lfgouvea@ufj.edu.br

livia.sousa@discente.ufj.edu.br

talys.filho@discente.ufj.edu.br

maria.aniceto@discente.ufj.edu.br

silvaniayukiko@hotmail.com

mariliabrasil@terra.com.br

*Graduado em Educação Física

pela Universidade Federal de Uberlândia, Uberlândia, Minas Gerais

Mestre em Genérica e Bioquímica

pela Universidade Federal de Uberlândia, Uberlândia, Minas Gerais,

Doutor em Doenças Tropicais

pela Universidade Federal do Pará (UFPA), Belém, Pará

Líder do Grupo de Estudo e Pesquisa Morfofuncional

na Saúde e Doença - GEPEMSAD

Professor da Universidade Federal de Jataí, Jataí, Goiás

**Graduanda/o em Fisioterapia pela Universidade Federal de Jataí, Brasil

Discente do Programa de Iniciação Científica, Tecnológica e em Inovação

Membro do GEPEMSAD

+Graduada em Fisioterapia pela Universidade do Estado do Pará

Mestre em Genética e Biologia Molecular pela UFPA

Doutora em Doenças Tropicais pela Universidade Federal do Pará, Brasil

Professora da Universidade do Estado do Pará, Santarém, Pará

+Graduada em Medicina pela Universidade Federal do Pará

Especialista nas áreas de Dermatologia, Infectologia e Saúde Coletiva

Mestre em Biologia de Agentes Infecciosos e Parasitários pela UFPA

Doutora em Neurociências e Biologia Celular pela UFPA

Pós-Doutorado pela Universidade de São Paulo, Brasil

Professora do Núcleo de Medicina Tropical da UFPA

(Brasil)

Reception: 04/08/2025 - Acceptance: 08/04/2025

1st Review: 07/02/2025 - 2nd Review: 07/29/2025

Accessible document. Law N° 26.653. WCAG 2.0

Suggested reference: Gouvêa-e-Silva, LF, Sousa, LGS, Modesto Filho, TF, Aniceto, MRR, Takanashi, SKL, & Xavier, MB (2025). Cardiometabolic Disorders in People Living with HIV in the Interior of the Amazon, Brazil. Lecturas: Educación Física y Deportes, 30(329), 77-94. https://doi.org/10.46642/efd.v30i329.8365

 

Abstract

    Introduction: HIV infection, combined with antiretroviral therapy (ART), predisposes people living with HIV (PLHIV) to develop metabolic changes, changes in body fat distribution and increased cardiovascular risk (CVR). Objective: To analyze the relationship between metabolic syndrome (MetS), dyslipidemia, lipodystrophy, and CVR with the sociodemographic and clinical characteristics of PLHIV in the interior of the Amazon, Brazil. Methods: Cross-sectional study, composed of 115 PLHIV, treated at a Specialized Outpatient Clinic. Sociodemographic, clinical, laboratory, body composition information was sought, as well as the presence of MetS, dyslipidemia, lipodystrophy and CVR. Data were analyzed using descriptive and inferential statistics, adopting p<0.05. Results: Males predominated (59.1%), as well as dyslipidemia (81.7%). It was observed that 22.6% of PLHIV had MetS, 37.4% had lipodystrophy and 8.7% had moderate CVR. Age ≥40 years was associated with MetS and lipodystrophy; and longer duration of ART use was associated with lipodystrophy (p<0.05). Smoking and lipodystrophy were associated with moderate CVR (p<0.05). Altered values for abdominal circumference, glucose, LDL-c, HDL-c, body mass index and blood pressure were associated with MetS (p<0.05). Conclusion: According to the data, the high frequency of PLHIV with dyslipidemia, lipodystrophy and MetS is worrying, as is the relationship between MS and lipodystrophy and moderate CVR. Thus, the need for continuous monitoring and assertive interventions to prevent the onset or worsening of cardiometabolic diseases in this population is highlighted.

    Keywords: HIV. Heart disease risk factors. Metabolic syndrome. Lipodystrophy. Dyslipidemias.

