life quality in rural area: a case study on … · annals. food science and technology 2017 life...

Annals. Food Science and Technology 2017

LIFE QUALITY IN RURAL AREA: A CASE STUDY ON OCCUPATIONAL DEPRIVATION IN GIURGIU COUNTY

Corneliu Sorin Iorga*1, Claudia Elena Mosoiu1, Nastasia Belc1, Livia Apostol1, Oana

Mihaela Niculae1, Claudia Elena Stoican1, Roxana Petricica1, Adrian Ovidiu Romedea1

1National Research & Development Institute for Food Bioresources – IBA Bucharest, 5, Baneasa Ancuta Street,

District 2, 020323, Bucharest, Romania *E-mail: [email protected]

ABSTRACT

The last decades UE mobilised a large amount of efforts, monney and resources in improving rural living condition in the Member States. The rural quality of life is significantly related to working environment. In Romania the desindustralization of urban area pushed back in rural area many people. Their skills are not allways apropriate to the new working environment, so they have difficulties in finding and/or assuming a job. The main dificulty in understanding the present situation is the lack of data. The type of questions to be answered generates reluctance to people interviewed. The relations between residents’ age, gender, education or marital status and life quality are essential in understanding the drivers of rural economy and its working environment, both formal or informal, as well as developing rural development strategies and local policies. The study aim to address the relations between individual caracteristics and their status on the local working environment for 357 persons from 30 villages from Giurgiu county. The random sample group was face-to-face interviewed based on a questionnaire covering ocupational items and personal data. Data analysis showed influence of personal caracteristics on the employment status of the persons.

Keywords: rural development, working environment, professional skills, job expectations, rural unemployment

Received: 31.07.2017 Received in revised form: 30.08.2017 Accepted: 05.09.2017

1. INTRODUCTION

Due to economic and social differences between

rural and urban areas, the lifestyle of individuals

is affected. Thus, in wealthier countries, rural

living conditions create a higher level of

wellbeing (F. Requena et al. 2016). According to

A. Martinovska (A. Martinovska et al. 2016), the

rural development depends on farmers’ positive

attitude, support from the social environment (in

Serbia and Bosnia and Herzegovina) and

behavioural control (in Bosnia and Herzegovina

and Macedonia). At the individual level, the

wellbeing for young people is centred around

their own lives and is determined by

relationships, psychological dimensions and

personal issues (L. Burke et al. 2007). The term

"Quality of life" is different from "Quality of

Living Conditions” and has been quantitatively

deducted through a model proposed by L. R.

D’Agostini (L. R. D’Agostini et al. 2008). A

study on girls showed that quality of life is a

correlation between physical activities and

health which implies less use of computer and

video gaming (M. Casey et al. 2016). Rural

older adults have to cope to specific quality life

challenges and social support or interpersonal

senzitivity are determinant for improving the

quality of life (M. Wedgewoorth et al. 2016).

Besides physical activities, other factors such as

work, reading and writing activities outline the

quality of life both for rural and urban areas (P.

Sampaio et al. 2013). A great importance for

improving lifestyle and quality of life is the

attitude towards traveles, a study conducted in

Vermont, Maine and New Hampshire (J.

Kolodinsky et al. 2013), but also the value of

culture (K. Scott et al. 2016). Another factor

with a great importance for finding a paid job is

the realization of the studies because there are

very few people who have not finished their

studies, but they have a paid job (A. Olgun et al.

2010). For people with health problems, such as

HIV-infected women in Oaxaca, Mexico, the

depression, family and emotional support lead to

the quality of life (C. Holtz et al. 2014). The life

of individuals differs due to

Available on-line at www.afst.valahia.ro 531 Volume 18, Issue 3, 2017


the area in which they live and due to their personal perception of life.

2. MATERIALS AND METHODS

The study used direct interviews with a random sample of 357 persons from rural area of Giurgiu county.

