Abstract
Background
HIV-related weight loss and wasting were the most common malnutrition and AIDS-defining conditions before HAART. HAART has led to more obese PLHIV. HIV-positive patients should eat micro- and macronutrient-rich foods to maintain optimal nutrition. This study examined whether Moringa oleifera Lam. leaf supplementation affects PLHIV receiving ART.
Methods
A randomized, double-blind, controlled trial was conducted. Two hundred patients with informed consent were randomly assigned to either the Moringa oleifera Lam. (MOG) group or the control group (COG). From baseline to six months of Moringa oleifera Lam. leaf supplementation, anthropometric parameters [weight; BMI] of the participants were assessed.
Results
One hundred seventy-seven patients completed the 6-month follow-up (89 MOG vs. 88 COG). During the study period, the MOG and COG had similar weights and BMIs (p>0.05). At baseline and six months, most participants in both study groups had a healthy BMI (18.5-24.9). Many participants were overweight; few were underweight ((BMI <18.5). MOG and COG BMI differences at baseline and six months were not significant (p> 0.05). All experiments were 95CI.
Conclusions
Moringa oleifera Lam. leaf powder had no effect on HIV-positive adults receiving antiretroviral therapy, in accordance with this study.
Keywords: Moringa oleifera Lam, HIV, BMI, antiretroviral therapy
INTRODUCTION
According to the 2019 UNAIDS report, there were 1,9 million HIV-positive individuals in Nigeria, with a prevalence of 1.5% among adults aged 15-49 [1]. Malnutrition and HIV/AIDS are inextricably linked [2]. During the pre-highly active antiretroviral therapy (pre-HAART) era, HIVrelated weight loss and wasting were the most prevalent forms of malnutrition and AIDS-defining conditions [3]. This was marked by a significant decrease in body fat, lean mass, and bone mass [4]
The introduction of HAART has proven effective in reducing morbidity and mortality associated with HIV infection [5, 6] and in ameliorating the syndrome of wasting associated with HIV [5]. On the other hand, it has been documented that the prevalence of overweight and obesity increases among HIV-positive individuals receiving HAART [7], which may increase the risk of cardiovascular and metabolic diseases [8].
Diet is of the utmost importance for maintaining optimal nutrition and preventing these complications [4]. Patients infected with HIV are urged to consume diets rich in micro- and macronutrients necessary for normal body function [4]. Unfortunately, the diet and food consumption of PLHIV in low-income settings, such as Nigeria, need improvement [9].
The powdered leaves of Moringa oleifera Lam., which has been shown to have a high nutritional value [10-13], could be a valuable addition to the diets of PLHIV. Moringa oleifera Lam. is a member of the Moringaceae family [14]. The leaves are a rich source of both macro- and micronutrients [16] and act as a good source of natural antioxidants [17] due to their high concentration of minerals, vitamins, and other vital phytochemicals.
We have already conducted a study demonstrating the effect of Moringa oleifera Lam. leaves on the immune status [18] and the quality of life of PLHIV on ART [19], which have been reported elsewhere. Consequently, the purpose of this manuscript is to determine if supplementation with Moringa oleifera Lam. leaves affects the weight and BMI of PLHIV on ART compared to placebo at the S.S Wali Virology Centre, Aminu Kano Teaching Hospital, Kano State, Nigeria.
MATERIALS AND METHODS
Study location
The study location was the Sadiq Suleiman Wali, known as S.S Wali Virology Centre at Aminu Kano Teaching Hospital, Kano State (AKTH), Nigeria.
AKTH is a tertiary health institution and referral center that operates a daily HIV clinic (5 days a week). It also serves as a center for clinical evaluation, laboratory tests, HIV counseling and testing (HCT), treatment, and care supported by the Federal Government and the Institute of Human Virology, Nigeria (IHVN) in partnership with its global partners, including the Centers for Disease Control and Prevention (CDC) and the Global Fund to Fight AIDS, Tuberculosis, and Malaria. The center attends to all patients with HIV infection diagnosed within the hospital or referred from outside the health facility.
Research design
The study was a double-blind, randomized controlled trial conducted from December 2017 to November 2018. All research participants and research team members, including the principal investigator (PI), were blinded to the allocation of participants to study groups.
