Skip to main content Accessibility help
×
Home

Diarrhoea, enteric pathogen detection and nutritional indicators among controls in the Global Enteric Multicenter Study, Kenya site: an opportunity to understand reference populations in case–control studies of diarrhoea

  • D. M. Berendes (a1) (a2), C. E. O'Reilly (a2), S. Kim (a2), R. Omore (a3), J. B. Ochieng (a3), T. Ayers (a2), K. Fagerli (a2), T. H. Farag (a4) (a5), D. Nasrin (a4), S. Panchalingam (a4), J. P. Nataro (a4) (a6), K. L. Kotloff (a4), M. M. Levine (a4), J. Oundo (a3), K. Laserson (a7) (a8), R. F. Breiman (a9) (a10) and E. D. Mintz (a2)...

Abstract

Given the challenges in accurately identifying unexposed controls in case–control studies of diarrhoea, we examined diarrhoea incidence, subclinical enteric infections and growth stunting within a reference population in the Global Enteric Multicenter Study, Kenya site. Within ‘control’ children (0–59 months old without diarrhoea in the 7 days before enrolment, n = 2384), we examined surveys at enrolment and 60-day follow-up, stool at enrolment and a 14-day post-enrolment memory aid for diarrhoea incidence. At enrolment, 19% of controls had ⩾1 enteric pathogen associated with moderate-to-severe diarrhoea (‘MSD pathogens’) in stool; following enrolment, many reported diarrhoea (27% in 7 days, 39% in 14 days). Controls with and without reported diarrhoea had similar carriage of MSD pathogens at enrolment; however, controls reporting diarrhoea were more likely to report visiting a health facility for diarrhoea (27% vs. 7%) or fever (23% vs. 16%) at follow-up than controls without diarrhoea. Odds of stunting differed by both MSD and ‘any’ (including non-MSD pathogens) enteric pathogen carriage, but not diarrhoea, suggesting control classification may warrant modification when assessing long-term outcomes. High diarrhoea incidence following enrolment and prevalent carriage of enteric pathogens have implications for sequelae associated with subclinical enteric infections and for design and interpretation of case–control studies examining diarrhoea.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Diarrhoea, enteric pathogen detection and nutritional indicators among controls in the Global Enteric Multicenter Study, Kenya site: an opportunity to understand reference populations in case–control studies of diarrhoea
      Available formats
      ×

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Diarrhoea, enteric pathogen detection and nutritional indicators among controls in the Global Enteric Multicenter Study, Kenya site: an opportunity to understand reference populations in case–control studies of diarrhoea
      Available formats
      ×

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Diarrhoea, enteric pathogen detection and nutritional indicators among controls in the Global Enteric Multicenter Study, Kenya site: an opportunity to understand reference populations in case–control studies of diarrhoea
      Available formats
      ×

