Emerging Technologies

Mobile Health Interventions to Enhance Self-Management of HIV and Non-Communicable Disease in Sub-Saharan Africa: A Systematic Literature Review

Citation: Kiplagat, A., Kako, P., Hawkins, M., Luo, J., Langat, B., Ngui, E., Kanari, C., Dressel, A., Kibicho, J., Cho, C., Mkandawire-Valhmu, L., & Weinhardt, L. (2023). Mobile health interventions to enhance self-management of HIV and non-communicable disease in Sub-Saharan Africa: A Systematic Literature Review. Online Journal of Nursing Informatics (OJNI), 26(3). https://www.himss.org/resources/online-journal-nursing-informatics


Objective: The purpose of this review was to better understand mobile phone-based self-management interventions for adults living with human immunodeficiency virus (HIV) HIV and/or non-communicable diseases (NCDs) specifically hypertension and diabetes, in Sub-Saharan Africa (SSA), identify gaps, and recommend improved interventions.  

Methods: We conducted a literature review and synthesis of peer-reviewed intervention studies conducted in SSA spanning a 10-year period between 2011 to 2021.  For the review, we examined evidence of mobile health interventions and identified gaps related to mobile health (mHealth) tools in self-management behaviors related to HIV, hypertension, and diabetes in SSA.

Results:  Out of 28 articles reviewed, only 12 (42.8%) were guided by a theoretical framework, which demonstrates the need for stronger theoretical frameworks and rigor for HIV and NCD interventions studies in SSA.

Conclusion: Our comprehensive review indicates that mHealth interventions in SSA lack a robust and standardized approach

Practice Implications: Mobile phones access in these regions has increased opportunities for greater access to much needed health information for patient centered self-management. mHealth research grounded in sound theoretical frameworks that are context specific are needed in SSA. Research focused on mHealth should also consider the inclusion of people living with disabilities. 


Chronic human immunodeficiency virus (HIV) and non-communicable diseases (NCDs), notably hypertension and diabetes, are increasingly becoming major public health concerns for the adult population in sub-Saharan Africa (Hebe et al., 2019) . As per recent estimate, 59% of all people living with HIV live in Sub-Saharan Africa (SSA) while hypertension has a prevalence of 31.1% and diabetes has 15% prevalence in adults aged 25-64 years (Bosu et al., 2019; UNAIDS, 2010; WHO, 2021). In SSA, the incidence of NCDs is increasing rapidly while HIV has transitioned to a chronic disease, placing a growing burden on already stretched healthcare systems in the region (Opoku et al., 2017). The double burden of chronic HIV and NCDs in the context of limited healthcare resources calls for culturally relevant, patient-centered self-management interventions.  In SSA, the use of mobile technologies and their applications among the adult population is continuously rising with approximately 86% of adults owning a cellphone, therefore expanding opportunities for implementation of mobile phone-based health interventions, which are cost effective and widely accepted by the target populations (Betjeman et al., 2013; GSMA, 2020). Low-cost mobile phone-based self-management interventions have appeal for users, as well as researchers, practitioners and policy makers who want to employ this technology to reach large target populations. The World Health Organization (WHO) has proposed further development and more widespread use of mobile health (mHealth) interventions for the prevention, management, and treatment of NCDs and their risk factors as part of its Global Action Plan for the prevention and control of NCDs (Opoku et al., 2017; WHO, 2013). As well, mHealth tools can fill urgent needs to aid in self-management and social support during the limited access to in person services due to the COVID 19 (Wion & Miller, 2021).

The purpose of this study was to better understand mobile phone-based self-management interventions for adults living with HIV and or NCDs, specifically hypertension and diabetes, in SSA, to identify gaps, and recommend further tailored interventions. The articles reviewed focused on health interventions in individual self-management of HIV, diabetes, and hypertension. The low cost of mobile interventions compared to the traditional in person care has appeal for users and researchers, practitioners, and policy makers wishing to employ this technology to reach large target populations as a cost-effective health intervention. The review of mobile health interventions in self-management support of HIV and NCDs in SSA is scant.  Past reviews have mostly focused on Western or Asian countries and the few targeting SSA are non-specific to self-management interventions for individuals living with HIV, diabetes, or hypertension (Aranda-Jan et al., 2014; Barsky et al., 2019; Betjeman et al., 2013; Chang et al., 2011).


Mobile phone health interventions are increasingly being used for the prevention and care of HIV, hypertension, and diabetes in SSA (Opoku et al., 2017). Although phone-based interventions have typically used the voice or text-based Short Message Service (SMS) features of mobile phones, the increasing availability and popularity of smartphones and smartphone applications (apps) has greatly expanded the possibilities for phone-based HIV interventions in SSA (Holloway et al., 2017; Mangone et al., 2016; Njoroge et al., 2017). mHealth interventions are critically important in the self-management of chronic diseases because of its ability to reach a large segment of the population cost-effectively, thus improving the quality of life particularly among adults who carry the highest burden of chronic disease and at the same time constitute the highest rate of users of mobile and smartphones in SSA.
mHealth, or mobile health, refers to the use of mobile smart or portable devices for health services and information while eHealth, or electronic health, refers to healthcare services provided with the support of information and communication technology (ICT) such as computers, mobile phones and satellite communications for health services and information (Moss et al., 2019). The mobile health (mHealth) interventions are preferred to electronic health (eHealth) interventions due to the high geographical coverage of the mobile network particularly in SSA countries (Free et al., 2013). The cost of setting up mHealth systems is considerably low compared to eHealth and ICT systems that require healthcare system and organizational stakeholder’s facilitation (Aranda-Jan et al., 2014; Lemaire, 2011). Mobile health-driven initiatives provide easy accessibility to self-management interventions at any location with minimal resources. The most frequently applied features are mobile text messages (SMS), software applications (app), and multiple media interventions (Aranda-Jan et al., 2014; Njoroge et al., 2017). Mobile health SMS communication entail a simple short message on behavior change targeting a particular population or a message about clinical information to healthcare providers (Forrest et al., 2015; Lester et al., 2010; Njoroge et al., 2017). There is an urgent need to understand efficacious self-management of mHealth interventions for HIV and NCDs in low- and middle-resource countries such as those in SSA. Systematic reviews of mHealth self-management interventions in SSA are urgently needed to fill this gap.



This systematic literature review was conducted using peer-reviewed articles published in the 10-year timeframe between 2011-2021. The search terms included mHealth, telehealth, telemedicine, telenursing, eHealth, smartphone, cellphone, mobile device, mobile phone, Kenya OR Sub-Saharan Africa, hypertension, OR diabetes, OR noncommunicable disease, OR chronic disease, OR heart failure, OR heart disease, OR cardiovascular disease. We employed an electronic search for relevant articles, such as, "mHealth interventions in HIV and chronic disease management in Sub-Saharan Africa.”  We searched reference lists in relevant articles to facilitate the process of identifying additional relevant articles. Based on the options displayed in the databases, keywords were sought in the entire text and not only in the titles or abstracts.

Search Methods

A systematic search was conducted using Clinical trial.gov, PubMed, CINAHL, Web of Science, and Global Health. Google Scholar was also searched, as well as the Republic of Kenya Ministry of Health website using specific terms and key words. The systematic review was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Liberati et al., 2009).

Inclusion Criteria

Specific criteria for inclusion included studies that were published between 2011 and 2021, written in English, and focused on mHealth interventions for self-management of HIV and NCDs including diabetes and hypertension in SSA. The studies had to have been published in peer-reviewed journals and had to have documentation of the methodology used in data collection and analysis.

Search Outcome

By applying the PRISMA guidelines we first identified and gathered all articles from the seven databases including the Kenya Ministry of Health website. The literature review process and initial write up of results was conducted by the first three authors (AK, PK, MH) with consensus from all authors.  The eligibility criteria for inclusion were: (1) Research articles conducted in SSA countries; (2) Discussion or documentation of health interventions in chronic disease self-management focusing on HIV, diabetes, and hypertension; (3) Utilization of mobile or smartphone phone technology in chronic disease self-management with a focus on HIV, diabetes, and Hypertension; (4) Peer-reviewed original publications; and (5) English-language articles. From this initial search, 366 articles were retrieved.