Ethical consideration
The study was reviewed and approved by the ethics committee of Aminu Kano Teaching Hospital (AKTH) Kano State, Nigeria (reference number NHREC/21/08/2008/AKTH/EC/2012), and the Biomedical Research Ethics Committee of the University of Kwazulu-Natal, Durban, South Africa, (reference number BFC294/16). The study was registered in the Pan African Clinical Trial Registry (identification number PACTR201811722056449).
Participants were informed about the aims of the study, and the study protocol was explained to them. This study was conducted in compliance with the principles enunciated in Helsinki’s Declaration. All the study participants provided signed written informed consent or thumbprint if unable to sign. They were also informed of their right to withdraw from the study at any time.
Participants
Participants were approached to participate in this study as they presented themselves to the clinic for any HIV services offered. The participants comprised of patients diagnosed with HIV infection receiving medical care at the S. S Wali Virology Center at the Aminu Kano Teaching Hospital (AKTH) Kano State, Nigeria.
Inclusion criteria: the inclusion criteria were an HIV diagnosis with CD4 counts _ 500 cells/mm3; 18 years or older; commenced ART at least for three months; on Tenofovir + Lamivudine + Efavirenz ART drug combination; male and female, and those who gave consent and complied with the study protocol.
Exclusion criteria: participants who had known allergy or intolerance to Moringa oleifera Lam. or placebo (cornstarch powder); pregnant women; active opportunistic infection; participants that took micronutrient or natural health product supplements within 30 days of screening and those that lived outside Kano State where the study was conducted were excluded.
Sample size estimation
The sample size was calculated to be able to detect a medium effect size (Cohen’s d=0.5) or 0.5 standard deviation in mean weight or CD4 by randomised control trial (RCT) arm with 90% power (1-β [type 2 error probability]), and 95% confidence (or 5% α error probability [type 1]) assuming a balanced 1:1 study design. A sample size of 172 patients was calculated, which was increased to 200 to give room for attrition.
Out of the 410 participants available for assessment of eligibility, 204 of the participants did not meet the inclusion criteria, 6 participants declined to participate, and the remaining 200 participants were randomly assigned to either Moringa oleifera Lam. group (MOG) or the Control group (COG) with 100 participants in each group. Only 177 participants completed the study (Figure 1). The sample size was calculated using G*Power version 3.1.9.2 [20].
Randomization
Block randomization was used to balance the groups throughout the enrolment period. The randomization sequence was generated using PASS 12.0 software (Wei’s Urn algorithm) by an independent person that was not part of the research team. As the recruited participants fulfilled the inclusion criteria and consented, a number was assigned to the patient and were randomly allocated into the MOG and COG groups. All research team members were blinded to the allocation of study participants to the respective study groups.
Intervention - Moringa oleifera Lam. nutritional supplement
The fresh Moringa oleifera Lam. leaves were obtained from Prime Global Agricultural Industries Limited, Kano State, Nigeria. The fresh leaves were identified and authenticated by a Botanist at the Department of Biological Science, Bayero University Kano (BUK), Nigeria. Confirmation of the taxonomic identity of the plant was achieved by comparison with voucher specimens kept at the Herbarium of the Department of Biological Sciences BUK. It was processed, manufactured, and packaged at Dala Foods, Nigeria Limited, Kano State, Nigeria.
Placebo
The placebo was obtained by colouring corn starch powder with chlorophyll [21]. It was also processed, manufactured, and packaged at Dala Foods Nigeria Limited Kano State, Nigeria.
Both the Moringa oleifera Lam. leaf powder and the placebo were similar in presentation and were identically packaged to be indistinguishable. The interventions were packaged into small (15 g) sachets each. Thirty (30) individual sachets were further packaged in a bigger green-colored plastic bag to be used as supplements taken together with meals for one month. It was sealed, labelled with the study code, visit no, subject no, and instructions on how to take it, and stored in a dry place away from heat and humidity.
Patients were randomly assigned and were either given Moringa oleifera Lam. or the placebo. They were instructed to divide each sachet three times daily (5 g) and add it to their foods before eating [22,23].
All the above procedure was performed by independent persons not part of the research. All the study participants were advised to maintain their regular diet from inception throughout the study. Additionally, they were also instructed not to consume Moringa oleifera Lam. in any form from other external sources throughout the study.
