Hostname: page-component-7479d7b7d-t6hkb Total loading time: 0 Render date: 2024-07-12T23:31:46.880Z Has data issue: false hasContentIssue false

A nutrition education programme improves quality of life but not anthropometric status of adults living with HIV in Abeokuta, Nigeria

Published online by Cambridge University Press:  14 May 2019

Temitope K Bello*
Affiliation:
Department of Human Nutrition, University of Pretoria, Private Bag X323, Pretoria 0001, South Africa
Gerda J Gericke
Affiliation:
Department of Human Nutrition, University of Pretoria, Private Bag X323, Pretoria 0001, South Africa
Una E Maclntyre
Affiliation:
Department of Human Nutrition, University of Pretoria, Private Bag X323, Pretoria 0001, South Africa
Piet Becker
Affiliation:
Research Office, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa
*
*Corresponding author: Email tkbello2070@gmail.com
Rights & Permissions [Opens in a new window]

Abstract

Objective:

The focus of interventions for adults living with HIV (ALH) in Nigeria has been mostly on prevention and provision of antiretroviral therapy (ART) with little consideration to nutrition-related matters. Therefore, the present study aimed to improve the quality of life (QoL) and anthropometric status of ALH in Abeokuta, Nigeria.

Design:

A quasi-experimental design where 200 conveniently selected participants were stratified by gender and duration on ART. The intervention group (n 100) received the nutrition education programme (NEP) for 12 weeks. The control group received a brochure on nutrition guidelines for ALH. Socio-biographical information, QoL and anthropometric status were assessed using previously validated questionnaires and standard techniques at baseline, week 12 and week 24. Generalised least squares (GLS) regression analysis was used for group comparisons. Anthropometric status was summarised by gender.

Setting:

Two tertiary hospitals in Abeokuta, Nigeria.

Participants:

ALH.

Results:

The NEP led to significant improvement in the physical functioning (week 12 and 24: P < 0·01), role limitation due to physical health (week 12: P = 0·01; week 24: P = 0·002) and pain (week 12: P = 0·01) constructs of the QoL of the intervention group compared with the control group. There was no significant difference (P = 0·07) between the mean weights of the two groups at baseline.

Conclusions:

There was a significant improvement at week 12 and week 24 in the QoL of the intervention participants. The results indicated that a tailored NEP could make a positive contribution to the management of ALH.

Type
Research paper
Copyright
© The Authors 2019 

Infection caused by HIV remains a public health issue due to it psychological, economic, social and clinical implications(1). HIV/AIDS is still one of the leading causes of death in Africa despite millions of dollars being spent on prevention, control and provision of antiretroviral therapy (ART). As at the end of 2016, an estimated one million deaths occurred globally from HIV/AIDS-related illnesses of which 16 % occurred in Nigeria(1). The pace of decline in the rate of death resulting from HIV/AIDS-related illnesses is too slow to reduce its societal effects. Hence, there is a need for the consideration of other types of health-care management such as appropriate nutrition support.

Research has shown that appropriate nutrition education (NE) in conjunction with the provision of ART and nutritional supplements is essential for the reduction of HIV-related morbidity and mortality rates(Reference Grobler, Siegfried and Visser2). Various studies have confirmed that healthy dietary choices are vital for the improved quality of life (QoL) and anthropometric status of adults living with HIV (ALH). Adequate nutrition is needed by HIV-infected individuals to maintain a healthy life, to strengthen immunity and resistance against opportunistic infections, and to reduce muscle wasting(Reference Piwoz and Preble3). For an improved QoL, weight gain and its maintenance, foods high in energy and protein are needed(Reference Grobler, Siegfried and Visser2). This may be due to the complex and close relationship that exists between the virus’ life cycle and nutrition as established by Semba and Tang(Reference Semba and Tang4).

Change in weight is common among ALH and is a good indicator of disease progression(Reference Mangili, Murman and Zampini5Reference Wanke, Silva and Knox8). The study of Carbonnel et al. (Reference Carbonnel, Beaugerie and Rached9) confirmed that damage to the lining of the gastrointestinal tract of seventy-nine weight-losing ALH was associated with depletion of micronutrients caused by a reduction in the absorption of nutrients. Consequently, HIV can cause weight loss and wasting among ALH, thereby altering their QoL.

Previous nutrition intervention studies confirmed that dietary supplements in conjunction with NE can lead to an improved nutritional status and QoL of ALH(Reference Ogalha, Luz and Sampaio10Reference McDermott, Shevitz and Must14). Unfortunately, in Nigeria, where 3·2 million of the 36·7 million people globally who are infected with HIV reside, little attention has been given to HIV and nutrition-related matters.

The aim of the present study was to implement a theory-guided nutrition education programme (NEP) for 12 weeks and to evaluate its effects on the primary (QoL) and secondary (anthropometric status) outcomes of ALH in the intervention group in comparison to those in the control group at week 12 and week 24. The constructs of the Social Cognitive Theory and the Health Belief Model, which have revealed success not only for fruit and vegetable consumption(Reference Thomson and Ravia15), but also in HIV prevention, smoking cessation(Reference Wiefferink, Peters and Hoekstra16) and other health-related behaviours, were incorporated in the NEP.

It was hypothesised that the intervention group would show a significant improvement in their QoL and anthropometric status compared with the control group at week 12 and week 24 (post-intervention).

