Reach and Support for All: targeting Non-Communicable Diseases in Businesses in Tanzania

Reach and Support for All: targeting Non-Communicable Diseases in Businesses in Tanzania

Non-communicable diseases in Tanzania

Non-communicable diseases (NCDs) kill 38 million people each year, of which an approximate 28 million occur in low resource settings [1]. Most NCD deaths are due to cardiovascular diseases (17.5 million annually) [1] and diabetes causes 1.5 million deaths each year [1]. In Tanzania itself, the percentage of annual deaths due to NCDs has been estimated to be around 31% [2] and is believed to be increasing due to urban migrations and dietary changes [3,4]. NCDs negatively impact the working class and businesses’ productivity [5]. Studies from high-income countries have shown that targeting businesses for screening and health program intervention is an effective way to reach people and to boost the economy [6,7]. Employee health programs are lacking in most countries in sub-Saharan Africa. Therefore, we sought to increase NCD awareness in Tanzanian businesses. 

RASA organization

Reach and Support for All (RASA) was created on October 11, 2015 as a non-profit organization composed of social workers, medical students, doctors and nurses conducting health education and health screening for NCDs. RASA started in Mwanza city, Tanzania, one of the major commercial cities in Tanzania and the second fastest growing city in Tanzania [8].  It screens participants from various institutions that are either privately or government owned. A typical screening takes place over one or two days. We use a questionnaire to obtain patient history(known diabetes and hypertension, family history of diabetes and hypertension, current treatment for diabetes and hypertension, smoking and alcohol consumption habits). The questionnaire relies on self-report for current medical conditions, family history of disease, and any treatment received.

After filling in the questionnaire, the patient gets screened for weight and height, then hypertension and finally diabetes if they are at risk. The WHO definitions are used for all diagnoses.

A BMI of <18.5kg/m² is classified as underweight, a BMI of ≥18.5 – 24.9 kg/m² is classified as normal weight, a BMI of 25–29.9 kg/m² is classified as being overweight and a BMI of ≥30 kg/m²as being obese [9].

Average systolic and average diastolic blood pressure are calculated using the average of the last two readings when available. Hypertension is defined as having a systolic blood pressure ≥140 mmHg and/or a diastolic blood pressure ≥90 mmHg. We define prehypertension as having a systolic pressure ranging from 120 to 139 mmHg and/or a diastolic pressure ranging from 80 to 89 mmHg. Stage 1 hypertension is defined as a systolic pressure ranging from 140 to 159 mmHg and/or a diastolic pressure ranging from 90 to 99 mmHg. Finally stage 2 hypertension is defined as a systolic pressure equal or greater than 160 mmHg and/or a diastolic pressure equal or greater than 100 mmHg. [10] Within stage 2 we can distinguish stage 3 (systolic pressure ranging from 180 to 199 mmHg and/or a diastolic pressure ranging from 110 to 119 mmHg) and stage 4 (systolic pressure equal or greater than 200 mmHg and/or a diastolic pressure equal or greater than 120 mmHg).

Participants are categorized as having diabetes mellitus if their Fasting Blood Glucose (FBG) levels are ≥7.0 mmol/L (126 mg/dL) or if their Random Blood Glucose (RBG) levels are ≥11.1mmol/L (200mg/dL). They are considered pre-diabetic if their FBG is 6.1–6.9 mmol/L (110–125 mg/dL)[11]. They are non-diabetic if their FBG is less than 6.1 mmol/L (110 mg/dL). Their diabetic status is undetermined if their RBG is <11.1 mmol/L (200mg/dL). We classify non-diabetic and undetermined as “other”.

Individuals diagnosed with hypertension or diabetes are referred to a local public hospital for treatment. Finally patients receive education on nutrition related to hypertension, diabetes, obesity. The lecture also includes the impact of the above diseases and their associated complications such as stokes, diabetic retinopathy, cardiovascular accidents, general body malaise and other NCDs. A Q&A allows us to test clients understanding on the subject matter. 

