Council Bluffs Community University District in Council Bluffs, Iowa, utilized Panorama Scholar Surveys in 2017 as portion of their CASEL Social Emotional Studying initiative. Social Psychological Discovering continues nowadays in Council Bluffs Neighborhood College District.
Panorama and CASEL, or the Collaborative of Academic, Social, and Psychological Mastering are two big and influential training consultants.
In 2013 Panorama Education emerged nationally as a company that conducts “surveys of college students, mother and father, instructors, and staff” and “analyzes this details and offers academics and administrators with obvious and constructive feedback that they can use to boost their training and their educational facilities.”
According to TechCrunch.com, “Partners also participated in the financing, which delivers the Boston-based company’s full raised considering that its 2012 inception to $105 million.
Panorama declined to expose at what valuation the Collection C was raised, nor did it offer any precise financial advancement metrics. CEO and co-founder Aaron Feuer did say the firm now serves 13 million pupils in 23,000 educational facilities throughout the United States, which signifies that 25{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of American college students are enrolled in a district served by Panorama these days. “
The Collaborative for Educational, Social, and Psychological Learning, or CASEL, describes alone as a “trusted resource for information about higher-good quality, proof-dependent social and psychological understanding,” recognized as “SEL.” CASEL states it “supports educators and coverage leaders and improves the encounters and outcomes for all PreK-12 college students.”
Social Emotional Finding out is nevertheless taught in Council Bluffs Local community University District.
“Through essential notion issues and our Strategies to Mastering, our pupils grow to be inquirers in and outside the house of faculty. Focused time to Social Emotional Understanding (SEL) enables lecturers to instruct on self-management techniques and social abilities. At the end result of our Key Decades Programme, 5th graders carry out little group study tasks with a need to acquire action. It is a demonstration of the understanding acquired whilst in attendance at our school. It is our target to inspire our learners so they obtain the abilities to be internationally-minded and impactful world citizens.”
Community colleges in Council Bluffs Neighborhood University District have an regular math proficiency rating of 62{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} (versus the Iowa general public faculty common of 70{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf}) and examining proficiency rating of 55{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} (versus the 68{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} statewide regular).
There is ample research documenting the existence and persistence of mental health and mental health care disparities over the past several decades (1). For example, research consistently suggests that there are racial and ethnic differences in prevalence of some mental disorders (e.g., compared to non-Hispanic Whites, Blacks/African Americans have higher rates of diagnosed schizophrenia [2] and American Indians/Alaska Natives have higher rates of posttraumatic stress disorder [3]). Across diagnostic categories, racial and ethnic minority individuals have more severe and persistent impairment than non-Hispanic White individuals (4, 5). Similarly, compared to cisgender heterosexual individuals, sexual and gender minorities have higher rates of depression symptoms and suicidal behaviors (6). Despite efforts to address mental health and mental health care disparities, there remains a significant gap between our ability to document, investigate, and understand mental health disparities and their causes and to translate this research knowledge into interventions that meaningfully reduce disparities in clinical and health care outcomes.
The National Institute on Minority Health and Health Disparities (NIMHD) Health Disparities Research Framework (hereafter “the framework”) is intended to encourage a comprehensive approach to understanding and addressing health disparities with respect to race/ethnicity, socioeconomic status, sexual and gender minority status, and rural versus urban residence (7, 8). The framework, which is an extension of the socioecological model, consists of two dimensions: domains of influence on health (biological, behavioral, physical and built environment, sociocultural environment, health care system) that occur at different levels of influence on health (individual, interpersonal, community, societal). The individual cells of the framework each represent categories of potential determinants of health disparities and/or intervention targets to address health disparities.
