 3 and 4).

The effects of HIV on BMD have yielded conflicting results. Our study is in line with Bolland MJ. et al. [26] and Kooij KW. et al. [27], who found that there were no significant differences in BMD between men with and without HIV after adjusting for traditional osteoporotic risk factors. In addition, a meta-analysis among PWH, mainly age below 50 years, and age- and sex matched controls showed that HIV infection was not associated with lower BMD after adjusting for traditional risks, mainly body weight [28]. This study further demonstrated that the BMD levels in well virally suppressed older PWH were comparable to people living without HIV, including older women. Interestingly, a recent study also showed that HIV status was not independently associated with volumetric BMD [29].

In contrast, several previous studies reported that PWH had a lower BMD and a higher fracture risk [30–33]. An early meta-analysis of 11 studies reported that PWH had higher risk of having low BMD (6.4 times) and osteoporosis (3.7 times) than people living without HIV [6]. Analysis using a large database from the U.S. healthcare system identified an increase in fracture prevalence among PWH compared to their controls, however, the data regarding factors associated with bone fragility were limited [34]. Several recent studies reported that there was a modest increase or even equivalent fracture risk after demographics, comorbidities, smoking, alcohol, and BMI were adjusted in the multivariate models [35, 36].

In the present study, the percentage of participants with a history of fractures, either all fractures or low-trauma fractures, was similar between PWH and healthy controls. Nearly half of the PWH underwent T-L X-ray radiographs. Of these, 6/87 (6.9%) men and 1/67 (1.5%) woman had morphometric vertebral fractures. Baseline characteristics and BMD results were comparable between those with or without vertebral fracture screening. Unfortunately, this study did not have vertebral fracture data in the control group for comparison. However, the percentage of morphometric vertebral fractures in PWH was less than what have been reported in the general population [37–40].

The underlying mechanisms for bone loss in PWH are multifactorial, including traditional, HIV-specific risk factors and ART. ART initiation, regardless of regimen, resulted in a 2–6% decrease in BMD over the first few years [21, 41, 42] and became stable or started to increase thereafter [5, 15, 43, 44]. This study did not find an association between HIV and ART (duration of HIV diagnosis, nadir or current CD4 cell count, or baseline HIV-1 RNA) as well as BMD. Although TDF and some protease inhibitors have been shown to be associated with BMD loss and may increase fracture risk [45, 46], this study did not detect this association, possibly partly due to the lower dose of TDF use. Thirty-five percent of the participants in this study used TDF at half dose or they were switched to non-TDF regimen before enrollment into the study.

Furthermore, vitamin D plays a key role in calcium and skeletal homeostasis and there is limited evidence that suggests low vitamin D levels are related to low BMD in PWH [47]. Several studies consistently demonstrated a high prevalence of vitamin D deficiency in PWH [18]. It can be related to traditional risk factors, specific ART including efavirenz and protease inhibitors, and HIV-induced chronic inflammation [18, 48, 49]. In this study, HIV infection was significantly associated with lower 25(OH)D levels in the multivariate model which was adjusted for age and BMI. However, neither serum 25(OH)D nor iPTH level was associated with BMD. The association of TDF and efavirenz as well as serum 25(OH)D levels were also not detected. In addition, this study did not observe the association of inflammatory biomarkers, hs-CRP and IL-6, and serum 25(OH)D levels among both men and women.

On the other hand, the level of bone turnover markers, serum P1NP and serum CTX, were higher in PWH compared to healthy controls. However, only serum P1NP remained significantly higher in HIV+men in the multivariate model. The absolute differences were small and the median (IQR) values for both groups were within the reference range, and therefore, unlikely to be clinically significant. Collectively, the results from this study indicated that bone loss or fracture risk in older virologically suppressed PWH are mainly caused by the traditional risk factors as seen in the general population. Once HIV infection was controlled after ART, bone loss or fracture risk can be reversed, at least some part, over time.

