Using Penalized Splines to Model Age- and Season-of-Birth-Dependent Effects of Childhood Mortality Risk Factors in Rural Burkina Faso

被引:18
作者
Becher, Heiko [2 ]
Kauermann, Goeran [1 ]
Khomski, Pavel
Kouyate, Bocar
机构
[1] Univ Bielefeld, Ctr Stat, Dept Business Adm & Econ, D-33501 Bielefeld, Germany
[2] Heidelberg Univ, Dept Trop Hyg & Publ Hlth, D-6900 Heidelberg, Germany
关键词
Child mortality; Non proportional hazard model; Penalized spline estimation; Survival time modeling; HAZARD; CHILDREN; MALARIA; AFRICA;
D O I
10.1002/bimj.200810496
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Several previous studies have identified risk factors for childhood mortality in high risk areas, such as Sub-Saharan Africa. Among these are lifestyle factors related for example to nutrition or sanitation. Other factors are related to social class, ethnicity and poverty in general. Few studies have investigated a dependence of these factors by age and season of birth which is the focus in this study. We perform a survival analysis of 9121 children born between 1998 and 2001 in a rural area of western Burkina Faso. The whole population is under demographic surveillance since 1993. All cause mortality is used as the endpoint and follow-up information until the age of five years is available. Recently developed spline regression methods are used for the analysis. Ethnic group, religion, age of mother, twin status, sex, and distance to next health center are used as covariates all of which having a clear effect on survival in standard Cox regression analysis. With penalized spline regression, a more detailed risk pattern is observed. Ethnicity is more related to death at early age, as well as age of mother. The effect of the risk factors considered also appear to be related with season of birth.
引用
收藏
页码:110 / 122
页数:13
相关论文
共 35 条
[1]   Cause-specific mortality rates in sub-Saharan Africa and Bangladesh [J].
Adjuik, M ;
Smith, T ;
Clark, S ;
Todd, J ;
Garrib, A ;
Kinfu, Y ;
Kahn, K ;
Mola, M ;
Ashraf, A ;
Masanja, H ;
Adazu, U ;
Sacarlal, J ;
Alam, N ;
Marra, A ;
Gbangou, A ;
Mwageni, E ;
Binka, F .
BULLETIN OF THE WORLD HEALTH ORGANIZATION, 2006, 84 (03) :181-188
[2]  
[Anonymous], 1984, Analysis of Survival Data
[3]  
Becher H, 2004, B WORLD HEALTH ORGAN, V82, P265
[4]   Dynamic Cox modelling based on fractional polynomials:: time-variations in gastric cancer prognosis [J].
Berger, U ;
Schäfer, J ;
Ulm, K .
STATISTICS IN MEDICINE, 2003, 22 (07) :1163-1180
[5]   Where and why are 10 million children dying every year? [J].
Black, RE ;
Morris, SS ;
Bryce, J .
LANCET, 2003, 361 (9376) :2226-2234
[6]  
Boor C.D., 2001, A Practical Guide to Splines
[7]   APPROXIMATE INFERENCE IN GENERALIZED LINEAR MIXED MODELS [J].
BRESLOW, NE ;
CLAYTON, DG .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1993, 88 (421) :9-25
[8]   Mixed model-based hazard estimation [J].
Cai, T ;
Hyndman, RJ ;
Wand, MP .
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2002, 11 (04) :784-798
[9]   Local linear estimation for time-dependent coefficients in Cox's regression models [J].
Cai, ZW ;
Sun, YQ .
SCANDINAVIAN JOURNAL OF STATISTICS, 2003, 30 (01) :93-111
[10]  
COX DR, 1972, J R STAT SOC B, V34, P187