 

Resumo

    Introdução: A infecção pelo HIV, juntamente ao uso da terapia antirretroviral (TARV), predispõem a pessoa vivendo com HIV (PVHIV) a desenvolver alterações metabólicas, na distribuição da gordura corporal e aumento do risco cardiovascular (RCV). Objetivo: Analisar a relação da síndrome metabólica (SM), dislipidemia, lipodistrofia e RCV com as características sociodemográficas e clínicas das PVHIV no interior da Amazônia, Brasil. Métodos: Estudo transversal, composto por 115 PVHIV, atendidas em um Ambulatório Especializado. Buscou-se informações sociodemográficas, clínicas, laboratoriais, da composição corporal, bem como da presença da SM, dislipidemia, lipodistrofia e RCV. Os dados foram analisados utilizando estatística descritiva e inferencial, adotando-se p<0,05. Resultados: O sexo masculino predominou (59,1%), bem como a dislipidemia (81,7%). Notou-se que 22,6% das PVHIV apresentaram SM, 37,4% lipodistrofia e 8,7% tinham o RCV moderado. A idade ≥40 anos associou-se com a SM e lipodistrofia; e o maior tempo de uso da TARV com a lipodistrofia (p<0,05). O tabagismo e a lipodistrofia se associaram com o RCV moderado (p<0,05). Valores alterados para circunferência abdominal, glicose, LDL-c, HDL-c, índice de massa corporal e pressão arterial se mostraram associadas com a SM (p<0,05). Conclusão: Conforme os dados, é preocupante a elevada frequência de PVHIV com dislipidemia, lipodistrofia e SM, bem como da relação da SM e lipodistrofia com o RCV moderado. Assim, ressalta-se a necessidade do monitoramento contínuo e intervenções assertivas para evitar a instalação ou o agravamento de doenças cardiometabólicas nesse público.

    Unitermos: HIV. Fatores de risco de doenças cardíacas. Síndrome metabólica. Lipodistrofia. Dislipidemias.

 

Resumen

    Introducción: La infección por VIH, junto con el uso de terapia antirretroviral (TAR), predispone a personas que viven con VIH (PVVIH) a desarrollar alteraciones metabólicas en la distribución de la grasa corporal y mayor riesgo cardiovascular (RCV). Objetivo: Analizar la relación entre el síndrome metabólico (SM), la dislipidemia, la lipodistrofia y el RCV con las características sociodemográficas y clínicas de las PVVIH en el interior de la Amazonia, Brasil. Métodos: Estudio transversal, compuesto por 115 PVVIH, atendidas en un Ambulatorio Especializado. Se buscó información sociodemográfica, clínica, de laboratorio, de composición corporal, así como la presencia de SM, dislipidemia, lipodistrofia y RCV. Los datos se analizaron mediante estadística descriptiva e inferencial, adoptando p<0,05. Resultados: Predominó el sexo masculino (59,1%), al igual que la dislipidemia (81,7%). Se observó que el 22,6% de las PVVIH tenía SM, el 37,4% lipodistrofia y el 8,7% RCV moderado. La edad ≥40 años se asoció con EM y lipodistrofia, y una mayor duración del uso de TAR se asoció con lipodistrofia (p<0,05). El tabaquismo y la lipodistrofia se asociaron con RCV moderado (p<0,05). Los valores alterados de perímetro abdominal, glucosa, c-LDL, c-HDL, índice de masa corporal y presión arterial se asociaron con EM (p<0,05). Conclusión: Según los datos, la alta frecuencia de PVVIH con dislipidemia, lipodistrofia y EM, así como la asociación de EM y lipodistrofia con RCV moderado, es preocupante. Por lo tanto, se enfatiza la necesidad de monitoreo continuo e intervenciones asertivas para prevenir la aparición o el empeoramiento de enfermedades cardiometabólicas en esta población.

    Palabras clave: VIH. Factores de riesgo de cardiopatía. Síndrome metabólico. Lipodistrofia. Dislipidemias.

 

Lecturas: Educación Física y Deportes, Vol. 30, Núm. 329, Oct. (2025)

---

 

Introduction 

 

    Globally, more than 39 million people living with HIV (PLHIV) have been reported (Unaids, 2024), and in Brazil, more than one million PLHIV have already been notified (Brazil, 2024). It is noted that, in addition to the increase in the number of notifications, PLHIV are living longer and with better quality of life due to the reduction in AIDS-related mortality rates promoted by the use of antiretroviral therapy (ART). However, despite the increased survival of PLHIV using ART, some adverse effects such as dyslipidemia, insulin resistance, and lipodystrophy may be favored by antiretroviral use (Lagathu et al., 2019). In addition, PLHIV face a higher risk of sudden cardiac death, which can be attributed to factors such as myocardial fibrosis, traditional cardiovascular risk factors, illicit drug use, and accelerated atherosclerosis. (Narla, 2021)

 