This study had some limitations. First, PWH were from a research clinic and were closely monitored and regularly followed. The findings from this study may not be applicable to other older PWH from other settings, where the resources are more limited. Second, all PWH included in the study were long term virologically suppressed, so this study could not investigate whether uncontrolled HIV could have had any significant long-term impact on the bone health or not. Third, one-third of PWH used TDF at half dose, hence this study cannot conclude whether TDF was not associated with low BMD. It is possible that lower tenofovir concentrations may lower the risk of having low BMD as seen in tenofovir alafenamide treated participants. Forth, smoking, alcohol consumption, and history of fracture were self-reported and could possibly have been underestimated. Fifth, index of bone microarchitectural quality, such as trabecular bone score, was not assessed in our study. It has been shown that PWH had worse bone microarchitecture than age- and sex-matched HIV negative persons [50]. Future studies evaluating the bone quality together with BMD may improves fracture prediction in older PWH with virological suppression. Finally, this study is a cross-sectional design, while a longitudinal study would have provided more information on the BMD changes over time and the fracture incidence, as well as the factors that influence bone loss and fracture.

In conclusion, older PWH with virological suppression did not have lower BMD and fracture rates were comparable to the general population. These results indicated that effective treatment for HIV and minimization of other traditional osteoporosis risk factors can help maintain good skeletal health and prevent premature bone loss.

Acknowledgments

The authors would like to thank the participants for volunteering in this study and HIV-NAT 207/006 study team for their contribution. The study team members are listed below.

HIV-NAT 207/006 study team

Lead author–Anchalee Avihingsanon (anchaleea2009@gmail.com)

HIV-NAT, Thai Red Cross–AIDS Research Centre: Anchalee Avihingsanon, Aroonsiri Sangarlangkarn, Sivaporn Gatechompol, Stephen J Kerr, Tanakorn Apornpong, Sasiwimol Ubolyam, Jaravee Jirapasiri, Supalak Phonphithak, Khuanruan Supakawee, and Sarapol Thongphan

Division of Endocrinology and Metabolism, Department of Medicine, Faculty of Medicine, Chulalongkorn University: Sarat Sunthornyothin, Lalita Wattanachanya

Division of Nuclear medicine, Department of Radiology, Faculty of Medicine, Chulalongkorn University: Tawatchai Chaiwatanarat

Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University: Aurauma Chutinet

Division of Infectious Diseases, Department of Medicine, Faculty of Medicine, Chulalongkorn University: Opass Putcharoen

Division of Perioperative and Ambulatory Medicine, Department of Medicine, Faculty of Medicine, Chulalongkorn University: Sarawut Siwamogsatham

Division of Cardiovascular Diseases, Department of Medicine, Faculty of Medicine, Chulalongkorn University: Sudarat Satitthummanid, Pairoj Chattranukulchai, Smonporn Boonyaratavej Songmuang and Aekarach Ariyachaipanich.

Data Availability

Data cannot be shared publicly because of confidentiality concerns. Data are available from the Chulalongkorn University Institutional Review Boards/ Ethics Committee (contact via chavalun.r@hivnat.org) for researchers who meet the criteria for access to confidential data.

Funding Statement

The authors received no specific funding for this work.

