Weakness of Biochemical Markers of Nutritional and Inflammatory Status

Home , Transferrin, Transthyretin

Weakness of biochemical markers of nutritional and in¯ammatory status as prognostic indices for growth retardation and morbidity of young children in central Africa

R Tonglet1,4, E Mahangaiko Lembo2,4, M Dramaix3 and P Hennart3,4

1School of Public Health, Faculty of Medicine, Catholic University of Louvain, Brussels, Belgium; 2Rural Health District of Kirotshe, Goma, Northern Kivu, Zaire; 3School of Public Health, Faculty of Medicine, Free University of Brussels, Brussels, Belgium; and 4Centre Scienti®que et MeÂdical de l'UniversiteÂ Libre de Bruxelles pour ses ActiviteÂs de CoopeÂration (CEMUBAC), Brussels, Belgium

Objective: To determine to what extent biochemical markers of the nutritional and in¯ammatory status of young children are related to subsequent growth retardation and morbidity. Design: Population-based follow-up study of a cohort of children from admission to ®nal survey round six months later. Setting: Health area in Northern Kivu, Zaire. Subjects: 842 children under two years of age of whom about one-third gave informed consent to capillary blood collection. Main outcome measures: Concentration of albumin, transferrin, transthyretin, a1-acid glycoprotein, C-reactive protein, and complement component C3 at baseline, and three and six months later. Incremental growth per 1 month, 3 months and 6 months of follow-up. Cumulative incidence of disease per 1 month and 3 months interval. Results: A high proportion of children was with low concentrations of transport proteins and high concentrations of acute-phase reactants. Weight growth and arm circumference growth did not vary signi®cantly with respect to initial concentrations of biomarkers, but subsequent height growth was lower in children with high values of transferrin, a1-acid glycoprotein, and complement component C3 at baseline. Cumulative incidence of malaria, respiratory illness, and diarrhoea was not signi®cantly affected by the concentration of the biomarkers at baseline. Conclusions: In this part of central Africa performing biochemical measurements should not be encouraged as a means for risk scoring in non-hospitalized children. Sponsorship: This research has been carried out on behalf of the Centre Scienti®que et MeÂdical de l'UniversiteÂ Libre de Bruxelles pour ses ActiviteÂs de CoopeÂration, which is a non-pro®t organization supported by the Belgian Agency for International Development, and by the European Commission. This work was supported in part by grants from the Fondation Universitaire David et Alice Van Buuren, the Fonds National de la Recherche Scienti®que et MeÂdicale (Contract 3.4526.90.F), the UNICEF representative in Zaire, and the SANRU Basic Rural Health Project (Project 660-0107 USAID, DSP, ECZ). Descriptors: biochemical markers; growth; morbidity; child; Africa; Zaire