RASA’s impact

So far 2486 employees from 24 different companies have been screened through RASA from October 2015 up to October 2016. The median age was 34 [27-45] years-old with 62.8% (1523/2486) of the employees being male. The median BMI was 25.5 [22.34-29.49] kg/m² with 31.1% (771/2483) of people screened being overweight and 22.1% (549/2483) being obese.

36.7% (911/2484) of employees were diagnosed with hypertension. Of those, 84.9% (773/911) were newly diagnosed, 12.0% (109/911) were previously diagnosed but not on any medication and 3.2% (29/911) were previously diagnosed and taking medication.  Among those diagnosed as non-hypertensive, 1.1% (18/1573) were previously diagnosed and taking medication. 5.6% (140/2484) of employees had severe hypertension and required urgent care.

A total of 1783 patients were screened for diabetes. Diabetes was diagnosed in 10.2% (181/1783) of those eligible for screening. Pre-diabetes was diagnosed in 1.6% (29/1783) of the patients. Out of all of those screened for diabetes, 11.7% (161/1375) were newly diagnosed (including pre-diabetic), 2.3% (31/1375) were previously diagnosed but not on any medication and 1.8% (25/1375) were previously diagnosed and taking medication. Socio-demographic and health characteristics are presented in Table 1.  

There was a significant difference in terms of BMI category between men and women (p<2.2e-16) as well as a significant difference in the presence of hypertension (p<2.2e-16). There was no significant difference in diabetes diagnosis between sexes.  The comparison is presented in Table 2.

During the same time period, 2804 patients coming from the community were screened as a comparison group. The median age was 39 [28-50] years old with 59.9% (1646/2803) of males. The median BMI was 23.9[21.02-27.77] kg/m² with 26.7% (748/2797) of people screened being overweight and 15.3% (428/2797) being obese. 34.2% (956/2798) of the community screened was diagnosed with hypertension, 6.1%(170/2798) had severe hypertension and required urgent care. 892  patients were screened for diabetes and it was diagnosed in 7.1% (63/892) of eligible patients.

There was a significant difference between businesses and communities in terms of age (p<2.2e-16), sex(p<2.2e-16), mean BMI (p<2.2e-16) and diabetes prevalence (p=0.01094). There was no significant difference in hypertension prevalence (p=0.061) but the difference in hypertension diagnostic stages was significantly different in the communities compared to businesses (p=0.0068 with Wilcoxon rank sum test). P-values and prevalence comparisons are presented in Table 2.

In terms of costs, the total budget for RASA for the months of October 2015 to October 2016 was a total of TZS 44,000,000 ($20,000). Of this annual budget, TZS 11,000,000 ($5,000) was used for office space rental and TZS 33,000,000 ($15,000) was used for RASA daily operations. These include purchase of screening equipment, allowances to staff/service providers, transport from office to screening sites and advertising. The actual cost that went in to HTN screening alone was TZS 21,001,000 ($9,546),  This means that the cost per new case of HTN diagnosed was TZS 11,250 ($5).

Lessons learned

The businesses screening show a higher prevalence of obesity and diabetes despite being composed of a younger population. RASA data also show that the percentage of newly diagnosed hypertensive employees is high and that some employees previously diagnosed and supposedly taking medication are still diagnosed with hypertension or diabetes. More people out of business had to be tested for diabetes compared to the general community. This can be explained by the fact that people in the businesses are significantly more likely to be overweight than people in the communities and thus more at risk for diabetes which implies testing. This points out an urgent need for screening services in businesses and the necessity of RASA work. Employee health programs, insisting on prevention and treatment are urgently needed. 

After re-screening one business of about 100 employees, 6 employees only were found to be present at the previous screening. Of those 6 employees, 5 had been diagnosed with hypertension on the first screening (of which only one had proceeded to get treatment). One out of 6 employees had been diagnosed with diabetes at the first screening and had the appropriate treatment at the second screening. These data show a real need for follow-up. We tried going back to several other businesses but encountered administrative difficulties, including change in staff and management. 

