Fig 1.
Relative geographical location of the study areas.
Different colors refer to different zones. The base map depicted in this image is taken and modified from Schendel, 2009 [26].
Table 1.
General features of the studied population.
Table 2.
Prevalence of different types of marriages.
Fig 2.
Background sociodemographic status of CM and non-CM participants.
a) Education levels of CM and non-CM individuals. For both males and females, we have seen higher participation in post-secondary and university level education by the non-CM individuals. b) Age distribution at marriage. No notable difference between CM and non-CM individuals were seen. c) The number of times individuals got married. The occurrence of more than once marriage was more prevalent in CM males. d) Type of marriage practiced. We observed a higher occurrence of polygynous marriage in the CM group. e) Women's place of birth and residence. CM females more tend to live in the same locale as the locale they were born. f) Type of families. More non-CM couples preferred to live in nuclear families. g) Working status. The number of females working for cash income was significantly different among CM and non-CM groups. h) Occupational distribution of CM and non-CM couples. For both male and female, non-CM individuals were more involved with professional, administrative, and clerical occupations. i) Wealth index based on the per head yearly income of families. 41.61% (40.42% in CM and 42.81% in non-CM) of all families represented the middle-income category. There was no significant difference between the wealth index of CM and non-CM families. * p < 0.05; † p < 0.01.
Fig 3.
Influence of CM, sex of offspring, age of mother, and sociodemographic factors on gross fertility.
B1, B2, B3, and B4 denote Northern Bengal, Eastern Bengal, Central Bengal and Southern Bengal geographical regions. * Significantly different from non-CM at p < 0.05, using a two-tailed students t-test. † Significantly different from non-CM at p < 0.01, using a two-tailed students t-test.
Fig 4.
Impacts of CM and sociodemographic factors on U5 child mortality.
CM families exhibit a higher rate of U5 mortality as compared to their non-CM counterparts. B1, B2, B3, and B4 denote Northern Bengal, Eastern Bengal, Central Bengal, and Southern Bengal geographical regions. * Analysis of variance (ANOVA) revealed a significant difference between CM and non-CM at p < 0.05; † ANOVA revealed a significant difference between CM and non-CM at p < 0.01.
Fig 5.
Impacts of CM on the Secondary Sex Ratio (SSR).
a) A significantly increased SSR (number of males/100 females at birth) among CM families was seen, as compared to the non-CM group for residence, wealth index, and geographical origins. B1, B2, B3, and B4 denote Northern Bengal, Eastern Bengal, Central Bengal, and Southern Bengal geographical regions. b) To a certain level (F = 0.0625), SSR rose with an increase in the coefficient of inbreeding. Further increase in the inbreeding coefficient caused a decline in SSR value. * Significantly different from non-CM at p < 0.05; † Significantly different from non-CM at p < 0.01.
Fig 6.
Differences in selection intensity between CM and non-CM families.
I value was higher in the CM groups as compared to the non-CM groups, especially in the males. B1, B2, B3, and B4 denote Northern Bengal, Eastern Bengal, Central Bengal, and Southern Bengal geographical regions.
Table 3.
Logistic regression analysis contrasting miscarriage/abortion and U5 mortality rates with different categories of CM.
The potential risk for miscarriage/abortion and U5 mortality rate rises with the increasing degree of consanguinity.
Fig 7.
U5 mortality with increasing degrees of inbreeding.
The (a) U5 mortality rate; (b) Mean child mortality per mother with the coefficient of inbreeding. Both (a) and (b) shows inflations in the U5 mortality rate and the mean number of child deaths per mother with increasing levels of homozygosity. * Analysis of variance (ANOVA) revealed a significant difference between CM and non-CM at p < 0.05; † ANOVA revealed a significant difference between CM and non-CM at p < 0.01.
Table 4.
Lethal equivalents per gametes and estimates of genetic load due to consanguinity.
Table 5.
Parental consanguinity and genetic diseases in children from all participants.
Offspring of CM couples had significantly higher proportions of genetic diseases as compared to their non-CM counterparts.
Table 6.
Pattern of congenital anomalies associated with parental consanguinity.
Fig 8.
Comparison of public health indices between CM and non-CM families.
At a 95% confidence level, no significant difference was observed between CM and non-CM groups.
Fig 9.
Level of knowledge and attitude towards consanguineous marriage among the CM couples.
Almost half of the respondents had no idea about the detrimental effects of CM. 26% of the couples who knew about the impact of consanguinity before or learned from our team during the interviews were still indifferent.