Introduction number of readily available blood markers of the nutritional status and the phlogistic reaction. These included transport In developing countries, many attempts have been made proteins such as albumin, transferrin, and transthyretin over the last three decades to ®nd early and sensitive (McFarlane et al, 1969; Ingenbleek et al, 1972; Whitehead indicators of severity and prognosis of protein-energy et al, 1973; Ingenbleek et al, 1975; Hay et al, 1975; Reeds malnutrition. For that purpose, several clinical, anthropo- and Laditan, 1976; Ogunshina and Hussain, 1980; Wade et metric, and biochemical measurements have been pro- al, 1988; Dramaix et al, 1993; Brasseur et al, 1994; posed, re¯ecting alterations related to either malnutrition Dramaix et al, 1996), as well as acute-phase reactants or infection, as well as their outcomes (Waterlow, 1992). like a -acid glycoprotein, and C-reactive protein (Ingen- Studies by McLaren, Pellett and Read (1967) in Jordan, and 1 bleek and Carpentier, 1985; Wade and Bleiberg-Daniel, Whitehead, Frood and Poskitt (1971) in Uganda, played a 1989). Noteworthy, most of these studies were carried out seminal part in stimulating interest in the identi®cation of in paediatric wards or feeding centres, and were therefore biochemical markers as means for risk scoring in the ®eld. unable to address the question of the attention that bio- Since then, a large body of literature has documented the chemical markers should deserve in non-hospitalized chil- clinical signi®cance and the complex relationships of a dren. We report here on a study designed to determine to what Correspondence: Prof Dr R Tonglet, Epidemiology Unit (UCL 30.34), School of Public Health, Faculty of Medicine, Catholic University of extent biochemical markers of the nutritional and in¯am- Louvain, Clos Chapelle-zux-champs 30, B-1200 Brussels, Belgium. matory status of young children in rural Africa were related Received 30 September 1996; accepted 1 November 1996 to growth retardation or morbidity. This analysis is part of a Weakness of biochemical markers R Tonglet et al 149 larger research project on the value of clinical, anthropo- values (for Belgian subjects) were as follows: ALB, 3.5± metric, biochemical and dietary measurements of nutri- 5.5 g per 100 ml; TFR, 221±369 mg per 100 ml; TTR, 10± tional status for growth promotion and child development 40 mg per 100 ml; AGP, 55±140 mg per 100 ml; CRP (Tonglet, 1994). lower or equal to 1 mg per 100 ml; and C3, 55±120 mg per 100 ml. Statistical analysis was performed by using the SPSS 4.0 Methods release for UNIX (Norussis, 1980). Our study examined the Bulenga peninsula, an area on the Continuous biochemical measurements (ALB, TFR, north-western shore of Lake Kivu (Zaire), with a fairly TTR, AGP, and C3) proved to be normally distributed typical pattern of growth de®cits, relative to the interna- (Kolmogorov±Smirnov test for normality, P > 0.05), and tional reference, among under-®ves (Tonglet et al, 1991). were categorized into three groups according either to In 1988, this area had a population of 17 874 in 4075 laboratory reference values or tertiles (low, medium, households (Reynders et al, 1992). In January 1989, we high). The numerical limits of these tertiles were as took a random sample of 2644 households from the census: follows: ALB, 3.7 and 4.2 g per 100 ml; TFR, 248 and 190 (7%) were not retrieved, 688 (26%) did not include an 312 mg per 100 ml; TTR, 13 and 19 mg per 100 ml; AGP, eligible child, 398 (15%) refused participation, and 1368 114 and 173 mg per 100 ml; and C3, 86 and 111 mg per (52%) gave informed consent. All children under two years 100 ml. CRP concentrations were treated as if they were of age in these 1368 households were enrolled in the study discrete data, and were ordered into two groups (low, high) (n 842; 423 boys and 419 girls). To allow control of divided by the value 1 mg per 100 ml. ALB, TTR, AGP, seasonality, enrolment took place in part every three and CRP concentrations were also combined in a formula months. allowing the determination of the prognostic in¯ammatory Children were followed during three months by weekly and nutritional index (PINI) (Ingenbleek and Carpentier, home visit, and a ®nal survey round was organized six 1985): [a1-GPA (mg/l) 6 CRP (mg/l)]/[ALB (g/l) 6 TTR months after enrolment. Data were collected by trained (mg/l)]. Measurements of the PINI were either ordered into interviewers, under close supervision by a medical staff. the ®ve groups proposed in the seminal paper or cate- Information was recorded by proxy reporting, namely by gorised in tertiles (low, medium, high) according to the interviewing the people taking care of the child, as well as following limits: 0.7 and 2.8. by health examination. Of the 842 children surveyed, 810 Growth was considered as the ®rst end point. Indicators (96%) completed the follow-up, 16 (2%) died, and 16 (2%) of attained growth after one, three and six months of follow were lost to follow-up. The ®nal survey round (at six up, as well as corresponding growth increments, were months) was still attended by 723 (86%) children, 15 obtained in each category of biochemical markers. Com- more deaths and 72 more losses having been noticed in parisons of means adjusted for age were made with analysis the meantime. The evolution of the cohort size in each of of covariance. the four groups was not signi®cantly different with respect Cumulative incidence of disease was the second end to enrolment period. point considered. Proportions of diseased children at one Anthropometric measurements were performed at the and three months were computed in each category of ®rst round and one, three and six months later. We used a biomarkers. Comparisons of proportions (risk ratios) were Salter-type balance and an ARTHAG-type wooden length made with contingency tables and the Chi-square test. gauge, as recommended by WHO (1983), and a commer- cial tape. Measurements were performed in duplicate and Results averaged. Weight was rounded to the nearest 50 gr, recum- bent length to the nearest 5 mm, and arm-circumference to The distribution of serum protein concentrations illustrated the nearest mm. the high proportion of children with low concentrations of Information on morbidity was collected every week. A transport proteins or high concentrations of acute-phase respondent who declared that the child had been sick since reactants (Table 1). There were no signi®cant differences the preceding visit, was asked to give a detailed description according to sex or age. A moderate seasonal effect of the recorded disease, and to determine whether and for appeared for nutritional biomarkers distribution, the highest how long the child had presented any tracer symptom out of proportions of children with low levels of ALB, TFR, and a short list of 28. New episodes were carefully distin- TTR being observed during the period of reduced food guished from continuing ones by counting the exact availability (October±February). number of days of illness for each episode. The minimal Transport protein concentrations were positively asso- coding list of associated signs and symptoms recommended ciated with each of them, as well as acute-phase reactants by WHO was used to determine the most probable diag- concentrations. The relationships between nutritional and nosis (WHO, 1978). In the analyses, attention was focused in¯ammatory biochemical markers were less straight: AGP on the most common diseases, i.e. malaria, respiratory was negatively associated with ALB and TTR; CRP was illnesses and diarrhoea. not associated with ALB and TFR, but was negatively At the ®rst round, 32% of the care-takers who kept the associated with TTR; C3 was positively associated with survey appointment gave informed consent to capillary ALB, TFR, and TTR (Table 2). blood collection (n 261/823). Serum was separated The distribution of the PINI index was markedly skewed immediately and stored at 20C before delivery to the to the left with a mean value of 6 (s.d. 16), and a median laboratory of the University Hospital Saint-Pierre, Brussels, value of 1. Table 3 shows the conversion of these measure- Belgium. Concentrations of serum albumin (ALB), trans- ments into ®ve ranks according to the scoring system ferrin (TFR), transthyretin (TTR, thyroid-binding prealbu- originally proposed by Ingenbleek and Carpentier (1985). min), a1-acid glycoprotein (AGP, orosomucoid), C-reactive At the ®rst round, adjusted means of weight, height, and protein (CRP) and third component of the complement (C3) arm circumference were similar in each category of bio- were determined by nephelometry. Laboratory reference chemical markers. After one, three and six months of Weakness of biochemical markers R Tonglet et al 150 Table 1 Number and mean value (s.d.) of biochemical measurements at baseline, and their distribution with regard to laboratory reference values

