Drought and intimate partner violence towards women in 19 countries in sub-Saharan Africa during 2011-2018: A population-based study.

BACKGROUND: Drought has many known deleterious impacts on human health, but little is known about the relationship between drought and intimate partner violence (IPV). We aimed to evaluate this relationship and to assess effect heterogeneity between population subgroups among women in 19 sub-Saharan African countries. METHODS AND
FINDINGS: We used data from 19 Demographic and Health Surveys from 2011 to 2018 including 83,990 partnered women aged 15-49 years. Deviations in rainfall in the year before the survey date were measured relative to the 29 previous years using Climate Hazards Group InfraRed Precipitation with Station data, with recent drought classified as ordinal categorical variable (severe: ≤10th percentile; mild/moderate: >10th percentile to ≤30th percentile; none: >30th percentile). We considered 4 IPV-related outcomes: reporting a controlling partner (a risk factor for IPV) and experiencing emotional violence, physical violence, or sexual violence in the 12 months prior to survey. Logistic regression was used to estimate marginal risk differences (RDs). We evaluated the presence of effect heterogeneity by age group and employment status. Of the 83,990 women included in the analytic sample, 10.7% (9,019) experienced severe drought and 23.4% (19,639) experienced mild/moderate drought in the year prior to the survey, with substantial heterogeneity across countries. The mean age of respondents was 30.8 years (standard deviation 8.2). The majority of women lived in rural areas (66.3%) and were married (73.3%), while less than half (42.6%) were literate. Women living in severe drought had higher risk of reporting a controlling partner (marginal RD in percentage points = 3.0, 95% CI 1.3, 4.6; p < 0.001), experiencing physical violence (marginal RD = 0.8, 95% CI 0.1, 1.5; p = 0.019), and experiencing sexual violence (marginal RD = 1.2, 95% CI 0.4, 2.0; p = 0.001) compared with women not experiencing drought. Women living in mild/moderate drought had higher risk of reporting physical (marginal RD = 0.7, 95% CI 0.2, 1.1; p = 0.003) and sexual violence (marginal RD = 0.7, 95% CI 0.3, 1.2; p = 0.001) compared with those not living in drought. We did not find evidence for an association between drought and emotional violence. In analyses stratified by country, we found 3 settings where drought was protective for at least 1 measure of IPV: Namibia, Tanzania, and Uganda. We found evidence for effect heterogeneity (additive interaction) for the association between drought and younger age and between drought and employment status, with stronger associations between drought and IPV among adolescent girls and unemployed women. This study is limited by its lack of measured hypothesized mediating variables linking drought and IPV, prohibiting a formal mediation analysis. Additional limitations include the potential for bias due to residual confounding and potential non-differential misclassification of the outcome measures leading to an attenuation of observed associations.
CONCLUSIONS: Our findings indicate that drought was associated with measures of IPV towards women, with larger positive associations among adolescent girls and unemployed women. There was heterogeneity in these associations across countries. Weather shocks may exacerbate vulnerabilities among women in sub-Saharan Africa. Future work should further evaluate potential mechanisms driving these relationships.

Introduction

Climate change, extreme weather events, and in particular droughts negatively impact human health [1-3]. Droughts are becoming increasingly common and of higher intensity in many regions across the globe including sub-Saharan Africa, due, at least in part, to human activity [4,5]. In 2011–2012, East Africa experienced a severe drought that spawned a subsequent refugee crisis [6]. In 2014–2016, Southern Africa experienced 2 years of an El Niño–induced drought, leading to national emergency declarations in a number of countries and exposing 38 million people across the region to drought [7]. In 2019, the number of individuals exposed to severe drought in sub-Saharan Africa swelled to 45 million [8]. There are significant gaps in our understanding of the relationship between droughts and human health.

Droughts lead to reduced agricultural production, impacting households’ food security and income [3,9]. These impacts may affect downstream health and behavioral outcomes such as nutrition [2,10], HIV prevalence and risk [11,12], and the incidence of infectious diseases such as diarrhea and respiratory infection [13,14]. One potential downstream effect of drought that has received little attention is intimate partner violence (IPV) towards women. In addition to being a global human rights concern, IPV is associated with a multitude of negative health consequences such as physical injury, high-risk sexual behaviors, HIV, reproductive disorders, adverse pregnancy outcomes, and psychological effects including suicidal ideation, drug abuse, and mental health disorders [15-20]. IPV is especially prevalent in Africa, where 36.6% of ever-partnered women experience physical and/or sexual IPV in their lifetime [21]. Studies suggest that deviations from long-term trends of temperature and precipitation, including drought, are associated with violence at the interpersonal, intergroup, and institutional levels [22-24]. Hypothesized mechanisms include food insecurity and migration [25-27]. There is no literature to date to our knowledge examining associations between drought and IPV. In addition to the above mechanisms, IPV may be influenced by drought through additional pathways including increased inequalities in access to resources, disordered urbanization, poverty, disempowerment, and psychological distress [22,28-30].

Drought may have heterogenous effects on IPV between population subgroups. For example, adolescent girls are at higher risk for IPV globally [31,32] due to their young age and inexperience with relationships. This vulnerability may be exacerbated during times of income instability and food insecurity. Employed women are at lower risk for IPV [33]. They may, in addition, experience fewer negative effects of drought due to economic independence and empowerment, which could lessen the negative impacts of drought on poverty and food insecurity, particularly if employment is not negatively impacted by drought. However, there is no research to our knowledge on the impacts of drought on IPV in these population subgroups.