References

  • 1.Antiretroviral Therapy Cohort C. Survival of HIV-positive patients starting antiretroviral therapy between 1996 and 2013: a collaborative analysis of cohort studies. Lancet HIV. 2017;4(8):e349–e356. doi: 10.1016/S2352-3018(17)30066-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Autenrieth CS, Beck EJ, Stelzle D, Mallouris C, Mahy M, Ghys P. Global and regional trends of people living with HIV aged 50 and over: Estimates and projections for 2000–2020. PLoS One. 2018;13(11):e0207005. doi: 10.1371/journal.pone.0207005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Wing EJ. HIV and aging. Int J Infect Dis. 2016. Dec;53:61–68. doi: 10.1016/j.ijid.2016.10.004 [DOI] [PubMed] [Google Scholar]
  • 4.Smit M, Brinkman K, Geerlings S, Smit C, Thyagarajan K, Sighem Av, et al. Future challenges for clinical care of an ageing population infected with HIV: a modelling study. Lancet Infect Dis. 2015;15(7):810–8. doi: 10.1016/S1473-3099(15)00056-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Dolan SE, Kanter JR, Grinspoon S. Longitudinal analysis of bone density in human immunodeficiency virus-infected women. J Clin Endocrinol Metab. 2006;91(8):2938–2945. doi: 10.1210/jc.2006-0127 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Brown TT, Qaqish RB. Antiretroviral therapy and the prevalence of osteopenia and osteoporosis: a meta-analytic review. AIDS. 2006;20(17):2165–2174. doi: 10.1097/QAD.0b013e32801022eb [DOI] [PubMed] [Google Scholar]
  • 7.Goh SSL, Lai PSM, Tan ATB, Ponnampalavanar S. Reduced bone mineral density in human immunodeficiency virus-infected individuals: a meta-analysis of its prevalence and risk factors. Osteoporos Int. 2018;29(3):595–613. doi: 10.1007/s00198-017-4305-8 [DOI] [PubMed] [Google Scholar]
  • 8.Shiau S, Broun EC, Arpadi SM, Yin MT. Incident fractures in HIV-infected individuals: a systematic review and meta-analysis. AIDS. 2013;27(12):1949–1957. doi: 10.1097/QAD.0b013e328361d241 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Prieto-Alhambra D, Guerri-Fernandez R, De Vries F, Lalmohamed A, Bazelier M, Starup-Linde J, et al. HIV infection and its association with an excess risk of clinical fractures: a nationwide case-control study. J Acquir Immune Defic Syndr. 2014;66(1):90–95. doi: 10.1097/QAI.0000000000000112 [DOI] [PubMed] [Google Scholar]
  • 10.Guerri-Fernandez R, Vestergaard P, Carbonell C, Knobel H, Aviles FF, Castro AS, et al. HIV infection is strongly associated with hip fracture risk, independently of age, gender, and comorbidities: a population-based cohort study. J Bone Miner Res. 2013;28(6):1259–1263. doi: 10.1002/jbmr.1874 [DOI] [PubMed] [Google Scholar]
  • 11.Amorosa V, Tebas P. Bone disease and HIV infection. Clin Infect Dis. 2006;42(1):108–114. doi: 10.1086/498511 [DOI] [PubMed] [Google Scholar]
  • 12.Arnsten JH, Freeman R, Howard AA, Floris-Moore M, Santoro N, Schoenbaum EE. HIV infection and bone mineral density in middle-aged women. Clin Infect Dis. 2006;42(7):1014–1020. doi: 10.1086/501015 [DOI] [PubMed] [Google Scholar]
  • 13.Compston J. Osteoporosis and fracture risk associated with HIV infection and treatment. Endocrinol Metab Clin North Am. 2014;43(3):769–780. doi: 10.1016/j.ecl.2014.05.001 [DOI] [PubMed] [Google Scholar]
  • 14.Mondy K, Tebas P. Emerging bone problems in patients infected with human immunodeficiency virus. Clin Infect Dis. 2003;36(Suppl 2):S101–105. doi: 10.1086/367566 [DOI] [PubMed] [Google Scholar]
  • 15.Mondy K, Yarasheski K, Powderly WG, Whyte M, Claxton S, DeMarco D, et al. Longitudinal evolution of bone mineral density and bone markers in human immunodeficiency virus-infected individuals. Clin Infect Dis. 2003;36(4):482–490. doi: 10.1086/367569 [DOI] [PubMed] [Google Scholar]
  • 16.McComsey GA, Tebas P, Shane E, Yin MT, Overton ET, Huang JS, et al. Bone disease in HIV infection: a practical review and recommendations for HIV care providers. Clin Infect Dis. 2010;51(8):937–946. doi: 10.1086/656412 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Nylen H, Habtewold A, Makonnen E, Yimer G, Bertilsson L, Burhenne J, et al. Prevalence and risk factors for efavirenz-based antiretroviral treatment-associated severe vitamin D deficiency: A prospective cohort study. Medicine (Baltimore). 2016;95(34):e4631. doi: 10.1097/MD.0000000000004631 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Mansueto P, Seidita A, Vitale G, Gangemi S, Iaria C, Cascio A. Vitamin D Deficiency in HIV Infection: Not Only a Bone Disorder. Biomed Res Int. 2015;2015(735615. doi: 10.1155/2015/735615 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Hernandez-Vallejo SJ, Beaupere C, Larghero J, Capeau J, Lagathu C. HIV protease inhibitors induce senescence and alter osteoblastic potential of human bone marrow mesenchymal stem cells: beneficial effect of pravastatin. Aging Cell. 2013;12(6):955–965. doi: 10.1111/acel.12119 [DOI] [PubMed] [Google Scholar]
