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Increasing Obesity in Treated Female HIV Patients from Sub-Saharan Africa: Potential Causes and Possible Targets for Intervention.

McCormick CL, Francis AM, Iliffe K, Webb H, Douch CJ, Pakianathan M, Macallan DC - Front Immunol (2014)

Bottom Line: Clinical factors strongly associated with obesity included female gender, black African ethnicity, non-smoking, age, and CD4 count (all P < 0.001); greater duration of cART did not predict obesity.Investigating body-weight perception, we found that weight and adiposity were underestimated by obese subjects, who showed a greater disparity between perceived and actual adiposity (P < 0.001).Although multifactorial, body-weight perception represents a potential target for intervention.

View Article: PubMed Central - PubMed

Affiliation: Clinical Infection Unit & Department of Genitourinary Medicine, St. George's Healthcare NHS Trust , London , UK.

ABSTRACT

Objectives: To investigate changing nutritional demographics of treated HIV-1-infected patients and explore causes of obesity, particularly in women of African origin.

Methods: We prospectively reviewed nutritional demographics of clinic attenders at an urban European HIV clinic during four one-month periods at three-yearly intervals (2001, 2004, 2007, and 2010) and in two consecutive whole-year reviews (2010-2011 and 2011-2012). Risk-factors for obesity were assessed by multiple linear regression. A sub-study of 50 HIV-positive African female patients investigated body-size/shape perception using numerical, verbal, and pictorial cues.

Results: We found a dramatic rise in the prevalence of obesity (BMI > 30 kg/m(2)), from 8.5 (2001) to 28% (2011-2012) for all clinic attenders, of whom 86% were on antiretroviral treatment. Women of African origin were most affected, 49% being obese, with a further 32% overweight (BMI 25-30 kg/m(2)) in 2012. Clinical factors strongly associated with obesity included female gender, black African ethnicity, non-smoking, age, and CD4 count (all P < 0.001); greater duration of cART did not predict obesity. Individual weight-time trends mostly showed slow long-term progressive weight gain. Investigating body-weight perception, we found that weight and adiposity were underestimated by obese subjects, who showed a greater disparity between perceived and actual adiposity (P < 0.001). Obese subjects targeted more obese target "ideal" body shapes (P < 0.01), but were less satisfied with their body shape overall (P = 0.02).

Conclusion: Seropositive African women on antiretroviral treatment are at heightened risk of obesity. Although multifactorial, body-weight perception represents a potential target for intervention.

No MeSH data available.


Related in: MedlinePlus

Comparison of nutritional demographics in HIV-clinic attenders to the general population. Distribution between different nutritional status groups for HIV-positive clinic attenders (solid bars) versus the general population (open and hatched bars). (A) Men, general population (open), black African men in general population (shaded), HIV-positive Caucasian males (solid bars), and (B) women, general population (open bars), black African women in general population (shaded), HIV-positive black African women (solid bars). Comparative data (HSE), expressed as percentage of each ethnic group, are from the Health Survey of England (n = 11,022; 5,443 classified by ethnic group, including 629 black Africans) (38). Note, HSE data did not give subgroup data for white Caucasian populations and were not subdivided at 20 kg/m2, so “underweight” and “normal” weight clinic attenders have been conflated to demonstrate comparable data.
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Figure 4: Comparison of nutritional demographics in HIV-clinic attenders to the general population. Distribution between different nutritional status groups for HIV-positive clinic attenders (solid bars) versus the general population (open and hatched bars). (A) Men, general population (open), black African men in general population (shaded), HIV-positive Caucasian males (solid bars), and (B) women, general population (open bars), black African women in general population (shaded), HIV-positive black African women (solid bars). Comparative data (HSE), expressed as percentage of each ethnic group, are from the Health Survey of England (n = 11,022; 5,443 classified by ethnic group, including 629 black Africans) (38). Note, HSE data did not give subgroup data for white Caucasian populations and were not subdivided at 20 kg/m2, so “underweight” and “normal” weight clinic attenders have been conflated to demonstrate comparable data.

Mentions: An alternative hypothesis is that HIV-positive patients are simply “normalizing” to the nutritional demographics of their background population. We therefore compared our observations with the most recent comparable ethnically categorized data, the “2004 Health Survey for England: Health of Ethnic Minorities” (HSE) (38) which includes BMI data on 11,022 UK residents, 5,443 classified by ethnicity. Although this national survey reported high obesity rates in black African women (38% BMI > 30 kg/m2, versus 23% in the general female population, with a further 31% overweight), our obesity rates exceeded these values by about 10% (Figure 4A). Conversely men in our HIV-positive cohort had lower levels of obesity than the general population (Figure 4B). In men, black African ethnicity did not appear to favor obesity, either in our cohort (P = 0.56), or in HSE, where obesity rates in black African men were lower than the general population (17 versus 22%) (38). It might be argued that data from 2004 do not represent a sufficiently contemporaneous comparator; however, more recent national obesity data categorized by ethnicity could not be identified. In order to compensate for this time difference, we compared obesity rates in women in England of all ethnicities in 2004 with those in 2011. Rates increased from 23 to 26% (43) suggesting that time-trends in obesity in the general population, whilst increasing, are unlikely to explain the increase prevalence of obesity seen in our clinic cohort.