    Moreover, the presence of certain cytokines and chemokines in PLHIV may predict disease progression and immune status, due to alterations in inflammatory mechanisms caused by HIV infection (Ngcobo et al., 2022). This low-grade inflammatory profile contributes to the development of metabolic syndrome (MetS) (Obare et al., 2025), as well as antiretroviral therapy favoring dyslipidemia, which also increases cardiovascular risk (CVR). (Ray, 2009)

 

    Lipodystrophy, in its different forms (lipoatrophy, lipohypertrophy, or mixed), may be related to a longer duration of ART use (Martinez et al., 2001). Thus, some antiretrovirals, such as stavudine and didanosine, have been strongly associated with mitochondrial toxicity and lipodystrophy (Ioannou et al., 2015). On the other hand, tenofovir has shown associations with better lipid profiles and less lipodystrophy compared with stavudine (Gallant et al., 2004). Furthermore, people with lipodystrophy are more susceptible to atherosclerotic vascular diseases due to the increased prevalence of dyslipidemia and diabetes mellitus. (Hussain, Patni, & Garg, 2019)

 

    Therefore, this manuscript aimed to analyze the relationship between metabolic syndrome, dyslipidemia, lipodystrophy and cardiovascular risk with the sociodemographic and clinical characteristics of PLHIV in the interior of the Amazon, Brazil.

 

Methods 

 

    The study is cross-sectional, conducted at the Center for Testing and Counseling and Specializated Assistance Service (CTC/SAS), located in Santarém, Pará, Brazil. Participants included in the study were individuals aged ≥18 years, of both sexes, and with positive serology for HIV. Pregnant and lactating women, bedridden PLHIV, and wheelchair users were excluded. Therefore, for convenience, the sample consisted of 115 PLHIV.

 

    All participants were informed about the study and signed the Free and Informed Consent Form. The study was approved by the Human Research Ethics Committee of the Tropical Medicine Center of the Federal University of Pará (CAAE: 27162514.9.0000.5172).

Data collection was performed through an interview (sociodemographic/clinical information), physical evaluation (body composition), and verification of medical records (clinical and laboratory information).

 

    For body mass measurements, a calibrated analog scale was used (Welmy® Industry and Commerce, Santa Bárbara D’Oeste - SP, Brazil), with 100 g precision, and for height, a stadiometer attached to the same scale was used, with 0.50 cm precision. Body mass index (BMI) was calculated by dividing body mass by squared height. Abdominal circumference was measured with an anthropometric tape (Sanny®, São Bernardo do Campo, São Paulo, Brazil), positioned at the umbilical scar (Fernandes Filho, 2003).

 

    Based on these results, BMI was classified according to WHO (2000) cutoffs. For abdominal circumference (men ≥102 cm; women ≥88 cm), glucose (≥100 mg/dL), triglycerides (≥150 mg/dL), HDL-c (high-density lipoprotein; men <40 mg/dL; women <50 mg/dL), blood pressure (systolic ≥130 mmHg; diastolic ≥85 mmHg), as well as for MetS classification, the cutoffs and guidelines of the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATP III; Grundy et al., 2005) were used. The reference values adopted for total cholesterol (<190 mg/dL), and LDL-c (low-density lipoprotein; ≥160 mg/dL) were those suggested by Faludi et al. (2017).

 

    It should be noted that any patient who presented at least one lipid alteration, according to the above cutoffs, was classified as having dyslipidemia. The diagnosis of lipodystrophy was based on clinical examination and patient report of body changes (Sonaglio et al., 2011). The diagnosis of AIDS was attributed to PLHIV who presented CD4+ T lymphocyte counts <200 cells/mm³ or a history of opportunistic infection or cancer in their clinical course. (Scherzer et al., 2011)

 

    The data were tabulated and organized for descriptive statistical analysis (minimum, maximum, median, interquartile range - IQR, absolute and relative frequency) and inferential analysis. After descriptive statistics, the D’Agostino-Pearson normality test was applied to assess data distribution. The data presented in Figure 1 showed a nonparametric distribution; thus, comparisons were performed with the Mann-Whitney test. In addition, the association of MetS, dyslipidemia, lipodystrophy, and CVR with the variables presented in the study was assessed using Simple Logistic Regression, which provided the Odds Ratio (OR) and 95% confidence interval (95% CI). The BioEstat 5.3 program was used for statistical analyses, and the significance level adopted was p<0.05. The GraphPad Prism 3.0 program was used to construct Figure 1.