Methodology

Research setting

The present study was conducted at two tertiary government hospitals in the urban setting of Abeokuta South, one of the twenty local government areas of Ogun State. The hospitals were selected because they were the only government hospitals in Abeokuta to provide free ART under the Nigerian Government’s National Antiretroviral Drug Access Programme. Approximately 1400 ALH at each hospital received free ART which they collected on a monthly basis. A needs assessment, conducted prior to the current study to determine the NE needs of the ALH at the two hospitals, showed the ALH attending the two hospitals to have similar demographic and anthropometric characteristics (P > 0·05)(Reference Bello17).

Study design

The present study was designed to evaluate the NEP’s effects on QoL and anthropometric status of ALH using a quasi-experimental design.

Sampling and sample size

A simple randomisation technique (tossing of a coin by a person not involved in the study) was used to randomise the two hospitals into intervention and control sites. Convenience sampling was used to recruit 200 ALH who met the inclusion criteria and consented to participate in the study. The sample size was determined from the results of the prior needs assessment(Reference Bello17) where 169 of the 243 participants answered all the Short Form (SF)-36 QoL questions with a mean of 65 (sd 14·7) %.

A sample of at least fifty participants per group would have 90 % power to detect an improvement of 10 % points in the QoL construct of scores of the intervention group. Therefore, a sample of at least 100 participants for each group was required to also allow for a 50 % dropout. The participants were stratified according to the duration on ART (0–<24 months and >24 months) and gender. Stratification for gender was based on the results of the needs assessment of 25 % male and 75 % female(Reference Bello17).

Participants were conveniently recruited with the assistance of the staff at the Centres for Public Health of the two selected hospitals. Participants were considered ineligible if any one of the following criteria was met: (i) <18 years or ≥50 years; (ii) unable to provide logical answers to questions asked on personal characteristics and family history; (iii) being on ART for ≥5 years(Reference Mwamburi, Gerrior and Wilson11); (iv) inability to attend 12 weeks of NEP and reassessment at 12 weeks post-implementation; (v) refusal to give both written and oral consent; (vi) pregnant or breast-feeding; and/or (vii) presence of active HIV-related opportunistic health conditions (tuberculosis, cancer, liver diseases) as documented on their medical records(Reference Nadhiroh18). The upper cut-offs for age and duration of ART were set to limit possible age- and ART-related co-morbidities. In addition, older age is often associated with reluctance to modify behaviour(Reference Derenne and Baron19).

Intervention

The intervention entailed the implementation of the NEP at the intervention hospital.

The NEP was developed by the authors to address the NE needs identified by the prior needs assessment within the context of the study sample(Reference Bello17). Selected constructs of the Social Cognitive Theory and the Health Belief Model were incorporated to enhance learning and positive changes in attitudes and dietary behaviour in order to improve QoL and anthropometric status. The NEP addressed the importance of nutrition in improving QoL and anthropometric status, and provided guidance to overcome the barriers to healthy eating to enable the intervention group to adopt the ideal behaviours(Reference Contento20Reference Sahyoun, Pratt and Anderson22). The educational objectives and curriculum of the NEP are given in Table 1.

Table 1 Nutrition education programme (NEP) curriculum(Reference Bello17)

QoL, quality of life.

The intervention participants received NE materials and the 12-week NEP. The intervention participants were allocated to one of seven groups on a first-come-first-served basis with a maximum of fifteen and a minimum of thirteen participants per group. The NEP was implemented from November 2015 to May 2016. The NEP consisted of: (i) an NE trainer’s manual which covered 12 weeks of group education for at least one hour per session; (ii) a participant’s workbook to be used at home by the intervention participants to revise the topics taught, this was to enhance participants’ confidence in performing acquired knowledge and skills; (iii) flipcharts for pictorial demonstration, thus participants compiled evidence through visual literacy; and (iv) a brochure summarising the NEP for self-learning. The researcher, a registered dietitian and fluent in the local language, facilitated the NEP and was assisted by trained research assistants.

Implementation at the control hospital

The control group participants received only the brochure.

Data collection

Quality of life

The primary outcome (QoL) was assessed at baseline, week 12 and week 24 in both the intervention and control groups using the SF-36 QoL questionnaire(Reference Han, Pulling and Telke23Reference Wagner, Gandek and Aaronson26). The questionnaire had previously been validated among ALH in Italy(Reference Arpinelli, Visona and Bruno27) and Taiwan(Reference Hsiung, Fang and Chang28). This questionnaire was pre-tested during the needs assessment among ALH at the two hospitals(Reference Bello17).

Anthropometric assessment

Participants’ anthropometric data (weight, height, mid-upper arm circumference (MUAC) and triceps skinfold (TSF)) were obtained by the trained research assistants using standard techniques(Reference Hsiung, Fang and Chang28, Reference Gibson29). All the measurements were done twice(Reference Gibson29, 30). A portable stadiometer (Leicester height measure; Invicta Plastics Limited, Leicester, UK) was used for the height measurement to the nearest 0·1 cm, and a portable calibrated electronic body scale (Seca flat weighing scale, four batteries type; Seca GmbH & Co. KG, Hamburg, Germany) was used for the weight measurements to the nearest 0·1 kg.

MUAC was measured according to standard procedures by using a non-stretchable tape measure. The measurement was recorded to the nearest 0·1 cm(30).

TSF was measured using a Slimglide calliper (ABS Plastics, Johannesburg, South Africa) according to standard techniques. Two measurements were taken per participant and recorded to the nearest 1 mm(Reference Gibson29, 30). The measurements were at least 15 s apart to allow the skinfold site return to normal. The researcher ensured that the zero point coincided with the start of the scale before any measurement was taken.