Compliance was monitored to evaluate adherence by self-report during biweekly telephone calls to the participants and monthly hospital visits.
Nutritional contents of Moringa oleifera Lam. leaves powder
The nutritional content of a 100 g Moringa oleifera Lam. leaf powder (Nigerian ecotype) was analyzed by a South African National Accreditation System (SANAS) [24] accredited laboratory ASPIRATA Food and Beverage Laboratory [25].
Accordingly, the nutritional content of Moringa oleifera Lam. leaf powder used in this study includes; 100 g contained an average of 28 g protein, 3.9 g total fat content (total saturated, monosaturated, and polysaturated fat), and 22 g carbohydrate. It contained 1791.82 mg calcium; 4879.26 mg potassium; 24 mg sodium; 2.88 mg Zinc and 37.78 mg iron.
Data collection
Socio-demographic information
At the beginning of the study, a questionnaire to determine each study participant’s socio-demographic information was administered by a trained nurse at the virology clinic. This included age, marital status, educational level, occupation, family size, and monthly income.
Anthropometric measurements
Weight was measured to the nearest 0.1 kg using a digital weighing scale (Tanita HD-372, Tanita Corporation, Tokyo, Japan), with participants wearing light clothing and without shoes. Height was measured to the nearest centimeter using a stadiometer (Seca 217, Seca Gmbh and co. KG., Hamburg, Germany). Body mass index (BMI) was calculated as the weight in kilograms divided by the square of height in meters. The BMI was categorised as underweight (BMI <18.5); normal weight (BMI 18.5-24.9); overweight (BMI 25.0-29.9) and obesity (BMI >30.0) [26]. A trained nurse conducted it at the virology centre at baseline and each monthly hospital visit under the supervision of the PI. Anthropometric measurements from baseline to the sixth month were used.
Study outcomes
The outcomes assessed were changes in anthropometric parameters (weight and body mass index [BMI]).
Data processing and analysis
All filled questionnaires were checked for completeness and consistency. The data input was done in Microsoft Excel and exported into SPSS version 26.0 and SAS version 9.4 statistical analysis software for further analysis. Continuous variables were described using the mean, standard deviation, and range, while categorical variables were reported mainly as frequency and percentage. Normality tests for the data were conducted using Kolmogorov- Smirnov and Shapiro-Wilk tests. The data that were not normally distributed were transformed through Box-Cox transformation. The weight was transformed through a lambda value -0.1 and BMI by lambda value -0.2. Repeated measures analysis of variance was deployed to determine significant changes in the mean of anthropometric parameters from baseline to the sixth month within each group. An independent t-test was used to determine the significant mean difference in anthropometric parameters between the two groups at each experiment stage. A linear mixed effect model analysis was deployed to determine the difference in anthropometrics parameters between the treatment groups over time to confirm variability between the two groups further. All statistical tests were performed at a 95% confidence level.
Data Quality Control
Data were collected by a trained nurse and trained research assistants after undergoing two-day intensive training to all data collectors and supervisors at the virology clinic. Calibration of anthropometric measuring weight scale was checked at zero before and after each measurement following standard protocol.
RESULTS
Figure 1 shows the flow chart of the participants’ progress in both study groups. Four hundred and ten patients were screened and assessed for eligibility. Two hundred and ten patients were excluded [204 did not meet the inclusion criteria for the study, and six refused to participate]. Two hundred patients were randomized into two groups. One hundred patients were randomly selected and allocated to the group receiving Moringa oleifera Lam. (MOG), and 100 patients were randomly allocated to the group receiving the placebo (COG). In the MOG, eight patients were lost to follow-up, and three discontinued taking the intervention. In the COG, nine patients were lost to follow-up, and three discontinued taking the intervention. One hundred and seventy-seven (177) patients with the mean_SD age of 41.57_8.23 years completed the six months study, and their data were included in the analysis (89 in the MOG and 88 in COG) (Figure 1).
