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Some Factors That Hinder Women Participation in Social, Political and Economic Activities in Tanzania

Elisia Losindilo***, AS Mussa*, RRJ Akarro**

**Assistant Lecturer, University of Dar es Salaam, Department of Mathematics, PO Box 35062, Dar es Salaam, Tanzania

*Senior Lecturer, Department of Statistics, PO Box 35047, Dar es Salaam, Tanzania

**Associate Professor, Department of Statistics, PO Box 35047, Dar es Salaam, Tanzania

*Corresponding Author:
RRJ Akarro
E-mail: [email protected]

Published date: March 14, 2010

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Abstract

This paper addresses women’s participation in social, political and economic activities. In particular, factors that hinder women from participating in social, political and economic activities in mainland Tanzania are discussed. Analysis shows that factors such as level of education, type of place of residence, marital status, religion, region of residence and age groups, with different levels of magnitude contribute differently to their poor participation. Cross-tabulation is used to establish the relationship between “participation” as the dependent variable and the aforementioned factors. Multiple logistic regressions were used to determine the relative importance of the factors. Results indicate that place of residence; age group and region of residence are significant while education and religion are insignificant.

Keywords

Women participation; social; political; economic; activities; Tanzania.

Introduction

The reality of the women of southern Africa, including Tanzania, is that they remain a vulnerable marginalized group that is yet to enjoy equality in status and access to services and resources with their counterparts. Women are found at the “bottom rung of poverty, of illiteracy, of landlessness” and are concentrated in rural areas where facilities and services are scarce. Women are the most affected by negative impacts of economic adjustment programmes. Cuts in social expenditure such as in health and education mostly affect women and girls who are victims of the worst forms of violence [1]. The customary laws have given men more power and control over resources and decision-making processes, hence making the system both patriarchal and undemocratic. This has led to widely differing access to resources and decision-making processes, which is partly the reason why women’s socio-economic and political status remain low.

Although women turn up in large numbers in every political election whereby they constitute more than half of the population in many countries, yet they are visibly absent in positions in the Government, parastatal organizations and private companies. Women remain concentrated in the so-called “female professions” and at the very best in the middle management positions, and hence miss the decision-making processes at higher levels. Thus, women are grossly underrepresented wherever decisions are made, regardless of the level or the institution involved. This is especially true within government machinery despite the fact Tanzania is signatory to many UN conventions and resolutions on gender equality. Women provide major labour input to many economic activities, varying from informal employment to selfemployment. Opportunities for women in the formal sector are very limited due to historical, social, cultural and political factors. Therefore, most women are compelled to find employment in the informal sector, which include business in petty trading in urban and rural areas, street trade, food processing, local beer brewing and hair salons. A few employed and unemployed women become sex workers, usually to supplement their incomes. This paper is aimed at identifying some factors that hinder women in participation in social, political and economic activities in Tanzania mainland. This is done with a view of designing programmes that may rectify the situation.

Methods

The Tanzanian mainland regions are classified into seven geographic zones [2]. The reasons for using zones are that each geographic area will have a relatively large number of cases and sampling errors will thus be reduced. The zones are selected in such a manner that cultural homogeneity is made as close as possible. The zones are defined below:-

Western: Tabora, Shinyanga and Kigoma.

Northern: Kilimanjaro, Tanga, Arusha and Manyara.

Central: Dodoma and Singida.

Southern Highlands: Mbeya, Iringa and Rukwa.

Lake: Kagera, Mwanza and Mara.

Eastern: Dar es salaam, Pwani and Morogoro.

Southern: Lindi, Mtwara and Ruvuma.

