The sins of the church: The long-term impacts of Christian missionary praxis on HIV and sexual behaviour in Zambia

Figures & data

Figure 1. HIV prevalence in Southern Africa from 1990 to 2019. Data source: World Bank Data (2020).

Figure 2. Demographic Health Survey (DHS) cluster locations.

Figure 3. Protestant and Catholic missionary churches in Northern Rhodesia, 1948.

Figure 4. Protestant and Catholic mission health centres in Northern Rhodesia, 1953.

Table 1. Christian missions and Human Immunodeficiency Virus (HIV) infection.

Dependent variable: HIV status
	1	2	3	4
Distance to church	−7.81e-05*	−0.00159**	−0.00151**	−0.00155**
	(4.20e-05)	(0.000637)	(0.000700)	(0.000650)
Distance to health centre	−0.0255**	−0.0175	−0.0169	−0.0199
	(0.0130)	(0.0125)	(0.0132)	(0.0130)
Protestant	−0.0216	−0.00238	−0.0195	−0.00586
	(0.0243)	(0.0242)	(0.0267)	(0.0265)
Age	0.113***	0.113***	0.126***	0.113***
	(0.00679)	(0.00680)	(0.00795)	(0.00762)
Age^2	−0.00127***	−0.00128***	−0.00140***	−0.00128***
	(9.38e-05)	(9.40e-05)	(0.000108)	(0.000104)
Married	0.0606*	0.0481	−0.00754	0.00716
	(0.0359)	(0.0357)	(0.0378)	(0.0361)
Female	0.173***	0.176***	0.249***	0.266***
	(0.0184)	(0.0183)	(0.0204)	(0.0254)
Urban	0.425***	0.374***	0.380***	0.329***
	(0.0266)	(0.0299)	(0.0332)	(0.0328)
Lifetime sex partners				0.0177***
				(0.00204)
Age first sex			−0.0258***
			(0.00364)
Asset index
Lowest index			0.132**	0.103**
			(0.0542)	(0.0515)
Low index			0.181***	0.163***
			(0.0459)	(0.0427)
Medium index			0.133***	0.124***
			(0.0425)	(0.0400)
High index			0.157***	0.155***
			(0.0436)	(0.0410)
Education level
No education			−0.115*	−0.0480
			(0.0622)	(0.0636)
Primary education			0.0219	0.0571
			(0.0454)	(0.0491)
Secondary education			0.105**	0.129***
			(0.0425)	(0.0457)
Constant	−3.448***	−3.897***	−3.516***	−3.803***
	(0.124)	(0.178)	(0.233)	(0.220)
Provincial FE	Yes	No	Yes	Yes
Occupational FE	No	No	No	Yes
Geographic controls	No	Yes	Yes	Yes
Observations	56,350	55,946	42,235	46,374

Note: Probit model estimates. Clustered robust standard errors at the DHS cluster level are given in parentheses. I use multiple correspondence analysis to calculate an asset index based on whether an individual owns a television set, bicycle, radio, refrigerator, motorcycle, truck, or electricity. The index ranks from lowest to highest depending on what the individual owns. The highest ranking is given to an individual who owns the most assets and the lowest is assigned to those who own the fewest; the comparison group in this analysis is individuals with the highest number of assets. The comparison group for education level is individuals with the highest level of education. Distance to the health centre is log-transformed. Geographic controls include whether a cluster is within 50 km of an explorer route, 50 km of the railway, or 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions only to those who answered that where they were living was their usual place of residence. Then I also include occupational and provincial fixed effects. ***p < .01, **p < .05, *p < .1.

Table 2. Christian missions and HIV infection in urban and rural areas.