Demographic characteristics of the participants
Table 1 shows the baseline demographic assessments of the 177 participants (89 in the MOG and 88 in the COG). The participants in both groups had similar baseline measures regarding gender, age, marital status, religion, ethnicity, level of education, family size, occupation, and monthly income.The majority of the participants were between 30 to 39 years, with a predominantly female population in both groups [MOG=70 (78.7%); COG=67(76.1%)]. Most of the participants were married [MOG= 42 (47.2%); COG= (38 (43.2%)] with Islam being the predominant religion [MOG= 64 (71.9%); COG= (66 (75%)]. More than half of participants belong to Hausa/Fulani ethnicity [MOG= 55 (61.8%0; COG= 47 (53.4%)]. A few of the participants in both groups were without any form of education [MOG= 15 (16.9%); COG= 16 (18.2%)] and majority earned a monthly income below the minimum wage of 30,000 (US $ 78.23) [MOG= 67 (75.3%); COG= 66 (75%)] (Table 1).
Table 2 shows the baseline anthropometric parameters [weight; BMI] of the study participants in MOG and COG. The means of weight (kg) for both groups were [MOG= 63.8 (_14.8); COG= 61.9 (12.5)]. The mean BMIs for MOG and COG were 24.84 (_4.76) and 23.75 (_3.82), respectively. More than half of the study participants had BMI within the normal range of 18.5-24.9 in both groups [MOG= (51.7%); COG= (58%)] while a considerable number were overweight with BMI values of 25.0-29.9 [MOG= (30.3%); COG= (31.8%)] for both study groups (Table 2).
Table 3 shows the comparison of BMI of participants at baseline and sixth month between MOG and COG. At both baseline and sixth month, most of the participants in both study groups had normal weight (BMI = 18.5-24.9). Only a few of the participants were underweight (BMI<18.5) or obese (BMI≥30.0). A considerable number were overweight. These differences in BMI categories at both baseline and sixth month were not found to be statistically significant (p> 0.05) in both MOG and COG. The descriptive analysis showed that the overall mean (±SD) BMI for MOG at baseline was 24.84 (±4.78) and 25.16 (±4.93) at 6th month while that of the COG was 23.75 (±3.82) and 24.19 (±4.09) at 6th month (Table 3).
Table 4 shows the result of repeated measures ANOVA to determine changes in anthropometric parameters within each study group. At six months follow-up, the difference in mean weight and BMI observed in the MOG was not statistically significant (P>0.05). However, a statistically significant (P<0.05) increase was observed in both the mean of weight and BMI of participants in the COG at the fifth and sixth months of the study (Table 4). Nonetheless, no significant (P>0.05) difference was observed in both the weight and BMI when compared between the MOG and COG using the independentsample test from study inception to the 6th month (Table 5).
A linear mixed-effect model was used to further assess for variability in anthropometric parameters between the MOG and COG. Table 6 shows the linear mixed effect model results showing the differences in weight and BMI between the two groups over the study period.
An unstructured correlation matrix was assumed for the model analysis. Estimate of fixed effects between MOG and COG showed that both the weight (p=0.5556) and BMI (p=0.5145) were not significantly (p>0.05) different over the study period.
Figure 2 shows the mean measurements of BMI and weight of study participants in both MOG and COG groups over the study period. The mean BMI and weight of both study groups were relatively constant throughout the study (Figure 2).
DISCUSSION
This manuscript reports a double-blinded randomized controlled trial conducted to determine the sixmonth impact of Moringa oleifera Lam. leaf powder supplementation on the weight and BMI of adult HIV patients receiving ART care at S. S Wali virology centre, AKTH, Kano State, Nigeria.
Over the study period, the Moringa oleifera Lam. leaf powder supplementation intervention did not impact the weight and BMI of the patients compared to the COG. However, a significant increase in weight and BMI was observed within the COG at the fifth and sixth months of study. The lack of significant change in weight and BMI observed in MOG could be attributed to the type of participants included in the study. At study inception, we observed that most of our study participants had a normal BMI. A considerable number were overweight, while only a few were underweight. As inclusion criteria, the study should have recruited underweight participants with BMI<18.5 kg/m2. This class of patients would probably have benefitted more in terms of improvement in weight and BMI from the Moringa oleifera Lam. leaves supplementation due to the vast amounts of nutrients constituted [27]. This is a limitation of our study. Alternatively, Moringa oleifera Lam. has been reported to control weight gain due to its low calorific content; as such, its use is advocated in obese individuals [28]. This factor could have also been attributed to the lack of change in weight and BMI observed in the MOG.