From the seven zones, the study selected the regions, Rukwa, Mwanza and Lindi to represent southern highlands, lake and southern zones respectively. The study, also decided to take Tabora region to represent western and central zones, due to their similar characteristics. Likewise, Dar es Salaam region represented eastern zone. Population of interest was women aged between 15 and 49 years. Hence, the study used secondary data collected from 2004/05 Tanzania Demographic and Health Survey, [2] a national sample survey of all women aged 15-49 and all men aged 15-49 years in a sub-sample of one-third of the household who were individually interviewed, and who were either permanent residents of the households or visitors, who were eligible to be interviewed, that were present in the household on the night before the survey. The data were expected to provide sufficient information on the factors that hinder women from participating in social, political and economic activities. A sample of 10,329 women was obtained in this manner. For a detailed information on data collection procedure by see [2]. Since the dependent variables were dichotomous, logistic regression was used in the analysis. In this study, the dependent variables for the logistic regression analysis were; currently working, selling land without permission, operate her account, knowledge of loan programmes and given loan. These were regarded as proxies to social, political, as well as economic participation. The dependent variables take a value of 1 when the individual declares that she participates and a value of zero when she does not participate. The independent variables are level of education, place of residence, marital status, religion, region of residence and age group.

The logistic regression used was of the form y =Probability (event) where z is the linear combination and is given by z = β01X1+…+βnXn + ε, and that X1 …Xn are independent variables [3].

Cross-tabulation is used to establish the relationship between variables by taking into account observed and expected values. Multiple logistic regressions was used to determine the relative importance of the factors that hinder women’s participation in social, political and economic activities, and to eliminate any that did not contribute significantly to explaining the variance in participation, once other factors were taken into account.

Results and Discussion

From a sample of 10,329 women in mainland Tanzania, the study showed that 75.7% live in rural areas while 24.3% live in urban areas. Moreover the age distribution showed that a much higher proportion of the population was in the younger age groups. Those aged between 15 and 19 years were 22.3%, and that 83% were below 40 years of age.

The majority of respondents were married ( 58.5%), followed by those not in a union (34.3%) that is, single and 7.2% were just living with a man. The education level among respondents was very low since the majority (60.7%) had primary level of education, 11.7% had secondary level of education and very few (0.1%) had university level of education.

Level of Education

Results show that women with post-secondary training level of education (79.5%), work more than those with post primary level of education and secondary level of education, (75.7%) and (39.9%) respectively. All women with postprimary training and university levels of education can sell land without permission; while about slightly less than a half of the women at primary level of education could not do so. The chi-square test has shown significant difference between level of education and selling land without permission (chi-square value: 13.467 and p value 0.009). On the other hand, there is significant association between level of education and respondents operating an account, with the chi-square test giving a value of 20.107 and an extreme small asymptotic significant value. A large group comprises of women with post-primary training, post-secondary training and university levels of education, while women with primary and secondary levels of education constitute a small group.

The results show that women with pre-school level of education know nothing about loan programmes. Around half of the post-primary trained women (50.4%) have knowledge of loan programmes as well as the post-secondary trained (44.1%). The above test gave the chi-square value of 35.383 and extreme small asymptotic significant value. It thus shows that the relationship between education levels and women’s knowledge of loan programmes as statistically significant. All women with pre-school and university levels of education had no any loan. The post-secondary training (15.9%) and primary level of education (2.9%) had loans. The chi-square test (with a value of 120.113) has shown significant difference in relationship between education level and women with a loan.

Place of Residence

The study shows that (85.5%) of women in Lindi Region, (84.1%) in Rukwa and (28.4%) in Dar es Salaam are currently working. The rate of working women is more pronounced in rural areas (72.7%) than in urban (52.9%).

Selling of land without permission is not restricted to particular region as far as women are concerned. The findings show that there is no significant association between place of residence and selling land without permission. The test gave the chi-square value of 2.790 and asymptotic significant value of 0.248 that shows the relationship is statistically insignificant.

Again, the results show that there is no significant association between the place of residence and operating an account. The test gave the chi-square value of 1.748 and asymptotic significant value of 0.186, which shows the relationship, is statistically insignificant.

Lindi region respondents, (55.2%), have knowledge of loan programmes, followed by respondents in Dar es Salaam region (46.8%) and only 15.9% of respondents in Rukwa region. The test gave the chi-square value of 192.706 and asymptotic significant value of 0.000 that shows that the relationship between region of residence and women’s knowledge of loan programmes is statistically significant. However, knowledge of loan programmes is greater among women in urban areas (42.4%) than in rural areas (24.5%). The test gave the chi-square value of 296.629 and extreme small asymptotic significant value, which shows that the relationship between types of place of residence and women’s knowledge of loan programmes is statistically significant.