In the present analysis, we used nationally representative, cross-sectional survey data from 19 countries in sub-Saharan Africa from the period 2011–2018 to investigate the relationships between drought and emotional, physical, and sexual violence among partnered women. Furthermore, we evaluated the evidence for differences in these associations between population subgroups (age group and employment status).

Methods

This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (S1 Checklist).

Data source and participants

This study used data from the Demographic and Health Surveys (DHS), which are cross-sectional, nationally representative household-based surveys funded by the United States Agency for International Development. The surveys use a stratified 2-stage cluster sampling design, selecting first a random sample of enumeration areas (EAs), followed by a random sample of households within each EA. All women aged 15 to 49 years within selected households are invited to complete a questionnaire. A random subset of women in the DHS samples are selected to participate in the domestic violence module.

We used surveys that included geolocated information on each EA and took place during or after 2011, using this year as a cutoff due to the availability of precipitation data (see S1 Table for a full list of surveys included in this analysis). We restricted our sample to the women who participated in the domestic violence module. We excluded women who were not currently married or residing with a male partner. Full information on the outcomes of interest and covariates was also required for inclusion. Mali was excluded from the analysis because no women experienced any level of drought in the study window.

Measures

Drought

Drought was measured using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data, which combine satellite imagery with weather station data to create raster rainfall estimates in millimeters at 0.05-decimal-degree resolution from 1981 onward [34]. Annual cumulative precipitation for the 12 months preceding the survey date was calculated for each unique survey date/EA combination. We then ranked this quantity of precipitation with the prior 29 years and converted this ranking to a percentile; for example, the 50th percentile signifies the median level of precipitation in the 30-year period. This use of deviations from long-term precipitation trends is standard in the literature, as it captures weather shocks representing deviations from the norm and therefore does not reflect inherent differences in populations that live in drier or wetter areas [11,12]. We generated an ordinal categorical variable of drought, classifying severe drought as annual precipitation equal to or lower than the 10th percentile of the historical record, mild/moderate drought as above the 10th percentile and equal to or below the 30th percentile, and no drought as above the 30th percentile. We also considered a binary categorization of drought, where drought was defined as annual precipitation in the 12 months prior to the survey that was lower than the 15th percentile of the historical record, reflecting the level of precipitation that impacts GDP and agricultural productivity, as defined previously in the literature [11,12,35]. The calculation and classifications of drought were specified a priori; however, we did not have a written prespecified protocol.

IPV outcomes

We considered 4 binary outcomes selected prior to analysis, each representing a different dimension of risk of and/or experience of IPV (see S2 Table for the definitions of outcomes): a binary indicator representing whether the respondent reported a controlling partner (a risk factor for IPV) and binary indicators for whether the respondent had ever experienced emotional violence, physical violence, or sexual violence by her husband/partner in the 12 months prior to the survey date. We also considered a count variable representing the number of IPV outcomes the respondent endorsed during the survey.

Covariates

We included several sociodemographic variables a priori that have theoretical or empirical associations with IPV [36]. These include respondent’s age (categorized into 15–19, 20–29, 30–39, and 40–49 years), a binary indicator of respondent literacy (literate versus not literate), a binary indicator of married, the number of live births the respondent has had (categorized into 0, 1–2, 3–4, and 5+), household size (categorized into 2–3, 4–5, and 6+), a binary indicator of rural residence, husband/partner’s education level (categorized into none, primary, secondary, or higher), and husband/partner’s age (categorized into 15–19, 20–29, 30–39, 40–49, and 50+ years).

Effect modifiers

We assessed effect modification by the respondent’s age group (adolescent [15–19 years] versus adult [20+ years]) and by the respondent’s employment status (binary yes/no for whether the respondent has worked in the last 12 months) to determine whether the associations differed between population subgroups, with the hypothesis that drought would have greater negative consequences for adolescent girls and unemployed women. We also assessed the presence of effect modification by country.

Statistical analysis

To assess the association between drought and binary IPV outcomes, a series of multivariable logistic regression models were specified for each of the 4 outcomes. For the count outcome (number of IPV outcomes endorsed), we specified an ordered logistic regression model. In all models, we included country fixed effects to control for country-level differences, such as in norms, sociodemographic characteristics, and economies, and we included robust standard errors clustered at the EA level. Because we included country fixed effects, our models are “within” estimators, comparing women with different drought statuses within a given country. We first ran the models with only country-level fixed effects and the drought variable (categorical and binary classifications included separately), and subsequently added in the covariates. We then derived marginal risk differences (RDs) by implementing Stata’s margins command, which estimates effects by first deriving predictions for each observation in the sample as if they were in each level of the exposure (no drought, mild/moderate drought, and severe drought). For each level of exposure, each individual’s marginal effect is then estimated by subtracting the predicted probability of the outcome under the reference group condition (no drought) from the predicted probability under drought conditions. The effect estimate is then averaged across all observations.

To assess whether our results were sensitive to country-specific outliers, we conducted sensitivity analyses alternately leaving out each of the 19 countries in the pooled models. To assess the presence of effect modification, we generated interaction terms between hypothesized effect modifiers and the binary drought variable; we then included the interaction terms and main effects in models for each outcome. We assessed interaction on the additive scale by calculating the relative excess risk due to interaction (RERI) [37]. We considered an alpha significance level of 0.10 for the RERI term. All analyses were carried out in Stata 14 and R version 3.4.

Ethical approval

DHS obtains informed and voluntary consent from survey participants, and permission to use DHS data was obtained from the DHS program. Specific approval for this de-identified secondary data analysis was not required.