On the other hand, Tshingani et al. reported an opposite effect of Moringa oleifera Lam. leaves. According to their findings, Moringa oleifera Lam. increased BMI in patients with physical activity. They reported a significant increase in BMI in patients with physical activity in the third and sixth months of taking Moringa oleifera Lam. leaves supplementation [29].
Although Moringa oleifera Lam. leaves intervention did not affect the weight and BMI of the participants in this study, previous research done by the same author reported a significant increase in the CD4 cell counts [18] and quality of life domains [19] of the participants in the MOG after six months of Moringa oleifera Lam. leaves supplementation.
The introduction of HAART has increased the prevalence of overweight and obesity in PLHIV [7] as seen in our study participants. This may increase the risk of cardiovascular and metabolic diseases [18] Additionally, Takarinda et al. reported a study conducted to determine the prevalence of malnutrition among HIV – positive patients that are enrolled in HIV treatment in Zimbabwe. The study reported that the majority of their study participants had a normal BMI (63.6%). Also, a high prevalence of overweight and obesity was observed amongst the study participants. The study suggested that HIV may change from a highly fatal infectious disease into a chronic manageable disease due to the high prevalence of obesity observed in the HIV population on ART. This is associated with an increased risk of cardiovascularrelated conditions such as hypertension and diabetes mellitus [30]. A similar result was reported in a hospital-based cross-sectional study conducted to assess the nutritional status among people living with HIV in Nepal, where most of the study participants were overweight or obese. The study also highlights the importance of nutritional programs being an integral part of the HIV/AIDS continuum of care [31]
Therefore, to address the burden of malnutrition, the use of Moringa oleifera Lam. could be advocated in PLHIV that are taking ART to control weight gain and reduce the risk of cardiovascular and metabolic diseases.
This being a double-blind, randomized placebo trial, a gold standard of intervention studies, gives strength and credence to the findings of this study. Some limitations of the study have been noted. The lack of inclusion of participants that were underweight as well as the sixth month duration of the study and not longer for any significant observable differences. Moringa oleifera Lam’s distinguishable taste could be a source of bias, including patients who were only on one ART regimen (tenofovir + lamivudine + efavirenz drug regimen) limits the generalizability of our study findings. Lastly, compliance, which was monitored by the self-reporting of the study participants, is a further limitation of the study.
CONCLUSIONS
This study revealed that Moringa oleifera Lam. leaf supplementation did not have impact on the weight and BMI of our study participants at sixth month.
TABLE 1:
Socio-demographic characteristics of participants.
| Variables | MOG (%) (N=89) | COG (%) (N=88) | P-value |
|---|---|---|---|
| Gender | |||
| Males | 19 (21.3) | 21 (23.9) | 0.689 |
| Female | 70 (78.7) | 67 (76.1) | |
| Age (years) | |||
| < 20 | 3 (3.4) | 1 (1.1) | 0.737 |
| 20-29 | 24 (27.0) | 21 (23.9) | |
| 30-39 | 37 (41.6) | 36 (40.9) | |
| 40-49 | 20 (22.5) | 22 (25.0) | |
| 50-60 | 5 (5.6) | 8 (9.1) | |
| Marital Status | |||
| Married | 42 (47.2) | 38 (43.2) | 0.838 |
| Single | 12 (13.5) | 10 (11.4) | |
| Divorced | 19 (21.3) | 20 (22.7) | |
| Widowed | 16 (18.0) | 20 (22.7) | |
| Religion | |||
| Islam | 64 (71.9) | 66 (75.0) | 0.642 |
| 25 (28.1) | 22 (25.0) | ||
| Ethnicity | |||
| Hausa/Fulani | 55 (61.8) | 47 (53.4) | 0.511 |
| Yoruba | 13 (14.6) | 15 (17.0) | |
| Igbo | 9 (10.1) | 15 (17.0) | |
| Others | 12 (13.5) | 11 (12.5) | |
| Primary | 14 (15.7) | 12 (13.6) | 0.971 |
| Secondary | 27 (30.3) | 24 (27.3) | |
| Tertiary | 20 (22.5) | 21 (23.9) | |
| Quranic | 13 (14.6) | 15 (17.0) | |
| None | 15 (16.9) | 16 (18.2) | |
| Entrepreneur | 15 (16.9) | 10 (11.4) | 0.840 |
| Trader | 23 (25.8) | 25 (28.4) | |
| Civil Servant | 15 (16.9) | 17 (19.3) | |
| Artisan | 19 (21.3) | 17 (19.3) | |
| Unemployed | 17 (19.1) | 19 (21.6) | |
| Family Size | |||
| 2-5 | 38 (42.7) | 32 (36.4) | 0.557 |
| 6-10 | 26 (29.2) | 25 (28.4) | |
| >10 | 25 (28.1) | 31 (35.2) | |
| Not Indicated | 11 (12.4) | 6 (6.8) | 0.672 |
| < 30,000 | 67 (75.3) | 66 (75.0) | |
| 30,001-60,000 | 6 (6.7) | 10 (11.4) | |
| 60,001-90,000 90,001-120,000 | 1 (1.1) 3 (3.4) | 1 (1.1) 2 (2.3) | |
| >120,000 | 1 (1.1) | 3 (3.4) |
Statistical test = Chi-square test.
