Risk factor model for pulmonary tuberculosis occurrence in Makassar using spatial approach

Stang,; Mallongi, Anwar; Dwinata, Indra; Sumarni, .

doi:10.1016/j.enfcli.2019.10.105

Cited by 7 publications

(8 citation statements)

References 3 publications

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“…A similar study conducted by Sari [16] shows the same thing, cigarette consumption of parents will be at risk of having children who have stunted 1.15 times greater than children whose parents do not consume cigarettes. Other studies show that smoking in the home is significantly related to the incidence of stunting [17], [19], [20].…”

Section: Discussionmentioning

confidence: 99%

Water, Sanitation Dan Hygiene Analysis, and Individual Factors for Stunting among Children Under Two Years in Ambon

Hasanah

Maria

Jafar

et al. 2020

Open Access Maced J Med Sci

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BACKGROUND: Nutrition problem is a problem that is still a threat in various countries around the world, one of which is stunting that occurs since the baby is in the womb and in the early period after the baby is born, but only appears after the child is 2 years old. AIM: This study aimed to analyze the water, sanitation and hygiene (WASH), and individual factors for the incidence of stunting in children aged 7–24 months in the slums of Ambon City. METHODS: The research was an analytical observational study using a case control study design. The population in this study was all children aged 7–24 months who suffered from stunting in Ambon. The samples were 150 child with a ratio of 1:1 for the case and control groups. RESULTS: The results showed that WASH (OR=2.7, CI 95%: 1.379–5.566) dan status Berat Badan Lahir Rendah (OR=5.1; CI 95%: 2.279–11.445) was a stunting risk factor. Meanwhile, diarrhea status (OR=2.4; CI 95%: 0.793–7.302), immunization (OR=1.4; CI 95%:0.622–3.260), and smoking history of household members (OR=1.1; CI 95%: 0.540–2.086) are risk factors, but statistically not significant. Maternal education (OR=1.0) is not a risk factor for stunting in children aged 7–24 months. CONCLUSION: The conclusion of this study is that the WASH condition and low birth weight status are risk factors for stunting in children aged 7–24 months in Ambon.

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Section: Discussionmentioning

confidence: 99%

Water, Sanitation Dan Hygiene Analysis, and Individual Factors for Stunting among Children Under Two Years in Ambon

Hasanah

Maria

Jafar

et al. 2020

Open Access Maced J Med Sci

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“…However, evidence described in the literature confirmed the importance of conducting a study to better understand how air quality and weather can influence the cases of TB. Environmental factors such as air quality index [ 15 ], concentration of carbon monoxide [ 16 ], nitrogen dioxide [ 17 ] and sulphur dioxide [ 18 ], particulate matter [ 19 ] and weather factors such as rainfall [ 20 ], humidity [ 21 ], temperature [ 22 ], wind speed [ 23 ], and atmospheric pressure [ 24 ], can enhance the reproduction and growth of Mycobacterium tuberculosis to a certain extent.…”

Section: Introductionmentioning

confidence: 99%

Association of sociodemographic and environmental factors with spatial distribution of tuberculosis cases in Gombak, Selangor, Malaysia

