Table 2 Studies on socioeconomic position (SEP) and malaria with analysis approaches

Siri 2010

Multivariable logistic regression

OR. wealth percentile [0.8 (0.7–0.9)]

ITN use, mosquito coils, age, location, gender of HH head

Strong

Coleman et al. 2010

Multivariable negative binomial regressions

OR. Reference (the 1st quartile) third [0.24 (0.09–0.65)], and fourth (least poor) [0.27 (0.10–0.79)]

Housing structure, closing windows on retiring

Strong

Loha et al. 2012

Poisson regression

(Beta coefficient = − 0.155, P-value = 0.043)

Age, gender, ITN use, and distance to the breeding place

Strong

Clark et al. 2008

Generalized estimating equations with control for repeated measures

IRR. Reference (SEP quartiles 1 and 2 combined). Third [0.83 (0.62–1.10)], fourth [0.77 (0.56–1.04)]

Age, gender, ITN use, distance to the swamp, household crowding

Strong

Snyman et al. 2015

Negative binomial regression models

IRR. Reference (lowest). Middle [0.91 (0.76–1.1)], highest [0.86 (0.72–1.03)]

Caregiver’s age, education, house construction, location, number of rooms

Moderate

Tusting et al. 2016

Multivariable logistic regression and causal steps approach-simulations and Bootstrapping

IRR. Reference (lowest), middle [1.12 (0.90–1.40)], highest [1.05 (0.83–1.34)]

Housing type explained 24.9% of the SEP effect, and food security explained 18.6%

Age, gender, level of education, housing type^a, food security^a, distance to facility, household size

Strong

Wanzirah et al. 2015

Multivariable logistic regression and negative binomial regression

OR. Reference (1st tertile)

Walukuba: 2nd tertile [0.82 (0.38–1.78)], 3rd tertile [0.83 (0.31–2.18)]

Kihihi: 2nd tertile [0.54 (0.28–1.06)], 3rd tertile [0.37 (0.20–0.71)]

Nagongera: 2nd tertile [0.72 (0.50–1.04)], 3rd tertile [0.71 (0.47–1.07)]

Age, gender, house type, floor material, roof material, eaves

Moderate

Asante et al. 2013

Cox proportional hazards regression

HR. Reference (least poor), less poor [1.54 (1.23–1.93)], poor [1.88 (1.50–2.35)], poorer [1.86 (1.50–2.31)], most poor [2.21 (1.77–2.76)]

Housing (thatched roof), location, distance to the health facility, ITN use

Strong

Haji et al. 2016

Multivariable logistic regression

OR. Reference (low), medium [1.51 (0.51–4. 45)], high [0.93 (0.35–2.45)]

Location, ITN use, age of the child, gender, sought advice before, knowledge of malaria

Moderate

Kabaghe et al. 2017

Modified Poisson regression

HPD. SEP [− 0.07 (− 0.11 to − 0.03)]

Age, ITN use, elevation and Normalized Difference Vegetation Index

Weak

Mathanga et al. 2015

Multivariable logistic regression

OR. Reference (poorest), poor [1.08 (0.82–1.42)], medium [1.30, 0.98–1.72)], less poor [1.26 (0.94–1.70)], least poor [0.74 (0.55–0.99)]

Age, gender, ITN use, reported fever, education status, household size, school feeding)

Moderate

Sakwe et al. 2019

Multivariable logistic regression

OR. Development Index [0.76 (0.58–0.99)]

Child age, gender, nutrition status, housing type, HH size, HH head education, and caregiver

Moderate

Skarbinski et al. 2011

Multivariable logistic regression

OR. Reference (least poor), 4th [2.10 (1.45–3.05)], 3rd [2.64 (1.80–3.87)], 2nd [2.84 (2.03–3.97)], 1st [3.46 (2.30–5.21)]

District, ITN use, IRN use

Weak

Skarbinski et al. 2012

Binomial regression modelling

OR. Reference (least poor), 4th [1.19 (0.71–2.00)], 3rd [1.72 (1.09–2.70)], 2nd [1.52 (1.01–2.29)], 1st [1.47 (0.98–2.20)]

