The findings of this study suggest possible association between atmospheric heat exposure and adverse pregnancy outcomes: miscarriage or stillbirth that could be further explored. The likelihood of experiencing a miscarriage or stillbirth increased twofolds with each additional pregnancy, although the effect was not statistically significant after adjustment for possible confounders. The findings are supported by findings from previous studies elsewhere (Strand et al. 2012, 2011).
Our study shows that it is possible to make this type of analyses using available data. However, potential limitations have to be considered and factored in when interpreting the findings, and when designing future studies to further explore the health effects of high ambient heat. One important limitation in this study was the difficulty in quantifying actual heat exposure and accurately linking that to pregnancy outcomes in the available datasets. Even though the maternal health survey provides a very good data on maternal health and pregnancy outcomes, geographical data (GPS data) was not collected as part of the survey. The lack of specific geographical data presented a challenge for linking the maternal health data to a specific geographical location. Thus, the mean WBGT we used were regional averages based on the women’s region of residence. We limited the year pregnancy ended to the last 3 years before the survey year on assumption that a shorter period will limit the effect of internal mobility on our results. However, although there is a limited likelihood, there still could be some women who might have changed region of residence at the time of the survey and this could have biased our findings to a smaller extent.
Although we suspect that most malformed fetuses would end up in miscarriage or stillbirth, it is not all miscarriages or stillbirths that are due to malformations. The reverse is also true that it is not all malformations that end up in miscarriage or stillbirth (Edwards et al.; Moretti et al. 2005). Thus, lack of comprehensive data on pregnancy outcomes, including fetal malformations, limited the analysis regarding adverse pregnancy outcomes in this study. Pregnancies that ended in induced-abortions were excluded, since they could not be directly linked to adverse pregnancy outcomes. However, there could be a subsample of women who might have undergone elective termination of the pregnancy upon detection of fetal malformation during pregnancy (Cragan and Khoury 2000).
The pattern for the crude odds ratios observed for rural/urban residence, education, antenatal care attendance, and miscarriage or stillbirth (Table 2) is suggestive that (1) selection bias due to high maternal mortality among women of low socio-economic status is highly probable, (2) these variables could be a proxy of exposure to high ambient heat, and (3) there could be high potential for differential diagnosis favoring high socio-economic status women. Therefore, to avoid the potential biases and over-adjustment in our models, rural-urban residence status, education, and number of antenatal care (ANC) visits were not included in the adjusted models. Detailed explanations in relation to the above are discussed as follows.
The finding from this study that women resident in rural areas have reduced likelihood of adverse pregnancy outcomes related to miscarriage or still birth could be due to the high maternal mortality in the rural areas of Ghana (Asamoah et al. 2011), such that women with adverse pregnancy outcomes in rural areas hardly survive compared to those from urban settings. Since the women’s questionnaire used in the Ghana Maternal Health Survey 2007 was administered to surviving women, there is a possibility of selection bias associated with maternal deaths from complications due to fetal abnormalities. It could also be that most of the people interviewed in the urban areas are the less privileged urban dwellers with worse situations. Another alternative explanation could also be that most of these high-risk pregnancies or births are better captured by healthcare facilities in urban settings that have access to proper prenatal diagnosis techniques.
The number of antenatal visits was not found to be significantly associated with pregnancy outcome contrary to what we expected. The number of antenatal visits ranged from 1 to 44 in the study sample. Thus, there are some women in the category “4+ visits” who visited ANC at unusually high rates (up to 44 times), which could be due to complications. Therefore, there could be some misclassification emanating from classifying ANC visits simply into three categories as: one , two to three, and four or more. We tried different classification options, but that did not impact on the observed results.
Women who experience miscarriage or stillbirths may be more likely to get pregnant again as a way of compensating for the loss. Thus, the association found between number of pregnancies and adverse pregnancy outcomes could be as a result of “reverse causation.”