The results show that (7.3%) of respondents in Dar es Salaam region were given loan, followed by Mwanza region respondents, (3.7%). The situation seemed to be worse in Rukwa region where only 1.7% of respondents were given loan. The results show that very few women were able to obtain loan, perhaps due to institutions requirements. The test gave the chi-square value of 24.653 and asymptotic significant value of 0.000 that shows that the relationship between place of residence and women with a loan is statistically significant. However, only 5.6% of urban women are given loans as compared with 2.3% of rural women, and that there is a relationship between place of residence and respondents receiving loan.

Age Group

The group of women found with largest working respondents was the one aged between 40 and 44 years old (84.6%), followed by a group aged between 45 and 49 years, (82.1%). The group with least women who were working was aged between 15 and 19 (43.6%). The findings have shown that age groups and respondents currently working are related, with chi-square value of 940.118 and extreme small asymptotic significant value.

Selling land without permission has shown to be high among women aged 40 to 44 years (73.9%) and very low in the age group of 15 and 19 years. The chi-square value of 24.293 was calculated and asymptotic significant value of 0.019 which indicated that the relationship between age groups and women selling land without permission as statistically significant.

Again, the results show that there is no significant association between age groups and operating an account. The test gave the chi-square value of 7.924 and asymptotic significant value of 0.244 that shows the relationship is statistically insignificant. However, knowledge of loan programmes is good among women aged between 40 and 44 years (36.2%), and the knowledge is almost the same for women aged 30 to 34 years (33.4%), 45 to 49 years (33.0%) and 35 to 39 years (32.7%). As a result, women aged between 40 and 44 years seemed to be given loans more than any other age group. Women aged 15 and 19 years (18.2%) have little knowledge of loan programmes. This is obvious since most of them are in the schooling age. The test for age group and knowledge of loan programmes gave the chi-square value of 186.630 and asymptotic significant value of 0.000 that shows the relationship is statistically significant.

Religion

There were more Christian women (Catholics and Protestants) who have responded to be currently working followed by Muslim women and those with no religion. Though those with no religion were relatively few, a higher percentage of them were working, (77.9%), while Catholics, Protestants and Muslims were 75.1%, 74.4% and 58.7% respectively. The results show the relationship to be statistically significant between religion and respondents currently working with chisquare value of 328.046 and asymptotic significant value of 0.000.

The results also show that there is a relationship between religious affiliations and respondents selling land without permission, since the test gave the chi-square value of 12.750 and asymptotic significant value of 0.047 that shows the relationship is statistically significant.

It has been realized that 83.9% of Catholics, 82.8% of Protestants and 62.8% of Muslims women operate account. The test gave the chi-square value of 17.858 and asymptotic significant value of 0.000 that shows that the relationship between religion and women operating account is statistically significant.

Knowledge of loan programmes is good among Catholics (32.5%), followed by Protestants and Muslims. The test gave the chi-square value of 218.332 and asymptotic significant value of 0.000 that shows that the relationship between religion and women’s knowledge of loan programmes is statistically significant.

The results show that only 0.3% of the non-religious are given loan as compared with 3.4% of Muslims and Catholics and 3.2% of Protestants. The test gave the chi-square value of 26.104 and asymptotic significant value of 0.000 that shows that the relationship between religion and women with a loan is statistically significant.

Marital Status

The percentage of women working is almost the same for both married women and those living with a man, (74.7%) and (75.3%) respectively and (54.8%) for those who are not in a union. The test gave the chi-square value of 425.268 and asymptotic significant value of 0.000 that shows that the relationship between marital status and women currently working is statistically significant.

Many women who are living with men, not married, can sell land without permission, (68.1%) than those living alone (64.7%), whereas, married women who can sell land without permission are lesser, (54.9%). The test gave the chisquare value of 4.822 and asymptotic significant value of 0.009 that shows that the relationship between religion and women selling land without permission is statistically significant.

