KnE Life Sciences | The 2nd International Meeting of Public Health 2016 (IMOPH) – Part II | pages: 422–429

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1. Introduction

The Indonesia Ministry of Health uses the infant, child, and maternal mortality rate, also morbidity figures of some diseases to asses the health degree. The degree of health status is influenced by several factors, including health factors, availability of health infrastructure, economic, education, social environment, heredity, and sanitation that is always forgotten by the Indonesian goverment.

If a city or village does not have good sanitation system, the environment will be polluted and public health will be disturbed so that the disease will be coming. The poor sanitation condition will potentially lead to increasing cases ofdiarrhea, malaria, dengue fever, and filariasis. In this study, the author will discuss the relationship between sanitation and diarrhea, because diarrhea is the direct impact of poor sanitary condition while malaria, dengue fever and filariasis indirect cause of poor sanitation which are mediated by mosquitos as the vector disease.

Diarrhea is endemic. The potential disease outbreak of diarrhea is often accompanied by death.. The cause of diarrhea in the community is the poor health behavior, poor waste management, and contaminated drinking water. There were 201,671 of diarrhea patient's cases in Aceh and only 89,447 patients that were treated. There were only 44.25% of this incidence that could be treated by Dinas Kesehatan Provinsi Aceh in 2015.

Kabupaten Pidie through sanitation working group began thinking to improve sanitation plan, develop, implementation, supervise and monitor the future development of sanitation. The government of Pidie realized that sanitation infrastructure was poor, indicated by the high incidence of diarrhea in Pidie by the third number after Northern Aceh and Bieuren based on Aceh health profile. The current domestic wastewater coverage in Pidie can be seen in Table 1 while the risked area and sanitation problems can be seen in Figure 1 (PPSP 2015).

Table 1

Domestic Wastewater Service Coverage Current In Pidie.

Village Area Bad Sanitation Sanitation with septic tank
Without Toilet* (family) System Onsite System Offsite
Cubluk ***, without septic tank** (family) Toilet with septic tank (family) MCK With Communal System Scale
/Toilet communal Area/
(family) Offside
Toilet Communal**** (family) Septic tank communal 1 > 10 KK (family) Wastewater Treat-ment Plant Communal (family) Offsite treatment (family)
1 2 3 4 5 6 7 8 9
Village Areas
Kec. Batee 4.887 471 331 72 45    - - -
Kec. Delima 4.899 2.938 882 96 84    - - -
Kec. Geumpang 1.821 463 45 17 12    - - -
Kec. Glumpang Baro 2.426 1.355 520 43 42    - - -
Kec. Glumpang Tiga 4.586 3.467 435 83 56    - - -
Kec. Grong-Grong 1.626 1.155 62 200 21    - - -
Kec. Indra Jaya 5.977 4.326 429 96 91    - - -
Kec. Kembang Tanjong 5.060 3.009 960 89 90    - - -
Kec. Keumala 2.342 1.141 312 41 41    - - -
Without Toilet* (family) System Onsite System Offsite
Cubluk ***, without septic tank** (family) Toilet with septic tank (family) MCK With Communal System Scale
/Toilet communal Area/
(family) Offside
Toilet Communal**** (family) Septic tank communal 1 > 10 KK (family) Wastewater Treat-ment Plant Communal (family) Offsite treatment (family)
Kec. Mane 2.000 653 61 15 12    - - -
Kec. Mila 2.423 1.619 232 44 42    - - -
Kec. Muara Tiga 4.626 2.601 304 59 47    - - -
Kec. Padang Tiji 5.176 2.770 858 126 130    - - -
Kec. Peukan Baro 4.796 3.136 348 105 111    - - -
Kec. Sakti 4.913 3.249 397 108 110    - - -
Kec. Simpang Tiga 5.314 1.095 3,232 86 110    - - -
Kec. Tangse 6.205 2.733 399 75 113    - - -
Kec. Tiro/Truseb 1.866 1.492 104 38 24    - - -
Kec. Titeu 1.796 1.445 93 19 25    - - -
Urban Areas
Kec. Kota Sigli 4.987 3.310 816 42 44    - - -
Kecamatan Mutiara 4.808 3.023 887 68 65    - - -
Kecamatan Mutiara Timur 8.120 4.814 1,736 117 123    - - -
Kecamatan Pidie 10.588 4.868 3,943 139 147    - - -

2. Methods

Validity refers to the approximate truth of an inference. Valid is the extentto which relevant evidence supports that inference as bring true or correct. Usually, that evidence comes from both empirical findings and the consistency of these findings with other sources of knowledge, including past finding and theories. Assessing validity always entails fallible human judgments. Validity is not absolute; various degrees of validity can be invoked. As a result, when we use prefaced by approximant or tentatively (Shadish et al. 2002).