Dependent variable: HIV status
Variables	Urban	Rural
Distance to church	0.000385	−0.00243***
	(0.000983)	(0.000841)
Distance to health centre	0.00461	−0.0256
	(0.0169)	(0.0193)
Protestant	−0.0280	−0.000585
	(0.0379)	(0.0372)
Age	0.138***	0.0918***
	(0.0121)	(0.00982)
Age^2	−0.00160***	−0.00101***
	(0.000169)	(0.000132)
Married	−0.0206	0.0191
	(0.0493)	(0.0499)
Female	0.361***	0.170***
	(0.0397)	(0.0323)
HIV knowledge	0.0131	0.0163**
	(0.00958)	(0.00678)
Lifetime sex partners	0.0179***	0.0162***
	(0.00357)	(0.00232)
Lowest asset index	0.144*	0.286***
	(0.0870)	(0.0847)
Low asset index	0.207**	0.145***
	(0.0829)	(0.0534)
Medium asset index	0.237***	0.0810*
	(0.0842)	(0.0452)
High asset index	0.274***	0.106**
	(0.0863)	(0.0469)
No education	−0.0551	−0.0455
	(0.103)	(0.113)
Primary education	0.145**	−0.0409
	(0.0608)	(0.103)
Secondary education	0.137***	0.0769
	(0.0516)	(0.102)
Constant	−4.003***	−3.446***
	(0.336)	(0.291)
Provincial FE	Yes	Yes
Occupational FE	Yes	Yes
Geographic controls	Yes	Yes
Observations	18,302	27,476

Note: Probit model estimates. Clustered robust standard errors at the DHS cluster level are given in parentheses. I use multiple correspondence analysis to calculate an asset index based on whether an individual owns a television set, bicycle, radio, refrigerator, motorcycle, truck, or electricity. The index ranks from lowest to highest depending on what the individual owns. The highest ranking is assigned to individuals who own the most assets and the lowest is assigned to those who own the fewest; the comparison group in this analysis is individuals with the highest number of assets. The comparison group for education level is individuals with the highest level of education. Distance to health centre is log-transformed. Geographic controls include whether a cluster is within 50 km of an explorer route, 50 km of the railway, or 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions to those who answered that where they were living was their usual place of residence. Then I also include occupational and provincial fixed effects. ***p < .01, **p < .05, *p < .1.

Figure 5. Correlation between current health centres and missionary health centres and stations in Zambia.

Table 3. Impact of proximity to a mission church on sexual behaviour.

	(1)	(2)	(3)
	All missions	Protestant	Catholic
Lifetime sex partners	−0.00351**	−0.00266	−0.00713***
	(0.00162)	(0.00184)	(0.00265)
Age at first sex	0.00223*	0.00216*	0.00165
	(0.00114)	(0.00121)	(0.00255)
Premarital abstinence	0.00110**	0.00142**	0.000906
	(0.000527)	(0.000585)	(0.00113)
Condom use	0.000876	0.000426	0.00302
	(0.00101)	(0.00110)	(0.00261)
Provincial FE	Yes	Yes	Yes
Occupational FE	Yes	Yes	Yes
Geographic controls	Yes	Yes	Yes
Individual controls	Yes	Yes	Yes

Note: Probit model estimates. Clustered robust standard errors at the DHS cluster level are given in parentheses. The comparison group for the asset index is individuals with the highest index. The comparison group for education level is individuals with the highest level of education. Distance to health centre is log-transformed, and distance to church is given in kilometres. Geographic controls include whether a cluster is within 50 km of an explorer route, 50 km of the railway, or 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions to those who answered that where they were living was their usual place of residence. Individual controls: age, age squared, married, female, condom knowledge, condom access, urban, P. ***p < .01, **p < .05, *p < .1.

Table 4. Impact of proximity to a mission health centre on sexual behaviour.

	(1)	(2)	(3)
	All missions	Protestant	Catholic
Lifetime sex partners	−0.0708	−0.0414	−0.0687
	(0.0448)	(0.0482)	(0.0627)
Age at first sex	−0.00927	−0.0175	−0.0349
	(0.0255)	(0.0276)	(0.0696)
Premarital abstinence	0.00274	−0.00191	−0.00305
	(0.0106)	(0.0124)	(0.0237)
Condom use	0.00952	0.00819	−0.0263
	(0.0222)	(0.0230)	(0.0749)
Provincial FE	Yes	Yes	Yes
Occupational FE	Yes	Yes	Yes
Geographic controls	Yes	Yes	Yes
Individual controls	Yes	Yes	Yes

Note: Probit model estimates. Clustered robust standard errors at the DHS cluster level are given in parentheses. The comparison group for the asset index is individuals with the highest index. The comparison group for education level is individuals with the highest level of education. Distance to health centre is log-transformed, and distance to church is given in kilometres. Geographic controls include whether a cluster is within 50 km of an explorer route, 50 km of the railway, or 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions to those who answered that where they were living was their usual place of residence. Individual controls: age, age squared, married, female, condom knowledge, condom access, urban, protestant, lifetime partners, asset index, education level. ***p < .01, **p < .05, *p < .1.