  • 20.Vikulina T, Fan X, Yamaguchi M, Roser-Page S, Zayzafoon M, Guidot DM, et al. Alterations in the immuno-skeletal interface drive bone destruction in HIV-1 transgenic rats. Proc Natl Acad Sci U S A. 2010;107(31):13848–13853. doi: 10.1073/pnas.1003020107 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Brown TT, McComsey GA, King MS, Qaqish RB, Bernstein BM, da Silva BA. Loss of bone mineral density after antiretroviral therapy initiation, independent of antiretroviral regimen. J Acquir Immune Defic Syndr. 2009;51(5):554–561. doi: 10.1097/QAI.0b013e3181adce44 [DOI] [PubMed] [Google Scholar]
  • 22.Holick MF, Binkley NC, Bischoff-Ferrari HA, Gordon CM, Hanley DA, Heaney RP, et al. Evaluation, treatment, and prevention of vitamin D deficiency: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab. 2011;96(7):1911–1930. doi: 10.1210/jc.2011-0385 [DOI] [PubMed] [Google Scholar]
  • 23.World Health Organization Institution Repository for Information Sharing. Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Report of a WHO Study Group. World Health Organ Tech Rep Ser. Geneva, Switzerland 1994. Available at https://apps.who.int/iris/handle/10665/39142 (accessed Nov 9, 2022) [PubMed] [Google Scholar]
  • 24.Kanis JA, Melton LJ 3rd, Christiansen C, Johnston CC, Khaltaev N. The diagnosis of osteoporosis. J Bone Miner Res. 1994;9(8):1137–1141. doi: 10.1002/jbmr.5650090802 [DOI] [PubMed] [Google Scholar]
  • 25.Genant HK, Wu CY, van Kuijk C, Nevitt MC. Vertebral fracture assessment using a semiquantitative technique. J Bone Miner Res. 1993;8(9):1137–1148. doi: 10.1002/jbmr.5650080915 [DOI] [PubMed] [Google Scholar]
  • 26.Bolland MJ, Grey AB, Horne AM, Briggs SE, Thomas MG, Ellis-Pegler RB, et al. Bone mineral density is not reduced in HIV-infected Caucasian men treated with highly active antiretroviral therapy. Clin Endocrinol (Oxf). 2006;65(2):191–197. doi: 10.1111/j.1365-2265.2006.02572.x [DOI] [PubMed] [Google Scholar]
  • 27.Kooij KW, Wit FW, Bisschop PH, Schouten J, Stolte IG, Prins M, et al. Low bone mineral density in patients with well-suppressed HIV infection: association with body weight, smoking, and prior advanced HIV disease. J Infect Dis. 2015;211(4):539–548. doi: 10.1093/infdis/jiu499 [DOI] [PubMed] [Google Scholar]
  • 28.Bolland MJ, Grey A, Reid IR. Skeletal health in adults with HIV infection. Lancet Diabetes Endocrinol. 2015;3(1):63–74. doi: 10.1016/S2213-8587(13)70181-5 [DOI] [PubMed] [Google Scholar]
  • 29.Thomsen MT, Wiegandt YL, Gelpi M, Knudsen AD, Fuchs A, Sigvardsen PE, et al. Prevalence of and Risk Factors for Low Bone Mineral Density Assessed by Quantitative Computed Tomography in People Living With HIV and Uninfected Controls. J Acquir Immune Defic Syndr. 2020;83(2):165–172. doi: 10.1097/QAI.0000000000002245 [DOI] [PubMed] [Google Scholar]
  • 30.Cazanave C, Dupon M, Lavignolle-Aurillac V, Barthe N, Lawson-Ayayi S, Mehsen N, et al. Reduced bone mineral density in HIV-infected patients: prevalence and associated factors. AIDS. 2008;22(3):395–402. doi: 10.1097/QAD.0b013e3282f423dd [DOI] [PubMed] [Google Scholar]
  • 31.Rivas P, Gorgolas M, Garcia-Delgado R, Diaz-Curiel M, Goyenechea A, Fernandez-Guerrero ML. Evolution of bone mineral density in AIDS patients on treatment with zidovudine/lamivudine plus abacavir or lopinavir/ritonavir. HIV Med. 2008;9(2):89–95. doi: 10.1111/j.1468-1293.2007.00525.x [DOI] [PubMed] [Google Scholar]
  • 32.Bonjoch A, Figueras M, Estany C, Perez-Alvarez N, Rosales J, del Rio L, et al. High prevalence of and progression to low bone mineral density in HIV-infected patients: a longitudinal cohort study. AIDS. 2010;24(18):2827–2833. doi: 10.1097/QAD.0b013e328340a28d [DOI] [PubMed] [Google Scholar]
  • 33.Jones S, Restrepo D, Kasowitz A, Korenstein D, Wallenstein S, Schneider A, et al. Risk factors for decreased bone density and effects of HIV on bone in the elderly. Osteoporos Int. 2008;19(7):913–918. doi: 10.1007/s00198-007-0524-8 [DOI] [PubMed] [Google Scholar]