Much of the focus in mental health disparities research, including research supported by the National Institutes of Health (NIH), has been either on single cells of the framework (e.g., individual-level biological determinants), single levels of influence (e.g., individual-level biological and behavioral determinants), or single domains of influence (e.g., lack of access to mental health care as the primary driver of disparities). However, this approach does not take into account the complex interaction of structural and social determinants of mental health that create mental health disparities. Thus, addressing mental health disparities requires research that explores factors at multiple levels of influence, particularly beyond the individual level. Such research should prioritize an understanding of how community, social, and structural factors, including structural racism and discrimination, impact individual-, community-, and population-level mental health outcomes. In addition, research that examines how domains and levels of influence interact across multiple levels (i.e., cell×cell interactions) is necessary to better approximate the real-world complexities of how interconnected determinants impact the mental health of individuals, families, communities, and populations.
To encourage mental health disparities research that uses a multidimensional approach and to provide researchers with a more tailored approach than other existing disparities frameworks and models, we offer an adaptation of the framework specific to mental health disparities (Figure 1). The examples provided within the cells of the framework are intended to be illustrative rather than exhaustive. This adapted framework is similar to other frameworks and models that describe social determinants of health (SDOH), such as those by the U.S. Department of Health and Human Services Healthy People 2030 (9) or the World Health Organization (10). What distinguishes this framework is that it includes both general SDOH and determinants that may be specific to mental health to promote a more comprehensive view of mental health disparities. In addition, the adapted framework emphasizes the simultaneous examination of both domains and levels of influence to provide an organizational structure with which to identify or conceptualize relevant determinants and generate appropriate strategies to address them.
FIGURE 1. An adaptation of the National Institute on Minority Health and Health Disparities Research Framework for mental health disparities
As a hypothetical example, suppose researchers and community partners wish to develop an intervention to improve help-seeking to address high rates of depression and posttraumatic stress disorder in a local Hmong population. The team views health literacy as the key feature driving low levels of help-seeking, but they also identify other relevant determinants, including lack of health insurance, food insecurity, lack of transportation, and lack of availability of Hmong-speaking providers. It becomes clear to the team that a health information–focused intervention alone is unlikely to result in improved help-seeking unless these structural barriers to accessing mental health care are also addressed. We are not suggesting that determinants in all cells of the framework must always be included to address health disparities, but we highlight the importance of examining the constellation of determinants relevant to the specific disparities being studied, and the need to intervene at the appropriate levels to have a sustained impact. The availability of a framework that emphasizes multidomain, multilevel determinants of health does not ensure that research approaches and interventions will successfully address mental health disparities—this depends upon how researchers and stakeholders apply and implement the framework.
Based on the concept of generations of health disparities research (11), we describe examples of three types of mental health disparities research in which the adapted framework may be implemented and that address SDOH. Note that research to document mental health disparities is not included here if does not also examine mechanisms or determinants of those disparities, or if SDOH are measured but included only as control variables in analyses. Although this research progression may be a natural evolution, we argue that the highly incremental research that has characterized much of the health disparities field is not necessary to replicate for mental health disparities, given that this foundational work is often relevant across health conditions and outcomes.
First Generation: Understanding How SDOH Cause, Sustain, or Mitigate Mental Health Disparities
This body of research moves beyond individual-level determinants of mental health disparities (e.g., lack of awareness of mental health problems, lack of health insurance) to identify higher-level social and structural factors that contribute to or mitigate health disparities. Factors such as family and community cohesion, population density, neighborhood-level disadvantage, neighborhood safety and community violence, community social climate, and community and national-level racism and discrimination have all been found to be associated with individual and community-level mental health symptoms and distress (12). This work is critical in identifying modifiable intervention targets that have potential to reduce mental health disparities. Because the social and policy landscape is constantly changing with respect to impacts on minoritized and marginalized populations, this work will always be needed. However, the current distribution, where most mental health disparities research reflects observational research to document and understand disparities, needs to be shifted more toward intervention and action. For example, a recent portfolio analysis conducted by the NIH Office of Disease Prevention of new NIH-funded extramural projects from fiscal year 2012 to 2019 (13) found that about two-thirds of prevention projects were observational, while randomized intervention studies accounted for less than one-fifth of projects, and this proportion declined over time. In addition, only 3.5{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of prevention projects included a randomized intervention to address a leading risk factor for death and disability in populations experiencing health disparities. Prevention research specific to mental health outcomes accounted for less than 8{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} of projects in fiscal year 2019 and mirrored these overall patterns (13).