Figure 6. Cagé and Rueda missions (2020) versus new geocoded (1948) missions for Zambia.

Table A1. Descriptive statistics for geocoded DHS data.

	Observations	Mean	Std. Dev.	Min.	Max.
Overall outcome variables
HIV positive	63,882	0.13	0.33	0	1
Condom use at first intercourse	17,312	0.30	0.46	0	1
Premarital abstinence	63,224	0.22	0.41	0	1
Lifetime sex partner	54,166	3.86	5.48	1	90
Age at First Sex	48,416	16.9	3.11	5	46
Female outcome variables
HIV positive	33,904	0.15	0.35	0	1
Age at first sex	23,702	16.5	2.6	7	39
Condom use first intercourse	9,777	0.30	0.46	0	1
Premarital abstinence	33,446	0.25	0.43	0	1
Lifetime sex partner	29,003	2.09	1.85	1	70
Male outcome variables
HIV positive	29,978	0.10	0.31	0	1
Age at first sex	24,714	17.3	3.52	5	46
Condom use first intercourse	7,535	0.29	0.45	0	1
Premarital abstinence	29,778	0.18	0.39	0	1
Lifetime sex partners	25,163	5.90	7.3	1	90
Explanatory variables
Distance to church	64,033	26.69	25.37	0.11	142.51
Log distance to health centre	64,033	3.47	1.00	−2.19	5.11
Protestant	62,939	0.81	0.39	0	1
Protestant church	64,033	0.82	0.38	0	1
Age	64,033	29.25	10.63	15	59
Age squared	64,033	968.59	698.07	225	3481
Married	58,139	0.62	0.49	0	1
Female	64,033	0.53	0.50	0	1
Urban	64,033	0.43	0.50	0	1
River 10 km	64,033	0.44	0.50	0	1
Explorer route 50 km	64,033	0.53	0.50	0	1
Rail 50 km	64,033	0.35	0.48	0	1
Mean log land elevation	64,033	1.31	0.16	0.73	1.87
Province	64,033	5.26	2.75	1	10
Asset index	63,224	2.86	1.30	1	5
Highest education level	64,015	1.49	0.71	0	3
Occupation	63,007	3.09	2.83	0	9

Table A2. Protestant and Catholic missionaries and HIV infection.

Dependent variable: HIV status
	Protestant	Catholic
Distance to church	−0.00182**	−0.00227*
	(0.000733)	(0.00126)
Distance to health centre	−0.0268*	0.0203
	(0.0145)	(0.0245)
Provincial FE	Yes	Yes
Occupational FE	Yes	Yes
Geographic controls	Yes	Yes
Individual controls	Yes	Yes
Observations	45,882	10,106

Note: Probit model estimates. Clustered robust standard errors at the DHS cluster level are given in parentheses. The comparison group for the asset index is individuals with the highest index. The comparison group for education level is individuals with the highest level of education. Distance to health centre is log-transformed, and distance to church is given in kilometres. Geographic controls include whether the cluster is within 50 km of an explorer route, 50 km of the railway, or 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions to those who answered that where they were living was their usual place of residence. Individual control: age, age squared, married, female, urban, asset index, education level. ***p < .01, **p < .05, *p < .1. FE = fixed effects.

Table A3. Christian missions and the heterogeneous impact on HIV infection.

	Female	Male
Distance to mission	−0.00145*	−0.00164**
	(0.000784)	(0.000819)
Distance to health centre	−0.0208	−0.0197
	(0.0155)	(0.0184)
Provincial FE	Yes	Yes
Geographic controls	Yes	Yes
Occupational FE	Yes	Yes
Individual controls	Yes	Yes
Observations	23,868	22,506

Note: Probit model estimates. Clustered robust standard errors at the DHS cluster level are given in parentheses. The comparison group for the asset index is individuals with the highest index. The comparison group for education level is individuals with the highest level of education. Distance to health centre is log-transformed, and distance to church is given in kilometres. Geographic controls include whether a cluster is within 50 km of an explorer route, 50 km of the railway, or 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions to those who answered that where they were living was their usual place of residence. Individual controls: age, age squared, married, female, urban, Protestant, lifetime partners, asset index, education level. ***p < .01, **p < .05, *p < .1.