Results

The analytic sample included 83,990 eligible women from 19 countries in sub-Saharan Africa. See Fig 1 for how the sample size was determined and S1 Table for the sample size in each country.

Fig 1

Flow chart depicting how the final analytic sample was selected.

Table 1 shows the outcomes and sociodemographic characteristics among respondents. In sum, under half (42.6%) of respondents were literate, and nearly three-quarters (73.3%) were married. A majority (66.3%) of the sample resided in rural areas. Most women (93.7%) had had at least 1 live birth prior to the survey. All age categories were represented, with the lowest proportion in the adolescent (15–19 years) category (6.3%). The IPV outcomes were common: 66.2% of women reported a controlling partner, and 19.0%, 5.2%, and 4.2% of women reported having experienced emotional, physical, and sexual violence in the 12 months prior the survey, respectively. The distribution of drought status differed substantially across countries (Fig 2), ranging from 2.9% of respondents experiencing any form of drought in Cameroon to 95.6% in Togo.

Table 1

Descriptive statistics of women aged 15 to 49 years currently married or living with a male partner included in IPV analyses (n = 83,990).

Covariate or outcome	Number (percent) (n = 83,990)
Age category (years)
15–19	5,316 (6.3)
20–29	35,036 (41.7)
30–39	29,052 (34.6)
40–49	14,586 (17.4)
Literate	35,817 (42.6)
Married	61,569 (73.3)
Employed within previous 12 months	61,666 (73.4)
Number of births
0	5,316 (6.3)
1–2	26,876 (32.0)
3–4	24,947 (29.7)
5+	27,329 (32.5)
Household size
2–3	17,698 (21.1)
4–5	29,311 (34.9)
6+	36,981 (44.0)
Rural residence	55,717 (66.3)
Husband/partner’s education
No education	18,993 (22.6)
Primary	31,987 (38.1)
Secondary	27,441 (32.7)
Higher	5,569 (6.6)
Husband/partner’s age category (years)
15–19	483 (0.6)
20–29	18,674 (22.2)
30–39	31,706 (37.8)
40–49	21,171 (25.2)
50+	11,956 (14.2)
IPV outcomes
Reported a controlling partner	55,628 (66.2)
Ever experienced emotional violence in previous 12 months	15,992 (19.0)
Ever experienced physical violence in previous 12 months	4,390 (5.2)
Ever experienced sexual violence in previous 12 months	3,539 (4.2)

IPV, intimate partner violence.

Fig 2

Proportion of respondents experiencing drought over the past 12 months in each country included in the analysis.

DRC, Democratic Republic of the Congo.

Table 2 shows the associations between drought and the IPV outcomes, with drought categorized as mild/moderate drought and severe drought compared with no drought. In adjusted analyses, women living in severe drought had a 3-percentage-point higher risk of reporting a controlling partner (marginal RD = 3.0, 95% CI 1.3, 4.6; p < 0.001) compared to those not experiencing drought. Mild/moderate drought was not associated with reporting a controlling partner (marginal RD = 0.0, 95% CI −1.1, 1.2; p = 0.95). Severe and mild/moderate drought were positively associated with reported physical violence (marginal RD for severe drought = 0.8, 95% CI 0.1, 1.5; p = 0.019; marginal RD for mild/moderate drought = 0.7, 95% CI 0.2, 1.1; p = 0.003) and sexual violence (marginal RD for severe drought = 1.2, 95% CI 0.4, 2.0; p = 0.001; marginal RD for mild/moderate drought = 0.7, 95% CI 0.3, 1.2; p = 0.001). We did not find evidence for associations between drought and emotional violence. These results were consistent when drought was classified as a binary variable (S3 Table). Associations between drought and IPV in addition to all covariates are shown as odds ratios in S4 Table. Models assessing the relationship between drought and a count of IPV outcomes endorsed showed similar results, with a positive, significant association between severe drought and IPV and a marginally positive, significant association between mild/moderate drought and IPV (S5 Table).

Table 2

Associations between severe and mild/moderate drought and intimate partner violence among women aged 15–49 years (n = 83,990).

Exposure	Outcome
	Reported a controlling partner		Emotional violence in previous 12 months		Physical violence in previous 12 months		Sexual violence in previous 12 months
	Unadjusted	Adjusted	Unadjusted	Adjusted	Unadjusted	Adjusted	Unadjusted	Adjusted
No drought	REF	REF	REF	REF	REF	REF	REF	REF
Mild/moderate drought	0.3 (−0.8, 1.2)	0.0 (−1.1, 1.2)	0.4 (−0.5, 1.3)	0.4 (−0.1, 1.7)	0.7** (0.3, 1.2)	0.7**(0.2, 1.1)	0.7**(0.3, 1.2)	0.7**(0.3, 1.2)
Severe drought	3.0*** (1.4, 4.7)	3.0*** (1.3, 4.6)	0.6 (−0.8, 1.9)	0.4 (−0.5, 1.3)	0.9* (0.2, 1.6)	0.8* (0.1, 1.5)	1.3**(0.5, 1.2)	1.2**(0.4, 2.0)

Coefficients are presented as marginal risk difference estimates in percentage points from logistic regression models, with 95% confidence intervals in parentheses. The unadjusted model includes country-level fixed effects. The adjusted model includes age category, literacy, marital status, number of births, household size, rural residence, husband/partner’s age, and husband/partner’s education. Standard errors are clustered at the enumeration area level. Asterisks denote level of significance