Compliance with the nutrition education programme

Participant attendance of the NEP was recorded at each session. Participants were reminded via telephone of their NEP sessions (intervention group) and their week 12 and 24 assessments (intervention and control groups).

Data analysis

Data were analysed using the statistical software package Stata release 10 (2007). Data were subjected to the Shapiro–Wilk test for normality. Means and standard deviations, or medians and interquartile ranges, of continuous data were calculated. Frequency and percentage distributions of categorical data were described. The QoL questionnaire was scored using the SF-36 scoring tables(31). All questions were scored on a scale of 0 to 100. A mean percentage score >70 % was considered good, 50–70 % as average or modest, and <50 % as poor(Reference Weiser, Fernandes and Brandson32). The average of the two measurements for all the anthropometric data was used for analyses(Reference Gibson29, 33, Reference Lee and Nieman34). Generalised least squares (GLS) regression analysis was used for group comparison of overall QoL and for the QoL constructs of the intervention and control groups. The QoL and anthropometric outcomes were compared at baseline, week 12 and week 24 using baseline data as covariates. The GLS regression considered missing values, interactions and discrete changes within and between groups from baseline through to week 24. Cronbach’s α was used to test the internal consistency of the QoL constructs. Testing was done at the 0·05 level of significance.

Ethical considerations

The study received approval from the Faculty of Health Science Research Ethics Committee, University of Pretoria, South Africa (number 311/2014) and from the two hospitals (numbers FMCA/470/HREC/2014 and SHA.144/vol. II/97). The procedures set down in the Declaration of Helsinki guidelines were strictly followed. Participants provided written informed consent prior to participation in the study. Participants were reimbursed for their transportation fare immediately after each training session.

Results

The flow of the participants through the study is shown in Fig. 1. In the intervention group, 23 % of the participants who started at baseline dropped out by week 12, and a further 7 % by week 24. In the control group, 28 % were not available at week 12 and a further 10 % at week 24. Of the 200 participants, fifty-one were males, comprising twenty-five in the intervention and twenty-six in the control group (Table 2). The mean age at baseline was 38 years for the intervention and 37 years for the control group. The majority (intervention: 57 %; control: 56 %) of the participants were married. The highest proportion of the participants in both groups had a junior secondary education and above (intervention: 76 %; control: 84 %). The majority of participants were self-employed (traders and contractors) in both the intervention (67 %) and control (58 %) groups. There were no significant differences between the distributions of educational status (P = 0·18) and duration of ART (P = 0·89) of the participants in the two groups. However, the difference between the income distributions of the participants was significant at baseline (P < 0·001).

Fig. 1 Flow of participants through the study

Table 2 Comparison of demographic characteristics between the intervention and control groups at baseline, week 12 and week 24: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

NCE, Nigerian Certificate in Education; HND, Higher National Diploma; SE, self-employment; ART, antiretroviral therapy.

* P < 0·05, **P ≤ 0·01.

P values derived from the t test for continuous variables (age) or Fisher’s test for categorical variables (all others).

Compliance with the nutrition education programme

The extent to which participants followed the dietary advice was measured by the change in the number of food groups consumed (individual dietary diversity score (IDDS)) derived from non-quantified 24 h recalls administered to both the intervention and control groups at baseline, week 12 and week 24. Intervention participants provided feedback on their experience and perceptions of the NEP during an open-ended structured interview on completion of the NEP (week 12)(Reference Bello17).

All NEP sessions were attended by thirty participants while the remainder (n 47) attended at least 50 % or more sessions (Fig. 1). The percentage of intervention participants who achieved IDDS ≥ 5 increased from 41 % at baseline to 67 % at week 24, suggesting compliance with dietary advice. In comparison, the percentage of control participants with IDDS ≥ 5 decreased over the study period from 37 % at baseline to 32 % at week 24. Responses to the open-ended interview at week 12 indicated that participants believed they had benefited from the NEP, specifically mentioning the importance of increasing the variety of foods in their diets(Reference Bello17).

Quality of life

All participants (n 200) completed the QoL questionnaire at baseline. At week 12 (intervention: 77 %; control: 72 %) and week 24 (intervention: 70 %; control: 62 %), most of the participants completed the QoL questionnaire. Table 3 shows the mean percentage construct scores and the mean differences between the intervention and control groups.

Table 3 Differences in mean quality of life (QoL) construct scores (%) between the intervention and control groups at baseline, week 12 and week 24: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

* P < 0·05, **P ≤ 0·01.

Differences in baseline mean of the intervention and control groups derived from ANOVA; P values derived from ANOVA.

Differences in baseline mean (crude mean) and predicted mean at week 12 and week 24 between groups derived from GLS (generalised least squares) random-effects regression taking the missing values into account; P values derived from GLS random-effects regression taking the missing values into account.

The difference in mean physical functioning construct scores between the intervention and the control groups was not significant at baseline (P = 0·24), but was significant at week 12 (P < 0·001) and week 24 (P < 0·001). The mean difference in role limitation due to the physical health construct scores between the intervention and the control groups was not significant at baseline (P = 0·11), but significant at week 12 (P = 0·006) and week 24 (P = 0·002).

Table 4 shows the within-group differences in the QoL construct scores from baseline to weeks 12 and 24. There was a significant improvement (P < 0·001), with an increase of 13 % from baseline to week 12 and 16 % to week 24, in the physical functioning construct score within the intervention group. The changes within the control group showed a non-significant decline of −0·5 % (P = 0·83) at week 12 and −0·6 % (P = 0·83) at week 24 in the physical functioning construct score. The intervention group had a significant increase in score in the role limitation due to physical health construct at week 12 (21 %; P < 0·001) and week 24 (25 %; P < 0·001). There was a decrease of −0·2 % (P = 0·95) within the control group in the role limitation due to physical health construct score at week 12, and an increase of 0·5 % (P = 0·09) at week 24, which were not significant.