Protein n Mean (s.d.) Proportion (%) of measurements (mg per 100 ml) out of the reference values

Low High

ALB 261 4001 1147 24 3 TFR 251 281 77 18 11 TTR 241 16 7 12 1 AGP 235 162 88 2 50 CRP 249 nr nr nr 34 C3 249 104 37 4 27

ALB serum albumin; TFR transferrin; TTR transthyretin; AGP a1-acid glycoprotein; CRP C-reactive protein; C3 complement component C3; nr not relevant.

Table 2 Correlation coef®cients between serum albumin (ALB), transferrin (TFR), transthyretin (TTR), a1-acid glycoprotein (AGP), and complement component C3 (C3). Mean values (s.d.) of the concentrations of these ®ve biomarkers according to categories of CRP level

ALB TFR TTR a1-GPA C3 Correlation matrix (Pearson's correlation coef®cients, * P < 0.05, ** P < 0.01) ALB Ð 0.46** 0.13* 7 0.17** 0.40** TFR 0.46** Ð 0.24** 7 0.02 0.46* TTR 0.13* 0.24** Ð 7 0.26** 0.14* a1-GPA 7 0.17** 7 0.02 7 0.26** Ð 0.44** C3 0.40** 0.46* 0.14* 0.44** Ð Comparison of means (mg per 100 ml) (Student t-test) CRP < 1 4007 281 17 143 99 (1022) (76) (7) (81) (36) CRP > 1 4034 280 14 197 114 (1175) (77) (6) (91) (37) P 0.85 0.92 0.003 < 0.001 0.002