IRS use, ITN use, wall material, roof material

Weak

Somi et al. 2007

Probit regression

Coefficients: SEP score based on PCA (numerical) = − 0.04 (P-value = 0.012)

ITN use, age, location, knowledge, eaves

Moderate

Somi et al. 2008

Probit regression

Coefficients: SEP score based on PCA (numerical) = − 0.074

Age, location, ITN use, HH size, eaves, knowledge

Moderate

Ssempiira et al. 2017

Bayesian geostatistical logistic regression

OR. Reference (poorest), richest [0.19 (0.14, 0.27)], richer [0.52 (0.42, 0.61)], medium [0.77 (0.85, 1.15)], poorer [0.86 (0.72, 1.04)]

Location, ITN use, IRS use, age, mothers’ education, land surface temperature

Moderate

Temu et al. 2012

Multivariable logistic regression

OR. Reference (poorest), 2nd quartile [0.9 (0.7–1.2)], 3rd quartile [0.9 (0.7–1.3)], and 4th quartile [0.5 (0.4–0.7)]

Age, year, ITN use, HH size, house construction, children with current fever

Weak

Zoungrana et al. 2014

Multivariable logistic regression

OR. Reference (high)

Low SEP [4.11 (1.44, 11.75)]

Age, gender, marital status, education, knowledge, ethnicity, residence, distance, travel time, HH size, decision making

Strong

Graves et al. 2009

Multivariable logistic regression

OR. Asset index [0.79 (0.66—0.94)]

Age, gender, altitude, monthly rain, ITN use, IRS use in the last 12 months

Moderate

Mmbando et al. 2011

Muitivariate logistic regression

Spatial analysis

OR. Reference (high), medium [1.6(1.3–1.9)], low [1.6 (1.4–1.91)]

Age, ITN use, ITN rate, housing, year, altitude

Moderate

Siri 2014

Multilevel logistic regression

OR. Wealth percentile [0.990 (0.987–0.992)]

Child age, mother’s age, ITN use, country, HH size, location, education, finished windows and ceilings

Moderate

Custodio et al. 2009

Multivariable logistic regression

OR. Reference (low), medium [0.97 (0.29–3.25)], high [0.15 (0.05–0.50)]

ITN use, antimalarials use in pregnancy, age, gender

Moderate

de Beaudrap et al. 2011

Multivariable logistic regression

OR. SEP score [0.75 (0.64–0.89)]

Child age, weight, housing score, ITN use, education and latitude

Moderate

Sonko et al. 2014

Multivariable logistic regression

For children 6–59 months, OR. Reference (poorest), 2nd [0.40 (0.20–0.70], 3rd [0.5 (0.30–0.90)], 4th [0.30 (0.10–0.60), 5th [0.10 (0.04–0.30)]

Children 5–14 years

2nd [0.60 (0.30–1.20]), 3rd [0.70 (0.50–1.10]), 4th [0.20 (0.10–0.50)], 5th [0.30 (0.10–0.60)]. For the general population

2nd [0.80 (0.40–1.30)], 3rd [0.80 (0.50–1.20), 4th (0.40 (0.20–0.80), 5th [0.20 (0.07–0.80)]

Housing (wall type, roof type, floor type, window type,) age, gender

Moderate

Chirombo et al. 2014

Structured additive logistic regression (Bayesian approach)

OR. Reference (poorest), richest [0.22 (0.14–0.37)], richer (0.42 (0.28–0.64)], medium [0.66 (0.45–0.96)], poorer [1.10 (0.76–1.60)]

ITN use, region, age and location

Weak

de Glanville et al. 2019

Multivariable logistic regression

Mediation analysis using a hierarchical approach

OR. SEP [0.76 (0.66–0.86)]

Minimal mediation by antimalarial use

Gender, age, access to health care (antimalaria use^a)

Moderate

Florey et al. 2012

GEE models with exchangeable correlation matrix and logistic distributions

OR. SEP [0.76 (0.54–1.05)]