Table 4 Differences in quality of life (QoL) mean construct scores (%) within the intervention and control groups from baseline to week 12 and week 24: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

* P < 0·05, **P ≤ 0·01.

Differences in baseline mean (crude mean) and predicted mean at week 12 and week 24 derived from GLS (generalised least squares) random-effects regression taking the missing values into account; P values derived from GLS random-effects regression taking the missing values into account.

There was a significant increase in the role limitation due to emotion construct score at week 12 (16 %; P < 0·001) and week 24 (22 %; P < 0·001) within the intervention group. In contrast, there was a decrease in the role limitation due to emotion construct score within the control group at week 12 (−2·7 %; P = 0·5) and an increase at week 24 (0·3 %; P = 0·94), which were not statistically significant.

Table 5 shows the internal consistency of the QoL questionnaire for the intervention and control groups using the Cronbach α reliability test. Cronbach’s α for the physical functioning of the intervention group was 0·86, and 0·89 for the control group; for the social functioning construct, the Cronbach’s α was low (intervention: 0·42; control: 0·20).

Table 5 Internal consistency of the quality of life (QoL) questionnaire for intervention and control groups: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

Anthropometric status

There were no significant differences in mean weight between the intervention and control groups at baseline (P = 0·19), week 12 (P = 0·17) and week 24 (P = 0·14). It follows that there was no significant differences in mean BMI between the intervention and control groups at baseline (P = 0·20), week 12 (P = 0·19) or week 24 (P = 0·16). At baseline, mean MUAC and TSF of the control group were significantly higher than those of the intervention group (P = 0·033 and P = 0·04, respectively). These significant differences remained at week 12 and, for mean TSF, at week 24 (Table 6).

Table 6 Differences in anthropometric mean values between the intervention and control groups at baseline, week 12 and week 24: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

MUAC, mid-upper arm circumference; TSF, triceps skinfold.

* P < 0·05, **P ≤ 0·01.

Differences in baseline mean of the intervention and control groups derived from ANOVA; P values derived from AVOVA.

Differences in baseline mean (crude mean) and predicted mean at week 12 and week 24 between groups derived from GLS (generalised least squares) random-effects regression taking the missing values into account; P values derived from GLS random-effects regression taking the missing values into account.

Table 7 shows that there were no significant differences in weight status within the intervention and control groups at week 12 (intervention: P = 0·18; control: P = 0·40) and week 24 (intervention: P = 0·08; control: P = 0·06). Similarly, there were no significant differences in MUAC and TSF status within groups at week 12 (MUAC: intervention: P = 0·5; control: P = 0·79; TSF: intervention: P = 0·5; control: P = 0·87) and week 24 (MUAC: intervention: P = 0·15; control: P = 0·35; TSF: intervention: P = 0·31; control: P = 0·69).

Table 7 Differences in anthropometric mean values within the intervention and control groups from baseline to week 12 and week 24: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

MUAC, mid-upper arm circumference; TSF, triceps skinfold.

* P < 0·05, **P ≤ 0·001.

Differences in baseline mean (crude mean) and predicted mean at week 12 and week 24 derived from GLS (generalised least squares) random-effects regression taking the missing values into account, P values derived from GLS random-effects regression taking the missing values into account.

Table 8 shows the anthropometry for the intervention and control groups according to gender from baseline to week 24. The mean BMI of males and females in the control group were slightly higher than those of the intervention group at all measurement points. In contrast to the other groups, the mean BMI of the female control participants could be classified as overweight at baseline (25·2 kg/m2) and increased over the study period to 26·2 kg/m2 at week 24. The mean TSF and MUAC for both males and females remained within the values associated with good health from baseline to week 24(Reference Lee and Nieman34 , Reference Fryar, Gu and Ogden35).

Table 8 Anthropometric status of the participants by gender: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

MUAC, mid-upper arm circumference; TSF, triceps skinfold.

Discussion

The first hypothesis related to QoL, as the primary outcome, was that the intervention group would have a significant improvement in their QoL compared with the control group at week 12 and week 24. The results supported this hypothesis. There was improvement in the construct scores of QoL of the intervention group compared with the control group. Some of the improvements were significant. There was no significant difference between the intervention and control groups’ scores in the physical functioning construct at baseline (P = 0·24), but there were significant differences at week 12 (P < 0·001) and week 24 (P < 0·001). Similarly, there was a significant difference between the intervention and the control groups’ scores in the role limitation due to the physical health construct at week 12 (P = 0·01) and week 24 (P = 0·002).

There are limited results available in the literature that focus on the impact of NE on QoL of ALH. However, the results of the present study are in agreement with previous studies. Mwamburi et al. demonstrated a similar significant improvement of 6 % in the physical construct of QoL among the intervention group, who received dietary counselling to increase energy intake by ≥2092 kJ/d (≥500 kcal/d), compared with the control group participants(Reference Mwamburi, Gerrior and Wilson11). Another study focusing on the QoL of ALH, including nutrition counselling, documented a significant improvement in the physical functioning construct of both the intervention and control groups(Reference Ogalha, Luz and Sampaio10). Ogalha et al. evaluated the impact of a 50 min education session on dietary needs and exercise on the QoL of seventy ALH in Brazil(Reference Ogalha, Luz and Sampaio10). These authors found significant improvement from baseline (intervention: 71 (sd 24); control: 71 (sd 28)) to week 12 (intervention: 91 (sd 17), P = 0·004; control: 84 (sd 24), P = 0·001) within the intervention and control groups, but a non-significant difference in improvement between the groups (P > 0·05).