Second Generation: Evaluating Interventions That Help Individuals Address SDOH or Mitigate Their Impact
This body of research recognizes that the unique experiences of minoritized and marginalized populations need to be acknowledged and addressed in the context of mental health interventions and care. Examples include 1) coping-focused interventions to help individuals manage or reduce distress associated with racism or other forms of discrimination, poverty, unemployment, family separations, and other challenging life circumstances (14, 15); 2) trauma-informed interventions that tailor services for individuals exposed to early or chronic traumatic events or poverty-related stressors (16–18); and 3) patient navigation or service linkage interventions that connect individuals to needed health and social services and/or address access barriers to facilitate engagement in care (19, 20). Such interventions, although a critical component of health and mental health care, only address the consequences of societal inequities and do not directly affect the systems and structures that cause and sustain mental health disparities. In isolation, these interventions will not be sufficient to reduce or eliminate mental disparities at the population level. However, based on our observation of applications submitted to NIH, interventions to help individuals or populations mitigate the impact of SDOH rather than changing the SDOH directly remain common.
Third Generation: Evaluating Interventions That Directly Impact SDOH to Produce Lasting Changes for Communities and Populations
Notably, this area seems to be characterized by more articles calling for social and structural interventions (21, 22) than articles describing the results from actual social and structural interventions (23), and the latter are particularly rare in the mental health field. To address mental health disparities, interventions must move beyond an individual-level treatment-focused model of mental health to emphasize families, organizations, and communities and encompass prevention and sustainable change. Examples of such interventions include medical-legal partnerships in which clinicians and legal personnel work to address discrimination or unfair practices related to housing, education, criminal justice, or other domains (24); alternatives to incarceration for individuals with severe mental illness charged with minor offenses (25); and the implementation of evidence-based depression treatment in faith-based settings (26). However, many structural interventions addressing SDOH have not been rigorously evaluated, and few studies have examined the impact of interventions on disparities (21). Although critically needed, research evaluating these types of interventions has many challenges. Balancing methodological rigor with feasibility and acceptability of study designs can be an issue that requires thoughtful communication and collaboration between research and community collaborators. Studies can be costly to execute, as testing interventions at organizational, neighborhood, or community levels requires these settings to be the unit of analysis rather than the individual, necessitating the inclusion of multiple sites or locations. Interventions addressing SDOH (e.g., racism and discrimination) are likely to have nonspecific outcomes relevant to a range of health conditions, which may pose a challenge to funders who prefer interventions to address disease-specific determinants of health leading to disease-specific outcomes. Despite these many challenges, such interventions hold the greatest promise for eliminating mental health disparities and achieving mental health equity.
On an encouraging note, NIH is beginning to emphasize the need for interventions that move beyond addressing SDOH at the individual level in recent funding opportunity announcements. Topics have included maternal mortality and morbidity (27), structural racism and discrimination (28), family- and community-level interventions (29, 30), physical activity (31), opioid misuse (32), HIV (33), firearm morbidity and mortality (34), and suicide and suicidal ideation and behaviors (35). Although these funding opportunities may include mental health determinants and outcomes, additional targeted opportunities from NIH and other funders of mental health research and services that are explicitly focused on SDOH and mental health disparities are likely needed to make significant progress in this area.
Taken together, this review suggests several important implications for mental health disparities research and clinical practices aimed at reducing disparities. First, this review highlights the opportunity for researchers to use and build upon the proffered mental health disparities framework to mechanistically explore SDOH that can subsequently inform appropriately framed and tailored interventions to reduce disparities. Second, from a clinical perspective, this review points to the importance of establishing a continuum of care to address mental health disparities, which includes both mental health promotion and prevention interventions among marginalized and minoritized populations. Development of interventions aimed at the promotion and prevention end of the mental health continuum of care would facilitate addressing the social and structural factors that have been identified as significant drivers of mental health disparities, including SDOH, and would increase the ultimate reach and range of intervention.
