Yasmin Bowers

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					Community Health and GIS: Using GPS and GIS for Foetal Alcohol Syndrome
Education and Outreach in the Bergriver Municipality in the Western Cape,
South Africa

Name of the Presenter: Yasmin Bowers

Author (s) Affiliation:
Yasmin Bowers, BA Hons, MSPH
Mount Sinai School of Medicine Department of Community and Preventative
New York City, NY, USA

Elmarie Nel
Chief Research Technologist
Medical Research Council
Pretoria, SA

Nontobeko R. Jacobs
University of Cape Town School of Public Health and Family Medicine
Cape Town, SA

Adlai Davids, BA Hons, MSc
Human Sciences Research Council
Port Elizabeth, SA

Dr. Kirstie Rendall-Mkosi, BSC (OT), MPH, PhD
University of Pretoria
School of Health Systems and Public Health
Pretoria, SA

Dr. Leslie London, MB ChB, BSc Hons (epid), DOH, MD, M.Med.,
University of Cape Town School of Public Health and Family Medicine
Cape Town, SA

Mailing Address:
Email Address:
Telephone number (s):
Fax number (s):

   I. Background:

Foetal Alcohol Syndrome
Foetal Alcohol Spectrum Disorders (FASD), an umbrella term describing the range of
symptoms that can be manifested by an individual whose mother drank alcohol during
pregnancy, including the narrower group Foetal Alcohol Syndrome (FAS). FAS is
used to describe physical and mental defects including brain damage, facial
deformities and growth deficits that an affected child exhibits (Science in Africa,

Collaborations between the University of Cape Town School of Public Health and
Family Medicine, University of Pretoria School of Health Systems and Public Health,
South Africa Medical Research Council, and the Human Sciences Research Council
are integral to FAS research and outreach within the study area in the Bergriver

FAS in South Africa
South Africa’s Western Cape Province is known to have the highest reported rates of
FAS in the world. In the rural area of Wellington, 46.4 per 1,000 (or 4.64%) school-
entry children aged 5 to 9 years have FAS (May et al, 2000) a rate that had risen by
more than 50% (to 65.2-74.2 per 1,000 school entry children) in a repeat study in the
same area 5 years later (Viljoen et al, 2005) [London, 2008].

Te Water Naude et al (2000) found a FAS rate of 5.7% amongst children 5 to 8 years
old living on farms in the Stellenbosch region (London, 2008). In the Northern Cape
Province, Viljoen et al (2008) found the prevalence of FAS/partial FAS in Grade 1
children to be 64/536 in De Aar and 97/1299 in Upington. Overall, 67.2 per 1,000
children had FAS features.

Origins of FAS in South Africa
High levels of FAS in South Africa can be traced to a mixture of social, historical and
psychological factors. In the Western Cape, part of the problem can be linked to the
availability of alcohol (London, 1999; Henn et al, 2005) and the institutional
provision of alcohol by colonial settlers to their farm laborers as part of the “dop”
system (Scully, 1992) which has manifested in widespread alcohol dependence and
misuse,(London et al, 1998a; Henn et al, 2005). The payment of alcohol to farm
workers as part of their conditions of employment is no longer legal in South Africa,
the “dop” system continued into the 1990s [London, 2008].

 “Shebeens" or informal bars are found in every township in South Africa. These bars
have replaced the “dop” system and continue to play a major role in a cycle of poverty
and alcohol dependence from which escape is extremely difficult (London, 1999).

Alcohol Availability, Accessibility, Consumption
Research has supported the association between alcohol availability, rates of alcohol
consumption, and drinking-related problems (Substance Abuse and Mental Health
Services Administration (SAMHSA)). Investigations in the US have found strong
relationships between alcohol outlet density and adverse outcomes such as alcohol-
related hospital admissions, child abuse and neglect, motor vehicle accidents,
pedestrian injuries, drunk driving and a range of mortality outcomes (Donnelly et al,

Outlet density impacts consumption by making low cost or volume discounted
alcohol available to persons predisposed to drink heavily (Gruenewald et al, 1996),
such as those persons within the Bergriver Municipality FAS research area. High
outlet density also reflects heavy drinking norms and preferences (Scribner et al,

2000), and underlying community features [Weitzman et al, 2003], such as the “dop”

Studies of natural experiments clarify the relationships between alcohol availability
and consumption. Studies indicate that a reduction in alcohol availability caused by
worker strikes or prohibitions on sales reduces the rates of alcohol consumption and
drinking-related problems (Edwards et al, 1994) [SAMHSA].