Table 3 Prognostic in¯ammatory and nutritional index (n 229 protein-energy malnutrition (Whitehead et al, 1973), and to measurements) assess the risk of death in hospitalized children (Hay et al, 1975). In Nigeria McFarlane and co-workers (1969) have Categories of risk n % found that serum transferrin correlated well with the nutri- > 30 Life-risk patients 10 4 tional states of 172 children attending the paediatric clinic. 21±30 High-risk patients 7 3 Their conclusion was con®rmed by Reeds and Laditan 11±20 Medium-risk patients 14 6 (1976)) who observed in 83 young patients suffering 1±10 Low-risk patients 93 41 from either marginal or severe undernutrition a signi®cant < 1 Non-infected subjects 105 46 relationship between transferrin concentrations and de®cits in length-for-age and weight-for-length. In Senegal the team headed by Ingenbleek et al (1975) has established follow up, weight growth and arm circumference growth the clinical signi®cance of the thyroid-binding prealbumin did not vary signi®cantly with respect to initial concentra- (transthyretin) in a group of 37 malnourished children. A tions of each biochemical marker, but subsequent height few years later, Ogunshima and Hussain (1980) have growth was signi®cantly lower among children admitted concluded from their study of 88 Nigerian pre-school into the study with high value of AGP, and C3, as children that transthyretin was the only parameter studied compared with their counterparts (Table 4). able to distinguish mild malnutrition from normal nutri- The disease-speci®c cumulative incidence per one tional status. month and three months interval did not differ signi®cantly Besides these encouraging results, other studies have with respect to initial concentrations of biomarkers. Risk noted that the value of albumin, transferrin or transthyretin ratio estimates were not far from 1 with rather narrow 95% concentration as a measure of nutritional status was limited con®dence intervals including the null point (Table 5). because of the complex relationships between these transport proteins and other biochemical markers such as acute- phase reactants (Ingenbleek et al, 1975; Wade et al, 1988; Discussion Ingenbleek and Carpentier, 1985) and iron (Delpeuch et al, Since the early sixties, many studies have been carried out 1980; Keusch and Farthing, 1986). Transport proteins in developing countries to determine the value of biochem- synthesis is reduced in both malnutrition and infection, ical measurements for the assessment of protein-energy but infection reduces free iron concentration causing an malnutrition. In Uganda, Whitehead et al (1971) were adaptive increase of the transferrin level. Phlogistic reac- among the ®rst to suggest that serum albumin could provide tants synthesis is increased in infection, but malnutrition an accurate means to distinguish between marasmus and reduces the concentration of complement component C3. kwashiorkor, to pick up the onset of the critical phase of Therefore, in an environment where both malnutrition and Weakness of biochemical markers R Tonglet et al 151 Table 4 Comparison of one month, three month and six month increments in weight, height, and arm-circumference (analysis of covariance; means adjusted for age), according to categories of biomarkers at baseline

Categories of Weight growth increments Height growth increments Arm circum. increments biomarkers (kg) (cm) (cm)

n 1 month 3 months 6 months n 1 month 3 months 6 months n 1 month 3 months 6 months