There is no relationship between marital status and operating an account. The test gave the chi-square value of 2.632 and asymptotic significant value of 0.268 that shows that the relationship is statistically insignificant.

Women living with men seem to be most knowledgeable about loan programmes (39.4%), followed by married women and the last group is women who are not in a union. The results gave the chi-square value of 54.047 and asymptotic significant of 0.000 that suggests that the relationship between marital status and women’s knowledge of loan programmes is statistically significant.

The percentage of women given a loan is the same for both married women and women living with a man (3.5%), and 2.1% for those women not in a union. The test gave the chi-square value of 15.202 and asymptotic significant value of 0.000 that shows that the relationship between marital status and women with a loan is statistically significant.

The results show that (100%) of women in Rukwa region operate their own account, followed by Dar es Salaam region (90.7%), but the situation is worse in Tabora region as only (25%) operate an account. The above test gave the chisquare value of 26.548 and asymptotic significant value of 0.000 that shows that the relationship between marital status and women operating an account is statistically significant. All these results are in line with [4]. The results discussed above are summarized in Table 1 below.

  Working Selling Land without permission Operating Account Loan Programme Having Loan
Level of Education Post Secondary work more than primary and secondary level. Post primary and University level can sell. Not as much as primary level. More of post primary and secondary training, followed by University level and lastly primary and secondary level. Post primary and secondary training have knowledge while pre- primary are not aware. Pre-school and university levels of education had no any loan. Very few post primary and secondary trained.
Place of Residence More working in Lindi, Rukwa and Dar es Salaam. Generally rural work more than urban Not restricted to any particular region No significant differences More  knowledgeable in urban than rural areas More in urban have loans than in rural.
Age Group More working aged 40-44, than aged 45-49, The least working aged 15 -19. High among aged 40-44 and very low in the age group of 15-19 years. No significant association between age groups and operating account. Good among aged 40-44, and equally less good at aged 30-34, 45-49 and 35-39 years. Very little knowledge at age 15-19 years. Those seemed to be given loan were at age 40- 44, more than any other age group.
Religion More working Christians (Catholics and Protestants) than Muslims and those with no religion More Christians (Catholics and Protestants) sell land without permission than Muslims and those with no religion More Catholics than Protestants followed by Muslims and last those with no religion Good among Catholics followed by Protestants and Muslims alike and than those with no religion More Muslims and Catholics followed by Protestants and lastly those with no religion
Marital Status Married women and those living with a man working equally than those who are not in a union More of those living with men, not married, can sell land without permission, than those living alone and lastly married women No relationship found. Knowledgeable are those living with men followed by married women and the last group is women who are not in a union. Same for both married and women living with a man and than those not in a union

Table 1: Summary Table

Logistic Regression Results

Logistic regression model was run to identify the relationship between contributing factors. The first logistic regression regarded working as the dependent variable and age, place of residence as covariates. The odds ratio shows that women aged 35-39 were 1.6 times more likely to be in work than those aged 45-49. On the other hand, those aged 30-34 were roughly 3 times less likely to be in work than those aged 45-49, while those aged 15-19 were two times more likely to be in work than those aged 45-49. This is to be expected because those aged 15-39 years were more energetic than those aged 45-49 years. The odds ratio suggests that as far as place of residence are concerned; urban women were 2.6 times less likely to be in a work as compared with rural women. This is because most of the rural women in Tanzania have a long day that is normally overloaded with a myriad of activities. The odds ratio further show that women in Dar es Salaam are1.8 times less likely to be in a work as compared with those in Lindi. On the other hand women in Tabora are10 times less likely to be in a work as compared with those in Lindi, while women in Rukwa are 3.4 times less likely to be in a work than those in Lindi. Another logistic regression regarded operating an account and knowledge on loan programmes as dependent variables and the factors were region, place of residence (whether rural or urban), age. As regards to regions in terms of operating an account, the odds ratio suggests that women in Dar es Salaam are 1033 times more likely to operate their own account, while those in Tabora are 729 times more likely to operate their own account as compared with those in Lindi.