Alcohol availability and Alcohol-related problems
The issue of outlet density is critical in terms of minimising alcohol-related harm in
the community. Research is needed to help determine specific thresholds above which
problems in a particular local area will manifest (Stockwell and Gruenewald, 2001),
and help understand the relationship between the concentration of specific licence
types (or lack thereof) and a range of alcohol-related harms for public benefit
(Donnelly et al 2006).

Our study explores the relationship of alcohol availability and accessibility as it
relates to consumption of alcohol by an at-risk population susceptible to FAS. The
alcohol-related harm for this study is use of alcohol by pregnant women or women
childbearing age, and subsequent health consequences such as FAS. Mapping these
outlets using GIS provides data on alcohol accessibility as an indicator of
consumption and subsequently FAS. Incorporating GIS data, results, and significance
into community outreach has proven effective in other parts of Africa, which is
modelled after for our study area where no such data existed before.

Alcohol Vendors and the South African Liquor Act
Determining the density of alcohol outlets (typically per 1,000 residents) provides
community members, city and local officials, and public policymakers with
information that can support effective public health intervention strategies. Analyzing
liquor licenses in a community of high-risk for alcohol-related problems might
prevent future issuances that would threaten public health and safety (SAMHSA).

In January 2009, there were approximately 900 licensed shebeens, 3,200 legal and
30,000 illegal shebeens in the Western Cape. GIS data could be used to analyze the
Western Cape Liquor Act, No. 4 of 2008 by providing baseline data in which to
compare after changes in enforcement and licensing have been made for legal and
illegal alcohol vendors (South African Press Association [SAPA], 2009).

The Act seeks to control the proliferation of drinking places in residential areas, and
to crack down on retailers and distributors who supply illegal shebeens through heavy
fines, jail terms and forfeiture of assets. Despite protests from shebeen owners, the
long-term benefits of the Act for crime prevention and health outweigh the immediate
loss of income (SAPA, 2009).

   II. Purpose:

The purpose of this study is to map legal and illegal alcohol vendors in the Bergriver
Municipality—a West Coast district in the Western Cape—as part of the FAS
prevention study. Formal documentation contributes toward planning outreach
initiatives via health communications, identifying socioeconomic and health rights

violations, and providing a baseline measure in which to compare the Western Cape
Liquor Act, No. 4 of 2008.

Relating risk behaviours to health impacts is revolutionizing public health, especially
through the spatial representation of a risk with a health outcome. In the study area,
alcohol vendors have never been mapped and GIS data is limited. The study’s purpose
of mapping an indicator of a risk behaviour to make inferences about FAS is a part of
a growing, yet fairly new, integration between GIS and Public Health.

   III. Methods:

Field work was undertaken in August 2008 by two primary researchers (YB and EN),
who visited the study site to identify and record legal and illegal alcohol vendors.
Their field work was assisted by a local community outreach organizer and the local
police services. Six of the local towns were visited over a period of three days—
Aurora, Eendekuil, Piketberg, Porterville, Redelinghuys, and Velddrif. Due to
flooding, Redelinghuys could not be visited. Therefore, vendors were plotted on
Google Earth using cross-street estimates and exported into ESRI ArcMap.

Using the Garmin Car GPS Device, Latitude and Longitude coordinates were saved as
a point of interest (units of Decimal Degrees) and recorded by hand (units of Degrees
Minutes Seconds) along with a description: Name, including Street and Number;
Town; Size- arbitrary values of small or large were used; Legal Status- determined by
license; Latitude; Longitude; and Additional Notes.

