Bayesian geostatistical modelling of stunting in Rwanda: risk factors and spatially explicit residual stunting burden

被引:10
|
作者
Uwiringiyimana, Vestine [1 ,2 ]
Osei, Frank [1 ]
Amer, Sherif [1 ]
Veldkamp, Antonie [1 ]
机构
[1] Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, POB 217, NL-7500 AE Enschede, Netherlands
[2] Univ Rwanda, Dept Food Sci & Technol, Coll Agr Anim Sci & Vet Med, POB 3900, Kigali, Rwanda
关键词
Stunting; Spatial pattern; Bayesian modelling; Spatial residuals; Rwanda; CHILD GROWTH; NUTRITIONAL-STATUS; HEALTH; PREDICTORS; EXPOSURE; UNDERNUTRITION; CONSEQUENCES; DETERMINANTS; MALNUTRITION; FRAMEWORK;
D O I
10.1186/s12889-022-12552-y
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background Stunting remains a significant public health issue in Rwanda and its prevalence exhibits considerable geographical variation. We apply Bayesian geostatistical modelling to study the spatial pattern of stunting in children less than five years considering anthropometric, socioeconomic and demographic risk factors in Rwanda. In addition, we predict the spatial residuals effects to quantify the burden of stunting not accounted for by our geostatistical model. Methods We used the data from the 2015 Rwanda Demographic and Health Survey. We fitted two spatial logistic models with similar structures, only differentiated by the inclusion or exclusion of spatially structured random effects. Results The risk factors of stunting identified in the geostatistical model were being male (OR = 1.32, 95% CI: 1.16, 1.47), lower birthweight (kg) (OR = 0.96, 95% CI: 0.95, 0.97), non-exclusive breastfeeding (OR = 1.24, 95% CI: 1.04, 1.45), occurrence of diarrhoea in the last two weeks (OR = 1.18, 95% CI: 1.02, 1.37), a lower proportion of mothers with overweight (BMI >= 25) (OR = 0.82, 95% CI: 0.71, 0.95), a higher proportion of mothers with no or only primary education (OR = 1.14, 95% CI: 0.99, 1.36). Also, a higher probability of living in a house with poor flooring material (OR = 1.22, 95% CI: 1.06, 1.41), reliance on a non-improved water source (OR = 1.13, 95% CI: 1.00, 1.27), and a low wealth index were identified as risk factors of stunting. Mapping of the spatial residuals effects showed that, in particular, the Northern and Western regions, followed by the Southern region of Rwanda, still exhibit a higher risk of stunting even after accounting for all the covariates in the spatial model. Conclusions Further studies are needed to identify the still unknown spatially explicit factors associated with higher risk of stunting. Finally, given the spatial heterogeneity of stunting, interventions to reduce stunting should be geographically targeted.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] Risk factors for child stunting in Bangladesh: an analysis using MICS 2019 data
    Chowdhury, Tuhinur Rahman
    Chakrabarty, Sayan
    Rakib, Muntaha
    Winn, Stephen
    Bennie, Jason
    ARCHIVES OF PUBLIC HEALTH, 2022, 80 (01)
  • [42] Spatial heterogeneity and risk factors for stunting among children under age five in Ethiopia: A Bayesian geo-statistical model
    Hagos, Seifu
    Hailemariam, Damen
    WoldeHanna, Tasew
    Lindtjorn, Bernt
    PLOS ONE, 2017, 12 (02):
  • [43] Risk factors for child stunting in Bangladesh: an analysis using MICS 2019 data
    Tuhinur Rahman Chowdhury
    Sayan Chakrabarty
    Muntaha Rakib
    Stephen Winn
    Jason Bennie
    Archives of Public Health, 80
  • [44] Risk Factors of Stunting among Children [24-59 months] in Sumatera
    Oktarina, Zilda
    Sudiarti, Trini
    JURNAL GIZI DAN PANGAN, 2013, 8 (03) : 175 - 180
  • [45] On selection of an appropriate logistic model to determine the risk factors of childhood stunting in Bangladesh
    Bhowmik, Kakoli Rani
    Das, Sumonkanti
    MATERNAL AND CHILD NUTRITION, 2019, 15 (01):
  • [46] Lifetime economic impact of the burden of childhood stunting attributable to maternal psychosocial risk factors in 137 low/middle-income countries
    Fawzi, Mary C. Smith
    Andrews, Kathryn G.
    Fink, Gunther
    Danaei, Goodarz
    McCoy, Dana Charles
    Sudfeld, Christopher R.
    Peet, Evan D.
    Cho, Jeanne
    Liu, Yuanyuan
    Finlay, Jocelyn E.
    Ezzati, Majid
    Kaaya, Sylvia F.
    Fawzi, Wafaie W.
    BMJ GLOBAL HEALTH, 2019, 4 (01):
  • [47] PROFILE OF THE PUBLIC HEALTH NUTRITION WORKFORCE IN FIVE HIGH BURDEN STUNTING COUNTRIES: CONSTRAINING AND ENABLING FACTORS
    Tharaney, M.
    Anson, M.
    Lamstein, S.
    Kappos, K.
    Narayan, A.
    Nekatebeb, H.
    ANNALS OF NUTRITION AND METABOLISM, 2013, 63 : 1031 - 1032
  • [48] Prevalence of and Risk factors for Stunting among School Children and Adolescents in Abeokuta, Southwest Nigeria
    Senbanjo, Idowu O.
    Oshikoya, Kazeem A.
    Odusanya, Olumuyiwa O.
    Njokanma, Olisamedua F.
    JOURNAL OF HEALTH POPULATION AND NUTRITION, 2011, 29 (04) : 364 - 370
  • [49] Stunting Among Under 5-Year-Olds in Nepal: Trends and Risk Factors
    Budhathoki, Shyam Sundar
    Bhandari, Amit
    Gurung, Rejina
    Gurung, Abhishek
    Ashish, K. C.
    MATERNAL AND CHILD HEALTH JOURNAL, 2020, 24 (SUPPL 1) : 39 - 47
  • [50] Associated factors to double burden of malnutrition stunting of child and overweight or obesity of mother in a secondary city of Benin
    Saizonou, J.
    Sossa-Jerome, C.
    Dembele, B.
    Mongbo, V.
    Ouendo, E-M.
    TROPICAL MEDICINE & INTERNATIONAL HEALTH, 2017, 22 : 310 - 310