 

Results 

 

    It is noteworthy that the median age of the participants was 38 years (IQR = 30-49 years; minimum = 20 years; maximum = 68 years), the time since diagnosis of HIV infection was 40 months (IQR = 20-79 months; minimum = 1 month; maximum = 190 months), and the time on ART was 28 months (IQR = 10-61 months; minimum = 0 month; maximum = 181 months). Regarding the distribution of diseases, MetS was observed in 22.6% (n=26), lipodystrophy in 37.4% (n=43), dyslipidemia in 81.7% (n=94), moderate CVR in 8.7% (n=10), and low CVR in 91.3% (n=105) of PLHIV.

 

    Figure 1 presents the comparison of age (Figure 1A), time since diagnosis of HIV infection (Figure 1B), and time on ART (Figure 1C) in relation to MetS, dyslipidemia, lipodystrophy, and CVR in PLHIV. It was observed that age was higher in patients with MetS (p=0.004), lipodystrophy (p<0.001), and moderate CVR (p<0.001). The time to diagnosis was longer only in PLHIV with lipodystrophy compared to those without lipodystrophy (p=0.005). Finally, PLHIV diagnosed with MetS (p=0.042) or lipodystrophy (p<0.001) showed longer duration of ART use.

 

Note: p – presence; a – absence; MS – metabolic syndrome; DYS – dyslipidemia; LIP – lipodystrophy; CVR – cardiovascular risk; l – low; m – moderate; ART – antiretroviral therapy; A to C - median values (interquartile range – 25%-75%; lower and upper extremities of the box); A to C – the lower and upper bars of the box represent minimum and maximum values. Source: Study data

 

    Table 1 presents the distribution of participants according to sociodemographic factors, as well as the association of these variables with MetS, lipodystrophy, and CVR. Dyslipidemia did not show a significant association with the variables in Table 1 (p>0.05), data not shown. Age ≥40 years was associated with the presence of MetS (p=0.029) and lipodystrophy (p<0.001). PLHIV with partners were associated with MetS (p=0.030), and smoking PLHIV with lipodystrophy (p=0.020) and moderate CVR (p=0.015) (Table 1).

 

Metabolic Syndrome

Lipodystrophy

Cardiovascular risk

All

No

Yes

OR

p

No

Yes

OR

p

Low

Mod

OR

p

Variables

n/%

n/%

n/%

CI95%

n/%

n/%

CI95%

n/%

n/%

CI95%

Sex

Male

68/59,1

55/61,8

13/50,0

1,0

45/62,5

23/53,5

1,0

58/55,2

10/100

1,0

Female

47/40,9

34/38,2

13/50,0

1,61 (0,67-3,90)

0,283

27/37,5

20/46,5

1,44 (0,67-3,12)

0,342

47/44,8

0/0

0 (0-∞)

0,693

Age (years)

< 40

66/57,4

56/62,9

10/38,5

1,0

55/76,4

11/27,3

1,0

66/62,9

0/0

1,0

≥ 40

49/42,6

33/37,1

16/61,5

2,71 (1,10-6,68)

0,029

17/23,6

32/72,7

9,41 (3,92-22,57)

<0,001

39/37,1

10/100

18805,34 (0-∞)

0,626

Schooling (years)

≥ 8

80/69,6

63/70,8

17/65,4

1,0

51/70,8

29/67,4

1,0

73/69,5

7/70,0

1,0

< 8

35/30,4

26/29,2

9/34,6

1,28 (0,51-3,25)

0,599

21/29,2

14/32,6

1,17 (0,52-2,65)

0,702

32/30,5

3/30,0

0,97 (0,24-4,02)

0,975

Marital status

Without a partner

70/60,9

59/66,3

11/42,3

1,0

44/61,1

26/60,5

1,0

64/61,0

6/60,0

1,0

With a partner

45/39,1

30/33,7

15/57,7

2,68 (1,10-6,55)

0,030

28/38,9

17/39,5

1,02 (0,47-2,23)

0,945

41/39,0

4/40,0

1,04 (0,28-3,91)

0,953

Income (minimum wage)

≥ 3

30/26,1

22/24,7

8/30,8

1,0

19/26,4

11/25,6

1,0

27/25,7

3/30,0

1,0

< 3

85/73,9

67/75,3

18/69,2

0,73 (0,28-1,93)

0,537

53/73,6

32/74,4

1,04 (0,44-2,47)

0,924

78/74,3

7/70,0

0,80 (0,19-3,35)

0,768

Alcohol consumption

No

84/73

65/73,0

19/73,1

1,0

52/72,2

32/72,7

1,0

79/75,2

5/50,0

1,0

Yes

31/27

24/27,0

7/26,9

0,99 (0,37-2,67)