Office of Disease Prevention, NIH, Bethesda, Md. (Alvidrez); Office for Disparities Research and Workforce Diversity, NIMH, Bethesda, Md. (Barksdale); National Institute on Minority Health and Health Disparities, NIH, Bethesda, Md. (Barksdale).
The views expressed in this article represent those of the authors and do not necessarily represent the views of NIH.
The authors report no financial relationships with commercial interests.
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Findings from our systematic review [16] were used to design a theoretical framework for the qualitative study [17]. Notable determinants identified in the systematic review were financial and time limitations, health/beauty paradox (= overweight/obesity as a sign of beauty and wealth), and lack of knowledge, self-efficacy, and skills. Qualitative study findings re-affirmed the systematic review findings concerning health/beauty paradox, knowledge, self-efficacy, and skills gaps. In addition, the qualitative study showed socio-cultural misconceptions around lifestyle PA, fruits, vegetables, and habitual orientation towards carbohydrate foods. We also found that there is a high trust in nutrition information shared on social and mass media, yet skills to evaluate this nutrition information are limited. Figure 1 below shows the logical model of needs assessment, summarises the determinants of dietary and PA in urban Uganda [16, 17].
Fig. 1
Logical model of needs assessment, summarizing the personal and environmental determinants of dietary and PA behavior in urban Uganda. Adapted from Yiga et al., [16] and Yiga et al., [17]
Step II: Formulation of behavioral intervention, performance, and change objectives
We hypothesised that changing the overall existing behaviours towards WHO healthy lifestyle guidelines in one intervention may meet strong resistance and thus may not be effective. For example, the planning group hypothesised that due to the existing health/beauty paradox and habitual orientation towards carbohydrate rich foods, interventions focusing directly on weight loss and reduction of portion sizes of foods rich in carbohydrates may meet strong resistance. Therefore, we decided to go for more feasible gradual changes able to enact clinically relevant metabolic improvements. We hypothesised that increased consumption of vegetables and fruits will indirectly translate into reduction of portion sizes of carbohydrate rich foods. In line with WHO health recommendations, the intervention aims to stimulate WRA to consume at least 400 g fruits and vegetables [13]. Moderate intensity PA that can be incorporated in daily life activities may be the achievable type of PA among WRA compared to structural high intensity PA [26]. Non-factual nutrition information influences dietary and PA behaviors in urban Uganda [17]. Thus, we decided to supplement the intervention with a component on information evaluation; to enact ability to distinguish evidence-based information from nonfactual information.
Accordingly, three behavioural intervention objectives were formulated.
1.
Women evaluate the accuracy of food, nutrition, and PA information.
2.
Women engage in moderate intensity PA for at least 150 min a week.
3.
Women consume at least one portion of vegetables and one portion of fruit every day.
Table 1 shows the behavioral intervention objectives, subdivided into POs providing the answer to the question; “what do the participants of the intervention need to do to achieve the behavioural objectives”. The model of food literacy [27] guided the formulation of POs. Food literacy is the interrelated combination of knowledge, skills and self-efficacy to (i) plan, (ii) select, (iii) prepare, (iv) eat food with the ultimate goal of developing a lifelong healthy, sustainable and gastronomic relationship with food within the prevailing environment [27, 28]. The POs were based on the above mentioned four components of food literacy (plan, select, prepare, and eat). For PA, a similar model was adopted, where “eat” was replaced with “do”, that is; plan, select, prepare, and do. The model of food literacy was chosen as it is a holistic behavior change model focusing on a “how to do approach” to initiate and sustain healthy eating habits [27, 28]. Evidence shows a positive association between food literacy and healthy dietary behaviors, particularly increased intake of vegetables and fruits [29, 30]. Table 2 shows the determinants considered to have a strong influence on accomplishing the created POs. Matrices of change objectives are presented in Additional file 3.