*p < 0.05

**p < 0.01

***p < 0.001.

Fig 3 shows the associations between drought and the 4 IPV outcomes as marginal RDs for each country individually, with drought classified as a binary variable (<15th percentile of mean annual precipitation). Five countries demonstrated positive, significant associations between drought and reporting a controlling partner; 1 country demonstrated a positive, significant association between drought and physical violence; and 2 countries demonstrated positive, significant associations between drought and sexual violence. These country-level analyses also revealed scenarios in which drought was protective against IPV. In Uganda, drought was protective for all outcomes, although we could not rule out a null or positive association between drought and reported sexual violence. In Namibia, drought was protective for reporting a controlling partner. Finally, in Tanzania, drought was protective for reported emotional violence. The results were significantly heterogeneous between countries for reporting a controlling partner (p for joint interaction term < 0.001), emotional violence (p for joint interaction term = 0.009), and physical violence (p for joint interaction term = 0.022), but not for reported sexual violence (p for joint interaction term = 0.40). Due to the heterogeneity of these associations, we specified pooled models sequentially leaving out 1 country; pooled results remained consistent for all outcomes (S6 Table). We also specified pooled models using mixed effects logistic regression (with random intercepts at the country level) in order to account for cluster heterogeneity; results were qualitatively consistent (in magnitude, direction, and statistical significance) across specifications (S7 Table).

Fig 3

Country-specific adjusted associations between drought and intimate partner violence.

Country-specific adjusted associations between drought and (A) reporting a controlling partner, (B) experiencing any emotional violence in the prior 12 months, (C) experiencing any physical violence in the prior 12 months, and (D) experiencing any sexual violence in the prior 12 months. All models control for respondent age category, literacy, marital status, number of births, household size, rural residence, husband/partner’s age, and husband/partner’s education. Associations are presented as risk differences (percentage points) and 95% confidence intervals. Standard errors are clustered at the enumeration area level. Results not shown for countries with insufficient outcome data. DRC, Democratic Republic of the Congo.

We found evidence for additive effect modification of the association between age (adolescent versus adult) and drought and between employment status and drought. RDs stratified by age category and employment status are presented in Table 3. Adolescents who experienced drought had a higher risk of reporting a controlling partner (marginal RD = 4.4, 95% CI 0.9, 7.9; p = 0.011) and emotional violence (marginal RD = 3.2, 95% CI 0.1, 6.3; p = 0.030) than those not living in drought. Among adult women, drought was not associated with reporting a controlling partner (marginal RD = 1.3, 95% CI 0.0, 2.6; p = 0.063) nor with emotional violence (marginal RD = −0.8, 95% CI −1.9, 0.3; p = 0.14). This heterogeneity was statistically significant (drought–adolescent RERI p = 0.092 for reporting a controlling partner and drought–adolescent RERI p = 0.011 for emotional violence). Drought was positively associated with risk of reported physical violence in both age groups, with no evidence for effect heterogeneity (drought–adolescent RERI p = 0.16). Drought was also associated with sexual violence among adult women (marginal RD = 0.7, 95% CI 0.1, 1.4; p = 0.014). This association was not statistically significant among adolescent girls (marginal RD = −0.2, 95% CI −1.9, 1.6; p = 0.86); however, there was no evidence for effect heterogeneity (drought–adolescent RERI p = 0.34).

Table 3

Associations between drought and intimate partner violence among women aged 15–49 years stratified by age and employment status (n = 83,990).

Outcome	Risk difference (95% CI)
	Stratified by age category		Stratified by employment status
	15–19 years	20+ years	Not employed	Employed
Reported a controlling partner	4.4* (0.9, 7.9)	1.3 (0.0, 2.6)	3.2** (1.1, 5.4)	0.7 (−0.9, 2.2)
Ever experienced emotional violence in previous 12 months	3.2* (0.1, 6.3)	−0.8 (−1.9, 0.3)	0.3 (−1.3, 1.9)	−0.8 (−2.2, 0.5)
Ever experienced physical violence in previous 12 months	2.0* (0.1, 3.8)	0.6* (0.0, 1.2)	1.1** (0.2, 2.0)	0.3 (−0.3, 1.0)
Ever experienced sexual violence in previous 12 months	−0.2 (−1.9, 1.6)	0.7* (0.1, 1.4)	1.5** (0.4, 2.5)	0.1 (−0.6, 0.9)

Coefficients are presented as risk difference estimates in percentage points from logistic regression models, with 95% confidence intervals in parentheses. Adjusted for respondent age category, literacy, marital status, number of births, household size, rural residence, husband/partner’s age, and husband/partner’s education. Standard errors are clustered at the enumeration area level. Asterisks denote level of significance

*p < 0.05

**p < 0.01.

There was also evidence of interaction between drought and employment for reporting a controlling partner (drought–employment RERI p = 0.050) and reporting sexual violence (drought–employment RERI p = 0.022). In both of these instances, unemployed women demonstrated positive associations between drought and IPV, whereas we did not observe associations among employed women. Drought was associated with greater risk of reported physical violence among unemployed women but not employed women, although there was no evidence for effect heterogeneity (drought–employment RERI p = 0.13). Drought and emotional violence were not associated among employed nor unemployed women (drought–employment RERI p = 0.19)

Discussion

While previous studies have found associations between heat waves and aggressive or violent behavior [38-40], this study extends the literature on climate variation and violence by exploring the relationship between drought and IPV towards women. Using cross-sectional surveys of 83,990 women from 19 countries in sub-Saharan Africa from the period 2011–2018, we found associations between drought and several manifestations of IPV in pooled analyses. Women in mild/moderate drought were at similar risk of physical violence to those in severe drought, with 0.7-percentage-point and 0.8-percentage-point marginal RDs, respectively. These estimates are large in magnitude given the prevalence of reported physical violence in the sample (5.2%), corresponding to 14% higher risk of reported physical violence in mild/moderate drought and 15% higher risk in severe drought. Women in severe drought were also at greater risk of reported sexual violence than those in mild/moderate drought. Similarly, these marginal RDs are substantially higher than baseline risk: severe drought was associated with a 28.6% higher prevalence of women reporting sexual violence in the sample (4.2%), and mild/moderate drought was associated with a 17% higher prevalence. Women who experienced severe drought were more likely to report having a controlling partner, a risk factor for IPV, while those in mild/moderate drought were not. Finally, we did not find evidence for an association between drought and emotional IPV in the pooled sample.