The significant improvements reported in the present study could have several explanations. The intervention group could have increased their physical activities since not only were they encouraged to do so during the education sessions, but were also empowered to understand the scientific benefits of exercise as established in previous studies, such as that of Hu et al., which showed that people who are physically active have a lower risk of cardiovascular and cancer diseases(Reference Hu, Tuomilehto and Silventoinen36). The NEP also addressed the roles of food in physical functioning, emotional well-being, energy and fatigue, social functioning, pain and general health. Furthermore, the improvement in dietary quality suggested by the 26 % increase in the percentage of participants with IDDS ≥ 5 at week 24 could have contributed to an improved sense of physical and emotional well-being and functioning. A study that evaluated the relationship between nutritional status and physical functioning among undernourished adults in Malaysia confirmed that poor nutrition can affect physical performance(Reference Singh, Manaf and Yusoff37).

The importance of a positive attitude was also emphasised to the intervention participants since previous studies have confirmed that participants can increase their happiness through positive attitudes(Reference Argyle38) and by improving social relationships(Reference Babicz-Zielińska39, Reference Schulz and Martire40). Participants in the intervention group were also educated that negative attitudes can lead to role limitations because negative emotions can affect appetite, among other things(Reference Desmet and Schifferstein41, Reference Spoor, Bekker and Van Strien42). The NEP might have been responsible for the significant improvement in role limitations related to emotional problems of the intervention group compared with the control group at week 24 (P = 0·02).

It was hypothesised that the anthropometric status of the intervention group would show significant improvements at weeks 12 and 24 when compared with the control group. Participants in the intervention group maintained the same mean BMI (24·0 kg/m2) associated with good health from baseline to week 24. The mean BMI of the control group increased insignificantly (P = 0·06) from a BMI associated with good health (24·9 kg/m2) at baseline to one associated with overweight at week 12 (25·4 kg/m2) and week 24 (25·7 kg/m2). The mean BMI of the intervention and control groups are comparable to those reported for ALH in other African studies. A large cross-sectional study in an HIV-prevalent rural South African area found a mean BMI of 25·4 kg/m2 among the HIV-infected women, while the mean BMI of HIV-infected men (21·1 kg/m2) was lower than that obtained in our study(Reference Malaza, Mossong and Bärnighausen43). A cross-sectional study of ALH in Cameroon reported a mean BMI of 25 kg/m2, with that of the women (25·2 kg/m2) being higher than that of the men (23·8 kg/m2; P = 0·047)(Reference Ngu, Choukem and Dimala44).

Regarding change in weight and BMI, van Niekerk et al. reported similar findings of a stable weight among 73 % of HIV-infected patients not receiving ART following an NE and counselling programme(Reference Van Niekerk, Smego and Sanne45). Our results differed from those of Batterham and Garsia(Reference Batterham and Garsia46) who reported a significant mean weight gain of 1·13 (sd 0·36) kg among participants who received only NE for 12 weeks; and those of Tabi and Vogel who reported, after a secondary analysis of observational data, weight gains of 2·69 kg (female) and 3·37 kg (male) among patients who received dietary counselling to increase protein intake(Reference Tabi and Vogel47).

In agreement with the mean BMI, both intervention and control groups maintained their baseline TSF and MUAC results indicative of good health (TSF: 32 mm for males; 31 mm for females; MUAC: 29 cm for males; 30 cm for females)(Reference Lee and Nieman34, Reference Fryar, Gu and Ogden35) to week 24. A review of the literature provided very limited reports on clinical trials measuring MUAC and TSF in ALH as part of the anthropometric prognostic indicators of a nutrition intervention. The literature review by Koethe et al. highlighted MUAC, TSF, waist and hip circumferences as being among the unexplored prognostic indicators in HIV in nutrition clinical trials(Reference Koethe, Chi and Megazzini48).

Given that the mean BMI of the intervention group remained in the upper normal range and that mean TSF and MUAC were constant throughout the study, it is questionable whether an increase in anthropometric measurements would have been desirable. While wasting and weight loss associated with opportunistic infections(Reference Wanke, Silva and Knox8) remain common complications of HIV/AIDS and must be appropriately managed when present, the increasing prevalence of overweight, obesity, lipohypertrophy and metabolic syndrome are concerns among ALH in the era post highly active ART in both high- and low- to middle- income countries(Reference Ali, Magee and Dave49Reference Lake, Stanley and Apovian51). A prospective cohort of South African HIV-infected women found that BMI increased from a median of 27 kg/m2 at diagnosis to 30 kg/m2 at 36 months (P < 0·0001), while the percentage women classified as obese rose from 34 % at diagnosis to 48 % (P = 0·004) at 36 months. Almost 11 % of the women developed metabolic syndrome during the 36-month follow-up period(Reference Sobieszczyk, Werner and Mlisana52). Cross-sectional studies from Kenya(Reference Kiama, Wamicwe and Oyugi53) and Nigeria(Reference Muhammad, Gezawa and Uloko54) have reported metabolic syndrome prevalence of 19 and 24 %, respectively, among ALH.

One of the aims of an NEP should be to maintain a healthy body weight. The BMI maintained by the intervention group could be associated with the content of the NEP (Table 1). The NEP emphasised healthy food choices and increasing dietary variety (rather than increasing energy intake) while encouraging participants to become more physically active.

