How does prolonged use of HAART a risk factor for obesity and overweight in people living with HIV/AIDS?
Obesity and overweight are defined as a condition of excess accumulation fat in the body to the extent that some of the body physiological functions can be greatly affected (Johnson et al., 2014; WHO, 2016; Crum et al., 2010). BMI (Body Mass Index) has been used an indicator to classify obesity and overweight by the World Health Organization. Having a BMI of 25 to 29.9 kg/m2 qualifies a person to be categorized as overweight, while a BMI of ≥30 kg/m2 is classical obese. However, overweight and obese are mutually exclusive as an obese person can also be overweight (WHO, 2016; Marks, 2016). Obesity and overweight can be such complex, it’s a multifactorial chronic disease and it cuts across the socio-demographic.
After the invention of highly active antiretroviral therapy (HAART), it’s evident that wasting is no longer hallmark among the HIV infected persons. This is with the exception that studies have linked HAART with a side effect such as peripheral lipoatrophy consequently people living with HIV/AIDs gaining weight. 63% of HIV-infected involved in a cohort study were found to be overweight or obese that was high rate compared to previous studies (Crum et al., 2008), the was supported by other studies that have established that obesity greatly impairs glucose metabolism. According to (Koeth et al., 2016) there exists a relationship among HIV infection and change in lipid metabolism, greater circulating ICAM-1, VCAM-1, and CD4, this was compared to HIV-uninfected controls after adjusting for age and other factors. However, the study determined that there was little effect on dyslipidemia and endothelial activation HIV- infected individuals on HAART. The finding by (Koeth et al., 2016) are supported by other published studies. For instance, a study conducted by Crum and colleagues determined that there was a relationship between HIV infection and weight gain.
The research was conducted by comparing patients with HIV infection who are overweight/obese to those underweight/normal weights. The research findings revealed that those individuals who are underweight/normal weights had probably added weight during HIV infection (Crum et al., 2008). Moreover, Crum and his collogues noted that the individuals who experienced reduced weight at the time of infection with HIV, the infected persons had their high BMI during the baseline and were categorized as obese/overweight, however, the individuals who added weight had high probability of being underweight or normal weight during first HIV diagnosis.
Research done by other scientists focused on the demographics to determine the relationship between HAART and weight gain or obesity. For example, a cohort study focusing on women was commissioned and done by Women interagency HIV Study (WIHS), the research reported that 40% of the women who were normal during the time of initiation to HAART ended up being overweight and 47% of the overweight women became obese after being introduced to HAART (Sharma et al, 2014). But it’s worth noting that there has been no consistency in the findings of published studies that focuses on the relationship between HAART and weight gain, hence more researchers have always developed an interest to carry more research using different approaches in order to achieve more information. A study conducted using cross-sectional study design involving HIV infected individuals revealed that 65% of the individuals were overweight or obese according to (Crum et al, 2010). It’s not possible to compare the findings from the study done by Sharma and colleagues and the other conducted by Crum, one the two studies used different study design Sharma used a cohort study design while Crum and his friends used a longitudinal study design. Moreover, the study conducted by Sharma et al., focused on women whereas the study by Crum and colleagues both men and women were recruited into the study.
According to (Leite et al, 2010) the thymidine analogs was found to have a greater effect on BMI by reducing its higher odds, at the same time a greater likelihood of BMI increase was associated with use of PI (Protease Inhibitor) and NNRTI (Non-Nucleoside Reverse Transcriptase Inhibitors) in the study the analogs were found to have effect adipose tissue besides the agents were associated to lipoatrophic. However, the same study by Leite suggested that the use of HAART may be antagonized by the cross-reaction effects of Protease inhibitor(PI) and NNRTI used on the BMI change. The female participants who stop the use of HAART at the final hospital attendance had a low chance of increase in weight as indicated by high BMI, hence this clearly demonstrated that HAART didn’t contribute so much to enable change in the BMI (Boodram et al., 2016; Leite et al, 2010). This was a cohort study which focused on women thus the study findings cannot be used to make a generalization to HIV-infected by men who are part of the community.