0,996

20/27,8

11/27,3

0,89 (0,38-2,11)

0,797

26/24,8

5/50,0

3,03 (0,81-11,33)

0,098

Smoking

No

106/92,2

82/92,1

24/92,3

1,0

70/97,2

36/83,7

1,0

99/94,3

7/70,0

1,0

Yes

9/7,8

7/7,9

2/7,7

0,97 (0,19-5,01)

0,977

2/2,8

7/16,3

6,8 (1,34-34,46)

0,020

6/5,7

3/30,0

7,07 (1,45-34,46)

0,015

Note: CI95% - 95% confidence interval; Mod- Moderate cardiovascular risk; ∞- Infinite. Source: Study data

 

    Table 2 presents the distribution of patients regarding AIDS diagnosis, time since HIV diagnosis, and time on ART use, as well as the association of these variables with the presence of MetS, lipodystrophy, and CVR. It is noteworthy that lipodystrophy was associated with time on ART use ≥30 months (p<0.001). The association of the variables in Table 2 with dyslipidemia did not reach significance (p>0.05), data not shown.

 

Metabolic Syndrome

Lipodystrophy

Cardiovascular risk

All

No

Yes

OR

p

No

Yes

OR

p

Low

Mod

OR

p

Variables

n/%

n/%

n/%

CI95%

n/%

n/%

CI95%

n/%

n/%

CI95%

AIDS diagnosis

No

53/46,1

38/42,7

15/57,7

1,0

32/44,4

21/48,8

1,0

48/45,7

5/50,0

1,0

Yes

62/53,9

51/57,3

11/42,3

0,54 (0,23-1,32)

0,180

40/55,6

22/51,2

0,83 (0,39-1,79)

0,647

57/54,3

5/50,0

0,84 (0,23-3,08)

0,795

Time of diagnosis of HIV (months)

< 40

56/48,7

47/52,8

9/34,6

1,0

40/55,6

16/34,0

1,0

52/49,5

4/40,0

1,0

≥ 40

59/51,3

42/47,2

17/65,4

2,11 (0,85-5,25)

0,106

32/44,4

27/66,0

2,10 (0,97-4,57)

0,058

53/50,5

6/60,0

1,47 (0,39-5,52)

0,566

Time of use of antiretroviral therapy (months)

< 30

60/52,2

50/56,2

10/38,5

1,0

47/65,3

13/30,2

1,0

57/54,3

3/30,0

1,0

≥ 30

55/47,8

39/43,8

16/61,5

2,05 (0,84-5,02)

0,115

25/34,7

30/69,8

4,33 (1,93-9,77)

<0,001

48/45,7

7/70,0

2,77 (0,68-11,30)

0,155

Note: CI95% - 95% confidence interval. Source: Study data

 

    Table 3 shows the distribution of participants regarding abdominal circumference, body mass index, glucose, triglycerides, total cholesterol, LDL-c, HDL-c, and blood pressure is presented, as well as the association of these variables with MetS, lipodystrophy, and CVR. The presence of MetS was associated with increased abdominal circumference (p<0.001), elevated body mass index (p=0.004), elevated glucose (p=0.004), elevated LDL-c (p=0.002), low HDL-c (p=0.003), and elevated blood pressure (p<0.001). Lipodystrophy was associated with alterations in triglycerides (p=0.001), and total cholesterol (p=0,002). Meanwhile, alterations in glucose (p=0.037), and triglycerides (p=0.035) were associated with moderate CVR in PLHIV. It should be noted that dyslipidemia was not significantly associated with the variables in Table 3 (p>0.05), data not shown.

 

Metabolic Syndrome

Lipodystrophy

Cardiovascular risk

All

No

Yes

OR

p

No

Yes

OR

p

Low

Mod

OR

p

Variables

n/%

n/%

n/%

CI95%

n/%

n/%

CI95%

n/%

n/%

CI95%

Abdominal circumference

Adequate

91/79,1

81/91,0

10/38,5

1,0

61/84,7

30/69,8

1,0

84/80,0

7/70,0

1,0

High

24/20,9

8/9,0

16/61,5

16,2 (5,54-47,38)

<0,001

11/15,3

13/30,2

2,40 (0,96-6,0)

0,060

21/20,0

3/30,0

1,71 (0,41-7,20)