FIGURE 2:
Charts showing mean measurements of BMI andweight in MOG and COG over the study period.
TABLE 2:
Description of baseline anthropometric parameters between MOG and COG.
| Baseline | |||
|---|---|---|---|
| Parameters | MOG (n = 89) Freq. (%) | COG (n = 88) Freq. (%) | p value |
| Anthropometrics | |||
| Weight (Kg) | |||
| Mean (±SD) | 63.8 (±14.8) | 61.9 (±12.5) | 0.361 |
| BMI (Kg/m2) | |||
| Underweight (<18.5) | 5 (5.6) | 5 (5.7) | |
| Normal (18.5 – 24.9) | 46 (51.7) | 51 (58.0) | |
| Overweight (25.0 – 29.9) | 27 (30.3) | 28 (31.8) | |
| Obese (> 30.0) | 11 (12.4) | 4 (4.5) | |
| Mean (±SD) | 24.84 (±4.8) | 23.75 (±3.8) | 0.093 |
Statistical test = independent sample t-test.
TABLE 3:
Changes in BMI of participants at baseline and 6th month in MOG and COG.
| BMI | Baseline | 6th month | ||||
|---|---|---|---|---|---|---|
| MOG n. (%) | COG n. (%) | P | MOG n. (%) | COG n. (%) | P | |
| Underweight (<18.5) | 5 (5.6) | 5 (5.7) | 0.357 | 5 (5.6) | 7 (8.0) | 0.549 |
| Normal Weight (18.5 – 24.9) | 46 (51.7) | 51 (58.0) | 0.781 | 41 (46.1) | 46 (52.3) | 0.600 |
| Overweight (25.0 – 29.9) | 27 (30.3) | 28 (31.8) | 0.576 | 29 (32.6) | 27 (30.7) | 0.872 |
| Obese (≥ 30.0) | 11 (12.4) | 4 (4.5) | 0.130 | 14 (15.7) | 8 (9.1) | 0.248 |
| Mean [±SD] (Kg/m2) | 24.84 [±4.78] | 23.75 [±3.82] | 25.16 [±4.93] | 24.19 [±4.09] | ||
| Minimum (Kg/m2) | 16.82 | 16.03 | 15.62 | 16.44 | ||
| Maximum (Kg/m2) | 37.97 | 34.68 | 39.84 | 35.67 | ||
Statistical test = independence sample t-test; SD=standard deviation.
TABLE 4:
Repeated measures ANOVA analysis of anthropometric parameters within each study group.