  • 34.Triant VA, Brown TT, Lee H, Grinspoon SK. Fracture prevalence among human immunodeficiency virus (HIV)-infected versus non-HIV-infected patients in a large U.S. healthcare system. J Clin Endocrinol Metab. 2008;93(9):3499–3504. doi: 10.1210/jc.2008-0828 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Womack JA, Goulet JL, Gibert C, Brandt C, Chang CC, Gulanski B, et al. Increased risk of fragility fractures among HIV infected compared to uninfected male veterans. PLoS One. 2011;6(2):e17217. doi: 10.1371/journal.pone.0017217 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Sharma A, Shi Q, Hoover DR, Anastos K, Tien PC, Young MA, et al. Increased Fracture Incidence in Middle-Aged HIV-Infected and HIV-Uninfected Women: Updated Results From the Women’s Interagency HIV Study. J Acquir Immune Defic Syndr. 2015;70(1):54–61. doi: 10.1097/QAI.0000000000000674 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Wattanachanya L, Pongchaiyakul C. Prevalence and risk factors of morphometric vertebral fracture in apparently healthy osteopenic postmenopausal Thai women. Menopause. 2020;28(1):12–17. doi: 10.1097/GME.0000000000001634 [DOI] [PubMed] [Google Scholar]
  • 38.Melton LJ 3rd, Kan SH, Frye MA, Wahner HW, O’Fallon WM, Riggs BL. Epidemiology of vertebral fractures in women. Am J Epidemiol. 1989;129(5):1000–1011. doi: 10.1093/oxfordjournals.aje.a115204 [DOI] [PubMed] [Google Scholar]
  • 39.Ho-Pham LT, Mai LD, Pham HN, Nguyen ND, Nguyen TV. Reference ranges for vertebral heights and prevalence of asymptomatic (undiagnosed) vertebral fracture in Vietnamese men and women. Arch Osteoporos. 2012;7(257–266. doi: 10.1007/s11657-012-0106-z [DOI] [PubMed] [Google Scholar]
  • 40.Fujiwara S, Kasagi F, Masunari N, Naito K, Suzuki G, Fukunaga M. Fracture prediction from bone mineral density in Japanese men and women. J Bone Miner Res. 2003;18(8):1547–1553. doi: 10.1359/jbmr.2003.18.8.1547 [DOI] [PubMed] [Google Scholar]
  • 41.Cassetti I, Madruga JV, Suleiman JM, Etzel A, Zhong L, Cheng AK, et al. The safety and efficacy of tenofovir DF in combination with lamivudine and efavirenz through 6 years in antiretroviral-naive HIV-1-infected patients. HIV Clin Trials. 2007;8(3):164–172. doi: 10.1310/hct0803-164 [DOI] [PubMed] [Google Scholar]
  • 42.Duvivier C, Kolta S, Assoumou L, Ghosn J, Rozenberg S, Murphy RL, et al. Greater decrease in bone mineral density with protease inhibitor regimens compared with nonnucleoside reverse transcriptase inhibitor regimens in HIV-1 infected naive patients. AIDS. 2009;23(7):817–824. doi: 10.1097/QAD.0b013e328328f789 [DOI] [PubMed] [Google Scholar]
  • 43.Bolland MJ, Grey AB, Horne AM, Briggs SE, Thomas MG, Ellis-Pegler RB, et al. Bone mineral density remains stable in HAART-treated HIV-infected men over 2 years. Clin Endocrinol (Oxf). 2007;67(2):270–275. doi: 10.1111/j.1365-2265.2007.02875.x [DOI] [PubMed] [Google Scholar]
  • 44.Bolland MJ, Horne AM, Briggs SE, Thomas MG, Reid IR, Gamble GD, et al. Long-Term Stable Bone Mineral Density in HIV-Infected Men Without Risk Factors for Osteoporosis Treated with Antiretroviral Therapy. Calcif Tissue Int. 2019;105(4):423–429. doi: 10.1007/s00223-019-00579-0 [DOI] [PubMed] [Google Scholar]
  • 45.Moran CA, Weitzmann MN, Ofotokun I. The protease inhibitors and HIV-associated bone loss. Curr Opin HIV AIDS. 2016;11(3):333–342. doi: 10.1097/COH.0000000000000260 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Grant PM, Cotter AG. Tenofovir and bone health. Curr Opin HIV AIDS. 2016;11(3):326–332. doi: 10.1097/COH.0000000000000248 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Dave JA, Cohen K, Micklesfield LK, Maartens G, Levitt NS. Antiretroviral Therapy, Especially Efavirenz, Is Associated with Low Bone Mineral Density in HIV-Infected South Africans. PLoS One. 2015;10(12):e0144286. doi: 10.1371/journal.pone.0144286 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Shahar E, Segal E, Rozen GS, Shen-Orr Z, Hassoun G, Kedem E, et al. Vitamin D status in young HIV infected women of various ethnic origins: incidence of vitamin D deficiency and possible impact on bone density. Clin Nutr. 2013;32(1):83–87. doi: 10.1016/j.clnu.2012.05.022 [DOI] [PubMed] [Google Scholar]
  • 49.Van Den Bout-Van Den Beukel CJ, Fievez L, Michels M, Sweep FC, Hermus AR, Bosch ME, et al. Vitamin D deficiency among HIV type 1-infected individuals in the Netherlands: effects of antiretroviral therapy. AIDS Res Hum Retroviruses. 2008;24(11):1375–1382. doi: 10.1089/aid.2008.0058 [DOI] [PubMed] [Google Scholar]
  • 50.Sharma A, Ma Y, Tien PC, Scherzer R, Anastos K, Cohen MH, et al. HIV Infection Is Associated With Abnormal Bone Microarchitecture: Measurement of Trabecular Bone Score in the Women’s Interagency HIV Study. J Acquir Immune Defic Syndr. 2018;78(4):441–449. doi: 10.1097/QAI.0000000000001692 [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision Letter 0