0,461

Body mass index

Normal

65/59,1

56/66,7

9/34,6

1,0

43/63,2

22/52,4

1,0

61/61,0

4/40,0

1,0

High

45/40,9

8/33,3

17/65,42

3,77 (1,50-9,54)

0,004

25/36,8

20/47,6

1,56 (0,72-3,41)

0,261

39/39,0

6/60,0

2,34 (0,62-8,85)

0,208

Glucose

Adequate

97/84,3

80/89,9

17/65,4

1,0

64/88,9

33/76,7

1,0

91/86,7

6/60,0

1,0

High

18/15,7

9/10,1

9/34,6

4,7 (1,63-13,61)

0,004

8/11,1

10/23,3

2,42 (0,87-6,72)

0,088

14/13,3

4/40,0

4,33 (1,09-17,31)

0,037

Triglycerides

Adequate

55/47,8

55/61,8

0/0

1,0

43/59,7

12/27,9

1,0

54/51,4

1/10,0

1,0

High

60/52,2

34/38,2

26/100

56084,18 (0-∞)

0,621

29/40,3

31/72,1

3,83 (1,69-8,66)

0,001

51/48,6

9/90,0

9,52 (1,17-77,91)

0,035

Total cholesterol

Adequate

81/70,4

66/74,2

15/57,7

1,0

58/80,6

23/53,5

1,0

75/71,4

6/60,0

1,0

High

34/29,6

23/25,8

11/42,3

2,10 (0,85-5,23)

0,109

14/19,4

20/46,5

3,60 (1,56-8,32)

0,002

30/28,6

4/40,00

1,66 (0,44-6,33)

0,453

LDL-c

Adequate

101/91,8

84/96,6

17/65,4

1,0

64/91,4

37/92,5

1,0

93/91,2

8/100

1,0

High

9/8,2

3/3,4

6/34,6

9,88 (2,25-43,44)

0,002

6/8,6

3/7,5

0,86 (0,20-3,66)

0,843

9/8,8

0/0

0 (0-∞)

0,873

HDL-c

Adequate

48/41,7

44/49,4

4/15,4

1,0

27/37,5

21/48,8

1,0

45/42,9

3/30,0

1,0

Low

67/58,3

45/50,6

22/84,6

5,37 (1,71-16,87)

0,003

45/62,5

22/51,2

0,62 (0,29-1,35)

0,234

60/57,1

7/70,0

1,75 (0,43-7,14)

0,435

Blood pressure

Adequate

92/80

83/93,3

9/34,6

1,0

59/81,9

33/76,7

1,0

86/81,9

6/60,0

1,0

High

23/20

6/6,7

17/65,4

26,12 (8,21-83,13)

<0,001

13/18,1

10/23,3

1,37 (0,54-3,48)

0,500

19/18,1

4/40,0

3,01 (0,78-11,75)

0,111

Note: CI95% - 95% confidence interval; ∞ - Infinite; HDL-c – High-density lipoprotein; LDL-c – Low-density lipoprotein. Source: Study data

 

    Table 4 presents the association between MetS, dyslipidemia, lipodystrophy, and CVR in PLHIV. An association was observed only between moderate CVR and the presence of MetS (p=0.040), and lipodystrophy (p=0.010).

 

	Metabolic Syndrome				Dyslipidemia				Lipodystrophy
	No	Yes	OR		No	Yes	OR		No	Yes	OR
Variables	n/%	n/%	CI95%	p	n/%	n/%	CI95%	p	n/%	n/%	CI95%	p
Cardiovascular risk
Low	84/94,4	21/80,8	1,0		20/95,2	85/90,4	1,0		70/97,2	35/81,4	1,0
Moderate	5/5,6	5/19,2	4,0 (1,06-15,10)	0,040	1/4,8	9/9,6	2,11 (0,25-17,69)	0,488	2/2,8	8/18,6	8,0 (1,61-39,69)	0,010
Lipodystrophy
No	60/67,4	12/46,2	1,0		15/71,4	57/60,6	1,0		--	--	--	--
Yes	29/32,6	14/53,8	2,41 (0,99-5,87)	0,052	6/28,6	37/39,4	1,62 (0,58-4,56)	0,358	--	--	--	--
Dyslipidemia
No	21/23,6	0/0	1,0		--	--	--	--	--	--	--	--
Yes	68/76,4	26/100	28042,09 (0-∞)	0,775	--	--	--	--	--	--	--	--

Note: CI95% - 95% confidence interval; ∞ - Infinite. Source: Study data

 

Discussion 

 

    According to the data presented, age, marital status, smoking, time since diagnosis of HIV infection, time on ART use, AIDS diagnosis, abdominal obesity, overweight/obesity, and altered values for glucose, triglycerides, total cholesterol, LDL-c, HDL-c, and blood pressure were associated with at least one of the conditions analyzed in the present study.

