Malaria Infection and Socioeconomics in Malaria Endemic Areas of East Nusa Tenggara, Indonesia

Nisa Fauziah, Edina Anindhita, Savira Ekawardhani, Deviyanthi Nur Afifah, Jontari Hutagalung

Abstract


More than 1.1 million people, or 20.90% of the population in East Nusa Tenggara (NTT), Indonesia, live below the poverty line, making NTT the third province with the highest number of poor people in Indonesia. The region of NTT, which is well known as one of the endemic areas for malaria in Indonesia, also has the highest number of adults with low nutritional status. This study aimed to assess the influence of socioeconomic factors on malaria-endemic areas in eastern Indonesia. A cross-sectional study was conducted in East Nusa Tenggara from January to March 2020. Bivariate and multivariate analyses were then performed on 317 population data of adults with low socioeconomic status. It was found that one of the socioeconomic factors, i.e., the age, is significantly associated with malaria (p-value = 0.031; OR = 1.684) with 40 being the age with the highest association. Thus, age is associated with malaria incidence in endemic areas.


Keywords


Malaria, socioeconomic, East Nusa Tenggara, Indonesia

Full Text:

PDF

References


  1. BPS East Nusa Tenggara. Update on the socioeconomic, 2021. Monthly Socioeconomic Data Report. ENT: BPS Cataloguing Data; 2021.
  2. Kemenkes RI. In nutritional status monitoring book Kemenkes RI. 2018. Kemenkes RI: Jakarta. p. 7–11.
  3. BPS East Nusa Tenggara. Update on Malaria Endemic 2015-2017. 2018. Number of malaria cases by district and city in East Nusa Tenggara. ENT: BPS Cataloguing Data: 2018.
  4. Kemenkes RI. Indonesia Healthy profile in data Kementerian Kesehatan Republik Indonesia. 2019. Kemenker RI: Jakarta p. 207.
  5. WHO. Malaria Endemic: World Malaria Report 2020. Malaria. Global Malaria Programme.; 2020.
  6. Mutsigiri-Murewanhema F, Mafaune PT, Shambira G, Juru T, Bangure D, Mungati M, Gombe NT, Tshimanga M. Factors associated with severe malaria among children below ten years in Mutasa and Nyanga districts, Zimbabwe, 2014-2015. Pan Afr Med J. 2017;27:23.
  7. Idris IO, Ayeni GO, Iyamu IO. Factors influencing severity of recurrent malaria in a conflict-affected state of South Sudan: an unmatched case-control study. Confl Health. 2022.16(34):1102.
  8. Gondwe T, Yang Y, Yosefe S, Kasanga M, Mulula G, Luwemba MP, et al. Epidemiological trends of malaria in five years and under children of Nsanje District in Malawi, 2015-2019. Int J Environ Res Public Health. 2021;18(23):12784.
  9. Nworgu FC, Egbunike GN. Nutritional potential of centrosema pubescens mimosa invisa and pueraria phaseoloides leaf meals on growth performance responses of broiler chickens. Am. J. Exp. Agric. 2013;3(3):506–519
  10. Sakwe N, Bigoga J, Ngondi J, Njeambosay B, Esemu L, Kouambeng C, et al. Relationship between malaria, anemia, nutritional and socio-economic status amongst under-ten children, in the North Region of Cameroon: A cross-sectional assessment. PLoS ONE. 2019;14(6):e0218442.
  11. Manumpa, S. Influence of demographic factors and history of malaria with the incidence malaria In MORU PHC. Jurnal Berkala Epidemiologi, 2017;4(3):338–48.
  12. Sylvester B, Gasarasi DB, Aboud S, Tarimo D, Massawe S, Mpembeni R. et al. Prenatal exposure to Plasmodium falciparum increases frequency and shortens time from birth to first clinical malaria episodes during the first two years of life: prospective birth cohort study. Malar J. 2016;15(1):379.
  13. O’Brien SF, Delage G, Seed CR, Pillonel J, Fabra CC, Davison K, et al. The epidemiology of imported malaria and transfusion policy in 5 nonendemic countries. Transfus Med Rev. 2015;29(3):162–71.
  14. Schwartz E, Sadetzki S, Murad H, Raveh D. Age as a risk factor for severe Plasmodium falciparum malaria in nonimmune patients. Clin Infect Dis. 2001;33(10):1774–77.
  15. Workineh L, Lakew M, Dires S, Kiros T, Damtie S, Heilemichael W, et al. Prevalence of malaria and associated factors among children attending health institutions at South Gondar Zone, Northwest Ethiopia: A Cross-Sectional Study. Glob Pediatr Health. 2021;8:2333794X211059107.
  16. Deribew A, Alemseged F, Tessema F, Sena L, Birhanu Z, Zeynudin A, et al. Malaria and under-nutrition: a community-based study among under-five children at risk of malaria, South-West Ethiopia. PLoS ONE. 2010;5(5):e10775.
  17. Pini A, Stenbeck M, Galanis I, Kallberg H, Danis K, Tegnell A. et al. Socioeconomic disparities associated with 29 common infectious diseases in Sweden, 2005-14: an individually matched case-control study. Lancet Infect Dis. 2019;19(2):165–176.
  18. Ravishankar A, Singh S, Rai S, Sharma N, Gupta S, Thawani R. Socio-economic profile of patients with community-acquired skin and soft tissue infections in Delhi. Pathog Glob Health. 2014;108(6):279–82.
  19. Degarege A, Fennie K, Degarege D, Chennupati S, Madhivanan P. Improving socioeconomic status may reduce the burden of malaria in sub-Saharan Africa: A systematic review and meta-analysis. PLOS ONE. 2019;14(1):e0211205.
  20. Sharma RK, Singh MP, Saha KB, Bharti PK, Jain V, Singh PP. et al. Socio-economic & household risk factors of malaria in tribal areas of Madhya Pradesh, Central India. Indian J Med Res. 2015;141(5):567–75.
  21. Guerra M, de-Sousa B, Ndong-Mabale N. Malaria determining risk factors at the household level in two rural villages of mainland Equatorial Guinea. Malar J. 2018;17(203):1–10.
  22. Carter R, Karunaweera ND. The role of improved housing and living environments in malaria control and elimination. Malar J. 2020;19(385):1–6.
  23. Warsito, T. Attaining the demographic bonus in Indonesia. J Pajak dan Keuang Negara. 2019;1(1):8.




DOI: https://doi.org/10.15395/mkb.v55n1.2902

Article Metrics

Abstract view : 468 times
PDF - 489 times

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.


 


Creative Commons License
MKB is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

 


View My Stats