Copyright

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

Corresponding author

Author for correspondence: D. M. Berendes, E-mail: dberendes@cdc.gov

References

Hide All
1.WHO (2013) WHO: Diarrhoeal disease. WHO Fact Sheets; #330.
2.Wolf, J et al. (2014) Systematic review: assessing the impact of drinking water and sanitation on diarrhoeal disease in low- and middle-income settings: systematic review and meta-regression. Tropical Medicine and International Health 19, 928942.
3.Petri, WA et al. (2008) Enteric infections, diarrhea, and their impact on function and development. Journal of Clinical Investigation 118, 12771290.
4.Platts-Mills, JA et al. (2015) Pathogen-specific burdens of community diarrhoea in developing countries: a multisite birth cohort study (MAL-ED). The Lancet Global Health 3, 564575.
5.Kotloff, KL et al. (2013) Burden and aetiology of diarrhoeal disease in infants and young children in developing countries (the Global Enteric Multicenter Study, GEMS): a prospective, case-control study. The Lancet 382, 209222.
6.Levine, MM and Robins-Browne, RM (2012) Factors that explain excretion of enteric pathogens by persons without diarrhea. Clinical Infectious Diseases 55, 303311.
7.Albert, MJ et al. (1999) Case-control study of enteropathogens associated with childhood diarrhea in Dhaka, Bangladesh. Journal of Clinical Microbiology 37, 34583464.
8.Rappelli, P et al. (2005) Pathogenic enteric Escherichia coli in children with and without diarrhea in Maputo, Mozambique. FEMS Immunology and Medical Microbiology 43, 6772.
9.Reither, K et al. (2007) Acute childhood diarrhoea in northern Ghana: epidemiological, clinical and microbiological characteristics. BMC Infectious Diseases 7, 104.
10.Bonkoungou, IJO et al. (2013) Bacterial and viral etiology of childhood diarrhea in Ouagadougou, Burkina Faso. BMC Pediatrics 13, 36.
11.Traoré, E et al. (1994) Child defecation behaviour, stool disposal practices, and childhood diarrhoea in Burkina Faso: results from a case-control study. Journal of Epidemiology and Community Health 48, 270275.
12.Baltazar, JC and Solon, FS (1989) Disposal of faeces of children under two years old and diarrhoea incidence: a case-control study. International Journal of Epidemiology 18, S16S19.
13.Kotloff, KL et al. (2012) The Global Enteric Multicenter Study (GEMS) of diarrheal disease in infants and young children in developing countries: epidemiologic and clinical methods of the case/control study. Clinical Infectious Diseases 55, S232S245. doi: 10.1093/cid/cis753.
14.Zafar, SN, Luby, SP and Mendoza, C (2010) Recall errors in a weekly survey of diarrhoea in Guatemala: determining the optimal length of recall. Epidemiology and Infection 138, 264269.
15.Arnold, BF et al. (2013) Optimal recall period for caregiver-reported illness in risk factor and intervention studies: a multicountry study. American Journal of Epidemiology 177, 361370.
16.Feikin, DR et al. (2010) Evaluation of the optimal recall period for disease symptoms in home-based morbidity surveillance in rural and urban Kenya. International Journal of Epidemiology 39, 450458.
17.Levine, MM et al. (2012) The Global Enteric Multicenter Study (GEMS): impetus, rationale, and genesis. Clinical Infectious Diseases 55, 215224.
18.Schilling, KA et al. (2017) Factors associated with the duration of moderate-to-severe diarrhea among children in rural western Kenya enrolled in the Global Enteric Multicenter Study, 2008–2012. The American Journal of Tropical Medicine and Hygiene 97, 160898.
19.Nygren, BL et al. (2016) The relationship between distance to water source and moderate-to-severe diarrhea in the global enterics multi-center study in Kenya, 2008–2011. American Journal of Tropical Medicine and Hygiene 94, 11431149.
20.Omore, R et al. (2013) Health care-seeking behavior during childhood diarrheal illness: results of health care utilization and attitudes surveys of caretakers in Western Kenya, 2007–2010. American Journal of Tropical Medicine and Hygiene 89, 2940.
21.Omore, R et al. (2016) Epidemiology, seasonality and factors associated with rotavirus infection among children with moderate-to-severe diarrhea in rural western Kenya, 2008–2012: the Global Enteric Multicenter Study (GEMS). PLoS ONE 11, 20082012.
22.Panchalingam, S et al. (2012) Diagnostic microbiologic methods in the GEMS-1 case/control study. Clinical Infectious Diseases 55, 294302.
23.World Health Organization (2011) WHO Anthro (version 3.2.2, January 2011) and macros. Child Growth Standards. Available at http://www.who.int/childgrowth/software/en/ (Accessed 29 May 2017).
24.WHO Multicentre Growth Reference Study Group (2006) WHO Child Growth Standards: Length/Height-for-age, Weight-for-age, Weight-for-Length, Weight-for-Height and Body Mass Index-for-Age. World Health Organization: Geneva.
25.Pham-Gia, T and Hung, TL (2001) The mean and median absolute deviations. Mathematical and Computer Modelling 34, 921936.
26.R Core Team (2015) R: A language and environment for statistical computing. Available at https://www.r-project.org/.
27.Robins-Browne, RM and Levine, MM (2012) Laboratory diagnostic challenges in case/control studies of diarrhea in developing countries. Clinical Infectious Diseases 55, 312316.
28.Blackwelder, WC et al. (2012) Statistical methods in the Global Enteric Multicenter Study (GEMS). Clinical Infectious Diseases 55, 246253.
29.Swerdlow, DL et al. (1992) Waterborne transmission of epidemic cholera in Trujillo, Peru: lessons for a continent at risk. The Lancet 340, 2432.
30.Ries, AA et al. (1992) Cholera in Piura, Peru: a modern urban epidemic. Journal of Infectious Diseases 166, 14291433.
31.Prendergast, AJ and Humphrey, JH (2014) The stunting syndrome in developing countries. Paediatrics and International Child Health 34, 250265.
32.Crane, RJ, Jones, KDJ and Berkley, JA (2015) Environmental enteric dysfunction: an overview. Food and Nutrition Bulletin 36, 76S87S.
33.Prendergast, AJ et al. (2014) Stunting is characterized by chronic inflammation in Zimbabwean infants. PLoS ONE 9, e86928. doi: 10.1371/journal.pone.0086928.
34.Guerrant, RL et al. (2014) The impoverished gut – a triple burden of diarrhoea, stunting, and chronic disease. Nature Reviews. Gastroenterology & Hepatology 10, 220229.
35.Kosek, M et al. (2014) Assessment of environmental enteropathy in the MAL-ED cohort study: theoretical and analytic framework. Clinical Infectious Diseases 59, S239S247.
36.Pickering, AJ et al. (2015) Effect of a community-led sanitation intervention on child diarrhoea and child growth in rural Mali: a cluster-randomised controlled trial. The Lancet Global Health 3, e701e711.
37.MAL-ED Network Investigators (2017) Childhood stunting in relation to the pre- and postnatal environment during the first 2 years of life: the MAL-ED longitudinal birth cohort study. PLoS Medicine 14, 121.
38.Liu, J et al. (2013) A laboratory-developed TaqMan Array Card for simultaneous detection of 19 enteropathogens. Journal of Clinical Microbiology 51, 472480.
39.Mengelle, C et al. (2013) Simultaneous detection of gastrointestinal pathogens with a multiplex Luminex-based molecular assay in stool samples from diarrhoeic patients. Clinical Microbiology and Infection 19, e458e465. doi: 10.1111/1469-0691.12255.
40.WHO and UNICEF. Progress on Sanitation and Drinking Water: 2015 Update and MDG Assessment [Internet]. 2015. Available from: http://www.wssinfo.org/.

Keywords

Type Description Title
WORD
Supplementary materials

Berendes et al. supplementary material
Tables S1-S5

 Word (37 KB)
37 KB

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed