Differentials in prevalence and correlates of metabolic risk factors of non-communicable diseases among women in sub-Saharan Africa: Evidence from 33 countries

Background: Even with the widespread recognition of non- communicable diseases (NCDs) in sub-Saharan Africa region, yet, sufficient evidence-based surveillance systems to confirm the prevalence and correlates of these diseases is lacking. In an attempt to understand the problem of NCDs in resource-constrained settings, this study was conducted to establish the pattern of the risk factors of NCDs in sub-Sahara Africa region. Methods: The current Demographic and Health Survey (DHS) data sets from 33 countries in sub-Sahara Africa region were used in this study. The individual woman component of DHS 2008-2016 was used. The outcome variables include anemia, hypertension and body mass index (underweight, overweight and obesity). BMI was categorized into; underweight (BMI < 18.5 kg/m2), normal (BMI 18.5-24.9 kg/m2), overweight (BMI 25.0-29.9 kg/m2) and obesity (BMI ≥30 kg/m2). Hemoglobin level: anemic < 12.0 g/dL (< 120 g/L) for women. Hypertension was defined as systolic blood pressure (SBP) ≥140 mmHg and/or diastolic blood pressure (DBP) ≥90 mmHg. Binary and multinomial logistic regression models were used to investigate the correlates of the variables. Results: The percentage of hypertension was highest among women in Lesotho with about 17.3% and lowest among women in Burundi (1.0%). Anemia was prevalent among sub-Saharan Africa women; where more than half of the women from several countries were anemic with Gabon (60.6%) reporting the highest prevalence. The percentage of obesity in sub-Saharan Africa showed that Lesotho (19.9%), Gabon (18.9%) and Ghana (15.6%) were the prominent countries with obese women, while Madagascar (1.1%) had the minimum obese women. Body mass index was significantly associated with hypertension and anemia. The behavioural or modifiable factors of hypertension and body mass index were; smoking, fruits, vegetables and alcohol consumption. While the non-modifiable significant factors include; age, residence, religion, education, wealth index, marital status, employment and number of children ever born. However, anemia shared similar factors except that smoking and vegetable consumption were not statistically significant. In addition, involvement in exercise was associated with anemia and hypertension. Conclusion: The problem of NCDs and associated factors remains high among women of reproductive age in sub-Sahara region. The findings of this study suggest that promotion of regular positive health care-seeking behaviour, screening and early treatment are essential to mitigate the burden of NCDs. Furthermore, preventive interventions of NCDs risk factors should be strengthened among key population through behavior change communication with support from government and stakeholders in health care. Data extracted for this study involved women of reproductive age (15–49 years) in nationally representative Demographic and Health Surveys conducted in 33 countries in sub-Sahara Africa region, 2008–2016. The study involved the following countries; Benin, Burkina-Faso, Burundi, Cameroon, Chad, Comoros, Congo, Cote d’Ivoire, Democratic Republic of Congo, Ethiopia, Gabon, Gambia, Ghana, Guinea, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao Tome & Principe, Senegal, Sierra Leone, Tanzania, Togo, Uganda, Zambia and Zimbabwe (See details in Table 1). DHS data is publicly available and can be accessed from MEASURE DHS database at http://dhsprogram.com/data/available-datasets.cfm. DHS are usually implemented by the National Population Commission (NPC) with financial and technical assistance by ICF International provisioned through the USAID-funded MEASURE DHS program. DHS involved multi-stage stratified cluster design based on a list of enumeration areas (EAs), which are systematically selected units from localities and constitute the Local Government Areas (LGAs). Details of the sampling procedure have been reported in previously [23]. Weighted percentage of high blood pressure, anemia and body mass index by countries in sub-Saharan Africa DHS program was established by the United States Agency for International Development (USAID) in 1984. It was designed as a follow-up to the World Fertility Survey and the Contraceptive Prevalence Survey projects. It was first awarded in 1984 to Westinghouse Health Systems (which subsequently evolved into part of OCR Macro). The project has been implemented in overlapping five-year phases; DHS-I ran from 1984 to1990; DHS-II from 1988 to1993; and DHS-III from 1992 to1998. In 1997, DHS was folded into the new multi-project MEASURE program as MEASURE DHS+. Since 1984, more than 130 nationally representative household-based surveys have been completed under the DHS project in about 70 countries. Many of the countries have conducted multiple DHS to establish trend data that enable them to gauge progress in their programs. Countries that participate in the DHS program are primarily countries that receive USAID assistance; however, several non-USAID supported countries have participated with funding from other donors such as UNICEF, UNFPA or the World Bank. DHS are designed to collect data on fertility and reproductive health, child health, family planning and HIV/AIDS. Due to the subject matter of the survey, women of reproductive age (15–49) are the main focus of the survey. Women eligible for an individual interview are identified through the households selected in the sample. Therefore, all DHS surveys utilize a minimum of two questionnaires-a Household Questionnaire and a Women’s Questionnaire. The risk factors of NCDs considered in this study; were anemia, hypertension and BMI (underweight, overweight and obesity). DHS grouped non-pregnant “anemic” women at: Hb level < 12.0 g/dl and non-pregnant “not anemic” women at: Hb level ≥ 12.0 g/dl. To adjust for anemia during pregnancy, women who were pregnant at the time of the surveys were categorized as “anemic” at: Hb level < 11.0 g/dl and “not anemic” at: Hb level ≥ 11.0 g/dl [6, 17]. BMI was calculated as the ratio of weight in kilograms (kg) to the square of height in meters (m2). BMI was categorized into; underweight (BMI < 18.5 kg/m2), normal (BMI 18.5–24.9 kg/m2), overweight (BMI 25.0–29.9 kg/m2) and obesity (BMI ≥30 kg/m2) [6, 9]. Hypertension was defined as systolic blood pressure (SBP) ≥140 mmHg and/or diastolic blood pressure (DBP) ≥90 mmHg [6, 10]. The systolic and diastolic blood pressures were confirmed by repeating the measurements three times and taking the average. Several factors including socio-demographic, economic and other maternal determinants were measured in this study: age (years) of women were categorized to 15–19/20–24/25–29/30–34/35–39/40–44/45–49; place of residence: rural/urban; educational attainment: no formal education/primary/secondary/higher education; religious background: Christianity/Islam/other religion or no religion; marital status: never married/married or living with partner; currently working: yes/no; number of children ever born: nulliparous/1–4/> 4; alcohol consumption: yes/no; smoking: yes/no; fruits consumption: low (< 2 days/week)/moderate (2–3 days/week)/high (≥4 days/week); vegetable consumption: low (< 2 days/week)/moderate (2–3 days/week)/high (≥4 days/week). In addition, the wealth scores were measured using principal components analysis approach based on a list of household assets, which include, number of household members, wall and roof materials, floor types, access to potable water and sanitation, type of cooking fuel, ownership of television, radio, motorcycle, refrigerator amongst others. Based on the weighted wealth scores, households were grouped into wealth quintiles; poorest, poorer, middle, richer and richest. The computation of wealth scores variable was conducted by DHS and has previously been reported [24]. We did the analyses using publicly available data from demographic health surveys. Ethical procedures were the responsibility of the institutions that commissioned, funded, or managed the surveys. All DHS surveys are approved by ICF international as well as an Institutional Review Board (IRB) in respective country to ensure that the protocols are in compliance with the U.S. Department of Health and Human Services regulations for the protection of human subjects. Prevalence of the risk factors of NCDs was reported by percentages. To adjust for data representation, the survey module (svyset) was used for all analyses to account for sample weight. Correlation matrix was used to conduct multicollinearity diagnostics to examine association between explanatory variables using a cut-off minimum of 0.6 known to cause multicollinearity [25]. All explanatory variables were retained for analysis due to lack of collinearity. Furthermore, variables that were statistically significant in the unadjusted model were added in the multivariable regression models to adjust for the effect of confounding. Binary and multinomial logistic regression models were used to investigate the factors associated with anemia, hypertension [14] and body mass index [4]. The level of statistical significance was set at 5%. All data analyses were conducted using Stata 13.0 (Statacorp, College Station, Texas, United States of America).