The Garmin “Current points of interest file” was opened in Excel. Name, Latitude
and Longitude Data were exported as a separate Excel Workbook. The other
attributes were added from the written journal and the file was saved as a “Comma
Separated Values” File, FASAlcohol.csv.

For Redelinghuys, estimated points were made in Google Earth and saved as three
different KML files. The Executable Program “KML2SHP” was used to create three
different shapefiles. The shapefiles were loaded into ArcMap and their Decimal
Degrees were recorded into the existing “FASAlcohol.csv” Excel Spreadsheet along
with their attributes.

The final Excel Spreadsheet was saved again as a “Comma Separated Values” File
“FASAlcohol.csv” and opened in ESRI ArcMap. The file was used as the XY
Coordinates and the projection was defined as WGS84. The resulting spatial data
layer was exported and saved as a shapefile “FAS Alcohol”.

Spatial data were acquired from the Provincial Government Western Cape
Department of Environmental Affairs and Development Planning including: Health
Districts, Landuse, Police Stations, Roads, Schools, Sustainability, Waste Sites and
Water Sources.

The “Clip 2” shapefile of the Department’s Landuse data was the smallest area in
shapefile format to contain FAS alcohol vendor study results. The “Join” Feature in

ArcMap was used to incorporate the attributes of the “Landuse” data into “FAS
Alcohol”, and saved as “FAS Alcohol Landuse”.

For display purposes only, the Spatial Analyst “Density” was used to summarize the
pattern of alcohol vendor density as a raster layer.

To display shapefiles in Google Earth, ArcToolbox 3D analyst “Layer to KML” (for
raster) and the ArcMap Extension “Export to KML” (for vector) were used.

Alcohol accessibility is defined by alcohol vendors/km2, alcohol vendor/person and
alcohol vendors/1000 persons. These calculations were made using population and
density data gathered from the Bergriver Spatial Development Framework: Draft
Framework for Discussion. The percentage and proportion of illegal alcohol vendors
were also calculated.

   IV. Results:

Figure 1: Foetal Alcohol Syndrome (FAS) study area of the Bergriver Municipality,
South Africa.

Figure 2: Towns within the FAS study area within the Bergriver Municipality, South

Figure 3: Legal and illegal alcohol vendors within the FAS study area within the
Bergriver Municipality, South Africa.

Table 1: Legal and illegal vendors by landuse and town.

Landuse          Illegal        Legal     Total
                 Alcohol        Alcohol
                 Vendors        Vendors
Cultivation                18         24        42
  Aurora                                1        1
  Eendekuil                 6           2        8
  Piketberg                 9           9       18
  Porterville               3           8       11
  Velddrif                              4        4
Mining                                  1        1
  Piketberg                             1        1
Natural                     3         11        14
  Piketberg                             4        4
  Redelinghuys                          1        1
  Velddrif                  3           6        9
Urban:                     24         22        46
  Aurora                    1         1         2
  Piketberg                 8         8        16
  Porterville               3         5         8
  Redelinghuys              1         1         2
  Velddrif                 11         7        18
Waterbodies                           6         6
  Velddrif                            6         6
Wetlands                    2         1         3
  Velddrif                  2         1         3
Total                      47        65       112

       Table 2: Legality, Population and Alcohol Vendor Density
Town             Illegal   Legal    Total    Proportion    Percent   Town Area     Total        Population   Alcohol      Alcohol    Alcohol
                                             Illegal:      Illegal   in km2        Population   Density      Vender       Vendor/P   Vendors/
                                             Legal                   (using                                  Density      erson      1000
                                                                     population                                                      Persons
                                                                     and density                             (vendors/k
                                                                     data)                                   m2)
Aurora           1         2        3        .5            33.33     71.2          420          5.9/km2      .042         .007       7
(Aug 5)
Eendekuil        6         2        8        3             75        74.1          1000         13.5/km2     .107         .008       8
(Aug 4)
Piketberg        17        22       39       .77           43.59     351           11900        33.9/km2     .111         .003       3
(Aug 4)