Julie AE Nelson

1 Aug 2022

PONE-D-22-09858Bone mineral density among virologically suppressed Asians older than 50 years old living with and without HIV: a cross-sectional studyPLOS ONE

Dear Dr. Avihingsanon,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Each of the two reviewers has made specific recommendations for something to add so please address this in your revised version.

Please submit your revised manuscript by Sep 15 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Julie AE Nelson, PhD

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at 

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and 

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Thank you for stating the following financial disclosure: 

The author(s) received no specific funding for this work. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

At this time, please address the following queries:

a) Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution. 

b) State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”

c) If any authors received a salary from any of your funders, please state which authors and which funders.

d) If you did not receive any funding for this study, please state: “The authors received no specific funding for this work.”

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

3. Thank you for stating the following in the Competing Interests section: 

I have read the journal's policy and the authors of this manuscript have the following competing interests: KR received honoraria or consultation fees and/or participation in a company sponsored speaker's bureau from: ViiV, Merck, Jensen-Cilag, Mylan and Gilead. The rest of the authors declare no conflict of interest.

Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, by including the following statement: "This does not alter our adherence to  PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests).  If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared. 

Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf.

4. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ

5. One of the noted authors is a group or consortium HIV-NAT 207/006 study team. In addition to naming the author group, please list the individual authors and affiliations within this group in the acknowledgments section of your manuscript. Please also indicate clearly a lead author for this group along with a contact email address.

6. We note that you have included the phrase “data not shown” in your manuscript. Unfortunately, this does not meet our data sharing requirements. PLOS does not permit references to inaccessible data. We require that authors provide all relevant data within the paper, Supporting Information files, or in an acceptable, public repository. Please add a citation to support this phrase or upload the data that corresponds with these findings to a stable repository (such as Figshare or Dryad) and provide and URLs, DOIs, or accession numbers that may be used to access these data. Or, if the data are not a core part of the research being presented in your study, we ask that you remove the phrase that refers to these data.

7. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The present manuscript is sound, however, It appears that a critical piece of data is missing. The adjusted BMD values adjust for age, BMD, and other traditional osteoporotic risk factors. The statistical analysis seemed appropriate and was rationalized. All data underlying the findings in their manuscript were made fully available. Moreover, the manuscript is presented in an intelligible fashion and written in standard English.

Reviewer #2: Introduction:

Well written overview of the current literature, as well as justification for the research conducted.

Methods:

Study population: further information should be detailed on how the cohort and sample selected for this specific AMH study were derived. Sample size (462 of which 256 were Women living with HIV (WLWHIV) ) appears adequate to make conclusions although the wide age range ( 12-50 years of age) result in small numbers in certain age groups.