Table 1 Behavioural intervention objectives subdivided into performance objectives
Table 2 Determinants of performance objectives for behavior intervention objectives
Step III: Selection of theory-based methods and practical strategies
We aimed to create an intervention capable of initiating and sustaining behaviour change. Eleven BCTs scientifically shown to enact changes in knowledge, skills, self-efficacy, subjective norms, and social support were selected, Additional file 4. The selected BCTs are supported by the self-regulation theory and self-determination theory which specifies the need for autonomy, competence, and relatedness to attain a positive behaviour change [33, 34]. Accordingly, our intervention aims to create behavioural change through enacting autonomy, competence, and relatedness. Providing information coupled with motivation interviewing creates a positive intention [35]. Implementation intentions can be achieved through goal setting [24, 34, 35]. Goal setting necessitates competence, which we hypothesised to be attained through a combination of (i) action planning; (ii) guided practice; ii) self-monitoring; iv) feedback on performance and v) planning of coping plans [24, 26, 34,35,36]. To sustain the behavioural goals requires relatedness, which can be achieved using a combination of social support, role modelling, feedback, planning coping responses and motivation interviewing [20, 24, 34].
The selected BCTs were then operationalised into practical strategies. BCTs; motivational interviewing, role modelling, feedback, guided practice, social support through exchanging ideas and planning coping responses were translated into interactive group-based sessions. Brainstorming workshops with planning group II and FGDs with target group revealed that group sessions may be the best strategy to deliver the intervention in this setting.
“Through education sessions, like you come in this group and give us a health talk, like the way you have come, you teach us and then us we can go and teach our other friends out there. Like for us every Tuesday we be meeting here, very many of us, so if you say you will give us one Tuesday in a week or month, or the last Tuesday of a month and you come and teach us”. “It would be very nice, because literally I share the information with others, so it will move, it moves much faster, because these groups are not only here, but also have these groups in other dioceses, so we can go visit them, and the teach them, but in health centers you only visit when you’re sick”. “Yes it helps, what I know is good, I wish it for my friends and we act as a support for each, and we as well spread it to other groups, example of myself, I used to never eat pumpkin, but I got it from these ladies, that this pumpkin is good and with time I gradually started to eat it until it become part of my diet”, participants in FGD 4 and 6.
Additionally, a recent systematic review shows that diet and PA interventions delivered through group sessions are effective in promoting clinically relevant weight loss [34]. These groups provide opportunities for social support, experience sharing, and may create a motivating atmosphere [22, 34]. Our needs assessment as well revealed that the community and church small groups are an opportunity to share dietary and PA counselling [16, 17]. Our environmental asset assessment revealed existence of women groups within religious structures. Existing groups boosts social cohesion, a facilitator for behavioural change [22].
The reading culture of Ugandans is low.
“We need more of practical, and also the pamphlet, some of us don’t really understand so much, but if it brings out the picture very well, even I can pick interest in it”. “Pamphlets, some people are lazy to read”, participants in FGD 5.
So, the BCT of “providing information through imagery” was translated into infographics with less text and more locally recognisable visuals. Evidence as well shows that visuals increase attention, interest, and credibility of the messages [20].
During FGDs with the target group, participants emphasised the need for practical vegetable preparation skills.
“like we are trying to reduce cooking oil and other stuff from our daily life, so maybe we meet in a group, there is a demonstration whereby some food stuffs are prepared in the best possible way which is to the taste, and people learn how to prepare them, because most of us, do not know how to cook, that is the truth, but somebody may not even fry food, but it tastes so good, if you know how to mix the ingredients and so on. Yes, include cooking demonstrations”, participants in FGD 2.