Table A4. Heterogeneous effect of Christian missions and lifetime sex partners.

	(1)	(2)	(3)	(4)
	Women	Men	Women	Men
Distance to Protestant mission	−0.000748	−0.00484
	(0.000733)	(0.00370)
Distance to health centre	−0.0135	−0.0776	0.000952	−0.162
	(0.0191)	(0.102)	(0.0247)	(0.122)
Distance to Catholic mission			−0.00214*	−0.0126**
			(0.00119)	(0.00500)
Provincial FE	Yes	Yes	Yes	Yes
Occupational FE	Yes	Yes	Yes	Yes
Geographic controls	Yes	Yes	Yes	Yes
Individual controls	Yes	Yes	Yes	Yes
Observations	19,937	18,736	4,354	4,292
R^2	0.038	0.058	0.059	0.064

Note: OLS model estimates. Clustered robust standard errors at the DHS cluster level are given in parentheses. The comparison group for the asset index is individuals with the highest index. The comparison group for education level is individuals with the highest level of education. Distance to church is given in kilometres. Geographic controls include whether a cluster is within 50 km of an explorer route, 50 km of the railway, or 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions to those who answered that where they were living was their usual place of residence. Individual control: age, age squared, married, female, urban, Protestant, asset index, education level. ***p < .01, **p < .05, * p < .1.

Table A5. Heterogeneous effects of Christian missionaries on premarital abstinence.

	(1)	(2)	(3)	(4)
	Women	Men	Women	Men
Distance to Protestant mission	0.00139*	0.00151**
	(0.000772)	(0.000714)
Distance to health centre	−0.00564	−0.000670	0.0157	−0.0195
	(0.0162)	(0.0147)	(0.0335)	(0.0330)
Distance to Catholic mission			−0.000249	0.00246*
			(0.00136)	(0.00135)
Provincial FE	Yes	Yes	Yes	Yes
Occupational FE	Yes	Yes	Yes	Yes
Geographic controls	Yes	Yes	Yes	Yes
Individual controls	Yes	Yes	Yes	Yes
Observations	23,542	22,434	5,110	5,023

Note: Probit model estimates. Clustered robust standard errors at the DHS cluster level are give in parentheses. The comparison group for the asset index is individuals with the highest index. The comparison group for education level is individuals with the highest level of education. Distance to health centre is log-transformed, and distance to church is given in kilometres. Geographic controls include whether a cluster is within 50 km of an explorer route, 50 km of the railway, or 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions to those who answered that where they were living was their usual place of residence. Individual control: age, age squared, married, urban, Protestant, asset index, education level. ***p < .01, **p < .05, *p < .1.

Table A6. Heterogeneous effect of Christian missionaries on age at first sex.

	(1)	(2)	(3)	(4)
	Women	Men	Women	Men
Distance to Protestant mission	−8.96e-05	0.00469***
	(0.00122)	(0.00175)
Distance to health centre	−0.00379	−0.0303	−0.0219	−0.0470
	(0.0293)	(0.0441)	(0.0499)	(0.106)
Distance to Catholic mission			5.95e-05	0.00238
			(0.00258)	(0.00384)
Provincial FE	Yes	Yes	Yes	Yes
Occupational FE	Yes	Yes	Yes	Yes
Geographic controls	Yes	Yes	Yes	Yes
Individual controls	Yes	Yes	Yes	Yes
Observations	16,452	18,491	3,364	4,093
R^2	0.229	0.169	0.156	0.157

Note: OLS model estimates. Clustered robust standard errors at the DHS cluster level are given in parentheses. The comparison group for the asset index is individuals with the highest index. The comparison group for education level is individuals with the highest level of education. Distance to church is given in kilometres. Geographic controls include whether a cluster is within 50 km of an explorer route, 50 km of the railway, or 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions to those who answered that where were living was their usual place of residence. Individual control: age, age squared, married, urban, Protestant, asset index, education level. ***p < .01, **p < .05, *p < .1.

