Table 3.

Risk factors for OM.

Author, Year of study, Year of publication, Journal/Conference	Country, Population	Study design	Population - risk group, age	Diagnostic method	Outcome	Study period	Risk of bias	Results and Conclusions
T. Bandyopadhyay; E. V. Raman 2018 Indian J Otolaryngol Head & Neck	Indian urban children	Case-control Selection method of controls not mentioned	Children 1–10 years old. 50 from tertiary care and 50 controls	Otoscopy, tymp, history recording,	Describe epidemiological characteristics and risk factors for OME	2012–2014	High Only univariate statistics	Not significant: Birth order, maternal age >30, prematurity, perinatal complication, Nose block, allergy, siblings, family structure, accommodation pattern Significant: NICU attendance, Bottle feeding, passive smoking, daycare,
Bowatte et al., 2018 Int J Environment Research and Public Health	Mozambique Bhopal Sao Paulo	Systematic review	Children various ages	Systematic review	Air pollution and OM	Older studies from 1990’s	High (rely on cross-sectional studies and case-control)	Higher risk with charcoal or wood use in houses (OR 3.09–3.18), living close to coking works, and air polluted areas
Hunt et al., 2018 PlosOne	Malawi	Cross-sectional with clinical examination	281 children aged 4–6 years	Video-otoscopy and hearing test	Chronic OM and risk factors	2016	High Cross-sectional	No significant associations
Deng et al., 2017 Chemosphere	Changsha, China	Retrospective	1617 children aged 3–4 years	Parental questionnaire	Lifetime prevalence of OM and pre- and postnatal pollution	2011–12	High Retrospective - parental questionnaire	adjusted OR (95% CI) = 1.44 (1.09–1.88) for a 27 μg/m3 increase in SO2 and postnatal exposure to indoor renovations with OR (95% CI) = 1.62 (1.05–2.49) for new furniture and 1.81 (1.12–2.91) for redecoration
Santos-Cortez et al., 2016 Otolaryngol Head Neck Surg	Philippines, community	Cross-sectional clinical study	All ages (n = 187)	Otoscopy, interviews, genetic testing	Identification of genetic and environmental determinants for OM	?	High Cross-sectional small survey	no association between otitis media and age, gender, body mass index, breastfeeding, tobacco exposure or deep swimming Association with A2ML1 genotype (OR 3.7 (95%CI: 1.3, 10.8; p = 0.005)
Fang et al., 2016 Int J Ped Otorhinolaryngol	Fiji	Cross-sectional clinical study	Children 0–18 years (n = 467)	Otoscopy and tympanometry	Examine prevalence, clinical features and QoL	2015	High Cross-sectional, wide age-range	Significant: Age (OR 0.53, 95% CI: 0.36–0.77) is a significant predictor of AOM, whereas male gender (OR 2.46, 95% CI: 1.13–5.37), smoke exposure (OR 2.81, 95% CI: 1.01–7.82), and concomitant chronic sinusitis (OR 6.05, 95% CI: 2.31–15.88) are significant predictors of OME.
Wang J et al., 2016 Acta Otolaryngol	China	Case-control Age-matched	Adults - Han Chinese - 206 cases and 210 controls	Otoscopy and standardized questionnaire	Risk factors for CSOM	?	High Case-control. Controls not described. Not validated questionnaire	male (OR1/40.42; 95% CI: 0.21–0.83), BMI increasing (OR1/40.85; 95% CI: 0.77–0.93), URTI (OR1/4152.85; 95% CI: 34.11–684.93), smoke/passive smoke (OR1/47.11; 95% CI: 3.36–15.07), residential location (urban area) (OR1/40.27; 95% CI: 0.13–0.56), serum calcium increasing (OR1/40.09; 95% CI: 0.01–0.71) were prime risk factors for CSOM
Orji et al., 2014 EAORL	Nigeria	Consecutive series of cases presenting at tertiary hospital	All ages 128 non-healing 58 healing	Not mentioned	Risk factor difference between healing (within 6 months) and non-healing (>24 months) CSOM	2010–2012	High Hospital selected cases Methods not mentioned	Significant: by logistic regression analysis: rural residence, multidrug-resistant bacteria, and bilateral CSOM (P = 0.001, 0.001, and 0.008, respectively). Others were onset of ear discharge before the age of 10 years, diabetes mellitus, persistent rhinorrhoea, home [10 miles away from hospital, and [7 persons in a family (P = 0.012, 0.041, 0.013, 0.010, and 0.043, respectively