Figure 1

Risk areas and sanitation problems.

fig-1.jpg

In this study, validity inference was assessed using Null Hypothesis (Ho) and the Alternative Hypothesis (H1) with F test. F test know as test model/Anova test, that test to see how of independent variables (x) the influence the dependent variables (y), or to test the regression model that we make good and significant or not good and not significant. In this study, we have to of the independent variable, there are Number of families who defecation (x 1 ) and Number of families who have unsafe latrines (x j ). And the dependent variable is diarrhea (y). F test can be done by comparing the F arithmetic with F table, where if F arithmetic > F table (Ho rejected and H1 accepted) and where if F arithmetic < F table (Ho accepted and H1 rejected).

3. Results and Discussion

This study will be used One – Way Anova Method, where Ho is sanitation have a significant effect on diarrhea; H1 is no significant effect of sanitation on diarrhea and analysis data with confidence level 95% and 5% error. The amount data is number of families who defecation (x 1 ) and the number of families who have unsafe latrines (x 2 ) on 23 sub-districts in Pidie (number of data 46) and the dependent variable (y) is diarrhea.

Table 2

Analysis data.


Number of families who defecation (x 1 ) xij 2 Number of families who have unsafe latrines (x j ) xij 2
4.887 23.882.769 471 221841
4.899 24.000.201 2.938 8631844
1.821 3.316.041 463 214369
2.426 5.885.476 1.355 1836025
4.586 21.031.396 3.467 12020089
1.626 2.643.876 1.155 1334025
5.977 35.724.529 4.326 18714276
5.060 25.603.600 3.009 9054081
2.342 5.484.964 1.141 1301881
2.000 4.000.000 653 426409
2.423 5.870.929 1.619 2621161
4.626 21.399.876 2.601 6765201
5.176 26.790.976 2.770 7672900
4.796 23.001.616 3.136 9834496
4.913 24.137.569 3.249 10556001
5.314 28.238.596 1.095 1199025
6.205 38.502.025 2.733 7469289
1.866 3.481.956 1.492 2226064
1.796 3.225.616 1.445 2088025
4.987 24.870.169 3.310 10956100
4.808 23.116.864 3.023 9138529
8.120 65.934.400 4.814 23174596
10.588 112.105.744 4.868 23697424
101.242 552.249.188 55.133 171.153.651
Total (T)=101.242+55.133=156.375
ΣTi2=101.2422+55.1332=13.289.590.253
Σxij2=552.249.188+171.153.651=723.402.839

Where: k = 2; N = 46

Andthen :k(N1)=2(461)=90
Nk1=46(2)1=91
k1=21=1

Correction (C)

C=T2k.n=156.37522×46=265.795.006

(7)

The sum of squares between sample (SSTr)

SSTr=Ti2NC=13.289.590.25346266.795.006=22.109.129

(8)

Sum of squares total (SST)

SST=xij2C=334.272.737.897.289.000265.795.006=334.272.737.621.493.994

Sum of squares of error sample (SSE)

SSE=SSTSSTr=334.272.737.621.493.99422.109.129=334.272.737.599.384.865
Table 3

The Formula of Recapitulation analysis of variance.


Variation Degrees of dependent Sum of squares Mean of squares RKf
df
Treatment k - 1 SSTr Ms(Tr)=SSTr/(k-1) MSTr/MSE
Error k (N -1) SSE MSE=SSE/k(n-1)
Sum Nk - 1 SST

Then:

Table 4

Recapitulation analysis of variance.


Variation Degrees of dependent Sum of squares Mean of squares RKf
df
Treatment 1 22.109.129 22.109.129 5.95269E-09
Error 90 334.272.737.559.384.865 3.714.141.528.882.040
Sum 91 334.272.737.621.493.994

With see F table with probability α (5%), df-numerator [(k – 1) = 1] and df-denominator [k(N-1) = 90] with data from the limit value of the F distribution table is 3.95 (F table) and F arithmetic is 5.95269E-09. It means F arithmetic < F table so that, Ho accepted and sanitation have significant effect on diarrhea.

4. Conclusions

As discussed, this study proved that sanitation had a significant effect on diarrhea. In this study from table distribution F, we got F table 3.95 with probability α (5%), df-numerator [(k – 1) = 1] and df-denominator [k(N-1) = 90] and F arithmetic is 5.95269E-09. It means F arithmetic < F table so that, Hypothesis nul (Ho) accepted and sanitation have significant effect on diarrhea.

To solve the current problem, we must build the good sanitation management in the urban area. The government needs to build an integrated system with universal access for safe and hygienic water and sanitation in the urban area. If it can be realized, the public health status can be increased.

References

1 

Damanhuri E., Environmental Statistic, ITB, 2001.

2 

Dinas Kesehatan Provinsi Aceh Bidang Pelaporan. 2015. Profil Kesehatan Propinsi Aceh 2014.

3 

Percepatan Pembangunan Sanitasi Pemukiman (PPSP). 2015. Strategi Sanitasi Kabupaten. Kabupaten Pidie Provinsi Aceh.

4 

Shadish, R. W., Chook, D.T., Campbell, T.D. 2002. Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin Company. 33-63.

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ISSN: 2413-0877