Outdoor night activity

Weak

Kahabuka et al. 2012

Multivariable logistic regression

OR. Reference (high), middle [1.00 (0.40–2.80)], and low [1.20 (0.40–3.70)]

Education, parity, hospital travel time, use of near public health facility, source of the first treatment

Weak

Ma et al. 2017

Multivariable logistic regression

OR. SEP [1.20 (0.94–1.50)]

Study site, age, HH size, education, HIV Status, ITN use, phone ownership

Moderate

West et al. 2013

Multivariable logistic regression

OR. Reference (poorest), mild [0.69 (0.34–1.40)], least poor [0.13 (0.05–0.34)]

HH spaying, cluster ITN coverage, age

Moderate

Williams et al. 2016

Multivariable logistic regression

OR. Reference (wealthiest), wealthy [1.82 (0.68–4.83)], medium [0.96 (0.18–5.02)], poor [6.48 (1.68, 25.0), poorest [6.55 (1.27–33.70)]

Education, age, gestation age, gravidity, country

Weak

Zgambo et al. 2017

Multivariable logistic regression

OR. Reference (richest), 2012 survey: poorest [2.90 (1.60–5.30)], poorer [2.3 (1.10–4.60)], middle [2.50 (1.30–5.00)], richer [1.9 (1.10–3.60)]

2014 survey: poorest [4.7 (1.3–16.2)], poorer [2.9 (0.9–10.0)], middle [2.7 (0.7–10.2)], richer [1.9 (0.4–8.0)]

ITN use, ITN ownership, IRS, region, location, Gender, child age, altitude, and education of the mother

Moderate

Gari T et al. 2016

A multilevel mixed effects Poisson regression

IRR. Reference (rich). Poor [0.94 (0.35–2.45)], medium [0.70 (0.33–1.50)]

Age, gender, HH head education, ITN use

Strong

Liu et al. 2014

Multivariable negative binomial regressions

IRR. Reference (middle). Poorest [1.316 (0.915–1.891)], poorer [1.292 (0.876–1.905)], richer [1.090 (0.667–1.782)], richest [1.059 (0.533–2.103)]

Age, housing index, regular repellent use, ITN use, location, water source, electricity

Strong

Vincenz et al. 2022

GEE for binary logistic regression

OR. [1.37 (0.99–1.91)]

Maternal age, gravidity, IPTP use, education, season

Weak

Mann et al. 2021

Multivariable logistic regression

OR. Reference (richest), poorest [4.60 (3.05–6.96)], poorer [4.18 (2.81–6.19)], middle [3.27 (2.26–4.71)], richer [2.23 (1.55–3.21)]

Age, gender, residence, education, nutrition (stunting)

Moderate

Emina et al. 2021

Generalized estimating equations with control for repeated measures

OR. Reference (poorest), poorer [1.20 (0.95–1.52)], middle [1.00 (0.77–1.31)], richer [0.69 (0.50–0.96)], richest [0.19 (0.10–0.37)]

Gender, child’s age, mother education, ITN use, sex of HH head, type of residence, province of residence

Moderate

Mwaiswelo et al. 2021

Multivariable logistic regression

OR. Reference (low). Medium [0.54, 0.36–0.83)], upper [0.41(0.25–0.66)]

ITN ownership, HH size, education, district (location)

Weak

Mangani et al. 2022

Multilevel logistic regression

OR. Reference (poorest), poorer [0.80 (0.65–1.00)], middle [0.74 (0.56–0.99)], richer [0.80 (0.62–1.01)], richest [0.64 (0.50–0.81)]

HH wall, roof materials, education, ITN use, child’s age, gender, distance from the irrigation scheme

Moderate

Ejigu 2020

Geostatistical logistic model

OR. Reference (poorest), poorer [0.99 (0.80–1.25)], middle [0.67 (0.53–0.85)], richer [0.52 (0.40–0.69)], richest [0.19 (0.11–0.31)]

Province, mothers’ education, anemia, ITN use, age in months, ITN coverage, malaria incidence

Weak