FAOSTAT FBS (kg/capita/year) |
|||||||||||
Food item |
1966 |
1971 |
1976 |
1981 |
1986 |
1991 |
1996 |
2001 |
2006 |
2011 |
% change (1966 – 2011) |
Total sugar |
16.4 |
16.6 |
17.4 |
21.9 |
22.8 |
27.4 |
22.2 |
24.4 |
29.7 |
29.9 |
82.3 |
Sugar cane |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
Sugar (raw equivalent) |
15.8 |
16.1 |
15.3 |
18.4 |
19.1 |
19.8 |
20.8 |
21.3 |
26.9 |
25.7 |
62.7 |
Sweeteners |
0.6 |
0.5 |
2.1 |
3.5 |
3.7 |
7.6 |
1.4 |
3.1 |
2.8 |
4.2 |
600 |
Honey |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
0.0 |
Total stimulants |
1.0 |
1.1 |
1.6 |
1.5 |
1.2 |
1.4 |
1.8 |
1.4 |
0.7 |
1.9 |
90 |
Coffee |
0.0 |
0.0 |
0.2 |
0.5 |
0.4 |
0.5 |
0.9 |
0.6 |
0.6 |
1.0 |
0.0 |
Tea |
1.0 |
1.1 |
1.4 |
1.0 |
0.8 |
0.9 |
0.9 |
0.8 |
0.1 |
0.9 |
-10 |
Total spices |
0.0 |
0.0 |
0.2 |
0.6 |
0.3 |
0.5 |
0.6 |
0.7 |
0.7 |
1.5 |
Source: author`s calculations using FAO Food Balance Sheet (FBS) data for Botswana.
With regards to fats and oil consumption patterns, data from FBS suggest (presented in Table 2 below) that there has been an increase in consumption of oil, but a decrease in consumption of animal fat. From a health perspective, an increase in oil consumption is of concern but, a careful inspection shows that this increase has been towards oils extracted either from crops or vegetable crops hence, tend to be a better alternative to oil (or fats) extracted from animals. While these results shed light somewhat, on a rising trend in the consumption of sugar, fats and oil, it would have been interesting if these were deduced from HIES surveys.
Table 2: Distribution of Per Capita Health Expenditure by Region by Financing Agents ($)
FAOSTAT FBS (kg/capita/year) |
||||||||||||
Food item |
1966 |
1971 |
1976 |
1981 |
1986 |
1991 |
1996 |
2001 |
2006 |
2011 |
% change (1966 – 2011) |
|
Total animal fats |
1.4 |
1.5 |
1.5 |
1.2 |
1.2 |
3.7 |
1.3 |
0.7 |
0.8 |
1.0 |
-28.6 |
|
Total oil crops |
1.6 |
1.8 |
3.4 |
5.1 |
4.3 |
7.2 |
7.6 |
6.5 |
9.0 |
10.3 |
543.8 |
Source: author`s calculations using FAO Food Balance Sheet (FBS) data.
Worth noting is that, HIES makes provision to allow one to observe household spending on alcohol beverages and tobacco. From a policy perspective this is commendable as knowledge of alcohol and tobacco consumption patterns is required for pricing policies in order to curb consumption of these food items since they are considered risk factors for some non-communicable diseases. However, adding questions related to illness and type of illness, body weight, height and body mass index can further enhance the HIES surveys. This will allow researchers to link consumption patterns with disease incidence. Consequently, as there is no single path to UHC, this will provide a window of opportunity for researchers to examine the potential opportunities of health financing reforms that can be explored to reach UHC while promoting preventive behaviour at the same time.
Conclusion and Recommendations
While most countries have kept pace with data revolution and ensuring big data by increasing the scope and coverage of existing household surveys, given the challenges associated with improvements in economic conditions and changes in age structure, more still needs to be done to improve the data collection methods so as to measure health outcomes and the attainment of universal health care coverage. This can be achieved by continuous improvements of existing household surveys to ensure comprehensiveness in how data collection is done so as to enhance the diversity of those surveys in availing scientific evidence on many grounds apart from their primary aim.
With regards to HIES, despite their primary aim of assisting in compilation of consumer price index, empirical evidence that has employed these surveys has guided policy on how to effectively strengthen UHC reforms. In some countries, income and expenditure surveys are currently guiding debates on how to promote preventive behaviour in efforts to curb NCDs in some developing countries. This has been made possible by the disaggregation of food items to allow an observation of consumption patterns for each item over time. For Botswana, there is need for data to be collected on a disaggregated form to enable an understanding of consumption patterns of different commodities in order to suggest possible health reforms to be adopted.
Since 1995/96, South Africa has conducted nationally representative income and expenditure surveys every 5 years (Statistics South Africa, 2011). Botswana has so far conducted nationally representative household income and expenditure surveys every 8 years: 1993/94, 2002/03 and 2009/10 [24].
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