 

    An association of age ≥40 years with the presence of MetS and lipodystrophy was observed, as well as of longer time on ART use with lipodystrophy in the present study. The literature already demonstrates a relationship of lipodystrophy with time of HIV exposure and chronic use of ART (Alikhani et al., 2019; Heath et al., 2001; Segatto et al., 2011). In addition, the systematic review by Cabrera et al. (2021) found that the use of protease inhibitors, prolonged use of ART, and time of HIV infection were associated with increased prevalence of dyslipidemia. Still according to the literature, MetS in PLHIV has been shown to be associated with older age and female sex (Sun, & Ren, 2012; Cabrera et al., 2021). However, HIV itself has specific characteristics that increase the prevalence of MetS regardless of sex (Nguyen et al., 2016). It should be noted that in the present study, no association of sex with the presence of MetS, lipodystrophy, CVR, and dyslipidemia was observed.

 

    Patients with MetS, lipodystrophy, and moderate CVR had higher values for age than PLHIV without these conditions. Jericó et al. (2005) found that among PLHIV, MetS predominated in those of older age, and Njelekela et al. (2017) demonstrated a higher prevalence of lipodystrophy in older PLHIV. Furthermore, aging promotes a functional decline in most organ systems, including the cardiovascular system, which favors the increase of CVR. (Boccara, 2017)

 

    In this context, PLHIV with lipodystrophy showed a longer time since diagnosis of HIV compared to those without lipodystrophy. In the study by Dos Santos et al. (2018), longer time since diagnosis was related to the development of lipodystrophy. Long periods of HIV and ART exposure can be considered risk factors for the development of lipodystrophy (Koethe et al., 2020), as well as the type of antiretroviral may contribute to the development of lipodystrophy, such as nucleoside reverse transcriptase inhibitors (NRTIs), especially stavudine (d4T) (Phan et al., 2012) and zidovudine (AZT), which are frequently associated with lipoatrophy (Finkelstein et al., 2015). In addition, prolonged use of ART contributes to the development of MetS (Møller et al., 2020), as observed in the present study, in which PLHIV with MetS had longer ART use compared to those without MetS. (Costa et al., 2019; Araujo et al., 2025)

 

    Although ART has reduced AIDS-related mortality (Dourado et al., 2006), other comorbidities stand out in the lives of PLHIV (Bica et al., 2001), such as cardiovascular diseases (Hanna et al., 2016). Despite no association being found between CVR and time since diagnosis or ART use, it is seen that ART, despite reducing chronic systemic inflammation, can contribute to dyslipidemia, lipodystrophy, and insulin resistance, thereby increasing CVR in PLHIV (Ballocca et al., 2016). Furthermore, a study conducted in Australia with PLHIV found that abacavir use was associated with increased risk of coronary heart disease. (Trevillyan, Cheng, & Hoy, 2013)

 

    The study by Kim et al. (2006), conducted with 3,142 individuals, indicated that there was a strong correlation between the presence of MetS in one spouse and the likelihood of the other spouse also presenting the condition. This suggests that shared environmental factors play a significant role in the development of MetS. In addition, marital stress levels were associated with a greater likelihood of women meeting MetS criteria, but not men (Whisman, Uebelacker, & Settles, 2010). In the present study, an association between having a partner and MetS was observed.

 

    Smoking is a well-established CVR factor in the literature (Teixeira et al., 2021; Menezes et al., 2021; Moura et al., 2021; Silva et al., 2020; Petoumenos et al., 2011; Helleberg et al., 2013). Furthermore, it is noted that the prevalence of smoking in PLHIV is higher than in people without HIV infection (Johnston et al., 2021). The smoking habit generates greater oxidation and glycation, which intensifies cellular aging, atherogenesis, the formation of dysfunctional lipoproteins, reduces HDL-c levels, and increases serum concentrations of VLDL-c and LDL-c compared to non-smokers (Park, Shin, & Cho, 2014; Craig, Palomaki, & Haddow, 1989). It is noteworthy that smoking cessation has been described as a therapeutic approach for lipodystrophy in PLHIV (Garcia-Viejo, Hernández, & Martínez, 2001). In the present study, both CVR and lipodystrophy were associated with smoking.