Researchers have established the relationship between reduced HIV infection severity among them, increased the CD4 count, reduced viral load and increased odds of higher BMI category as suggested by (Boodram et al., 2009). Findings from other studies have suggested that women who have well managed HIV through treatment using ARVs were found to have increased BMI, this was contrary to individuals at the late stages of HIV/AIDS, the change in BMI could then be attributed to unrelated factors other than HIV disease, such as poor diet, lack of physical activities. However, most of the study failed to identify those confounding factors.
Research Law And Ethical Considerations
Ethics as used in research has been defined as a set of values and standards that have been adopted by the scientific community to regulate research activities according to (Miller et al., 2012; National Committee for Research Ethics in the Social Sciences and the Humanities (NESH) booklet, 2004-2005). Research ethics are found in guidelines at the same time embedded in law hence research ethics and law overlap. For example, it is illegal to recruit an individual to a study that can cause harm and suffering to them, the same action is deemed unethical considering research ethics guidelines. Research guidelines are not enforced by any kind of formal power, but when researchers go against any research guideline that is entrenched in the law then they can be prosecuted.
Medical and social scientist researchers over the years have continued to develop and improve ethical standards to govern the process of research since the first international code was agreed upon and adopted referred as (Nuremberg code,1947). After Nuremberg trial attention was directed to relationship between the researcher and their participants, the code highlighted 10 key principles to be adhered to when conducting research, and the emphasis was on voluntarism and written consent. The accepted ethics standards are meant to protect the participants, and researchers.
National Committee for Research Ethics in the Social Sciences and the Humanities (NESH), formulated guidelines to be followed and maintained during the entire research process: First, research ethics, freedom of research and society, the researchers are required to observe ethics standards such as impartiality and honesty among others at the same time, researchers are required to recognize and protect independent research. Another important area as highlighted in the NESH guideline is the respect for participants taking part in the study. Researchers are required to ensure the following: ensure freedom and self-determination; guarantee privacy and confidentiality to the participants; safeguard against harm and suffering according to (NESH booklet, 2004-2005).
The researchers should avoid undue intrusion, this is a key element that the researcher should consider before embarking on a research. First, the researcher should be able to determine whether the research findings will add any value to the already known information in the research area, assess if the research objectives will be attained using the taken approach taken. At the same time, the researcher should avoid processes that will subject participants to unnecessary suffering.
Informed consent in the context of research is document that prove willingness of an individual to take part in a research. It is a requirement that the participants should be given adequate information about the research, the language used in the consent form should be simple and clear to enable participants to make decision willingly about their participation in the study.
Consent of archiving data is another fundamental issue with regards to research ethics. For example, most of the researchers make their data set available to the entire research community by archiving them in the database, and without proper consent from the study participants, this can be matter of a great concern. The participants should be empowered to enable them to make decision on the data storage after the research is done. There are issues to consider including: how long should the participant’s information be kept before a fresh consent is sought from them to enable further storage? should the details identifying researcher be removed from the recording? Under the guidelines of the researcher are under the obligation to prevent the re-use of identifiable data collected during one particular research and such data can’t be used for administrative or commercial purposes according to (Miller et al., 2012).
There are regulations that governs the recruitment of children as participants in research. Several countries have ratified UN convention on the rights of children, which contain clause highlighting children right to participation. This empowers children on their right to be consulted, right to information, and challenge decision that is made on their behalf this is according to (Alderson and Morrow, 2011; Morrow and Richards, 1996). Researchers should ensure that the children are protected from the risk of distress or humiliation, the best approach to this is by listening to children opinion on what worry them most. When children under the age of 15 are recruited into the study a written consent from the parent is a requirement (Dickson-Swift et al., 2008).
- Cross-sectional Research Design
Cross-sectional Design is aimed at finding the prevalence of the problem, the phenomenon by taking snap-chat or cross-section of the population according to according to (Eriksson et al., 2015). For example, social scientist can use it to determine demographic characteristics of a population (parameter). However, these studies require direct contact with study population. For the health researchers, cross-sectional studies are used to determine the burden of disease or health problem of a study population the study findings can then be used to inform public health policies (Public Health Action Support Team (PHAST), 2011). According to (Creswell, 2013; Neuman, 2006), there are two types of cross-sectional design: descriptive design that purely determine the burden of a specific disease in the defined study population; Analytical cross-sectional study that is used to determine the risk factor and the outcome. According to (PHAST, 2011), the risk factor and association are measured simultaneously, hence making it difficult to assess whether exposure proceeded or followed the disease.