Statistical Analyses appear appropriate.

Results:

The findings indicate the expected relationship between younger age and higher AMH levels. Of Interest, and in support of their hypothesis, the authors found that among the women over 35 years of age, the AMH levels were associated with HIV status and shortened telomere length in PBMCs, with WLWHIV having lower AMH levels compared to women of similar age range who were not HIV infected. These findings support earlier studies that suggested WLWHIV and provide a potential laboratory marker, AMH, to help provide guidance for WLWHIV with regards to fertility, and child spacing decisions. Some limitations to the findings include that the WLWHIV had increased risk of other risk factors that could also impact on telomere length and ovarian function such as smoking, and drug use.

Conclusions: well thought out and not overreaching.

In summary, an interesting and useful manuscript in terms of better understanding of the role of AMH over time and hypotheses generating in terms of differences seen among WLWHIV and women without HIV in terms of ovarian aging and reproductive health.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachment

Submitted filename: PONE-D-22-09858_Rec.pdf

Click here for additional data file. (68.7KB, pdf)
PLoS One. 2022 Nov 21;17(11):e0277231. doi: 10.1371/journal.pone.0277231.r002

Author response to Decision Letter 0

30 Sep 2022

Reviewers' comments:

Reviewer #1:

1. Improve mechanics, table organization, spacing as well as formatting of tables in the document.

RESPONSE: Thank you for the suggestion. We have managed to make sure that all the tables are well formatted and easy to read.

2. A few lines, for example, Line 57 appear to need citations.

RESPONSE: Thank you for pointing out this this. We have carefully rechecked to ensure that all the sentences had proper citations, including the sentence in line 58-59. Reference 3, 4, and 50 were added into the References section.

3. The reproductive history in Table 1 is unclear. Is menstruation exhausted referring to the number of women that have reached menopause?

RESPONSE: Thank you for. Yes, “menstruation exhausted” referred to the number of women that have reached menopause. We have added “n (%)” after each category of reproductive history in Table 1.

4. Empty boxes in tables 3 and 4

RESPONSE: All variables with p-values ≤ 0.20 from the univariate analyses were included in the multivariable regression model. Therefore, all the empty boxes in Table 3 and Table 4 were left blank because these variables that were not significant in the univariate models were not included in the multivariate analyses. The detailed methodology regarding the adjusted models was provided in the Statistical analysis section of, line 132-133.

5. What units are being presented in table 6?

RESPONSE: We have added the units of P1NP, CTX and 25(OH)D in Table 6.

6. Were any of the women in the study on hormonal replacement therapy?

RESPONSE: All the women in the study were not on hormonal replacement therapy.

7. In the abstract it is written, “After adjusting for age, BMI, 45 and other traditional osteoporotic risk factors, BMD of virologically suppressed older PWH did not differ from participants without HIV”, however, no data is shown highlighting adjusted BMD. A similar statement is made in the discussion, lines 259-260, which states, “after adjusting for clinical risk factors listed above, there was no difference in BMD at any sites between PWH and people living without HIV”, however, adjusted BMD values are not in the manuscript. All that is shown in table 2, which has the unadjusted BMD values, which are lower in people with HIV compared to people without HIV.

RESPONSE: Analysis of the comparison of adjusted BMD between HIV+ and HIV- participants of both sexes (shown below) indicated that the BMD values after adjustment were comparable between HIV- and HIV+ of both sexes.

Comparison of adjusted BMD between HIV+ and HIV- participants of both sexes

Site HIV status Absolute BMD (g/cm2) Adjusted model* P-valueⱡ

Mean difference 95% CI

Men (n=297)

Lumbar spine uninfected 0.96 (0.14) ref -

infected 0.94 (0.16) -0.002 (-0.04, 0.04) 0.93

Total hip uninfected 0.91 (0.13) ref -

infected 0.86 (0.13) -0.03 (-0.06, 0.003) 0.076

Femoral neck uninfected 0.74 (0.12) ref -

infected 0.71 (0.11) -0.02 (-0.04, 0.01) 0.26

Women (n=184)

Lumbar spine uninfected 0.88 (0.18) ref -

infected 0.85 (0.16) -0.04 (-0.08, 0.01) 0.12

Total hip uninfected 0.81 (0.17) ref -

infected 0.79 (0.13) -0.01 (-0.05, 0.03) 0.56

Femoral neck uninfected 0.66 (0.21) ref -

infected 0.64 (0.12) -0.02 (-0.06, 0.02) 0.32

*Adjusted for age, BMI, and smoking status in men and for age, BMI, and menstruation

status in women; ⱡ P-values were estimated by linear regression models

• We have demonstrated in Table 3 and Table 4 that HIV status was not correlated with BMD in both men and women in the multivariate analyses. So, we did not include the table above in our manuscript.