| MOG | COG | ||||||
|---|---|---|---|---|---|---|---|
| Mean Diff (I-J) | Std. P Error | Mean Diff (I-J) | Std. Error | P | |||
| BMI Baseline (I) | 1st month | -0.018 | 0.072 0.999 | -0.028 | 0.051 | 0.999 | |
| 2nd month | -0.148 | 0.097 0.999 | -0.179 | 0.073 | 0.336 | ||
| 3rd month | -0.150 | 0.118 0.999 | -0.215 | 0.089 | 0.366 | ||
| 4th month | -0.212 | 0.128 0.999 | -0.293 | 0.102 | 0.106 | ||
| 5th month | -0.313 | 0.143 0.665 | -0.390* | 0.106 | 0.009* | ||
| 6th month | -0.317 | 0.141 0.568 | -0.446* | 0.113 | 0.003* | ||
| Weight Baseline (I) | 1st month | -0.045 | 0.181 0.999 | -0.091 | 0.133 | 0.999 | |
| 2nd month | -0.427 | 0.224 0.999 | -0.500 | 0.193 | 0.238 | ||
| 3rd month | -0.483 | 0.282 0.999 | -0.602 | 0.233 | 0.238 | ||
| 4th month | -0.640 | 0.306 0.827 | -0.784 | 0.267 | 0.089 | ||
| 5th month | -0.899 | 0.342 0.213 | -1.045* | 0.283 | 0.008* | ||
| 6th month | -0.876 | 0.343 0.259 | -1.216* | 0.301 | 0.002* | ||
*Statistically significant.
TABLE 5:
Independent – sample analysis showing the differences in anthropometric parameters between MOG and COG.
| Study groups | Mean weight (SD) | |||||||
|---|---|---|---|---|---|---|---|---|
| n | Admission | 1st month | 2nd month | 3rd month | 4th month | 5th month | 6th month | |
| MOG | 89 | 63.83 | 63.88 | 64.26 | 64.31 | 64.47 | 64.73 | 64.71 |
| (14.77) | (14.89) | (14.76) | (14.93) | (14.93) | (15.00) | (15.07) | ||
| COG | 88 | 61.94 | 62.03 | 62.44 | 62.55 | 62.73 | 62.99 | 63.16 |
| (12.54) | (12.92) | (13.26) | (13.36) | (13.37) | (13.38) | (13.49) | ||
| Diff (CL at 95%) p (interaction) | > 0.001 | 1.89 | 1.85 | 1.82 | 1.76 | 1.74 | 1.74 | 1.55 |
| Mean BMI (SD) | ||||||||
| MOG | 89 | 24.84 | 24.86 | 24.99 | 24.99 | 25.06 | 25.16 | 25.16 |
| (4.76) | (4.84) | (4.82) | (4.88) | (4.87) | (4.93) | (4.93) | ||
| COG | 88 | 23.75 | 23.78 | 23.92 | 23.96 | 24.04 | 24.14 | 24.19 |
| (3.82) | (3.93) | (4.02) | (4.04) | (4.10) | (4.08) | (4.09) | ||
| Diff (CL at 95%) | 1.09 | 1.08 | 1.07 | 1.03 | 1.02 | 1.02 | 0.97 | |
| p (interaction) | > 0.001 | |||||||
TABLE 6:
Linear mixed effects model showing the differences in anthropometric parameters between MOG and COG over the study period.
| Estimates of Fixed Effects | |||||||
|---|---|---|---|---|---|---|---|
| 95% CI | |||||||
| Parameter | Estimate | Std. error | t | Sig. | Lower Bound | Upper Bound | |
| Intercept | 61.92 | 1.47 | 42.02 | 0.0001 | 61.43 | 63.65 | |
| Weight | MOG | -0.05 | 0.08 | -0.59 | 0.5556 | -0.20 | -0.11 |
| COG | 0 | 0 | - | - | - | - | |
| Intercept | 23.73 | 0.47 | 50.98 | 0.0001 | 23.61 | 24.32 | |
| BMI | MOG | -0.02 | 0.03 | -0.65 | 0.5145 | -0.08 | -0.04 |
| COG | 0 | 0 | - | - | - | - | |
FIGURE 1:
Flow chart of participants.
Acknowledgments
The authors wish to acknowledge all the patients who participated in this study. We wish to acknowledge and convey our sincere appreciation to the management and staff of Dala Foods Nigeria Limited, Kano State, who assisted in producing the interventions. Lastly, we wish to acknowledge Marothi Peter Letsoalo of the Centre for the AIDS Programme of Research in South Africa (CAPRISA) and Tesleem K. Babalola for assisting with the statistical data analysis.
Funding Statement
Funding sources. This study has been funded by the Department of Science and Innovation of South Africa. (Contract No. DST/CON 0196/2011) and College of Health Sciences, University of Kwazulu- Natal, Durban, South Africa.
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