After screening the 366 articles, 221 articles were excluded because they fell outside the SSA region. That left 145 articles remaining for the eligibility assessment stage. Out of the 145 articles, 117 were assessed and found not eligible due to lack of focus on mHealth interventions for self-management of HIV, diabetes, or hypertension; or they merely addressed interventions without description of a clear methodology. Finally, 28 studies that met the criteria were synthesized for the purpose of this review. Included articles were fully read and assessed for quality and appropriateness for the study. Figure 1 is the PRISMA flow chart that depicts how the articles were selected. Details of the 28 articles selected for the review are catalogued by year, author, country, research question or hypothesis, design, and findings as shown in Table 1.

Table 1: Published studies of Mobile Health Interventions to Enhance Self-Management of HIV and Non-Communicable Disease in SSA.

Quality Aassessments

The quality of each article was assessed by consensus of the first three authors (AK, PK, MH) and deemed to have met the following conditions: (1) Appropriateness of research design; (2) Appropriateness of overall method and analysis procedure; (3) Generalizability of research findings to the target population from which the sample was drawn; (4) Relevance of the study's purpose in addressing questions raised in the review; and (5) Trustworthiness of study findings in relation to the focus of our review.


Our review of the published literature identified 28 interventions focused on chronic disease self-management of HIV, hypertension, and diabetes in SSA, published between 2011 and 2021. The characteristics of the individual studies are reported in Table 1 and a summary of the interventions and categories are shown in Table 2. Out of 28 articles selected for review 18 (64.3%) were randomized control trials and 10 (35.7%) were other intervention studies (non-randomized control trials, an uncontrolled pilot study, a cohort study, and pre/post-test studies). The 28 studies took place in seven countries in SSA (Kenya, Tanzania, South Africa, Nigeria, Cameroon, Ghana, and Malawi). The total number of participants in all 28 studies was 9,209. In the studies that reported participants’ gender, there were more females (72%) than males (28%). Six studies did not report participants’ gender distribution.

Six theoretical frameworks guided these studies. Five studies (17.8%) were guided by behavior change and communication theories (Aunon et al., 2020; Leon et al., 2015; Owolabi et al. 2019; Ronen et al. 2018; John et al., 2016), three studies (10.8%) by Technology Acceptance Theory in mHealth interventions (Smillie et al. 2014; Nichols et al. 2019; Sarfo et al. 2019). Other theories mentioned included Self-determination Theory in one study (3.6%) (Sarfo et al. 2019), Appreciative Qualitative Inquiry in one study (3.6%) (Fry et al., 2020), Self-Regulation Theory in one study (3.6%) (Sarna et al., 2019), and Applied Entertainment Education Communication Theory in one study (3.6%) (Winskell et al., 2018). Sixteen studies (57.1%) did not identify or mention a theory or theoretical framework that was used to guide their studies.


Articles included in the review showed that the main themes of mHealth interventions were to improve desired behaviors and outcomes related to HIV prevention, Antiretroviral Therapy (ART) adherence, and retention of care/follow-up, hypertension control, medication adherence and complication prevention, diabetes prevention, medication adherence and complications prevention, and general patient management and referral through teleconsultation. Details of these themes were synthesized as part of this review.

HIV prevention, ART adherence, and retention of care (12 studies)

Most articles on HIV self-management focused on Antiretroviral Therapy (ART) adherence, HIV prevention, and retention, reported in 43% of the studies reviewed. Nine of the studies utilized text message interventions with the option of communicating with a healthcare provider.  One study offered a call option from the healthcare provider to offer counselling (John et al., 2016), and two studies utilized smartphone applications to provide HIV information and ART adherence messages (Ivanova et al., 2019; Winskell et al., 2018). The information, motivation, and behavioral (IMB) skills framework was used and tailored to influence medication adherence through text messaging (Aunon et al., 2020; Barsky et al., 2019; Winskell et al., 2018). The impact of SMS programs on adherence has been studied in multiple randomized controlled trials (RCTs), which have generally demonstrated improved adherence and viral suppression especially when the message is customized to the participants’ local language and confidentiality was assured (Aunon et al., 2020; Georgette et al., 2016; Leon et al., 2012; Lester et al., 2010; Smillie et al., 2014).  