et al. 2021

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Tuberculosis (TB) cases have increased drastically over the last two decades and it remains as one of the deadliest infectious diseases in Malaysia. This cross-sectional study aimed to establish the spatial distribution of TB cases and its association with the sociodemographic and environmental factors in the Gombak district. The sociodemographic data of 3325 TB cases such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency, and smoking status from 1st January 2013 to 31st December 2017 in Gombak district were collected from the MyTB web and Tuberculosis Information System (TBIS) database at the Gombak District Health Office and Rawang Health Clinic. Environmental data consisting of air pollution such as air quality index (AQI), carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter 10 (PM10,) were obtained from the Department of Environment Malaysia from 1st July 2012 to 31st December 2017; whereas weather data such as rainfall were obtained from the Department of Irrigation and Drainage Malaysia and relative humidity, temperature, wind speed, and atmospheric pressure were obtained from the Malaysia Meteorological Department in the same period. Global Moran’s I, kernel density estimation, Getis-Ord Gi* statistics, and heat maps were applied to identify the spatial pattern of TB cases. Ordinary least squares (OLS) and geographically weighted regression (GWR) models were used to determine the spatial association of sociodemographic and environmental factors with the TB cases. Spatial autocorrelation analysis indicated that the cases was clustered (p<0.05) over the five-year period and year 2016 and 2017 while random pattern (p>0.05) was observed from year 2013 to 2015. Kernel density estimation identified the high-density regions while Getis-Ord Gi* statistics observed hotspot locations, whereby consistently located in the southwestern part of the study area. This could be attributed to the overcrowding of inmates in the Sungai Buloh prison located there. Sociodemographic factors such as gender, nationality, employment status, health care worker status, income status, residency, and smoking status as well as; environmental factors such as AQI (lag 1), CO (lag 2), NO2 (lag 2), SO2 (lag 1), PM10 (lag 5), rainfall (lag 2), relative humidity (lag 4), temperature (lag 2), wind speed (lag 4), and atmospheric pressure (lag 6) were associated with TB cases (p<0.05). The GWR model based on the environmental factors i.e. GWR2 was the best model to determine the spatial distribution of TB cases based on the highest R2 value i.e. 0.98. The maps of estimated local coefficients in GWR models confirmed that the effects of sociodemographic and environmental factors on TB cases spatially varied. This study highlighted the importance of spatial analysis to identify areas with a high TB burden based on its associated factors, which further helps in improving targeted surveillance.

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“…According to the characteristics of the respondents (employment status) respondents with a good quality of life are more frequent [148 (91.9%)]. However, respondents who work and have a good quality of life (100%), i.e., respondents with private employment/ state (14), TNI/Polri (2), and the Labor / PRT/Farmer (9) people (Table 2). The results of the analysis of the characteristics of respondents relationship glaucoma patients with glaucoma patient quality of life (Table 3), there is no significant relationship between gender and quality of life of patients with glaucoma with p = 0.237> α (0.05).…”

Section: Resultsmentioning

confidence: 99%

“…The same result was shown by Hamzah et al [8] that there is a relationship between gender and quality of life with p = 0.001. the productivity of the patient. Such activities can work both fixed and activities performed daily [14], [15], [16].…”

Section: Discussionmentioning

confidence: 99%

Correlation of Age, Gender, and Employment Status with Quality of Life Glaucoma Patient

Hardianti

Noor

Saleh

et al. 2020

Open Access Maced J Med Sci

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BACKGROUND: People with glaucoma sometimes do not feel the symptoms of glaucoma until the end of the stage, so the risk of blindness will be even greater. Glaucoma is a form of visual impairment, also the second cause of blindness after cataracts. However, in contrast to cataracts, glaucoma cannot be cured through surgery so that the blindness experienced is permanent. AIM: This study aimed to determine the relationship between the characteristics of respondents (age, gender, and occupational status) and the quality of life of glaucoma patients. METHODS: This study used quantitative research with cross-sectional method. Interviews were conducted on 250 glaucoma patients at community eye health centers. To determine age, sex, and employment status related to quality of life, the data were analyzed using Chi-square and logistic regression. RESULTS: The age with p-value 0668 and gender with p-value employment status in 0237 and 0105 with p values were not related to the quality of life of glaucoma patients. The results of logistic regression analysis showed that the employment status with a significance of 0046 was a factor related to the quality of life. CONCLUSION: No relation to gender, age, and income with the quality of life of patients with glaucoma in Makassar Community Eye Health Centers in 2018 was found.

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Risk factor model for pulmonary tuberculosis occurrence in Makassar using spatial approach

Cited by 7 publications

References 3 publications

Water, Sanitation Dan Hygiene Analysis, and Individual Factors for Stunting among Children Under Two Years in Ambon

Water, Sanitation Dan Hygiene Analysis, and Individual Factors for Stunting among Children Under Two Years in Ambon

Association of sociodemographic and environmental factors with spatial distribution of tuberculosis cases in Gombak, Selangor, Malaysia

Correlation of Age, Gender, and Employment Status with Quality of Life Glaucoma Patient

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