When conducting, research using this design it is highly required to carry out pre-test/Post-test to assess the change in a situation or a problem. This design has three feature: no time dimension; groups are recruited based on the differences that already exist but based on randomization. The design is restricted to measuring the difference change in the sample population rather than a process of change observed this is according to (Robson and McCartan, 2016; Green and Thorogood, 2013). Hence, findings from the cross-sectional study can only be used for making causal inferences using relativity passive approach.
This Design is an observationally based research just like cross-sectional, hence no intervention required from the researcher according to (Plano et al., 2015). However, the researcher is required to collect data on the same subject over a period lasting for many years, the hallmark of this design is that the researchers are able to observe and record changes in the characteristics of the study population according to (Endedijk et al., 2014). Longitudinal study design can be used by social scientist to determine the cause-and-effect relationships contrary to a cross-sectional study which lack this ability due to its scope. Therefore, the researchers using a longitudinal design in their studies can predict the feature outcome based on the earlier determined factors.
According to (Johnson et al., 2013), experimental design is a blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. when using, experimental design has clearly specified treatment group and control group (Green and Thorogood, 2013). Experimental design must have randomization, has a control group, and manipulation is done by the researcher. There are different types of experimental design such as randomized block design, randomized control trial, matched pair design, between subject design and Quasi-Experimental Design among others (Creswell, 2013). In this design, the researcher separates the sample into homogenous blocks, thereafter treatment is then randomly assigned to each block. Samples within the block should have greater variability compared to sample between the block. For example, units can be grouped in terms of Male or female with each in its own block according to (Johnson et al., 2013; PHAST, 2011). In randomized controlled trial participants are randomly two or more groups to test treatment. However, all the participants have equal opportunity to be placed in either group. The experimental group is subjected to treatment and the outcome is observed.
Social and health scientist using experimental research have the advantage of identifying cause and effect relationship. Besides, the researcher using this design can limit the alternative explanations and infer causal relationship in the study, the approach also provides the highest level of evidence for as single study according to (Johnson et al., 2013). However, the experimental design also has some setback first the design is artificial hence the results may not be generalized well to the real world, artificial manipulation may also alter the responses of participants (University of Southern California Libraries, 2016).
The design is mostly used by medical scientists and social scientist for research purposes. The research is carried out in a period, units who are representative of a population are recruited in the study (University of Southern California Libraries, 2016). The researchers using this design collects data by observation, there are two types of cohort study namely open and closed.When a researcher is using open cohort it’s worth noting that the individual participants can withdraw their participation at any time and the entry of another individual is allowed at any time. It’s only possible for the researchers using open cohort design to calculate rate based data for example incidence rate. While in closed cohort study design, the participants have defined time for recruitment, it is expected that there is no recruitment of new participants into the study after it’s onset, therefore, the study population remains the same throughout the study. Therefore, for the researchers who studies risk factors its recommended to use cohort study design that can be relied upon. This is because cohort studies measures can establish that these causes preceded the outcome in a study, and thus, it is possible for the researcher to explain difference between the cause and effect. Cohort studies are flexible and can establish effect over-time related to different changes in political, social and economic. Research done using cohort study design may have limitations that include lack of control on confounding factors in the study, at the same time it’s not easy to perform sample randomization in cohort studies making external validation difficult.
Probability Sampling Method
It’s a sampling process where every unit within the sample population have a fair chance of being selected and the probability can be determined accurately. This can also be referred as equal probability selection according to (Cohen et al., 2013). The method includes:
Every member of the population has a fair chance to be selected and thus eliminating bias. However, the sample frame is required (Gall et al., 2003). Researchers can adopt this method when selecting samples from a homogenous and small population. The sampling is achieved by assigning numbers to each unit in the sample frame. Since there is no control of the distribution of the sample, some samples may be poorly distributed this makes it undesirable sampling technique according to (Becker, Bryman and Ferguson, 2012; Creswell, 2002). Some of the advantages of using this sampling method include estimates can be calculated easily, besides units within population having equal probability selection enabling statistical inferences. However, simple random sampling also has some short coming it is not possible to use this method if the sample frame is large, at the same time minority subgroup may be small in number
- Systematic Samplingmethod
The method is often used when elements can be ordered or listed in a manner. The element is selected at every identified position may be every 10th is selected but the first selection is done randomly (Creswell, 2013).