The research covered revenues sources and ocupational status corelated to personal profile. The questionnaire personal profile includes age, location, marital status, education, number of persons in care, status of legal documents: birth, ID, marriage or studies diplomas. Income sources or land in use are also followed. Ocupational items covered the basic profession, work experience, last activity, status on labor market, last job profile. Age, gender, education level and marital status are the considered factors for covariance, upon which is determined the covariance of dependent values list of data. They were seted 3 level of values for age groups, 2 gender categories, 8 educational stages, and 6 for marital status.

Interpretation and analysis of the data was made using IBM SPSS 24 PS IMAGO 4.0 program and Microsoft Excell 2010 program.

The variability was determined with ANOVA method. The covariance disscussion was detailed for relevant results (σ < 0.05).

3. RESULTS AND DISCUSSION

3.1. Results Interviews covered 30 villages in Giurgiu county. Gaujani, Rasuceni and Mihai Bravu have the largest population samples. Comana, Fratesti, Oinacu, Roata de Jos have only 1 person interviwed (Fig. 1). The study concentrated mainly on population between 18 and 45 years old (93.3%), considered to have the most significant developing potential. Youths under 31 y.o. represent 57,4% from the sample (205 persons). From legal point of view, all the group has ID cards. By contrast, only 31,4% (112 persons) have labor cards and 65,3% (223 persons) have studies licenses. Education level data indicate 152 persons (59.7%) with less than 8 classes degree and only 27.1% with high school or higher degrees. 127 persons declare they have 1 or more persons in care, 92.1% of them having 3 or less persons in care.

Fig. 1 Residence distribution of respondents



Table 1. Number of persons in care

Valid Cumulative

Number of persons in care Frequency Percent Percent Percent

1 55 15.4 43.3 43.3

2 47 13.2 37.0 80.3

3 15 4.2 11.8 92.1

4 6 1.7 4.7 96.9

5 1 .3 .8 97.6

6 1 .3 .8 98.4

8 1 .3 .8 99.2

9 1 .3 .8 100.0

Total valid 127 35.6 100.0

Missing sistem 230 64.4

Total 357 100.0

Table 2. Land in use

Valid Cumulative Land area (ha) Frequency Percent Percent Percent

.05 1 .3 3.1 3.1

.10 1 .3 3.1 6.3

.15 1 .3 3.1 9.4

.25 1 .3 3.1 12.5

.50 8 2.2 25.0 37.5

.80 3 .8 9.4 46.9

1.00 4 1.1 12.5 59.4

1.48 1 .3 3.1 62.5

1.70 1 .3 3.1 65.6

1.75 1 .3 3.1 68.8

1.80 1 .3 3.1 71.9

1.86 1 .3 3.1 75.0

2.00 2 .6 6.3 81.3

2.50 2 .6 6.3 87.5

3.00 1 .3 3.1 90.6

4.00 2 .6 6.3 96.9

36.00 1 .3 3.1 100.0

Total valid 32 9.0 100.0


Total 357 100.0

Marital status data indicate mostly single or married persons, 333 persons (94.3%). The result is consistent with the population sample’s age group considered by the study.

Sources of revenues

Only 1 person from the group consider his/hers income as sufficient. The majority (86.6%) apreciate their incomes as at most barely enough or less. 13 persons refused to offer an

answer. For 32 persons (9.0%) to have some land in use is a revenues resource, of witch 59.4% have 1 ha of land or less, indicating a subsistence farming activity (Table 2). The rest of 91% of the respondents are based exclusively on different forms of public or social funding or simply on random incomes. A significant number of subjects (131 persons, 37.7%) did not indicate a source or did not want to offer details (Table 3).



Skills and ocupation 119 respondents declared certificated skills for

53 professions, from a large range of activities.

The rest did not answer (40.3%) or declared themselves as non skilled (87 persons, 24.4%). The working experience varry between 0 and 34

years, declared by 165 respondents (46.2%). Multiple jobs experience was reported by 96 respondents, mostly for 2 to 4 jobs, but also

Table 4. Income distribution

more divers experience was registered (Table 5). The unemployment duration is varying from 3 to 20 years. Yet only 40 respndents offered data on this issue, suggesting a much wider reality. From 357 respondents, 262 (73.4%) declared they do not know the local job opportunities offer. The chances for new jobs is negatively perceived by 58.6% from respondents, according to Table 6.

Valid Cumulative Frequency Percent Percent Percent

Unemployment benefits 9 2.5 2.8 2.8

Children allowances 70 19.6 22.0 24.8

Sickness pension 4 1.1 1.3 26.1

Survivorship pension 6 1.7 1.9 28.0

Social aid 9 2.5 2.8 30.8

Random incomes 92 25.8 28.9 59.7

Others 128 35.9 40.3 100.0

Total valid 318 89.1 100.0


Total 357 100.0

Table 5. Multi jobs experience Valid Cumulative

Frequency Percent Percent Percent

1 63 17.6 39.6 39.6

2 48 13.4 30.2 69.8

3 22 6.2 13.8 83.6

4 11 3.1 6.9 90.6

5 8 2.2 5.0 95.6

6 3 .8 1.9 97.5

7 1 .3 .6 98.1

10 3 .8 1.9 100.0

Total valid 159 44.5 100.0

Missing system 198 55.5

Total 357 100.0

Table 6. Chance to find a job on present economical context

Valid Cumulative Frequency Percent Percent Percent

I am sure I will find a job 36 10.1 12.8 12.8

Probably I will find a job 80 22.4 28.5 41.3

I am not so sure I will find a job 106 29.7 37.7 79.0

I don't think I will find a job 42 11.8 14.9 94.0

No opinion 17 4.8 6.0 100.0

Total valid 281 78.7 100.0

Missing system 76 21.3

Total 357 100.0



Fig. 2. The income sources variance with ager group factor

Fig. 3. Variance of working experience with age group factor

3.2. Disscussion

Covariance analysis showed that number of persons in care is influenced by gender, age group and education level. Although the land in use surface is not depending on any individual factor, the income varry with gender, age group, education level and marital status.

Work experience variance is related to age group, marital status and education level, which is also influencing the multiple jobs experience. While the level of awarness on local jobs opportunities varry by age group and education

level, the expectation of finding new

jobs appear to be depending on gender basis only.

Group age influence The 18-31 y.o. group seems to rely mainly on random incomes, or do not prefer to dislose their sources. The adult group, 32-45 y.o. is relying also on children allowances, sickness pensions or survival pensions. It is significant that all the groups do not indicate unemployment benefits (Fig. 2). They might exit from the unemployment benefits program or never be eligible fo it. This is an indicator of sever material deprivation. Only 165 persons indicated thei working experience.



Although the 18-31 y.o. has less experience, the data revealed that also the 32-45 y.o. age group has a large distribution of working experience, even from 1 year. Also the group over 45 y.o. seems to have a large distribution af the working experience. This indicates an unsustainable working environment, with many lay-offs or job dissapearance (Fig. 3).

The respondents level of information on local job opportunities indicates that the 18-31 y.o. age group is significantly less informed (10%) than the 32-45 y.o. group (19%) or over 45 y.o. group (35% ). That is suggesting a lack of interest of the rural younger generation for

local jobs, or even lack of trust in rural working environment (Fig 4). Education influence The nember of persons in care it is decreasing with the educational level. That suggest that multi generation families are rare and the people in care are mostly children (Tabe 5). Uneducated persons rely mainly on social aid, while the under 8 classes graduates are based on children allowances and random incomes. Children allowances are relevant for all medium educated categories. All categories depend in great measure on random or other types of incomes (Fig. 6).

Fig. 4. Variance of the information level on local jobs opportunities with age group factor

Fig. 5. Number of persons in care – variation upon education level



Fig. 6. Income sources variation with educational level

Fig. 7. Working experience variation with education level

Fig. 8. Multiple jobs experience variation with education level

Lower education is generating also less working experience, wich suggest that lower education offers less chances for regular working contracts, generating retirement working seniority (Fig. 7). Lack of education appears to offer less flexibility for multiple jobs, while medium level education seems apropriate for 2 or more jobs experience.

The university degree level jobs are more stable, people do not need to change to many jobs (Fig. 8). Information level about local jobs is increasing with education level of the respondents, from almost absent for uneducated people to almost 40% for university graduates (Fig. 9).