 

    Abdominal adiposity is closely related to insulin resistance, hyperglycemia, dyslipidemia, the development of hypertension, and pro-inflammatory states, all risk factors for the development of MetS (Spinler, 2006). In this context, the present study observed that both abdominal circumference and elevated BMI were associated with the presence of MetS. Thus, studies involving PLHIV have demonstrated this association of MetS with overweight (Pereira et al., 2024) and abdominal obesity. (Watanabe et al., 2022; Pereira et al., 2024)

In addition, insulin resistance, which is related to elevated blood glucose and diabetes mellitus, is a central component of MetS and is linked to several cardiometabolic abnormalities that increase CVR (Ciolac, & Guimarães, 2004). In PLHIV with lipodystrophy, insulin resistance is common and is associated with hypertriglyceridemia and hepatic steatosis, both risk factors for cardiovascular disease (Sekizkardes et al., 2020). Hypertriglyceridemia and insulin resistance are common in PLHIV using ART, increasing CVR risk (Addy et al., 2003). In the present study, an association was observed between lipodystrophy and CVR with hypertriglyceridemia, and between hypercholesterolemia and lipodystrophy. On the other hand, low HDL-c and elevated LDL-c were associated with MetS. Thus, early evaluation of these metabolic parameters (Moraes et al., 2009) is of utmost importance for better prevention and health promotion in PLHIV.

 

    In the study by Zanuzzi et al. (2020), PLHIV showed a high prevalence of hypertension (40%) and MetS (38.5%), especially among those using ART. It is also noteworthy that treatment duration was positively associated with both conditions. Thus, PLHIV on ART use presented higher systolic and diastolic blood pressure compared to those not in treatment, this association being indicated by the fact that hypertension is one of the key components of MetS (Grundy et al., 2005), as well as for higher CVR (Bazmandegan et al., 2023; Bloomfield et al., 2011), regardless of the presence of HIV infection (Jericó et al., 2005). The mechanisms usually associated with elevated blood pressure are abdominal obesity, insulin resistance, oxidative stress, endothelial dysfunction, and increased inflammatory mediators. (Yanai et al., 2008)

 

    The relationship between MetS and CVR exists because they share common risk factors, such as overweight/obesity, abdominal obesity, hypertension, hypertriglyceridemia, hypercholesterolemia, elevated blood glucose, and low HDL-c (Meirelles, 2014). In addition, MetS is also an important CVR factor (Rodrigues, & Toigo, 2015), since the low-grade chronic inflammation related to HIV may not be fully predicted by traditional risk scores, such as the Framingham Risk Score. (Nix, & Tien, 2014)

 

    Lipodystrophy in PLHIV generates metabolic and hormonal changes that increase CVR (Sacilotto et al., 2021). Thus, lipodystrophy in this population, especially when associated with ART use, is strongly related to insulin resistance (Estrada et al., 2006; Grinspoon, 2001), and dyslipidemia (Mikhail, 2003), due to changes in fat distribution, i.e., loss of subcutaneous fat and increased visceral adiposity. (Estrada et al., 2006; Grinspoon, 2001)

 

    Although the study did not observe an association between lipodystrophy and MetS, it is observed that lipodystrophy can generate insulin resistance (Estrada et al., 2006; Grinspoon, 2001), and dyslipidemia (Mikhail, 2003), which are factors associated with MetS (Grundy et al., 2005; Meirelles, 2014). In this context, the importance of comprehensive health monitoring of PLHIV and of prevention and health promotion actions is highlighted.

 

    Among the limitations of the study, the cross-sectional model and the lack of adjustment for confounding factors in the logistic regression analysis limit the interpretation of results and the generalization of findings. The absence of longitudinal follow-up does not allow causality to be established between the findings. However, the study is highly relevant as it provides novel data on the metabolic health of PLHIV in the municipality of Santarém and surrounding region, contributing to the understanding of regional particularities and the formulation of more effective health strategies for prevention and treatment, as well as serving as a guide for future research on the subject.

 

Conclusion 

 

    In line with the aims of this manuscript, it can be concluded that PLHIV receiving care in the interior of Pará present a concerning prevalence of dyslipidemia, lipodystrophy, and MetS. Although moderate CVR was observed at a relatively low frequency, it should not be overlooked. In this context, factors such as older age, smoking, longer duration of ART use, and altered glucose and triglyceride levels were associated with these conditions. The regional data obtained, including the high prevalence of dyslipidemia and alterations in body composition, underscore the need for comprehensive clinical monitoring and more effective multiprofessional interventions for PLHIV.

 

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