Several confounding factors might have contributed to the positive changes in the QoL of the intervention group. The control group received the NE brochure only, without any contact with the NEP team during the study period. Thus, the increased social interaction and attention from the NEP team, rather than the content of the NEP itself, might have resulted in the improved QoL of the intervention group. Furthermore, as ART compliance was not monitored, better compliance among the intervention group could have contributed to the improvement seen in the QoL. Likewise, changes in personal circumstances, illness or other factors unrelated to the NEP could have influenced the results of both the intervention and control groups.

A shortcoming of the present study was that physical activity of the participants was not assessed. It is therefore not possible to conclude whether the significant improvement in the physical functioning construct of the intervention group resulted from increased physical activity, a healthier diet or changed perceptions of the participants. A further limitation was that the study design was quasi-experimental and not a randomised controlled trial that serves as a gold standard(Reference Harris, McGregor and Perencevich55). The study involved only two government hospitals in one of thirty-six states in Nigeria, implying that the conclusions of the present study may not be generalised to all ALH in Nigeria. The study was also limited by lack of observation at private hospitals; the ALH attending private hospitals might have better economic power than their counterparts at government hospitals. Hence contrary results might be observed among the ALH at private hospitals.

Conclusions

It can be concluded that the NEP played a significant role in improving the general well-being (QoL) of the ALH. The study has shown that NE that focuses on healthy diet principles and practices could make a positive contribution to the management needed by ALH.

It is therefore recommended that policy makers and health-care workers incorporate NE in the management among ALH in order to improve their QoL and maintain healthy anthropometric status.

Acknowledgements

Acknowledgements: The authors are indebted to the Head of Public Health, nurses, public health physicians, medical officers, community health workers, environmental health officers, health attendants and administrative staff of the two government hospitals in Abeokuta, Nigeria. The research assistants are also appreciated. The authors are thankful to the participants for their patience throughout the study. Financial support: The authors gratefully acknowledge Department of Research and Innovation (DRI) of the University of Pretoria, Tertiary Education Trust Funds (TET Funds) and Red Cross International Lagos branch for their support in this study. The funders had no roles in the study design, data collection, analysis and the preparation of the manuscript. The University of Johannesburg and National Research Foundation of South Africa is acknowledged for the postdoctoral fellowship support for first author (T.B.K.). Conflict of interest: The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article. Authorship: T.K.B., G.J.G., U.E.M. and P.B. contributed to the conception and research design. P.B., T.K.B. and U.E.M. contributed to the data analysis. T.K.B. was actively involved in data acquisition. P.B., T.K.B., U.E.M. and G.J.G. contributed to the interpretation of the data. T.K.B., G.J.G., U.E.M. and P.B. drafted the manuscript. All authors critically revised, agreed and approved the final manuscript. Ethics of human subject participation: This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Faculty of Health Science Research Ethics Committee, University of Pretoria, South Africa (number 311/2014) and the two hospitals (numbers FMCA/470/HREC/2014 and SHA.144/vol. II/97). Participants provided written informed consent prior to participation in the study. Participants were reimbursed for their transportation fare immediately after each training session.

Author ORCID

Una E MacIntyre, 0000-0001-6334-2188.