ART adherence is noted to be increasing among emerging adults (15-24 years), which are arguably the most dynamic and challenging group of populations living with HIV (Ivanova et al., 2019; John et al., 2016). A study in Kenya found that ART adherence improved in all young adult participants after three months of mobile phone messages (Ivanova et al., 2019). As access to the internet and smartphones in SSA is growing, these types of interventions hold great potential and warrant further research grounded in solid theoretical frameworks. Out of the 12 articles focusing on HIV self-management using mHealth, only half (n=6) were reported to be guided by a theoretical framework or combinations of more than one framework. The theoretical frameworks guiding the six articles included Information–Motivation–Behavioral Skills (IMB) framework, Trans-theoretical Model (TTM), Behavior Change Communication theory, Self-Regulation Theory, Theory of Reasoned Action, Technology Acceptance Model, Applied Entertainment-Education communication, and Social Cognitive Theory. Most interventions through mobile phones targeted women and young girls (Aunon et al., 2020; Pop-Eleches et al., 2011; Ronen et al., 2018; Sarna et al., 2019). In addition to mHealth interventions, some studies focused on Electronic Medical Records.

The adoption of Electronic Medical Records (EMR) is associated with high quality data for clinical decision making and better healthcare workers compliance with clinical guidelines on initiation of antiretroviral therapy (ART) among ART-eligible HIV patients leading to effective patient follow-up and retention of care (Castelnuovo et al., 2012). A study conducted in Kenya reported functional EMR systems were associated with appropriate placement and documentation of HIV patients on ART in resource limited settings (Oluoch et al., 2014).

Hypertension control, medication adherence, and complication prevention (8 studies)

Blood pressure management and control was reported in 28% of studies reviewed. 75% of the studies reviewed under hypertension self-management utilized a text message intervention with tele-consultation follow-up with the primary care provider; and the remaining 25% utilized smartphone applications for monitoring and tracking blood pressure. A study in Tanzania on blood pressure self-management and medication adherence noted that communities and participants in the study needed to be involved in providing input into development of the messages to ensure the study was tailored to the local language and culturally-appropriate (Barsky et al., 2019). 

mHealth interventions can also be beneficial for most people with physical disabilities because they have numerous health conditions or risks unique to disabling conditions that would benefit from mHealth apps and minimize travelling long distances to see a healthcare provider  for needs that could otherwise be addressed via text messaging or mobile apps (Haricharan et al., 2017; Jones et al., 2018). Studies have also demonstrated that people who are deaf can effectively use text messaging systems for self-management, for example, SMSs were effective in improving deaf people’s knowledge of hypertension and healthy living. However, SMSs need to be tailored to accommodate the unique communication needs and preferences, and to explore how to accommodate these needs and preferences among deaf or  other special categories of people with physical and communication disabilities (Haricharan et al., 2017). Teleconsultation and text messaging is reported to facilitate management of diabetic complications, especially retinopathy, vascular, and kidney complications in rural settings where accessing a healthcare provider is usually difficult  (Kurji et al., 2013; Nanji et al., 2020)

Diabetes prevention, medication adherence and complications prevention (7 studies)

Blood pressure management and control was reported in 25% of studies reviewed, 71% of the studies reviewed under diabetes self-management utilized text message interventions with follow-up calls from healthcare providers; and the remaining 29% of the studies utilized tele-consultation by a remote healthcare consultant, with an on-site non-expert healthcare provider and patients to provide expert opinion of management and prevention of complications in diabetic patients in hard to reach and rural healthcare facilities.

Two studies conducted in two diabetic remote clinics in Kenya reported that patients preferred the teleophthalmology option for future ophthalmologic screenings compared to face to face screening as a cost-effective intervention in improving diabetic retinopathy screening (Kurji et al., 2013; Nanji et al., 2020). Specifically, on participant experience, patients were satisfied with the information they received from the teleophthalmology nurse with less consultation fees compared to the in-site consultant ophthalmologist visit. They did not see any reason for seeing an in-person ophthalmologist when the teleophthalmology nurse could address their issues via the telemedicine arrangement (Kurji et al., 2013). Furthermore, patients said they preferred to use teleophthalmology as their method of choice for future diabetic eye screenings, citing the time saved, convenience, and ability to view the inside of their eye (just like the ophthalmologist sees) as reasons that they favored the use of teleophthalmology.