ALB Total 209 0.21 0.59 1.11 210 1.2 2.8 5.1 209 0.1 0.1 0.3 Low 69 0.22 0.59 1.13 70 1.1 2.9 5.1 70 0.1 0.1 0.3 Medium High 140 0.20 0.59 1.10 140 1.3 2.7 5.1 139 0.1 0.0 0.3 P 0.70 0.99 0.74 0.34 0.70 0.91 0.86 0.66 0.68 TFR Total 200 0.20 0.58 1.09 201 1.2 2.7 5.1 200 0.1 0.1 0.2 Low 71 0.15 0.66 1.06 71 1.5 3.2 5.3 70 0.1 0.1 0.3 Medium High 129 0.23 0.54 1.10 130 1.1 2.5 4.9 130 0.1 0.0 0.2 P 0.19 0.17 0.72 0.13 0.06 0.45 0.64 0.27 0.53 TTR Total 192 0.20 0.58 1.09 193 1.2 2.8 5.0 192 0.1 0.1 0.3 Low 62 0.13 0.63 1.09 63 1.3 2.9 4.7 62 0.1 0.1 0.4 Medium High 130 0.23 0.56 1.09 130 1.2 2.7 5.2 130 0.1 0.0 0.2 P 0.09 0.45 0.98 0.68 0.53 0.25 0.69 0.40 0.11 AGP Total 186 0.20 0.57 1.09 187 1.2 2.8 5.2 186 0.1 0.1 0.2 Low Medium 121 0.21 0.58 1.09 122 1.4 3.1 5.9 122 0.1 0.0 0.2 High 65 0.19 0.56 1.08 65 0.9 2.2 3.9 64 0.1 0.1 0.3 P 0.71 0.84 0.90 0.03 0.01 0.00 0.93 0.77 0.49 CRP Total 198 0.21 0.58 1.09 199 1.2 2.7 5.1 198 0.1 0.1 0.3 Low 127 0.19 0.57 1.07 128 1.1 2.6 4.9 128 0.1 0.0 0.2 High 71 0.25 0.61 1.12 71 1.3 3.0 5.4 70 0.0 0.1 0.3 P 0.29 0.63 0.67 0.51 0.27 0.28 0.20 0.27 0.49 C3 Total 199 0.20 0.58 1.09 200 1.2 2.7 5.0 199 0.1 0.1 0.3 Low Medium 127 0.21 0.60 1.09 128 1.4 3.1 5.5 127 0.1 0.1 0.3 High 72 0.19 0.54 1.09 72 0.9 2.1 4.2 72 0.1 0.0 0.3 P 0.77 0.44 0.95 0.03 0.00 0.00 0.44 0.16 0.94 PINI Total 181 0.19 0.57 1.09 182 1.2 2.8 5.1 181 0.1 0.1 0.3 Low Medium 115 0.18 0.58 1.08 116 1.2 2.8 5.0 115 0.2 0.1 0.3 High 66 0.21 0.55 1.11 66 1.2 2.8 5.2 66 0.0 0.0 0.3 P 0.69 0.79 0.80 0.93 0.95 0.71 0.01 0.54 0.99

ALB serum albumin; TFR transferrin; TTR transthyretin; AGP a1-acid glycoprotein; CRP C-reactive protein; C3 complement component C3; PINI prognostic in¯ammatory and nutritional index. infection are prevailing, biochemical measurements hardly sequent three month interval. In addition, we noted that discriminate which part in the change of protein concentra- even the construction of a composite index such as the PINI tion results from undernutrition and which part is the did not improve the clinical value of the biochemical consequences of infection. The correlations we observed measurements. between transport and in¯ammatory proteins illustrate this Although we cannot completely rule out the possibility dilemma. of a self-selection of the children, we are rather con®dent Moreover, most early studies of biomarkers of the with these results because of the lack of any difference in nutritional status may be criticised on a variety of grounds. growth or morbidity between children who gave consent to Typically, they involved few children who were not ran- blood collection and those who did not. domly sampled in the population but selected at the clinic, and who were studied cross-sectionally. This kind of study design impairs both the precision and the validity of the Conclusions results. Nonetheless, it prevents from establishing a tem- From this work in this part of central Africa performing poral relationship between the concentrations of biomar- biochemical measurements should not be encouraged as a kers and the subsequent nutritional and health status of the means for risk scoring in children from the community. child. However concluding with this that measurements of bio- In this population-based study we tried to address chemical indicators is ever a waste of time and money prospectively the question of the ability of biochemical would not be right. As our team has previously demon- markers to identify children who were at high risk of strated it in the same socio-economic and nutritional subsequent growth retardation or morbidity. Our main environment, the measurement of an indicator such as ®nding is the demonstration that clinically signi®cant serum albumin concentration is crucial in hospitalized effects of nutritional and in¯ammatory biochemical mar- children because albumin seems to be the best single kers on these issues are very few. Incremental growth was predictor of subsequent risk of dying among children not affected by the concentrations of biomarkers at base- admitted to the paediatric ward in poor nutritional condi- line. The only exception was the linear growth retardation tion (Dramaix et al, 1993; Brasseur et al, 1994; Dramaix et which was observed among children characterised by high al, 1996. levels of AGP and C3. This observation is a good case for a causal relationship between infection and a falling-off in AcknowledgementsÐWe thank Pascal Mweze Zihindula and Alain Wodon height velocity. We observed also that protein concentra- for their assistance on data collection and analysis, Jean Duchateau for tions at baseline were not associated with an increased risk having performed all biochemical measurements in his laboratory, as well of malaria, respiratory illness, or diarrhoea over the sub- as all the participants in our study for their co-operation. 1 52