References

Joint United Nations Programme on HIV/AIDS (2017) UNAIDS Data 2017. http://www.unaids.org/sites/default/files/media_asset/20170720_Data_book_2017_en.pdf (accessed July 2017).Google Scholar
Grobler, L, Siegfried, N, Visser, ME et al. (2013) Nutritional interventions for reducing morbidity and mortality in people with HIV. Cochrane Database Syst Rev issue 2, CD004536.Google Scholar
Piwoz, E & Preble, E (2000) HIV/AIDS and Nutrition: A Review of the Literature and Recommendations for Nutritional Care and Support in Sub-Saharan Africa. Washington, DC: SARA Project, USAID.Google Scholar
Semba, RD & Tang, A (1999) Micronutrients and the pathogenesis of human immunodeficiency virus infection. Br J Nutr 81, 181189.CrossRefGoogle ScholarPubMed
Mangili, A, Murman, D, Zampini, A et al. (2006) Nutrition and HIV infection: review of weight loss and wasting in the era of highly active antiretroviral therapy from the nutrition for healthy living cohort. Clin Infect Dis 42, 836842.CrossRefGoogle ScholarPubMed
Wheeler, DA, Gibert, CL, Launer, CA et al. (1998) Weight loss as a predictor of survival and disease progression in HIV infection. J Acquir Immune Defic Syndr 18, 8085.CrossRefGoogle ScholarPubMed
Tang, AM, Forrester, J, Spiegelman, D et al. (2002) Weight loss and survival in HIV-positive patients in the era of highly active antiretroviral therapy. J Acquir Immune Defic Syndr 31, 230236.CrossRefGoogle ScholarPubMed
Wanke, C, Silva, M, Knox, T et al. (2000) Weight loss and wasting remain common complications in individuals infected with human immunodeficiency virus in the era of highly active antiretroviral therapy. Clin Infect Dis 31, 803805.CrossRefGoogle ScholarPubMed
Carbonnel, F, Beaugerie, L, Rached, AA et al. (1997) Macronutrient intake and malabsorption in HIV infection: a comparison with other malabsorptive states. Gut 41, 805810.CrossRefGoogle ScholarPubMed
Ogalha, C, Luz, E, Sampaio, E et al. (2011) A randomized, clinical trial to evaluate the impact of regular physical activity on the quality of life, body morphology and metabolic parameters of patients with AIDS in Salvador, Brazil. J Acquir Immun Def Synd 57, Suppl. 3, S179S185.CrossRefGoogle Scholar
Mwamburi, DM, Gerrior, J, Wilson, IB et al. (2004) Combination megestrol acetate, oxandrolone, and dietary advice restores weight in human immunodeficiency virus. Nutr Clin Pract 19, 395402.CrossRefGoogle ScholarPubMed
Dwyer, JT, Larive, B, Leung, J et al. (2002) Nutritional status affects quality of life in hemodialysis (HEMO) study patients at baseline. J Ren Nutr 12, 213223.CrossRefGoogle ScholarPubMed
de Luis, D, Aller, R, Bachiller, P et al. (2003) Isolated dietary counselling program versus supplement and dietary counselling in patients with human immunodeficiency virus infection. Med Clin (Barc) 120, 565567.CrossRefGoogle ScholarPubMed
McDermott, AY, Shevitz, A, Must, A et al. (2003) Nutrition treatment for HIV wasting: a prescription for food as medicine. Nutr Clin Pract 18, 8694.CrossRefGoogle ScholarPubMed
Thomson, CA & Ravia, J (2011) A systematic review of behavioral interventions to promote intake of fruit and vegetables. J Am Diet Assoc 111, 15231535.CrossRefGoogle ScholarPubMed
Wiefferink, CH, Peters, L, Hoekstra, F et al. (2006) Clustering of health-related behaviors and their determinants: possible consequences for school health interventions. Prev Sci 7, 127149.CrossRefGoogle ScholarPubMed
Bello, TK (2017) Development, implementation and impact evaluation of a nutrition education programme for adults living with HIV/AIDS in Abeokuta, Nigeria. PhD Thesis, University of Pretoria.Google Scholar
Nadhiroh, SR (2006) Good nutrition for quality of life of PLWHA (people living with HIV/AIDS). Indones J Public Health 3, 2934.Google Scholar
Derenne, A & Baron, A (2002) Behavior analysis and the study of human aging. Behav Anal 25, 151160.CrossRefGoogle Scholar
Contento, IR (2011) Nutrition Education: Linking Research, Theory, and Practice, 2nd ed. New York: Jones and Bartlett.Google Scholar
Contento, IR (2007) Nutrition Education: Linking Research, Theory, and Practice, 1st ed. New York: Jones and BartlettGoogle Scholar
Sahyoun, NR, Pratt, CA & Anderson, A (2004) Evaluation of nutrition education interventions for older adults: a proposed framework. J Am Diet Assoc 104, 5869.CrossRefGoogle ScholarPubMed
Han, C, Pulling, CC, Telke, SE et al. (2002) Assessing the utility of five domains in SF-12 Health Status Questionnaire in an AIDS clinical trial. AIDS 16, 431439.CrossRefGoogle Scholar
Jelsma, J, MacLean, E, Hughes, J et al. (2005) An investigation into the health-related quality of life of individuals living with HIV who are receiving HAART. AIDS Care 17, 579588.CrossRefGoogle ScholarPubMed
Ware, JE, Kosinski, M, Gandek, B et al. (1998) The factor structure of the SF-36 Health Survey in 10 countries: results from the IQOLA Project. J Clin Epidemiol 51, 11591165.CrossRefGoogle ScholarPubMed
Wagner, AK, Gandek, B, Aaronson, NK et al. (1998) Cross-cultural comparisons of the content of SF-36 translations across 10 countries: results from the IQOLA project. J Clin Epidemiol 51, 925932.CrossRefGoogle ScholarPubMed
Arpinelli, F, Visona, G, Bruno, R et al. (2000) Health-related quality of life in asymptomatic patients with HIV: evaluation of the SF-36 Health Survey in Italian patients. Pharmacoeconomics 18, 6372.CrossRefGoogle ScholarPubMed
Hsiung, P-C, Fang, C-T, Chang, Y-Y et al. (2005) Comparison of WHOQOL-BREF and SF-36 in patients with HIV infection. Qual Life Res 14, 141150.CrossRefGoogle ScholarPubMed
Gibson, RS (2005) Principles of Nutritional Assessment, 2nd ed. New York: Oxford University Press.Google Scholar
Centers for Disease Control and Prevention (2007) National Health and Nutrition Examination Survey (NHANES). Anthropometry Procedures Manual. https://www.cdc.gov/nchs/data/nhanes/nhanes_07_08/manual_an.pdf (accessed July 2013).Google Scholar
Rands Health (2009) Medical Outcomes Study: 36-Item Short Form Survey Instrument. http://www.rand.org/health/surveys_tools/mos/mos_core_36item.html (accessed March 2019).Google Scholar