The six studies that used text messaging for diabetic self-management showed that diabetic patients were comfortable with the idea of receiving health promotion-related messaging on their phone but wanted a way to easily distinguish health messaging from spam messages (Leon et al., 2021; Webb & Rheeder, 2017). Participants also wanted the messages to be customized to include an option of receiving messages in their first language and to avoid medical jargon so that they could easily understand the text message (Leon et al., 2021; Webb & Rheeder, 2017). Findings showed that glycemic control, increased confidence in self-care, as well as reduction in diabetic complications improved dramatically with a dedicated intervention team (Rotheram-Borus et al., 2012). Importantly, however, text messaging was not always an effective intervention.  For example, a study conducted in South Africa reported that a text messaging intervention did not bring about any significant improvement in medication, dietary, or physical activity adherence levels, and suggested the need to design more effective strategies for improving adherence to recommended lifestyle changes in this setting (Owolabi et al., 2019).

General patient management and referral through teleconsultation (1 study)  

One study focused on a networked referral management and clinical decision support in a smartphone application (Fry et al., 2020). The study was designed and implemented in rural Kenya where nurses and clinical officers (similar to physician assistants) were trained to document electronically, share non-emergency cases, and receive expert opinions from a network of remote physicians/consultants. In this study, the intervention app was reported to be beneficial by healthcare workers because it facilitated greater equity and efficiency in healthcare delivery, specifically facilitating equitable access to care, improving referral mechanisms, reducing healthcare delivery cost and time, and increasing access to data for decision-making (Fry et al., 2020).


Findings from our comprehensive literature review underscore the idea that mHealth interventions in SSA lack standardized approaches. Some mHealth interventions utilized text messages, others utilized more robust applications, such as physician interactions. These differing interventions highlight the need for clear articulation of what mHealth interventions entail to aid with future comparability of studies and in addressing gaps to improve mHealth interventions.  We examined multiple databases, spanning 10 years of literature, and only found 28 studies. This suggests that more robust research on mHealth interventions that are based on clear theoretical or conceptual frameworks are needed to aid in replicability, implementation, and translation of research, especially as cellphones, including smart phones are commonly being used in SSA.

There was inconsistency with the use of theory or theoretical frameworks to guide interventions. To inform a study, a theory or conceptual framework is important for demonstrating the causal pathways and links between constructs, and to aid in replication, implementation, and translation (Glanz et al., 2015). Theoretical underpinnings are particularly important for mHealth interventions to aid in better understanding of the linkages between mHealth and behavioral decisions. Future mHealth intervention studies should thus consider strong theoretical underpinning.

However, while having a theoretical underpinning for mHealth studies is important, our review findings showed a range of theories were utilized among the studies: Five studies applied behavior change and communication theories, and three studies applied Technology Acceptance Theory. Other theories utilized in the studies included Self-determination Theory, Appreciative Qualitative Inquiry, Self-Regulation Theory, and Applied Entertainment Education Communication Theory. The range of theories used can make comparisons between studies difficult. As Glanz and Bishop (2010) noted, explanatory and change theories, “…may have different emphases but are quite complementary.” (p. 401) Meaning, appropriate theories may be used to frame different studies for specific purposes. This underscores the importance not only of theory, but the review of previous literature to understand what theories were used and how they were used (i.e., causal, or explanatory), in order to further the effectiveness and comparability of mHealth intervention.

Moreover, the literature reflects that linguistic and cultural sensitivity are extremely important to ensure context-appropriate application of the proposed intervention. While there are some languages spoken across a number of SSA countries, such as Kiswahili, English, and French, there are numerous languages spoken in this region, and ensuring context applicability is essential (Maho, 2004). For example, the country of Zambia has seven national languages (Kula & Marten, 2008), exemplifying the wide diversity of cultures and languages within and across countries throughout SSA. Contrary to how it is often portrayed, SSA is far from homogeneous. Hence, interventions need to be devised and implemented with local partners to ensure that interventions are linguistically and culturally sensitive. This finding was explicit in the literature reviewed.

