Trends and Contributing Factors to Contraceptive Use in Kenya: A Large Population-Based Survey 1989 to 2014

Abstract

Kenya is among the leading nations in family planning in Africa, having the first official nationwide family planning program in sub-Saharan Africa. However, Kenya is still one of the most highly populated countries in Africa with a population of more than 52 million. The objective of this study was to assess the trends and contributing factors of contraceptive use. We conducted a multi-wave cross-sectional study using both the demographic health survey (DHS) and family planning effort index (FPE) datasets, analyzing five-year waves from 1989 to 2014. This study indicates that contraceptive use increased from 24.0% to 42.6%, with a change % of 77.5%. Despite changes in women’s characteristics, these characteristics posed little on the time trend of contraceptive use in Kenya. In addition, the policy component of FPE scores had a positive association with contraceptive use with negligible change after adjusting for social and demographic factors 1.055 (1.046–1.065). There was a fluctuating trend of the additional FPE components throughout the years. Women with lower education, those married to husbands with lower education, unmarried, and rural women remain behind in family planning service utilization. Targeted programs are still needed for these special groups. Policy adherence is vital for continued progress.

Factors Associated With the Utilisation and Unmet Need for Modern Contraceptives Among Urban Women in Kenya: A Cross-Sectional Study

“…This study found that slightly more than half of urban women of reproductive age used modern contraceptives while about 17% of them had unmet needs for FP. Our results show that there was an increase in the prevalence of modern contraceptive use and a decrease in unmet need for FP in urban areas between 2014 and 2018, a pattern observed in other studies in Kenya ( 11 , 12 ). These improved FP indicators could be attributed to the overall increase in investment in government- and partner-supported programs in urban areas ( 22 ) and the government's commitment to improving access to FP services in order to increase modern CPR to 66% in 2030 ( 8 ).…”

“…For example, in 2014, about 40% of urban women were not using modern contraceptives and a further 13% had an unmet need for FP ( 7 , 10 ). Recent studies have also found a persistent low use of modern contraceptive and a high unmet need in urban areas ( 11 , 12 ). This is despite, a general expectation that access to FP services is better in urban than rural areas hence a need to explore this phenomenon.…”

“…Therefore, urbanisation, urban population dynamics and the rise of urban informal settlements cannot be ignored in the bid to achieve health goals including FP. Consistent FP programmes to build on gains of previous urban FP programs such as Tupange ( 22 ) are needed to address the increased demand and need for FP in urban areas but to also address other confounders of FP use including poverty, low education level, exposure to FP messages in the media and FP commodities' stockouts ( 11 , 12 ). Also, while previous studies have consistently shown the prevalence of unmet need for FP to be lower in urban areas than in rural areas ( 11 , 12 ), a possible rich-poor gap in unmet need for FP among urban women may be masked.…”

“…Consistent FP programmes to build on gains of previous urban FP programs such as Tupange ( 22 ) are needed to address the increased demand and need for FP in urban areas but to also address other confounders of FP use including poverty, low education level, exposure to FP messages in the media and FP commodities' stockouts ( 11 , 12 ). Also, while previous studies have consistently shown the prevalence of unmet need for FP to be lower in urban areas than in rural areas ( 11 , 12 ), a possible rich-poor gap in unmet need for FP among urban women may be masked. Hence, to better inform urban FP programming and policies in Kenya, the study aimed to determine factors associated with modern contraceptive use and unmet needs for FP among urban women in 11 counties in Kenya.…”

Socioeconomic status effects on health vary between rural and urban Turkana

“…Instead, we find that the presence and direction of SES effects are modified as a function of lifestyle. We also found similar opposing effects when examining a fitness-related trait: high SES predicts more offspring in the pastoralist setting, partially driven by wealth effects on polygyny, but fewer offspring in the urban setting, where polygyny is uncommon and greater wealth is likely associated with later marriage and family planning [71].…”