The findings from this analysis coincide with the broader literature on climate and violence, which suggests that drought is associated with increased conflict at the national and sub-national levels [22-24]. These associations are attributed to rising commodity prices and increased scarcity of resources such as fresh water during drought. Drought has also been linked to increases in the incidence of personal violence, such as murder [41] and property crimes [22,42]. Our findings suggest that another manifestation of this relationship between drought and violence may exist in the context of IPV.

There are several potential mechanisms that could explain the relationships between drought and dimensions of IPV. Drought may impact a household’s income by negatively affecting agricultural production, food supply, health, and household savings. Poverty, in turn, is associated with IPV [25-27]. These income and food production shocks may lead to food insecurity, which has been linked with IPV in several settings, including Nepal, the United States, Brazil, and Southern Africa [43-47]. Both food insecurity and poverty create risk for IPV through the pathway of stress [48,49], which results from hunger, worry about food access, and financial strain on the household. Stress may impact physical IPV and could also affect a partner’s desire to control his wife’s movements and behaviors. Poverty and food insecurity can also lead to poor mental health conditions such as depression, a risk factor for IPV [49,50]. In addition, poverty and food insecurity may lead to disempowerment. For example, living in a food-insecure and impoverished household may impact a woman’s ability to leave an abusive partner, due to economic dependence [51]. Finally, drought is a known contributor to migration [52-54], and migrant women are at higher risk for IPV due to their lack of social support and the added vulnerability of their migrant status [55-57].

We found interactions between drought and age, such that adolescent girls in drought demonstrated higher risk of reporting a controlling partner and emotional violence, while adult women did not. Research has found that younger women, including adolescent girls, are at higher risk for IPV [31]. Our findings suggest that the impacts of drought exacerbate these vulnerabilities, potentially due to the fact that younger women have lower social standing and are relatively inexperienced [32]. We did not find evidence for an association between drought and reported sexual violence among adolescent girls; this may be due to study power constraints, given the small number of adolescent girls who experienced sexual violence (n = 247). We also found that unemployed women in drought had higher risk of reporting a controlling partner, sexual violence, and physical violence, while these associations were not found in employed women. Both of these findings—that younger women and unemployed women in drought are at higher risk for IPV—suggest that power imbalances may be compounded by drought and subsequent poverty and food insecurity. These 2 findings may be linked, as younger women are less likely to be economically independent from their partners. In contrast with our findings and other literature documenting a protective association between employment and IPV [33], some previous work has suggested that female employment may increase risk of IPV due to perceived power imbalances by the spouse [58,59]. However, in the context of drought, it may be that the woman’s income contributes to household resilience to poverty and food insecurity associated with drought, which in turn decreases risk for violence. Given the cross-sectional nature of the data, it is difficult to disentangle the directionality of the relationship between employment and IPV. Qualitative and longitudinal studies are needed to elucidate the mechanisms underpinning the association between employment and IPV in the context of drought.

Contrary to our hypothesis, we found 3 settings in which drought was protective against IPV. In Namibia, a setting with markedly high prevalence of drought, women who lived in drought areas were less likely to report a controlling partner and physical violence. In Uganda and Tanzania, countries with very low prevalence of drought (7.9% and 0.7%, respectively), we found drought was protective for reporting emotional violence. One potential explanation is that these countries experienced excessive rains during the 30 years prior to the survey, and therefore drought may reflect reprieve. More research, including qualitative studies, is needed in these countries to elucidate potential mechanisms driving these associations and to better understand the heterogeneity in these findings.

We did not find evidence for an association between drought and emotional violence in the pooled sample, also contrary to our hypothesis. This may be because emotional violence is less clearly defined than physical and sexual violence and is therefore more prone to measurement error, leading to an attenuation of the association.

Strengths and limitations

The strength of this study is that it includes 19 different countries in sub-Saharan Africa, representing varying agricultural systems, environments, and sociodemographic makeups. The surveys took place across an 8-year window and represent a range of drought conditions. The potential for confounding is low in this study because we defined drought as precipitation relative to the 29 previous years, and, as such, the exposure should be independent from potential confounding variables, that is, we have removed variation representing factors associated with historically drier or wetter places.