Table 5 Number of incident cases (ni) and ratios (95% CI) of disease-speci®c cumulative incidence per one month and 3 months interval between categories of nutritional and in¯ammatory biomarkers at baseline Categories of biomarkers Malaria Respiratory illness Diarrhoea

1 month 3 months 1 month 3 months 1 month 3 months

n ni RR (95% CI) ni RR (95% CI) ni RR (95% CI) ni RR (95% CI) ni RR (95% CI) ni RR (95% CI) Weak

ALB Low 85 25 0.9 (0.6±1.3) 55 1.0 (0.9±1.2) 44 1.0 (0.8±1.3) 68 0.9 (0.8±1.1) 38 0.9 (0.7±1.3) 69 1.0 (0.9±1.2) ness

Medium High 175 60 1 112 1 91 1 147 1 83 1 138 1 of bio

TFR Low 85 28 1.0 (0.7±1.4) 56 1.0 (0.8±1.2) 46 1.0 (0.8±1.3) 69 1.0 (0.9±1.1) 41 1.1 (0.8±1.4) 72 1.1 (1.0±1.2) chemic

Medium High 165 56 1 106 1 86 1 138 1 75 1 128 1 R Ton al

TTR Low 80 25 0.9 (0.6±1.3) 49 0.9 (0.8±1.1) 35 0.7 (0.6±1.0) 61 0.9 (0.8±1.0) 38 1.0 (0.8±1.4) 63 1.0 (0.9±1.1) glet ma

Medium High 160 57 1 105 1 96 1 139 1 74 1 128 rkers et

AGP Low Medium 157 55 1 105 1 96 1 138 1 72 1 126 1 al High 77 28 1.0 (0.7-1.5) 51 1.0 (0.8±1.2) 32 0.7 (0.5±0.9) 58 0.9 (0.7±1.0) 36 1.0 (0.8±1.4) 63 1.0 (0.9±1.2) CRP Low 165 52 1 104 1 90 1 138 1 76 1 131 1 High 84 32 1.2 (0.8±1.7) 57 1.1 (0.9±1.3) 42 0.9 (0.7±1.2) 67 1.0 (0.8±1.1) 38 1.0 (0.7±1.3) 67 1.3 (1.1±1.5) C3 Low Medium 166 55 1 107 1 99 1 141 1 78 1 134 1 High 82 29 1.1 (0.7±1.5) 53 1.0 (0.8±1.2) 32 0.7 (0.5±0.9) 64 0.9 (0.8±1.1) 37 1.0 (0.7-1.3) 64 1.0 (0.9±1.1) PINI Low Medium 151 51 1 99 1 92 1 131 1 69 1 118 1 High 77 30 1.3 (0.9±1.8) 51 1.0 (0.8±1.2) 35 0.8 (0.6±1.0) 60 0.9 (0.8±1.0) 37 1.1 (0.8±1.4) 66 1.1 (1.0±1.3)

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