Hence, BCT of “guided practice” was specifically translated into a practical vegetable group cooking session. We also included vegetable recipes based on locally available vegetables in the intervention infographics. Intervention strategies linked to personal metabolic health and lifestyle needs, and environmental opportunities may help drive behaviour change and positively influence health outcomes [37]. Thus, BCT of; implementation intentions, goal setting and action planning were translated in to; (i) creating “if then plans” in line with metabolic health, (ii) SMART fruit/vegetable/PA goals, detailed action plans to achieve set SMART goals drawn considering environmental opportunities. Figure 2 below shows the hypothesised intervention logical model (conceptual framework) of behavioural change. Practical strategies built from BCT are hypothesized to effect changes in the change objectives, which in turn translate in changes in the determinants. Changes in the determinants in turn result in attainment of POs and corresponding behavioural intervention objectives.
Fig. 2
hypothesised intervention logical model for behavioural change (conceptual framework for the intervention)
Step IV: Development of the intervention programme
The practical strategies were built into the intervention scope and sequence, Additional file 5. The intervention consists of five interactive group sessions, 150 min each, Fig. 3. A booklet (infographics); on benefits/recommendations, local vegetable recipes, and practical tips to eat more fruits, vegetables and do more PA is included as a guide, Additional file 6. Tools to assess PA and food environment for opportunities were included, Additional file 7. As well a self-monitoring tool for PA, fruit and vegetable intake was included for participants to track their behaviour daily goals for use in the feedback sessions, Additional file 8. The infographics were designed with locally recognisable images as cultural relevance of health promotion materials is vital for the success of an intervention [20]. Messages on the infographics were framed in a positive and active tone as evidence shows that positively framed messages are more acceptable [20].
Fig. 3
Showing delivery timeline of the intervention sessions, intervention content (organised practical strategies from step III), role of participants, and anticipated outcome per session
Brain storming workshop with planning group I and FGDs with the target group identified religious institution women group structures as an appropriate potential delivery channel. The women group structures boosts established social networks, community reach (85{e4f787673fbda589a16c4acddca5ba6fa1cbf0bc0eb53f36e5f8309f6ee846cf} Ugandans are Christians) and trust. The channel offers an opportunity for assessing the intervention effectiveness in an unrestricted real-life community setting.
“Religious institutions because they are transparent, religious organizations because they reach out to a bigger community and then they are transparent. The health centers, there is that rudeness, and still for health centers will only meet those people who come to them, but the church, you get a bigger audience”, “Come to churches like this, people really belong to this communities, then you say every third Saturday or Sunday of the month, from 4 to 5 pm, there will always be a nutritional class, for the first-time people may not come, but eventually they come, if it is a free class”, participants in FGD 4.
STEP V: Adoption and implementation plan
The intervention will be delivered through institutional religious women groups (results of environmental asset assessment framework – see step IV). Through meetings with the strategic community leaders, a collaboration was established with Our Lady of Africa Catholic Parish, Mbuya. Mbuya Catholic Parish has six sub parishes. Within these sub parishes they are existing women groups, and these groups will be utilized for face-to-face intervention group sessions. FGDs with target group and meetings with planning group II pointed at the importance of opinion peer leaders being part of the implementation team.
“Our women group leader has helped us a lot, she taught us the dangers of cooking in polyethene bags and taught us the use of banana leaves, us we had got so much used to using the polyethene bags, she can’t eat the food you have prepared in polyethene bags, even if she visits you and if you have cooked like that, she can’t eat that food. “We have musawo (village health team) in our group, she usually brings for us education sessions on how to eat, she goes a lot for these education sessions and what she learns she brings them back to us”, participants in FGD 6.
Scientific evidence shows that the efficacy and acceptability of health promotion interventions increases if peer opinion leaders within the target group are part of the implementation team [38]. Peer opinion leaders provide entry and legitimacy to the external change agents and may help drive changes in social norms. Selection of peer opinion leaders: the intervention will be delivered within existing women groups. Leaders of these existing groups will be selected to work as peer opinion leaders on the implementation team. The main role and responsibilities peer opinion leaders will be to (i) mobilize fellow women to participate in the intervention, (ii) follow up and (iii) give social support to participating women to attain set intervention goals. Women leaders will be given a two – day refresher training on mobilization and leadership skills, as mobilization is the routine responsibility for women leaders in their usual group meetings. The planning group I designed the sessions to be moderated by health behavior coach (PhD researcher) following the techniques of motivational interviewing [39]. A general guide (scope & sequence) will ensure consistency during the group sessions.