Our results show interventions were focused on an individual condition such as HIV, hypertension, or diabetes. Thus, mHealth interventions are lacking that are targeted at those facing multiple chronic conditions, such as diabetes and hypertension, as well as HIV/AIDS. Our study underscores the need for future studies to include the experiences of those with multiple chronic conditions, and how mHealth interventions can serve this growing population in SSA. Additionally, it is important to note that future interventions must address the complexity of having a mobile phone, while living in a community with limited access to electricity to charge it. Meaning, if future researchers plan on doing mHealth interventions using mobile phones, they should make sure that the phones can be regularly charged. The provision of charging devices, such as solar chargers for phones, ought to be considered in the development of mHealth interventions. Solar power, as it supports the United Nations Sustainable Development Goal #7, is emphasized throughout SSA  (Lee & Callaway, 2018). Access, however, due to factors like poverty and limited access to the electrical grid, hinder energy accessibility (Ulsrud, 2020). Therefore, future mHealth interventions ought to address lack of access to charge devices if they seek to truly facilitate mHealth interventions.

Our review also showed a paucity of literature around the use of mobile phones in chronic disease self-management for people living with disability. Future mhealth self-management interventions and research should pay attention to this important population especially because more people are living with non-communicable diseases such as hypertension and diabetes whose complications can be disabling. Jones et al (2018) highlighted the benefits of using mobile phones for people with physical disabilities to address numerous health conditions or risks unique to them. For example, text messaging can reach people with hearing impairment. People with mobility challenges can be reached using mobile phones which minimize travelling long distances to meet with the healthcare provider for a health issue consultation and advice. Interventions that promote maximizing use of mhealth tools for populations with disabilities are urgently needed.  While text messaging or even calling can be used to address health needs of people living with chronic conditions, further research on the use of mobile health in chronic disease self-management among people living with disabilities as a cost-effective intervention needs to be explored for more evidence-based interventions and recommendations.


Emerging evidence from our literature synthesis suggests that mHealth interventions may be a cost-effective option to improve HIV, hypertension, and diabetes self-management in SSA where the healthcare systems are not robust, and resources are limited.  The COVID 19 pandemic has underscored the importance of mHealth based interventions for people living with HIV to ensure sustained access to health care (Wion & Miller, 2021). Moving forward, the next-generation of mHealth programs must be customized to local settings and should be based on evidence-based behavioral theories and incorporate advances in ICT so that they can meet the target population’s unique and ever-changing needs.

Implications to Practice

Mobile phone access in these regions has increased so there are opportunities to increase access to much needed health information for patient centered self-management. mHealth research grounded in sound theoretical frameworks that are context specific are needed in SSA. Research focused on mHealth should also consider the inclusion of people living with disabilities. 

We are grateful to all colleagues and faculty who provided us with technical guidance and suggestions of review materials and reports during this literature review process.

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Author Biographies

Augustine Kiplagat, MPH, RN, PCCN, PhD Candidate
Associate Clinical Professor
Bon Secours Memorial College of Nursing, Richmond, Virginia, USA

Corresponding Author

Peninnah M. Kako, RN, PhD, FNP-BC
Associate Professor
College of Nursing, University of Wisconsin-Milwaukee
1921 E Hartford AV, Milwaukee WI. 53211

Maren M. Hawkins, BA, PhD Candidate
Joseph J Zilber School of Public Health, University of Wisconsin-Milwaukee, WI. USA

Jake Luo, PhD
Associate Professor
Department of Health Informatics and Administration
College of Health Sciences, University of Wisconsin, Milwaukee, WI. USA

Bernard Langat, M.B. Ch.B., MSc.
Programme Director (HIV, TB, Malaria and NCDs)
African Medical Research Foundation, Kenya

Emmanuel Ngui, DrPh 
Associate Professor,
Joseph J Zilber School of Public Health, University of Wisconsin-Milwaukee, WI. USA

Catherine Kanari, MD
Amref Health Innovations
African Medical Research Foundation, Kenya

Anne Dressel, PhD, CFPH, MLIS, MA
Assistant Professor
College of Nursing, University of Wisconsin-Milwaukee, WI. USA

Jennifer Kibicho, PhD, CPK(K)
Associate Professor
College of Nursing, University of Wisconsin-Milwaukee, WI. USA

Chi Cho
Associate Researcher, Statistician
College of Health Sciences, University of Wisconsin Milwaukee, WI.

Lucy Mkandawire-Valhmu, RN, PhD
Associate Professor
College of Nursing, University of Wisconsin-Milwaukee, WI. USA

Lance S. Weinhardt, Ph.D. 
Professor, Community and Behavioral Health Promotion
Joseph J. Zilber School of Public Health
University of Wisconsin Milwaukee, WI. USA