This analysis has several limitations. First, causal claims are challenging in this context due to the cross-sectional nature of DHS surveys. However, given the low likelihood of reverse causality, the directionality of this hypothesized relationship is supportable. Second, there may be inconsistencies in how data were collected across countries and years with respect to IPV. However, the DHS program strives to achieve standardization in data collection procedures across locations and timepoints. Third, the IPV outcomes may be misclassified because women tend to underreport experiences of IPV, which could affect the magnitude of associations, and there may be cultural differences in reporting IPV across regions and countries. However, we do not believe that IPV reporting bias would depend on drought exposure status within countries, and therefore any bias would be toward the null on average, suggesting that our results underestimate the magnitude of true associations. Fourth, although we hypothesize several mechanisms, this study does not include a direct mediation analysis. A formal mediation analysis was not possible in this context due to the lack of collection of data in the DHS on several hypothesized mediators. For example, although we have data on wealth measured with an asset index, we do not believe this adequately captures the income and expenditure shocks associated with drought. Repeating this analysis in a new dataset with measures of hypothesized mediators, including mental health, food security, migration history, and expenditure indicators, could be an important next step in this field of research. Fifth, we do not include sampling weights in this analysis, which may limit the generalizability of our findings. However, the inclusion of 19 countries across sub-Saharan Africa, rather than restricting the study to 1 country, enhances the external validity of these findings. Sixth, the IPV questions were only asked of married and cohabitating women, and hence the results are not generalizable to women with a different relationship status. Since unmarried, non-cohabitating women are also at risk for IPV, future studies should assess these associations among all women. Seventh, we were unable to assess the impact of repeated exposure to drought, given the availability of CHIRPS rainfall data. Eighth, given the observational nature of the data, residual confounding may bias the observed associations. However, by using EA-level deviation from long-term precipitation as the definition of drought, the possible variation related to sociodemographic factors associated with historically drier or wetter places that may also impact IPV should be removed, and therefore we do not expect confounding to be substantial. Finally, the CHIRPS precipitation dataset relies on both satellite data and ground stations. The distribution of stations across sub-Saharan Africa is not consistent, and some countries may have less accurate precipitation data than others, leading to the potential for misclassification of drought in some settings. However, by classifying drought as the percentile of annual precipitation over the past 30 years, rather using absolute estimates of rainfall, we believe we have reduced the potential for misclassification.

Conclusions and implications

There is a growing body of literature on the health effects of drought across the globe. Our study contributes to this field of inquiry, with results suggesting that drought may impact IPV. This finding has broad implications, as drought may be contributing not only to IPV, but to downstream health-related consequences of IPV such as reproductive disorders, physical injury, and psychological effects. Given the anticipated acceleration of weather shocks and drought events in the coming years, more research is imperative to elucidate the pathways linking drought and violence in order to best tailor interventions aimed at reducing the effects of drought on IPV.

STROBE checklist.

(DOC)

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List of surveys included in analysis.

(DOCX)

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Definition and dimensions of the outcomes considered in this analysis.

(DOCX)

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Associations between drought and IPV among women aged 15–49 years in pooled analysis with drought considered as a binary variable.

(DOCX)

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Associations between drought and IPV among all women aged 15–49 years in pooled analysis with covariates.

(DOCX)

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Associations between drought and number of IPV outcomes endorsed among all women aged 15–49 years in pooled analysis.

(DOCX)

Click here for additional data file.

Associations between drought and IPV among women aged 15–49 years in pooled analysis with each country sequentially removed.

(DOCX)

Click here for additional data file.

Associations between drought and IPV among women aged 15–49 years in pooled analysis specified with multilevel logistic regression.

(DOCX)

Click here for additional data file.

24 Nov 2019

Dear Dr. Epstein,

Thank you very much for submitting your manuscript "Drought and intimate partner violence: findings from 19 countries in sub-Saharan Africa" (PMEDICINE-D-19-03834) for consideration at PLOS Medicine.

Your paper was discussed among the editorial team and sent to independent reviewers, including a statistical reviewer. The reviews are appended at the bottom of this email and any accompanying reviewer attachments can be seen via the link below:

[LINK]

In light of these reviews, we will not be able to accept the manuscript for publication in the journal in its current form, but we would like to invite you to submit a revised version that fully addresses the reviewers' and editors' comments. You will appreciate that we cannot make a decision about publication until we have seen the revised manuscript and your response, and we expect to seek re-review by one or more of the reviewers.

In revising the manuscript for further consideration, your revisions should address the specific points made by each reviewer and the editors. Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments, the changes you have made in the manuscript, and include either an excerpt of the revised text or the location (eg: page and line number) where each change can be found. Please submit a clean version of the paper as the main article file; a version with changes marked should be uploaded as a marked up manuscript.

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We hope to receive your revised manuscript by Dec 13 2019 11:59PM. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

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Please use the following link to submit the revised manuscript:

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Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

Please let me know if you have any questions. Otherwise, we look forward to receiving your revised manuscript in due course.

Sincerely,

Richard Turner, PhD

Senior Editor, PLOS Medicine

rturner@plos.org

-----------------------------------------------------------

Requests from the editors:

Please add an additional sentence or two to the data statement so as to assist readers in locating and accessing the study data.

Please adapt your title so that the portion after the colon makes the study design (e.g. "a cross-sectional study") clear.

We ask you to note in the "methods and findings" subsection of your abstract the countries which do not fit with the pattern of "drought associated with IPV".

In your abstract and elsewhere, please include p values alongside CI where available.

Please add summary demographic details about study participants to your abstract.

Please add a new final sentence to the "methods and findings" subsection of your abstract, in which you summarize the study's main limitations.

After the abstract, we will need to ask you to add a new and accessible "author summary" section in non-identical prose. You may find it helpful to consult one or two recent research papers published in PLOS Medicine to get a sense of the preferred style.

At line 48, please add "In this study, we found that ..." or similar.

In the paragraph at lines 85-89, please use a consistent tense (i.e., "we used ... we evaluated").

Early in the methods section of your main text, please state whether or not the study had a protocol or prespecified analysis plan, and if so attach the document(s) as a supplementary file (referred to in the methods section). Please highlight analyses that were not prespecified.