Weiser, SD, Fernandes, KA, Brandson, EK et al. (2009) The association between food insecurity and mortality among HIV-infected individuals on HAART. J Acquir Immune Defic Syndr 52, 342349.CrossRefGoogle ScholarPubMed
World Health Organization (2004) Global Database on Body Mass Index. http://www.assessmentpsychology.com/icbmi.htm (accessed April 2019).Google Scholar
Lee, R & Nieman, D (2003) Nutritional Assessment. Washington, DC: McGraw Hill Higher Education.Google Scholar
Fryar, CD, Gu, Q & Ogden, CL (2012) Anthropometric reference data for children and adults: United States, 2007–2010. Vital Health Stat 11 issue 252, 148.Google Scholar
Hu, G, Tuomilehto, J, Silventoinen, K et al. (2005) The effects of physical activity and body mass index on cardiovascular, cancer and all-cause mortality among 47 212 middle-aged Finnish men and women. Int J Obes (Lond) 29, 894902.CrossRefGoogle ScholarPubMed
Singh, DK, Manaf, ZA, Yusoff, NAM et al. (2014) Correlation between nutritional status and comprehensive physical performance measures among older adults with undernourishment in residential institutions. Clin Interv Aging 9, 14151423.CrossRefGoogle ScholarPubMed
Argyle, M (2013) The Psychology of Happiness. New York: Routledge.CrossRefGoogle Scholar
Babicz-Zielińska, E (2006) Role of psychological factors in food choice – a review. Pol J Food Nutr Sci 15, 379384.Google Scholar
Schulz, R & Martire, LM (2004) Family caregiving of persons with dementia: prevalence, health effects, and support strategies. Am J Geriatr Psychiatry 12, 240249.CrossRefGoogle ScholarPubMed
Desmet, PM & Schifferstein, HN (2008) Sources of positive and negative emotions in food experience. Appetite 50, 290301.CrossRefGoogle ScholarPubMed
Spoor, ST, Bekker, MH, Van Strien, T et al. (2007) Relations between negative affect, coping, and emotional eating. Appetite 48, 368376.CrossRefGoogle ScholarPubMed
Malaza, A, Mossong, J, Bärnighausen, T et al. (2012) Hypertension and obesity in adults living in a high HIV prevalence rural area in South Africa. PLoS One 7, e47761.CrossRefGoogle Scholar
Ngu, RC, Choukem, S-P, Dimala, CA et al. (2018) Prevalence and determinants of selected cardio-metabolic risk factors among people living with HIV/AIDS and receiving care in the South West Regional Hospitals of Cameroon: a cross-sectional study. BMC Res Notes 11, 305.CrossRefGoogle ScholarPubMed
Van Niekerk, C, Smego, R & Sanne, I (2000) Effect of nutritional education and dietary counselling on body weight in HIV-seropositive South Africans not receiving antiretroviral therapy. J Hum Nutr Diet 13, 407412.CrossRefGoogle Scholar
Batterham, MJ & Garsia, R (2001) A comparison of megestrol acetate, nandrolone decanoate and dietary counselling for HIV associated weight loss. Int J Androl 24, 232240.CrossRefGoogle ScholarPubMed
Tabi, M & Vogel, RL (2006) Nutritional counselling: an intervention for HIV-positive patients. J Adv Nurs 54, 676682.CrossRefGoogle ScholarPubMed
Koethe, JR, Chi, BH, Megazzini, KM et al. (2009) Macronutrient supplementation for malnourished HIV-infected adults: a review of the evidence in resource-adequate and resource-constrained settings. Clin Infect Dis 49, 787798.CrossRefGoogle ScholarPubMed
Ali, MK, Magee, MJ, Dave, JA et al. (2014) HIV and metabolic, body, and bone disorders: what we know from low-and middle-income countries. J Acquir Immune Defic Syndr 67, Suppl. 1, S27S39.CrossRefGoogle ScholarPubMed
Mankal, PK & Kotler, DP (2014) From wasting to obesity, changes in nutritional concerns in HIV/AIDS. Endocrinol Metab Clin 43, 647663.CrossRefGoogle ScholarPubMed
Lake, JE, Stanley, TL, Apovian, CM et al. (2017) Practical review of recognition and management of obesity and lipohypertrophy in human immunodeficiency virus infection. Clin Infect Dis 64, 14221429.CrossRefGoogle ScholarPubMed
Sobieszczyk, ME, Werner, L, Mlisana, K et al. (2016) Metabolic syndrome after HIV acquisition in South African women. J Acquir Immune Defic Syndr 73, 438445.CrossRefGoogle ScholarPubMed
Kiama, CN, Wamicwe, JN, Oyugi, EO et al. (2018) Prevalence and factors associated with metabolic syndrome in an urban population of adults living with HIV in Nairobi, Kenya. Pan Afr Med J 29, 90.CrossRefGoogle Scholar
Muhammad, FY, Gezawa, ID, Uloko, A et al. (2017) Metabolic syndrome among HIV infected patients: a comparative cross sectional study in northwestern Nigeria. Diabetes Metab Syndr 11, Suppl. 1, S523S529.CrossRefGoogle ScholarPubMed
Harris, AD, McGregor, JC, Perencevich, EN et al. (2006) The use and interpretation of quasi-experimental studies in medical informatics. J Am Med Inform Assoc 13, 1623.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Nutrition education programme (NEP) curriculum(17)

Figure 1

Fig. 1 Flow of participants through the study

Figure 2

Table 2 Comparison of demographic characteristics between the intervention and control groups at baseline, week 12 and week 24: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

Figure 3

Table 3 Differences in mean quality of life (QoL) construct scores (%) between the intervention and control groups at baseline, week 12 and week 24: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

Figure 4

Table 4 Differences in quality of life (QoL) mean construct scores (%) within the intervention and control groups from baseline to week 12 and week 24: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

Figure 5

Table 5 Internal consistency of the quality of life (QoL) questionnaire for intervention and control groups: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

Figure 6

Table 6 Differences in anthropometric mean values between the intervention and control groups at baseline, week 12 and week 24: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

Figure 7

Table 7 Differences in anthropometric mean values within the intervention and control groups from baseline to week 12 and week 24: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016

Figure 8

Table 8 Anthropometric status of the participants by gender: adults living with HIV (n 200), Abeokuta, Nigeria, November 2015–May 2016