With regard to age group, the odds ratio shows that women aged 20-24 are roughly 1.9 times more likely to have knowledge of loan programmes than those aged 45-49. On the other hand, those aged 25-29 are 1.7 times more likely to have knowledge than those aged 45-49, while those aged 35-39 are roughly 1.5 times more likely to have knowledge of loan programmes than those aged 45-49. This is because those aged 15-35 years are considered as the greatest and most important asset for the present and future generations. Their strength in number, their ability to learn, develop and acquire new skills and qualifies young women to be a vital group of people who can contribute enormously to the national economy and worldwide.

As regards place of residence, the odds ratio suggests that compared with rural women, urban women are 2.5 times more likely to have knowledge of loan programmes. This is to be expected, as women in rural areas are less likely to be exposed to mass media, as some of the training programmes regarding loans for women were broadcast through various media channels. Transport is another barrier, as in most of the rural areas it is very poor, and so it is difficult for women to attend centres where training is taking place.

The odds ratio further shows that women in Dar es Salaam are 4.1 times less likely to have knowledge of loan programmes than those in Lindi. On the other hand, women in Tabora are 3 times less likely to have knowledge of loan programmes than those in Lindi, while women in Rukwa are 2.6 times less likely to have knowledge of loan programmes than those in Lindi. Likewise, women in Mwanza are 6 times less likely to have knowledge of loan programmes than those in Lindi.

As regards age group, the odds ratio suggests that, compared with women with aged 45-49, women aged 20-24 are 9.5 times more likely to be given a loan. On the other hand, women aged 25-29 are 9 times more likely to be given a loan than those aged 45-49, while those aged 35-39 are 5.4 times more likely to be given a loan as compared with those with aged 45-49. Women aged 40-44 are 7.5 times more likely to be given a loan as compare with those aged 45-49.

Logistic regression results showed that education level, age group, place of residence, religion and region were statistically significant with women currently working. The odds ratio shows that women aged 35-39 were 1.6 times more likely to be in work than those aged 45-49. Those aged 30-34 were roughly 3 times less likely to be in work than those aged 45-49, while those aged 15-19 were two times more likely to be in work compared with those aged 45-49.

The odds ratio showed that, urban women were 2.6 times less likely to work compared to rural women.

The odds ratio furthermore showed that women in Dar es Salaam were1.8 times less likely to be in work compared with those in Lindi. On the other hand women in Tabora were10 times less likely to be in work compared with those in Lindi, while women in Rukwa were3.4 times less likely to be in work than those in Lindi.

As regards to women selling land without permission, logistic regression results showed that education level, age group, religion, marital status and region were insignificant.

Logistic regression further showed that place of residence and region of residence were statistically significant with women operating an account. The odds ratio suggested that, compared with women in Lindi, women in Dar es Salaam were 1033 times more likely to operate their own account, while those in Tabora were 729 times more likely to operate their own account than those in Lindi.

Furthermore, the results showed that age group, place of residence and region were statistically significant regarding knowledge of loan programmes. The odds ratio showed that women aged 20-24 were roughly 1.9 times more likely to have knowledge of loan programmes than those aged 45-49. Those aged 25-29 were 1.7 times more likely to have knowledge than those aged 45-49, and those aged 35-39 were roughly 1.5 times more likely to have knowledge of loan programmes than those aged 45-49. Moreover, the odds ratio suggested that compared with rural women, urban women were 2.5 times more likely to have knowledge of loan programmes.

The odds ratio showed that women in Dar es Salaam were 4.1 times less likely to have knowledge of loan programmes than those in Lindi. Women in Tabora were 3 times less likely to have knowledge of loan programmes than those in Lindi, while women in Rukwa were 2.6 times less likely to have knowledge of loan programmes than those in Lindi. Likewise, women in Mwanza were 6 times less likely to have knowledge of loan programmes than those in Lindi.