Table A7. Heterogeneous effect of Christian missionaries on condom use at first intercourse.

	(3)	(4)	(5)	(6)
	Female	Male	Female	Male
Distance to health centre	0.0158	−0.00524	−0.0892	0.0489
	(0.0278)	(0.0343)	(0.101)	(0.0786)
Distance to Protestant mission	0.000261	0.00115
	(0.00129)	(0.00175)
Distance to Catholic mission			0.00524	0.00158
			(0.00365)	(0.00326)
Provincial FE	Yes	Yes	Yes	Yes
Occupational FE	Yes	Yes	Yes	Yes
Geographic controls	Yes	Yes	Yes	Yes
Individual controls	Yes	Yes	Yes	Yes
Observations	3,806	3,342	725	627

Note: Probit model estimates. Clustered robust standard errors at the DHS cluster level are given in parentheses. The comparison group for the asset index is individuals with the highest index. The comparison group for education level is individuals with the highest level of education. Distance to health centre is log-transformed, and distance to church is given in kilometres. Geographic controls include whether a cluster is within 50 km of an explorer route, 50 km of the railway, or 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions to those who answered that where they were living was their usual place of residence. Individual controls: age, age squared, married, condom knowledge, condom access, urban, Protestant, lifetime partners, asset index, education level. ***p < .01, **p < .05, *p < .1.

Table A8. Oster test for Christian missionary impact on HIV infection.

Dependent variable: HIV status
R-max: 1.3R^2
Distance to church	−0.0002***
	(0.00008)
Distance to health centre	−0.0037*
	(0.00181)
Oster coefficient	0.57
R-max: 2.2R^2
Distance to church	−0.0002***
	(0.00008)
Distance to health centre	−0.0037*
	(0.00181)
Oster coefficient	0.14
R-max: 3.3R^2
Distance to church	−0.0002***
	(0.00008)
Distance to health centre	−0.0037*
	(0.00181)
Oster coefficient	0.08
Individual controls	Yes
Provincial FE	Yes
Occupational FE	Yes
Observations	46,374

Note: Probit model estimates. Clustered robust standard errors at the DHS cluster level are given in parentheses. The comparison group in this analysis is individuals with the highest number of assets. The comparison group for education level is individuals with the highest level of education. Distance to health centre is log-transformed. Geographic controls include whether a cluster is within 50 km of an explorer route, 50 km of the railway, or 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions to those who answered that where they were living was their usual place of residence. Then I also include occupational and provincial fixed effects. ***p < .01, **p < .05, *p < 0.

Table A9. Comparison between author geocoded missions and Cagé and Rueda (2020) missions.

Dependent variable: HIV status
Variables	New geocoded missions	Cagé and Rueda missions
Distance to church	−0.00188***	−0.000128
	(0.000646)	(0.000198)
Constant	−3,944***	−4,031***
	(0.218)	(0.213)
Provincial FE	Yes	Yes
Occupational FE	Yes	Yes
Geographic controls	Yes	Yes
Individual controls	Yes	Yes
All other controls	Yes	Yes
Observations	45,264	45,215

Note: Probit model estimates. Clustered robust standard errors at the DHS cluster level are given in parentheses. The comparison group for the asset index is individuals with the highest index. The comparison group for education level is individuals with the highest level of education. Distance to health centre is log-transformed, and distance to church is given in kilometres. Geographic controls include whether a cluster is within 50 km of an explorer route, 50 km of the railway, of 10 km of a river, and mean land elevation in logarithmic form. For all the models, I confine the regressions to those who answered that where they were living was their usual place of residence. Individual controls: age, age squared, married, condom knowledge, condom access, urban, Protestant, lifetime partners, asset index, education level. ***p < .01, **p < .05, *p < .1.

World Bank, World Development Indicators. 2020. HIV/AIDS. Retrieved from https://databank.worldbank.org/databases/hiv/aids

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Cagé, J., and V. Rueda. 2020. “Sex and the Mission: The Conflicting Effects of Early Christian Missions on HIV in sub-Saharan Africa.” Journal of Demographic Economics 86 (3): 213–257. https://doi.org/10.1017/dem.2019.16.

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