To your methods section, please add a brief statement on ethics approval, which might state that specific approval was not required for the present study, for example.

Throughout your text, please format reference call-outs as follows: "... human activity [4,5].".

Please avoid "-0.0", as at line 234, for example.

Please ensure that all reference citations have full access information (e.g., reference 9). References 29, 32 and 41 may need some additional information.

Please add a completed checklist for the most appropriate reporting guideline, which may be STROBE or RECORD, referred to in your methods section. In the checklist, individual items should be referred to by section (e.g., "Methods") and paragraph number rather than by page or line numbers, as the latter generally change in the event of publication.

Comments from the reviewers:

*** Reviewer #1:

This is a very impressive and important study detailing the social and psychological impact of droughts in Sub-Saharan Africa. The authors have performed a very commendable job of using nationally-representative data from 19 countries and demonstrate that exposure to prolonged periods of drought is associated with different forms of interpersonal violence. It points to the need to address the emotional impacts of a very specific climate-related event which threaten the lives of women in particular and families in general as they struggle to cope with the economic consequences of such events.

There are a few suggestions offered that would improve the quality and impact of the manuscript, however. First, the authors should probably document the number of people whose lives have been affected by drought in Sub-Saharan Africa, both today and during the study period. Such information is readily available from sources such as the UN and the WHO. Second, IPV was assessed using four binary indicators, but this raises the question as to whether someone could experience more than one form of IPV. It would be helpful if the authors examined whether there was a dose-response relationship between extent of drought and number of IPV indicators or explain why such a comparison is not meaningful or possible with the data. Third, while Figure 2 illustrates differences in drought level by country, there are also important differences in drought level within each country during the study period. Women in some of these countries may have been exposed to longer periods of drought than others but the results do not appear to reflect this. If the ranking of quantity of precipitation does reflect these differences, then the authors should explain how it does so. Fourth, the proposed conceptual framework presented in the discussion section on p. 19 should be eliminated as the study provided no results supporting it. A discussion of potential causal mechanisms is appropriate, but presentation of a conceptual framework such as the one proposed in the manuscript is premature. Fifth, while the inclusion of 19 countries may enhance the external validity of the study findings, it also increases the likelihood of ignoring important cultural differences within those 19 countries. This should be addressed as a potential limitation as cultural differences may result in different patterns of reporting of the different forms of IPV. While drought may reflect a reprieve in Uganda and Tanzania, it does not appear to be the case in Namibia.

*** Reviewer #2:

This is a well-written study investigating ecological associations at a country level between drought and IPV in sub-Saharan Africa. The introduction presents a clear justification for the study. The methods are reported in appropriate detail and there are good measures of drought rates and sensitive measures of IPV across 4 outcomes (being controlled, victim of violence, emotional abuse, and sexual violence). These IPV-related outcomes are based on self-report measures and the authors excluded 31% of participants who were asked questions in the domestic violence module of a questionnaire as they were not married or living with a partner.

Some major areas that need clarification:

1. Why did the authors exclude these 31% of participants. Is it the case that only those who are married or living with a male partner can experience IPV? I would assume that intimate relationships (and therefore IPV) can exist outside of these inclusion criteria, and thus the IPV estimates reported in the paper may be biased one way or the other due to this exclusion (and I would suspect that they are biased upwards).

2. The covariates were categorized a priori. Was this the same for other variables (e.g. drought, IPV-related outcomes)? Was there a statistical plan?

3. The findings appear to show considerable between-country heterogeneity, which would question their decision to pool findings and present overall marginal risk differences. Can they estimate the degree of heterogeneity? Looking at control-related outcome, 11 countries had no clear relationship with drought, 2 were negatively associated, and 6 were positively associated. This is too much statistical heterogeneity in my view for a pooled estimate.

4. There is also heterogeneity across the 4 IPV-related outcomes - in that emotional outcomes are not associated with drought, unlike pooled estimates for sexual violence or interpersonal violence.

5. The conclusion starts referring to 'increased risk' whereas the results discussed marginal risk differences. Consistency in the presentation of the findings is required.

Overall, with the substantial between-country and across-outcome heterogeneities, I think that the findings do not warrant the relatively firm conclusions drawn. Other measures of IPV would be helpful to triangulate the findings, which as they stand are hypothesis-generating.

*** Reviewer #3:

Alex McConnachie

This review considers the use of statistics in the paper by Epstein and colleagues, which investigates the association between periods of drought and reports of intimate partner violence in sub-Saharan Africa.

Overall, I think the statistical elements of the paper are very good. The data sources are well described, and the use of logistic regression to assess the association of interest is perfectly reasonable. Presenting the results on an absolute scale, rather than as odds ratios, is an interesting approach, and perfectly reasonable. Use of interactions to assess variations in associations between subgroups is good.

The comments that I have are generally quite minor.

Line 140 mentions the minimum household size as being 1, when I think it should be 2. I saw the same thing in Appendix S4.

Line 199 uses the word "relationship", when "association" is slightly preferable, to avoid any implication of causality.

Figure 3 shows country-specific associations. Are these derived from separate models, with different covariate effects in each model, or from models with country-by-drought interactions? Are these associations significantly different? I suspect they are, but a p-value would help.

Line 291 raised an interesting point. Does this mean that it was not possible from the survey data used, to identify women who had experienced IPV in the previous 12 months, but had left the household by the time of the survey? Even if this were possible, it would probably also be necessary to identify women who had left a partner in the past 12 months without experiencing IPV, and I can imagine this would be more difficult.