Ideally, we would visit again businesses already screened to allow for follow-up of the beneficiaries and for screening of new employees. This would allow us to investigate if the beneficiaries are actually putting into practice the lifestyles we recommended them and if the referrals are going to the hospital and indeed getting the appropriate treatment. For the business screenings to come we will plan 2 screenings to start with, to overcome those difficulties. We have also started discussions of cooperation with insurance companies in order to facilitate referral and to encourage our beneficiaries to seek treatment.

RASA’s challenges and solutions

In order to screen more people, create on-site alerts, reduce time and cost of data entry at the office, and reduce human error in data entry, the use of electronic tablets or smartphones on site is the next step we want to implement. In addition, we plan on improving our emergency response system with a private means of transportation  and an onsite emergency team. Private transportation will help quickly getting the patients the care needed: so far emergency cases have been rushed to the hospital via taxi cars or motorbikes, which is not a long-term reliable solution. An onsite emergency team is needed as well to help reduce health risks in cases of an emergency as well as compensate for the lack of an ambulance at the screening site. 

Finally for RASA to be self-reliant, RASA is considering  establishing a health and wellness program that will offer nutritional consultation services,  and aerobics.  The program will initially enroll beneficiaries from RASA screening activities but will also be open to all members of the community in need of the services. The funds raised will be used for RASA’s activities and the health program itself. 

RASA’s way forward

RASA is a Tanzanian NGO that is dedicated to screening NCDs in businesses. It has so far only held screening in Mwanza city. The next step is to expand geographically its activities. At the moment RASA intends to start a cooperation with the Tanzanian military. This will allow for screening of an important economically active part of the population and a part of the population less likely to self-refer to healthcare facilities for screening. In addition, RASA is looking to expand to other major Tanzanian cities such as Dar Es Salaam, Arusha and Dodoma to increase its outreach and to start setting up a hub-and spoke model for its services. This expansion should lead to the creation of a national de-indentified database for obesity, hypertension and diabetes in businesses in Tanzania. This database will inform health policies targeting employed populations and focused on prevention. The complementary health and wellness program will help determining the components of an effective treatment and prevention program, advocate for evidence-based policies and raise awareness for healthy food policies. RASA’s ultimate goal is to help reduce mortality due to NCDs in Tanzania.

REFERENCES

1. WHO. Noncommunicable diseases fact sheet. Consulted on November 14^th 2016. Available at: http://www.who.int/mediacentre/factsheets/fs355/en/
2. WHO NCD Country Profiles, Tanzania. Consulted on November 14^th 2016. Available at:http://www.who.int/nmh/countries/tza_en.pdf
3. Mayige, M., Kagaruki, G., Ramaiya, K., &Swai, A. (2012). Non communicable diseases in Tanzania: a call for urgent action. Tanzania journal of health research, 13(5).
4. Hamada, A., Mori, M., Mori, H., Muhihi, A., Njelekela, M., Masesa, Z., Mtabaji, J. &Yamori, Y (2010) Deterioration of traditional dietary custom increases the risk of lifestyle-related diseases in young male Africans. Journal of Biomedical Science 17 (Suppl. 1)(S34).
5. PAHO. The economic burden of Non-communicable Diseases in the Americas. Issue brief on NCDs. Consulted on November 14t 2016. Available at: http://www.paho.org/hq/index.php?option=com_docman&task=doc_view&gid=15737&Itemid=270
6. Berry, L., Mirabito, A.M., &Baun, W. (2010). What's the hard return on employee wellness programs? Harvard Business Review, 88(12), 104-112.
7. Baicker, K., Cutler, D., and Song, Z. (2010). Workplace wellness programs can generate savings. Health Affairs 29(2), 304-311.
8. Tanzania Daily News. Tanzania: Mwanza Seen Fastest Growing Region After Dar. Consulted on November 14^th 2016. Available at:

http://allafrica.com/stories/201506160369.html

9.                  WHO. Global database on BMI. Consulted on November 14^th 2016. Available at:http://apps.who.int/bmi/index.jsp?introPage=intro_3.html