Another limitation worth considering is that the sample selection in this study is very restrictive as it only includes last pregnancies/births in the last 3 years prior to the survey (2004–2007). This is also apparent in the final study sample, which was a very young population (average 22 years, median 22 years) compared to the average age of 29 years for respondents to the entire women’s questionnaire (Ghana Statistical Service (GSS) Ghana Health Service (GHS), and Macro International 2009). We also observed from the data that many pregnancies happened at a relatively low age. This could be a marker of socio-economic status and possibly linked to the heat exposure measure. An example is being forced to work outdoors in high ambient heat to assure food security. Thus, there could be a potential risk of over-adjustment by adjusting for both age a pregnancy and number of pregnancies.
Lastly, on the suitability of making this type of analyses using available dataset, we observed that this study lacked data on some factors that are known from previous studies to impact on the susceptibility of an individual to outdoor heat exposure such as time spent inside and outside at the home, work, and recreational environments that influence daily physical activity level, and adaptation behaviors such as air conditioner use, hydration, and removal from the hot environment (Anderson and Bell 2009; Medina-Ramón and Schwartz 2007; O’Neill et al. 2005; Van Zutphen et al. 2012).
Figures 2 and 3 show the very narrow range of monthly and yearly heat levels in Ghana. Thus, the lack of statistically significant results may be due to the very similar heat exposure situations for all women. Therefore, additional analysis using data from a different country with wide ambient heat variations (e.g., very hot summers and cool winters) will be essential for further studies on this topic.
The use of monthly average WBGT makes the range of values very small, which may explain the lack of any significant effect. It may well be that individual superhot days during key periods of pregnancy is what may cause heat effects on the fetus. This is supported by evidence from a recent study in northeast Ghana, which indicated that the WBGT in the working environment of farmers could peak at 33.0 to 38.1 °C during the middle of the day and dropped to 14.0–23.7 °C in the early mornings during the same season (Frimpong et al. 2017). Generally, the yearly maximum WBGT (WBGT max) values had a very narrow variation (ranged from 26.1 to 27.5) compared to the yearly average (WBGT mean) (ranged from 24.0 to 26.1 °C) over the study period (2004–2007), making the WBGT mean a preferred index for this particular study.
We narrowed down the exposure window in the analyses by time and place, both of which are relevant for better estimation of exposure to high ambient heat (Basu 2009). However, we found a stronger effect size when we focused the exposure lens by using only the four selected regions, but rather negligible effect when we focused on both narrow time window (exposure at second month of pregnancy) and place (Table 4). This could be as a result of the difficulties in accurately linking the heat exposure values to the specific geographic location of the woman at the second month of pregnancy. Short period relocations during early or late pregnancies are possible. The selective analyses of the four administrative regions, using two regions in northern Ghana, which are further apart from the two selected southern regions could have partly reduced the bias in misclassifying heat exposure, since we expect that mass mobility between the extreme north and the extreme south regions is less likely in a short time period. Future analysis of this sort will benefit from inclusion of specific geographical data into surveys regarding maternal health and pregnancy outcomes that could be linked to remote sensing data.
Our intention with study was to empirically evaluate an attempt to use existing epidemiological information from a national survey in a low-income setting, combined with existing information from routine weather observation, which has been made available through the HOTHAPS initiative. If this is a feasible way forward, many similar studies could be made in similar countries/geographical areas, since similar data already exists, e.g., through the existence of data generated by more than a hundred Demographic Health and Surveillance Sites (DHSS), almost exclusively in low-income settings around the world. Even if our approach could be deemed as insufficient in comparison with well-designed study utilizing the specific state-of-the-art measurements, we think that it can generate a better founded discussion regarding which data would be needed, and perhaps how the analytical models could be developed, for making cost-efficient use of already existing information, i.e., we think that our study could contribute to further steps forward regarding research on the effect of ambient high temperatures on pregnancy outcome and on health outcomes in general. This is an area where more epidemiological studies are warranted, in order to estimate important aspects of the impact of global climate change on health.