Step VI: Development of an evaluation plan
Study design, setting and timing
The effectiveness of the intervention will be evaluated through a cluster-randomized controlled trial. The intervention will be evaluated in Kampala, the capital city of Uganda. The six sub parishes of Mbuya catholic parish will be randomized to treatment and control arms, Fig. 4. The treatment arm will be exposed to both the developed intervention infographics and face to face group sessions while the control arm will only receive the developed intervention infographics. An awareness session will be organized to distribute the infographics to the control arm. Within the sub parishes, there are existing women groups. These existing groups will be utilized for face-to-face intervention group sessions. For the intervention purposes, each group will be limited to a maximum of 14 members. The study period is divided into two phases: a three-month intervention and a three-month post-intervention follow-up phase.
Fig. 4
Recruitment
The PhD researcher and women leaders of existing groups will make presentations about the intervention during one of the routine meetings. Flyers with details of the intervention will be distributed for sharing with members who are absent during the briefing. At the end of the presentations, interested participants will be invited for the first session to test their eligibility to participate in the study. Eligible participants will be provided with an informed consent form to endorse.
Inclusion criteria
i)
Sex (women),
ii)
Age (18 to 45 years),
iii)
Central obesity [waist circumference ≥ 80 cm]),
iv)
Fluent in either Luganda or English (sessions will be conducted in Luganda/English).
v)
Willingness to follow the three-months intervention and three months follow-up,
vi)
Willingness to sign the informed consent.
Exclusion criteria
i.
Being treated for diabetes Mellitus Type 1 or Type 2, hypertension, high cholesterol, or any other cardio-metabolic related disease.
ii.
Pregnancy.
Outcomes
Primary outcome is reduction in waist circumference. Decreases in waist circumference are recommended as critically important treatment target for reducing adverse cardiometabolic health risks [15]. Secondary outcomes include optimisation of, fasting blood glucose, total cholesterol, HDL, LDL, triglycerides, body composition, food literacy, PA, and fruit and vegetable intake.
Sample size calculation
Sample size calculation is based on waist circumference.
To calculate the sample size, we used the formula described by Rutterford, Copas [40], Table 3.
Table 3 Description of sample size calculation
Randomization
The six sub parishes (clusters) will be listed alphabetically. A cluster randomization with a 1:1 allocation will then be applied to randomize the sub parishes to either the treatment or control arm. In the sub parishes, women group leaders and participants will be blinded about the study arms.
Data collection
Table 4 gives an overview of the different measurements and time points during the study.
Table 4 Measurements and time points
Data analysis
Data will be analysed using R software. To evaluate the effects of the intervention, multilevel analysis will be used. Using this technique, regression coefficients will be adjusted for the clustering of observations within sub parishes. We will define two levels in our multi-level analysis: (1) participant and (2) sub parishes. Linear mixed effect models will be used to examine the effect of the intervention on each of the outcome values. All analyses will be performed according to the intention-to treat-principle [42]. To assess changes in metabolic health between the intervention and control groups, a linear mixed effect model will be built where “time” (end line measurement (M2) will be compared with base-line measurement (M1) and post-follow up measurement (M3)), treatment (and interaction of time and treatment) as well as age will be specified as fixed effects, and sub parishes and participants as random factors. For all linear mixed models, compatibility with mixed-model assumptions will be checked by inspection of residual plots and Q-Q plots. In the case of heteroscedastic residuals, data will be log transformed. Tukey or Benjamini–Hochberg procedures will be applied when performing post hoc analyses to further identify differences within treatments as well as between time points. Statistical outliers will be defined as any observation which has an absolute residual exceeding 3 times the residual standard deviation. p < 0.05 will be considered significant in all analyses.