Increasing Obesity in Treated Female HIV Patients from Sub-Saharan Africa: Potential Causes and Possible Targets for Intervention.

McCormick CL, Francis AM, Iliffe K, Webb H, Douch CJ, Pakianathan M, Macallan DC - Front Immunol (2014)

Comparison of nutritional demographics in HIV-clinic attenders to the general population. Distribution between different nutritional status groups for HIV-positive clinic attenders (solid bars) versus the general population (open and hatched bars). (A) Men, general population (open), black African men in general population (shaded), HIV-positive Caucasian males (solid bars), and (B) women, general population (open bars), black African women in general population (shaded), HIV-positive black African women (solid bars). Comparative data (HSE), expressed as percentage of each ethnic group, are from the Health Survey of England (n = 11,022; 5,443 classified by ethnic group, including 629 black Africans) (38). Note, HSE data did not give subgroup data for white Caucasian populations and were not subdivided at 20 kg/m2, so “underweight” and “normal” weight clinic attenders have been conflated to demonstrate comparable data.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230180&req=5

Figure 4: Comparison of nutritional demographics in HIV-clinic attenders to the general population. Distribution between different nutritional status groups for HIV-positive clinic attenders (solid bars) versus the general population (open and hatched bars). (A) Men, general population (open), black African men in general population (shaded), HIV-positive Caucasian males (solid bars), and (B) women, general population (open bars), black African women in general population (shaded), HIV-positive black African women (solid bars). Comparative data (HSE), expressed as percentage of each ethnic group, are from the Health Survey of England (n = 11,022; 5,443 classified by ethnic group, including 629 black Africans) (38). Note, HSE data did not give subgroup data for white Caucasian populations and were not subdivided at 20 kg/m2, so “underweight” and “normal” weight clinic attenders have been conflated to demonstrate comparable data.
Mentions: An alternative hypothesis is that HIV-positive patients are simply “normalizing” to the nutritional demographics of their background population. We therefore compared our observations with the most recent comparable ethnically categorized data, the “2004 Health Survey for England: Health of Ethnic Minorities” (HSE) (38) which includes BMI data on 11,022 UK residents, 5,443 classified by ethnicity. Although this national survey reported high obesity rates in black African women (38% BMI > 30 kg/m2, versus 23% in the general female population, with a further 31% overweight), our obesity rates exceeded these values by about 10% (Figure 4A). Conversely men in our HIV-positive cohort had lower levels of obesity than the general population (Figure 4B). In men, black African ethnicity did not appear to favor obesity, either in our cohort (P = 0.56), or in HSE, where obesity rates in black African men were lower than the general population (17 versus 22%) (38). It might be argued that data from 2004 do not represent a sufficiently contemporaneous comparator; however, more recent national obesity data categorized by ethnicity could not be identified. In order to compensate for this time difference, we compared obesity rates in women in England of all ethnicities in 2004 with those in 2011. Rates increased from 23 to 26% (43) suggesting that time-trends in obesity in the general population, whilst increasing, are unlikely to explain the increase prevalence of obesity seen in our clinic cohort.

Bottom Line: Clinical factors strongly associated with obesity included female gender, black African ethnicity, non-smoking, age, and CD4 count (all P < 0.001); greater duration of cART did not predict obesity.Investigating body-weight perception, we found that weight and adiposity were underestimated by obese subjects, who showed a greater disparity between perceived and actual adiposity (P < 0.001).Although multifactorial, body-weight perception represents a potential target for intervention.

View Article: PubMed Central - PubMed

Affiliation: Clinical Infection Unit & Department of Genitourinary Medicine, St. George's Healthcare NHS Trust , London , UK.

ABSTRACT

Objectives: To investigate changing nutritional demographics of treated HIV-1-infected patients and explore causes of obesity, particularly in women of African origin.

Methods: We prospectively reviewed nutritional demographics of clinic attenders at an urban European HIV clinic during four one-month periods at three-yearly intervals (2001, 2004, 2007, and 2010) and in two consecutive whole-year reviews (2010-2011 and 2011-2012). Risk-factors for obesity were assessed by multiple linear regression. A sub-study of 50 HIV-positive African female patients investigated body-size/shape perception using numerical, verbal, and pictorial cues.

Results: We found a dramatic rise in the prevalence of obesity (BMI > 30 kg/m(2)), from 8.5 (2001) to 28% (2011-2012) for all clinic attenders, of whom 86% were on antiretroviral treatment. Women of African origin were most affected, 49% being obese, with a further 32% overweight (BMI 25-30 kg/m(2)) in 2012. Clinical factors strongly associated with obesity included female gender, black African ethnicity, non-smoking, age, and CD4 count (all P < 0.001); greater duration of cART did not predict obesity. Individual weight-time trends mostly showed slow long-term progressive weight gain. Investigating body-weight perception, we found that weight and adiposity were underestimated by obese subjects, who showed a greater disparity between perceived and actual adiposity (P < 0.001). Obese subjects targeted more obese target "ideal" body shapes (P < 0.01), but were less satisfied with their body shape overall (P = 0.02).

Conclusion: Seropositive African women on antiretroviral treatment are at heightened risk of obesity. Although multifactorial, body-weight perception represents a potential target for intervention.

No MeSH data available.


Related in: MedlinePlus