Just like simple random sampling, systematic sampling is an equal probability sampling method, this is because all the elements have the same probability of selection. In systematic sampling, a different subset of the same size has different selection probabilities this feature distinguishes it from simple random sampling. Systemic sampling enjoys good geographic distribution according to population density besides its easy method to apply according to (Cohen et al., 2013). Meanwhile, systemic sampling method has some disadvantages for example if hidden periodicity is hidden in the study population coincides with that of selection then bias can be introduced during the sampling process. The Sampling may be biased if hidden periodicity in population coincides with that of selection, besides it may be difficult to assess the precision of estimate from just one survey.
It is used by researchers where study population, possesses distinct categories, the elements can be separated into subgroups called strata, thereafter the elements are randomly selected from each subgroup (Cohen et al., 2013). However, every element in the stratum has an equal chance of being selected, proportionate representation is ensured by using the same sampling fraction for all the strata. To ensure adequate representation of the minority subgroups of interest in the study population stratification and varying sampling fraction between the strata is required. Stratified sampling has certain impediments. First it requires sampling frame for the entire population to be prepared differently for each stratum, secondly in some cases stratified sampling can potentially require a large sample as compared to other sampling methods.
Data Collection Methods
It defined as having a conversation between two or more individuals where in that conversation certain questions are asked by the interviewer to get response from the interviewee (Bilsborrow, 2016). This is an alternative method to survey, when using this approach the interviewer can reduce non-response, at the same time the clarification about certain confusing questions can also be made making this approach very friendly to the interviewee. This is a good approach to gather information from busy individuals or individuals who cannot read and write within the community. According to (Lewis, 2015) this method is important in that the researcher can gain more insight the context of the topic and useful to gather stories and quote from the community. However, the approach can face certain challenges that include vulnerability to bias introduced due to interviewer’s personal influence, it can be time consuming with high cost implications, and at some time seem intrusive to the interviewee especially if the questions are very sensitive.
This data collection method can be achieved in different ways:
Face-to-face interviews can help a researcher establish a good relationship with the interviewee and hence have opportunity to clarify his opinion about the certain responses, at the same time high response rate can be achieved when this method is used.
The other approach is through telephone interview, the method is less costly and time taken is less. However, the method is prone to bias this is because not every member of the population has a phone hence some it is not possible for every member to have equal opportunity to be interviewed. The response rate from the members of the population is low, this is because not every member of the population will create time for phone conversation.
Computer Assisted Personal Interviewing (CAPI) has same attributes as face to face interview the only difference is that laptop or tablets are used to fill the responses from the respondents instead of paper questionnaire. This approach has some advantages that include reduced time involve in processing data.
This is a method preferred by many researchers, its direct observation on the ongoing activities, processes and workflow in real world. This method has certain advantages such as it does not rely on the respondent’s willingness for answers unlike when using interview or survey approach. At the same time the researcher rely on seeing rather than relying on whatever is said by the respondent. However, this method has setbacks when used to collect data it is vulnerable to bias introduced by the researcher through wrong observations, at the same time people can behave in a manner when under observation this does not reflect the true picture when individuals are not under any observation according to (Bilsborrow, 2016).
This method is very important when intention is to gather information that is deemed difficult to obtain using other data collection methods. Researchers have defined focus group as gathering of individuals with certain characteristics and can provide information of qualitative nature in focused discussion and the group is composed of about six to twelve individuals, the group should be small enough to allow for participation of each member in the group (Saczynski, 2013). Perceptions and views on certain topics are probed by trained moderators and this should be done without pressure. Some of the advantages of this method is that outcomes can be achieved easily, the cost of conducting focus group discussion is cheap as compared to surveys and personal interviews. However, this data collection approach has limitation such as its difficult to put together the group and people may be influenced by the presence of peers when answering specific questions.
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