However, we have provided p-value “P>0.1” in the abstract as the followings:

“After adjusting for age, BMI, 45 and other traditional osteoporotic risk factors, BMD of virologically suppressed older PWH did not differ from participants without HIV (P>0.1)”.

• In Discussion section, we have also added the table references “(Table 3 and Table 4)” in line 271-273 as the following:

“…after adjusting for clinical risk factors listed above, there was no difference in BMD at any sites between PWH and people living without HIV (Table 3 and Table 4).”

8. Elevated circulating levels of bone turnover markers such as P1NP and CTX can be indicative of dysregulated bone turnover, which can also drive increased fracture risk. It is worth discussing what this could mean for long-term bone quality for people living with HIV. For instance, it has been shown that there is reduced bone microarchitecture in people with HIV despite comparable BMD relative to HIV age-matched sex-matched HIV negative persons, therefore even if there are no significant BMD differences there are other factors outside of BMD that may drive fracture risk.

RESPONSE: We have expanded our discussion on page 21 in Discussion section, line 335-337, as the followings:

“Fifth, index of bone microarchitectural quality, such as trabecular bone score, was not assessed in our study. It has been shown that PWH had worse bone microarchitecture than age- and sex-matched HIV negative persons [50]. Future studies evaluating the bone quality together with BMD may improves fracture prediction in older PWH with virological suppression. Finally, this study is a cross-sectional design, while a longitudinal study would have provided more information on the BMD changes over time and the fracture incidence, as well as the factors that influence bone loss and fracture.”

Reviewer #2:

1. Ideally, a longitudinal design would have been used. The authors should comment on the rationale for only presenting cross sectional data for this cohort which is in long term follow up.

RESPONSE: Thank you for your suggestion. Currently, the longitudinal study of these participants is undergoing to follow-up on measuring the changes in BMD and the fracture incidence, as well as identifying the factors that influence bone loss and fracture.

• In the current study, we report the outcome of BMD, calciotropic hormones, vitamin D status, and bone turnover markers at the patients’ baseline visit compared to HIV-uninfected controls.

• We have expanded our discussion on page 22 in Discussion section, line 339-341.

2. The reason that 38% of those on TDF ART were on a half dose should be further detailed.

RESPONSE: All treatment regimens and doses were based on the physician’s decision since this is an observational study, and the reason behind it may probably due to the reduced creatinine clearance or low body weight of patients. We have added more detail in Results section (line 160-162) as the following:

“Among these, 35% used TDF at half dose. Of note, since this is an observational study, all ART regimens and doses were based on the physician’s decision and local guidelines, and the reason behind it may probably because of reduced creatinine clearance or low body weight of patients.”

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (23.6KB, docx)

Decision Letter 1

Julie AE Nelson

24 Oct 2022

Bone mineral density among virologically suppressed Asians older than 50 years old living with and without HIV: a cross-sectional study

PONE-D-22-09858R1

Dear Dr. Avihingsanon,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Julie AE Nelson, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: In addition to fully addressing all of the reviewers' comments, the authors improved the readability of the manuscript and provided further justification for the formatting.

Reviewer #2: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

Acceptance letter

Julie AE Nelson

28 Oct 2022

PONE-D-22-09858R1

Bone mineral density among virologically suppressed Asians older than 50 years old living with and without HIV: A cross-sectional study

Dear Dr. Avihingsanon:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Julie AE Nelson

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Attachment

    Submitted filename: PONE-D-22-09858_Rec.pdf

    Click here for additional data file. (68.7KB, pdf)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (23.6KB, docx)

    Data Availability Statement

    Data cannot be shared publicly because of confidentiality concerns. Data are available from the Chulalongkorn University Institutional Review Boards/ Ethics Committee (contact via chavalun.r@hivnat.org) for researchers who meet the criteria for access to confidential data.

    Articles from PLOS ONE are provided here courtesy of PLOS

    RESOURCES