Fig.9. Variation af information about local jobs opportunities level upon education level

Fig.10. People in care – gender weight evolution

Fig.11. Income sources gender weght evolution

Gender influence

Women are more involved in taking care of other people. The proportion is more relevant for 1 to 5 persons, while bigger number are sugessting rather exceptions (Fig. 10). They are significantly more dependent on social wellfare, while men appear to rely on random and other income sourges (Fig.11). Women are

more skeptical on finding a job in present economical situation. While they are more willing to address this question, their expectations appear to be lower (Fig. 12). Data indicate a potential lack of gender equality in the rural community.



Fig.12. Gender variation of job expectations

Fig. 13. Incomes sources variation with marital status

Fig.14. Working experience variation with marital status

4. CONCLUSIONS

The study focused on rural population from Giurgiu county. The group sample consisted in 357 persons, mainly under 45 years old, form 30 villages. Data revealed that education level in rural area is rather low, 58.7% of

respondents have less than 8 classes graduated. The income is considered barely enough of less by 86.6% of respondents. Only 9% of the respondents have or have in work some land, majority of them less than 1 ha.



Although majority of respondents rely their income on public funds, many showed reluctants to answer this questions.

There is a large range of certified skills in the group, but also a high rate of people without any qualification (24.4%). Consequently a significant low expectation on finding a job in the area.

Age, education and marital status influence the life quality of persons. Gender influence also

indicates a potential discrimination environment.

5. ACKNOLEDGEMENTS

The study was financed by The European

Commission and The Romanian Government through the project POSDRU/83/5.2/S/53508 “Valorificarea capitalului uman în zonele rurale din Romania, prin dobândirea de abilităti si cunostinte cu valoare adaugată ridicată”

6. REFERENCES

[1] Felix Requena, Rural–urban living and level of

economic development as factors in subjective well-being, Social Indicators Research, 128, 2016, 693–708;

[2] Aleksandra Martinovska Stojcheska, Ana Kotevska, Natalija Bogdanov, Aleksandra Nikolic, How do farmers respond to rural development policy challenges? Evidence from Macedonia, Serbia and Bosnia and Herzegovina, Land Use Policy, 59, 2016, 71–83;

[3] Lisa Burke, Paula M. Geldens, Subjective wellbeing and its meaning for young people in a rural australian center , Social Indicators Research 82, 2007, 165–187;

[4] Luiz R. D’Agostini, Alfredo C. Fantini, Quality of

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Mooney, W. Payne, Patterns of time use among regional and rural adolescent girls: Associations with correlates of physical activity and health-related quality of life, Journal of Science and Medicine in Sport, 19, 2016, 931–935;

[6] Monika Wedgeworth, EdD, Michael A. LaRocca, MA, William F. Chaplin, PhD, Forrest Scogin, PhD, The role of interpersonal sensitivity, social support, and quality of life in rural older adults, Geriatric Nursing xx, 2016, 1-5

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[8] Jane M. Kolodinsky, Thomas Patrick DeSisto, David Propen, Matthew E. Putnam, Erin Roche, William R. Sawyer, It is not how far you go, it is whether you can get there: modeling the effects of mobility on quality of life in rural New England, Journal of Transport Geography , 31, 2,013 113– 122;

[9] Karen Scott, Frances Rowe, Venda Pollock, Creating the good life? A wellbeing perspective on cultural value in rural development, Journal of Rural Studies xxx, 2016, 1-10;

[10] Akın Olgun, Sevtap Guler Gumus, Hakan Adanacioglu, Schooling and factors affecting decisions on schooling by household members in the rural areas of Turkey, Social Indicators Research, 98, 2010, 533–543;

[11] Carol Holtz, Richard Sowell, Lewis VanBrackle, Gabriela Velasquez, Virginia Hernandez-Alonso, A quantitative study of factors influencing quality of life in rural mexican women diagnosed with HIV, Journal of the Association of nurses in aids care, Vol. 25, No. 6, November/December 2014, 555-567.


life quality in rural area: a case study on … · annals. food science and technology 2017 life...

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