10.              Brookes, L. (2004). The updated WHO/ISH hypertension guidelines. Medscape Cardiology.

11.              WHO. Screening for Type 2 Diabetes. Consulted on November 14^th. Available at:

http://www.who.int/diabetes/publications/en/screening_mnc03.pdf

TABLES

Characteristics	Measure/ subcharacteristic	Businesses (N=2486)	Communities (N=2804)	P-value for difference
		Measure	Measure
Sociodemographic
Age  (years)	Median (IQR) [Min,Max]	34 (27,45) [15,89], NA=0	39 (28,50) [16,100], NA=3	p<2.2e-16
Sex	Male	62.8% (1523/2486)	59.9% (1646/2803)	p<2.2e-16
Health
BMI (kg/m2)	Mean (SD) [Min, Max]	26.1 (5.1) [13.4,52.0], NA=3	24.8 (5.0) [13.8,54.5] , NA=7	p<2.2e-16
BMI category	Underweight	3.2% (80/2483)	5.8% (162/2797)	p<2.2e-16
	Normal	43.6%(1083/2483)	52.2% (1459/2797)
	Overweight	31.1% (771/2483)	26.7% (748/2797)
	Obese	22.1% (549/2483)	15.3% (428/2797)
Hypertension	Yes	36.7% (911/2484)	34.2%(956/2798)	0.06095
Hypertension category	No	21.9% (1943/2484)	26.7% (747/2798)	3.678e-06 *
	Prehypertension	41.5% (543/2484)	39.1% (1095/2798)
	Stage 1	24.7% (614/2484)	20.5% (573/2798)
	Stage 2	12.0% (297/2484)	13.7% (383/2798)
Diabetes	Yes	10.2%(181/1783)	7.1% (63/892)	0.01094
Diabetes category	Diabetic	10.2% (181/1783)	7.1% (63/892)	0.02347 *
	Pre-diabetic	1.6% (29/1783)	2.1% (19/892)
	Other**	88.2% (1573/1783)	90.8% (810/892)

Table 1 – Sociodemographic and health characteristics of the business and the community populations

*Wilcoxon rank sum test also statistically significant

**Non-diabetic and indeterminate

Characteristics	Measure/ subcharacteristic	Business males             N=1523		Business females          N=963	P-value for difference
		Measure		Measure
Sociodemographic
Age  (years)	Median (IQR) [Min,Max]	34 (27,45) [15,87], NA=0		34 (26,45) [18,89], NA=0	0.9014
Health
BMI (kg/m2)	Mean (SD) [Min, Max]	25.2 (4.4) [13.4,43.5], NA=1	27.5 (5.7) [15.2,52.0], NA=2		p<2.2e-16
BMI category	Underweight	3.6% (55/1522)	2.6% (25/961)		p<2.2e-16
	Normal	48.7% (741/1522)	35.6%(342/961)
	Overweight	31.7%(483/1522)	30.0%(288/961)
	Obese	16.0% (243/1522)	31.8%(306/961)
Hypertension	Yes	41.6% (632/1521)	29.0%(279/963)		3.055e-10
Hypertension category	No	15.8%(241/1521)	31.4%(302/963)		p<2.2e-16
	Prehypertension	42.6%(648/1521)	39.7%(382/963)
	Stage 1	29.1%(442/1521)	17.9%(172/963)
	Stage 2	12.5%(190/1521)	11.1%(107/963)
Diabetes	Yes	10.0%(108/1079)	10.4%(73/704)		0.8683
Diabetes category	Diabetic	10.0%(108/1079)	10.4%(73/704)		0.9467
	Pre-diabetic	1.6% (17/1079)	1.7%(12/704)
	Other	88.4%(954/1079)	87.9%(619/704)

Table 2 – Comparisons between men and women within businesses.

*Wilcoxon rank sum test also statistically significant

**Non-diabetic and indeterminate