The results showed that education level, age group and place of residence were statistically significant regarding women being given a loan. The odds ratio suggested that, compared with women aged 45-49, women aged 20-24 were 9.5 times more likely to be given a loan. Women aged 25-29 were 9 times more likely to be given a loan than those aged 45- 49, while those aged 35-39 were 5.4 times more likely to be given a loan as compared with those aged 45-49. Women aged 40-44 were 7.5 times more likely to be given a loan as compared with those aged 45-49.

From the above summary of the results, it shows that background status (level of education, place of residence, marital status, religion, region of residence and age group) are the factors that contribute to women’s poor participation in social, political and economic activities, but the factors differ in magnitude. The study further observes that place of residence (Rural, Urban) has an effect on women’s participation in social, political and economic activities. Logistic Regression results are in line with Lusindilo (2007).

Conclusion

Participation in social, political and economic activities was associated with education level, place of residence, age group, religion, marital status and region of residence of the respondents.

From logistic regression results, background status (level of education, place of residence, religion, region of residence and age group) contribute to women’s participation in working, though marital status does not. Furthermore, education level, age groups religion, marital status and region of residence contribute to women’s decision-making, such as selling land. However place of residence and region of residence contribute to women’s operating their own bank account. In addition, age group, place of residence and region of residence contribute to women’s having knowledge of loan programmes. Lastly, age group contributes to women being given a loan.

Therefore, in general, the study concludes that place of residence, region of residence and age group are the factors that hinder women from participating in social, political and economic activities.

The study also concludes that the factors have different levels of magnitude implying that there are other factors that contribute more to women’s poor participation like place of residence, age group and region of residence.

On the other hand, level of education and religion contribute less to women’s poor participation in social, political and economic activities.

The study furthermore concludes that place of residence (Urban, Rural) has a great effect on women’s participation in social, political and economic activities. The study observes that women in rural areas have little knowledge of loan programmes compared with women in urban areas; also rural women work more than urban women do.

Recommendations

In general, the study on the factors that hinder women from participating in social, political and economic activities has observed that women are faced with various constraints. As a result, policy makers and Government could intervene in the following areas

• Banking policies: Banking policies could develop strategies for ensuring that obstacles preventing women from borrowing are addressed. In addition, banking policies should encourage mobilization of financial resources from all possible sources, such as personal savings, informal sources like Rotating Saving and Credit Association (ROSCAs) and guarantee informal schemes as well as group savings.

• Social-Cultural Dynamics: In some socio-cultural settings, women remain second-class citizens. This prevents women from making decisions and owning property, and so policy makers and NGOs should aim at modifying the low status of women and enhancing co-operation between men and women to promote sustainable development.

• Women’s representation on decision-making bodies should be increased in order to represent their concerns, at both national and local levels.

• Civic Education: There is a need for the Government to conduct civic education on an on-going basis, link with, and support NGOs that are engaged in these activities.

• Access to education and particularly higher education is the key to women’s empowerment in Tanzania. Women face numerous constraints in accessing education and training at all levels. Though existing social attitudes try to encourage girls to receive education, boys have an added advantage when it comes to access because they are not subject to home chores, pregnancies, etc. There is a need to link up education programmes, like Female Undergraduate Scholarship Programme (FUSP) managed by the UDSM (University of Dar es Salaam), with other major initiatives that promote girls’ and women’s empowerment.

• The Government should provide financial support schemes for girls and women in training institutions. The policy makers should design adult education programmes to encourage and promote the enrolment and attendance of women. There is a need to review the school curriculum in order to strengthen and encourage participation and achievement of girls in mathematics and science subjects.

The policy makers, together with NGOs (Non Governmental Organization) like UMATI (Family Planning Association of Tanzania)

• Should concentrate on policies that encourage and facilitate the return of those who have dropped out due to pregnancy.

• Land policy should promote fair access to land, fair distribution of land titles to men and women and all parties involved in any co-ownership, so that women stand a better chance of using land as a resource for starting Income Generating Activities (IGAs). This could also place women in a better position to obtain credit for production activities.

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