Porterville      6         13       19       .46           31.58     278.2         7900         28.4/km2     .068         .002       2
(Aug 5)

Redelinghuys     1         2        3        .5            33.33     67.7          840          12.4/km2     .044         .0035      3.5
Aug 5)

Velddrif         16        24       40       .67           40        694.8         10700        15.4/km2     .057         .0037      3.7
                 47        65       112      .72           41.96     1537          32760        109.5/km2    0.429        0.0272     27.2

   V. Discussion:

Density of alcohol vendors is an indicator of alcohol accessibility and consumption.
Towns with the highest calculated alcohol densities are Piketberg and Eendekuil.
The GIS Density analysis is based upon the clustering nature of the vendors
regardless of the towns’ demarcation; high densities were calculated for Porterville
and Velddrif. These towns should be prioritized for FAS education and intervention.

Landuse factors into the location of legal alcohol vendors (i.e. zoning laws) and
illegal shebeens (i.e. residential customer base). Densely populated alcohol vendors
are located within the “Cultivation” and “Urban Residential” landuse, which spatially
narrows the scope of FAS outreach initiatives.

Illegal shebeens are easily accessible and located within poor, dense settlements
called “townships”, where FAS is most abundant. Because illegal vendors (42%) are
clustered, alcohol use is difficult to track, monitor, and regulate. Eendekuil, Piketberg,
Porterville, and Velddrif have the densest townships and illegal shebeens.

Piketberg’s population of 11,900 has 17 illegal shebeens compared to De Aar’s
population of 28,000 having 98 (Science in Africa, 2006). For perspective, in 2000,
FAS incidence in De Aar was 12% in grade one students (Vilojeon et al, 2008). This
further supports the association between illegal shebeens and FAS.

The formal documentation of alcohol vendors allows for the future investigation of
health implications, such as FASD and alcohol related trauma or death. GIS
documentation also offers a visual course of action strategy for FAS monitoring,
intervention, and regulation.

Socioeconomic Rights
According to the Provincial GIS data, there are no clinics or new health facilities in
Redelinghuys (population 840) or Eendekuil (population 1000). Eendekuil has a
relatively high proportion of alcohol vendors (6:8 illegal). The lack of health
resources is exacerbated by alcohol accessibility and raises concerns about the health
rights (i.e. accessibility, availability, acceptability and quality) of this marginalized

During data collection, a culture of tolerance of alcohol availability was exemplified
by police escorts that easily identified illegal shebeens and inebriated people who laid
in the streets after presumably using part of their grant money for alcohol. Changing
this culture is best effected by comprehensive interventions that include actions to
reduce the distal determinant of alcohol abuse.

Community Health
Due to the sensitive nature of the study results, a map of easily identifiable legal and
illegal alcohol vendors could create a converse effect where one may use the map to
find and purchase alcohol. Instead, mapping location of vendors in relation to the
frequency of FAS cases could act as a powerful educational tool to change behaviours
in the community. This work is currently ongoing in the study area in collaboration
with local community partners, alongside other preventive actions.

   VI. Conclusion:

The GPS collection of legal and illegal alcohol vendors provided GIS data to enhance
the existing FAS outreach in the Bergriver Municipality of the Western Cape. The
study has documented supportive evidence of alcohol accessibility which is an
indicator of a behavioural risk that leads to FAS. Future data collection is needed to
analyze the impact that the Western Cape Liquor Act, No. 4 2008 has had on legal
and illegal alcohol vendors in the study area. It is important to continue to collect
health data at the same scale for further spatial analysis of alcohol accessibility and

   VII. Acknowledgements
Funders that are acknowledged in the study include: 1) The Centers for Disease
Control grant U01 DD000044; 2) Fogarty International Centre; and 3) Mt Sinai
School of Medicine International Exchange Program for Minority Students.

Di-anne Oktober is acknowledged for her field work assistance in Piketberg.

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