***

Any attachments provided with reviews can be seen via the following link:

[LINK]

13 Dec 2019

Submitted filename: Drought_IPV_Response_vf.pdf

Click here for additional data file.

29 Jan 2020

Dear Dr. Epstein,

Thank you very much for re-submitting your manuscript "Drought and intimate partner violence: a population-based study from 19 countries in sub-Saharan Africa" (PMEDICINE-D-19-03834R1) for consideration at PLOS Medicine.

I have discussed the paper with editorial colleagues and it was also seen again by two reviewers. I am pleased to tell you that, provided the remaining editorial and production issues are dealt with, we expect to be able to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

Our publications team (plosmedicine@plos.org) will be in touch shortly about the production requirements for your paper, and the link and deadline for resubmission. DO NOT RESUBMIT BEFORE YOU'VE RECEIVED THE PRODUCTION REQUIREMENTS.

***Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.***

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

Please also check the guidelines for revised papers at http://journals.plos.org/plosmedicine/s/revising-your-manuscript for any that apply to your paper. If you haven't already, we ask that you provide a short, non-technical Author Summary of your research to make findings accessible to a wide audience that includes both scientists and non-scientists. The Author Summary should immediately follow the Abstract in your revised manuscript. This text is subject to editorial change and should be distinct from the scientific abstract.

We hope to receive your revised manuscript within one week. Please email us (plosmedicine@plos.org) if you have any questions or concerns.

We ask every co-author listed on the manuscript to fill in a contributing author statement. If any of the co-authors have not filled in the statement, we will remind them to do so when the paper is revised. If all statements are not completed in a timely fashion this could hold up the re-review process. Should there be a problem getting one of your co-authors to fill in a statement we will be in contact. YOU MUST NOT ADD OR REMOVE AUTHORS UNLESS YOU HAVE ALERTED THE EDITOR HANDLING THE MANUSCRIPT TO THE CHANGE AND THEY SPECIFICALLY HAVE AGREED TO IT.

Please ensure that the paper adheres to the PLOS Data Availability Policy (see http://journals.plos.org/plosmedicine/s/data-availability), which requires that all data underlying the study's findings be provided in a repository or as Supporting Information. For data residing with a third party, authors are required to provide instructions with contact information for obtaining the data. PLOS journals do not allow statements supported by "data not shown" or "unpublished results." For such statements, authors must provide supporting data or cite public sources that include it.

Please let me know if you have any questions. Otherwise, we look forward to receiving the revised manuscript shortly.

Sincerely,

Richard Turner, PhD

Senior Editor, PLOS Medicine

rturner@plos.org

------------------------------------------------------------

Requests from Editors:

Please add to your conflict of interest statement that SDW is a member of PLOS Medicine's editorial board.

We ask you to restructure the title to better match journal style, and suggest "Drought and intimate partner violence in 19 countries in sub-Saharan Africa during 2011-2018: a population-based study".

Can you quote a mean age for study participants around line 40?

At line 65, we suggest amending the text to "... intimate partner violence towards women." or similar. We suggest making similar amendments elsewhere in your ms, e.g. at line 80 and in the title.

To the sentence at the end of the "methods and findings" subsection of your abstract summarizing study limitations, we ask you to add a few words to mention 1-2 further limitations, such as the possibility of unmeasured confounding affecting the results.

Around line 162 of your main text, please state explicitly that your study did not have a written prespecified analysis plan or protocol.

Around line 393, we suggest mentioning possible umeasured confounding in the list of potential study limitations.

Please add an author or group name to reference 8.

Please add additional access information to references 1 and 37 as needed.

Noting references 29 and 30, for example, please ensure that journal names are abbreviated as appropriate in your reference list.

Comments from Reviewers:

*** Reviewer #1:

The revised manuscript appears somewhat responsive to the reviews. The authors appear to have misunderstood recommendation 2 provided by Reviewer 1. Given that there are four different indicators of IPV, the question is whether greater exposure to drought results in more than one indicator (e.g., control plus physical violence plus emotional violence). This was not addressed by the authors. Second, given the inability to assess duration of exposure to drought with the data available, the authors should note this as a limitation to the study because it weakens the finding of an association between drought and IPV.

*** Reviewer #2:

The authors have responded to most of the queries comprehensively. However, there is one issue that needs further consideration - the between-country heterogeneity has not been sufficiently addressed in the revision in my view. There is no mention of this major limitation in the discussion. Further, the large heterogeneity would argue against having a pooled estimate in Fig 3 - and ranges can be reported instead. The authors have presented p values for the joint interaction term to estimate the degree of heterogeneity - but it is unusual and I would have expected to see I squared (which are easier to interpret and more widely used). They have argued that they have used a random effects model to account for this - but this is not considered appropriate for observational data if the heterogeneity is substantial.

***

Any attachments provided with reviews can be seen via the following link:

[LINK]

13 Feb 2020

Submitted filename: Drought_IPV_ResponseLetter_2.docx

Click here for additional data file.

21 Feb 2020

Dear Ms. Epstein,

On behalf of my colleagues and the academic editor, Dr. Lawrence Palinkas, I am delighted to inform you that your manuscript entitled "Drought and intimate partner violence towards women in 19 countries in sub-Saharan Africa during 2011-2018: a population-based study" (PMEDICINE-D-19-03834R2) has been accepted for publication in PLOS Medicine.

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Thank you again for submitting the manuscript to PLOS Medicine. We look forward to publishing it.

Best wishes,

Richard Turner, PhD

Senior Editor

PLOS Medicine

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