Analysis of Time-Series Variation Patterns of Total Fertility Rate for the Last 20 Years (2000-2020) in 335 Secondary Medical Areas in Japan and its Association with Social Status of Women

Abstract

Japan’s Total Fertility Rate (TFR) is below the population replacement level, and the government is calling on local governments to develop policies to improve the TFR. However, a comparison of TFR values by prefecture shows that the highest value in 2022 is 1.70 in Okinawa Prefecture, while the lowest is 1.04 in Tokyo, indicating notable regional differences.

This study analyzes the relationship between time-series changes in TFR and geographical and socioeconomic background factors for all municipalities in Japan. In particular, we will examine the relationship between TFR and gender indicators in order to clarify the relationship between women’s social advancement and TFR.

In order to utilize demographic data of small municipalities as raw data, we organized information on municipal mergers over the last 20 years (2000-2020) and used a method to aggregate data by secondary medical area. The time-series variation of TFR in each secondary medical area was converted into a comprehensive index by factor analysis, and the two groups were compared by Mann-Whitney U test (MWU-test), dividing them by high and low factor scores. In addition, the geographic distribution of TFR-trend-factors was evaluated by choropleth maps.

Eleven factors were extracted, and two of them, TFR-trend-factor 1 (maintenance of high TFR) and TFR-trend-factor 3 (linear upward trend of TFR), showed positive trends for TFR. MWU-test results showed that both TFR-trend-factor 1 and 3 were significantly associated with gender indicators (economy, education, health, and political participation). This suggests that the higher social status of women in society may increase the TFR.

On the other hand, the strength and direction of the impact on TFR tended to vary depending on the TFR-trend-factor and the social advancement indicator items of each region. Therefore, it is also important to analyze the relationship between the sub-indexes and individual data and TFR.